Proteomic analysis of Enterococcus faecalis cell

membrane proteins under alkaline stress conditions

A Thesis submitted in fulfilment of the requirements for

admission to the degree of Doctor of Philosophy

Peter Cathro

MDS, Cert Tert T

School of Dentistry

The University of Adelaide

South Australia

i

Table of Contents Abstract ................................................................................................................................. iv

Statement of Authorship ....................................................................................................... vi

Acknowledgements .............................................................................................................. vii

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

1.1 Apical periodontitis ...................................................................................................... 1

1.1.1 Endodontic disease ............................................................................................... 1

1.1.2 Prevalence ............................................................................................................. 3

1.1.3 Polymicrobial nature ............................................................................................. 4

1.1.4 Factors influencing persistent apical periodontitis ............................................... 4

1.2 Enterococcus faecalis .................................................................................................. 5

1.2.1 The genus .............................................................................................................. 5

1.2.2 Strains of E. faecalis ............................................................................................. 5

1.2.3 Gram-positive features .......................................................................................... 6

1.2.4 The genomics of E. faecalis .................................................................................. 8

1.2.5 Pathogenicity island .............................................................................................. 8

1.2.6 The role of E. faecalis in persistent apical periodontitis ....................................... 9

1.2.7 Carbohydrate uptake ............................................................................................. 9

1.2.8 Stress response .................................................................................................... 10

1.2.9 Biofilm growth .................................................................................................... 11

1.3 Proteomics ................................................................................................................. 13

1.3.1 Definition ............................................................................................................ 13

1.3.2 Proteomic techniques .......................................................................................... 13

1.3.3. Mass spectrometry ............................................................................................. 15

1.3.4 Liquid chromatography tandem mass spectrometry ........................................... 15

1.4 Bioinformatics ........................................................................................................... 16

1.5 Membrane proteome of E. faecalis ............................................................................ 17

1.6 Quantification and labelling ....................................................................................... 18

1.7 Continuous culture in the post-genomic era .............................................................. 21

1.8 Overall aims of the study ........................................................................................... 21

Chapter 2. Experimental Investigations ............................................................................... 23

2.1 Effect of alkaline pH on growth rate and phenotypic expression of E. faecalis V583 . 23

2.1.1 Abstract ............................................................................................................... 23

2.1.2 Background ......................................................................................................... 23

2.1.3 Methods .............................................................................................................. 25

ii

2.1.4 Results ................................................................................................................. 26

2.1.4.1 pH 8 .............................................................................................................. 26

2.1.4.2 pH 11 ............................................................................................................ 28

2.1.4.3 Phenotypic differences ................................................................................. 29

2.1.5 Discussion ........................................................................................................... 29

2.1.6 Conclusion .......................................................................................................... 31

2.2 1D SDS-PAGE and in-solution proteomic analysis of E. faecalis membrane proteins: Pilot study ........................................................................................................................ 32

2.2.1 Abstract ............................................................................................................... 32

2.2.2 Background ......................................................................................................... 32

2.2.3 Methods .............................................................................................................. 33

2.2.3.1 Growth conditions ........................................................................................ 33

2.2.3.2 In solution digestion ..................................................................................... 34

2.2.3.3 1D SDS-PAGE ............................................................................................ 34

2.2.3.4 Liquid chromatography - Orbitrap tandem mass spectrometry (LC MS/MS) of protein samples .................................................................................................... 35

2.2.3.5 Data analysis ................................................................................................ 35

2.2.4 Results ................................................................................................................. 36

2.2.5 Discussion ........................................................................................................... 36

2.2.5.1 Cell wall digestion ....................................................................................... 37

2.2.5.2 Cell surface shaving ..................................................................................... 37

2.2.5.3 Cell surface labelling ................................................................................... 38

2.2.6 Conclusion .......................................................................................................... 40

2.3 Isolation and identification of E. faecalis membrane proteins using membrane shaving and one-dimensional SDS-PAGE coupled with mass spectrometry ............................... 41

2.3.1 Abstract ............................................................................................................... 41

2.3.2 Background ......................................................................................................... 41

2.3.3 Methods .............................................................................................................. 43

2.3.3.1 Growth conditions ........................................................................................ 43

2.3.3.2 1D SDS-PAGE ............................................................................................ 43

2.3.3.3 Membrane shaving ....................................................................................... 44

2.3.3.4 Liquid chromatography - electrospray ionisation tandem mass spectrometry .. 45

2.3.3.5 Protein analysis ............................................................................................ 47

2.3.4 Results ................................................................................................................. 47

2.3.5 Discussion ........................................................................................................... 51

2.3.6 Conclusions ......................................................................................................... 54

2.4 Influence of Enterococcus faecalis V583 cell membrane protein expression on biofilm formation and metabolic responses to alkaline stress ...................................................... 56

iii

2.4.1 Abstract ............................................................................................................... 56

2.4.2 Background ......................................................................................................... 57

2.4.3 Methods .............................................................................................................. 61

2.4.3.1 Growth conditions ........................................................................................ 61

2.4.3.2 Membrane shaving ....................................................................................... 61

2.4.3.3 Peptide ICPL labelling ................................................................................. 61

2.4.3.4 Liquid chromatography - electrospray ionisation tandem mass spectrometry .. 62

2.4.3.5 Protein analysis ............................................................................................ 63

2.4.4 Results ................................................................................................................. 64

2.4.4.1 Continuous culture ....................................................................................... 64

2.4.4.2 ICPL labelling .............................................................................................. 64

2.4.5 Discussion ........................................................................................................... 66

2.4.6 Conclusion .......................................................................................................... 75

Chapter 3. Overall Discussion ............................................................................................. 76

3.1 Proteins implicated in biofilm formation ................................................................... 80

3.2 Correlation between metabolism and peptidoglycan turnover .................................. 81

3.3 Correlation to bacteriocin resistance .......................................................................... 82

3.4 Membrane proteins associated with stress response .................................................. 83

3.5 Future Studies ............................................................................................................ 84

3.5.1 Construct and characterise individual markerless deletion mutants of EF0114 and EF1927 and a double-knockout mutant ....................................................................... 84

3.5.2 Determine regulation of EF0114 and EF1927 gene expression ......................... 84

Chapter 4. Overall Conclusion ............................................................................................. 86

Chapter 5. References .......................................................................................................... 88

Appendix 1 ........................................................................................................................... 96

Appendix 2 ........................................................................................................................... 97

Appendix 3 ......................................................................................................................... 101

Appendix 4 ......................................................................................................................... 106

Appendix 5 ......................................................................................................................... 111

Appendix 6 ......................................................................................................................... 112

Appendix 7 ......................................................................................................................... 113

Appendix 8 ......................................................................................................................... 114

iv

Abstract

Background: Enterococcus faecalis is able to survive in a number of biological niches,

which are often nutrient limited and in which the pH can vary greatly. Endodontic (root

canal) treatment of a tooth with a severely inflamed, infected or necrotic pulp usually

involves the chemo-mechanical debridement of the canal(s) using metal files, irrigants such

as sodium hypochlorite and often inter-appointment medicaments such as calcium hydroxide

(~pH 12.5 to 12.8) placed in the main root canal to help in the elimination of surviving

bacteria. E. faecalis is commonly recovered from endodontic infections that have persisted

following treatment with this highly alkaline medicament. The expression of the cell

membrane proteins under alkaline conditions at a biologically relevant growth rate may

increase our understanding of how E. faecalis can adapt and persist.

Aims:

1. To determine the phenotypic changes of E. faecalis V583 when grown at a slow growth

rate at pH 11.

2. To investigate and quantify cell membrane protein expression of E. faecalis V583, at pH

11 compared to pH 8, at an imposed growth rate using continuous culture.

Methods: E. faecalis ATCC V583 was grown in a chemostat at pH 8 (control) and pH 11.

Under each pH condition, the maximum growth rates were determined and an imposed

growth rate of one-tenth the organism’s maximum growth rate (μrel) was used for growth at

pH 8 or 11. After steady state had been achieved, cells were harvested, lysed and membrane

proteins were fractionated by ultracentrifugation, homogenisation in carbonate buffer, and

membrane shaving. Following chymotrypsin digest (in the presence of RapiGest®) of the

membrane fraction, heavy- or light-isotope-coding protein labels (ICPL) were added to

samples from pH 8 or 11. Heavy-labelled (pH 11) and light-labelled (pH 8) samples were

combined and the relative proportion of membrane proteins were identified using Liquid

chromatography, electrospray ionisation (LC-ESI) mass spectrometry and MaxQuant

analysis. The MaxQuant labelled ratios of membrane associated proteins were log2

transformed, and the proteins that deviated by more than one standard deviation (SD) from

the mean were considered to be up- or down-regulated.

Results: The mean generation time at pH 8 was 1.16 hours and 7.7 hours at pH 11. One-

tenth of the maximum growth rate (0.1 μrel) was determined and set at 0.059 h-1 for pH 8 and

v

0.009 h-1 for pH 11. The extreme alkaline conditions produced co-aggregation of the cells

into flocs (a variant of biofilm formation) with the appearance of an extracellular matrix.

These observations are consistent with a shift towards spontaneous biofilm formation.

Six proteins had a log2 H/L ratio (pH 11/pH 8) greater than one SD of the mean including:

Polysaccharide biosynthesis family protein EF0669 (2SD), Glycosyl hydrolase, family 20

EF0114 (4SD), Glycerol uptake facilitator protein EF1927 (1SD), whilst five proteins had a

log2 ratio one SD less of the mean: PTS system IIC component EF1838 (1D), PTS system

IID component EF0456 (2SD), C4-dicarboxylate transporter EF0108 (1SD), PTS system

mannose-specific IID component EF0022 (1SD).

Conclusion: When cultured at an imposed slow growth rate, extreme alkaline conditions

resulted in a reduced mean generation time and altered expression of several membrane

proteins. Collectively these membrane proteins appear to be involved in the transition to

biofilm formation seen at pH 11. It was hypothesised that the capsule observed at pH 11

protects the cell from destructive OH- ions whilst concentrating H+ ions and substrates

required for the electrochemical gradient close to the cell membrane.

Keywords: Enterococcus faecalis, isotope-coding protein labels (ICPL), alkaline pH,

membrane shaving.

vi

Statement of Authorship

This work contains no material which has been accepted for the award of any other degree

or diploma in any university or other tertiary institution and, to the best of my knowledge

and belief, contains no material previously published or written by another person accept

where due reference has been made in the text.

