experimental studies of red blood cells ......composition has, not only on rbc metabolism and...

EXPERIMENTAL STUDIES OF RED BLOOD

CELLS DURING STORAGE

Marie Anne Balanant

MEngBiotech

Submitted in fulfilment of the requirements for the degree of

Doctor of Philosophy

School of Chemistry, Physics and Mechanical Engineering

Science and Engineering Faculty

Queensland University of Technology

in collaboration with

The Australian Red Cross Blood Service, Brisbane, Queensland, Australia

2018

Experimental studies of red blood cells during storage i

Keywords

Atomic Force Microscopy

Confocal imaging

Cytoskeleton

Echinocytes

Image analysis

Mechanical testing

Optical tweezers

Red Blood Cell

Scanning Electron Microscopy

Spectrin

Stomatocytes

Storage

ii Experimental studies of red blood cells during storage

Acknowledgements

I would like to thank my supervisory team, Prof YuanTong Gu, Prof Robert

Flower, Dr Emilie Sauret and Dr Suvash Saha, for their advice and support during the

past three years. I would especially like to thank Prof YuanTong Gu for giving me the

opportunity to complete my PhD in his research group. I am deeply grateful to Dr

Emilie Sauret for her moral support during the hardships I faced during my PhD

journey. I would also like to express my profound gratitude to Prof Robert Flower for

being a mentor to me during the past four years I have spent at the Blood Service. I am

especially grateful to Dr Helen Faddy for her guidance and advice during the redaction

of this thesis. I would also like to acknowledge the support I received from the

members of the LAMSES research group, particularly Sarah Barns and Nadeeshani

Maheshika Geekiyanage, who worked with me on this project. I acknowledge QUT

financial support through the QUT Postgraduate Research Award and the QUT Equity

Scholarship, as well as the services of professional editor, Diane Kolomeitz, who

provided copyediting and proofreading services, according to the guidelines laid out

in the university-endorsed national ‘Guidelines for editing research theses’.

Work conducted during this PhD took place across five laboratories; I would like

to acknowledge QUT biomedical laboratory, the Blood Service research laboratory,

the Institute of Health and Biomedical Innovation (IHBI) imaging facilities, the

Central Analytical Research Facility (CARF), and their staff, for helping me turn my

research ideas into successful experiments. Some of the data reported in this thesis

were obtained at CARF with the help of Rachel Hancock and Natalia Danilova. CARF

is operated by the Institute for Future Environments and access to CARF is supported

by generous funding from the Science and Engineering Faculty (QUT). I would

especially like to thank Dr Christina Theodoropoulos from IHBI imaging facilities, for

her help in establishing my confocal imaging protocols. A special thank you goes to

UQ Optical Micro-manipulation Group, and to Prof Halina Rubinsztein-Dunlop, Dr

Alexander Stilgoe, and Anatolii Kashchuk, for opening their laboratory to me and for

their generosity in time, advice and ideas during our collaboration.

Lastly, I would like to say a big thank you to the members of the Australian Red

Cross Blood Service Research Laboratory for welcoming me in their team, right from

my first day in Australia.

Experimental studies of red blood cells during storage iii

Australian governments fund the Australian Red Cross Blood Service to provide

blood, blood products and services to the Australian community.

iv Experimental studies of red blood cells during storage

Abstract

Red blood cell (RBC) transfusions are life-saving procedures, restoring the

oxygen perfusion to organs and tissues after critical blood loss or anaemia. Between

donation in one of the Australian Red Cross Blood Service (ARCBS) collection

centres, and transfusion in a hospital, RBCs are stored in an artificial storage solution

at 4ºC, for up to 42 days. During that time, damage to the RBC structural components

accumulates. This damage is due to depletion of the cells’ energy and other resources,

and to the accumulation of metabolic wastes in the bag. The most visible sign of aging

in storage is the shape transformation of the RBCs: they lose their smooth and

biconcave shape, and acquire spicules over their surface. RBCs then become rounder

and shed pieces of their membrane through microvesiculation. The shape

transformation happening to RBCs in storage decreases their surface area to volume

ratio and is at the origin of a lower RBC deformability. It is thought transfusions of

products containing a high number of RBC with altered morphologies have a lower

efficiency, as the cells mechanical properties are degraded. They cannot flow through

the narrowest sections of the capillary network and are quickly removed from

circulation. Transfusions of products with a high number of RBCs presenting an

altered shape have also been associated with higher risks of adverse transfusion-related

events in patients.

Many studies report the different RBC morphologies observed during storage,

but their physical properties have not been extensively studied, and measurements,

such as their volume or surface area, are missing. Several hypotheses have attempted

to explain the mechanisms behind the shape transformation of RBCs during aging;

however, no consensus has been reached. Most of these hypotheses do not explain how

shape transformation impacts the mechanical properties of the RBCs. The relationship

between storage duration, shape transformation and RBC mechanical properties

remains unexplained.

During this PhD, I first monitored RBC morphology during storage and when

resuspended in a physiological environment. I demonstrated that the buffer

composition has the largest influence on RBC shape, even after long storage periods.

I also showed that the reversibility of RBC shape was maintained for a majority of

cells during storage. However, a small percentage of RBCs lose the ability to reverse

Experimental studies of red blood cells during storage v

their shape after a few weeks in storage, and have acquired irreversible damage. I

proposed a new protocol to evaluate RBCs’ physical properties, using confocal

imaging and image analysis methods. Using this protocol, I have measured the surface

area and volume of RBCs at different stages of their shape transformation.

I then investigated the link between RBC shape and their mechanical properties.

I developed an improved atomic force microscopy (AFM) indentation protocol, using

a spherical indenter. Data from this study was used to calibrate a RBC numerical model

developed by my collaborator, Sarah Barns; combined results from both experimental

and modelling work showed that the lipid bilayer was primarily responsible for

resisting the bending of the membrane. Finally, I studied RBC global deformability

during storage using optical tweezers stretching. I demonstrated that mechanical

properties of RBCs that maintained their biconcave morphology during storage, were

not different from freshly donated RBCs. RBC shape transformation and reduction in

deformability are not dissociable during aging in storage, and neither did mechanical

properties evolve with storage duration.

Experimental data produced during this project have been used to calibrate and

validate an RBC numerical model. This model is designed to identify the contribution

of different membrane components to RBC mechanical properties. It will also have

predictive value regarding the effect damage that these components would have on

mechanical properties. This numerical model has application in designing improved

storage conditions for RBCs.

This PhD highlighted the importance of preserving shape reversibility during

storage, as shape is linked to the RBC mechanical properties. The results obtained

increase the available knowledge on the process of RBC aging in storage. This project

is part of a continuous effort to improve industrial practices, especially relevant now,

regarding the uncertainties raised by clinical studies on the adverse effects that RBCs,

after being stored for long periods of time, produce in patients. The development of

new storage protocols should be based on understanding the effect the storage solution

composition has, not only on RBC metabolism and antigenic properties, but also on

integrity of their structural components.

vi Experimental studies of red blood cells during storage

Statement of Original Authorship

The work contained in this thesis has not been previously submitted to meet

requirements for an award at this or any other higher education institution. To the best

of my knowledge and belief, the thesis contains no material previously published or

written by another person except where due reference is made.

Signature: QUT Verified Signature

Date: _________________________

Experimental studies of red blood cells during storage vii

List of Publications

Journal papers

Barns S^, Balanant MA^, Sauret E, Flower R, Saha SC, Gu YT. (2017).

Investigation of red blood cell mechanical properties using AFM indentation and

coarse-grained particle method. Biomedical Engineering OnLine, 16(140).

Balanant MA, Flower RL, Sauret E, Gu YT. (2018). Evidence of failure of red

blood cell recovery associated with storage: quantification of accumulation of sphero-

echinocytes is method dependent. (submitted)

Balanant MA, et al. Measurement of Deformability Properties of Red Blood

Cells through Stretching using Optical Tweezers. (in preparation)

Balanant MA, et al. Accurate measurements of Red Blood cell Volume during

echinocytosis using confocal imaging and surface reconstruction. (in preparation)

^ Contributed equally

Conference abstracts

Balanant MA, Kashchuk AV, Stilgoe AB, Flower RL, Rubinsztein-Dunlop H,

Sauret E, Saha SC, & Gu YT. (2017). Measurement of Deformability and Elasticity

Properties of Red Blood Cells through Stretching using Optical Tweezers. Presented

at the 27th regional congress of the International Society of Blood Transfusion,

Copenhagen, Denmark. Harold Gunson Fellowship and Young Investigator Award.

Flower RL, Balanant MA, Sauret E, Saha SC, Gu YT. (2017). Storage-related

Morphological Changes in Red Blood Cells. Presented at the 28th regional congress of

the International Society of Blood Transfusion, Guangzhou, China.

Balanant MA, Barns S, Sauret E, Gu YT. (2016). Investigation of Red Blood

Cell Membrane Elasticity using AFM Indentation and the Coarse-Grained Particle

Method. Presented at the 10th Australasian Biomechanics Conference, Melbourne,

Australia.

viii Experimental studies of red blood cells during storage

Poster presentations

Balanant MA*, Kashchuk A, Stilgoe AB, Flower RL, Rubinsztein-Dunlop H,

Sauret E, Saha SC, Gu YT. (2017). Experimental Study of the Aging Effects on the

Red Blood Cell. Presented at 2017 Australian Society for Medical Research

Postgraduate Student Conference, Brisbane, Australia.

Balanant MA*, Dean MM, Flower RL, Sauret ES, Saha SC, Gu YT. (2016).

Storage-Related Morphological Changes in Red Blood Cells: Telling the Whole Story.

Poster presented at the 2016 Annual Scientific Meetings of the HAA, Melbourne,

Australia.

* Presenting author

Experimental studies of red blood cells during storage ix

Table of Contents

Keywords .................................................................................................................................. i

Acknowledgements .................................................................................................................. ii

Abstract ................................................................................................................................. ivv

Statement of Original Authorship .......................................................................................... vii

List of Publications .............................................................................................................. viiii

Table of Contents .................................................................................................................. ixx

List of Figures ........................................................................................................................ xii

List of Tables ...................................................................................................................... xivv

List of Abbreviations ..............................................................................................................xv

Chapter 1: Introduction ...................................................................................... 1

1.1 Background .....................................................................................................................1

1.2 Research objectives ........................................................................................................3

1.3 Significance and innovation ...........................................................................................3

1.4 Thesis Outline .................................................................................................................5

Chapter 2: Literature Review ............................................................................. 7

2.1 RBC function and structure ............................................................................................7

2.2 RBCs and transfusion ...................................................................................................19

2.3 Assessment of RBC physical and mechanical properties .............................................25

2.4 Summary and Implications ...........................................................................................29

Chapter 3: Assessment of RBC shapes during storage .................................. 31

3.1 Introduction ..................................................................................................................31

3.2 Aims..............................................................................................................................33

3.3 Materials and Methods .................................................................................................34

3.4 Results ..........................................................................................................................38

3.5 Discussion .....................................................................................................................45

3.6 Conclusion ....................................................................................................................49

Chapter 4: Physical characterisation of the echinocytic transformation ..... 51

4.1 Introduction ..................................................................................................................51

4.2 Aims..............................................................................................................................53

4.3 Materials and methods ..................................................................................................53

4.4 Results ..........................................................................................................................59

4.5 Discussion .....................................................................................................................64

4.6 Conclusion ....................................................................................................................65

x Experimental studies of red blood cells during storage

Chapter 5: Study of local membrane properties using AFM ......................... 67

5.1 Introduction .................................................................................................................. 67

5.2 Aims ............................................................................................................................. 70

5.3 Materials and Methods ................................................................................................. 71

5.4 Results .......................................................................................................................... 74

5.5 Discussion .................................................................................................................... 79

5.6 Conclusion ................................................................................................................... 81

Chapter 6: Study of global cell deformability using optical tweezers ........... 83

6.1 Introduction .................................................................................................................. 83

6.2 Aims ............................................................................................................................. 85

6.3 Materials and methods ................................................................................................. 85

6.4 Results .......................................................................................................................... 89

6.5 Discussion .................................................................................................................... 95

6.6 Conclusion ................................................................................................................... 98

Chapter 7: Conclusions...................................................................................... 99

7.1 Main research findings ................................................................................................. 99

7.2 Limitations ................................................................................................................. 102

7.3 Future work ................................................................................................................ 104

7.4 Summary of research project ..................................................................................... 104

References ............................................................................................................... 107

Appendices .............................................................................................................. 124

Appendix A - Ethics approval - The Blood Service Human Research Ethics Committee ... 124

Appendix B - Ethics approval - QUT University Human Research Ethics Committee ....... 126

Experimental studies of red blood cells during storage xi

List of Figures

Figure 1.1: Research framework ............................................................................................ 6

Figure 2.1: Image of RBCs taken with a Scanning Electron Microscope at x5000

magnification ................................................................................................... 8

Figure 2.2: A red cell traversing from the splenic cord to splenic sinus ................................ 9

Figure 2.3: Proposed distribution of phospholipids between inner and outer layer of

the human erythrocyte membrane. ................................................................ 10

Figure 2.4: Schematic representation of two types of multiprotein complexes in the

red cell membrane. ........................................................................................ 11

Figure 2.5: Schematic illustrating a) a folded repeated spectrin structure comprised

mostly of the 106-residue repeats, and b) a peptide segment in which

one repeat has unfolded ................................................................................. 12

Figure 2.6: Model for transition between the a) intact and b) expanded forms of the

erythrocyte membrane ................................................................................... 12

Figure 2.7: Hypothetical interactions between detergent resistant molecules of the

RBC membrane and the cytoskeleton. .......................................................... 13

Figure 2.8: Schematic diagram showing the discocyte – echinocyte – stomatocyte

transformations .............................................................................................. 14

Figure 2.9: Illustration of the echinocytic and stomatocytic transformations.

Scanning electron microscopy ....................................................................... 15

Figure 2.10: Schematic representation of the proposed binding of amphipathic

compounds that are crenators or cup-formers to the phospholipid

regions of the erythrocyte membrane ............................................................ 17

Figure 2.11: Schematic representation of the mechanism of control of erythrocyte

shape by Band 3 proteins............................................................................... 18

Figure 2.12: Whole blood units are centrifuged (a) then separated into their

different components using automated machines (b) .................................... 20

Figure 2.13: Scanning electron microscope picture of RBCs on the 42nd day of

storage. .......................................................................................................... 23

Figure 3.1: Proportion of echinocytes (a) and stomatocytes (b) observed after 20

minutes incubation at RT, in cold-agglutinin-depleted FFP, SAGM

and ‘artificial plasma’. ................................................................................... 38

Figure 3.2: Evolution of shape repartition of echinocytes, stomatocytes and

discocytes during storage .............................................................................. 39

Figure 3.3: SEM images of representative RBC morphologies (5000x) in PBS (a-

c), in SAGM (d-f) and in Krebs (g-i), and from fresh blood (a, d, g),

day 3 (b, e, h) and day 42 samples (c, f, i)..................................................... 40

Figure 3.4: Percentages of echinocytes with an irreversible morphology in fresh

blood samples, after 3 and 42 days of storage, and when resuspended

in either SAGM, PBS or Krebs ..................................................................... 41

Figure 3.5: Percentage of echinocytes (a-b) and stomatocytes (c-d) observed after

20 minutes (a, c) or 2 hours (b, d) incubation ............................................... 42

Figure 3.6: Evolution of cell apparent diameters during 42 days of storage. ...................... 43

xii Experimental studies of red blood cells during storage

Figure 3.7: MCV measurement during 42 days of storage................................................... 44

Figure 3.8: Percentage of haemolysis over 50 days of storage, means and standard

variation are represented. (* p < 0.05, *** p < 0.001, n=6) ........................... 45

Figure 3.9: Illustration of how buffer composition influences RBCs morphology

range in SAGM (a), ‘artificial plasma’ (b) and cold-agglutinin-

depleted FFP (c). ............................................................................................ 46

Figure 4.1: Extraction of voxel size, using surface reconstruction of calibration

beads. ............................................................................................................. 55

Figure 4.2: Image processing steps, from confocal stack images to membrane

contours ......................................................................................................... 56

Figure 4.3: Comparison of results obtained from 2D and 3D filling functions .................... 57

Figure 4.4: Point cloud representing the surface of a discocyte ........................................... 57

Figure 4.5: Cell surface reconstruction process, from the point cloud to the

triangulated mesh ........................................................................................... 58

Figure 4.6: 3D reconstruction of a discocyte membrane, visualised in Matlab ................... 59

Figure 4.7: Visual representation of surface reconstruction quality of a discocyte

(a) and an echinocyte (b) ............................................................................... 61

Figure 4.8: Surface reconstruction for a discocyte (a, b), an echinocyte I (d, e), an

echinocyte II (g, h) and an echinocyte III (j, k) and the corresponding

initial confocal data used to generate them (c, f, i, l). .................................... 63

Figure 4.9: Numerical model predictions for the 3D morphologies of a discocyte

(a), an echinocyte I (b) and an echinocyte III (c) ........................................... 64

Figure 5.1: Principle of AFM imaging and indentation. ...................................................... 68

Figure 5.2: Schematic for indentation grid pattern over a RBC surface .............................. 72

Figure 5.3: Force deformation curves plotted for 64 indentation points .............................. 73

Figure 5.4: Original AFM scan of a RBC (a) and corresponding effective Young’s

modulus map (b). ........................................................................................... 74

Figure 5.5: (a) Deflection scan of a RBC (16 µm x 16 µm) and (b) height profile

for section marked with red line on deflection scan.. .................................... 75

Figure 5.6: Scans of RBCs from the same blood sample for varying concentrations

of poly-D-lysine and incubation times ........................................................... 76

Figure 5.7: (a) Comparison between experimental data and the modified Hertz

equation for a typical sample where E=9.83 kPa, (b) effective

Young’s modulus for each cell ...................................................................... 77

Figure 5.8: Adhered shape of RBCs predicted by the numerical model (a) and

verified by confocal imaging (b). .................................................................. 78

Figure 5.9: Model indentation representation (a) and associated force deformation

curves (b). ...................................................................................................... 79

Figure 6.1: Optical tweezers experimental set up ................................................................ 86

Figure 6.2: Force associated with the stretching of a single discocyte between two

laser traps ....................................................................................................... 87

Figure 6.3: Force-deformation curves for a series of 20 stretches realised on a

single discocyte. ............................................................................................. 89

Experimental studies of red blood cells during storage xiii

Figure 6.4: Population frequency distribution for both discocytes and echinocytes

in function of the force required to stretch them ........................................... 90

Figure 6.5: Gradient values (N/µm) over 50 days for both discocytes (a) and

echinocytes (b). ............................................................................................. 91

Figure 6.6: Gradient values (N/µm) for discocytes (a, c, e, g) and echinocytes (b, d,

f, h). An increase in average gradient can be seen between the first

(c-d), the second (e-f) and third replicates (g-h) ............................................ 92

Figure 6.7: Force required to stretch discocytes in function of replicate number and

diamide concentration ................................................................................... 94

Figure 6.8: Force required to stretch discocytes in function of replicate number and

ATP depletion treatment ............................................................................... 95

xiv Experimental studies of red blood cells during storage

List of Tables

Table 2.1: Composition of SAGM ....................................................................................... 21

Table 2.2: Summary of surface area and volume measurements on RBCs .......................... 26

Table 3.1: Artificial plasma composition based on human fresh plasma ............................. 35

Table 3.2: Impact of incubation time and temperature on RBC morphology ...................... 42

Table 4.1: Confocal voxel calibration values ....................................................................... 60

Table 4.2: Surface area and volume measurements for four different RBC

morphologies ................................................................................................. 61

Table 5.1: Experimental AFM indentation data summary over the 15 cells included

in this study .................................................................................................... 78

Experimental studies of red blood cells during storage xv

List of Abbreviations

AFM Atomic force microscopy

ANOVA Analysis of variance

ARBCS Australian Red Cross Blood Service

ATP Adenosine triphosphate

BSA Bovine serum albumin

DiI 1,1'-dioctadecyl-3,3,3'3'-tetramethylindocarbocyanine

perchlorate

EDTA Ethylenediaminetetraacetic acid

EMA European Medicine Agency

E-PHA Erythroagglutinating phytohemagglutinin

FDA Food and Drug Administration

FFP Fresh frozen plasma

Hb Haemoglobin

HMDS Hexamethyldisilizane

MCV Mean corpuscular volume

NA Numerical aperture

NBA National Blood Authority

PBS Phosphate-buffered saline

PC Phosphatidylcholine

PE Phosphatidylethanolamine

PS Phosphatidylserine

pRBC Packed red blood cells

RBC Red blood cell

RCT Randomised controlled trial

xvi Experimental studies of red blood cells during storage

ROS Reactive oxygen species

RT Room temperature

SAGM Saline, adenine, glucose, and mannitol solution

SEM Scanning electron microscopy

SM Sphingomyelin

TGA Therapeutic Good Administration

TRALI Transfusion-related acute lung injury

WBC White blood cell

2D Two-dimensional

3D Three-dimensional

Chapter 1:Introduction 1

Chapter 1: Introduction

This PhD project was designed to understand how red blood cell (RBC) aging in

storage results in cellular morphological changes and degraded mechanical properties.

The two main axes of research focused on characterising RBC shapes during storage

and when placed back into a physiological environment, as well as characterising

mechanical properties for cells assuming these shapes. The first section of this chapter

describes the background behind this PhD project (Section 1.1). Then, the main

objectives are presented (Section 1.2), as well as the project significance and

innovations (Section 1.3). Finally, the last section gives the thesis outline and brief

summaries of the content of each chapter (Section 1.4).

1.1 Background

Between 2009 and 2011, 1207 cases of patients suffering serious adverse effects

after being transfused with blood products were reported in Australia [1].

Approximately 68% of these incidents were due to RBC transfusions. Several clinical

studies associate adverse reactions in recipients with the decrease in quality of RBC

units during storage [2-6]. The results of some of these studies find a relationship

between extended storage of RBCs and an increased risk of multiple organ failure [6],

transfusion-related acute lung injury (TRALI) [5] and overall higher mortality [3] for

patients. Following these observations, a growing number of questions regarding the

‘age of blood’ were raised, resulting in the implementation of randomised controlled

trials (RCTs). Three large RCTs observed the effect of RBC storage on mortality [7-

9], in conditions corresponding to Australian protocols. However, these RCTs gave

contradictory results on patient outcomes and do not advise for storage duration to be

changed from 42 days [10]. Another approach to answering the ‘age of blood’ question

is to understand how RBCs age during storage, and how in vitro aging could lead to

adverse transfusion-related reactions in patients.

RBCs are made of a composite membrane surrounding a haemoglobin (Hb) rich

cytoplasm. The membrane mechanical properties are determined by the interactions

between its lipid bilayer and the spectrin-based cytoskeleton tethered underneath [11;

2 Chapter 1:Introduction

12]. During storage, metabolism slows down and damage accumulates in the structural

components of the membrane [13]. Thus, mechanical properties, such as RBC ability

to deform and pass through narrow sections of the capillary network, are affected [14].

Transfusion of RBC units containing a high number of RBC with low deformability is

thought to be associated with reduced transfusion efficiency and higher risks of

adverse events [15; 16].

The mechanisms of RBC aging during storage are not well understood at present

[17]. Studies have identified effects of the storage lesion on membrane components;

however, there is no clear understanding on the link between individual protein

malfunction and the overall shape transformation: shape transformation is thought to

result from the storage lesion [17] or from the natural aging pathway of RBC [18].

Investigation of the relationship between RBC shapes and their mechanical properties

are usually limited to global population studies without separating RBC morphologies

[19]. Results from these studies associate the decreased deformability properties of

RBCs after long periods of storage, either to the reduced surface area to volume ratio

or the altered function of the cytoskeleton [19-21]. However, limited data are available

on the physical characteristics of the different RBC morphologies, to confirm when

volume reduction starts for RBCs in storage. To provide an answer to these questions,

the evolution of RBC morphology and their physical and mechanical properties were

monitored, as they aged in storage during this PhD. This work created new

understanding of the relationship between storage duration, shape transformation and

RBC mechanical properties.

This PhD project was part of a larger research collaboration project between the

Australian Red Cross Blood Service (ARCBS) and QUT. The overall research project

aimed to understand the aging mechanism of RBCs during storage, by establishing a

numerical model of in vivo RBC aging using experimental data. This model will be

useful to predict outcomes of proposed improvements to current storage protocols,

before starting large-scale experimental validations. This PhD project used an

experimental approach to track physical parameters of RBCs during storage. The

membrane mechanical properties, such as its deformability, and RBC morphology

were monitored during in vitro aging. These results provided new understanding of the

evolution of the RBC membrane properties during storage, and helped establish

hypotheses related to the changes affecting its structure. In collaboration with two

other PhD students in the same research group, Sarah Barns and Nadeeshani


Maheshika Geekiyanage, the numerical three-dimensional (3D) model of RBC aging

in storage is being developed. This model uses realistic physical parameter values

obtained during this PhD project. These values were used to calibrate and validate the

model.

1.2 Research objectives

This PhD project aimed to provide quantitative measurements of RBC

membrane mechanical properties during aging in storage. As RBC shape evolves

during storage, the relationship between RBC morphology and deformability was also

investigated. The main aims of this project were:

- To describe the morphological changes happening to RBCs during storage.

- To understand which mechanical parameters are the most representative of

RBC unit quality during storage.

- To identify the role of different membrane components on RBC membrane

deformability.

- To effectively integrate experiments with numerical modelling to explore the

aging mechanism of RBC during storage.

1.3 Significance and innovation

RBC transfusions are mainly used for patients suffering from cancer or blood

diseases (35%) or undergoing surgery (18%) [22]. In Australia, over 750,000 units of

RBC units are used each year [23], and half of them are used for patients over 65 years

of age, and considered medically fragile [1]. Reducing patients’ adverse events was

one of the priorities of the National Blood Authority (NBA) for its strategic plan for

2013-2017, and this priority was renewed in the latest strategic plan for 2018-2021

[24; 25]. The goal of this project was to establish new ways to quantify RBC unit

quality during storage. By understanding how RBCs age in vitro and what parameters

affect their deformability the most, improvements to current storage protocols can be

proposed. These improvements will lead to lower risks of transfusion-related adverse

events in patients.


Between 2011 and 2012, over 27,000 units of RBC were discarded, for a cost of

over 9.5 million Australian dollars [24]. The wastage reduction of expired blood

products is another priority of the Australian NBA. Understanding how RBC units age

during storage will lead to better stock management, and reduced risks of shortage. It

will also result in improved performances and supply chain efficiency.

Through this research project, new knowledge on RBC aging was generated and

increased the bank of information available on the effect of current storage protocols

on RBCs. This knowledge will contribute to helping the ARCBS in making decisions

regarding the continuous improvement of blood manufacturing protocols.

This PhD project developed an innovative approach to understand the

mechanisms of RBC aging in storage. Many studies focus on RBC product

immunogenicity; however, a transdisciplinary approach was chosen during this PhD

and concentrated on the alteration of the RBC function during storage. This is one of

very few studies characterising RBC membrane deformability for single cells, and as

a function of cell morphology [19; 26-30]. This project also questions the relevance of

assessing RBC aging in vitro in buffer with no clinical relevance, such as phosphate

buffered solutions. The main innovations of this project were:

- The assessment of RBC shape changes during storage, and the determination

of the influence of environmental factors.

- The creation of a novel and accurate method to measure RBC surface area

and volume, using confocal imaging and image analysis.

- The establishment of an improved atomic force microscopy (AFM)

indentation protocol, and the determination of the limits of AFM as

mechanical testing method.

- The assessment of RBC membrane deformability for discocytic and

echinocytic shapes during storage, using optical tweezers stretching.

The new experimental protocols developed during this project have the

possibility to be adapted and translated in other research projects. The data produced

by this PhD project contributed to the calibration and validation of two numerical

models, representing the shape transformation and the mechanical behaviour of RBCs.


1.4 Thesis Outline

In the first chapter of this document (current chapter), the project general

background, as well as its significance in the research field and main innovations are

presented. The research framework is presented at the end of this section, in Figure

1.1.

In Chapter 2, a focused review of the literature relative to this PhD project is

presented. The RBC structure and function are initially described. Then, RBC storage

protocol and storage associated effects on RBC product quality are described. Lastly,

different experimental methods used to characterise RBC shape and mechanical

properties are introduced.

In Chapter 3, cell shape in three clinically relevant buffers are characterised as

RBCs’ age, specifically fresh frozen plasma (FFP), SAGM, and a physiological buffer

called ‘artificial plasma’. The objective of this study was to understand how storage

and buffer composition affect the shape transformation process. Results have the

possibility to help develop solutions to prevent the appearance of RBCs with an

irreversible echinocytic morphology during storage.

In Chapter 4, the physical properties of RBC as they transition from discocytes

to echinocytes were measured (volume, surface area). Sequential 3D representations

of the cells as they evolve from discocytes to echinocytes gave more insights on the

successive changes happening to the RBC membrane. The 3D meshes representing the

different morphologies make possible the validation of numerical models using these

different shapes.

In Chapter 5, a mechanical study was undertaken to measure local membrane

elasticity using AFM indentation. This study was conducted in order to identify the

role of different components in membrane deformability. An improved Hertzian

model, and a new protocol for spherical indentation were used. Measured force

deformation data were comparable with the literature, and were used to calibrate and

validate a numerical model.

In Chapter 6, the deformation of both discocytes and echinocytes was recorded

under tensile stretch, as they age in storage, in order to identify differences in

mechanical behaviour between these morphologies. Two in vitro models of RBC aging


were developed to provide potential explanations to structural changes happening to

the membrane during storage.

Finally, Chapter 7 provides a conclusion to this work and summarises the main

findings. The limitations to this project and recommendations for future work are

described here.

Figure 1.1: Research framework

Chapter 2:Literature Review 7

Chapter 2: Literature Review

In this chapter, a critical review of the literature is presented. The following

topics are discussed: the RBC membrane structure and morphology (Section 2.1), then

RBC product preparation for transfusion and the damage that accumulates during

aging in storage (Section 2.2), and finally, the different existing methods available to

characterise the physical and mechanical properties of RBCs (Section 2.3). The final

section of the chapter develops the conceptual framework for the study (Section 2.4).

2.1 RBC function and structure

2.1.1 Human RBC physiology

RBC function

RBCs, or erythrocytes, make up 70% of all cells in the human body and represent

over 90% of cells found in blood circulation [31]. Their characteristic resting shape is

a biconcave disk, with a diameter of 8 µm and a thickness of 2 µm on average (Figure

2.1) [32]. RBCs’ main role is to ensure the distribution of dioxygen to tissues and

removal of metabolic wastes, such as carbon dioxide [33]. The ability of RBCs to

capture and release dioxygen at different locations of the body is linked to their high

content of Hb. Hb makes up 98% of the non-water content of RBCs’ cytoplasm [34].