I give consent to this copy of my thesis, when deposited in the University Library, being

made available for loan and photocopying, subject to the provisions of the Copyright Act

1968.

Signed:

Peter Cathro Date:

vii

Acknowledgements

I would like to thank a number of people who provided guidance and encouragement during

the course of this work.

Dr Peter Zilm, who has been a mentor, colleague and friend over many years and without

whose support this thesis and our other joint research endeavours would not have been

possible.

Dr Stephen Kidd, for his dedication and willingness to supervise this project and his

wonderful insights into the world of bioinformatics.

Associate Prof Neville Gully, for his help in guiding this and other research projects over

the years.

Dr Peter McCarthy, for his expert research skills and “rescuing” my precious samples.

Prof Peter Hoffmann, for his support and generous help facilitating the proteomic

components of the project.

Camilla, Samuel, Emily & Alfred, my wonderful family, I cannot thank them enough for

their ongoing love and care of me.

This study was supported by several grants from the Australian Dental Research Foundation,

The Dental School University of Adelaide and the Australian Society of Endodontology.

I sincerely thank the staff at the Adelaide Proteomic Centre for their excellent technical

assistance.

1

Chapter 1. Introduction

1.1 Apical periodontitis

1.1.1 Endodontic disease

Teeth consist of two main components, namely the crown and the root. The crown is

comprised of enamel, dentine and the extension of the pulp tissues from the root. The root

is generally below the gingival margins and is covered with cementum. The root is largely

comprised of dentine and contains the pulp in the root canals. The pulp consists primarily of

loose connective tissue predominated by fibroblasts, undifferentiated mesenchymal cells,

collagenous fibres, blood vessels (arterioles, venules), and neural tissue (Mjör & Fejerskov

1979). In the development of teeth, the pulp plays a major role in the production of dentine,

which ultimately encloses the pulp tissue once root development is complete. The dental

pulp is therefore normally protected by dentine and enamel but may become infected

subsequent to caries, defective restorations or traumatic injuries to the tooth (Kakehashi et

al 1966). The pulp has a limited capacity to launch an effective immune response to invading

bacteria, and due to being enclosed by hard tissues there is minimal ability for tissue

expansion with inflammation, resulting in an increased intrapulpal pressure which may cause

marked pain for the patient. Unresolved inflammation can cause either a gradual or rapid

destruction of the pulp in a coronal-apical direction. As a natural consequence of microbial

infection, the pulp may become necrotic, with infectious microorganisms colonizing the

main body of the root canal, penetrating into the dentinal tubules, lateral canals or

anastomoses, the formation of biofilms and ultimately resulting in infection and/or

inflammation of the periapical tissues (termed apical periodontitis) (Figure 1) (Moller et al

1981, Sundqvist et al 1998, Love 2001, Nair 2006).

2

Figure 1. Light microscopic view demonstrating an infected root canal system with biofilm formation (BF) in an accessory canal (AC) and the presence of apical periodontitis (AP) (Nair 2006).

Endodontics is primarily concerned with the prevention or elimination of apical

periodontitis. If the pulp becomes inflamed it may be reversibly damaged, i.e. it has the

ability to heal. This occurs through the normal inflammatory and repair process seen

throughout the body and also by the increased deposition of dentine to "wall-off" the pulp

from the advancing irritants (Bjørndal 2002). If the bacterial assault on the pulp overcomes

the ability for repair, then the pulp becomes irreversibly damaged and eventually becomes

necrotic with no mechanisms available to manage the invading bacteria or their toxic by-

products (e.g. endotoxins) (Barthel et al 1997). The ultimate outcome of the pulp disease

process is a root canal space that is pulpless and infected (Jansson et al 1993)

The treatment options for a tooth with irreversible pulpitis or an infected root canal system

are usually limited to extraction or endodontic therapy. The management of an infected root

canal system relies on the use of antimicrobial strategies involving a number of procedures

including instrumentation, irrigation, medication and a restoration to prevent

recontamination. Following access to the root canals, instrumentation is carried out with

endodontic files that enlarge the root canals and create a shape that facilitates the placement

3

of irrigants, medicaments and ultimately the root filling (obturation) material.

Instrumentation allows for some limited mechanical removal of bacteria (Byström &

Sundqvist 1981), but it is the use of antimicrobial irrigants such as sodium hypochlorite or

dressings such as calcium hydroxide used as an inter-appointment medicament (Byström &

Sundqvist 1985, Byström et al 1985) that are crucial in significantly reducing microbial

numbers. The release of hydroxide ions (~pH 12) from calcium hydroxide is thought to be

responsible for its antimicrobial effect, causing lipid peroxidation which results in

destruction of the phospholipid component of bacterial cell walls (Siqueira & Lopes 1999).

The effects of an alkaline pH are known to cause a dramatic reduction in the viability of

bacteria, for example, the survival of Enterococcus faecalis has been shown to decrease to

0.001% at pH 11 and 0.00001% at pH 12 compared to the growth at pH 7 (Appelbe &

Sedgley 2007). On a cellular level, the response to an extreme alkaline environment has been

attributed to the activation of proton pumps to help maintain pH homeostasis (Evans et al

2002) or more generalised survival responses with a common set of proteins being expressed

(Petrak et al 2008, Wang et al 2009).

During endodontic treatment, the combination of the antimicrobial strategies aid in removing

organic matter from the canal, such as pulp tissue, and in eliminating bacteria. Following the

disinfection stages, the root canal is then usually obturated with gutta-percha and an

appropriate sealer to prevent (or at least reduce) the recontamination of the root canal system

or the entry of periradicular fluid. Collectively the stages of root canal treatment render the

canal a hostile, nutrient depleted environment, making bacteria survival a challenge. Even

in this hostile environment, bacteria can survive and lead to persistent apical periodontitis

(Sedgley et al 2005).

1.1.2 Prevalence

Billions of teeth are retained through root canal treatment, and in high or very highly

developed countries this represents the equivalent of two treatments per patient (Pak et al

2012). The root canal system is not a simple evenly tapered shape, but rather is complex

with many accessory canals and webs, which provide safe-harbours for bacteria (Nair 2006,

Vertucci 1984). Completed to a high standard, endodontic therapy enjoys a very high success

rate in the order of 85 to 95% (Sjögren et al 1997, Elemam & Pretty 2011). If the primary

treatment has failed and re-treatment is attempted, then the expected success drops to the

4

order of 60 to 80% (Sjögren et al 1990, Elemam & Pretty 2011). Correlating success rates

to the amount of teeth treated means that hundreds of millions of teeth have persistent

infection. Endodontic treatment can be expensive, and as such there is a health and financial

burden to individuals and society in managing endodontic infections and retaining teeth for

life.

1.1.3 Polymicrobial nature

Utilizing molecular techniques, an average of 20 taxa are recovered per tooth with a primary

endodontic infection (Munson et al 2002), but over 391 bacterial taxa have been detected in

different samples of primary infections (Siqueira & Rôças 2009).

Initially the infected root canal is populated with a mixed anaerobic population dominated

by obligate anaerobes (Byström & Sundqvist 1981). Following irrigation and medication

protocols, Gram-negative bacteria are not usually recovered, with Fusobacterium

nucleatum, Prevotella sp. and Campylobacter rectus being notable exceptions (Byström &

Sundqvist 1985, Sakamoto et al 2007). In contrast, Gram-positive facultative or anaerobic

bacteria have been found to survive the endodontic treatment protocols and include

streptococci, Parvimonas micra, Actinomyces sp., Propionibacterium sp.,

Pseudoramibacter alactolyticus, Lactobacilli and E. faecalis (Chávez de Paz et al 2005,

Gomes et al 1996). If the primary treatment fails with evidence of persistent infection, then

E. faecalis is the most frequently recovered species, with prevalence occurring in up to 90%

of cases (Molander et al 1998, Siqueira & Rôças 2009).

1.1.4 Factors influencing persistent apical periodontitis

Root canal therapy can be considered to fail for two main reasons. The first is that the

microbial numbers were not reduced sufficiently during the initial treatment, allowing

persistence of the disease process (Nair 2006). The second is recontamination of the root

canal system, usually as a result of a defective restoration or the progression of caries (Ray

& Trope 1995). If there is evidence of infection associated with a root filled tooth, then the

clinical options would include monitoring, extraction, re-treatment or apical surgery. The

success of re-treatment is principally related to the cause of the infection. If the canals were

poorly treated in the first instance without procedural errors, success can be high, but if the

primary treatment was carried out to a high technical standard, or if procedural errors had

occurred, then the success rate is lower.

5

This lowered success rate is primarily due to a shift in the bacterial population residing in

the root canal system (Molander et al 1998) and also the limitations in overcoming iatrogenic

errors that may have been created when the root canal was initially treated. Errors include

transportation (deviation from the true root canal), ledging, apical blockages and perforation.

If calcium hydroxide medicament is used in the management of a primary infection, the

diffusion of hydroxyl ions into the dentinal tubules takes 3 to 4 weeks to penetrate to the

outer layers of dentine (Nerwich et al 1993). The initially high pH has been reported to be

buffered by dentine, thereby reducing the antimicrobial effect of calcium hydroxide

(Haapasalo et al 2000). In contrast, Athanassiadis et al (2010) report that dentine did not

inactivate calcium hydroxide when used in a commercial paste formulation and that E.

faecalis was unable to survive this medicament.. If root canal therapy fails, then E. faecalis

is commonly recovered and like most bacteria, it has the ability to form a biofilm that is

firmly attached to the dentinal tubules within the root canal system (Seet et al 2012).

1.2 Enterococcus faecalis

1.2.1 The genus

Enterococci species belonging to the genus are ubiquitous and are found in a wide variety of

habitats including food, soil, waterlines, sewage, and the human gastro-intestinal tract

including the oral cavity (Franz et al 1999). Typically, enterococci can tolerate high salt

concentrations (up to 6.5%), a wide pH range (4.6 to 12), a wide temperature range (10 to

45C), desiccation, bile acids, detergents, antimicrobials including certain antibiotics,

pancreatic secretions (pH ≥10) and they can survive pasteurisation.

1.2.2 Strains of E. faecalis

E. faecalis is an opportunistic bacterium, being a major cause of infective endocarditis,

urinary tract infections and bacteraemia, and with intrinsic resistance to many antibiotics and

antimicrobial agents representing a significant nosocomial burden (Paulsen et al 2003, Korja

et al 2005).