Hb is a small molecule (64 kDa molecule) with a cooperative affinity for dioxygen

[35]: the protein conformation changes in relation to its degree of saturation in

dioxygen. When the pressure in dioxygen is high, for example in the lungs, the affinity

of Hb for dioxygen increases, the protein ‘stocks up’ on dioxygen molecules. In the

tissues, where the pressure in dioxygen is low, the affinity of Hb for dioxygen is

reduced, the protein releases molecules of dioxygen.

8 Chapter 2:Literature Review

Figure 2.1: Image of RBCs taken with a Scanning Electron Microscope at x5000 magnification

RBC life cycle

RBCs are highly differentiated cells. During differentiation from blood stem

cells (haematopoietic stem cells) to functional RBCs, the nucleus and the majority of

the cells’ organelles are extruded [36]. As a consequence, mature RBCs cannot

undergo cell division [37]. As the cells differentiate from myeloid progenitors to

mature reticulocytes, the intracellular content in Hb increases, and the membrane

acquires a specialised set of structural proteins [38]. The final stages of maturation and

the transformation into a biconcave disk take place in circulation, after the cells leave

the bone marrow. Differentiated RBCs are described in a simple way as being ‘bags

of Hb’.

RBCs have an expected life span of 120 days in circulation. As RBCs age, their

membrane loses some of its elasticity and flexibility, resulting in a lower cell

deformability [39]. Older RBCs that no longer have the ability to go through narrow

pores present in the spleen are removed from circulation (Figure 2.2). Other

mechanisms for the removal of senescent cells include phagocytosis triggered by the

presentation of surface removal markers, such as the exposure of denatured Band 3 or

phosphatidylserine (PS) [40; 41].


Figure 2.2: A red cell traversing from the splenic cord to splenic sinus. From “Red cell

membrane: past, present, and future”, by N. Mohandas and P.G. Gallagher, 2008, Blood,

112(10): p. 3939-48 [11].

RBC mechanical properties

The ability of RBCs to flow through the narrowest sections of the circulatory

system, without rupturing, is linked both to their shape and to their membrane

properties. The high surface area-to-volume ratio of the biconcave shape enables RBCs

to deform strongly when placed under shear flow conditions or under compression

[42]. The unique structure of the RBC membrane, composed of a lipid bilayer and a

two-dimensional (2D) cytoskeleton network, is at the origin of its high flexibility and

resistance to tensile and shear strains (see Section 2.1.2 below) [43; 44].

2.1.2 RBC membrane structure

The RBC membrane is made of two main components: a lipid bilayer, in which

proteins are embedded, and a 2D cytoskeleton network anchored beneath it.

RBC lipid bilayer

The lipids present in the bilayer are asymmetrically distributed. The external

leaflet is rich in sphingomyelin (SM) and phosphatidylcholine (PC), while the internal

leaflet contains mostly phosphatidylethanolamine (PE) and PS (Figure 2.3).

Cholesterol is present in both leaflets [45]. This asymmetry is maintained by adenosine

triphosphate (ATP) dependent active transport [46]. Thus, failure to maintain

asymmetry and PS exposure are detected as markers of senescence for RBCs. The lipid

composition influences the rigidity of the membrane, due to the difference in

temperature of fusion between different lipids: lipid molecules have been shown to be

organised over the membrane surface into ‘raft’ areas or ‘liquid domains’, containing

a higher concentration of sphingolipids and cholesterol [47]. These rafts are linked to

the membrane skeleton and play a role in the membrane stability. The integrity of the


membrane bilayer and its bending stiffness are related to the proportion of both liquid

and solid lipid phases [45; 48].

Figure 2.3: Proposed distribution of phospholipids between inner and outer layer of the human

erythrocyte membrane (Sph, sphingomyelin; PC, lecithin, PE, phosphatidylethanolamine, PS

phosphatidylserine). Adapted from “The asymmetric distribution of phospholipids in the

human red cell membrane. A combined study using phospholipases and freeze-etch electron

microscopy”, by A.J. Verkleij, et al., 1973, Biochimica et Biophysica Acta (BBA) -

Biomembranes, 323(2), 178-193 [45].

RBC membrane proteins

Numerous proteins are included in the lipid bilayer. Transmembrane proteins are

often grouped in multi-protein complexes [12] with important biological roles for the

cell: they act as transport channels for water, ions or larger molecules, take part in

maintaining the structural integrity of the membrane or interact with proteins on the

surface of other cells [11]. Band 3 is a transmembrane anion exchanger, and is the most

common protein found on the RBC surface [49]. Band 3 is damaged by oxidation when

RBCs age and its breakdown is involved in senescence signalling pathways [41]. It

also has an important role in membrane protein complexes anchoring the cytoskeleton

to the bilayer [12].

RBC cytoskeleton

Contrary to most cells, RBCs do not have a transcellular cytoskeleton but a ‘2D’

cytoskeleton anchored just below the bilayer’s inner leaflet [50; 51]. This skeleton

explains the unique properties of RBCs as it gives the cells their elasticity. As shown

in Figure 2.4, the membrane proteins and the membrane skeleton are linked through


proteins such as ankyrin, Band 3 and protein 4.1 [50-53]. The strong links between the

membrane and the skeleton ensure that the surface area remains constant without

vesiculations and without membrane breakage [54].

Figure 2.4: Schematic representation of two types of multiprotein complexes in the red cell

membrane, from “Protein 4.1R-Dependent Multiprotein Complex: New Insights into the

Structural Organization of the Red Blood Cell Membrane”, by M. Salomao, et al., 2008,

Proceedings of the National Academy of Sciences of the United States of America, 105(23), 8026-

8031 [12].

The spectrin network

The RBC cytoskeleton is composed of two main types of proteins: actin and

spectrin [55]. Spectrin is made of the assembly of 2 α and 2 β subunits, forming a long

tetrameric protein. Each segment, inside the subunits, is made of repeated α-helix

sections that fold upon themselves, condensing the protein [56]. When stretched, the

segments unfold and the protein becomes longer (Figure 2.5). This conformation

change is reversible, and the molecules have the ability to contract again when the

stretching force is removed [57]. It was shown that temperature influences the

conformation of spectrin, changing its equilibrium state and the number of segments

folded. At lower temperature, spectrin proteins will be shorter and denser [58].


Figure 2.5: Schematic illustrating a) a folded repeated spectrin structure comprised mostly of

the 106-residue repeats, and b) a peptide segment in which one repeat has unfolded, adapted

from “Spectrin Folding versus Unfolding Reactions and RBC Membrane Stiffness”, by Q. Zhu,

et al., 2008, Biophysical Journal, 94(7), 2529-2545 [59].

Spectrin molecules are linked to actin filaments to form a connected network

(Figure 2.6). A reorganisation of the connections inside this network happens when

the membrane is stretched, as illustrated by the differences between Figure 2.6a and b.

Self-association sites between spectrin proteins (circles in Figure 2.6a) disappear, and

spectrin proteins are reconfigured to form longer chains [60]. The reorganisation of

the spectrin/actin network is thought to be responsible for the RBC membrane

elasticity and deformability [61]. It is an active phenomenon, depending on energy

provided by ATP molecules [62; 63].

Figure 2.6: Model for transition between the a) intact and b) expanded forms of the erythrocyte

membrane (red and blue filaments: spectrin; red bars: actin), adapted from “Native

ultrastructure of the red cell cytoskeleton by cryo-electron tomography”, by A. Nans, et al.,

2011, Biophysical Journal, 101(10), 2341-2350 [60]


Membrane components and their mechanical properties

In summary, the RBC membrane is a complex association of lipids,

transmembrane proteins and skeletal proteins. The interactions between all the

components of the RBC membrane have not been elucidated yet, but models of its

organisation are emerging (Figure 2.7). The mechanical properties of RBC membrane

are explained by its structure: the lipid bilayer gives the membrane its bending stiffness

(or flexibility), while the cytoskeleton gives the membrane its elastic properties.

Overall cell deformability is the ability of the RBC membrane to resist tensile,

compressible and shear strains through the combination of both its flexibility and

elasticity. Thus, it is important to study RBC membrane deformability in case of

pathological or altered cells in order to understand how the underlying structure is

affected by the condition.

Figure 2.7: Hypothetical interactions between detergent resistant molecules of the RBC

membrane and the cytoskeleton, adapted from “Membrane rafts of the human red blood cell”,

by A. Ciana, et al., 2014, Molecular Membrane Biology, 31(2-3), 47-57 [47].

2.1.3 RBC shapes

RBCs adopt a large range of shapes (or morphologies) from the influence of their

environment (such as pH, or osmotic pressure), their age or pathological conditions.

In this document, the focus will be on shapes produced by environmental conditions

or aging in storage.


The stomatocyte – discocyte – echinocyte transformation

The characteristic RBC biconcave shape is called the discocytic shape.

Discocytes are recognisable by their smooth and flat ‘doughnut’ appearance. Two

main types of shape transformation result from the biconcave shape (Figure 2.8). The

first one is the echinocytic transformation, which results in rounder cells covered in

spicules (Figure 2.8, right side transformation). The second is the stomatocytic

transformation, during which RBCs are transformed into rounder cells, with a single

larger central concavity (Figure 2.8, left side transformation) [42].

Figure 2.8: Schematic diagram showing the discocyte – echinocyte – stomatocyte

transformations, from “Red Cell Structure, Shapes and Deformability”, by M. Bessis, et al.,

1975, British Journal of Haematology, 31(s1), 5-10 [42].

Both transformations are progressive, with intermediate stages (Figure 2.9) [64].

During the echinocytic transformation, RBCs first acquire an ‘irregular contour’ and

are echinocytes I. Then, RBCS progressively develop spicules over their surface, while

remaining flat, at which stage they are echinocytes II. Finally, the cells get rounder,

with over 30 spicules on their surface. At this stage, RBCs are echinocytes III. The

final stage of the echinocytic transformation is irreversible: the cells shed

microparticles (vesicles made of the RBC membrane, containing Hb rich cytoplasm)

from the end of their spicules until they become spherical. They are then sphero-

echinocytes. During the stomatocytic transformation, RBCs evolve from having two

shallow concavities, to having a single concavity on one side. At this stage, they are

stomatocytes I. Then, the concavity will become deeper, the cells taking a ‘cup-shape’

morphology and becoming stomatocytes II. The final stage of the stomatocytic

transformation is also irreversible, as RBCs internalise part of their membrane through

endocytosis, until they too, become nearly spherical. They are then sphero-

stomatocytes.


Both shape transformations are associated with a reduction of surface area-to-

volume ratio. Thus, sphero-echinocytes and sphero-stomatocytes have lower

deformability than discocytes [65].

Figure 2.9: Illustration of the echinocytic and stomatocytic transformations. Scanning electron

microscopy, x5000 magnification.

Shape transformation agents

Shape transformations are the result of changes in the RBCs’ environment. The

‘environment’ encompasses the medium in which the cells are resuspended, incubation

temperature, experimental setup characteristics such as the material imaging chambers

are built from, or any external parameter that could influence cell shape. Different

factors are at the origin of shape changes [66]:

- pH: low pH promotes the transformation of RBCs into echinocytes, whereas

high pH results in stomatocytes. The discocyte shape is found at

physiological pH, around 7.4 [67; 68].

- Osmolality and ion concentrations: high concentrations in electrolytes such

as calcium, sodium or potassium [69] promote the echinocytic shape, but low


concentrations promote the stomatocytic shape [70], even at constant

osmolarity [71].

- Glass effect: incubation of RBCs on a glass surface promotes the appearance

of echinocytes [72; 73]. Plasma or bovine serum albumin (BSA) rich

medium are used in most experiments conducted over glass, to counteract its

echinocytic effect. BSA also prevents RBCs from adhering to glass

substrates.

- Temperature: temperatures below 20°C promote echinocytes in solution,

whereas temperatures above 37°C promote stomatocytes [74]. At

physiological temperature and in physiological buffer, a mix of different

morphologies is usually observed.

- Amphiphilic agents: amphiphilic components inserted into the membrane

lipid bilayer produce either echinocytic or stomatocytic shape, depending on

which leaflet they have the highest affinity for [75-77].

This list is non-exhaustive; RBC shape is affected by many other factors present

in the environment. Most studies agree that reversible echinocytic transformations

triggered by the RBC environment are not associated with a variation of internal

volume [78-80]. They are then linked to the organisation of different components

inside the membrane.

Shape transformation mechanisms

Several hypotheses [77; 81; 82] were proposed regarding the mechanisms of

shape transformation resulting from the environment. A consensus on the exact

mechanisms of shape transformation has not been established at present [83]. The main

proposed mechanisms are:

- The bilayer couple hypothesis: the earliest hypothesis regarding shape

transformation was established by Sheetz and Singer (1974) [77]. This

hypothesis considers the two leaflets of the lipid bilayer behaving

independently. Amphiphilic agents will preferentially be included in the

outer or inner layer, based on their structure or their charge, increasing the

surface area of one of these leaflets. The difference in surface area between

leaflets would be at the origin of the shape transformation (Figure 2.10).

When the outer layer expands, the difference in surface area is compensated


by the outward crenation of the surface, resulting in the RBCs taking an

echinocytic morphology. On the opposite, when the amphiphilic agent is

preferentially included in the inner leaflet, the difference in surface area is

compensated by the invagination of the membrane and stomatocytes are

created.

Figure 2.10: Schematic representation of the proposed binding of amphipathic compounds that

are crenators or cup-formers to the phospholipid regions of the erythrocyte membrane, adapted

from “Biological membranes as bilayer couples. A molecular mechanism of drug-erythrocyte

interactions”, by Sheetz and Singer, 1974, Proceedings of the National Academy of Sciences of

the United States of America [77].

However, experiments using amphiphilic drugs were able to demonstrate the

acquisition of the echinocytic and the stomatocytic shape [77], but not their

reversibility. A new model was needed to explain the RBC shape

transformation [75].

- The ‘cytoskeleton organisation’ hypothesis: Cytoskeleton isolated from the

membrane and resuspended in solutions at different ionic strength has the

ability to contract and expand, reproducing the stomatocyte-discocyte-

echinocyte transformation [81]. These results suggest that the RBC shape

transformation may not rely solely on the lipid bilayer, but is also dependent

on the cytoskeleton organisation. However, the shape transformations

observed on isolated spectrin-actin networks were only reversible for short

periods, before the network started shrinking [84] or breaking down [85].

The RBC shape transformation was then hypothesised to rely on cooperation

between the bilayer and the cytoskeleton [85].


- The ‘Band 3 conformation’ hypothesis: This hypothesis was developed by

Wong (1994) [82]. Band 3 proteins have two main conformations: the

outward facing conformation allows anions to enter the cells (Figure 2.11a),

while the inner facing conformation allows the efflux of anions (Figure

2.11b). Band 3 is linked to spectrin molecules through ankyrin, and

conformation changes in Band 3 are hypothesised to either fold or unfold

spectrin [66]. The ratio of outward facing to inward facing Band 3 protein

would determine the overall folding state of the spectrin network (Figure

2.11). In a physiological environment, the ratio of inward facing to outward

facing Band 3 proteins is 15:1, agreeing with a dense cytoskeleton network

[60]. When external anion concentration changes, Band 3 proteins change

their conformation to allow for an osmotic balance between the cell

cytoplasm and its environment to be found. The Band 3 conformation ratio

changes, and so is the organisation of the spectrin network. The cytoskeleton

then pulls or relaxes the membrane, changing the cell shape. In this

hypothesis, an increase in the extracellular pH inhibits anion efflux through

the ionisation of Hb and reduction of intracellular Cl-, resulting in a

shortening of the spectrin network, and the appearance of echinocytes [86].

Figure 2.11: Schematic representation of the mechanism of control of erythrocyte shape by

Band 3 proteins, adapted from “A Basis of Echinocytosis and Stomatocytosis in the Disc–Sphere

Transformations of the Erythrocyte”, by P. Wong, 1999, Journal of Theoretical Biology, 96(3),

343-361[66].


Current hypotheses regarding the RBC shape transformation consider an active

role from both the cytoskeleton and the lipid bilayer. Shape transformation is an active

ATP-dependent mechanism. It results from the organisation of the spectrin network,

its interaction with the lipid bilayer through anchoring protein complexes and the

surface area and bending constraints of the lipid bilayer [85; 87]. In order to get more

insights on the mechanisms regulating the RBC shape, focus shifted from studying

cells in a static environment, to studying their response to mechanical stresses [88].

New studies now aim to identify the role of the different membrane components in

maintaining membrane integrity under strain, with the hope of clarifying their

relationship [58; 62].

This PhD project is part of the effort made to understand the link between RBC

shape, membrane structure and mechanical properties. The studies presented in this

document are applied to understanding the effect of aging in vitro on the RBC shape,

and what consequences storage have on the ability of the cells to flow in circulation

after transfusion. Current concerns regarding RBC storage are presented in the next

section, and a review of methods available for the study of RBC shape and membrane

properties is presented in Section 2.3.

2.2 RBCs and transfusion

2.2.1 RBC transfusions

RBCs are transfused to prevent severe anoxia in patients and reset the oxygen

perfusion to the organs. In Australia, RBC products are transfused to patients suffering

from cancers or blood diseases (35% of RBC transfusions), patients undergoing

surgery (18%), patients with medical problems such as heart, stomach and kidney

diseases (13%), orthopaedic patients (10%), obstetric patients (8%), and trauma

patients (2%) [22]. The remaining RBC products are transfused for other causes of

anaemia.

2.2.2 RBC processing and RBC products

In Australia, whole blood donations are separated into their three main

components: RBC, plasma and platelets. After reception in one of the ARCBS

processing centres, units of whole blood are centrifuged. Three layers appear after

centrifugation (Figure 2.12a). RBCs are denser than plasma and fall to the bottom of


the bag, making the bottom layer. Plasma makes up the top layer, and at the interface

between RBCs and plasma, platelets and white blood cells (WBCs) form a layer called

‘buffy coat’ [89]. Centrifuged units are slowing pressed using automated machines to

extract plasma and RBCs and collect them into separate bags (Figure 2.12b): plasma

is pushed from the unit through tubing connected to the top of the bag, and RBCs flow

through tubing connected to the bottom of the bag. Only the buffy coat is left inside

the original whole blood unit.

Figure 2.12: Whole blood units are centrifuged (a) then separated into their different

components using automated machines (b), adapted from “Why is whole blood split three

ways?”, by S. Heatley, 2010, Transfusion Fact Sheets, The Australian Red Cross Blood Service,

2(4) [89].

Before reaching the bag in which they are going to be stored, RBCs pass through

a leukoreduction filter: a few WBCs may still be present in the RBC fraction after

centrifugation, and the leukoreduction filter has the goal to remove them [90; 91].

Transfusion of RBC products containing WBCs are associated with lower quality of

product and increased adverse events in patients [92; 93]. Leukoreduction filters are

composed of a mesh that is too small for WBCs to pass. As RBCs are smaller and very

deformable, they are not stopped by the filter.

After leukoreduction, RBCs are collected in a 450 mL bag already containing

105 mL of a storage solution made of a saline solution supplemented in adenine,

glucose and mannitol (SAGM) [94; 95]. SAGM detailed composition can be found in

Table 2.1 below.


Table 2.1: Composition of SAGM [94; 95]

Constituent Concentration

Dextrose monohydrate 9.0 g/L

Sodium chloride 8.77 g/L

Mannitol 5.25 g/L

Adenine 0.169 g/L

SAGM is used to protect RBCs during storage. It was first developed by Hogman

et al. (1981) [96]. SAGM was designed to keep RBCs supplied with glucose and

adenine during storage. Glucose and adenine participate in the RBC metabolism and

the production of ATP. Mannitol was found to prevent RBC haemolysis during cold

storage by preventing the osmotic imbalance between the intracellular content and the

storage solution [97; 98]. Using mannitol reduces the number of free Hb molecules

released by haemolysis, which participate in the oxidation of membrane structural

component after binding to dioxygen molecules.

Once RBCs are resuspended in SAGM, the bag is sealed and placed at 4°C.

Processed RBC products are commonly called packed RBC (pRBC) units. After

processing is completed, pRBC units are kept for up to 42 days at 4°C [95; 99]. If they

are not used before this time, pRBC units are discarded.

2.2.3 Guidelines for the quality of stored RBC products

Protocols for RBC separation and storage of pRBC units are based on safety and

quality criteria established by regulating authorities: the ARCBS follows

recommendations from the NBA, and guidelines from the Therapeutic Good

Administration (TGA) and from the Council of Europe regarding the quality of blood

products [95; 100; 101].

The Council of Europe guidelines approves pRBC storage protocols based on

quality and efficiency criteria. In order for a protocol to be approved, a minimum of

75% of transfused RBCs should be present in circulation 24h after transfusion, and

haemolysis level should stay below 0.8% at the end of the storage period. Based on

these criteria, pRBC units’ storage conditions were fixed at a maximum of 42 days at

4°C in Australia.


2.2.4 RBC aging in vitro and the storage lesion

During storage, RBCs undergo significant modifications known as ‘storage

lesion’. This affects cellular metabolism and damages structural components, inducing

shape transformation [17; 102]:

- Metabolic slowdown: SAGM supplements RBCs with glucose and adenine,

two metabolites used during the glycolytic metabolic pathway, in order to

maintain the energy metabolism during storage. However, lactate and

protons, created as metabolic waste, accumulate in the storage bag and

acidify the pH. Enzymes, such as phosphofructokinase, responsible for the

conversion of glucose and adenine into ATP, are inhibited at low pH and the

metabolism progressively slows down [103]. Adenine is not available after

18 days of storage [104]. The intracellular concentration of ATP reduces

from the third week of storage [105], inhibiting all active mechanisms inside

the cells. Storage at 4°C instead of room temperature (RT) ensures the

acidification of the pRBC units takes weeks instead of days [102]. The

glycolytic metabolism was shown to be restored in the hours following

transfusion [106].

- Oxidative damage: in the donors’ circulation, Hb is close to being saturated

in dioxygen. These dioxygen molecules are at the origin of oxidative damage

during storage [102]. Reactive oxygen species (ROS) accumulate and

damage membrane lipids and proteins, resulting in lipid peroxidation and

cytoskeletal protein fragmentation. Oxidised Hb binds and denatures

transmembrane ion exchangers, such as Band 3, deregulating the osmotic

balance and metabolism even more [107; 108]. Denaturation of Band 3

changes its interactions with already damaged ankyrin and spectrin proteins,

remodelling the cytoskeleton organisation. Oxidation of membrane proteins

results in RBC shape changes and decreases RBC deformability [109; 110].

- Shape changes: RBC shape is altered during storage due to the accumulation

of structural damage to both the lipid bilayer and the cytoskeleton and

changing environment, such as the increasing acidity of the storage solution.

The shape transformation that RBCs go through with aging in storage is

similar to the echinocytic transformation: spicules progressively appear over

their surface, and become rounder until they reach a sphero-stomatocytic


stage [111; 112]. Microparticles, containing broken structural elements, are

shed from the end of the spicules [113], as a possible salvage mechanism

[114; 115]. Oxidative damage of cytoskeletal proteins and shape

transformation result in decreased deformability after long periods of storage

[14; 116; 117].

After transfusion, parts of storage-associated morphology changes are

reversible, as metabolism and ATP production are restored. However, some structural

damage to cytoskeleton proteins, and surface area and volume loss through the

formation of microparticles are irreversible. The number of sphero-echinocytes in

pRBC units increase from 7% after 5 days of storage, to 29.9% [118] or 39.5% [111]

at day 42 (Figure 2.13). Because of the oxidative injury affecting anchoring and

cytoskeletal proteins, sphero-echinocytes are more fragile. They have a higher risk of

haemolysing during storage and after transfusion [119], releasing free Hb in the

circulation.

Figure 2.13: Scanning electron microscope picture of RBCs on the 42nd day of storage, from

“Influence of Storage on Red Blood Cell Rheological Properties”, by T.L. Berezina, et al., 2002,

Journal of Surgical Research, 102(1), 6-12 [118].

2.2.5 Questions regarding the age of blood

The changes occurring during the 42 days of storage decrease the quality of

RBCs and are associated with transfusion complications for patients.

Transfusion of older pRBC units are hypothesised to produce more adverse

events in patients, due to their higher level of haemolysis and high content of RBCs

with altered shapes [16; 120]. RBCs presenting irreversible storage injury and sphero-

echinocytic shapes are removed quickly from circulation after transfusion; they present

markers of RBC senescence, and are not deformable enough to cross the splenic pores.


Destruction of these cells by the liver will release large quantities of free Hb, saturating

iron-carrying proteins, such as ferritin and transferrin. Free iron in circulation was

associated with increased risk of infections in transfused patients, as iron promotes

pathogen proliferation [121; 122]. Transfusion of old pRBC units was also associated

with increased risks of TRALI [5], and mortality [4].

On the other hand, other studies report no adverse effects after transfusion of old

pRBC units, and, in particular, no association with an increase in patient mortality [10;

123]. Another study shows that cells altered by the storage lesion were not cleared

faster than recently donated RBCs after transfusion [124], thus disproving the

foundations of the iron hypothesis.

The contradiction between results, when it comes to the question of the age of

blood, led to the implementation of large-scale RCTs. Three studies investigated the

effect of transfusion of RBCs stored in SAGM for up to 42 days, on patient mortality

[7-9]. These three studies were all inconclusive [125-128]. One main weakness of

these studies is that the older pRBC units were chosen following the hospitals’ usual

practices, with an average of 22 days [9], 24 days [8] and 28 days [7], far from their

maximum shelf-life of 42 days. There are ethical questions to be considered when

designing an RCT, and transfusion of very old pRBC units during trials was not

considered acceptable. The ‘young’ and ‘old’ units were not that different in terms of

storage duration and expected storage lesion, especially considering that the storage

lesion starts affecting RBCs after the third week of storage, on average.

Adding to the inconclusive RCT trials, researchers are questioning the suitability

of chosen quality criteria for RBC storage: current standards monitor the level of

haemolysis after 42 days and the recovery of 75% of transfused RBCs at 24h after

transfusion. These criteria represent the ability of the cells to stay in circulation but do

not consider, for example, the dioxygen transport capacity. They were also assessed

on healthy volunteers, not patients [129]. Studies report that the initial characteristics

of a blood sample is predictive of its quality at the end of the storage period: aging is

a linear phenomenon, and from controlling initial parameters at donation, properties

of the old pRBC unit could be predicted [130]. Some donors are described as ‘poor

storers’ or ‘super storers’ as their blood consistently ages poorly or exceptionally well

in storage [16]. Suggestions are made to individually assess pRBC unit quality, either

at donation or just before transfusion [131; 132].


This PhD project focused on establishing the link between shape transformation

and mechanical properties of stored RBCs, in order to produce quantitative values of

RBC quality using mechanical testing. The next section presents methods used to

characterise RBC physical and mechanical properties.

2.3 Assessment of RBC physical and mechanical properties

2.3.1 Imaging methods

Light microscopy

Bright field and phase contrast imaging require limited sample preparation and

image live cells. These methods are useful to observe the appearance of RBCs and

quantify the number of discocytes, echinocytes or stomatocytes [112; 133]. However,

the resolution of bright field and phase contrast imaging only reaches x1,000

magnification at its highest [134], and cannot resolve details over the RBC membrane.

Confocal imaging couples fluorescence imaging and pinholes to remove out-of-

focus light, resulting in higher resolution imaging [135]. Samples are labelled using

fluorescent compounds before imaging. Slices of the samples are imaged sequentially,

before being stacked [135]. Thus, 3D images of the labelled cells are obtained.

Confocal imaging was applied to RBC in order to extract their 3D morphology [136],

and quantify their size [137]. However, it was found out to be inaccurate for

quantitative measurements [137].

Scanning electron microscopy

Scanning electron microscopy (SEM) uses a focused electron beam to create an

indirect image from a sample [134]. Samples are placed in a vacuum chamber to

prevent air and water particles from interfering with the electrons. Thus, biological

samples need to be fixed and dried before imaging [138]. SEM has been used

extensively to study the morphology of RBCs during aging in storage [72; 93; 111;

118; 139; 140].

Shape characterisation

Since the description of the stomatocyte-discocyte-echinocyte transformation by

Bessis (1972) [64], efforts have been made to characterise the physical properties of

the different morphologies, such as their surface area or volume [30; 80; 137; 141-


143]. A wide range of methods were used: bright-field imaging [142], SEM imaging

[143], confocal imaging [137] and quantitative phase imaging [30; 80; 141]. A

summary of results from these studies can be found in Table 2.2 below. Most studies

focused on the discocytic morphology, and two studies only measured properties of

stomatocytes [142; 143]. No data are available on the echinocytic morphology.

Table 2.2: Summary of surface area and volume measurements on RBCs

Method Shape Volume Surface Area

Quantitative phase imaging Discocyte 94 fL 135 µm2 [141]

Quantitative phase imaging Discocyte 86 < < 102 fL [80]

Quantitative phase imaging Discocyte 89.7 fL 152.7 µm2 [30]

Bright-field imaging Discocyte

Stomatocyte

99 fL

89 fL

134 µm2

143 µm2 [142]

SEM imaging Discocyte

Stomatocyte

97.91 fL

141.73 fL

129.95 µm2

138.73 µm2 [143]

Confocal imaging Discocyte 90.7 fL [137]

As mentioned in Section 2.1.3, the mechanisms behind RBC shape

transformation are not well understood. Characterisation of the cells’ physical

properties as their morphology evolves, either because of their environment or because

of the storage lesion, is made difficult by the fact that common observation methods

influence the results. For example, observation of RBC shape using bright field

microscopy possibly produces shape artefacts due to the presence of a glass coverslip,

or due to the increasing heat from the light source [72]. Similarly, SEM imaging

involves a chemical fixation of the cells before dehydration. Most SEM studies used

glutaraldehyde as fixative, which has a strong, shape-changing effect on RBCs [139;

143; 144].

Characterising the shape of RBCs as they age in storage requires an

understanding of the effect of their storage environment first. Many studies reporting

aging effect on cell shape do not discuss the effect that buffer, temperature or imaging

technique have on their observations [30; 133]. Reference studies reporting the number

of RBCs presenting an irreversible morphology after storage [17; 111; 118] used a

concentration of glutaraldehyde reported to produce between 10% and 20% of cell

shrinkage in the buffer used, which is phosphate-buffered saline (PBS) [144]. Results


presented during these studies show the combined effects of the storage lesion, PBS

composition, and chemical volume shrinkage on RBC shape. To correctly assess shape

transformation caused by aging in storage, current SEM protocols need to be improved

[17; 111; 118].

2.3.2 Mechanical testing

The RBC membrane mechanical properties come from the interaction between

its active cytoskeleton, which provides it with high elasticity, and the lipid bilayer that

resists large deformations [85]. During aging in storage, structural components such

as spectrin and Band 3 are affected by oxidative stress, altering their structure and

function [107-110]. Furthermore, a shape transformation is observed as the cells spend

more time in storage [112; 139; 143; 144]. Mechanical studies have investigated the

relationship between shape and deformability using a range of methods such as

microvascular flow [14; 19; 145], micropipette aspiration [44; 88; 146; 147], AFM

[29; 148-153], and optical tweezers [26; 154-161] .

Microfluidics devices

Global RBC deformability is a criterion of pRBC unit quality after storage, and

a large number of studies investigated the behaviour of stored RBC under flow

condition in microfluidics devices [14; 145]. These devices imitate capillary networks

and they were demonstrated to be sensitive enough to detect flow rate modification

due to RBC shape transformation [19]. Results on the effect of storage duration in

SAGM on cell deformability are contradictory. One study observed a reduction in flow

rate through a microvascular device and associated it to a decrease in deformability

[14], whereas another concluded that storage duration did not alter RBC deformability,

by comparing the deformability index of RBCs after different storage periods, and at

different flow rates [145]. Microfluidic studies remain inconclusive. Contradicting

results may be due to the different percentages of RBCs with altered shapes in the

samples tested. Samples containing more echinocytes would appear less deformable,

using a microvascular device. However, these methods measure an overall sample

deformability average, and do not account for donor variation and different sample

sensitivity to storage [116]. Experimental methods testing single cells may be more

suitable to link cell shape and mechanical properties.


Micropipette aspiration

The first mechanical testing method applied to RBCs was micropipette

aspiration [146]. This method works by pulling the RBC membrane inside a

micropipette with an internal diameter under 1 µm, until the part left outside the

micropipette (the ‘residue’) becomes spherical and the membrane cannot stretch

anymore. The pressure is recorded and the critical tension of the membrane, as well as

its resistance, are measured [146]. Micropipettes have been used to understand the

organisation of the RBC membrane [44; 88; 147], and showed that echinocytes have a

reduced membrane resistance compared to discocytes [146], but this technique has not

yet been applied to studying the aging of RBCs in storage. The forces applied to the

RBC membrane during testing produce extreme local deformations that are not

predictive of global cell deformability. Local deformability is not an accurate indicator

for RBC behaviour in the circulation after transfusion.

AFM

AFM was applied to RBCs to measure the local membrane deformation under

compression: a probe applies a known force on the membrane, and the resulting

deformation is recorded [148]. AFM was successfully used to study the RBC

membrane deformability [149; 150] and provided a new explanation to the shape

transformation mechanisms [151]. AFM was applied to study the effects of storage on

RBCs membrane properties [29]. Storage was associated to reduced membrane

elasticity and correlated to RBCs transforming from discocytes to echinocytes [29].

However, RBCs in that study were air-dried before testing, altering the osmotic

equilibrium of the membrane and modifying its properties. Moreover, AFM samples

need to be adhered on a substrate before indentation, and adhesion protocols have been

shown to influence RBC membrane properties due to lateral tension created between

the cell and the substrate [152; 153]. Optimised protocols would need to be developed

first, and then applied to study RBC aging in storage using AFM.

Optical tweezers

Optical tweezers use focused laser beams to trap and manipulate micrometric

objects [154]. They have a large range of biological applications, given their ability

to apply and measure force in the piconewton range, making them ideal to study

intracellular forces [155]. Optical tweezers have successfully been used to stretch RBC

by trapping and pulling on beads attached to their membrane [156-161]. It has been


shown that the traps could also be applied directly on the RBCs without damaging

them [161]. Using direct trapping, RBCs were stretched after different storage

durations, by pulling on the membrane of RBCs adhered to a substrate [26]. Results

of this study showed a decrease in deformability during storage, but the experiments

stopped after 21 days of storage, and the effects of the storage lesion are reported to

affect RBCs, mostly after the third week of storage [105]. This study was too short,

and did not report the effect the storage lesion could have after 42 days of storage [26].

It also did not consider the effect RBC shape could have on membrane deformability

[26]. A longer study would be required to fully characterise the evolution of the RBC

membrane deformability over the 42 days of storage.

2.4 Summary and Implications

The RBC membrane composite structure gives it its unique deformability

properties. The relationship between the damage affecting the membrane structural

components during storage, the shape transformation and the cell global deformability

is still unclear. Several important limitations to published results are summarised as

follows:

- The effect of storage lesion on RBC shape was measured in buffer with no

clinical relevance [111; 118; 140]. These studies do not discuss the effect of

environment on the observed results.

- A handful of studies characterised the physical properties of discocytes,

such as their surface area of internal volume [80; 137; 141; 143]. However,

very few studies focused on the evolution of physical properties during the

discocytic-stomatocyte [142; 143] or the discocyte-echinocyte

transformations, either due to environmental conditions or storage duration.

- AFM is a powerful tool to understand the organisation of the RBC

membrane down to the protein level, but current protocols give limited

results due to the sample preparation step [152; 153].

- AFM has not been applied to understanding the evolution of live RBC

membrane deformability during a long period of storage in SAGM and its

relationship to cell shape [29].


- Optical tweezers can be used to manipulate and stretch RBCs without

damaging them, but most protocols use beads attached to the cell membrane

as handles, producing large local deformations when the cell is stretched

[156-161]. Stretching RBCs between two traps directly applied to the cell

has not been tested yet.

- Optical tweezers stretching has not yet been used to study the mechanical

behaviour between different RBC morphologies and was mainly applied to

discocytes.

- Optical tweezers stretching was only applied to study RBC deformability for

short periods in storage [26]. No study covers the 42 days of storage.

This PhD project aimed to overcome these limitations by studying the effect of

aging in storage on RBC shape, then characterising the physical properties of the

different shapes, such as their volume or surface area. Once the cell shape was

characterised, two mechanical studies were conducted, using AFM and optical

tweezers, assessing RBCs mechanical properties. Insights on the relationship between

cell aging in storage, their shape and their mechanical properties, were gained during

this project.

Chapter 3:Assessment of RBC shapes during storage 31

Chapter 3: Assessment of RBC shapes during

storage

In this chapter, the morphology of RBCs after different storage durations and in

different buffers was observed, to understand the link between storage duration,

environment and RBC shape. RBCs were resuspended into cold-agglutinin-depleted

FFP, SAGM and ‘artificial plasma’ buffers, and imaged using bright field microscopy.

The percentages of different morphologies, as well as cell diameters, were recorded.

Other parameters such as sample haemolysis were monitored as well, as an indicator

of pRBC unit quality.

3.1 Introduction

During routine storage, RBCs progressively accumulate structural damage,

commonly called the storage lesion, [162; 163] which affects both cellular metabolism

and structural components [17; 164]. It is widely accepted that as a consequence, cell

shape evolves during storage, from the characteristic biconcave discocytic shape to a

shrunken echinocytic shape with spicules over the surface. This shape transformation

reaches an irreversible stage when membrane surface area is lost through

microvesiculation. The resulting cells are called sphero-echinocytes. After 42 days of

storage, up to 29% of cells assume an irreversible echinocyte morphology, assessed

using a nucleopore filtration method [118], and 31% [140] or 39% as demonstrated

using SEM imaging [111].

The environment the cells are in, also influences their shape. This discovery in

the early 20th century was at the beginning of investigations into the relationship

between RBC shape, and buffer composition. It led to the discovery of membrane

transport mechanisms [69]. Different factors influence RBC shape, such as age, pH,

temperature and buffer. Shape changes were shown to be the result of the combined

effects of these different factors [42]. SEM imaging was used to quantify the different

RBC shapes present in samples stored for 42 days [111; 118; 140]. The shapes

observed during these studies did not account for the effect that buffers could have on

the observed results: PBS was used in the fixation buffer in these studies, but has no

32 Chapter 3:Assessment of RBC shapes during storage

clinical relevance [111; 118; 140]. This may lead to an imprecise estimate of the shape

recovery inside the transfused product. Studies observing cell morphology in an

environment closer to physiological conditions (through buffer composition, or

temperature) could give a better estimate of shape changes during storage and the

percentage of echinocytes with an irreversible morphology at the end of the storage

period.

To separate age-effects from buffer-effects on cellular morphology, RBC shape

was observed during storage when resuspended in three buffers, selected based on their

clinical relevance: the standard storage solution used in Australia, made from a saline

solution supplemented in SAGM [165]; FFP depleted in cold agglutinins (cold-

agglutinin-depleted FFP); and a physiological-like buffer called ‘artificial plasma’.

SAGM is a hyperosmolar solution with respect to physiological osmolarity and

protects the cellular membrane from breakage during storage [96]: using this buffer,

internal volume was expected to reduce, decreasing membrane tension. It would be

interesting to verify if SAGM would prevent the echinocytic transformation of the cell

when placed back into a physiological environment.

FFP was used to model in vivo environment for RBCs with regards to its

chemical composition. FFP was chosen instead of fresh plasma to have a consistent

source of plasma through the study [165]. The reversibility of the SAGM-induced

stomatocytes in FFP could predict shape reversibility post transfusion. Plasma contains

three main components: water (90%), proteins (8%, among which 5.6% is albumin),

and salts (1%) [166; 167]. Traces of other organic components such as lipids are also

found. When frozen, components found in plasma, such as clotting factors, form a

solid fraction called cryoprecipitate. This precipitate is discarded when the liquid

fraction of plasma is collected for experiments. Thus, cold-agglutinin-depleted FFP

has a composition that differs from fresh plasma (such as lower protein content). An

‘artificial plasma’ buffer was created to reproduce some of the properties of fresh

plasma, such as its ionic composition and high protein content. ‘Artificial plasma’ is

less complex than FFP.

Two temperatures were tested here to investigate the effect that incubation

temperature, 4°C or at RT, has on cell morphology. One of the mechanisms, thought

to be at the origin of the echinocytic transformation, is the folding of spectrin upon

itself [58]. Spectrin unfolding depends on temperature: at lower temperature, spectrin


3D conformation is denser, making the protein shorter [57; 58]. As the spectrin

molecules create a network tethered beneath the membrane bilayer, lower

temperatures were hypothesised to be at the origin of the condensation of the

membrane and the appearance of echinocytes [57; 58]. As the cells spend more time

in storage, metabolism slows down. To ensure an equilibrium state between the cells

and their new environment had been reached, two incubation times were used: 20

minutes and 2 hours.

Other than shape, a parameter representative of RBC product quality is the level

of haemolysis following prolonged storage [130]: as the cells age, the integrity of the

membrane can be ruptured, leading to free Hb in solution. Transfusions of RBC

concentrates with high levels of haemolysis could be associated with reduced patient

outcomes and increased risk of infection [16]. Hb present in the supernatant was

monitored using an absorbance assay through this study [168]. Haemolysis level was

calculated proportionally to the total Hb and original haematocrit [169].

This study was designed to evaluate the combined effect of environment and

storage duration on RBC morphology. The objective of this study was to quantify the

different shapes that RBCs assume in storage and when restored to physiological

conditions. Parameters that affect cell shape included in this study are buffer

composition, incubation time and temperature, and storage duration. Cell volume

(mean corpuscular volume or MCV) as well as the level of haemolysis in each sample

were monitored as product quality indicators.

3.2 Aims

This study aimed to:

- Characterise RBC shape when incubated in different buffers after storage in

SAGM,

- Separate the effects of storage and buffer composition on cell shape,

- Describe shape changes expected to happen during RBC aging in storage.


3.3 Materials and Methods

3.3.1 Ethics approval

Ethics approval was obtained from the Blood Service Human Research Ethics

Committee (Balanant270515, 27th May 2015, Appendix A) and from QUT University

Human Research Ethics Committee (1500000511, 9th July 2015, Appendix B).

3.3.2 pRBC

Leukodepleted pRBC units were obtained from the processing department of the

ARCBS (Kelvin Grove, Brisbane, Australia). The units were obtained on the day, or

on the day after standard processing and filtration procedures were completed. Ten A

positive pRBC units were used in total in this study.

3.3.3 Fresh blood samples

Fresh whole blood samples were collected in ethylenediaminetetraacetic acid

(EDTA) spray-coated blood collection tubes (BD Biosciences, Franklin Lakes, New

Jersey, USA) from two consenting healthy volunteers. RBCs were separated from

plasma by centrifugation, and used within one hour of collection.

3.3.4 FFP

FFP units were obtained from the processing department of the ARCBS. Two A

positive FFP units were used in this study.

3.3.5 Plasma preparation

FFP was depleted in cold agglutinins prior to use, so RBC did not agglutinate

during incubation at 4ºC. Both units of A positive FFP were thawed and aseptically

pooled. Pooled FFP was then depleted of cold agglutinins by incubation with A

positive cells from a single pRBC unit (3:1 V/V) at 4°C for 2 hours. The tubes were

inverted every 30 min to mix. RBC and agglutinins were removed by centrifuging the

suspension (3,160g for 20 min), at 4°C. The incubation step was completed twice and

an extra centrifugation step was added after the second incubation to remove any RBC

left in suspension. The clear supernatant was collected and split into 450 mL PVC bags

(Macopharma, Chatswood, Australia) before being frozen at -30°C until use.

Efficiency of cold agglutinin depletion was verified by incubating RBC with the

depleted FFP for one hour at 4°C and observing cell shape under bright field

microscopy. No agglutination was observed.


3.3.6 Artificial plasma preparation

The artificial plasma buffer was realised to replicate theoretical plasma

composition (Table 3.1). After dissolving the chemicals and BSA into milliQ water,

pH was adjusted to 7.4. Carbonate-bicarbonate buffer, calcium chloride dihydrate,

potassium phosphate, and albumin were obtained from Sigma-Aldrich (St Louis,

USA), sodium chloride from Univar (Downers Grove, USA) and potassium chloride

from BDH AnalaR (VWR, Radnor, USA).

The lipid fraction present in the ‘artificial plasma’ buffer was composed of fatty

acids attached to BSA proteins. Only highly purified BSA is certified free of any trace

of lipids, whereas the BSA used here still contains a small quantity of fatty acids bound

to it [170].

Table 3.1: Artificial plasma composition based on human fresh plasma

Physiological values Artificial plasma buffer

Water 90% QSP 100 mL

Proteins

Albumin (BSA) 8% 8g

Salts

Sodium 135 – 146 mM 140 mM

Potassium 3.5 – 5.2 mM 4.4 mM

Calcium 2.1 – 2.7 mM 2.4 mM

Carbonate 23 – 31 mM 27 mM

Phosphate 0.7 - 1.4 mM 1 mM

3.3.7 Time course study

At days 2, 9, 16, 23, 30, 37, 42 and 50 of storage (day 1 is collection day, blood

is processed within 24h of donation), RBCs were sampled aseptically and resuspended

in SAGM (MacoPharma), thawed cold-agglutinin-depleted FFP, or in ‘artificial

plasma’, for a final suspension volume of 1 mL and a final haematocrit of 1:1000. The

cells were then incubated at 4°C or RT, for either 20 minutes or 2 hours. The cell

suspensions (20 µL) were deposited onto coverslips, then imaged. Pictures were taken

over 3 different fields of view using a 60X objective (NA=0.70) on an inverted IX73

Olympus microscope (Shinjuku, Tokyo, Japan) and cell diameter was measured for 30

randomly chosen cells per field of view using Olympus acquisition software. The


number of discocytes, echinocytes, and stomatocytes was counted for each field of

view. The time-course experiments observing RBC morphology in ‘artificial plasma’

were conducted before the time-course experiments using cold-agglutinin-depleted

FFP and SAGM, and only until day 42 of storage. The other time course experiments

were conducted until day 50, which explains the different time-lines in this chapter.

3.3.8 Scanning electron microscopy

SEM imaging was used to quantify RBC shape at the beginning and at the end of

the storage period. RBCs were sampled from fresh blood samples from two volunteers

and from three units of pRBCs at day 3 and 42 of storage. RBCs were resuspended

into PBS (Lonza, Basel, Switzerland), SAGM (Macopharma) or Krebs buffer (Sigma-

Aldrich) to make up 500 µL of solution at 5% haematocrit. Cold-agglutinin-depleted

plasma, or ‘artificial plasma’, was not used in this study as glutaraldehyde would have

transformed RBC suspension in these two buffers into a gellified solid. Krebs was

reported to preserve the discocytic shape of RBCs and was used in this experiment

[112]. RBCs were then fixed by progressively adding 500 µL of a concentrated 2%

glutaraldehyde solution (Sigma-Aldrich) in the cell suspension to reach a final volume

of 1 mL. The cells were incubated for 30 min at RT and in the dark, before being

centrifuged and washed in the corresponding buffer. This fixation protocol was

established in order to limit RBC shape changes due to the presence of glutaraldehyde,

and RBCs prepared following the same protocol without addition of glutaraldehyde

were used as control samples for RBC shape [144].

After fixation, 300 µL of RBC suspension at 2.5% haematocrit was adhered to

coverslips coated with poly-D-lysine (Sigma-Aldrich). A second fixation step was

realised on the adhered RBCs by incubating the coverslips in osmium tetroxide in

cacodylate buffer (1%) for one hour (Proscitech, Kirwan, Australia). The coverslips

were then dried by incubating them in an ascending series of ethanol, then by

incubating them with hexamethyldisilizane (HMDS) for 30 min (Proscitech). The

HMDS incubation step was repeated twice before the coverslips were dried in open air

for over an hour. Finally, the coverslips were gold coated and imaged with a Zeiss

Sigma FESEM (Zeiss, Oberkochen, Germany). Number of echinocytes and total

number of RBCs were counted on three fields of view per condition. The whole

experiment was conducted at RT to limit the influence of temperature on cell shape.


3.3.9 MCV measurement

The MCV was measured on RBCs sampled from the pRBC units at 8 time-points

using a CELL-DYN Emerald automated cell analyser following manufacturer’s

instructions (Abbott, Chicago, USA). The automated sample analysis also quantified

total Hb. This value of total Hb represents Hb proteins present inside the cells as well

as in the supernatant. It was used later to calibrate the level of haemolysis during

storage.

3.3.10 Haemolysis monitoring

After running the samples through the cell analyser, the remaining cells were

centrifuged and the supernatant collected for Hb titration using an absorbance assay.

Free Hb concentration was determined following a modified Harboe’s method [168]

based on Hb absorption wavelength and corrected for non-specific absorption:

Free Hb (g L⁄ ) = (167.2 ∗ A415 − 83.6 ∗ A340 − 83.6 ∗ A450)/1000 (3.1)

where A415 is absorbance at 415 nm for Hb absorption, and A340 and A450 are the

corrective terms for non-specific protein absorption at 340 nm and albumin absorption

at 450 nm respectively. This free Hb concentration is transposed back to percentage of

haemolysis using haematocrit and total Hb values given by the automated cell analyser

[169]:

Percentage haemolysis (%) = (100 − Hct) ∗ Free Hb Total Hb⁄ (3.2)

where Hct is the sample haematocrit in L/L and Total Hb is the sample concentration

in Hb (g/L).

3.3.11 Statistical analysis

Statistical analyses and representation of data were performed using GraphPad

Prism 7.00 (GraphPad Software, La Jolla, USA). Evolution of shape percentages

during storage was analysed using a one-way analysis of variance (ANOVA), and

comparison between experimental parameters with a two-way ANOVA followed by

post hoc analysis with a Bonferroni adjustment. The Bonferroni post hoc test was

chosen over the Tukey post hoc test because of the variation in the number of samples,

as well as the small number of samples [171]. A value of p < 0.05 was considered

statistically significant.


3.4 Results

3.4.1 Influence of buffer and storage duration on RBC morphology

In this section, the effect of buffer composition and storage duration on RBC

shape was observed. The percentage of discocytes, echinocytes and stomatocytes

observed at different time-points during the study changed with the different buffers

used (Figure 3.1 presents the percentage of echinocytes and stomatocytes, Figure 3.2

presents cumulated results).

Figure 3.1: Proportion of echinocytes (a) and stomatocytes (b) observed after 20 minutes

incubation at RT, in cold-agglutinin-depleted FFP, SAGM and ‘artificial plasma’. Means and

standard deviation are represented (n=6 units for cold-agglutinin-depleted FFP and SAGM, n=4

for ‘artificial plasma’).

The number of echinocytes observed in cold-agglutinin-depleted FFP increased

with storage duration (p=0.0220), and very few stomatocytes could be observed. Of

all the RBCs resuspended in cold-agglutinin-depleted FFP, 66% presented an

echinocytic shape at day 2 and this percentage increased to 83% then 88% at day 9 and

day 16 respectively (Figure 3.1a). Between day 16 and day 42, no evolution was

measured in the percentage of echinocytes in cold-agglutinin-depleted FFP (p=0.7631)

and this percentage was stable at 90%. At any time, the percentage of stomatocytes in

cold-agglutinin-depleted FFP represented less than 2% of the RBCs observed, and

averaged at 0.5% over the study (Figure 3.1b).

In ‘artificial plasma’, cell shape changed with storage duration. Only 0.5% of

RBCs were echinocytes at day 2 and this percentage increased to 30% of the cells by

day 42 (p<0.0001). Stomatocytes represented 46% of the cells at day 2 and their

proportion decreases to 13% by day 42 (p=0.0066). There was no evolution in the

percentage of discocytes observed in ‘artificial plasma’ during the study (p=0.7153)


(Figure 3.2). By contrast to results found in SAGM, shape changes in cold-agglutinin-

depleted FFP and ‘artificial plasma’ were linked to storage duration, through an

increase of the proportion of echinocytes.

Figure 3.2: Evolution of shape repartition of echinocytes, stomatocytes and discocytes during

storage (20 min incubation at RT). Means are presented over 6 samples.

There was no significant evolution in the number of stomatocytes observed in

SAMG during storage (p=0.4312), and very few echinocytes were seen. Less than 5%

of the cells suspended in SAGM were echinocytes at any time, with an average of 2%

over the study (Figure 3.1a). The average of stomatocytes observed was 66% over the

study (Figure 3.2).

3.4.2 Irreversible echinocyte content

The percentage of echinocytes presenting an irreversible morphology was

measured. The definition of an irreversible shape was based on the definition from


Blasi et al. (2012) [111] and Berezina et al. (2002) [118] stating that ‘RBC assuming

spheroechinocyte, spherostomatocyte, spherocyte, ovalocyte, and degenerated shapes

are irreversibly changed cells’. Echinocytes were therefore considered having reached

an irreversible morphology when they presented the characteristics of late echinocytes

III with more than 20 spicules over their surface, or a spherical shape, or presented the

characteristics of spheroechinocytes [42]. Typical SEM images for cells obtained from

a fresh blood sample and from a single pRBC unit at day 3 and at day 42 and in

different buffers are presented in Figure 3.3. Percentages of echinocytes presenting an

irreversible morphology are presented in Figure 3.4.

Figure 3.3: SEM images of representative RBC morphologies (5000x) in PBS (a-c), in SAGM (d-

f) and in Krebs (g-i), and from fresh blood (a, d, g), day 3 (b, e, h) and day 42 samples (c, f, i).


For PBS and Krebs, there was a significant increase in the number of RBCs, with

an irreversible echinocytic morphology between fresh blood and day 42 and between

day 3 and day 42 (Figure 3.4). The percentage of echinocytes reported changed

strongly in function of the buffer they were fixed in: in Krebs, 35.91 % of all RBCs on

average are irreversibly transformed into echinocytes after 42 days of storage, whereas

only 2.66 % of cells in SAGM presented that morphology.

Figure 3.4: Percentages of echinocytes with an irreversible morphology in fresh blood

samples, after 3 and 42 days of storage, and when resuspended in either SAGM, PBS or Krebs.

Means and standard variation are presented. (* p < 0.05, **** p < 0.0001)

The optimised fixation protocol presented in this study indicated only 12.62 %

of all cells in PBS taking an irreversible echinocytic morphology. This indicates better

pRBC product quality after 42 days of storage than published results of 29 % to 39.5

% [111; 118].

3.4.3 Influence of temperature and incubation time on cell shape

Samples in SAGM and cold-agglutinin-depleted FFP were incubated either at

4°C or at RT, and then observed after either 20 minutes or 2 hours (Figure 3.5).

Percentage of echinocytes and stomatocytes for each of these conditions are shown in

the Figure 3.5, and statistical analysis results are presented in the Table 3.2 below. No

statistically significant effect of temperature or incubation time could be observed on

the percentages of stomatocytes in cold-agglutinin-depleted FFP or echinocytes in

SAGM. This is most likely due to the very limited number of cells with these

morphologies present in these buffers.

The percentage of stomatocytes after incubation in SAGM at 4ºC and for 2h, was

reduced compared to other conditions (p = 0.0004, Figure 3.5d). For the other


conditions, incubation time had no influence on cell shape; RBCs appear to have

reached an equilibrium state with their environment after 20 minutes.

Figure 3.5: Percentage of echinocytes (a-b) and stomatocytes (c-d) observed after 20 minutes (a,

c) or 2 hours (b, d) incubation. Means and standard deviation over 6 units are presented.

Temperature strongly affects the percentage of echinocytes in cold-agglutinin-

depleted FFP and the percentage of stomatocyte in SAGM after 2 hours incubation (p

< 0.0001).

Table 3.2: Impact of incubation time and temperature on RBC morphology

% Echinocytes Cold-agglutinin-

depleted FFP

SAGM

Temperature (4ºC vs RT) After 20 min p < 0.0001 p = 0.3619

After 2 hours p < 0.0001 p = 0.1017

Incubation time (20 min vs 2 h) At 4°C p = 0.4435 p = 0.3380

At RT p = 0.2292 p = 0.0773

% Stomatocytes Cold-agglutinin-

depleted FFP

SAGM

Temperature (4ºC vs RT) After 20 min p = 0.1188 p = 0.3975

After 2 hours p = 0.0550 p < 0.0001

Incubation time (20 min vs 2 h) At 4°C p = 0.4647 p = 0.0004

At RT p = 0.5377 p = 0.3913


3.4.4 Evolution of RBC volume during storage

RBC volume is usually measured during storage, as an indicator of

echinocytosis. Echinocytes are thought to have reduced internal volume when they

reach a sphero-echinocyte shape, as membrane surface area and internal volume are

lost through microparticle shedding [112]. Size and volume were estimated using two

different methods: cell diameter was measured on calibrated bright field images

(Figure 3.6), and cell volume was measured using an automated cell analyser using the

Coulter principle (Figure 3.7).

The apparent diameter was measured from bright field images. It decreased for

cells resuspended in plasma (p = 0.0002 and p = 0.0058 at 4C and RT respectively) as

well as cells resuspended in SAGM at 4°C (p = 0.0078) during the 42 days of the study

(Figure 3.6). Apparent diameter for RBCs incubated in SAGM at RT remained

constant (p = 0.9698).

Figure 3.6: Evolution of cell apparent diameters during 42 days of storage. Diameters were

measured on bright field images after a 20 minutes incubation. Means and standard deviation

over 6 units are presented (n=6).

The reduction in apparent diameter is due to the increased sphericity of

stomatocytes and echinocytes and an increase in their transverse diameter. It is difficult

to extrapolate 3D dimensions and quantify possible volume loss using these data,

which is why MVC measurements were realised using an automated cell analyser.

The volume measurements obtained using an automated cell counter were

obtained on samples extracted from the pRBC units, without dilution. Thus,


information such as haematocrit and total Hb concentration were also available. This

information was used to calculate the level of haemolysis (see Section 3.4.5). There is

a significant increase in MCV measurements during storage (p = 0.0004). A decrease

of cell internal volume was expected because of microparticle shedding towards the

end of the storage period. The automated cell analyser is a suitable method to analyse

fresh blood sample in a routine testing laboratory, but it may not be suitable to monitor

aging cell properties during storage [97; 137]. A new method of analysis is required to

characterise physical properties of stored RBC.

Figure 3.7: MCV measurement during 42 days of storage. Upper and lower physiological limits

are represented by horizontal dashed lines at 100 fL and 79.5 fL. Means and standard

deviations over 6 units are presented. (** p < 0.01, ***p < 0.001, n=6)

3.4.5 Evolution of cell haemolysis during cold storage

Haemolysis is an indicator of product quality and is linked to cell membrane

fragility. An indirect haemolysis measurement by titration of free Hb present in SAGM

supernatant was realised (Figure 3.8). Free Hb concentration in storage bags is linked

to the initial sample haematocrit and total Hb concentration. Free Hb values are

standardised using total Hb concentration to obtain the proportion of cell haemolysis

during storage [169]. In these samples, the average haemolysis increased between day

2 and day 50 (p= 0.0024) and reached 0.12% at day 50.


Figure 3.8: Percentage of haemolysis over 50 days of storage, means and standard variation are

represented. (* p < 0.05, *** p < 0.001, n=6)

3.5 Discussion

3.5.1 RBC shape is function of buffer over age

One objective of this study was to link cell shape with environment and to

measure recovery in a physiological environment. Buffer and storage duration are two

important factors influencing shape [72; 139] and were the first parameters studied.

The shape of RBCs resuspended in cold-agglutinin-depleted FFP and SAGM was

found to be independent from storage duration, but dependent on the buffer used.

The percentage of echinocytes in cold-agglutinin-depleted FFP was linked to the

altered properties of FFP, compared with fresh plasma [42]. Freezing or incubating

plasma for several hours at 4°C or at 37°C results in echinocytogenic properties of the

plasma, due to a degradation of the lipidic fraction [172].

As SAGM has hyperosmolar properties, it was expected to produce shrunken

cells (SAGM was designed to reduce pressure on the cell membrane to protect it during

storage) [98]; however, stomatocytes represented the majority of cells observed. The

swelling of the cells observed in this study is likely to be due to the membrane

increased osmotic fragility and reduced integrity when stored in SAGM [173]. It was

also reported that acidic pH promotes the appearance of swollen cells, as observed here

[98; 174]. Mannitol is used in SAGM to prevent haemolysis and counteract the osmotic

imbalance created by other components present in SAGM, such as potassium and

glucose, but its effect does not seem enough to prevent RBCs from swelling [97].