E. faecalis strain MMH594 was responsible for a number of life threatening infections

following trauma or conditions requiring life support and seems to be the prototype from

which strains E. faecalis V586 and V583 have evolved (Huycke et al 1991, Shankar et al

6

2002). The vancomycin resistant serial isolates (V583 and V586) were obtained from blood,

urine and stool cultures from a chronically infected patient (Sahm et al 1989). Shankar et al

(2002) identified that the modulation of many of the resistance features including

transposases, transcriptional regulators, and aggregation substance present in the isolates

were contained within a pathogenicity island. However, none are known to code for

antibiotic resistance. Cytolysin (a toxin) and the surface protein Esp, which is involved in

colonisation and biofilm formation are common virulence factors in E. faecalis clinical

isolates. The genes coding for these could be localised on the chromosome of V586, but the

organism appears to be phenotypically non-cytolytic, even though it contains the cytolysin

operon. The genes encoding cytolysin and Esp however, were not found in V583. E. faecalis

V583 (esp-, cyl-) seems to occur through the spontaneous deletion of DNA from the V586

genome, occurring at a frequency of approximately 1 in 103 when V586 was cultivated in

vitro (Shankar et al 2002).

1.2.3 Gram-positive features

E. faecalis is a Gram-positive facultative bacterium. Gram-positive bacteria are surrounded

by a thick and rigid single cell wall, which is composed primarily of peptidoglycan (Figure

2). This is in contrast to the double membrane seen in Gram-negative bacteria (Cordwell

2006, Solis & Cordwell 2011).

Figure 2. Cell wall architecture of Gram-positive bacteria from Solis and Cordwell (2011).

The surface of Gram-positive bacteria comprises proteins, biological molecules such as

teichoic, lipoteichoic, teichuronic acids (providing a net negative charge), slime capsules

and biofilms (Solis & Cordwell 2011). Of all the bacterial genes, it is estimated that

approximately 20 to 30% encode for membrane proteins (Padan et al 2005). Bacterial

surface proteins have a number of different functions but are principally involved in cellular

homeostasis of the cell in response to the extracellular environment.

7

The roles include:

1. Nutrient acquisition and the control of metabolic activities

2. Transport of waste products out of the cell

3. Chelation of iron and other important growth factors

4. Signal transduction of the external environment

5. Colonisation, adherence to surfaces.

6. Communication with other bacteria and quorum sensing

7. Defence against host immune responses, toxins, antibiotics and other antimicrobial

agents

8. Adaption to environmental changes

9. Biofilm formation with the production of extracellular polymeric substances (EPS)

(Cordwell 2006, Benachour et al 2009, Opsata et al 2010, Solis & Cordwell 2011).

As the surface proteins are in close contact with the external environment and have direct

communication with the cytoplasm, they are also targets for potential vaccines and

antibiotics (Solis & Cordwell 2011).

A central role of cell membrane proteins is in the regulation of metabolic pathways. This can

be by signaling into the cell the environmental changes in the amount and availability of

various carbohydrates, oxygen concentration, environmental stresses, exposure to

bacteriocins and toxins (Dressaire et al 2008, Mehmeti et al 2012), with the responses

occurring in complex and strain-dependent manners (Bizzini et al 2010). Any of these

environmental conditions may have a dramatic effect on the growth rate of the organisms as

energy (ATP) is diverted from biomass to survival mechanisms.

The rigid cell wall provided by the heavy cross-linking between peptidoglycan strands in

Gram-positive bacteria creates difficulties when examining protein expression of cell

membrane proteins (Cordwell 2006). Additional proteomic challenges include the relatively

low abundance of membrane proteins compared to cytosolic proteins, the innate

hydrophobic nature of membrane proteins which have poor solubility and the technical

difficulties of recovering pure surface fractions without contamination of cytosolic proteins

(Solis & Cordwell 2011).

8

1.2.4 The genomics of E. faecalis

Paulsen et al (2003) reported the complete genome sequence for E. faecalis V583,

identifying 3337 predicted protein-encoding open reading frames (ORFs) with over a quarter

of the genome consisting of mobile or foreign DNA, which are thought to contribute to the

accumulation of drug resistance and virulence factors. As with genomic studies of bacteria,

a large proportion of the genes that have been identified have not been functionally

classified. Many of these however are predicted to encode for membrane-associated proteins

(Cordwell 2006).

E. faecalis has a strong similarity with other low-GC Gram-positive bacteria with a set of

conserved genes that are involved in transcription, translation, protein synthesis and

transport (PTS and ABC transporters) (Paulsen et al 2003).

1.2.5 Pathogenicity island

The cluster of virulence determinants in the pathogenicity island (PAI) of E. faecalis V583

occurs between the ORFs EF0479 - EF0628 and matches the ORFs within E. faecalis

MMH594 (EF0001 to EF0129) reported by Shankar et al (2002). The PAI is approximately

150 kilobases, and varies only slightly between strains V583 and V586 and MMH594

(Shankar et al 2002).

Genes within the PAI code for transposases, transcriptional regulators and also for proteins

that have functions in adaptation to the environment, including survival and virulence

(Shankar et al 2002). The PAI has a great deal of similarity with other low-GC Gram-

positive bacteria and is therefore likely acquired by horizontal gene transfer (Paulsen et al

2003).

Adhesins (aggregation substance and hemagglutinin), DNA-damage inducible proteins, zinc

metalloprotease and components of the phospho-transferase system (PTS) are some of the

known virulence traits that are encoded in the PAI (Shankar et al 2002, Paulsen et al 2003,

Benachour et al 2009). As stated above, E. faecalis V583 is deficient in both the cytolysin

and Esp genes and only a limited number of membrane proteins associated with virulence

have been identified (Maddalo et al 2011).

9

1.2.6 The role of E. faecalis in persistent apical periodontitis E. faecalis is a common commensal organism in the human gastrointestinal tract (surviving

the pH extremes of gastric acid) and the oral cavity (Sedgley et al 2004). Its presence in the

oral microbiome of an individual may also reflect the recent ingestion of certain cheeses and

fermented foods where they contribute to flavour and preservation (Sedgley et al 2004,

Zehnder & Guggenheim 2009, Opsata et al 2010).

During the management of endodontic disease, calcium hydroxide is often used as a general

antimicrobial dressing that is spun into the root canal and left for a period of time typically

from one week to a few months. It has been demonstrated that use of this medicament with

a high pH can effect a 99% reduction in viability of E. faecalis V583 (Plutzer 2009).

E. faecalis is more commonly isolated from persistent infections compared to primary

infections (89.6% versus 67.5%) (Sedgley et al 2006) suggesting that it has the capacity to

survive chemo-mechanical procedures (Yap et al 2014) and to survive in a nutrient limited

environment (Sedgley et al 2005).

1.2.7 Carbohydrate uptake

E. faecalis, like most bacteria, are able to utilise a large variety of carbon sources and can

adapt to the changing environment (Bizzini et al 2010). In response to the concentration

gradient of nutrients, the presence of specific carbon sources, and to physical and chemical

stresses, there are a number of sensory-regulator systems that function by phosphorylating

histidine, serine, and aspartate residues on the proteins involved (Postma et al 1993). One of

these systems is the phosphoenolpyruvate (PEP)-PTS, which couples phosphorylation to the

translocation of carbohydrates across the cell membrane. The PEP-PTS is also involved in

the regulation of a number of metabolic pathways (Postma et al 1993).

E. faecalis V583 has over 35 probable PTS-type sugar transporters with the genome

encoding for the uptake of 15 different sugars which are metabolised by the Embden-

Meyerhof and pentose phosphate pathways (Paulsen et al 2003). In addition to PEP-PTS,

the membrane transport for sugar and polyol utilisation can occur through ABC (ATP-

binding cassette transporter family), MIP (major intrinsic protein transporter family), and

Gnt (gluconate transporter family) systems (Paulsen et al 2003). The transport of

carbohydrates by non-PTS systems require ATP to be expended for transport and

10

phosphorylation, however the PTS system utilises PEP which provides the energy for uptake

and is energetically equivalent to ATP (Postma et al 1993). As the use of the PTS system is

energy efficient, it helps explain why normally the PTS is used for the uptake of glucose,

fructose or sucrose, and the metabolism of less favourable carbon sources are repressed, e.g.

glycerol, via the ATP-dependent phosphorylation by glycerol kinase (GlpK) to yield

glycerol-3-phosphate (Paulsen et al 2003, Deutscher et al 2006, Bizzini et al 2010).

1.2.8 Stress response

Cellular stress response has been defined as a defence reaction of cells to damage that

environmental forces inflict on macromolecules (Kultz 2005). E. faecalis has a number of

ORFs that have a potential role in responses to oxidative stress, osmotic stress and genes

related to metal-ion resistance and cation homeostasis mechanisms which may play a role in

pH, salt, metal and desiccation resistance (Paulsen et al 2003).

In response to environmental stress, a limited number of proteins, or protein families that are

expressed have been identified (Wang et al 2009). E. faecalis has been shown to up-regulate

certain proteins as part of a stress response to glucose starvation (Giard et al 1997), and the

major heat shock proteins DnaK and GroEL to elevated temperatures, acid, bile salts

(Flahaut et al 1996) and alkaline stress responses (Flahaut et al 1997).

The understanding of the mechanisms by which a small proportion of an E. faecalis

population can survive elevated pH levels remains incomplete and uncertain. It has been

proposed that the toxic effects of high pH are primarily regulated by a membrane proton

pump, which maintains optimal cytoplasmic pH levels (Evans et al 2002). There is however

conflicting evidence on the role of protein synthesis in response to calcium hydroxide. Evans

et al (2002) used chloramphenicol to inhibit protein synthesis and found no effect on cell

survival. They concluded that stress-induced protein production is not important for survival

of E. faecalis at high pH. Distel et al (2002) showed no difference in the protein profiles of

planktonic bacteria that had been subjected to a calcium hydroxide dressing in tooth roots

compared to the inoculum culture. Although only a few cells could be recovered from the

root canals, when they were examined by phase contrast microscopy, the cells were seen to

be embedded in an extracellular matrix (indicative of a biofilm). To extract protein from the

cells, trichloroacetic acid (TCA) was applied to whole cells and the resultant pellet

suspended in x2 SDS-PAGE sample buffer. A separate lysozyme treatment was used to

11

produce cell-free lysates. SDS-PAGE was performed on the cell lysates but there was

difficulty resolving the proteins, as the matrix was only partially soluble with trichloroacetic

acid (TCA)/SDS and lysozyme treatment followed by SDS-PAGE did not produce well-

separated proteins. Apart from a protein smear, only a single band at 32 kDa was resolved.