Effect of storage duration was visible for cells resuspended in ‘artificial plasma’,

where a link between the different shapes observed and the length of the storage period

could be established. Longer storage periods were associated with a reduction of the

percentage of stomatocytes and an increase in the percentage of echinocytes. Aging in

storage is linked to a shift toward the echinocytic morphology for cells in cold-

agglutinin-depleted FFP and ‘artificial plasma’. There was no evolution in the

percentage of discocytes observed in ‘artificial plasma’ indicating a continuous shift

between stomatocytic, discocytic and echinocytic morphologies: the cells that become

echinocytes are replaced in the discocytic fraction by cells that cannot assume the

stomatocytic morphology anymore in this environment.

The morphologies observed during experiments were a mix between discocytes

and either stomatocytes or echinocytes. This is explained by individual cell properties:

at donation time, cells just matured from reticulocyte stage (neocytes), cells close to

being removed from circulation (gerocytes) and any stage in between are all collected

in a single donation [175]. Some cells are already old at day 2 of storage, while some

cells will still be considered as ‘young’ even after 42 days in the fridge. This is why

RBC samples will have a range of shapes the cells take (grey areas in diagrams in

Figure 3.9).

Figure 3.9: Illustration of how buffer composition influences RBCs morphology range in SAGM

(a), ‘artificial plasma’ (b) and cold-agglutinin-depleted FFP (c).

Depending on the buffer they are resuspended in, this range of shapes are pushed

towards the extremes; either stomatocytes in SAGM or echinocytes in cold-agglutinin-

depleted FFP (Figure 3.9a, c), or balanced around the discocytic shape in ‘artificial

plasma’ (Figure 3.9b). This study suggests that even after a long period at 4°C and in

an artificial environment, cell shape change is still preserved: cells coming from the


same sample shift from their stomatocytic shape, when placed in SAGM, to being

echinocytes when placed in cold-agglutinin-depleted FFP.

RBC deformability is correlated with their sphericity index, thus, their shape.

Quantification of the percentage of echinocytes with an irreversible morphology

during storage was used as an indicator of pRBC product quality, with sample

haemolysis [111; 118]. Using an improved glutaraldehyde fixation protocol in this

study, fewer cells qualified as irreversible echinocytes, but the proportion changed

depending on the buffer used. Characterisation of shape irreversibility, based on

current cell morphology criteria, could be improved on by using clinically relevant

buffers. The irreversibility of a shape should not depend on the buffer the cells are

observed in. Suggestions are made for cell deformability to be measured as a quality

criterion on individual pRBC units, instead of RBC morphologies: deformability is

proposed to be a better indicator of RBC behaviour in circulation [19; 21; 145; 176].

New microvascular devices are being developed as new bed-side diagnosis tools to

assess stored RBCs’ ability to flow through a capillary network, to be used just before

transfusion [19; 21; 145; 176]. These devices would give good predictions of sample

resistance to shear forces, and of the number of cells being removed from circulation

after transfusion.

3.5.2 RBC shape is sensitive to temperature, not incubation time

Influences of incubation time and temperature on cell morphology were two

other parameters investigated. Storage was reported to affect active membrane

mechanisms such as membrane transports due to the depletion in ATP [104]. Ionic

exchange slows down during storage [177], and longer incubations were tried here to

verify that an equilibrium state was reached before imaging the cells. No significant

differences could be observed between cells incubated for only 20 minutes and cells

resuspended for 2 hours before imaging, except for 2h incubation in SAGM at 4°C,

where the percentage of stomatocytes observed was lower than in other conditions.

The shorter incubation time of 20 minutes was enough for the cells to equilibrate with

their environment.

Lower temperatures resulted in smaller numbers of echinocytes in cold-

agglutinin-depleted FFP and stomatocytes in SAGM. Temperature alters the

conformation of membrane structural proteins and spectrin has been shown to fold and

shorten at lower temperature [57; 178]. Shorter spectrin molecules would condense the


cytoskeleton network and this is hypothesised to produce echinocytes [57; 178]. An

opposite shape transformation was observed in this study. One possible explanation is

that the slowdown of metabolism during cold storage will increase the time required

for the cell to change shape. Lower temperature reduces the number of both

echinocytes and stomatocytes for these conditions. It may take more than 20 minutes

for the temperature to affect protein structure in SAGM, which could explain why

short incubations at 4°C did not result in lower stomatocyte count.

3.5.3 Haemolysis stays low during storage

Haemolysis values in this study were below 0.2% at any time point, and largely

under the thresholds of 0.8% and 1% recommended by the European Committee on

Blood Transfusion and the Food and Drug Administration (FDA) respectively [100].

These values are also below other reported measurements collected from units also

stored in SAGM, which record a maximum haemolysis level below 0.4% by day 42 of

storage [111; 174]. On Figure 3.8, the standard deviation shows a large sample

variability, due to donor variation. RBCs from different donors do not react similarly

to storage conditions [179].

Results presented in this chapter indicate that pRBCs units tested 42 days of cold

storage meet quality requirements established by regulatory authorities: both the

European Medicine Agency (EMA) and the FDA recommend that at least 75% of

transfused RBCs stay in circulation for 24 hours after transfusion [179; 180].

3.5.4 Limitations of current volume measurement techniques

Bright field imaging and automated cell analysis were demonstrated to be

unsuitable methods to determine internal volume variation during storage. MCV

results contradicted the established idea of internal volume reduction during aging in

storage [181]. One explanation for the apparent volume increase could be linked to the

way the cell analyser works: cells in a concentrated sample are sucked through the

analyser and diluted in a sheath flow to enable single cell measurements. Data shown

in Figure 3.2 prove how sensitive RBCs are to their environment, and limited

information is available on the fluidics solutions inside the analyser. This buffer

composition and its ionic strength could be at the origin of cell swelling. Another

aspect to consider is the Coulter principle used in the automated cell analyser [182]:

every cell crossing the counter orifice creates a resistance in the voltage between two


electrodes. It is possible that the electric properties of the aging RBC membrane

influenced the results here, and not cell volume. The automated cell analyser may not

be appropriate to record changes happening to RBCs when aging and in storage

condition with high haematocrit. On the other hand, it has been reported that RBC

volume is stable during storage [78]. The overall increased sphericity in that case could

be a combination of decreased surface area due to microparticle shedding and variation

in internal volume. In order to more accurately quantify membrane surface loss and

volume variation, a new method based on confocal imaging will be developed and

presented in the following chapter.

3.6 Conclusion

All units tested during this study met blood authorities’ recommendations

regarding the quality of RBC products for clinical use. The percentage of echinocytes

with an irreversible morphology that will get cleared in circulation was very low and

haemolysis was below 0.8%. Contrary to expectations, storage duration did not appear

to be the main factor influencing RBC shape. The cell environment, principally the

buffer composition, had a greater impact on cellular morphology. Understanding the

buffer effect on cell shape helps characterise the reversibility of the shape and give a

better estimate of product quality.

The number of echinocytes with irreversible morphological changes found

during this study was less than 5% at any time, and very few of these cells were sphero-

echinocytes (stomatocytes were always reversible). This is less alarming than previous

studies reporting up to 39% of irreversible echinocytes after 42 days of storage [111].

It is important to note that SEM imaging in previous studies was performed after fixing

the samples using 2.5% glutaraldehyde in PBS for 1h [111]: high concentrations of

glutaraldehyde and PBS have been shown to produce echinocytes [144]. This

demonstrates again the importance of using the correct buffer, or understanding the

effect of the buffer used when studying RBC shape changes. The reduced number of

echinocytes in the present study could be linked to improved storage practices in the

past decade, or sample preparation protocols tested here.

There are several limitations to this study. Firstly SAGM may have a dilution

effect on RBC shapes, and morphology may depend on haematocrit (Institut National


de la Transfusion Sanguine, personal communications, June 23rd 2017). Cold-

agglutinin-depleted FFP demonstrated an echinocytic effect on RBCs due to its

production process and because its influence on cell shape is so strong, it could mask

other shape change effects. Finally, the ‘artificial plasma’ buffer cannot reproduce all

the aspects of plasma, and its use as a prediction model for cell shape after transfusion

is limited. However, ‘artificial plasma’ was useful here to preserve the discocytic

morphology and showed that cell shape results from a balance between cell age and

the environment. Based on the results presented here, an ideal buffer to study RBC

morphology should have a composition close to the physiological environment, with

a high protein content. Although BSA is acknowledged to protect the discocytic shape

in most buffers, it was not used in all experiments presented in the following chapters

to avoid unwanted interactions with some chemicals. Glutaraldehyde, for example,

crosslinks proteins and transforms buffers containing BSA into a gel-like substance

within seconds [183]. SAGM was not considered as a suitable buffer for most

experiments, especially mechanical testing protocols, due to the increased fragility of

the cell membrane it creates.

The echinocytic transformation has been at the origin of numerous research

publications on RBC shape for the past 50 years, with no consensus reached on its

mechanisms. In the early 1970s, Brecher and Bessis came to the conclusion that

experimental observation conditions, such as the use of glass coverslips, could be the

source of the echinocytes they observed, and so, it would be difficult to separate

morphologies resulting from a pathological condition or aging, from experimental

artefacts [72]. This study tends to confirm this conclusion. It is clear that RBC

morphological studies during aging should focus on the percentage of echinocytes with

an irreversible morphology, rather than on the general number of echinocytes in a

given environment.

Indirect methods to characterise internal cell volume may have bias coming from

sampling buffer or their mechanical principle. In the next chapter, a new method to

characterise cell shape, volume and surface area using a reconstituted 3D mesh, will

be presented.

Chapter 4:Physical characterisation of the echinocytic transformation 51

Chapter 4: Physical characterisation of the

echinocytic transformation

In the previous chapter, it was shown that storage was associated with an

echinocytic shift in cold-agglutinin-depleted FFP and ‘artificial plasma’. This shape

transformation is not fully understood yet [83], and physical properties of echinocytes

have not been characterised before. In this chapter, a novel method to measure RBC

surface area and volume is presented, which uses confocal imaging and image analysis.

By monitoring physical properties of RBCs as they transform from discocytes to

echinocytes, insights on the mechanisms behind the shape transformation can be

obtained.

4.1 Introduction

Mechanisms behind RBC shape transformation are still not fully understood.

Hypotheses that include the bilayer couple hypothesis [77], cytoskeleton and lipid

bilayer reorganisation [151], and proteins conformation shift were formed, but no

consensus has been reached yet. Moreover, a limited number of studies report physical

properties of the different RBC shapes, and most of the data available is dedicated to

discocytes, limiting the understanding that could be gained by comparing internal

volume evolution or spicule appearance on echinocytes, for example.

It was shown in the previous chapter that buffer influences RBC shape. Direct

characterisation of cell physical properties, such as their volume or surface area, is

made difficult because the buffer composition affects the results. In the case of

automated cell analyser measurements, the property monitored during storage is

volume variation or membrane dielectric charge evolution [184]. It is challenging to

separate the actual volume variation, from density and surface area loss associated with

extended storage periods. Thus, the different methods used to assess changes in RBC

volume result in contradictory findings, reporting increase [103; 185-187], decrease

[26; 188; 189] or no evolution [78-80] of internal volume during storage. These

measurements do not account for the shape of the cells, but usually propose population

average.

52 Chapter 4:Physical characterisation of the echinocytic transformation

Given the importance of understanding the link between cell shape and their

membrane properties in aging and illness, there is a need for descriptive data for each

of the RBC morphology observed in storage. This study focused on producing

calibrated 3D representations of RBCs at different stages of the echinocytic

transformation, using confocal imaging.

Direct imaging methods, such as bright field microscopy and SEM were used in

an attempt to produce RBC quantitative measurements, with limited success. Bright

field microscopy has originally been used to study cellular morphology, by

extrapolating 3D shapes from 2D images [142; 190]. The manual image analysis

process and the different equations used to calculate a typical RBC internal volume in

these studies gave wide variations in results, with expected discocyte volume varying

between 84 and 130 fL. These studies also reported the large influence that buffer

composition has on cell morphology and internal volume, and concentrated on

discocytic and stomatocytic morphologies [142]. Recent advances in SEM have

generated very high resolution images of the RBC surface and were able to describe

shape evolution during storage [111; 118]. Extension to 3D imaging is now possible

using rotating SEM stages, however, the images produced are incomplete due to the

presence of a substrate under the sample [191]. Complex image analysis procedures

are required to assemble the final 3D reconstructed image. Sample treatment for SEM

is also time consuming, and can produce imaging artefacts [143; 192]. Accurate

volume measurements for single RBCs are not available at this time from SEM studies.

Confocal imaging has successfully been applied to cell shape assessment, up to

the internal organelle organisation [193]. It has advantages of requiring limited sample

treatment and can be applied to live cells. Image resolution is far lower than for SEM

imaging, but it is possible to individually label and image internal content, enabling

in-depth characterisation of the sample. This method has been reported for discocytes,

and volume measurement was trialled, but with large uncertainties due to the image

analysis protocol [137]. Another advantage of confocal imaging is that buffers are

easily replaced during sample preparation to suit experiments, and in the case of RBCs,

to produce morphologies of interest.

In this study, a series of experiments on RBC morphology is presented, and the

resulting physical characteristics extracted from confocal images of RBCs, such as

internal volume and surface area. RBCs were imaged following a single step staining


protocol, followed by fixation using glutaraldehyde. An advantage of the proposed

method is that the results link shape and quantitative measurements, as dimensions

were calibrated using fluorescent beads.

Future use of results produced by this method are the calibration or validation of

numerical RBC models using accurate 3D meshes produced by image analysis. RBC

numerical models have been developed based on simplified assumptions to predict and

understand the RBC membrane mechanisms and its age or in sickness [194-196], but

morphological transformations are currently limited to modelling different

morphologies using fixed referenced shapes as a target.

4.2 Aims

This study aimed to:

- Establish a calibrated imaging method of the RBC membrane,

- Characterise physical properties of discocytes and echinocytes,

- Produce 3D meshes representing cell surface and easily used in numerical

models.

4.3 Materials and methods


Refer to Section 3.3.1.

4.3.2 RBC samples


4.3.3 Methods

Fresh blood was centrifuged and supernatant and buffy coat were discarded.

RBCs were washed and stained with 1,1'-dioctadecyl-3,3,3'3'-

tetramethylindocarbocyanine perchlorate (DiI, 1uL/1x106 cell) for 2 min at 37°C

(Thermo Fisher Scientific, Scoresby, Australia) in 200 µL of SAGM (MacoPharma),

Krebs (Sigma-Aldrich) or 2X PBS (Lonza). After staining, the cells were fixed by

progressively adding a 2% glutaraldehyde solution until a final volume of 400 µL was


reached. RBCs were incubated with glutaraldehyde for 30 min, in the dark. The

different buffers (SAGM, PBS, Krebs and 2X PBS) were used to produce a range of

shapes from stomatocytes to echinocytes. These buffers were used during the staining

and fixation step. Buffers such as cold-agglutinin-depleted FFP and ‘artificial plasma’

presented in the previous chapter, were not used in this protocol as BSA interferes with

DiI staining. After fixation, the cells were resuspended in buffers containing 50%

glycerol (Merck Millipore, Frenchs Forest, Australia) for imaging. Imaging chambers

were constructed using two coverslips spaced by double-sided tape. Confocal

fluorescence microscopy was performed using a Leica TCS SP5 microscope (63x

1.4NA oil) and image acquisition was realised using Leica Application Suite software

(Leica, Wetzlar, Germany). Size calibration was realised using TetraSpeck fluorescent

beads (Thermo Fisher Scientific, lot 1884299). Image analysis was realised using

Matlab (Mathworks, Natick, USA) and a mesh of the cell surface was realised in

Meshlab (Visual Computing Lab, Pisa, Italy) following the process described in

Section 4.3.6.

4.3.4 System optimisation

The imaging protocol was optimised to obtain high quality data, by mounting

the cells in a high refractive index and optimising acquisition parameters [197].

Spherical aberration results in a decrease in image intensity when the imaging

plan gets further away from the coverslip. It is caused by difference in refractive

indices between the different components present over the beam pathway. In order to

reduce spherical aberration, the cells were fixed in glutaraldehyde after staining so

they could be resuspended in a medium with a high glycerol content and maintain their

shape. Glycerol increases the reflective index of the medium, bringing it closer to the

reflective indices of the coverslip and the immersion oil.

Acquisition parameters were first chosen using the system optimisation function,

then adjusted. The z-axis step size was chosen as close as possible to the lateral

resolution to avoid under- or over-sampling [198]: voxel size on the x and y axes was

0.060 µm, the z-step was chosen at 0.084 µm. The pinhole was reduced to 50 µm to

increase resolution and reduce out-of-focus light [199]. A 2-step line averaging was

selected during scanning to remove noise.


4.3.5 Voxel calibration

Calibration beads were used to obtain accurate voxel size. The x and y axes

belong to the focal plane and voxel size on this plane defines lateral image resolution.

Axial resolution is defined by the voxel size on the z axis and is used during image

stacking to produce 3D volumes.

Voxel size on the xy plane was calculated first, using a circle fitting function on

the largest section of the stack. The number of voxels composing the horizontal x and

y axes were extracted [200]. Then, an ellipsoid fitting function was applied over the

whole stack to obtain the number of voxels making the vertical z axis [201]. The data

produced by confocal imaging and the extrapolated bead obtained from it can be seen

in Figure 4.1.Calibration beads have a certified diameter of 4 µm ± 0.14 µm, it was

then possible to calculate voxel dimensions and calibrate the three axes. Calibration

beads were added to each sample to account for set up variation: slight variations in

medium composition or distance between the two coverslips affect the beam path and

impact on the calibration measurements.

Figure 4.1: Extraction of voxel size, using surface reconstruction of calibration beads. The

ellipsoid fitting step was used to calculate the z diameter of the calibration beads. The blue dots

represent the point cloud extracted from confocal images and the grey sphere represents the

fitted ellipsoid over that section.

4.3.6 Image processing

After calibrating voxel size, the data obtained from RBCs were analysed and

measurements extracted. Images from a stack were loaded into Matlab and each image

was processed individually. The edges of the cell were visible due to the high intensity


of the fluorescent dye included in the lipid bilayer. First, background noise was

cleaned. The original images (Figure 4.2a) were converted into binary images using

Otsu’s thresholding method (Figure 4.2b). An image inversion and an opening

function were used to remove background noise. The results of this first cleaning step

can be seen in Figure 4.2c, where noise initially present around the cell was erased

(see top right corner of Figure 4.2c).

Figure 4.2: Image processing steps, from confocal stack images to membrane contours. The

original black and white image (a) was first inverted (b) to remove background noise (c) then

filled (d). The edges of the cell were then be selected (e) to be used to create the point cloud (f).

The whole stack was cleaned of background noise following this process, before

a 3D filling function removed any internal holes missed by the thresholding step

(Figure 4.2d). The 3D filling function preserves information regarding complex

folding patterns of the membrane, whereas a 2D filling function would erase them (see

Figure 4.3 for more details). This was especially relevant for concavities in discocytes

and stomatocytes, as well as preserving spicules originating from out-of-plane sections

in echinocytes.


Figure 4.3: Comparison of results obtained from 2D and 3D filling functions. Side view

schematics of a cell imaged by confocal (a) and the corresponding confocal image (b). A 2D

filling function would fill in the space corresponding to external medium present in the

concavity of the cell (c), while a 3D filling function preserves this information (d).

Next, the edges of the cell, corresponding to the RBC membrane, were isolated

and smoothed (Figure 4.2e). A number of point coordinates were selected at equally

spaced intervals around the edges (Figure 4.2f), forming a single layer of the point

cloud. By assembling all the layers extracted from the stack, a 3D point cloud

representing the surface of the cell was extracted (Figure 4.4). All dimensions were

then converted from voxel to micrometres using voxel size values obtained from the

calibration beads.

Figure 4.4: Point cloud representing the surface of a discocyte

In order to link the different slices of the stack, a homogeneous mesh was

reconstituted over the point cloud to create the cell surface. The 3D matrix containing

the point cloud coordinates was opened in Meshlab (Figure 4.5a). The normals were

computed for each point in the cloud (Figure 4.5b), taking into account the nearest 20


neighbour points. Then, surface reconstruction was realised using the screened Poisson

surface reconstruction tool with a reconstruction depth of 8 [202; 203]. The set of

parameters was established to have the closest fit between the newly created surface

and the original point cloud (Figure 4.5c with normal apparent and Figure 4.5d,

without). The surface reconstructed using this function created a pure triangulated

mesh, where each face was composed of three vertices linked together. This surface

was then smoothed while preserving the normals’ orientation (Figure 4.5e), and

simplified so it only contained 4,000 faces (Figure 4.5f). To verify the accuracy of the

surface reconstruction, the distance between the layer of points from the point cloud

and the reconstructed surface was visualised (see Section 4.4.2).

Figure 4.5: Cell surface reconstruction process, from the point cloud to the triangulated mesh.

From the point cloud extracted from the original stack image (a), normals are computed (b) to

enable surface reconstruction (c and d) in Meshlab. The surface, made of a pure triangulated

mesh, is then smoothed (e) and simplified (f) before being exported.

The mesh coordinates and connectivity were imported into Matlab to calculate

the cell’s internal volume and surface area. Other parameters are also easily accessed,

such as the number of spikes on echinocytes and their dimensions. Total surface area

was calculated from summing the areas of the individual triangles that formed the


mesh. Volume was calculated by projecting the triangles onto the xy plane and then

multiplying the projected area by the average height of the vertices in the z-direction.

To account for the directional sense in these calculations, the cross-product for each

triangle was an outward pointing normal vector. The code calculating volume and

surface area was developed by Sarah Barns, in her numerical model, and applied to the

experimental data in this study.

Figure 4.6: 3D reconstruction of a discocyte membrane, visualised in Matlab

4.3.7 Statistical analysis

Comparison of surface area and volume between discocytes and the different

echinocytic morphologies was realised using a one-way ANOVA.

4.4 Results

4.4.1 Calibration of voxel size

The calibrated voxel size for three samples can be found in Table 4.1 below. The

error on the xy plane voxels were small, ranging from 5% to 12% in the samples tested

here. The voxels were slightly smaller on these axes than was expected, from looking

at the system values. Lateral resolution was comprised between 0.0528 µm and 0.0567

µm per voxel, instead of the 0.060 µm predicted by the system. Difference between

the system-predicted axial resolution and its calculated value was larger and reached

up to 30% with these samples. Voxel size on the z axis was calculated to range from

0.0591 µm to 0.0683 µm, which was smaller than the expected 0.084 µm. Calibration

values differed between samples, highlighting the need for individual sample

calibration.


A similar calibration method using fluorescent beads was found in the literature

and demonstrated a larger distortion on the z axis, finding an error of 8.7% for voxel

size in that dimension [198]. The error found in this study is smaller than the error

calculated here, most likely because of the different specimen preparation protocols:

tissue samples were mounted in a gelatine-mounting medium and not glycerol. Error

on the z axis is always expected to be higher than error on the xy plane due to spherical

aberration.

Table 4.1: Confocal voxel calibration values

Krebs (n=8 beads) PBS (n=3 beads) PBS 2X (n=3 beads)

x and y

axes z axis

x and y

axes z axis

x and y

axes z axis

Extracted

bead radius

35.24 ±

0.22 voxels

33.84 ±

0.46 voxels

37.86 ±

1.50 voxels

29.28 ±

0.17 voxels

35.43 ±

0.11 voxels

30.19 ±

0.40 voxels

Theoretical

voxel size 0.06 µm 0.084 µm 0.06 µm 0.084 µm 0.06 µm 0.084 µm

Calculated

voxel size 0.0567 µm 0.0591 µm 0.0528 µm 0.0683 µm 0.0564 µm 0.0662 µm

Percentage

of error 5.42 % 29.65 % 11.96 % 18.68 % 5.92 % 21.13 %

4.4.2 Validation of mesh accuracy

To validate the Poisson surface reconstruction accuracy over the point cloud, a

quality function representing the distance between the surface and the point cloud was

applied. Distance between the two layers is colour coded and can be seen in Figure

4.7: areas in blue represent the sections where the reconstructed surface matches the

point cloud, whereas areas in red represent sections where the reconstructed surface is

further away from the point cloud.


Figure 4.7: Visual representation of surface reconstruction quality of a discocyte (a) and an

echinocyte (b) (colour scale going from high accuracy sections in blue to lower accuracy in red)

The most inaccurate sections are localised at the end of the spicules on the

echinocyte (Figure 4.7b). On these areas, the point clouds stopped before reaching the

tip of the spicules and the Poisson surface reconstruction function had to extrapolate

the position of the membrane. The resulting surface was further away from the point

cloud, and coded in red. On the discocyte, it can be seen that red areas often correspond

to the location of vertices, suggesting that smoothing created some distance between

the two layers here. The red sections may then not be correlated with a low quality of

the surface reconstruction, but rather to a reduction of the individual variation between

data points and averaging of the surface over the whole cell. Moreover, red and blue

sections are alternating over the cell surface, reinforcing this hypothesis. The surface

reconstruction realised using Meshlab produced accurate meshes over the point clouds.

4.4.3 RBC volume and surface area

The 3D meshes obtained from confocal images were used to extract volume and

surface area properties of different RBC morphologies. Table 4.2 below summarises

these properties for discocytic and echinocytic morphologies: this study covered the

chemically induced transformation from discocyte to echinocyte III. All values

presented here were obtained from the same blood sample, to facilitate comparison

and remove inter-donor variability. Bessis’ classification was used to define the

different morphologies [64]. A discocyte corresponds to a ‘normal biconcave red cell’,

an echinocyte I to an ‘irregularly contoured red cell’, an echinocyte II to a ‘flat red cell

with spicules’ and finally an echinocyte III to ‘an ovoid or spherical cell with 30 to 50

spicules evenly distributed over its surface’. Images from representative meshes can

be seen in Figure 4.8.

Table 4.2: Surface area and volume measurements for four different RBC morphologies


Discocyte

(n=5 cells)

Echinocyte I

(n=5 cells)

Echinocyte II

(n=5 cells)

Echinocyte III

(n=5 cells)

Surface area

(µm2) 139.45 ± 14.28 145.24 ± 13.65 146.93 ± 15.53 132.09 ± 10.65

Volume (fL) 96.29 ± 11.12 94.52 ± 12.57 99.49 ± 8.47 92.47 ± 6.08

No surface area modifications were expected as the cells got further away from

their normal discocyte shape in this study, as shape transformation was chemically

induced using buffer composition on RBCs from fresh blood samples. The main way

for RBC to shed some excess membrane surface is through microvesiculation and this

process is associated with aging and the storage lesion [114]. Results confirm this

hypothesis, as surface area remained stable at 140.93 ± 14.83 µm2 (p=0.3389). This

value matches previous studies, which reported surface area measurements between

135 µm2 and 145 µm2 [141; 142; 204; 205].

No volume changes were observed between the four morphologies (p=0.7186)

and the average volume calculated here over the four morphologies was 95.69 ± 10.21

fL. The same blood sample was analysed using an automated cell counter and a volume

of 92.4 fL was reported using this method, the variation in volume measurement

between the automated method and the 3D reconstruction method is less than 4%. The

3D surface reconstruction method using confocal images was shown to be accurate to

produce volume and surface area measurements.


Figure 4.8: Surface reconstruction for a discocyte (a, b), an echinocyte I (d, e), an echinocyte II

(g, h) and an echinocyte III (j, k) and the corresponding initial confocal data used to generate

them (c, f, i, l).

4.4.4 Shape change model validation

Meshes representing the different stages of the echinocytic transformation were

used for comparison with a numerical shape change model. This model, created by

Nadeeshani Maheshika Geekiyanage, PhD student in the same research group,

predicted the various RBC morphologies (Figure 4.9), but information such as number

of spicules and their repartition over the cell surface, or their radius of curvature

obtained from confocal images, will be useful to further calibrate it. This numerical

model is used to isolate the membrane components responsible for RBC shape

changes, and explain the mechanisms behind echinocytosis.


Figure 4.9: Numerical model predictions for the 3D morphologies of a discocyte (a), an

echinocyte I (b) and an echinocyte III (c)

4.5 Discussion

The echinocytic transformation is often hypothesised to be linked to RBC

volume reduction [146]. However, there were no significant volume differences

between the four morphologies measured in this study. The absence of volume

variation observed between discocytes and echinocytes agrees with previous studies

reporting that echinocytosis, when induced by modifying the cells’ environment, was

not directly related to internal volume reduction [206-208]. Environment-associated

echinocytosis is explained by protein conformation inside the membrane and lipid

repartition in the bilayer, whereas a change in cytoskeletal organisation seems more

likely for age-related echinocytosis [87]. It is necessary when studying the

echinocytosis process to mention whether the shape change phenomenon is related to

the cells’ environment or to their age and storage condition. Very few measurements

are available for echinocyte populations, especially for in vitro aging, and comparison

of current results with previously reported values is difficult.

The accuracy of the surface reconstruction is limited by the quality of the

biological data. Improvements to the current data acquisition protocol, and reduction

of the fluorescence halo from out-of-focus sections of the membrane, could lead to

enhanced reconstitution, especially for echinocytes; with the current method, spicules

that are close together are difficult to dissociate and sections of the membrane end up

being ‘merged’ together by the image analysis process. This results in spicules looking

rounder and shorter than in the original confocal image (Figure 4.8h, l). This averaging


of the surface did not seem to affect measurements in this study, but improved 3D

reconstructed cells will enable observation of volume modification at a smaller scale.

This surface reconstruction method proposed in this chapter still require a lot of

manual handling of the data and the use of different computer software. A larger

number of meshes and more accurate results could be obtained by developing an

automated analysis process.

4.6 Conclusion

Calibrated confocal imaging was shown to produce accurate 3D reconstitution

of the RBC surface for different morphologies. The results presented here demonstrate

the suitability of confocal imaging to study cell morphology and extract quantitative

measurements from confocal data. Future work could extend the study to other

clinically relevant RBC shapes, such as stomatocytes. Characterisation of aging cell

properties would be also possible by monitoring the cells during the 42 days of

standard storage. One main finding coming from these measurements confirms that

chemically induced echinocytosis is not associated with an internal volume reduction.

Meshes representing the cell surface can be used for validating shape change models.

Recording physical characteristics of stored cells has the potential to be helpful in

confirming the existence of different echinocytosis pathways.

The protocol presented in this chapter used RBCs fixed with glutaraldehyde,

which is known to alter RBC shape. Effects of glutaraldehyde on cell shape were

mitigated by using optimal chemical concentration, incubation time, and mixing rate

[144], and finally checking the fixed cell morphology against a control sample. The

fixation step was required here to preserve cell shape and membrane integrity when

resuspended into a buffer with high glycerol content. The current protocol could be

improved by removing this fixation step and imaging live cells: glycerol is not required

to ensure limited imaging aberration as quantitative measurements are all calibrated

using fluorescent beads. Live cell imaging could extend this study to monitoring

changes related to modifications to their environment. This method could track

modifications to RBC morphology happening in the few minutes following medium

or temperature changes.

Mechanical testing comparing discocytes and echinocytes may not record the

same effect whether they are studying echinocytes produced by their environment or


by aging during storage. The optical tweezers mechanical study presented in Chapter

6 will focus on characterising the membrane deformability of echinocytes appearing

during cold storage.

Chapter 5:Study of local membrane properties using AFM 67

Chapter 5: Study of local membrane properties

using AFM

The changes in RBC shape during storage are thought to be associated with a

modification of their membrane structure [109; 110]. AFM indentation has been shown

to differentiate between healthy and dysfunctional RBCs, by extracting their

membrane mechanical properties [209-215]. However, many limitations were

highlighted regarding current sample preparation protocols and data analysis [153;

216]. This chapter presents a novel experimental protocol for RBC indentation using

spherical probes. An improved analysis model was used to extract quantitative values

of the RBC membrane Young’s modulus.

5.1 Introduction

As RBCs age, they accumulate damage to some of their structural components,

especially to the layer of cytoskeleton tethered beneath the lipid bilayer. The

degradation of the structural components of the membrane leads to reduced

deformability and elasticity, and could be associated with a higher clearance rate of

transfused RBCs by the liver [14; 19]. Understanding what parts of the RBC are

affected the most by standard storage protocols could contribute to the development

of better processing practices and increased product quality. Mechanical testing has

been used on RBCs with this objective before, with a large range of techniques looking

at different properties of the membrane, such as AFM, micropipette aspiration,

ektacytometry, microfluidic devices or optical tweezers.

In this chapter local elasticity behaviour was measured using AFM. AFM is used

to test and compare mechanical properties of the samples studied. It has successfully

been used on RBCs and demonstrated the modifications in membrane elasticity for

cells from patients with haematological disorders. It is now being investigated as a

potential diagnosis tool for diseases such as diabetes [209-215]. AFM experiments aim

to isolate the role of each membrane component to the cell mechanical properties: the

lipid bilayer is usually associated with bending resistance, while the cytoskeleton gives

the membrane its elasticity. AFM applies a force onto a sample via a cantilevered probe

68 Chapter 5:Study of local membrane properties using AFM

while displacement is measured [149; 210; 217-219]. A schematic representation of

the AFM principle can be found in Figure 5.1. The force-deformation curves obtained

by AFM indentation experiments describe the deformability behaviour of the cell

membrane and can be further used in the calibration and validation of a numerical

model associated with this PhD project. The model will then be able to identify the

role of each membrane component in the RBC membrane deformability.

Figure 5.1: Principle of AFM imaging and indentation. Probe position is given by the deflection

of a laser beam on the tip of the cantilever. Knowing the force applied during indentation, force-

deformation curve can be obtained.

A major advantage of using AFM over other experimental methods is that force

and deformation is measured at greater resolution. Deformation is detected by a sensor,

which measures the deflection of a laser beam reflected off the cantilever’s end at far

greater accuracy than estimating deformation distances from optical microscope

images (Figure 5.1). Force is correlated against the deformation measurement using

the stiffness properties of the cantilever. AFM also provides control over the

indentation point, meaning that force acting on the membrane is quantified locally.

Finally, AFM is performed while cells are submerged in liquid, meaning the cells are

studied in a physiological environment [212].

Probe shape is an important consideration, with most AFM studies of RBCs

using conical and pyramidal tips [29; 149; 210-212; 217]. These sharp tips push the

membrane beyond physiological limits leading to penetration and rupture. They also

tend to catch and pull the cell membrane with them as they progress forward, resulting

in large membrane deformation and inaccurate height measurements. Indentation with


sharp tips can also trigger a reorganisation of the cytoskeleton to alleviate the local

stress and disrupt lipid organisation between the two leaflets of the bilayer, with

consequences as visible as a transition between echinocytic and discocytic shapes

[151]. This may be a contributing factor to the hundredfold variation in effective

Young’s modulus of the RBC membrane reported by various studies using sharp tips

[29; 149; 210-212; 217]. In order to observe the behaviour of the membrane within

physiological limits, spherical indenters can be used [150; 215]. Their smoothness

reduces the potential for penetration, rupture and non-physiological localised strains.

In this study, spherical probes with a diameter of 5 µm were chosen to balance tip

height and contact area diameter: with small beads, the top of the cantilever was likely

to touch the cell membrane during indentation around the edges of the cell, while large

beads would have inaccurate indentation positioning. It was reported that probe

diameter had very limited impact on the extracted effective Young’s modulus, and

indentation made with probes of different diameter should have comparable results

[220].

The Hertz model equation for the deformation of elastic materials has been

widely used for analysing experimental RBC force-indentation data in order to

estimate the stiffness of the membrane [29; 149; 210-212; 215; 217]. This method of

analysis has gained popularity in recent times, likely due to its simplicity, which

enables this standard equation to be routinely fitted to the experimental curves to

extract an effective Young’s modulus of the RBC membrane [149; 210; 217].

However, the trade-off of this analysis is that there are significant limitations in

reasoning the assumptions of solid mechanics contact for biological samples [221]: the

Hertz model equation is valid for semi-spherical solids with linear elasticity and

infinite thickness and most of these assumptions are not verified in RBCs’ indentation.

In order to improve on current Young’s modulus estimates, a modified Hertz model

equation by Dimitriadis et al. [222] was used. This model includes thickness samples,

and, while still limited in its assumptions, is more suitable for biological sample

indentation. It should still be emphasised that the effective Young’s modulus is only a

qualitative estimate of the membrane’s stiffness, due to the assumption of the model.

A significant challenge of applying AFM to RBCs is preserving the elasticity of

the membrane during imaging and indentation, while protecting its natural

organisation [211; 217]. The cells need to be immobilised during imaging, while


preserving their shape and membrane properties. Poly-lysine is a chemical typically

used for this purpose, which causes bonding between the substrate and negative

charges of the membrane surface proteins; however it can also cause membrane

tension [153; 223]: the concentration of poly-D-lysine required for sufficient adhesion

means that some cells start spreading on the substrate, which in certain cases leads to

membrane rupture due to increased lateral tension [224]. To balance adhesion strength

against preservation of the membrane’s natural state, the adhesion protocol was to be

carefully considered. A preliminary optimisation study was used here to select the best

parameters for AFM indentation of RBCs immobilised on a poly-D-lysine coated

substrate. In order to prevent cells from spreading once adhered, glutaraldehyde was

used. Glutaraldehyde is a non-specific cross-linker that stabilises the membrane by

binding proteins from the cytoskeleton and the lipids from the bilayer together [224].

It is commonly used for fixation before RBC AFM experiments, due to the very high

deformability of the membrane and the experimental difficulties it causes when

spreading [211; 217]. Therefore, following incubation with poly-D-lysine, the cells

were lightly fixed using this chemical.

This study focused on generating a mechanical properties’ estimate of the RBC

membrane, using low strain probe indentation with an optimised samples preparation

protocol. The new experimental AFM indentation protocol was used to accurately

measure RBC force-deformation behaviour, while protecting the membrane

organisation. The effective Young’s modulus obtained here was an improved estimate

to the cell elasticity properties, as the model used to extract it took into account

physical properties of biological samples, such as limited thickness. This study was

the first to apply spherical indentation and a Hertz modified equation for finite

thickness samples to RBCs.

5.2 Aims

This chapter aimed to:

- Establish the validity of the use of a spherical probe for imaging and

indenting RBCs,

- Propose an optimised sample preparation protocol that balances sample

immobilisation and membrane organisation,


- Improve current numerical results of estimated RBC membrane Young’s

modulus by using an improved, Hertz-based model more adapted to

biological samples.

5.3 Materials and Methods



5.3.2 RBC samples


5.3.3 AFM Probes preparation

Spherical indenters were assembled using Hydra2R-100NG tipless cantilevers

(AppNano, Mountain View, USA) and melamine beads (Sigma-Aldrich). A bead was

attached to the tip of the cantilever using a two-part epoxy glue. Placement of the bead

was controlled using the AFM piezo electric manipulator.

5.3.4 Adhesion to Substrate

Poly-D-lysine coated substrate was prepared by incubating the Petri dishes (TPP,

Trasadingen, Switzerland) with poly-D-lysine (from 1µg/mL to 1 mg/mL, Sigma-

Aldrich) in PBS (Sigma-Aldrich) for 10 min at RT before being rinsed, dried and kept

at 4°C before use. The cells were resuspended in PBS (1:1000) and incubated for 10

min, 30 min or 1 hour at RT. Results and selection of optimal parameters are described

in Section 5.4.2. After incubation, the cells were lightly fixed for 30 seconds in

glutaraldehyde (1%) in cacodylate buffer (Proscitech). PBS was used for AFM

analysis, at RT.

5.3.5 Indentation protocol

A NanoSurf FlexAFM with NanoSurf C3000 software (NanoSurf, Liestal,

Switzerland) was used to indent the samples (n = 15 cells). The RBC surface was first

scanned to identify the cell’s shape profile and then indented following a grid pattern

to measure the deformation response, as can be seen in Figure 5.2.


Figure 5.2: Schematic for indentation grid pattern over a RBC surface. Red dots represent the

location of the indentations.

Maximum indentation force was set between 0.5 nN and 2.5 nN and resulted in

deformations of less than 200 nm. The applied force was kept particularly small as

Hategan et al. [153] reported membrane rupture when 14 nN was exceeded with a

sharp tip. The deformation depth was kept to less than 10% of cell height, which

averaged 2.1 µm at its maximum, to minimise the effect of the substrate [222].

Indentation speed was set to 1 µm/s, as measurements at slower speeds may experience

sample drift [210]. At a higher speed (above 5 µm/s), the dynamic reaction force from

the membrane has also been found to influence the extracted elasticity values. Ciasca

et al. [210] found that the measured effective Young’s modulus for healthy RBCs did

not differ for indentation speeds between 1 and 5 µm/s.

5.3.6 Experimental Data Analysis

As stated in the introduction, Hertz-based models have significant limitations in

reasoning solid mechanics contact assumptions. However, they have been widely used

to analyse RBC force-indentation results [29; 149; 210-212; 215; 217]. This study

aimed to provide accurate force-deformation data for the associated numerical model

calibration. Extraction of numerical value for the effective Young’s modulus was used

to validate the measurements against previous studies and verify that the Hertz

modified equation for finite sample thickness described the force-deformation trend.

This was then used to benchmark the numerical model’s performance.

Force-height curves were extracted using the SPIP image processing software

(3D Vizualisation Studio, Horsholm, Denmark) and were analysed using Matlab

(MathWorks). Force deformation curves were first plotted together. As the probe

indented a square area containing the cell of interest surrounded by empty substrate

following a grid pattern, two different deformation behaviours could be observed:


curves representing indentations over the hard substrate are visibly shorter and closer

to presenting a linear deformation behaviour (Figure 5.3, blue section), while

indentation over the cell surface follows a non-linear deformation, described by the

Hertz model (Figure 5.3, red section).

Figure 5.3: Force deformation curves plotted for 64 indentation points. Indentations over hard

substrate follow a different deformation behaviour from indentations over the RBC membrane.

It was then possible to select indentation curves corresponding to the cell

membrane based on their deformation behaviour. The data corresponding to

indentation curves over the centre of the cell membrane was fitted to the Hertz equation

modified by Dimitriadis et al. [222] for spherical tip shape, which corrects for finite

sample thickness,

𝑭 =𝟏𝟔

𝟗𝑬𝑹𝟎.𝟓𝜹𝟏.𝟓[𝟏 + 𝟏. 𝟏𝟑𝟑𝝌 + 𝟏. 𝟐𝟖𝟑𝝌𝟐 + 𝟎. 𝟕𝟔𝟗𝝌𝟑 + 𝟎. 𝟎𝟗𝟕𝟓𝝌𝟒],

(5.1)

where 𝜒 =(𝑅𝛿)0.5

ℎ,

𝐹 is the applied force, 𝐸 is the effective Young’s modulus, 𝛿 is the indentation depth,

𝑅 is the indenter radius and ℎ is the cell height. As RBCs lack organelles, no

corrections are needed to take into account the heterogeneous intracellular content. To

further reduce the substrate’s impact on the measured force-deformation behaviour,

only results from indentation performed at the centre of the cells were considered to


extract the effective Young’s modulus numerical value. This is because the centre of

the cell is furthest from the bonding to the substrate. Indentation at the centre also

means that inclination and asymmetry of the contact area between the cell and probe

are minimised [225]. Average for the cell was calculated using these selected values

(see Section 5.4.3). The number of selected points and effective Young’s modulus

mean and standard deviation values can be found in Table 5.1 for all the cells included

in this study. This method of selection was quite accurate, as can be seen in Figure 5.4:

the effective Young’s modulus of the selected indentation curves in Figure 5.3 were

represented on an effective Young’s modulus map (Figure 5.4b) and they match the

centre of the original AFM scan of the cell studied (Figure 5.4a). The curves

corresponding to indentation over the substrate were not analysed and were associated

with an effective Young’s modulus of 0 kPa on the colour map.

Figure 5.4: Original AFM scan of a RBC (a) and corresponding effective Young’s modulus map

(b).

5.4 Results

5.4.1 Suitability of spherical probes

Preliminary investigations confirmed that the spherical probes provided high

quality imaging without significant displacement of the membrane. This is illustrated

in Figure 5.5, which shows a typical height profile measured from forward and

backward scanning of a RBC. It can be seen that both profiles are superimposed

(Figure 5.5b), indicating that the probe did not deform the membrane during scanning.

Furthermore, the profile appeared unchanged even after several scans.


Figure 5.5: (a) Deflection scan of a RBC (16 µm x 16 µm) and (b) height profile for section

marked with red line on deflection scan. The forward scan (black line) and backward scan (grey

line) are superimposed.

5.4.2 Optimisation of the adhesion protocol

AFM indentation can only be performed if cells are immobilised on the substrate.

Existing protocols in the laboratory used a poly-D-lysine coating to adhere the cells to

their substrate. Poly-lysine creates electrostatic interactions with the cell membrane.

This non-specific binding was proven to be versatile and working well with a large

range of cell types. In order to balance adhesion strength against preservation of the

membrane’s natural state, poly-D-lysine coating concentration and incubation time

were chosen from a parametric study. Cells were incubated for specified times at RT

in PBS to allow them to sink and then adhere to poly-D-lysine coated Petri dishes. A

range of poly-D-lysine concentrations and incubation times were trialled, with AFM

scanning results for each combination are shown in Figure 5.6. It can be seen that when

the concentration of poly-D-lysine is too low, the cells detach during scanning, causing

significant imaging artefacts (1 and 10 µg/mL cases, in Figure 5.6b, e and j: partial

cells are visible). When the concentration and incubation times were too high,

excessive membrane tension was evident in the extent of the dome-like shapes (Figure

5.6d, g-h, k-l).


Figure 5.6: Scans of RBCs from the same blood sample for varying concentrations of poly-D-

lysine and incubation times. Note that the incomplete images in (b), (e), (f), (i) and (j) are caused

by cell detachment and movement during scanning. Scan sizes: 15 µm x 15 µm for (a); 30 µm x

30 µm for (b), (e), (i), (j); 40 µm x 40 µm for remainder.

To minimise tension in the uppermost part of the cell membrane while

maintaining sufficient adhesion during scanning, a concentration of 100 µg/mL of

poly-D-lysine and incubation time of 10 minutes were chosen (Figure 5.6c) and used

for indentation experiments.

5.4.3 Effective Young’s modulus extraction

Indentation was realised on 15 cells from four different blood units. Information

regarding each cell’s effective Young’s modulus mean and standard deviation was

summarised in Table 5.1 and a graphical representation can be found in Figure 5.7.

The experimental data was observed to closely fit the force-deformation trend

predicted by the modified Hertz equation (Figure 5.7a).


Figure 5.7: (a) Comparison between experimental data and the modified Hertz equation for a

typical sample where E=9.83 kPa, (b) effective Young’s modulus for each cell; the mean is 7.42

kPa (solid line) with a standard deviation of 3.42 kPa (dotted lines)

An effective Young’s modulus for each cell is shown in Figure 5.7b. The average

was found to be 7.42 kPa with a standard deviation of 3.42 kPa. This aligned with

previous studies investigating the effective Young’s modulus of the RBC membrane,

which has reported values between 0.1-0.2 kPa [215] and 98 ± 17 kPa [212]. The wide

range was attributed to the differences in sample preparation and indentation protocols,

as well as analysis methods: experiments reported in the literature were realised with

a large range of probe shapes, as well as different fixation procedures for RBCs

(supplementary information [210]). Fixed and dried samples have higher measured

Young’s modulus (between 26 ± 3 kPa [211] and 98 ± 17 kPa [212]) compared to

those who do not mention a fixation step (between 0.1-0.2 kPa [215] and 4.9 ± 0.5 kPa

[149]). Indentation parameters such as indentation speed are not often reported, which

makes it hard to find the origin of the variation between samples apparently prepared

following the same protocol.

Data were collected from four samples at different times during storage: tested

cells were kept at 4°C between 7 and 27 days at the time of the experiment. The effect

of storage duration was verified on the numerical value of effective Young’ modulus

collected. Data points on Figure 5.7b were plotted by ordering cells from the shortest

to longest storage duration. No significant evolution of effective Young’s modulus was

observed here in function of cell age (p=0.6981). RBCs have been reported to have

constant mechanical properties between the second and fourth week of storage [226],

and this may explain the lack of correlation between effective Young’s modulus and


storage duration reported here. This could also be due to the large experimental error

masking smaller aging effects. Donor variation was again the most important source

of variation between collected data points.

Table 5.1: Experimental AFM indentation data summary over the 15 cells included in this study

Effective

Young’s

Modulus

mean (Pa)

Effective

Young’s

Modulus

standard

deviation (Pa)

Storage

duration

(days)

Sample

number

9833.08 852.67 7 2

8700.29 1132.03 7 2

4716.67 1366.96 8 2

5206.29 1046.41 13 3

8644.05 457.31 13 3

4632.97 270.90 14 3

11788.77 1893.27 14 3

15431.17 1804.12 14 4

8081.06 425.88 14 4

5565.44 249.00 14 4

1402.82 63.03 14 4

3288.75 1311.71 22 1

10015.77 255.49 26 4

9887.31 1527.53 26 4

9428.29 730.66 27 1

5.4.4 Numerical model

The numerical model developed by Sarah Barns in parallel to this PhD project

used a coarse-grained particle method: the cell membrane was discretised into particles

connected by a triangulated network of springs representing the different forces

exerted on the membrane. RBCs tend to form dome shapes when adhering to a

substrate. This was verified using 3D image reconstitution based on confocal images

(Figure 5.8b). The numerical model was able to match this shape by creating attraction

force between the substrate and the cell membrane (Figure 5.8a).

Figure 5.8: Adhered shape of RBCs predicted by the numerical model (a) and verified by

confocal imaging (b).


Indentation by a 5 µm bead was realised on the adhered model (Figure 5.9a).

Using the data from experimental AFM indentation, both 2D and 3D models were

calibrated and produced force deformation curves with trends following experimental

curves very closely, especially for the 3D model (Figure 5.9b).

Figure 5.9: Model indentation representation (a) and associated force deformation curves (b).

The numerical model was demonstrated to be able to match indentation

experiments realised on RBCs. It was used to study the influence of experimental

parameters such as probe shape or diameter of the extracted Young’s modulus, and

successfully demonstrated the limitation of the Hertzian contact model (article in

preparation). The validated model has potential to be used as predictive model for RBC

behaviour under mechanical stress, and can be used to propose a new set of equations

for biological samples’ indentation.

The main finding from replicating AFM indentation on this numerical model

was that, for small indentation, the mechanism opposing the deformation was the

bending resistance provided by the lipid bilayer. The lipid bilayer tries to remain as

flat as possible and play the largest part in preserving indentation deformation.

5.5 Discussion

Experimental parameters such as indentation location, probe geometry and

indentation speed, to name a few, are linked to large variation in the calculated

Young’s modulus numerical value [210; 220]. This has a significant impact on the

interpretation and comparison of quantitative values, with most studies only reporting

an average. Regarding indentation location, Ciasca et al. [210] found an effective


Young’s modulus significantly higher for the central region compared to near the

edges. In fact, for a ‘typical’ cell, Young’s modulus was as high as 9 kPa at the centre,

as low as 0.06 kPa near the edge, and 1.87 kPa when averaged over the surface. This

study was not the only one reporting these variations [210-212]. Probe geometric

differences also have a substantial impact on measured Young’s modulus, as local

strains imposed on the membrane by sharp probes may exceed physiological levels

and subsequently trigger a reorganisation of the membrane structure. Having different

probes also means that different Hertz equations have been applied in an attempt to

take into account the geometry, and some equations neglected modifications for finite

sample thickness and substrate effects. While acknowledging complicating factors in

the comparison, the results of the present study are comparable with existing data. It

is also shown that the experimental data follows the trend predicted by the modified

Hertz equation (Figure 5.7a).

The use of Hertzian contact models to study biological sample mechanical

properties has raised an increasing number of questions from the scientific community

[216; 221]: most of the working hypotheses cannot be verified using the original Hertz

model, especially regarding sample homogeneity and the half space assumption. RBCs

are not made of a uniform material but are constituted of several layers with different

mechanical properties: the lipid bilayer creates bending resistance and has low

elasticity while the spectrin network tethered beneath has an opposite role of giving

the membrane its elastic properties. The Hb rich cytoplasm provides material

incompressibility and is likely to influence deformation behaviour for large

deformation at high indentation speed. Regarding the half space assumption, the

modified model developed by Dimitriadis et al. [222] used in this study, attempts to

take sample thickness into consideration, but has not succeeded in making results

independent from probe geometry (Barns et al., to be published, 2018). There is a need

for a new model adapted to biological samples that accounts for probe geometry,

indentation speed and sample thickness, while being easy to use with raw experimental

data. The experimental data collected will contribute to develop and validate a

numerical model that will attempt to improve on the current Hertz model.


5.6 Conclusion

AFM indentation data, while limited due to sample preparation and treatment,

was used successfully to estimate an effective Young’s modulus value for RBCs, under

these conditions. This value was used to calibrate and validate a coarse grained

numerical model. This model will have potential to improve on current indentation

model framework and should lead to better estimate of cell mechanical properties

using AFM.

This study demonstrated the utility of spherical probe indentation to characterise

the mechanical properties of the RBC membrane. The modified Hertz equation for a

finite thickness model accurately described the RBC membrane behaviour under small

indentations. The effective Young’s modulus value extracted from experimental data

was comparable with similar studies reported in the literature [149; 210]. This Young’s

modulus was successfully used to establish a numerical model predicting RBC

behaviour under spherical indentation. This model has the potential to answer current

questions regarding the suitability of the Hertz model to describe biological sample

indentation.

The two main limitations of the study presented here are the adhesion protocol

and the use of glutaraldehyde. Adding glutaraldehyde is known to have an effect on

the membrane function, and consequently, studies using this method have reported a

higher Young’s modulus. In order to avoid the use of glutaraldehyde, a new adhesion

method should be developed based on different adhesion mechanisms: electrostatic

bonds created by poly-D-lysine have been at the origin of the cells spreading over the

substrate, and thus the need for glutaraldehyde. Adhesion bonds based on specific RBC

membrane properties (carbohydrate moieties or surface receptors) could be

investigated in future studies and may preserve RBC shape better without requiring

glutaraldehyde. Liu et al. [227] tested different adhesion protocols, and the use of

erythroagglutinating phytohemagglutinin (E-PHA) showed promising results, as it

balanced adhesion strength and preserved cell morphology well.

AFM is a promising method to assess cell properties and was successfully used

in pathology and oncology studies [209-215]. Its implementation can be challenging

and results are still dependent on the experimenter and the quality of the sample

preparation. As this technique becomes increasingly used in mechanobiology research


laboratories, we can expect future improvements and we could potentially see AFM

applied to diagnosis tools in the coming years.

Chapter 6:Study of global cell deformability using optical tweezers 83

Chapter 6: Study of global cell deformability using

optical tweezers

In the previous chapter, AFM indentation was used to successfully extract a

Young’s modulus using spherical indentation. AFM indentation characterises the

membrane at a local scale, but has limited application to understand global membrane

mechanical properties due to the cell’s interaction with its substrate [153; 223]. In this

chapter, RBCs global deformability was measured during storage using a novel two-

trap optical tweezers protocol [228]. The properties of both discocytes and echinocytes

were assessed during storage, in order to determine the influence of both shape and

storage duration on cell mechanical properties. Two in vitro protocols were also

developed to model aging effect on the RBC membrane during storage. Global RBC

deformability is associated with their ability to stay in circulation after transfusion [14;

229].

6.1 Introduction

Mechanical testing is commonly used to determine RBC membrane

deformability. A large range of techniques exist, such as AFM, micropipette

aspiration, ektacytometry, microfluidic devices or optical tweezers, to look at different

properties of the membrane. AFM experiments, presented in Chapter 5, give limited

results in regards to membrane deformability due to sample immobilisation and

fixation steps. AFM experiments generate insight on local mechanical behaviour down

to the molecular scale, but are not optimum for global cell deformability studies. AFM

results are also largely dependent on the experimental setup (probe geometry,

indentation speed), and model used to extract mechanical properties [220], such as the

Young modulus.

After studying local membrane properties using AFM (Chapter 5), a method to

study global cell deformability properties was sought. Ektacytometry studies the

global cell deformation under shear strain and measure responses to prolonged

deformation with limited damage to the cell. High throughput methods, such as flow

characterisation in microfluidic channels, give an overall good representation of the

84 Chapter 6:Study of global cell deformability using optical tweezers

deformability of population studied when flowing through narrow sections of the

channels. These last two methods have been applied to study RBC aging in storage

[39; 145] but tend to have results over the whole sample without differentiating

between subpopulations or individual behaviours in that sample.

Optical tweezers have several advantages compared to the methods mentioned

above. They combine single cell measurement and deformations within physiological

limits. They also have the advantage of studying cells in liquid environments without

any other treatment required than dilution of the blood sample. Replicating in vivo

conditions using an isotonic buffer or body temperature can be implemented in optical

tweezers experiments and are preferable to get better prediction of RBC behaviour

after transfusion. Previous experiments on RBC mechanical properties used beads

attached to the membrane as handles to facilitate force calibration and trapping [156;

157; 161; 230-232]. Bead trapping methods have been useful for validating modelling

simulations [158]. The force applied to the beads is higher than the maximum force a

cell tolerates before accumulating heat damage and lysing. However, using beads leads

to localised deformations of the membrane at the bead attachment point. A solution

proposed by Czerwinska et al. [26] to avoid using beads, is to adhere the cells to the

bottom substrate and use a single trap to pull on the cell and detach it. This method has

the disadvantage of replicating the measuring artefacts from AFM experiments and the

force recorded represents both membrane deformation and adhesion strength.

RBCs can be stretched without beads using two traps simultaneously [233; 234].

Trapping the cells directly with laser power around 220 mW was demonstrated to

produce cell deformation without damaging the sample [235]. Agrawal et al. (2016)

[234] successfully applied a double trap stretching method to identify differences in

deformability in RBC from healthy and diabetic patients, showing the suitability of

optical tweezers in studying RBC populations.

The current study aimed to measure the overall cell deformability of discocytes

and echinocytes in a physiological environment as they aged during routine blood

storage conditions. This study was undertaken to help explain the relationship between

deformability, cell morphology and storage duration. Many mechanical studies on

RBCs either measure properties in large blood samples without differentiating

between cell morphologies[187], or only consider discocytes [236]. This study is the

first to compare the differences in deformability behaviour between discocytes and


echinocytes, as they age during routine storage, using tensile stretching. Two in vitro

models of oxidative damage and ATP depletion were also used to reproduce effects of

storage on RBC deformability. These two models were used to provide new

explanations of the storage-related echinocytic transformation.

6.2 Aims

This chapter aimed to:

- Establish the suitability of using optical tweezers to quantify RBC

mechanical properties during aging in storage,

- Compare the deformability behaviour of discocytes and echinocytes under

tensile strain,

- Gain insights into the molecular mechanisms behind the RBC membrane

mechanical properties, using in vitro models of oxidative damage and ATP

depletion.

6.3 Materials and methods

6.3.1 Ethics clearance

Refer to Section 3.3.1

6.3.2 RBCs and plasma samples

Refer to Section 3.3.2 for information regarding pRBC units and Sections 3.3.4

and 3.3.5 for information regarding FFP units and cold-agglutinin-depleted FFP

preparation.

6.3.3 Optical tweezers set up

All optical tweezers experiments were realised in the UQ Optical Micro-

manipulation Group research laboratory, with the help of Anatolii Kashchuk and Dr

Alexander Stilgoe. To prevent sample evaporation during testing and direct contact of

the sample with an immersion oil of the condenser, sample chambers were made using

two coverslips spaced by double-sided tape. A schematic of the optical tweezers

experimental set up can be seen in Figure 6.1. A laser beam was first split by a


polarising beam splitter into two beams, to create the two traps with opposite

polarisations and then focused on the chamber. One of the beams was moved away

from the other during the experiments using a spatial light modulator while the other

remained still. The scattered light was collected by a condenser with high numerical

aperture in order to collect as many of the scattered photons as possible. Using the

property of the condenser lens to transfer angular distribution of the light into a spatial

distribution of the light in the back focal plane, the change of the momentum of the

light, and thus the optical force, are measured by detecting a centroid of the light

pattern. The back focal plane of the condenser was imaged on an optical position

sensitive detector. To measure the optical force acting on the RBC from one beam, we

use a polariser next to the detector to cut the movable beam and let the stationary beam

through. Calibration of the detector was performed using an equipartition theorem, by

tracking the position of the trapped spherical particle.

Figure 6.1: Optical tweezers experimental set up (unpublished image by Anatolii

Kashchuk)

Details of the optical system are as follows: a laser beam (IPG Photonics YLD-

5 fibre laser, 1070 nm) was expanded to fill the back aperture of the objective (water

immersion 60, NA 1.2). A spatial light modulator was used to move one of the laser

beams and stretch a RBC. A collimated light was focused onto the sample chamber. A

dichroic mirror separated the trapping beam from the illumination beam. A high


numerical aperture condenser (silicon oil immersion 100, NA 1.35) collected scattered

light, which was imaged on the position sensitive detector (On-track PSM2-10 with

OT-301DL amplifier) using a relay lens [228].