The authors concluded that the protein smear suggests the presence of active proteases in the

sample and that more research was needed to resolve all the proteins associated with the

putative biofilm.

In contrast, Flahaut et al (1997) found that chloramphenicol treatment of a culture at pH 10.5

resulted in a 9% decrease in alkaline tolerance and that 37 proteins from whole cells were

induced more than two-fold by alkaline stress, with nine proteins being amplified more than

five-fold. Appelbe & Sedgley (2007) investigated the effect on gene expression on E.

faecalis after prolonged exposure to alkaline pH on planktonic bacteria grown aerobically.

The authors identified increased levels of gene transcripts for ftsZ, pbp5, dnaK, napA, tsf,

and groEL between 72 and 120 hours when grown at a pH of 10. Transcripts of ftsZ, a gene

involved in cell division increased by 37-fold. Proteomic studies on the oral bacterium, F.

nucleatum have also identified ftsZ, dnaK (HSP70) and groEL (HSP60) as being regulated

by growth pH (Zilm et al 2007).

1.2.9 Biofilm growth

Biofilms can be defined as bacterial communities that are encased in a matrix of extracellular

polymeric substance (EPS), that are adherent to each other (flocs) and/or to biotic or abiotic

surfaces or interfaces which exhibit altered growth phenotypes (Costerton et al 1995, Donlan

& Costerton 2002). Bacteria within a biofilm display a distinctive phenotype, with an altered

cell surface and metabolic profile and collectively they form an organised community. These

features provide the bacteria with an increased resistance to antibacterial agents and stressful

environments (Costerton et al 1995). Cellular adhesion and the alteration in phenotype seem

to result from the expression of a factor that de-represses a large number of genes which

would not normally be expressed in planktonic culture (Costerton et al 1995).

Biofilm formation can be regarded as a generalised adaptation to many environmental

conditions; this has involved ecological, industrial and anatomical niches and includes an

infected, necrotic root canal system (Nair 2006). Biofilm production has been shown to

increase with an increase in pH (Zilm & Rogers 2007, Hostacka et al 2010). Zilm and Rogers

12

(2007) found that elevated pH (greater than 8.2) produces a shift from a planktonic lifestyle

to the spontaneous flocculation and biofilm formation by F. nucleatum. It is therefore

possible, that the use of calcium hydroxide may induce the formation of E. faecalis biofilms,

which in turn may serve as a protective system to facilitate survival in the high pH conditions

associated with endodontic medicaments such as calcium hydroxide and other potential

antimicrobial agents. Wilson et al (2014) demonstrated that different E. faecalis isolates,

when subjected to sub-minimum inhibitory concentration (MIC) levels of antimicrobial

agents such as sodium hypochlorite (NaOCl), calcium hydroxide, clindamycin, and

tetracycline showed significant clonal variation in biofilm formation. In particular, two

isolates increased biofilm formation in tetracycline and one in the presence of NaOCl.

The protective strategies include comparatively slow growth, the acquisition of large

complex nutrient molecules, export of harmful metabolic waste products, horizontal gene

transfer within and between species and the development of a protective physiochemical

environment to enhance microbial survival (Stewart & Costerton 2001, Socransky &

Haffajee 2002). An additional survival strategy of some bacteria is the ability to transform

into dormant, very small (±0.3 µm) spherical ultra-microbacteria that can be fully

resuscitated many years later (Costerton et al 1995).

The majority of studies in the endodontic literature that investigated the efficacy of irrigants

and medicaments have used bacteria grown in the planktonic phase as a batch culture.

Bacteria grow rapidly in an ideal growth environment but can also be killed relatively easily

when the environment is changed. There is a shift in more recent investigations to examine

the effect of irrigants and medicaments on endodontic pathogens that have been grown as a

biofilm rather than the planktonic phase (Dunavant et al 2006).

Only a limited number of membrane proteins associated with biofilm formation in E. faecalis

have been identified and include major facilitator family transporter (EF0082), Ornithine

carbamoyltransferase (EF0105), Na+/H+ antiporter (EF0402), ABC transporter, ATP

binding/permease protein (EF0790), phosphate import ATP-binding protein PstB 1

(EF1755) and a predicted protease Eep (EF2380) (Maddalo et al 2011).

13

1.3 Proteomics

1.3.1 Definition

The complete genomes for a large number of bacteria have been reported. However, it is the

profile of protein expression that provides bacteria the ability to respond phenotypically to

changes in the environment (Costerton et al 1995).

Proteomics is the study of the complete set of proteins expressed as a result of gene and

cellular function of any organism (Aebersold & Mann 2003, Yang et al 2012). With changes

in genetic and environment factors, and under certain growth conditions only a limited

number of proteins are expressed. The wide range of differential expression makes the study

of proteomics complicated (Wolff et al 2008, Lottspeich 2009). In addition, proteins are

more heterogeneous than gene expression and are prone to a variety of post-translational

modifications (PTM) (Fleron et al 2010) making the dynamic range and complexity of

proteins a challenge to study, especially if quantitative analysis is required (Lottspeich

2009).

1.3.2 Proteomic techniques

As mentioned previously, proteomic analysis of Gram-positive membrane and cell wall

proteins is challenging. Various proteomic methods have been utilised to analyse the

proteome of microorganisms under consideration. One of the most commonly used methods

is to separate the low abundant proteins from the more abundant by the use of

multidimensional gel-based separation steps (Lottspeich 2009). Once the sample has been

separated into protein ‘spots’, they can be enzymatically digested to peptides and then

analysed and identified using mass spectrometry.

Two-dimensional gel electrophoresis (2-DE) has been a popular technique to study bacterial

proteins. In the first dimension, the proteins are separated by isoelectric focusing and then

the use of mass-based sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-

PAGE) in the second (Cordwell 2006, Lottspeich 2009).

A number of limitations of the use of 2-DE in proteomics have been identified. Proteins that

have extremely low or high-molecular weights are often not visible on the gels. With regards

to membrane proteins, they are not particularly soluble in 2-DE buffers, so proteins that are

14

hydrophobic, that are either extremely acidic or alkaline or contain many trans-membrane

domains are often under-represented (Cordwell 2006, Wang et al 2009, Solis & Cordwell

2011). With the advent of genomic sequencing it is possible to predict the proteome in silico

of the whole cell and identify proteins that are positively or negatively hydrophobic in nature.

The grand average of hydropathy (GRAVY) score is a measure of the hydrophobicity of

proteins with a negative GRAVY score being more hydrophilic in nature and more

compatible with 2-DE analysis, whilst for proteins with positive GRAVY scores there is a

higher chance of them having a trans-membrane location. A large number of trans-

membrane domains (greater than three) are difficult to resolve utilizing 2-DE separation

(Cordwell 2006). Gel-based proteomics have additional limitations, including

reproducibility and the inability to reliably quantify protein expression (Lottspeich 2009).

To help overcome some of the inadequacies of gel based techniques, methods have been

developed to enrich bacterial surface proteins which involve differential solubility and

membrane protein enrichment, but these techniques seem to be more successful for Gram-

negative membrane proteins (Cordwell 2006).

Prior to mass spectrometry identification, the proteins under investigation need to be

enzymatically digested into peptides. This is problematic with membrane proteins as they

are surrounded by lipids, which need to be solubilised by detergents before they can be

enzymatically digested. Trypsin is the most commonly used enzyme for protein digestion,

however a further complication is that there are very few cleavage sites for trypsin in

membrane proteins (Wolff et al 2008).

Newer non-gel based strategies have been developed to provide analysis of bacterial

membrane proteins - for example, multi-dimensional protein identification technology

(MudPIT). A cell lysate is subjected to tryptic digest followed by two-dimensional liquid

chromatography; a strong cation exchange in the first dimension followed by reverse-phase

chromatography in the second. The peptides are then identified using tandem mass

spectrometry (MS/MS) by either electrospray ionisation (ESI) or matrix -assisted laser

desorption ionisation mass spectrophotometry (MALDI-MS) (Cordwell 2006). A number of

disadvantages have been acknowledged with MudPIT, including difficulties with

quantification and the under sampling of minor peptides (Lottspeich 2009).

SDS has good solubilising efficiency of integral membrane proteins (IMPs) and therefore

SDS-PAGE has been proposed for separation of bacterial surface proteins. Bands are cut

15

from the gels, subjected to digestion (usually with trypsin) and analysed by liquid

chromatography and tandem mass spectrometry (LC-MS/MS). Whilst this method is good

for protein identification, it is unsuitable for the quantification of protein expression between

two biological samples unless eluted proteins are labelled before enzymatic digestion

(Cordwell 2006).

1.3.3. Mass spectrometry

With the development of protein ionisation methods, and the availability of whole genome

databases, mass spectrometry has become an incredibly powerful tool for the analysis of

complex protein samples (Aebersold & Mann 2003).

Mass spectrometers consist of three main components. The first is an ion source. Ionisation

of the analytes in solutions is achieved using either electrospray ionisation (ESI) or from

dry, crystalline matrix samples with matrix-assisted laser desorption/ionisation (MALDI).

ESI can be used in conjunction with liquid based chromatography, which has proven to be

useful for the analysis of complex structures (Aebersold & Mann 2003). The second

component of the mass spectrometer is a mass analyser used to measure the mass-to-charge

(m/z) ratio and the third component is a detector that registers the number of ions at each m/z

value.

1.3.4 Liquid chromatography tandem mass spectrometry

Peptides produced from the proteolytic digestion of proteins are separated based on their

hydrophobicity by liquid chromatography and enter the mass spectrometer where they are

then ionised (Ryu 2014). The resulting range of peptides, with defined mass-to-charge ratios

(m/z), forms the precursor ion spectra (MS1 spectra). Individual ionised peptides with high

intensities from the MS 1 spectrum are then fragmented into ions to form a resultant MS/MS

spectrum of one peptide. The MS1 spectra are used for peptide quantification whilst the data

from the tandem mass spectra is mainly used for peptide identification (Ryu 2014).

16

1.4 Bioinformatics

Tandem mass spectrometry records peptide sequences based on the mass and intensity of

the fragment ions in the MS/MS spectra. As amino acids, except isoleucine and leucine, have

a known and unique mass, the peptide sequence can be determined either manually or by the

use of automated algorithms which is necessary if the genome sequence is unknown (Ryu

2014). If a suitable protein sequence database is available then a number of programs are

available for identification of peptides by matching the MS/MS spectra against the selected

database (Arrey et al 2010). Following determination of the charge state and mass of the

precursor ion, the enzyme used for digestion and selection of the appropriate data-base,

peptide sequences with theoretical masses that are within a mass tolerance are considered as

theoretical candidate peptide sequence possibilities (Ryu 2014). The theoretical spectrum is

then matched with the observed MS/MS spectra. The theoretical spectra that has the highest

correlation to the observed spectra is assigned the peptide sequence. Common examples of

database-searching software include Sequest and Mascot.

A limitation with the assignment of theoretical to observed peptide sequence spectra is that

it may be incorrect due to “noise” of the MS/MS data, incomplete inclusion of peptides in

databases and incorrect peptide assignments.

Cox and Mann (2008) described a software package that uses a set of algorithms to extract

information from raw MS data. It focuses on the features of mass and intensity of the peptide

peaks in the MS spectra, rather than the MS/MS fragmentation spectra. By improvements in

determining the mass accuracy in the MS data, an increased proportion of fragmentation

spectra can be achieved. The same authors have provided evidence that the false-discovery

rate of peptide and protein identification is stringent using the MaxQuant algorithms (de

Godoy et al 2008).

Protein subcellular localisation can be predicted with bioinformatics techniques on species

whose genome has been sequenced (Zhou et al 2008). For the determination of membrane

protein localisation, tools that calculate the hydrophobicity in helical stretches of

transmembrane proteins give an indication of the anchoring and orientation of the protein. It

also indicates secretion signal domains for transmembrane protein (Solis & Cordwell 2011).

There are many different algorithm tools and many have been incorporated into one pipeline,

17

e.g. Augur (Billion et al 2006), Surface Localisation Extracellular Proteins (SLEP)

(Giombini et al 2010) and LocateP (Solis & Cordwell 2011).

Zhou et al (2008) developed and presented the most detailed and accurate sub-cellular

location (SCL) of Gram-positive bacteria. LocateP combines existing high-precision

subcellular-location identifiers with further improvements in the identification of specific

SCLs such as N-anchored proteins. The authors/designers have designated seven protein

locations for Gram-positive bacteria: intracellular, multi-transmembrane, N-terminally

membrane anchored, C-terminally anchored, lipid- anchored, LPxTG-type cell-wall

anchored, and secreted/released proteins (Figure 3).

Figure 3. LocateP subcellular localisation for Gram-positive bacteria (Zhou et al 2008).

1.5 Membrane proteome of E. faecalis

There have been limited studies on the membrane-embedded proteins of E. faecalis, and

prior to 2011 only nine had been identified (Benachour et al 2009, Bøhle et al 2011),

representing approximately 1.5% of the predicted membrane embedded proteome (Maddalo

et al 2011)

Maddalo et al (2011) increased the recovery of membrane-embedded proteins to 10%. After

using a buffer containing lysozyme, the cells were passed through a french press and the

membrane fractions were solubilised in n-dodecyl -D-maltoside (DDM) and fractions were

18

separated by anion exchange chromatography. Fractions were then collected and subjected

to non-denaturing blue native-PAGE (BN-PAGE) in the first dimension, followed by SDS-

PAGE in the second dimension. Protein spots were excised manually from the gel and the

peptides were analysed by mass spectrometry. The MS/MS data was processed by

qualitative analysis software and all hits were verified with the E. faecalis OG1RF genome

by BLASTN. Bioinformatic analysis of amino acid sequence was carried out with

SignalP3.0 (to identify cleavable signal peptide), SCAMPI (to identify transmembrane

helices) and PRED-LIPO (to identify lipoproteins). The authors identified six proteins

associated with biofilm formation and 11 having a role in virulence.

The technique described by Maddalo et al (2011) appears to be the most comprehensive

study of the membrane proteome of E. faecalis to date. In order to investigate how the

membrane proteins are involved in survival strategies under different environmental

settings, quantitative analysis of membrane proteins would be of particular interest.

1.6 Quantification and labelling

Two-dimensional LC-MS/MS protocols have been useful in mapping surface proteins;

however the technique doesn’t allow comparative analysis between samples. This can be

overcome by using amino acid tags or labels (Cordwell 2006). Reproducible protein

quantification of membrane proteins is problematic and has led to the publication of a

number of protocols, each with their respective strengths and weaknesses (Cordwell 2006,

Solis & Cordwell 2011).

The ICAT protocol covalently labels cysteine residues of protein lysates derived from two

different experimental conditions with either the light (12C) or heavy (13C) stable isotopes of

the same chemical reagent (Gygi et al 1999). Following digestion, labelled peptides are then

combined and analysed by MS. Protein expression is quantified by identifying the light- and

heavy-labelled peptides with the ratio of ion signal intensities or peak areas being directly

related to peptide abundance. A major disadvantage of this method is that the protocol does

not detect proteins that do not contain, or contain only one cysteine residue (Lottspeich 2009,

Cordwell 2006). A further complication is that some peptides can remain bound to the avidin

column and chemical modification can be difficult when dealing with small samples (Ong

et al 2002). The main advantage of using ICAT is that there is an improvement in dealing

19

with proteins that are poorly resolved using 2DE systems such as hydrophobic membrane

proteins.

Isobaric Tag for Relative and Absolute Quantitation (iTraQ) is an alternative protocol to

ICAT. The iTraQ system uses four N-terminal-binding tags, which allows for increased

proteome coverage as proteins with a single or no cysteine residues are also included. The

four isobaric tags are comprised of an amine-specific reactive group, a neutral linker group

and a reporter region (Cordwell 2006). The tags have an identical mass, but contain

differences in mass in their reporter and linker regions. The iTraQ system can accommodate

the comparative analysis of up to four different samples in a single experiment.

Quantification of protein abundance is determined by comparing the relative proportion of

individual peaks in the fragmentation spectra following MS/MS of iTraQ tagged peptides

(Wiese et al 2007).

A significant difference compared to ICAT labelling is that isotopic labelling with iTraQ

tags occurs after enzymatic digestion of the protein. This increases the sample complexity

and generally favours proteins of high abundance (DeSouza et al 2005). Limitations of

iTRAQ include poor detectability of the reporter ions in several types of mass spectrometers

(Paradela et al 2010) and that quantification of iTRAQ labelling is performed in the low

mass range of the MS/MS spectra (Leroy et al 2010).

Isotope Coding Protein Label (ICPL) is a non-isobaric technique used to label primary

amines found in proteins. The N-hydroxysuccinimide (NHS) label is directed to all lysine

residues and protein N-termini, and is used in a top-down proteomic approach. Lysine

residues are more abundant than the cysteine groups and therefore a larger number of

peptides can be quantified compared to the ICAT technique (Brunner et al 2010). Depending

on the ICPL reagent kit used, up to four different proteome states can be analysed in the one

experiment (Brunner et al 2010).

Quantification is determined by comparing the relative abundance of the differentially

labelled peptides, measured as either peak intensity or area (Paradela et al 2010). There have

been very few published papers that have utilised ICPL and none seem to have reported the

investigation of E. faecalis with this labelling technique.

20

The main steps using ICPL for comparative analysis of samples are detection and then

quantification and identification of differentially expressed peptides labelled with different

isotopic markers. For each lysine residue the peptide mass is increased by 105.02, 109.05,

111.04 or 115.07 Da respectively depending on the label used. Depending on the number of

states compared, the peptides consequently appear as doublets, triplets or quadruplets in the

MS-spectra (Brunner et al 2010b). For the analysis of complex samples, an additional

fractionation step (e.g. by 1D-PAGE) is required and the workflow has been described by

Paradela et al (2010) (Figure 4).

Figure 4. Diagram of the standard experimental workflow used in the analysis of ICPL- labelled samples from Paradela et al (2010).

Conventional ICPL protocols label the proteins prior to enzymatic digestion, which means

the samples can be combined to reduce technical variance in downstream processes (Turvey

et al 2014). The disadvantage is that only 60 to 70% of the identified proteins can be

quantified (Fleron et al 2010, Leroy et al 2010). Three reasons have been presented. The

first is that not all lysine containing peptides of a particular protein are sighted in a particular

LC-MS run, probably because the post labelling trypsin digestion results in rather long

peptides (Leroy et al 2010). The second is that ICPL reacts with lysine, which can interfere

with protease digestion (Fleron et al 2010). The third is that only lysine-containing peptides

can be quantified (Leroy et al 2010). Paradela et al (2010) found that only between 54% and

21

64% of Salmonella enterica identified proteins were amenable to quantification and

therefore proposed modifying the technique by labelling at the peptide level (not protein

level) immediately after protein digestion.

Labelling at the peptide level should allow tagging of all peptides as they target the N-

terminal primary amine, which would mean that potentially all proteins could be quantified

(Leroy et al 2010). Fleron et al (2010) and Leroy et al (2010) utilised ICPL labelling at the

peptide level and to our knowledge, this has not been used to investigate protein expression

in E. faecalis.

1.7 Continuous culture in the post-genomic era

Hoskisson and Hobbs (2005) presented an excellent overview on the value of continuous

culture using the chemostat, which was developed simultaneously in 1950 by Monod, and

Novick and Szilard. The chemostat enables the study of bacterial growth in defined physio-

chemical conditions that are constant and separated from the fluctuations present when

bacteria are grown in batch culture. The principle underlying continuous culture is that the

growth rate of an organism, relative to its maximum growth rate is determined by the

availability of a limiting nutrient. Growth medium is pumped into the chemostat and is

balanced by the outflow of depleted medium and a combination of living and dead cells.

Chemostat usage was prevalent in the 1960s and became widely accepted as a way of

culturing cells under conditions which closely resembled the in vivo environment. More

recently continuous culture has experienced resurgence when utilizing techniques such as

proteomics, transcriptomics and metabolomics as they require growth in a stable

environment where single growth parameters can be manipulated and others held constant.

The use of a chemostat enables the acquisition of reliable biological samples and is ideally

suited to proteomic studies investigating biological responses to specific growth conditions.

1.8 Overall aims of the study

Previous studies investigating the stress response of E. faecalis to high pH have focused

predominantly on the transcription of generalised stress response genes coding for

intracellular proteins and the response of proton/nutrient pumps. An understanding of

changes in cell membrane protein expression at alkaline pH may help to elucidate other

mechanisms for adaptation and survival associated with endodontic therapy. The aim of this

22

study was to grow E. faecalis in continuous culture at pH 8 and pH 11, using conditions

appropriate to an endodontically treated root canal and compare the phenotype and

differential membrane protein expression. ICPL was used in conjunction with MS/MS for

identification and quantification of up- and down regulated proteins.