6.3.4 Time-course experiments

RBCs were sampled aseptically from 4 pRBC units at weekly intervals during

routine storage and placed into cold-agglutinin-depleted FFP to model a physiological

environment. Experiments were conducted at day 2, 9, 16, 23, 30, 37, 42 and 50,

extending the study past standard storage duration. At each time point, 5 discocytes

and 5 echinocytes were tested per unit. Definition of discocytes and echinocytes were

based on Bessis’ classification [64]. Discocytes or early stage I echinocytes were

included in the ‘discocyte’ category and the ‘echinocyte’ category corresponds to stage

III echinocytes.

Figure 6.2: Force associated with the stretching of a single discocyte between two laser traps.

The force exerted to maintain the cell in a stretched state increases, until the cell escapes the

trap. The force then suddenly reduces to its baseline level.

The cells were trapped between two laser beams and stretched progressively at

a rate of 0.102 µm per second until they escaped the trap. The force exerted on the cell

membrane was recorded (Figure 6.2). The gradient, or slope of the force-separation

curve, represents the force required to elongate the cell per unit of distance. The visco-

elastic forces were not considered to affect quantitative results during stretching, as

measurements were realised once the cell has reached a steady state. The distance

between the laser beams was slowing increased by 0.102 µm step for every second,


and force measurements were only recorded during the second half of this second.

Measurements were realised in triplicate for each cell, meaning each cell was stretched

three times in a row.

6.3.5 In vitro model of oxidative damage

In order to model oxidative damage to RBCs during storage, day 3 RBCs from

3 pRBC units were oxidised using diamide [110; 224; 237; 238]. A volume of 2.5 µL

of RBCs was resuspended in 1 mL of PBS (Sigma-Aldrich) supplemented with

diamide (Sigma-Aldrich) and incubated for 30 min at RT. Diamide concentration

ranged from 0.05 mM to 5 mM. The cells were then washed in PBS + 5% BSA (Sigma-

Aldrich), then the cell suspension was placed into an imaging chamber. BSA was used

to prevent RBCs from adhering to the coverslip.

6.3.6 In vitro model of metabolism slowdown

ATP depletion experiments were realised on day 3 RBCs from 5 pRBC units. A

volume of 2.5 µL of RBCs was resuspended in 1 mL of PBS supplemented with 6 mM

iodoacetamide (Sigma-Aldrich) and 10 mM inosine (Sigma-Aldrich) in PBS (Sigma-

Aldrich) [239-242]. The cell suspension was then incubated for 2 hours at 37°C. After

incubation, the cells were kept in PBS containing the same concentration of

iodoacetamide and inosine, and supplemented with BSA (Sigma-Aldrich). The cell

suspension was then placed into an imaging chamber. BSA was used to prevent RBCs

from adhering to the coverslip.

6.3.7 Data analyses

Data analyses and gradient (the slope of the force-deformation curve) extraction

were performed using an in-house Matlab code. The gradients were calculated on the

latest section of the stretching curves, before the cell escaped from the trap (see Figure

6.2). The earlier section of the curve corresponded to the traps shifting until the traps

reached the edges of the cell. Force measurements on that part corresponded to the

force required to trap the cell but not to stretch it.

Statistical analyses were performed using GraphPad Prism 7.00 (GraphPad

Software) or IBM SPSS Statistics 23 (IBM, Armonk, USA) software. For the time-

course study, 76 data points were excluded from data analyses due to uncertainties in

the measures. Among these 76 data points, 59 could not been extracted from the raw

data files due to experimental artefacts and the 17 others were determined as outliers,


over a total of 960 data points. Statistical analyses for overall deformability involved

a Welch’s modified ANOVA. Time evolution and replicate effect were verified using

a two-way repeated measures ANOVA, followed by post hoc analysis with a

Bonferroni adjustment using day 2 values as the control [171].

For both the oxidative and metabolic studies, statistical analyses included a two-

way ANOVA, followed by post hoc analysis with a Bonferroni adjustment [171]. For

results obtained during the oxidative study, 3 data points were determined as outliers

and excluded.

6.4 Results

6.4.1 RBC behaviour under tensile strain

To ensure the RBCs were not damaged by the laser power applied, a series of 20

stretches was performed consecutively on discocytic and echinocytic cells. No sign of

membrane degradation was observed (Figure 6.3) as the curves followed each other

closely. If damage occurred during the stretching process, mechanical properties and

deformation behaviour would have been expected to evolve after repeated stretching.

Figure 6.3: Force-deformation curves for a series of 20 stretches realised on a single discocyte.

Each colour represents a different stretch.

Interestingly, RBC deformation under tensile stretch was not always linear:

some cells (both discocytes and echinocytes) presented a sawtooth pattern as shown in

Figure 6.3 above. This pattern was not due to rupture or damage of the membrane

component, as it reappears in successive stretches. After observing the cell closely as


it was stretched, it was also verified that this was not due to a rotation of the cell

between the traps. The drop in the curve represented a sudden softening of the RBC

membrane, which could be due to a sudden reorganisation of the cytoskeleton, most

likely of the spectrin network as it reforms its junctions with anchoring structures [58;

59; 243]. Further analysis focused on comparing the membrane elastic deformation

only. The results presented next were extracted from the final linear section of the

force-deformation curves, without including the sawtooth pattern, if present.

6.4.2 Influence of morphology on deformability

This study aimed to compare discocyte and echinocyte properties under stretch

over 50 days of storage. More force was required to stretch an echinocyte compared

to a discocyte over the same distance (p<0.0001, Figure 6.4). This first observation

was realised comparing discocytes and echinocytes, without separating the cells based

on their length of time in storage. The echinocyte population was shifted toward the

right side of the graph compared to the discocyte population, showing an increased

gradient for these cells.

Figure 6.4: Population frequency distribution for both discocytes and echinocytes in function of

the force required to stretch them (gradient). (**** p < 0.0001)

6.4.3 Influence of storage duration on deformability

The evolution of deformability of both discocytes and echinocytes were

evaluated separately over the 50 days of the study, to observe the effect of storage

duration on cell mechanical properties.

Cell deformability was recorded for discocytes (Figure 6.5a) and echinocytes

(Figure 6.5b) between 2 and 50 days of storage. No changes could be observed in the


cellular deformability over the 50 days of the study for either RBC morphology

(p=0.0722, and p=0.5185, for discocytes, and echinocytes, respectively). Cells after

50 days of storage behaved very similarly to day 2 cells for both discocytes and

echinocytes.

Figure 6.5: Gradient values (N/µm) over 50 days for both discocytes (a) and echinocytes (b).

Graphs are showing means and standard variation for average over the three replicates.

6.4.4 Replicate effect

While the average gradient did not change over the 50 days of storage, an

increase in the force required to stretch the cells was observed during the three

replicates at each time point, for discocytes and echinocytes (p < 0.0001 for both

morphologies, Figure 6.6). The force required to stretch RBCs over the same distance

was raised by 63 % and 30 % on average between the first and third replicate, for

discocytes and echinocytes respectively.

For discocytes, the gradient was constant over storage for the first and second

replicates, with an average value at 1.50 ± 0.15 x10-5 N/µm for the first stretch,

increasing to 1.82 ± 0.22 x10-6 N/µm for the second stretch (p < 0.0001). Values for

the third stretch increased after day 37 (Figure 6.6g). The average gradient over the

first 30 days was 2.21 ± 0.26 x10-5 N/µm for the third stretch.

Similarly, for echinocytes, gradient values were found to be constant for the first

two replicates over the 50 days of the study. The average went from 1.95 ± 0.78 N/µm,

to 2.23 ± 0.11 N/µm for the second stretch. Except for a lower gradient value at day

16 (Figure 6.6h), gradient values for the third replicate were also constant, with an

average of 2.54 ± 0.26 N/µm.


Figure 6.6: Gradient values (N/µm) for discocytes (a, c, e, g) and echinocytes (b, d, f, h). An

increase in average gradient can be seen between the first (c-d), the second (e-f) and third

replicates (g-h). (* p < 0.05, ** p < 0.01)


The gradient difference between stretches did not increase with storage duration,

with the exception of the third replicate for discocytes. In that case, the gradient value

increased with storage duration.

Two hypotheses were made to explain the replicate effect observed here. It could

possibly be due to either accumulated damage to the cytoskeleton that would prevent

it from working smoothly over repeated strain [17; 107; 244], or to a metabolism

slowdown and reduction of intracellular ATP [103; 164]. Two models were thus

established to study the effects of oxidation on the cytoskeleton and chemical ATP

depletion on RBC membrane properties.

6.4.5 Effect of oxidative damage on RBC mechanical properties

Oxidative experiments were conducted to verify whether cytoskeleton oxidation

would affect the deformability of RBCs under tensile strain. Oxidation promotes

crosslinking of membrane cytoskeletal proteins such as spectrin and alters

cytoskeleton behaviour [245]. Contrary to glutaraldehyde, which is a non-specific

crosslinker, diamide targets spectrin molecules specifically, and is better suited for

modelling cytoskeletal damage [224; 246]. This chemical was thus chosen to conduct

a study on cytoskeletal oxidation.

The diamide oxidation model was used previously to study the effect of

oxidative damage on cell deformability using microfluidics, ektacytomerty, AFM, and

micropipette aspiration experiments [110; 224; 237; 238]. Several experiments

conducted on fresh RBCs do not report a shape transformation even after incubation

with a high concentration of diamide [224; 237; 238]. However, Sinha et al. [110]

reported ‘visible morphological changes in a dose-dependent manner’, and appearance

of echinocytes. Similarly, the current study found a large shape shift from discocytes

to echinocytes after incubation with diamide. To allow for comparison between results

obtained here and in published work [224; 237; 238], all data reported in this section

were obtained from the discocytes found in samples after diamide treatment (Figure

6.7).


Figure 6.7: Force required to stretch discocytes in function of replicate number and diamide

concentration (* p < 0.05, ** p < 0.01)

Cytoskeletal oxidation using diamide had no effect on the gradient value

(p=0.2125). Replicate effect was only significant for cells incubated with 5 mM

diamide (p=0.0189 between the first and second replicate and p=0.0030 between the

first and third replicate). Donor effect was likely large during this experiment, as RBC

from different individuals had different sensitivity to diamide treatment.

6.4.6 Effect of ATP depletion on RBC mechanical properties

The second hypothesis for the replicate effect is a lower availability in ATP for

stored RBC. ATP plays an essential role in the remodelling of the spectrin network. It

reduces the affinity of protein 4.1.R for spectrin and thus helps dissociate the spectrin-

actin links, as protein 4.1.R which holds them together [62; 241]. An intracellular

decrease in ATP availability would result in membrane stiffening and, possibly, shape

changes [242; 247]. RBC metabolism slows down during storage and it was reported

that intracellular ATP concentration decreases from day 14 [105; 164]. This could be

a possible explanation for the replicate effect observed in this study: the stock of ATP

present in the cell will be depleted by the first stretch, and following measurements

would report a stiffening of the cell membrane as the cell cannot metabolise ATP fast

enough to compensate for the depletion.

Several ATP depletion models were found in the literature [239-242]. The

simplest model is to reversibly reduce ATP production by starving the cells in a

glucose-free medium for 24h, at 37°C. Another way is to chemically deplete the

cytoplasm in ATP and inorganic phosphates by incubating the cells with


iodoacetamide and inosine [239-242]. The second method was chosen to observe the

most drastic effects of ATP depletion on RBCs.

Contrary to the oxidation model, most studies using a chemical depletion model

report a shape transformation when the cells are depleted in ATP [239; 240]. The same

observation was made in this study: a large number of RBCs assumed an echinocytic

morphology, as expected. Results reported here were measured on discocytes, to

facilitate comparison with both the literature, and results from the time course study

(Figure 6.8).

Figure 6.8: Force required to stretch discocytes in function of replicate number and ATP

depletion treatment

Results comparing the day 3 control samples and the ATP depleted samples can

be found in Figure 6.8. As expected, the force required to stretch the cells was higher

after ATP depletion (p < 0.0001). However, no replicate effect could be observed here.

The large standard error is likely due to donor variation, and the limited number of

samples could mask other effects.

6.5 Discussion

6.5.1 Influence of RBC shape on cell deformability

Results obtained from analysing the time-course study confirm previous studies

conducted on the mechanical properties of echinocytes [19; 205]. Different mechanical

properties were expected for different shapes, as echinocytes are thought to be the

result of damaged cytoskeletal proteins, such as band 3, protein 4.1 and spectrin [140].


The lower surface area-to-volume ratio could also be at the origin of the stiffer

behaviour of echinocytes.

However, the degradation of membrane components usually associated with the

storage lesion [107; 245] did not have an effect on cell mechanical properties here.

Increases in stiffness and morphological transformations seem linked to each other. At

this point, it is unclear if cytoskeleton damage due to the storage lesion starts the

morphological transformation, or if the increased stiffness in echinocytes is only linked

to their increased sphericity and reduced internal volume.

During storage, the proportions of discocytes and echinocytes change; more

echinocytes appear as the cells get stored for longer and are placed back into a

physiological environment (see Chapter 3). Published mechanical studies report an

overall sample deformability reduction during storage [14; 19; 116; 118]. Results

presented here support previously published work [117; 244]. Published values may

be due to an increased number of stiffer echinocytes in the sample, rather than an

increased stiffness of discocytes only.

6.5.2 Insights into the RBC membrane mechanics

While the stiffening of some cell types or tissues has been reported for other cell

types, the behaviour of RBCs under repetitive strain has not been described previously.

RBC behaviour could be expected to be very different from other cell types, as these

cells do not possess microtubules or a cross-cellular cytoskeleton [50]. The study

conducted by Henon, et al. [156] report an apparent stiffening of the cell membrane

after trapping RBCs for over 15 min. Here, the three replicates took less than a minute

each. It could have been expected that cells under strain would become more

deformable, as they undergo continuous deformation in circulation: a reduced

deformability could lead to higher cell clearance. However, the opposite results were

found here. It was demonstrated in Section 6.4.1 that the gradient increase between

replicates was not due to heat damage from the laser. Two in vitro models were

established to find the origin of this apparent increase in cell stiffness over repeated

strains.

The oxidation model developed during this study differs to most published work

using this oxidation model by the high percentage of echinocytes found after

incubation with diamide. This could be linked to their use of fresh blood sample


instead of processed RBC samples [110; 224; 237; 238]. In this study, in some

samples, it was challenging to find enough discocytes to complete the experiments.

The cells that did not go through the morphological transformation are likely to belong

to a marginal population, either of very young RBCs, or atypical RBCs. The results

produced on these cells may not reflect the actual evolution of membrane property

after oxidation, and thus, conclusions using the oxidative model are uncertain.

Nonetheless, the shape transformation observed here supports the hypothesis that the

echinocytic transformation during storage is linked to the oxidation of membrane

components.

Diamide affects membrane viscosity, rather than its stiffness, which may explain

that, contrary to expectations, no significant difference could be observed between

treated and untreated samples. Mechanical studies previously demonstrate that the

diamide oxidative model is method dependent. A summary of published contradictory

data, linking experimental setup and results, can be found in Forsyth et al. (2010)

[224]. The diamide oxidation model was shown to be insufficient to elucidate the

mechanical changes happening to the RBC membrane during storage. Oxidation is

also strongly correlated with shape transformation [224; 237; 238] and is unlikely to

be the main factor behind the replicate effect discovered for both discocytes and

echinocytes in our time-course study.

The metabolic slowdown model linked a reduction in intracellular ATP with an

increase in membrane stiffness in discocytes. The model used during this study

chemically depleted the cells in ATP using inosine and iodoacetamide, effectively

shutting down the metabolic process. A more moderate ATP depletion model may be

better suited to model the metabolic modulation during storage [240], and observe the

replicate effect.

The oxidation and ATP depletion models were preliminary studies, used to

assess the suitability of optical tweezers to investigate RBC molecular mechanisms.

While inconclusive at this stage, there are many possibilities to improve on these

models and this will be considered as future work for this project. As for the oxidative

model, ATP depletion was more likely to be a cause for echinocytes to appear in a

sample. Validation of hypotheses regarding the echinocytic transformation could be

realised using optical tweezers on similar models.


6.6 Conclusion

Direct trapping of the RBC membrane using optical tweezers was found to be a

useful method to characterise RBC populations and investigate RBC membrane

mechanics. The different experiments conducted on RBCs using two-trap optical

tweezers stretching show the suitability of this method to study mechanisms behind

RBC membrane properties. Optical tweezers experiments showed good potential to

extract the role of different membrane components, and to characterise RBC

populations during routine storage.

Using this method, it was shown that discocytes require less force to be stretched

than echinocytes, over the same distance, meaning they are more deformable.

Interestingly, discocyte and echinocyte properties did not evolve during the storage

period. Previous studies have reported a decrease in deformability properties for

samples stored for a longer period [14; 116; 117]. However, they do not account for

the increased number of echinocytes, and produce an overall sample average.

Discocytes in those samples may have been just as deformable after long periods in

storage as fresh ones, but less numerous. With the current oxidative and ATP depletion

models, no conclusions could be drawn on molecular mechanisms yet, but future work

can extend on these models using the two-trap method developed here.

Future work to extend this study would ideally focus on observing the repartition

of tensile strain over the membrane using fluorescent labelling, for example [88; 248].

By isolating, labelling or inhibiting different actors in the membrane, more knowledge

can be gained about properties of the RBC membrane using methods such as optical

tweezers.

Chapter 7:Conclusions 99

Chapter 7: Conclusions

During this PhD, RBC aging during storage was studied through physical and

mechanical characterisation. In this chapter, the main findings of this PhD project are

summarised (Section 7.1), then limitations of this project are discussed (Section 7.2).

Finally, recommendations for future work are presented (Section 7.3).

7.1 Main research findings

As RBCs age in storage, they accumulate damage to their structural component,

mainly due to oxidative stress. The structural components of the RBC membrane are

present in their membrane and cytoskeleton, and play an important role in regulating

their shape, and their mechanical properties. For example, the spectrin network is

thought to give the RBC membrane its elasticity, while the lipid bilayer resists strong

deformations [87]. Studies have identified effects of the storage lesion on individual

membrane components, but the link between these individual effects and the overall

shape transformation is still unexplained. It is also not clear if the storage lesion is

responsible for the RBC shape transformation during storage or if it results from the

natural aging pathway of RBCs. The decreased deformability properties of RBCs after

long periods of storage are either thought to be associated with the reduced surface

area-to-volume ratio, or to the altered function of the cytoskeleton [19-21]. To provide

an answer to these questions, the evolution of both the morphology and the mechanical

properties of RBC during storage were monitored during this PhD. This work created

new understanding of the relationship between storage duration, shape transformation

and RBC mechanical properties.

During this PhD, it was demonstrated that the buffer used to resuspend RBCs

influences their shape more than the length of storage. Buffers with high osmolarity

can produce either echinocytes (in 2X PBS) or stomatocytes (in SAGM); the

interaction between the buffer constituents and the RBC membrane govern the

changes. It was also shown that echinocytosis due to an increase in buffer osmolarity

was not associated with internal cell volume reduction. These results question the idea

that the echinocytic morphology is produced by an excess of membrane surface area

100 Chapter 7:Conclusions

after an efflux of water from the cell in concentrated medium. The membrane

components are responsible for the shape transformations, and alteration of these

components during storage produces degraded RBC shape, such as echinocytes.

Using AFM experiments, the lipid bilayer was found to provide membrane

resistance against bending, for small and localised indentations. The cytoskeleton was

shown to be at the origin of membrane elasticity using optical tweezers stretching, and

it was demonstrated that the deformability properties are affected by the shape

transformation occurring during storage. The shape transformation was found to have

a larger effect on cell global deformability than the storage duration. These results

show the importance of maintaining shape reversibility at any point during the storage

period, to the discocytic morphology. Testing for shape reversibility when RBCs are

resuspended in a physiological environment could be used as an indicator of product

quality.

Results obtained during this PhD were successfully integrated into two

numerical models. Data characterising the physical properties of RBC as they

transform from discocytes to echinocytes was used to calibrate a numerical model

developed by Nadeeshani Maheshika Geekiyanage, and representing the RBC shape

changes. The AFM data was incorporated into a numerical model developed by Sarah

Barns. This model studies the effect different membrane components play on the RBC

mechanical properties, and demonstrated the limitations of commonly used

mathematical models to describe mechanical behaviour of biological samples.

Knowledge generated during this PhD project will contribute to the continuous

improvement of RBC processing protocols. By understanding how storage conditions

affect RBC shape and deformability, suggestions can be made to enhance the storage

solution composition. Thus, RBC quality would be better preserved during storage,

resulting in lower numbers of adverse events in patients.

Main research findings for each study presented in this document are

summarised below:

- Chapter 3 characterised cell shape in three clinically relevant buffers as

RBCs age, specifically FFP depleted in cold-agglutinins, SAGM, and a

physiological buffer called ‘artificial plasma’. Understanding how storage

and buffer composition affects the echinocytic process could help develop


solutions to prevent the appearance of echinocytes with irreversible

morphologies during storage. The main findings were that the majority of

cells in SAGM assume a stomatocytic shape, whereas the majority of RBCs

are echinocytes in cold-agglutinin-depleted FFP. In ‘artificial plasma’, cell

shapes were a mix of stomatocytes, discocytes and echinocytes. An increase

in the number of echinocytes was observed during storage in cold-agglutinin-

depleted FFP and ‘artificial plasma’, but buffer composition had the largest

influence on cell shape. A small fraction of RBCs acquired anirreversible

echinocytic morphology, characterised by their round shapes covered in

spicules. The proportion of echinocytes with an irreversible morphology

after 42 days of storage depends on the buffer in which RBCs are

resuspended. In PBS, 12.62 % of RBCs presented an irreversible echinocytic

morphology, but they were only 2.66 % in SAGM. These values indicate a

better pRBC product quality than reported before [111; 118]. RBCs with this

irreversible echinocytic morphology are hypothesised to be at the origin of

reduced transfusion efficiency.

- In order to understand how shape changes happen, the physical properties of

RBCs, as they transition from discocytes to echinocytes, need to be measured

(such as volume and surface area). A new method, based on confocal

imaging and image analysis, was developed to measure RBC properties

during the echinocytic transformation (Chapter 4). Sequential 3D

representations of the cells as they evolve from discocytes to echinocytes

gave more insights on the succession of changes happening to their

membrane. During this PhD, it was shown that the echinocytic process, due

to a change in buffer composition, did not result in internal volume variation

of RBCs. This result consolidates the hypothesis that different mechanisms

exist for echinocytosis, whether it is due to environmental conditions or

aging. The 3D meshes representing the different morphologies make

possible the validation of numerical models using these different shapes.

- A mechanical study, presented in Chapter 5, measured local membrane

elasticity using AFM indentation. An improved Hertzian model and an

optimised protocol for spherical indentation were used during this study. An

average Young’s modulus of 7.42 ± 3.42 kPa was measured for the stored


RBC membrane. The force deformation data were comparable with the

literature and were used to calibrate and validate a numerical model.

- The force-deformation of both discocytes and echinocytes were recorded

under tensile stretch as they age in storage (Chapter 6). Optical tweezers were

used to describe the behaviour of both morphologies when stretched, and to

identify differences in their mechanical behaviour. One important finding

was that, for each morphology, there was no apparent time evolution in the

cells’ stretching behaviour for the duration of the experiment. Mechanical

changes are strongly linked to shape transformation so that these two distinct

properties cannot be measured individually. Echinocytes appeared stiffer and

require more force to stretch than discocytes. This effect was possibly linked

to oxidative damage, using an in vitro oxidation model. During repeated

stretching, the force required to stretch RBCs increased: the cells appear

stiffer after three stretches. This is the first time RBC membrane response to

repeated strains was observed. An ATP-depletion model was used to

investigate whether metabolism slowdown was at the origin of the replicate

effect. The data from this preliminary model has been inconclusive to date,

but provide a basis for future work regarding the active remodelling of the

RBC membrane using optical tweezers.

7.2 Limitations

The main limitations from this work are presented below:

- Buffers: different buffers were selected for AFM indentation and optical

tweezers stretching. For example, buffers containing proteins (such as FFP)

would have prevented RBC adhesion to the substrate, so PBS was chosen

instead in the optimised AFM indentation protocol. In opposition, to prevent

RBC from adhering to the coverslip during optical tweezers stretching, cold-

agglutinin-depleted FFP was chosen. FFP also closely model a physiological

environment. As RBC shape depends on the buffer in which the cells are

resuspended, mechanical properties can also be affected [146]. Using

different buffers can lead to experimental variation between results and make

comparison between results more difficult.


- Temperature: for AFM indentation and optical tweezers stretching,

mechanical testing was realised at RT. Temperature influences the fluidity

of the lipid bilayer [45], as well as the configuration of the spectrin network

[58]. The extracted membrane properties may have been different if

experiments had been conducted at 37°C.

- Number of samples: As most of the studies presented in this document

correspond to the development and optimisation of novel experimental

protocols, a limited number of samples were used. Donor variation is at the

origin of a large source of error in quantitative data [132]. This error could

be reduced by repeating the experimental protocols developed during this

project, on a larger number of samples. Experiments could also be conducted

on sample identified as coming from ‘super storers’ or ‘poor storers’ in order

to identify critical failure point in RBC membrane mechanics at the origin of

product quality degradation during storage.

These limitations may affect quantitative results obtained during this PhD.

Nevertheless, trends related to aging in storage can still be isolated from current

results, and are good indicators of the evolution of RBC shape and mechanical

behaviour during aging in vitro.

Each experimental method has its own limitations, which are briefly summarised

below:

- SEM: Quantification of echinocytes with an irreversible morphology using

SEM imaging is still dependent on the fixation protocol [144]. This protocol

was optimised during this PhD, but RBCs still undergo strong chemical

treatment and were not observed in their native state.

- Confocal imaging: this protocol relied on a lipophilic probe being inserted

into the membrane. This probe made the membrane more fragile, and cells

needed to be fixed before imaging. In order to develop a method to observe

live cells, the staining step needs to be improved by trialling other labelling

methods. The method could then be applied to studying aging cells in

storage.

- AFM: the two main limitations of AFM are that adhesion creates membrane

tension, measurable during indentation [153; 223], and that the Hertzian


model is not suitable to analyse indentation data from biological samples

[216; 221; 249].

- Optical tweezers: using this method, the scattered light is collected. This is

an indirect measurement of the force applied to the cell, which can be

affected by other objects in suspension on the beam path.

7.3 Future work

The new method established to accurately measure RBC surface area and

volume was only applied to RBCs from fresh blood samples during this PhD. This

method can be extended to measure physical properties of RBC aging during storage.

While no variations in volume and surface area could be detected when echinocytosis

was chemically induced, echinocytosis resulting from aging in vitro may give different

results and validate the hypothesis of the existence of different echinocytosis

mechanisms.

Following the completion of a successful time-course experiment using optical

tweezers stretching to measure RBC deformability during storage, new protocols will

be developed. It would be interesting to add cytoskeleton labelling to current

experimental protocol and observe if the cytoskeleton density changes during

stretching. Using this method, we could observe whether the strain is distributed

uniformly around the cell membrane or located around specific areas. In this case, we

could identify potential failure points over the RBC membrane surface [147].

Another potential use of cytoskeleton labelling would be to apply the ‘cysteine

shotgun’ method developed by Krieger et al. (2011) to optical tweezers [248]. This

method uses a double labelling protocol to only identify parts of the spectrin network

that unfold when stretched. This protocol would complete data acquired with the first

cytoskeleton labelling protocol.

7.4 Summary of research project

This PhD project was part of a continuous effort to identify measurements that

can contribute to improvement of RBC product quality during storage. By monitoring

RBC morphological and mechanical properties during storage and developing new


protocols to characterise the cells, the relationship between RBC shape, and their

global deformability as well as the time spent in storage, is clearer. This work

contributed to increasing the available knowledge of RBC membrane mechanics and

cell aging in vitro. This new knowledge will be helpful in improving current storage

protocols, and will lead to better outcomes for transfused patients.

References 107

References

1. National Blood Authority Haemovigilance Advisory Committee. (2013).

Australian Haemovigilance Report - Data for 2009-10 and 2010-11.

Canberra.Retrieved from http://www.blood.gov.au/haemovigilance-reporting

2. Steiner, M. E., Assmann, S. F., Levy, J. H., Marshall, J., Pulkrabek, S., Sloan,

S. R., Triulzi, D., & Stowell, C. P. (2010). Addressing the question of the effect

of RBC storage on clinical outcomes: The Red Cell Storage Duration Study

(RECESS). Transfusion and Apheresis Science, 43(1), 107-116.

3. Weinberg, J. A., McGwin, J. G., Griffin, R. L., Huynh, V. Q., Cherry, I. I. I. S.

A., Marques, M. B., Reiff, D. A., Kerby, J. D., & Rue, I. I. I. L. W. (2008). Age

of Transfused Blood: An Independent Predictor of Mortality Despite Universal

Leukoreduction. The Journal of Trauma: Injury, Infection, and Critical Care,

65(2), 279-284.

4. Wang, D., Sun, J., Solomon, S. B., Klein, H. G., & Natanson, C. (2012).

Transfusion of older stored blood and risk of death: a meta-analysis.

Transfusion, 52(6), 1184-1195.

5. Tung, J. P., Fraser, J. F., Nataatmadja, M., Colebourne, K. I., Barnett, A. G.,

Glenister, K. M., Zhou, A. Y., Wood, P., Silliman, C. C., & Fung, Y. L. (2012).

Age of blood and recipient factors determine the severity of transfusion-related

acute lung injury (TRALI). Critical Care, 16(1).

6. Zallen, G., Offner, P. J., Moore, E. E., Blackwell, J., Ciesla, D. J., Gabriel, J.,

Denny, C., & Silliman, C. C. (1999). Age of transfused blood is an independent

risk factor for postinjury multiple organ failure. The American Journal of

Surgery, 178(6), 570-572.

7. Eikelboom, J. W., Cook, R. J., Barty, R., Liu, Y., Arnold, D. M., Crowther, M.

A., Devereaux, P. J., Ellis, M., Figueroa, P., Gallus, A., Hirsh, J., Kurz, A.,

Roxby, D., Sessler, D. I., Sharon, Y., Sobieraj-Teague, M., Warkentin, T. E.,

Webert, K. E., & Heddle, N. M. (2016). Rationale and Design of the Informing

Fresh versus Old Red Cell Management (INFORM) Trial: An International

Pragmatic Randomized Trial. Transfusion Medicine Reviews, 30(1), 25-29.

8. Fergusson, D., Hutton, B., Hogan, D. L., LeBel, L., Blajchman, M. A., Ford, J.

C., Hebert, P., Kakadekar, A., Kovacs, L., Lee, S., Sankaran, K., Shapiro, S.,

Smyth, J. A., Ramesh, K., Bouali, N. R., Tinmouth, A., & Walker, R. (2009).

The Age of Red Blood Cells in Premature Infants (ARIPI) Randomized

Controlled Trial: Study Design. Transfusion Medicine Reviews, 23(1), 55-61.

9. Lacroix, J., Hébert, P., Fergusson, D., Tinmouth, A., Blajchman, M. A.,

Callum, J., Cook, D., Marshall, J. C., McIntyre, L., & Turgeon, A. F. (2011).

The Age of Blood Evaluation (ABLE) Randomized Controlled Trial: Study

Design. Transfusion Medicine Reviews, 25(3), 197-205.

10. Chai-Adisaksopha, C., Alexander, P. E., Guyatt, G., Crowther, M. A., Heddle,

N. M., Devereaux, P. J., Ellis, M., Roxby, D., Sessler, D. I., & Eikelboom, J.

W. (2017). Mortality outcomes in patients transfused with fresher versus older

red blood cells: a meta-analysis. Vox Sanguinis, 112(3), 268-278.

11. Mohandas, N., & Gallagher, P. G. (2008). Red cell membrane: past, present,

and future. Blood, 112(10), 3939-3948.

12. Salomao, M., Zhang, X., Yang, Y., Lee, S., Hartwig, J. H., Chasis, J. A.,

Mohandas, N., & An, X. (2008). Protein 4.1R-Dependent Multiprotein

Complex: New Insights into the Structural Organization of the Red Blood Cell

108 References

Membrane. Proceedings of the National Academy of Sciences of the United

States of America, 105(23), 8026-8031.

13. Hess, J. R. (2016). RBC storage lesions. Blood, 128(12), 1544-1545.

14. Burns, J. M., Yang, X., Forouzan, O., Sosa, J. M., & Shevkoplyas, S. S. (2012).

Artificial microvascular network: a new tool for measuring rheologic

properties of stored red blood cells. Transfusion, 52(5), 1010-1023.

15. Bosman, G. J. C. G. M. (2013). Survival of red blood cells after transfusion:

processes and consequences. Frontiers in Physiology, 4, 376.

16. Hod, E. A., & Spitalnik, S. L. (2012). Stored red blood cell transfusions: Iron,

inflammation, immunity, and infection. Transfusion Clinique et Biologique,

19(3), 84-89.

17. D'Alessandro, A., Kriebardis, A. G., Rinalducci, S., Antonelou, M. H., Hansen,

K. C., Papassideri, I. S., & Zolla, L. (2015). An update on red blood cell storage

lesions, as gleaned through biochemistry and omics technologies. Transfusion,

55(1), 205-219.

18. Gifford, S. C., Derganc, J., Shevkoplyas, S. S., Yoshida, T., & Bitensky, M.

W. (2006). A detailed study of time-dependent changes in human red blood

cells: from reticulocyte maturation to erythrocyte senescence. British Journal

of Haematology, 135(3), 395-404.

19. Piety, N. Z., Reinhart, W. H., Pourreau, P. H., Abidi, R., & Shevkoplyas, S. S.

(2016). Shape matters: the effect of red blood cell shape on perfusion of an

artificial microvascular network. Transfusion, 56(4), 844-851.

20. Wang, Y., You, G., Chen, P., Li, J., Chen, G., Wang, B., Li, P., Han, D., Zhou,

H., & Zhao, L. (2016). The mechanical properties of stored red blood cells

measured by a convenient microfluidic approach combining with mathematic

model. Biomicrofluidics, 10(2), 024104.

21. Kwan, J. M., Guo, Q., Kyluik-Price, D. L., Ma, H., & Scott, M. D. (2013).

Microfluidic analysis of cellular deformability of normal and oxidatively

damaged red blood cells. American Journal of Hematology, 88(8), 682-689.

22. Quested, B. (2010). Who gets transfused red cells? Bloodhound on the trail!

Transfusion Fact Sheets. Retrieved on the 02/02/2018 from

http://resources.transfusion.com.au/cdm/ref/collection/p16691coll1/id/224

23. National Blood Authority. (2015). Trends in fresh blood product issues in

Australia. Retrieved on the 11/02/2018 from

https://www.blood.gov.au/pubs/2015-haemovigilance/part-05-fresh-blood-

product-use-and-haemovigilance-systems/trends-fresh-blood-product-

issues.html

24. National Blood Authority. (2013). National Blood and Blood Product Wastage

Reduction Strategy 2013 - 2017 (pp. 12). Canberrra.

25. National Blood Authority. (2017). Corporate Plan 2017-18 to 2020-21 (pp. 24).

Canberrra.

26. Czerwinska, J., Wolf, S. M., Mohammadi, H., & Jeney, S. (2015). Red Blood

Cell Aging During Storage, Studied Using Optical Tweezers Experiment.

Cellular and Molecular Bioengineering, 8(2), 258-266.

27. Ghosh, S., Chakraborty, I., Chakraborty, M., Mukhopadhyay, A., Mishra, R.,

& Sarkar, D. (2016). Evaluating the morphology of erythrocyte population: An

approach based on atomic force microscopy and flow cytometry. Biochimica

et Biophysica Acta (BBA) - Biomembranes, 1858(4), 671-681.

28. Girasole, M., Cricenti, A., Generosi, R., Congiu-Castellano, A., Boffi, F.,

Arcovito, A., Boumis, G., & Amiconi, G. (2000). Atomic force microscopy


https://www.blood.gov.au/pubs/2015-haemovigilance/part-05-fresh-blood-product-use-and-haemovigilance-systems/trends-fresh-blood-product-issues.html



References 109

study of erythrocyte shape and membrane structure after treatment with a

dihydropyridinic drug. Applied Physics Letters, 75(24), 3650-3652.

29. Lamzin, I. M., & Khayrullin, R. M. (2014). The quality assessment of stored

red blood cells probed using atomic-force microscopy. Anatomy Research

International, 2014, 1-5.

30. Park, H., Lee, S., Ji, M., Kim, K., Son, Y., Jang, S., & Park, Y. (2016).

Measuring cell surface area and deformability of individual human red blood

cells over blood storage using quantitative phase imaging. Scientific Reports,

6, 34257.

31. Bianconi, E., Piovesan, A., Facchin, F., Beraudi, A., Casadei, R., Frabetti, F.,

Vitale, L., Pelleri, M. C., Tassani, S., Piva, F., Perez-Amodio, S., Strippoli, P.,

& Canaider, S. (2013). An estimation of the number of cells in the human body.

Annals of Human Biology, 40(6), 463-471.

32. Arey, L. B. (1917). The normal shape of the mammalian red blood corpuscle.

American Journal of Anatomy, 22(3), 439-474.

33. Dean, L. (2005). Blood and the cells it contains. In National Center for

Biotechnology Information (US) (Ed.), Blood Groups and Red Cell Antigens.

Bethesda, USA.

34. Hess, J. R. (2014). Measures of stored red blood cell quality. Vox Sanguinis,

107(1), 1-9.

35. Perutz, M. F. (1965). Structure and function of haemoglobin. Journal of

Molecular Biology, 13(3), 646-668.

36. McGrath, K. E., Bushnell, T. P., & Palis, J. (2008). Multispectral imaging of

hematopoietic cells: Where flow meets morphology. Journal of Immunological

Methods, 336(2), 91-97.

37. Grasso, J. A., & Woodard, J. W. (1967). DNA Synthesis and Mitosis in

Erythropoietic Cells. The Journal of Cell Biology, 33(3), 645-655.

38. Liu, J., Guo, X., Mohandas, N., Chasis, J. A., & An, X. (2010). Membrane

remodeling during reticulocyte maturation. Blood, 115(10), 2021-2027.

39. Bosch, F. H., Werre, J. M., Schipper, L., Roerdinkholder-Stoelwinder, B.,

Huls, T., Willekens, F. L. A., Wichers, G., & Halie, M. R. (1994). Determinants

of red blood cell deformability in relation to cell age. European Journal of

Haematology, 52(1), 35-41.

40. Antonelou, M. H., Kriebardis, A. G., & Papassideri, I. S. (2010). Aging and

death signalling in mature red cells: from basic science to transfusion practice.

Blood Transfusion, 8 Suppl 3, s39-47.

41. Bosman, G. J. C. G. M., Werre, J. M., Willekens, F. L. A., & Novotny, V. M.

J. (2008). Erythrocyte ageing in vivo and in vitro: structural aspects and

implications for transfusion. Transfusion Medicine, 18(6), 335-347.

42. Bessis, M., & Mohandas, N. (1975). Red Cell Structure, Shapes and

Deformability. British Journal of Haematology, 31(s1), 5-10.

43. Brody, J. P., Han, Y., Austin, R. H., & Bitensky, M. (1995). Deformation and

flow of red blood cells in a synthetic lattice: evidence for an active

cytoskeleton. Biophysical Journal, 68(6), 2224-2232.

44. Evans, E. A., Waugh, R., & Melnik, L. (1976). Elastic area compressibility

modulus of red cell membrane. Biophysical Journal, 16(6), 585-595.

45. Verkleij, A. J., Zwaal, R. F. A., Roelofsen, B., Comfurius, P., Kastelijn, D., &

van Deenen, L. L. M. (1973). The asymmetric distribution of phospholipids in

the human red cell membrane. A combined study using phospholipases and

110 References

freeze-etch electron microscopy. Biochimica et Biophysica Acta (BBA) -

Biomembranes, 323(2), 178-193.

46. Seigneuret, M., & Devaux, P. F. (1984). ATP-dependent asymmetric

distribution of spin-labeled phospholipids in the erythrocyte membrane:

relation to shape changes. Proceedings of the National Academy of Sciences of

the United States of America, 81(12), 3751-3755.

47. Ciana, A., Achilli, C., & Minetti, G. (2014). Membrane rafts of the human red

blood cell. Molecular Membrane Biology, 31(2-3), 47-57.

48. Drabik, D., Przybyło, M., Chodaczek, G., Iglič, A., & Langner, M. (2016). The

modified fluorescence based vesicle fluctuation spectroscopy technique for

determination of lipid bilayer bending properties. Biochimica et Biophysica

Acta (BBA) - Biomembranes, 1858(2), 244-252.

49. Campanella, M. E., Chu, H., & Low, P. S. (2005). Assembly and regulation of

a glycolytic enzyme complex on the human erythrocyte membrane.

Proceedings of the National Academy of Sciences of the United States of

America, 102(7), 2402-2407.

50. Bennett, V. (1989). The spectrin-actin junction of erythrocyte membrane

skeletons. Biochimica et Biophysica Acta - Reviews on Biomembranes, 988(1),

107-121.

51. Shen, B. W., Josephs, R., & Steck, T. L. (1986). Ultrastructure of the intact

skeleton of the human erythrocyte membrane. The Journal of Cell Biology,

102(3), 997-1006.

52. Nicolas, V., Kim, C. L., Gane, P., Birkenmeier, C., Cartron, J. P., Colin, Y., &

Mouro-Chanteloup, I. (2003). Rh-RhAG/ankyrin-R, a new interaction site

between the membrane bilayer and the red cell skeleton, is impaired by Rh-

null-associated mutation. Journal of Biological Chemistry, 278(28), 25526-

25533.

53. Takakuwa, Y., Tchernia, G., Rossi, M., Benabadji, M., & Mohandas, N.

(1986). Restoration of normal membrane stability to unstable protein 4.1-

deficient erythrocyte membranes by incorporation of purified protein 4.1.

Journal of Clinical Investigation, 78(1), 80-85.

54. Mohandas, N., & Evans, E. (1994). Mechanical Properties of the Red Cell

Membrane in Relation to Molecular Structure and Genetic Defects. Annual

Review of Biophysics and Biomolecular Structure, 23(1), 787-818.

55. Sheetz, M. P. (1979). Integral membrane protein interaction with Triton

cytoskeletons of erythrocytes. Biochimica et Biophysica Acta, 557(1), 122-

134.

56. DeSilva, T. M., Peng, K. C., Speicher, K. D., & Speicher, D. W. (1992).

Analysis of human red cell spectrin tetramer (head-to-head) assembly using

complementary univalent peptides. Biochemistry, 31(44), 10872-10878.

57. An, X., Lecomte, M. C., Chasis, J. A., Mohandas, N., & Gratzer, W. (2002).

Shear-response of the spectrin dimer-tetramer equilibrium in the red blood cell

membrane. Journal of Biological Chemistry, 277(35), 31796-31800.

58. An, X., Guo, X., Zhang, X., Baines, A. J., Debnath, G., Moyo, D., Salomao,

M., Bhasin, N., Johnson, C., Discher, D., Gratzer, W. B., & Mohandas, N.

(2006). Conformational stabilities of the structural repeats of erythroid spectrin

and their functional implications. Journal of Biological Chemistry, 281(15),

10527-10532.

59. Zhu, Q., & Asaro, R. J. (2008). Spectrin Folding versus Unfolding Reactions

and RBC Membrane Stiffness. Biophysical Journal, 94(7), 2529-2545.

References 111

60. Nans, A., Mohandas, N., & Stokes, D. L. (2011). Native ultrastructure of the

red cell cytoskeleton by cryo-electron tomography. Biophysical Journal,

101(10), 2341-2350.

61. Discher, D. E., & Carl, P. (2001). New insights into red cell network structure,

elasticity, and spectrin unfolding - a current review. Cellular and Molecular

Biology Letters, 6(3), 593-606.

62. Gauthier, E., Guo, X., Mohandas, N., & An, X. (2011). Phosphorylation-

dependent perturbations of the 4.1R-associated multiprotein complex of the

erythrocyte membrane. Biochemistry, 50(21), 4561-4567.

63. Weed, R. I., LaCelle, P. L., & Merrill, E. W. (1969). Metabolic dependence of

red cell deformability. Journal of Clinical Investigation, 48(5), 795-809.

64. Bessis, M. (1972). Red cell shapes. An illustrated classification and its

rationale. Nouvelle Revue Francaise d'Hematologie, 12(6), 721-745.

65. Rand, R. P. (1964). Mechanical Properties of the Red Cell Membrane.

Biophysical Journal, 4(4), 303-316.

66. Wong, P. (1999). A Basis of Echinocytosis and Stomatocytosis in the Disc–

Sphere Transformations of the Erythrocyte. Journal of Theoretical Biology,

196(3), 343-361.

67. Rand, R. P., Burton, A. C., & Canham, P. (1965). Reversible Changes in Shape

of Red Cells in Electrical Fields. Nature, 205, 977.

68. Weed, R. I., & Bessis, M. (1973). The discocyte-stomatocyte equilibrium of

normal and pathologic red cells. Blood, 41(3), 471-475.

69. Wakeman, A. M., Eisenman, A. J., & Peters, J. P. (1927). A study of Human

Red Blood Cell Permeability Journal of Biological Chemistry, 73(2), 14.

70. Canham, P. B. (1970). The minimum energy of bending as a possible

explanation of the biconcave shape of the human red blood cell. Journal of

Theoretical Biology, 26(1), 61-81.

71. Tachev, K. D., Danov, K. D., & Kralchevsky, P. A. (2004). On the mechanism

of stomatocyte–echinocyte transformations of red blood cells: experiment and

theoretical model. Colloids and Surfaces B: Biointerfaces, 34(2), 123-140.

72. Brecher, G., & Bessis, M. (1972). Present Status of Spiculed Red Cells and

Their Relationship to the Discocyte-Echinocyte Transformation: A Critical

Review. Blood, 40(3), 333-344.

73. Eriksson, L. E. (1990). On the shape of human red blood cells interacting with

flat artificial surfaces - the 'glass effect'. Biochimica et Biophysica Acta,

1036(3), 193-201.

74. Glaser, R. (1979). The shape of red blood cells as a function of membrane

potential and temperature. Journal of Membrane Biology, 51(3-4), 217-228.

75. Isomaa, B., Hägerstrand, H., & Paatero, G. (1987). Shape transformations

induced by amphiphiles in erythrocytes. Biochimica et Biophysica Acta (BBA)

- Biomembranes, 899(1), 93-103.

76. Deuticke, B. (1968). Transformation and restoration of biconcave shape of

human erythrocytes induced by amphiphilic agents and changes of ionic

environment. Biochimica et Biophysica Acta (BBA) - Biomembranes, 163(4),

494-500.

77. Sheetz, M. P., & Singer, S. J. (1974). Biological membranes as bilayer couples.

A molecular mechanism of drug-erythrocyte interactions. Proceedings of the

National Academy of Sciences of the United States of America, 71(11), 4457-

4461.

112 References

78. Greenwalt, T. J., Sostok, C. Z., & Dumaswala, U. J. (1990). Studies in red

blood cell preservation. 2. Comparison of vesicle formation, morphology, and

membrane lipids during storage in AS-1 and CPDA-1. Vox Sanguinis, 58(2),

90-93.

79. Jaferzadeh, K., & Moon, I. (2015). Quantitative investigation of red blood cell

three-dimensional geometric and chemical changes in the storage lesion using

digital holographic microscopy. Journal of Biomedical Optics, 20(11),

111218-111218.

80. Moon, I., Yi, F., Lee, Y. H., Javidi, B., Boss, D., & Marquet, P. (2013).

Automated quantitative analysis of 3D morphology and mean corpuscular

hemoglobin in human red blood cells stored in different periods. Optics

Express, 21(25), 30947-30957.

81. Johnson, R. M., Taylor, G., & Meyer, D. B. (1980). Shape and volume changes

in erythrocyte ghosts and spectrin-actin networks. The Journal of Cell Biology,

86(2), 371-376.

82. Wong, P. (1994). Mechanism of Control of Erythrocyte Shape: A Possible

Relationship to Band 3. Journal of Theoretical Biology, 171(2), 197-205.

83. Lux, t. S. E. (2016). Anatomy of the red cell membrane skeleton: unanswered

questions. Blood, 127(2), 187-199.

84. Svoboda, K., Schmidt, C. F., Branton, D., & Block, S. M. (1992).

Conformation and elasticity of the isolated red blood cell membrane skeleton.


85. Lange, Y., Hadesman, R., & Steck, T. (1982). Role of the reticulum in the

stability and shape of the isolated human erythrocyte membrane. The Journal

of Cell Biology, 92(3), 714-721.

86. Wolosin, J. M., Ginsburg, H., & Cabantchik, Z. I. (1977). Functional

characterization of anion transport system isolated from human erythrocyte

membranes. Journal of Biological Chemistry, 252(7), 2419-2427.

87. Nakao, M. (2002). New insights into regulation of erythrocyte shape. Current

Opinion in Hematology, 9(2), 127-132.

88. Discher, D. E., Mohandas, N., & Evans, E. A. (1994). Molecular Maps of Red

Cell Deformation: Hidden Elasticity and in Situ Connectivity. Science,

266(5187), 1032-1035.

89. Heatley, S. (2010). Why is whole blood split three ways? Transfusion Fact

Sheets. Retrieved on the 02/02/2018 from


90. Müller-Steinhardt, M., Janetzko, K., Kandler, R., Flament, J., Kirchner, H., &

Klüter, H. (1997). Impact of various red cell concentrate preparation methods

on the efficiency of prestorage white cell filtration and on red cells during

storage for 42 days. Transfusion, 37(11-12), 1137-1142.

91. Sonker, A., Dubey, A., & Chaudhary, R. (2014). Evaluation of a Red Cell

Leukofilter Performance and Effect of Buffy Coat Removal on Filtration

Efficiency and Post Filtration Storage. Indian Journal of Hematology and

Blood Transfusion, 30(4), 321-327.

92. Hebert, P. C., Fergusson, D., Blajchman, M. A., Wells, G. A., & et al. (2003).

Clinical outcomes following Institution of the Canadian Universal

Leukoreduction Program for red blood cell transfusions. The Journal of the

American Medical Association, 289(15), 1941-1949.

93. Antonelou, M. H., Tzounakas, V. L., Velentzas, A. D., Stamoulis, K. E.,

Kriebardis, A. G., & Papassideri, I. S. (2012). Effects of pre-storage


References 113

leukoreduction on stored red blood cells signaling: A time-course evaluation

from shape to proteome. Journal of Proteomics, 76, 220-238.

94. The Australian Red Cross Blood Service. (2015). Additives and

anticoagulants. Retrieved on the 03/02/2018 from

https://transfusion.com.au/blood_products/components/additives_anticoagula

nts

95. The Australian Red Cross Blood Service. (2015). Blood Component

Information - An extension of blood component labels. Retrieved on the

03/02/2018 from

http://resources.transfusion.com.au/cdm/singleitem/collection/p16691coll1/id

/18/rec/1

96. Hogman, C. F., Hedlund, K., & Sahlestrom, Y. (1981). Red cell preservation

in protein-poor media. III. Protection against in vitro hemolysis. Vox

Sanguinis, 41(5-6), 274-281.

97. Beutler, E., & Kuhl, W. (1988). Volume control of erythrocytes during storage.

Transfusion, 28(4), 353-357.

98. Jarvis, H. G., Gore, D. M., Briggs, C., Chetty, M. C., & Stewart, G. W. (2003).

Cold storage of ‘cryohydrocytosis’ red cells: the osmotic susceptibility of the

cold-stored erythrocyte. British Journal of Haematology, 122(5), 859-868.

99. The Australian Red Cross Blood Service. (2016). Blood component storage

temperature range. Retrieved on the 03/02/2018 from

https://transfusion.com.au/blood_products/storage/storage_temperature_range

100. European Committee on Blood Transfusion. (2015). Guide to the Preparation,

Use and Quality Assurance of Blood Components (18th ed.). Strasbourg:

Council of Europe.

101. The Therapeutic Good Administration. (2008). Therapeutic Goods Act 1989

Therapeutic Goods Orders No 81 - Standards for Blood and Blood

Components. Retrieved from

https://www.legislation.gov.au/Details/F2008L04724

102. Hess, J. R. (2010). Red cell changes during storage. Transfusion and Apheresis

Science, 43(1), 51-59.

103. D'Alessandro, A., Gray, A. D., Szczepiorkowski, Z. M., Hansen, K., Herschel,

L. H., & Dumont, L. J. (2017). Red blood cell metabolic responses to

refrigerated storage, rejuvenation, and frozen storage. Transfusion, 57(4),

1019-1030.

104. Paglia, G., Sigurjónsson, Ó. E., Bordbar, A., Rolfsson, Ó., Magnusdottir, M.,

Palsson, S., Wichuk, K., Gudmundsson, S., & Palsson, B. O. (2016). Metabolic

fate of adenine in red blood cells during storage in SAGM solution.

Transfusion, 56(10), 2538-2547.

105. Rolfsson, O., Sigurjonsson, O. E., Magnusdottir, M., Johannsson, F., Paglia,

G., Gudmundsson, S., Bordbar, A., Palsson, S., Brynjolfsson, S.,

Gudmundsson, S., & Palsson, B. (2017). Metabolomics comparison of red cells

stored in four additive solutions reveals differences in citrate anticoagulant

permeability and metabolism. Vox Sanguinis, 112(4), 326-335.

106. Valeri, C. R., & Hirsch, N. M. (1969). Restoration in vivo of erythrocyte

adenosine triphosphate, 2,3-diphosphoglycerate, potassium ion, and sodium

ion concentrations following the transfusion of acid-citrate-dextrose-stored

human red blood cells. Journal of Laboratory and Clinical Medicine, 73(5),

722-733.

https://transfusion.com.au/blood_products/components/additives_anticoagulants

https://transfusion.com.au/blood_products/components/additives_anticoagulants

http://resources.transfusion.com.au/cdm/singleitem/collection/p16691coll1/id/18/rec/1

http://resources.transfusion.com.au/cdm/singleitem/collection/p16691coll1/id/18/rec/1

https://transfusion.com.au/blood_products/storage/storage_temperature_range

114 References

107. Kriebardis, A. G., Antonelou, M. H., Stamoulis, K. E., Economou‐Petersen,

E., Margaritis, L. H., & Papassideri, I. S. (2007). Progressive oxidation of

cytoskeletal proteins and accumulation of denatured hemoglobin in stored red

cells. Journal of Cellular and Molecular Medicine, 11(1), 148-155.

108. Wither, M., Dzieciatkowska, M., Nemkov, T., Strop, P., D'Alessandro, A., &

Hansen, K. C. (2016). Hemoglobin oxidation at functional amino acid residues

during routine storage of red blood cells. Transfusion, 56(2), 421-426.

109. Willekens, F. L. A., Werre, J. M., Bosman, G. J. C. G. M., & Novotny, V. M.

J. (2008). Erythrocyte ageing in vivo and in vitro: structural aspects and

implications for transfusion. Transfusion Medicine, 18(6), 335-347.

110. Sinha, A., Chu, T. T. T., Dao, M., & Chandramohanadas, R. (2015). Single-

cell evaluation of red blood cell bio-mechanical and nano-structural alterations

upon chemically induced oxidative stress. Scientific Reports, 5, 9768.

111. Blasi, B., D’Alessandro, A., Ramundo, N., & Zolla, L. (2012). Red blood cell

storage and cell morphology. Transfusion Medicine, 22(2), 90-96.

112. Roussel, C., Dussiot, M., Marin, M., Morel, A., Ndour, P. A., Duez, J., Le Van

Kim, C., Hermine, O., Colin, Y., Buffet, P. A., & Amireault, P. (2017).

Spherocytic shift of red blood cells during storage provides a quantitative

whole cell-based marker of the storage lesion. Transfusion, 57(4), 1007-1018.

113. Sparrow, R. L., Sran, A., Healey, G., Veale, M. F., & Norris, P. J. (2014). In

vitro measures of membrane changes reveal differences between red blood

cells stored in saline-adenine-glucose-mannitol and AS-1 additive solutions: a

paired study. Transfusion, 54(3), 560-568.

114. Delobel, J., Barelli, S., Canellini, G., Prudent, M., Lion, N., & Tissot, J. D.

(2016). Red blood cell microvesicles: a storage lesion or a possible salvage

mechanism. ISBT Science Series, 11, 171-177.

115. Kriebardis, A. G., Antonelou, M. H., Stamoulis, K. E., Economou-Petersen,

E., Margaritis, L. H., & Papassideri, I. S. (2008). RBC-derived vesicles during

storage: Ultrastructure, protein composition, oxidation, and signaling

components. Transfusion, 48(9), 1943-1953.

116. Matthews, K., Myrand-Lapierre, M.-E., Ang, R. R., Duffy, S. P., Scott, M. D.,

& Ma, H. (2015). Microfluidic deformability analysis of the red cell storage

lesion. Journal of Biomechanics, 48(15), 4065-4072.

117. Frank, S. M., Abazyan, B., Ono, M., Hogue, C. W., Cohen, D. B., Berkowitz,

D. E., Ness, P. M., & Barodka, V. M. (2013). Decreased erythrocyte

deformability after transfusion and the effects of erythrocyte storage duration.

Anesthesia and Analgesia, 116(5), 975-981.

118. Berezina, T. L., Zaets, S. B., Morgan, C., Spillert, C. R., Kamiyama, M.,

Spolarics, Z., Deitch, E. A., & Machiedo, G. W. (2002). Influence of Storage

on Red Blood Cell Rheological Properties. Journal of Surgical Research,

102(1), 6-12.

119. Safeukui, I., Buffet, P. A., Deplaine, G., Perrot, S., Brousse, V., Ndour, A.,

Nguyen, M., Mercereau-Puijalon, O., David, P. H., Milon, G., & Mohandas,

N. (2012). Quantitative assessment of sensing and sequestration of spherocytic

erythrocytes by the human spleen. Blood, 120(2), 424-430.

120. Rapido, F. (2017). The potential adverse effects of haemolysis. Blood

Transfusion, 15(3), 218-221.

121. Karafin, M. S., Carpenter, E., Pan, A., Simpson, P., & Field, J. J. (2017). Older

red cell units are associated with an increased incidence of infection in

References 115

chronically transfused adults with sickle cell disease. Transfusion and

Apheresis Science, 56(3), 345-351.

122. Chadebech, P., Bodivit, G., Razazi, K., de Vassoigne, C., Pelle, L., Burin-des-

Roziers, N., Bocquet, T., Bierling, P., Djoudi, R., Mekontso-Dessap, A., &

Pirenne, F. (2017). Red blood cells for transfusion in patients with sepsis:

respective roles of unit age and exposure to recipient plasma. Transfusion,

57(8), 1898-1904.

123. Desmarets, M., Bardiaux, L., Benzenine, E., Dussaucy, A., Binda, D.,

Tiberghien, P., Quantin, C., & Monnet, E. (2016). Effect of storage time and

donor sex of transfused red blood cells on 1-year survival in patients

undergoing cardiac surgery: an observational study. Transfusion, 56(5), 1213-

1222.

124. Peters, A. L., Beuger, B., Mock, D. M., Widness, J. A., de Korte, D.,

Juffermans, N. P., Vlaar, A. P. J., & van Bruggen, R. (2016). Clearance of

stored red blood cells is not increased compared with fresh red blood cells in a

human endotoxemia model. Transfusion, 56(6), 1362-1369.

125. Garraud, O. (2017). Clinical trials in Transfusion Medicine and hemotherapy:

Worth moving forward in evaluating ‘fresh’ versus ‘old’ blood cell

components? Transfusion and Apheresis Science, 56(1), 98-99.

126. Francis, R. O., & Hod, E. A. (2017). The questions surrounding stored blood

do not get old. Transfusion, 57(6), 1328-1331.

127. Remy, K. E., Sun, J., Wang, D., Welsh, J., Solomon, S. B., Klein, H. G.,

Natanson, C., & Cortés-Puch, I. (2016). Transfusion of recently donated (fresh)

red blood cells (RBCs) does not improve survival in comparison with current

practice, while safety of the oldest stored units is yet to be established: a meta-

analysis. Vox Sanguinis, 111(1), 43-54.

128. Liumbruno, G. M., & AuBuchon, J. P. (2010). Old blood, new blood or better

stored blood? Blood Transfusion, 8(4), 217-219.

129. D’Alessandro, A., & Seghatchian, J. (2017). Hitchhiker's guide to the red cell

storage galaxy: Omics technologies and the quality issue. Transfusion and

Apheresis Science, 56(2), 248-253.

130. Hess, J. R., Sparrow, R. L., Van der Meer, P. F., Acker, J. P., Cardigan, R. A.,

& Devine, D. V. (2009). Red blood cell hemolysis during blood bank storage:

using national quality management data to answer basic scientific questions.