23

Chapter 2. Experimental Investigations

2.1 Effect of alkaline pH on growth rate and phenotypic expression of E. faecalis V583

2.1.1 Abstract

The mechanisms by which E. faecalis can persist in a highly alkaline environment are poorly

understood. The majority of studies investigating survival use bacteria grown in batch

culture, which does not replicate the growth rate in the organism’s natural environment. The

maximum growth rate was determined for E. faecalis V583 at pH 8 and pH 11 and with the

use of a chemostat, an imposed growth rate was set at one-tenth of the relative maximum

growth rate for each pH condition. After growth equilibration was achieved in the chemostat,

samples were harvested and prepared for SEM analysis. The maximum growth rate

decreased from 1.16 hours at pH 8 to 7.7 hours at pH 11. At pH 11 there was evidence of

spontaneous biofilm production.

Keywords: Enterococcus faecalis, Alkaline pH, Biofilm

2.1.2 Background

Bacteria inhabit a wide range of environment conditions, but ultimately spend most of their

time in a starving or non-growing state (Hecker & Volker 2001), and many have the capacity

to adapt to changing conditions. E. faecalis is a commensal organism found in the human

oral cavity, gastro-intestinal tract and vagina. Within the gastro-intestinal tract it survives an

acidic pH, but it is also found to persist in root canals that have been treated with the strongly

alkaline medicament calcium hydroxide and with a limited nutrient supply (Distel et al 2002,

Siqueira & Rôças 2004).

Expression of intracellular, membrane-associated and extracellular proteins play a crucial

role in the response to a changing extracellular environment, but there is conflicting evidence

on the role of protein expression in response to calcium hydroxide. The majority of the

proteins identified to be associated with a response to an increase in pH are intracellular and

the role of membrane-associated and extracellular proteins remains unclear (Flahaut 1997,

Evans 2002, Appelbe & Sedgley 2006, Zilm et al 2007).

24

The majority of studies in the endodontic literature that have investigated the efficacy of

irrigants and medicaments have used bacteria grown in the planktonic phase in batch culture.

Bacteria replicate by binary fusion, which is a form of asexual reproduction producing two

daughter cells. In a closed system, four phases of growth have been determined, namely the

lag phase, the log phase, the stationary phase, and the final death phase. The growth through

these phases is usually reliably reproducible when faced with a new nutrient rich

environment. The lag phase is characterised by initial growth that is slow as the bacteria

adapts to the environment and prepares for rapid growth (Prats et al 2006).

The log phase or exponential phase is when the most rapid replication is undertaken and the

rate of division is termed the growth rate, with the time taken for the population to double

being termed the generation time (td). The exponential phase continues until the nutrient

source starts to become depleted and thereby limits rapid growth. This latter phase is termed

the stationary phase in which there may be induction of stress proteins in an attempt to adapt

to the restricted conditions (Hecker & Völker 2001).

The final phase is death, when the bacteria ultimately die. Under ideal conditions growth

rate is high with cellular division occurring rapidly but under conditions of nutrient

depravation, reproduction is slowed down. In extreme conditions it is thought that some

bacteria, including E. faecalis may even enter a viable but non-cultivatable state (Portenier

et al 2003).

The transition between growth phases (lag, log and stationary) in a closed system involves

sudden differences in the environment with each change dramatically affecting the

bacterium’s chemical composition, structure and functionality (Keevil et al 1987). Genomic

or proteomic studies on bacteria in a closed system are virtually impossible as gene

expression are likely to be growth phase dependent.

Alternatively, continuous culture in a chemostat more closely resembles growth in the

organism’s natural environment as the growth rate is dependent upon a limiting nutrient and

physiological conditions such as oxygen levels, pH can be tightly controlled. Steady state is

achieved in a chemostat when bacteria grow at a constant rate in a constant environment

(Hoskisson & Hobbs 2005). If a single growth parameter is changed, such as nutrient supply,

25

pH or oxygen level, the steady state of the culture will re-establish to reflect the changed

environment.

In a closed system the td during log phase is fixed but in continuous culture the specific

growth rate (μ) becomes variable and can be set to closely represent the in vivo environment.

At steady state, μ is numerically equal to the Dilution rate (D) of the growth medium in the

culture vessel (Keevil et al 1987). The dilution rate is a function of the flow rate of the

nutrient medium and the volume of the culture vessel, such that:

Td= Ln2/µ

At steady state, D=µ and therefore Td = Ln2/D

D (h-1) = Flow rate (mLhr -1)/ Volume of culture vessel (mL)

The purposes of this study were two-fold. The first was to determine the effect of an

increased pH on the maximum growth rate of E. faecalis V583 when grown in a chemostat,

and the second was to investigate the phenotypic changes when the culture was grown at a

tenth of the relative maximum growth rate at pH 8 and pH 11.

2.1.3 Methods

E. faecalis ATCC V583 strain was purchased from Cryosite (NSW, Australia) and

maintained on Columbia blood agar (Oxoid, Victoria, Australia) at 37°C. Culture purity was

periodically checked by culturing onto Bile Aesculin agar (Oxoid). E. faecalis was grown

by continuous culture using a model C30 BioFlo Chemostat (New Brunswick Scientific,

Edison NJ USA) with a culture volume of 365 mL. Growth was initiated by inoculating the

growth chamber containing Todd Hewitt Broth (THB) (92 g/4 L) with a 24 hour THB-grown

batch culture of the organism. THB was pumped through the chemostat and growth pH was

maintained at 8.0 by the automatic addition of 2 M KOH or 2 M HCl using a Fermac 260

pH controller (ElectroLab, Tewkesbury UK). Half the volume of the culture vessel was then

removed and quickly re-filled with THB. When the culture temperature had stabilised and

was also maintaining the controlled pH level, 10 mL aliquots were removed each hour and

the biomass determined by measuring the optical density (OD560 nm). The OD readings were

log transformed against time and the maximum growth rate (μmax) determined. Duplicate

replicates were performed for pH 8 growth conditions.

26

After the µmax was determined at pH 8, the medium flow rate was set at 0.1 rel (21.5 mL/h-

1) giving a dilution rate of 0.059 h-1 and an estimated generation time of 11.69 hours which

is typical of natural ecosystems (Hamilton et al 1979). After equilibration (ten generations),

10 mL cell culture samples were harvested daily over a four week period and pooled. The

pH in the chemostat was then incrementally increased to 11. After a period of approximately

one month (~60 generations) and using the same protocol as used for pH 8, attempts were

made to determine the maximum growth rate whilst maintaining the controlled pH level.

The procedure was repeated numerous times but there were large variations in the growth

curves and the exponential growth phase could not reliably be determined.

As an alternative, 30 mL of the THB growth medium was transferred to sterile tubes,

adjusted to pH 11 with the addition of KOH and then inoculated with 3 mL of E. faecalis

V583 recovered from the chemostat in which the growth conditions had been maintained at

pH 11 for approximately six weeks. 1 mL aliquots were removed each hour and the biomass

determined by measuring the optical density (OD560 nm). The maximum growth rate was

determined as above in triplicate.

Bacteria grown at each pH were harvested by centrifugation (6,000x g), at 4°C for 20

minutes. 1 mL of each sample was used for SEM analysis. Standard SEM sample processing

was undertaken. After the samples had undergone critical point of drying they were coated

with carbon and gold and analysed under a SEM (Philips XL 30, field emission SEM;

Eindhoven, The Netherlands).

2.1.4 Results

2.1.4.1 pH 8

The maximum mean generation time for E. faecalis grown in batch culture in THB at pH 8

was 1.27 hours and 1.05 hours, resulting in an average of 1.16 hours.

The dilution rate for maximum growth (μmax) was determined by the following equation

Td = ln2/D, where Td is the doubling time and D the Dilution rate.

D= 0.69/1.16

= 0.59 h-1 (μmax)

27

The dilution rate was set to 0.1 μrel (.059 h-1). The flow rate (F= mL/h) in a chemostat

chamber of 365 mL was determined by:

D = F/vol

μmax D = 0.59 h-1

0.1 μrel D = 0.059 h-1

F = 0.059 x 365 mL(volume of chemostat)

= 21.5 mL/hr-1

The generation time was determined by the following equation:

Td = ln2/D

0.69/0.059 h-1 = 11.69 hours

Steady state was achieved over ten generations (116.9 hours) before harvesting cells for

analysis.

A SEM of bacterial cells grown at pH 8 is shown in Figure 5. The cocci shaped cells show

little evidence of an extracellular matrix.

28

Figure 5. SEM of E. faecalis grown at pH 8 in continuous culture with an imposed generation time of 12 hours (0.1 μrel).

2.1.4.2 pH 11

The mean generation time, for E. faecalis grown in batch culture in THB at pH 11 was 7.7

hours for all replicates (Appendix 1).

Using the same equations as for pH 8, the dilution rate at maximum growth (μmax) was .09

h-1. Growth at 0.1 μrel, therefore was indicative of a generation time of 77 hours. Steady state

was achieved after 10 generations (770 hours) and the flow rate set to 3.3 mL/hr-1 (365 mL

working volume of chemostat x 0.009h-1).

29

2.1.4.3 Phenotypic differences

An observation of note was that that chemostat chamber became coated with a biofilm at pH

11. SEM analysis (Figure 6) revealed round cocci cells surrounded by an extracellular

matrix.

Figure 6. SEM of E. faecalis grown at pH 11 in continuous culture with an imposed generation time of 77 hours (0.1 μrel).

2.1.5 Discussion

During balanced growth, the cell’s composition, size, metabolism and protein expression

respond to changes in growth rate (Mehmeti et al 2012). Many publications examining

protein expression in bacteria use an overnight planktonic culture, which in many cases does

not represent growth of the organism in vivo. Many bacteria grow in nature as a biofilm,

however the heterogeneous physiological state of biofilm inhabitants makes it difficult to

quantify changes in protein expression in response to external stimuli. In an attempt to mimic

environmental conditions, a relative growth rate (μrel) can be determined and used to provide

an indication of gene expression in natural habitats. Comparisons of protein expression

which are dependent upon environmental conditions such as pH can then be investigated.

When a tooth is undergoing endodontic therapy the chemo-mechanical phase will limit the

30

nutrient availability to microorganisms in the canal and those that have penetrated the

dentinal tubules by removing necrotic pulp tissue. The additional application of a calcium

hydroxide dressing will initially create an alkaline environment (~pH 12) but as the

medicament diffuses through dentine, the pH is buffered and reduces to ~pH 9 to 10

(Nerwich et al 1993, Siqueira & Lopes 1999).

The maximum growth rate of E. faecalis at pH 11 was approximately eight times lower than

when grown at pH 8. The decreased growth rate is an indication of a stressful environment

in which greater metabolic energy is required for cell survival whilst genes involved in cell

division are repressed (Padan et al 2005). In order to represent a more realistic in vivo

environment within a root canal, the supply (flow) of THB was reduced to give a relative

growth rate of one-tenth the maximum growth rate for each pH condition. This was an

arbitrary parameter as the actual in vivo growth rate within a root canal is unknown. However

the mean generation time for dental plaque ranges from 3 to 4 hours for developing

supragingival plaque and 3 to 14 hours for organisms colonizing tooth fissures (Socransky

et al 1977, Hamilton et al 1979).

At pH 11 there was phenotypic evidence of clumping of the cells into flocs (a variant of

biofilm formation) with coatings around the cells consistent with the production of

extracellular polymeric substances (EPS). Survival of E. faecalis has been shown to decrease

to 0.001% at pH 11 (Appelbe & Sedgley 2007) and in combination with the spontaneous

production of EPS, which would contribute to optical density readings, helps explain the

difficulty trying to establish the μmax at pH 11 within the chemostat.

There are numerous adaptations of alkali-tolerant bacteria that facilitate their ability to grow

at alkaline pH including cation/proton transporters, proton capture at the cell surface, acid

production from the metabolism of certain amino acids and sugar fermentation, and

modifications to the secondary cell wall polymers (Padan et al 2005). Of the survival

strategies, the cation/proton antiporters are reported to play the dominant role in alkali-

tolerant and extremely alkaliphilic bacteria (Padan et al 2005) and is perhaps the most

important survival strategy for E. faecalis (Evans et al 2002). The import of H+ ions into the

cell provides two main functions; the first is to lower the cytoplasmic pH and the second is

to provide the proton motive force required for ATP generation by ATP synthase.

31

2.1.6 Conclusion

The maximum growth rate was determined and found to be different for E. faecalis grown

at pH 8 and 11. Growth at pH 11 significantly reduced the generation time compared to

growth at pH 8. The extreme alkaline conditions produced a shift towards spontaneous

biofilm formation which was consistent with the appearance of an extracellular matrix. The

exact mechanism(s) by which E. faecalis is able to adapt and survive this extreme alkaline

pH, in particular the membrane proteins remains poorly understood and warrants further

investigation.

32

2.2 1D SDS-PAGE and in-solution proteomic analysis of E. faecalis membrane proteins: Pilot study

2.2.1 Abstract

The study of Gram-positive bacterial membrane proteins is hampered by their

hydrophobicity, extreme iso-electric points and relatively low abundance compared to

cytosolic proteins. The aim of this pilot study was to investigate two protocols to recover

and optimise membrane protein identification. Using E. faecalis V583 grown in batch

culture, cells were harvested by centrifugation and then lysed with a French Press. The cell

envelope was separated by centrifugation and dissolved in SDS buffer. The first approach

utilised in-solution digestion with typsin. In the second approach, 1D SDS-PAGE was used

with two prominent bands cut from the gel and then subjected to in-gel tryptic digestion.

LC-MS/MS was performed on the peptides from both approaches, The majority of proteins

identified from both protocols were identified as having a cytoplasmic location. The results

highlight the need to optimise the resolution of the membrane protein fraction to increase

membrane protein purity prior to identification by mass spectrometry

Keywords: Enterococcus faecalis, 1 D SDS-PAGE

2.2.2 Background

E. faecalis is a Gram-positive facultative anaerobic bacteria, and as such contains a cell

envelope that encapsulates the cytoplasmic proteins. The cell envelope consists of a

cytoplasmic membrane in which peripheral and transmembrane proteins are embedded and

the cell wall, which is comprised of a peptidoglycan layer.

Cell wall anchored proteins transcend the peptidoglycan layer and have external cell

projections. Lipoproteins similarly transcend the peptidoglycan layer but also extend to the

cytoplasmic membrane. Peripheral proteins can be identified on the internal surface of the

cytoplasmic membrane, whilst cell wall associated proteins are found on the external surface

of the cytoplasmic membrane and the external surface of the peptidoglycan layer.

The study of cell surface proteins is difficult due to the heavy cross-linking between

peptidoglycan strands which provides a rigid surface, the relative low abundance compared

to cytosolic proteins, their poor solubility, intrinsic hydrophobic nature, alkaline iso-electric

33

points and problematic isolation of pure surface fractions (Nandakumar et al 2005, Cordwell

2006, Solis & Cordwell 2011, Yang et al 2012)

The fundamental stages in the isolation of membrane-associated proteins include growth of

the bacteria, separation of the membrane proteins from the intracellular proteins, digestion

into peptides before analysis by mass spectrometry (MS).

The aim of this pilot study was to evaluate the application of mechanical cell lysis of E.

faecalis using a French Press, separation of the membrane fraction with centrifugation,

recovery of the membrane proteins with either in solution enzymatic digestion or separation

with 1D SDS-PAGE, followed by liquid chromatography tandem mass spectrometry for

protein identification.

2.2.3 Methods

2.2.3.1 Growth conditions

E. faecalis ATCC V583 strain was purchased from Cryosite (NSW, Australia) and

maintained on Columbia blood agar (Oxoid, Victoria, Australia) at 37°C. Culture purity was

periodically checked by culturing onto Bile Aesculin agar (Oxoid). 1000 mL sterile Todd

Hewitt Broth (THB) was inoculated with 1 mL of an overnight broth and incubated at 37°C

for 3 days. Bacteria were harvested by centrifugation (6,000x g), at 4°C for 20 minutes. Cells

were washed twice with saline (0.9% w/v) at 4°C and cells were finally resuspended in 12

mL of ice cold saline. Cells were lysed by two passes (60,000 kPa) through a SLM Aminco

French Press (Thermo Fisher Scientific). Endogenous proteinase activity was controlled

during lysis by the addition of 100 L of bacterial protease inhibitor cocktail (Sigma-

Aldrich, St. Louis MO USA). Nucleic acids were then degraded by the addition of

Deoxyribonuclease I (2000 Units), Ribonuclease A (1000 Units) and MgCl2 (50 mM) and

incubated on ice for 60 minutes. Intact cells were removed by centrifuging twice (8,000x g

at 4C for 5 minutes) and removing the supernatant.

The cell envelope and cytoplasmic contents were separated by centrifugation (15,000x g)

for 20 minutes at 4C. The cell envelope proteins were dissolved in 0.5 mL SDS 4x buffer

with agitation using a 1 mL pipette for 15 minutes. The sample was boiled for 5 minutes,

allowed to cool then centrifuged (12,000x g) for 5 minutes at room temperature. 400 µL of

34

supernatant was then removed and 1.2 mL of Milli Q H2O added. The protein concentration

was determined using a RCDC kit (BioRad, Hercules CA USA).

2.2.3.2 In solution digestion

An aliquot containing 1 mg protein in 1 mL of SDS buffer was prepared for MS analysis

following trypsin digest with reduction and acylation as per the following protocol

(performed by staff at the Adelaide Proteomics Centre).

The sample was precipitated with 6 mL of ice-cold acetone and centrifuged (15,000x g). The

pellet was then resuspended in 0.5 mL Guanidine/Tris/EDTA buffer and sample was then

processed by:

1. 0.5 mL of sample was added onto a VivaspinTM concentrator (Vivaproducts,

Massachusetts, USA) and reduced to a volume of about 80 µL.

2. Reduced with 5 µL 1 M dithiothreitol (DTT) in 100 mM ammonium bicarbonate.

3. Alkylated with 20 µL of 0.55 M iodoacetamide (IAA) (Sigma-Aldrich).

4. Digested with 20 µg of sequencing grade modified trypsin (Promega Corporation,

Madison, Wisconsin, USA) in 50 mM ammonium bicarbonate

The sample peptides were extracted and reduced by vacuum centrifugation to approximately

5 µL then resuspended with 50 µL 0.1% FA in 3% Acetonitrile (ACN).

2.2.3.3 1D SDS-PAGE

40 uL of sample (1.0 mg mL-1) was loaded onto a Criterion TGX Precast gel (BioRad) and

separation performed at 200 V constant voltage. After completion, two prominent resolved

protein ‘bands’ were cut from the gel and subjected to in-gel tryptic digestion. Briefly, the

samples were washed in 500 µL of 50 mM ammonium bicarbonate (NH4HCO3) and

processed as follows:

1. Destained with 50 mM ammonium bicarbonate in 30% ACN.

2. Reduced with 0.5 µmol DTT in 100 mM ammonium bicarbonate.

3. Alkylated with 2.75 µmol IAA in 100 mM ammonium bicarbonate.

4. Digested with 100 ng of sequencing grade modified trypsin (Promega) in 5 mM

ammonium bicarbonate in 10% ACN

5. Resulting peptides were extracted using 3 washes of 1% formic acid (FA) in water, 1%

FA in 50% ACN and 100% ACN respectively.

35

The volumes of the resulting peptide extracts were reduced by vacuum centrifugation to

approximately 1 µL then resuspended with 0.1% FA in 2% ACN to a total volume of ~10

µL.

2.2.3.4 Liquid chromatography - Orbitrap tandem mass spectrometry (LC MS/MS) of protein samples

LC MS/MS was performed using the Ultimate 3000 RSL HPLC (Dionex, Germany) and the

LTQ Orbitrap XL ETD mass spectrometer (Thermo Fisher Scientific) coupled via the

Nanospray Source I (Thermo Fisher Scientific). The HPLC and Mass Spectrometer were

connected using a Nanospray Source I (Thermo Fisher Scientific) and a nanospray emitter

(New Objective, MA). The column used was Acclaim® PepMap RSLC 75 µm x 15 cm

(Dionex) as the analytical column and Acclaim® PepMap RSLC 75 µm x 2 cm as the

enrichment column.

Two µL of sample was loaded on the enrichment column at a flow rate of 3 µL min-1 in

Mobile Phase A (0.1% FA in 2% v/v ACN) and resolved with 2 to 40% B gradient of Mobile

Phase B (0.1% FA in 80% w/v ACN) over 30 minutes at a flow rate of 300 nL min-1.