Transfusion, 49(12), 2599-2603.

131. Tzounakas, V. L., Kriebardis, A. G., Papassideri, I. S., & Antonelou, M. H.

(2016). Donor-variation effect on red blood cell storage lesion: A close

relationship emerges. Proteomics – Clinical Applications, 10(8), 791-804.

132. Tzounakas, V. L., Georgatzakou, H. T., Kriebardis, A. G., Voulgaridou, A. I.,

Stamoulis, K. E., Foudoulaki-Paparizos, L. E., Antonelou, M. H., &

Papassideri, I. S. (2016). Donor variation effect on red blood cell storage

lesion: a multivariable, yet consistent, story. Transfusion, 56(6), 1274-1286.

133. Piety, N. Z., Gifford, S. C., Yang, X., & Shevkoplyas, S. S. (2015). Quantifying

morphological heterogeneity: a study of more than 1 000 000 individual stored

red blood cells. Vox Sanguinis, 109(3), 221-230.

134. Allen, T. D. (2015). Microscopy: a very short introduction (First ed.). Oxford,

United Kingdom: Oxford University Press.

135. Pawley, J. (2006). Handbook of Biological Confocal Microscopy. Boston, MA:

Springer US.

116 References

136. Khairy, K., Foo, J., & Howard, J. (2008). Shapes of Red Blood Cells:

Comparison of 3D Confocal Images with the Bilayer-Couple Model. Cellular

and Molecular Bioengineering, 1(2), 173-181.

137. Rappaz, B., Barbul, A., Emery, Y., Korenstein, R., Depeursinge, C.,

Magistretti, P. J., & Marquet, P. (2008). Comparative study of human

erythrocytes by digital holographic microscopy, confocal microscopy, and

impedance volume analyzer. Cytometry. Part A, 73A(10), 895-903.

138. Kremer, A., Lippens, S., Bartunkova, S., Asselbergh, B., Blanpain, C.,

Fendrych, M., Goossens, A., Holt, M., Janssens, S., Krols, M., Larsimont, J.

C., Mc Guire, C., Nowack, M. K., Saelens, X., Schertel, A., Schepens, B.,

Slezak, M., Timmerman, V., Theunis, C., Van Brempt, R., Visser, Y., &

Guerin, C. J. (2015). Developing 3D SEM in a broad biological context.

Journal of Microscopy, 259(2), 80-96.

139. Longster, G. H., Buckley, T., Sikorski, J., & Derrick Tovey, L. A. (1972).

Scanning electron microscope studies of red cell morphology. Changes

occurring in red cell shape during storage and post transfusion. Vox Sanguinis,

22(2), 161-170.

140. D’Alessandro, A., D’Amici, G. M., Vaglio, S., & Zolla, L. (2012). Time-course

investigation of SAGM-stored leukocyte-filtered red bood cell concentrates:

from metabolism to proteomics. Haematologica, 97(1), 107-115.

141. Evans, E., & Fung, Y. C. (1972). Improved measurements of the erythrocyte

geometry. Microvascular Research, 4(4), 335-347.

142. Jay, A. W. (1975). Geometry of the human erythrocyte. I. Effect of albumin on

cell geometry. Biophysical Journal, 15(3), 205-222.

143. Eskelinen, S., & Saukko, P. (1983). Effects of glutaraldehyde and critical point

drying on the shape and size of erythrocytes in isotonic and hypotonic media.

Journal of Microscopy, 130(Pt 1), 63-71.

144. Squier, C. A., Hart, J. S., & Churchland, A. (1976). Changes in red blood cell

volume on fixation in glutaraldehyde solutions. Histochemistry, 48(1), 7-16.

145. Cluitmans, J. C. A., Venkatachalam, C., Janssen, A. M., Brock, R., Huck, W.

T. S., & Giel, J. C. G. M. B. (2014). Alterations in Red Blood Cell

Deformability during Storage: A Microfluidic Approach. BioMed Research

International.

146. Rand, R. (1964). Mechanical Properties of the Red Cell Membrane - I.

Membrane Stiffness and Intracellular Pressure. Biophysical Journal, 4(2), 115-

135.

147. Discher, D. E., & Mohandas, N. (1996). Kinematics of red cell aspiration by

fluorescence-imaged microdeformation. Biophysical Journal, 71(4), 1680-

1694.

148. A-Hassan, E., Heinz, W. F., Antonik, M. D., D’Costa, N. P., Nageswaran, S.,

Schoenenberger, C.-A., & Hoh, J. H. (1998). Relative Microelastic Mapping

of Living Cells by Atomic Force Microscopy. Biophysical Journal, 74(3),

1564-1578.

149. Lekka, M., Fornal, M., Pyka-Fościak, G., Lebed, K., Wizner, B., Grodzicki,

T., & Styczeń, J. (2005). Erythrocyte stiffness probed using atomic force

microscope. Biorheology, 42(4), 307-317.

150. Bremmell, K. E., Evans, A., & Prestidge, C. A. (2006). Deformation and nano-

rheology of red blood cells: An AFM investigation. Colloids and Surfaces B:

Biointerfaces, 50(1), 43-48.

References 117

151. Melzak, K. A., Lazaro, G. R., Hernandez-Machado, A., Pagonabarraga, I.,

Cardenas Diaz de Espada, J. M., & Toca-Herrera, J. L. (2012). AFM

measurements and lipid rearrangements: evidence from red blood cell shape

changes. Soft Matter, 8(29), 7716-7726.

152. Khalisov, M. M., Timoshchuk, K. I., Ankudinov, A. V., & Timoshenko, T. E.

(2017). Atomic force microscopy of swelling and hardening of intact

erythrocytes fixed on substrate. Technical Physics, 62(2), 310-313.

153. Hategan, A., Law, R., Kahn, S., & Discher, D. E. (2003). Adhesively-Tensed

Cell Membranes: Lysis Kinetics and Atomic Force Microscopy Probing.


154. Isaac, C. D. L., Alexander, B. S., Halina, R.-D., & Timo, A. N. (2017). Visual

guide to optical tweezers. European Journal of Physics, 38(3), 034009.

155. Svoboda, K., & Block, S. M. (1994). Biological Applications of Optical

Forces. Annual Review of Biophysics and Biomolecular Structure, 23(1), 247-

285.

156. Henon, S., Lenormand, G., Richert, A., & Gallet, F. (1999). A new

determination of the shear modulus of the human erythrocyte membrane using

optical tweezers. Biophysical Journal, 76(2), 1145-1151.

157. Sleep, J., Wilson, D., Simmons, R., & Gratzer, W. (1999). Elasticity of the Red

Cell Membrane and Its Relation to Hemolytic Disorders: An Optical Tweezers

Study. Biophysical Journal, 77(6), 3085-3095.

158. Dao, M., Lim, C. T., & Suresh, S. (2003). Mechanics of the human red blood

cell deformed by optical tweezers. Journal of the Mechanics and Physics of

Solids, 51(11–12), 2259-2280.

159. Mills, J. P., Qie, L., Dao, M., Lim, C. T., & Suresh, S. (2004). Nonlinear elastic

and viscoelastic deformation of the human red blood cell with optical tweezers.

Mechanics & Chemistry of Biosystems, 1(3), 169-180.

160. Soni, H., Khan, M., & Sood, A. (2009). Optical tweezer for probing erythrocyte

membrane deformability. Applied Physics Letters, 95(23), 233703-233703-

233703.

161. Fontes, A., Castro, M. L. B., Brandão, M. M., Fernandes, H. P., Thomaz, A.

A., Huruta, R. R., Pozzo, L. Y., Barbosa, L. C., Costa, F. F., Saad, S. T. O., &

Cesar, C. L. (2011). Mechanical and electrical properties of red blood cells

using optical tweezers. Journal of Optics, 13(4), 044012.

162. Antonelou, M. H., & Seghatchian, J. (2016). Insights into red blood cell storage

lesion: Toward a new appreciation. Transfusion and Apheresis Science, 55(3),

292-301.

163. Holme, S. (2005). Current issues related to the quality of stored RBCs.

Transfusion and Apheresis Science, 33(1), 55-61.

164. Bordbar, A., Johansson, P. I., Paglia, G., Harrison, S. J., Wichuk, K.,

Magnusdottir, M., Valgeirsdottir, S., Gybel-Brask, M., Ostrowski, S. R.,

Palsson, S., Rolfsson, O., Sigurjónsson, O. E., Hansen, M. B., Gudmundsson,

S., & Palsson, B. O. (2016). Identified metabolic signature for assessing red

blood cell unit quality is associated with endothelial damage markers and

clinical outcomes. Transfusion, 56(4), 852-862.

165. The Australian & New Zealand Society of Blood Transfusion. (2016).

Guidelines for transfusion and immunohaematology laboratory practice: The

Transfusion Science Standing Committee. Sydney. Retrieved from

https://www.anzsbt.org.au/pages/anzsbt-guidelines.html

118 References

166. Handin, R. I., Lux, S. E., & Stossel, T. P. (2003). Blood: principles and

practice of hematology (Vol. 2nd). Philadelphia, Pa: Lippincott Williams &

Wilkins.

167. Sigma-Aldrich. (2017). Blood Basics - Plasma and Blood Protein Ressource.

Retrieved on the 05/10/2017 from http://www.sigmaaldrich.com/life-

science/metabolomics/enzyme-explorer/learning-center/plasma-blood-

protein/blood-basics.html

168. Cookson, P., Sutherland, J., & Cardigan, R. (2004). A simple

spectrophotometric method for the quantification of residual haemoglobin in

platelet concentrates. Vox Sanguinis, 87(4), 264-271.

169. Sowemimo-Coker, S. O. (2002). Red blood cell hemolysis during processing.

Transfusion Medicine Reviews, 16(1), 46-60.

170. Sigma-Aldrich. (2000). Bovin Serum Albumin - Product Information.

Retrieved on the 07/03/2018 from

https://www.sigmaaldrich.com/content/dam/sigma-

aldrich/docs/Sigma/Product_Information_Sheet/a2153pis.pdf

171. Laerd Statistics. (2015). Statistical tutorials and software guides. Retrieved

on the 28/03/2017 from https://statistics.laerd.com/

172. Owen, J. S., Brown, D. J., Harry, D. S., McIntyre, N., Beaven, G. H., Isenberg,

H., & Gratzer, W. B. (1985). Erythrocyte echinocytosis in liver disease. Role

of abnormal plasma high density lipoproteins. Journal of Clinical

Investigation, 76(6), 2275-2285.

173. Zehnder, L., Schulzki, T., Goede, J. S., Hayes, J., & Reinhart, W. H. (2008).

Erythrocyte storage in hypertonic (SAGM) or isotonic (PAGGSM)

conservation medium: influence on cell properties. Vox Sanguinis, 95(4), 280-

287.

174. Gevi, F., D'Alessandro, A., Rinalducci, S., & Zolla, L. (2012). Alterations of

red blood cell metabolome during cold liquid storage of erythrocyte

concentrates in CPD–SAGM. Journal of Proteomics, 76(Supplement C), 168-

180.

175. Keegan, T. E., Heaton, A., Holme, S., Owens, M., & Nelson, E. J. (1992).

Improved post-transfusion quality of density separated AS-3 red cells after

extended storage. British Journal of Haematology, 82(1), 114-121.

176. Picot, J., Ndour, P. A., Lefevre, S. D., El Nemer, W., Tawfik, H., Galimand,

J., Da Costa, L., Ribeil, J. A., de Montalembert, M., Brousse, V., Le Pioufle,

B., Buffet, P., Le Van Kim, C., & Français, O. (2015). A biomimetic

microfluidic chip to study the circulation and mechanical retention of red blood

cells in the spleen. American Journal of Hematology, 90(4), 339-345.

177. Bennett-Guerrero, E., Veldman, T. H., Doctor, A., Telen, M. J., Ortel, T. L.,

Reid, T. S., Mulherin, M. A., Zhu, H., Buck, R. D., Califf, R. M., & McMahon,

T. J. (2007). Evolution of adverse changes in stored RBCs. Proceedings of the


17068.

178. Wallas, C. H. (1979). Sodium and potassium changes in blood bank stored

human erythrocytes. Transfusion, 19(2), 210-215.

179. Dumont, L. J., AuBuchon, J. P., & Biomedical Excellence for Safer

Transfusion, C. (2008). Evaluation of proposed FDA criteria for the evaluation

of radiolabeled red cell recovery trials. Transfusion, 48(6), 1053-1060.

http://www.sigmaaldrich.com/life-science/metabolomics/enzyme-explorer/learning-center/plasma-blood-protein/blood-basics.html



https://www.sigmaaldrich.com/content/dam/sigma-aldrich/docs/Sigma/Product_Information_Sheet/a2153pis.pdf

https://www.sigmaaldrich.com/content/dam/sigma-aldrich/docs/Sigma/Product_Information_Sheet/a2153pis.pdf

https://statistics.laerd.com/

References 119

180. Blood Products Advisory Committee. (2004). Irradiated RBC acceptance

criteria. Retrieved on the 01/12/2017 from

http://www.fda.gov/ohrms/dockets/ac/04/transcripts/2004-4057t1.htm

181. Bosch, F. H., Werre, J. M., Roerdinkholder-Stoelwinder, B., Huls, T. H.,

Willekens, F. L., & Halie, M. R. (1992). Characteristics of red blood cell

populations fractionated with a combination of counterflow centrifugation and

Percoll separation. Blood, 79(1), 254-260.

182. Coulter, W. H. (2000). High Speed Automatic Blood Cell Counter and Cell

Size Analyzer Hematology : Landmark Papers of the Twentieth Century

(Elsevier Science ed., pp. 913 - 921). Burlington, USA.

183. Coetzee, J., & van der Merwe, C. F. (1985). Penetration rate of glutaraldehyde

in various buffers into plant tissue and gelatin gels. Journal of Microscopy,

137(2), 129-136.

184. Han, V., Serrano, K., & Devine, D. V. (2010). A comparative study of common

techniques used to measure haemolysis in stored red cell concentrates. Vox

Sanguinis, 98(2), 116-123.

185. Arduini, A., Minetti, G., Ciana, A., Seppi, C., Brovelli, A., Profumo, A.,

Vercellati, C., Zappa, M., Zanella, A., Dottori, S., & Bonomini, M. (2007).

Cellular properties of human erythrocytes preserved in saline-adenine-

glucose-mannitol in the presence of L-carnitine. American Journal of

Hematology, 82(1), 31-40.

186. Brugnara, C., & Churchill, W. H. (1992). Effect of irradiation on red cell cation

content and transport. Transfusion, 32(3), 246-252.

187. Henkelman, S., Dijkstra-Tiekstra, M. J., de Wildt-Eggen, J., Graaff, R.,

Rakhorst, G., & van Oeveren, W. (2010). Is red blood cell rheology preserved

during routine blood bank storage? Transfusion, 50(4), 941-948.

188. Högman, C. F., Löf, H., & Meryman, H. T. (2006). Storage of red blood cells

with improved maintenance of 2,3‐bisphosphoglycerate. Transfusion, 46(9),

1543-1552.

189. Huang, Y. X., Wu, Z. J., Mehrishi, J., Huang, B. T., Chen, X. Y., Zheng, X. J.,

Liu, W. J., & Luo, M. (2011). Human red blood cell aging: correlative changes

in surface charge and cell properties. Journal of Cellular and Molecular

Medicine, 15(12), 2634-2642.

190. Ponder, E. (1930). The measurement of the diameter of erythrocytes. V. The

relation of the diameter to the thickness. Quarterly Journal of Experimental

Physiology, 20(1), 29-39.

191. Baghaie, A., Tafti, A. P., Owen, H. A., D'Souza, R. M., & Yu, Z. (2017). SD-

SEM: sparse-dense correspondence for 3D reconstruction of microscopic

samples. Micron, 97, 41-55.

192. Morel, F. M., Baker, R. F., & Wayland, H. (1971). Quantitation of human red

blood cell fixation by glutaraldehyde. The Journal of Cell Biology, 48(1), 91-

100.

193. Wood, S. T., Dean, B. C., & Dean, D. (2013). A linear programming approach

to reconstructing subcellular structures from confocal images for automated

generation of representative 3D cellular models. Medical Image Analysis,

17(3), 337-347.

194. Fedosov, D. A., Caswell, B., & Karniadakis, G. E. (2010). A multiscale red

blood cell model with accurate mechanics, rheology, and dynamics.


http://www.fda.gov/ohrms/dockets/ac/04/transcripts/2004-4057t1.htm

120 References

195. Salehyar, S., & Zhu, Q. (2016). Deformation and internal stress in a red blood

cell as it is driven through a slit by an incoming flow. Soft Matter, 12(13),

3156-3164.

196. Polwaththe-Gallage, H.-N., Saha, S. C., & Gu, Y. (2014). Deformation of a

three-dimensional red blood cell in a stenosed micro-capillary. Paper presented

at the 8th Australasian Congress on Applied Mechanics, Melbourne, Australia.

197. Waters, J. C. (2009). Accuracy and Precision in Quantitative Fluorescence

Microscopy. The Journal of Cell Biology, 185(7), 1135-1148.

198. Prakash, Y. S., Smithson, K. G., & Sieck, G. C. (1993). Measurements of

Motoneuron Somal Volumes Using Laser Confocal Microscopy: Comparisons

with Shape-Based Stereological Estimations. NeuroImage, 1(2), 95-107.

199. Pawley, J. (2006). Foundations of Confocal Scanned Imaging in Light

Microscopy Handbook of Biological Confocal Microscopy. Boston, MA:

Springer US.

200. Bucher, I. (2005). Circle fit (Version 1.0). Retrieved from MATLAB Central

File Exchange, on the 02/01/2018,

https://au.mathworks.com/matlabcentral/fileexchange/5557-circle-

fit?s_tid=gn_loc_drop

201. Petrov, Y. (2015). Ellipsoid fit (Version 1.3). Retrieved from MATLAB

Central File Exchange, on the 02/01/2018,

https://au.mathworks.com/matlabcentral/fileexchange/24693-ellipsoid-fit

202. Corsini, M., Cignoni, P., & Scopigno, R. (2012). Efficient and Flexible

Sampling with Blue Noise Properties of Triangular Meshes. IEEE

Transactions on Visualization and Computer Graphics, 18(6), 914-924.

203. Kazhdan, M., & Hoppe, H. (2013). Screened poisson surface reconstruction.

Association for Computing Machinery Transactions on Graphics, 32(3), 1-13.

204. Canham, P. B., & Burton, A. C. (1968). Distribution of Size and Shape in

Populations of Normal Human Red Cells. Circulation Research, 22(3), 405-

422.

205. Park, Y., Best, C. A., Badizadegan, K., Dasari, R. R., Feld, M. S., Kuriabova,

T., Henle, M. L., Levine, A. J., & Popescu, G. (2010). Measurement of red

blood cell mechanics during morphological changes. Proceedings of the


6736.

206. Hoffman, J. F. (1987). On the mechanism and measurement of shape

transformations of constant volume of human red blood cells. Blood Cells,

12(3), 565-588.

207. Gedde, M., Yang, E., & Huestis, W. (1995). Shape response of human

erythrocytes to altered cell pH. Blood, 86(4), 1595-1599.

208. Nakao, M., Hoshino, K., & Nakao, T. (1981). Constancy of cell volume during

shape change of erythrocytes induced by increasing ATP content. Journal of

Bioenergetics and Biomembranes, 13(5), 307-316.

209. Buys, A. V., Van Rooy, M. J., Soma, P., Van Papendorp, D., Lipinski, B., &

Pretorius, E. (2013). Changes in red blood cell membrane structure in type 2

diabetes: a scanning electron and atomic force microscopy study.

Cardiovascular Diabetology, 12, 25.

210. Ciasca, G., Papi, M., Di Claudio, S., Chiarpotto, M., Palmieri, V., Maulucci,

G., Nocca, G., Rossi, C., & De Spirito, M. (2015). Mapping viscoelastic

properties of healthy and pathological red blood cells at the nanoscale level.

Nanoscale, 7(40), 17030-17037.

https://au.mathworks.com/matlabcentral/fileexchange/5557-circle-fit?s_tid=gn_loc_drop

https://au.mathworks.com/matlabcentral/fileexchange/5557-circle-fit?s_tid=gn_loc_drop

https://au.mathworks.com/matlabcentral/fileexchange/24693-ellipsoid-fit

References 121

211. Dulińska, I., Targosz, M., Strojny, W., Lekka, M., Czuba, P., Balwierz, W., &

Szymoński, M. (2006). Stiffness of normal and pathological erythrocytes

studied by means of atomic force microscopy. Journal of Biochemical and

Biophysical Methods, 66(1–3), 1-11.

212. Girasole, M., Dinarelli, S., & Boumis, G. (2012). Structure and function in

native and pathological erythrocytes: a quantitative view from the nanoscale.

Micron, 43(12), 1273-1286.

213. Hayashi, K., & Iwata, M. (2015). Stiffness of cancer cells measured with an

AFM indentation method. Journal of the Mechanical Behavior of Biomedical

Materials, 49, 105-111.

214. Kamruzzahan, A. S. M., Kienberger, F., Stroh, C. M., Berg, J., Huss, R., Ebner,

A., Zhu, R., Rankl, C., Gruber, H. J., & Hinterdorfer, P. (2004). Imaging

morphological details and pathological differences of red blood cells using

tapping-mode AFM. Biological chemistry, 385(10), 955-960.

215. Li, M., Liu, L., Xi, N., Wang, Y., Dong, Z., Xiao, X., & Zhang, W. (2012).

Atomic force microscopy imaging and mechanical properties measurement of

red blood cells and aggressive cancer cells. Science China Life Sciences,

55(11), 968-973.

216. Glaubitz, M., Medvedev, N., Pussak, D., Hartmann, L., Schmidt, S., Helm, C.

A., & Delcea, M. (2014). A novel contact model for AFM indentation

experiments on soft spherical cell-like particles. Soft Matter, 10(35), 6732-

6741.

217. Maciaszek, J. L., & Lykotrafitis, G. (2011). Sickle cell trait human erythrocytes

are significantly stiffer than normal. Journal of Biomechanics, 44(4), 657-661.

218. Scheffer, L., Bitler, A., Ben-jacob, E., & Korenstein, R. (2001). Atomic force

pulling: probing the local elasticity of the cell membrane. European Biophysics

Journal, 30(2), 83-90.

219. Girasole, M., Cricenti, A., Generosi, R., Congiu‐Castellano, A., Boumis, G., &

Amiconi, G. (2001). Artificially induced unusual shape of erythrocytes: an

atomic force microscopy study. Journal of Microscopy, 204(1), 46-52.

220. Carl, P., & Schillers, H. (2008). Elasticity measurement of living cells with an

atomic force microscope: data acquisition and processing. Pflugers Archiv -

European Journal of Physiology, 457(2), 551-559.

221. Sen, S., Subramanian, S., & Discher, D. E. (2005). Indentation and adhesive

probing of a cell membrane with AFM: theoretical model and experiments.


222. Dimitriadis, E. K., Horkay, F., Maresca, J., Kachar, B., & Chadwick, R. S.

(2002). Determination of elastic moduli of thin layers of soft material using the

atomic force microscope. Biophysical Journal, 82(5), 2798-2810.

223. Hategan, A., Sengupta, K., Kahn, S., Sackmann, E., & Discher, D. E. (2004).

Topographical Pattern Dynamics in Passive Adhesion of Cell Membranes.


224. Forsyth, A. M., Wan, J., Ristenpart, W. D., & Stone, H. A. (2010). The

dynamic behavior of chemically “stiffened” red blood cells in microchannel

flows. Microvascular Research, 80(1), 37-43.

225. Fuqian, Y. (2003). Axisymmetric indentation of an incompressible elastic thin

film. Journal of Physics D: Applied Physics, 36(1), 50.

226. Friedlander, M. H., Simon, R., & Machiedo, G. W. (1998). The relationship of

packed cell transfusion to red blood cell deformability in systemic

inflammatory response syndrome patients. Shock, 9(2), 84-88.

122 References

227. Liu, F., Burgess, J., Mizukami, H., & Ostafin, A. (2003). Sample preparation

and imaging of erythrocyte cytoskeleton with the atomic force microscopy.

Cell Biochemistry and Biophysics, 38(3), 251-270.

228. Bui, A., Kashchuk, A., Balanant, M. A., Nieminen, T., Rubinsztein-Dunlop,

H., & Stilgoe, A. (2018). Absolute calibration of arbitrarily shaped particles in

optical tweezers (under review).

229. Shevkoplyas, S. S., Yoshida, T., Gifford, S. C., & Bitensky, M. W. (2006).

Direct measurement of the impact of impaired erythrocyte deformability on

microvascular network perfusion in a microfluidic device. Lab on a Chip, 6(7),

914-920.

230. Li, Y., Wen, C., Xie, H., Ye, A., & Yin, Y. (2009). Mechanical property

analysis of stored red blood cell using optical tweezers. Colloids and Surfaces

B: Biointerfaces, 70(2), 169-173.

231. Wu, J., Li, Y., Lu, D., Liu, Z., Cheng, Z., & He, L. (2009). Measurement of the

Membrane Elasticity of Red Blood Cell with Osmotic Pressure by Optical

Tweezers. Cryoletters, 30(2), 89-95.

232. Tan, Y., Sun, D., Wang, J., & Huang, W. (2010). Mechanical Characterization

of Human Red Blood Cells Under Different Osmotic Conditions by Robotic

Manipulation With Optical Tweezers. IEEE Transactions on Biomedical

Engineering, 57(7), 1816-1825.

233. Liao, G.-B., Bareil, P. B., Sheng, Y., & Chiou, A. (2008). One-dimensional

jumping optical tweezers for optical stretching of bi-concave human red blood

cells. Optics Express, 16(3), 1996-2004.

234. Agrawal, R., Smart, T., Nobre-Cardoso, J., Richards, C., Bhatnagar, R., Tufail,

A., Shima, D., Jones, P. H., & Pavesio, C. (2016). Assessment of red blood cell

deformability in type 2 diabetes mellitus and diabetic retinopathy by dual

optical tweezers stretching technique. Scientific Reports, 6, 15873.

235. Bronkhorst, P. J., Streekstra, G. J., Grimbergen, J., Nijhof, E. J., Sixma, J. J.,

& Brakenhoff, G. J. (1995). A new method to study shape recovery of red blood

cells using multiple optical trapping. Biophysical Journal, 69(5), 1666-1673.

236. Bhaduri, B., Kandel, M., Brugnara, C., Tangella, K., & Popescu, G. (2014).

Optical assay of erythrocyte function in banked blood. Scientific Reports, 4,

6211.

237. Prado, G., Farutin, A., Misbah, C., & Bureau, L. (2015). Viscoelastic Transient

of Confined Red Blood Cells. Biophysical Journal, 108(9), 2126-2136.

238. Shin, S., Ku, Y., Park, M. S., & Suh, J. S. (2005). Slit-flow ektacytometry: laser

diffraction in a slit rheometer. Cytometry. Part B, Clinical cytometry, 65(1), 6-

13.

239. Rodríguez-García, R., López-Montero, I., Mell, M., Egea, G., Gov, Nir S., &

Monroy, F. (2015). Direct Cytoskeleton Forces Cause Membrane Softening in

Red Blood Cells. Biophysical Journal, 108(12), 2794-2806.

240. Park, Y., Best, C. A., Auth, T., Gov, N. S., Safran, S. A., Popescu, G., Suresh,

S., & Feld, M. S. (2010). Metabolic remodeling of the human red blood cell

membrane. Proceedings of the National Academy of Sciences of the United

States of America, 107(4), 1289-1294.

241. Betz, T., Lenz, M., Joanny, J.-F., Sykes, C., & Pollard, T. D. (2009). ATP-

Dependent Mechanics of Red Blood Cells. Proceedings of the National

Academy of Sciences of the United States of America, 106(36), 15320-15325.

242. Tuvia, S., Almagor, A., Bitler, A., Levin, S., Korenstein, R., & Yedgar, S.

(1997). Cell Membrane Fluctuations are Regulated by Medium

References 123

Macroviscosity: Evidence for a Metabolic Driving Force. Proceedings of the


5049.

243. Ortiz, V., Nielsen, S. O., Klein, M. L., & Discher, D. E. (2005). Unfolding a

linker between helical repeats. Journal of Molecular Biology, 349(3), 638-647.

244. Nagababu, E., Scott, A. V., Johnson, D. J., Dwyer, I. M., Lipsitz, J. A.,

Barodka, V. M., Berkowitz, D. E., & Frank, S. M. (2016). Oxidative stress and

rheologic properties of stored red blood cells before and after transfusion to

surgical patients. Transfusion, 56(5), 1101-1111.

245. Kriebardis, Anastasios G., Antonelou, Marianna H., Stamoulis,

Konstantinos E., Economou-Petersen, E., Margaritis, Lukas H., & Papassideri,

Issidora S. (2007). Storage-dependent remodeling of the red blood cell

membrane is associated with increased immunoglobulin G binding, lipid raft

rearrangement, and caspase activation. Transfusion, 47(7), 1212-1220.

246. Fischer, T. M., Haest, C. W. M., Stöhr, M., Kamp, D., & Deuticke, B. (1978).

Selective alteration of erythrocyte deformability by SH-reagents. Evidence for

an involvement of spectrin in membrane shear elasticity. Biochimica et

Biophysica Acta (BBA) - Biomembranes, 510(2), 270-282.

247. Gov, N. S., & Safran, S. A. (2005). Red Blood Cell Membrane Fluctuations

and Shape Controlled by ATP-Induced Cytoskeletal Defects. Biophysical

Journal, 88(3), 1859-1874.

248. Krieger, C. C., An, X., Tang, H.-Y., Mohandas, N., Speicher, D. W., &

Discher, D. E. (2011). Cysteine shotgun—mass spectrometry (CS-MS) reveals

dynamic sequence of protein structure changes within mutant and stressed

cells. Proceedings of the National Academy of Sciences of the United States of

America, 108(20), 8269-8274.

249. Guz, N., Dokukin, M., Kalaparthi, V., & Sokolov, I. (2014). If Cell Mechanics

Can Be Described by Elastic Modulus: Study of Different Models and Probes

Used in Indentation Experiments. Biophysical Journal, 107(3), 564-575.

124 Appendices

Appendices

Appendix A- Ethics approval - The Blood Service Human Research Ethics

Committee

Appendices 125

126 Appendices

Appendix B - Ethics approval - QUT University Human Research Ethics

Committee

Appendices 127

experimental studies of red blood cells ......composition has, not only on rbc metabolism and...

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