Ionizable species (300 < m/z < 2000) were trapped and the six most intense ions eluting at

the time were fragmented by collision-induced dissociation (CID) or electron transfer

dissociation (ETD) dependent on charge state and mass-to-charge ratio (m/z). The following

data-decision tree was used for selecting precursors for ETD instead of the default CID

fragmentation:

Charge state 3 and m/z < 650

Charge state 4 and m/z < 900

Charge state 5 and m/z < 950

Active exclusion was used to exclude a precursor ion for 5 seconds after selection for

fragmentation.

2.2.3.5 Data analysis

Data analysis was performed using the XCalibur software (Version 2.0.7, Thermo Fisher

Scientific). MS/MS spectra were extracted and submitted to the Mascot search engine using

36

Proteome Discoverer (Version 1.3, Thermo Fisher Scientific). Protein localisation was

determined using PSORT.

2.2.4 Results

Identification of the three membrane proteins from the most highly resolved 1D SDS-PAGE

gel bands were all predicted as having a cytoplasmic localisation. The majority of the 65

identified proteins from the in-solution digest (Appendix 2) were also predicted to have a

cytoplasmic location. Due to the low number of identified proteins obtained with both

protocols and the propensity for a cytoplasmic localisation, no further analysis of these

proteins was conducted.

2.2.5 Discussion

For species in whose genome has been sequenced, high-throughput computational methods

have been developed to predict the subcellular localisation of proteins (Zhou et al 2008).

Combining the predicted locations from the 1D-SDS-PAGE bands and the in-solution

samples, it became readily apparent that before any further proteomic studies were

conducted, it was necessary to optimise the membrane protein fraction using alternative

protocols to increase membrane protein purity.

Future experiments were therefore directed at pre-fractionation of the proteome so that cell

wall and membrane proteins could be enriched and specifically characterised. Similar

techniques have been used for secretomics, phosphor-proteomics, and metallo-proteomics

(Yang et al 2012).

Nandakumar et al (2005) investigated various cell lysis and solubilisation methods to

enhance proteomic analysis of membrane and cell wall associated proteins from

Staphylococcus aureus. The authors used the enzyme lysostaphin to lyse bacterial cells

instead of mechanical disruption which can cause heating of the sample and is prone to

cytosolic protein contamination. It also reduces multiple ultracentrifugation steps which can

result in a loss of low abundant proteins. Following lysostaphin treatment, solubilisation of

membrane proteins using a combination of urea, thiourea, amidosulfobetaine 14 (ASB 14)

and dithiothreitol (DTT) yielded the best sample range for subsequent 2DE and mass

spectrometric analysis (Nandakumar et al 2005). 2DE however has severe limitations for

37

investigating the predominantly hydrophobic membrane proteins, due to limited solubility

and their abundance is often too low to be readily observed (Solis & Cordwell 2011).

Alternative techniques used for producing surface-enriched protein preparations have been

described by Solis and Cordwell (2011).

2.2.5.1 Cell wall digestion

Enzymatic digestion of the peptidoglycan wall, under isotonic conditions allows the

protoplast to remain intact and for the selective release of surface proteins (Figure 7A).

2.2.5.2 Cell surface shaving

Cell surface-exposed proteins are removed by enzymatically shaving the surface (Figure

7B). Released peptides are then subjected to mass spectrometry (Cordwell 2006) to identify

and quantitate proteins. A major advantage is that there is little or no contamination from

cytoplasmic proteins (Rodríguez-Ortega 2006).

Proteolytic digestion of the exposed regions of membrane proteins from intact cells utilises

proteases, for example trypsin, that are site-specific over a short incubation period. All

surface proteins, including membrane-embedded proteins that traverse the cell wall are

targeted. It is important that the cell does not rupture and are therefore kept under isotonic

conditions that limit osmotic disruption. False positive strategies have been employed to

help reduce the number of cytosolic contaminants (Solis & Cordwell 2011).

Benachour et al (2009) used enzymatic treatment with mutanolysin or in vivo trypsinolysis

to extract the outer surface proteins from E. faecalis JH2-2, and then analysed them by gel

electrophoresis or with liquid chromatography-electrospray ion trap tandem mass

spectrometry. The authors found eight secreted proteins and 38 cell surface proteins. Two of

the proteins were common to both groups and 35 of the 44 proteins had signal peptide or

transmembrane domains consistent with an extracellular localisation. The authors concluded

that the in vivo trypsinolysis could be amenable to micro-preparative separations allowing

high-throughput analysis to identify bacterial membrane proteomes. Conventional trypsin

treatment led to cell lysis, but after several attempts the authors found that trypsin digestion

in ammonium bicarbonate (pH 8) containing 0.5 mol L-1 sucrose for cells in the stationary

phase worked well.

38

2.2.5.3 Cell surface labelling

Impermeable tags or other molecules such as Cy dyesTM and biotin are used to bind to

surface-exposed proteins on intact cells, but not to the inner components of the cell (Figure

7C). The membrane-embedded proteins are also not targeted. The protein fractions are then

extracted and the tagged proteins identified by fluorescent imaging using differential in-gel

electrophoresis (DIGE) or affinity chromatography. Biotin has a low molecular weight and

has a high specificity for avidin, which allows for an easy and selective purification process

(Solis & Cordwell 2011). However extreme care must be taken not to induce cell lysis or to

affect cell permeability as all of the cytoplasmic proteins will be labelled (Solis & Cordwell

2011).

Surface labelling coupled to strong cation exchange (SCX) chromatography and LC-MS/MS

is an emerging technology in the identification of cell envelope proteins.

Figure 7. Summary of cell envelope fractionation techniques from Solis & Cordwell (2012). (A) Cell wall digestion for Gram-positive organisms, (B) Cell surface shaving for Gram-positive organisms, (C) Cell surface labelling for Gram-positive and Gram-negative organisms, (D) Membrane precipitation/extraction for Gram-positive and Gram-negative morphologies, (E) Membrane shaving applicable to Gram-positive or Gram-negative organisms.

Integral membrane proteins have a number of functions including initiation of signal

transduction pathways and detection of external environment changes. This group of

39

proteins is particularly difficult to analyse as they are integrated with the membrane and have

poor solubility. The following techniques have been developed:

1. GeLC-MS/MS

SDS is an effective detergent to dissolve highly hydrophobic membrane proteins, but this is

not compatible with 2-DE. A label-free quantitative proteomic strategy termed GeLC-

MS/MS has been developed in which membrane proteins can be separated by 1-D SDS-

PAGE and then bands of equal size can be excised, digested, purified and analysed by LC-

MS/MS (Solis & Cordwell 2011, Yang et al 2012). The SDS denatures all proteins in a cell

lysate, but must then be removed before downstream analysis methods. Combinations of

other separation or enrichment techniques can be used in conjunction with GeLC-MS and

biotinylation. The disadvantages of this technique are poor reproducibility and resolution

(Yang et al 2012).

2. Sodium carbonate precipitation

Membranes have traditionally been enriched by differential centrifugation or by

precipitation by sodium carbonate (pH~11), which allows solubilisation of peripheral, and

integral membrane proteins in strong detergents. In contrast to cell-wall digestion, cell-

surface shaving and cell-surface labelling, the cells are lysed and then the membrane fraction

enriched by precipitation with sodium carbonate (Solis & Cordwell 2011). Following

precipitation, detergents such as SDS or zwitterionic detergents can be used to extract

proteins. SDS is extremely effective for solubilising proteins, but it is not compatible with

isoelectric focusing (IEF), however it is compatible with 1-D SDS-PAGE (Solis & Cordwell

2011).

3. Proteinase-K/chymotrypsin shaving of membranes

Membrane shaving is different to cell surface shaving in that the membrane has been

previously extracted and purified, and all proteins within the membrane are targeted rather

than just surface exposed proteins. Membrane shaving can be achieved with the use of

proteases such as chymotrypsin, pronase or proteinase-K, which allow mild digestion in the

presence of detergents and high surface coverage by releasing membrane-embedded

peptides. There is no need for membrane solubilisation and the peptides that are generated

can be directly analysed by LC-MS/MS (Solis & Cordwell 2011).

40

Wolff et al (2008) investigated the efficacy of three fractionation approaches and found that

a combined approach of 1D SDS-PAGE and membrane shaving produced the highest

recovery of membrane associated proteins.

2.2.6 Conclusion

Membrane-embedded proteins are especially difficult to study due to the innate

hydrophobicity of the transmembrane domain. Recovery of the E. faecalis membrane

proteins utilizing in-solution enzymatic digestion or separation with 1D SDS-PAGE

followed by liquid chromatography tandem mass spectrometry for protein identification was

hampered by ‘contamination’ with cytosolic proteins. Searching the proteomic literature, a

number of fractionation protocols have been used to enrich for integral membrane proteins

with membrane shaving showing the greatest promise (Wolff et al 2008). Optimisation of

membrane protein isolation for E. faecalis requires verification before being used on

precious experimental samples.

41

2.3 Isolation and identification of E. faecalis membrane proteins using membrane shaving and one-dimensional SDS-PAGE coupled with mass spectrometry

2.3.1 Abstract

E. faecalis is a significant nosocomial pathogen which is able to survive in diverse

environments and resist killing with antimicrobial therapies. The expression of cell

membrane proteins play an important role in how bacteria respond to environmental stress.

As such, the capacity to identify and study membrane protein expression is critical to the

understanding of how specific proteins influence bacterial survival. E. faecalis V583 was

grown in batch culture and the cells were lysed with a French Press. The membranes were

fractionated by ultracentrifugation, homogenisation in carbonate buffer, and then by either

membrane shaving or by 1Dimensional-SodiumDodecyl Sulfonic acid-Poly Acrylamide Gel

Electrophoresis (1D SDS-PAGE), coupled with Liquid Chromotography-Electro Spray

Ionisation mass spectrometry (LC-MS). Two hundred and twenty two membrane-associated

proteins were identified which represents approximately 24 percent of the predicted

membrane-associated proteome. One hundred and seventy were isolated using 1D-SDS-

PAGE and 68 with membrane shaving, with 36 proteins being common to both techniques.

Ninety seven percent of the proteins identified by membrane shaving were membrane

associated with the majority being integral membrane proteins (89%). The majority of

proteins identified with known physiology are involved with transportation across the

membrane. The combined 1D-SDS-PAGE and membrane shaving approach produced the

greatest number of membrane proteins identified from E. faecalis to date.

Keywords: Enterococcus faecalis, Proteomics, 1D-SDS-PAGE, Membrane shaving, Mass

spectrometry

2.3.2 Background

The cytoplasmic membrane of a bacterium plays a crucial role in homeostasis and the ability

to invade, adapt and respond to the extracellular environment. Membrane proteins that are

expressed have a wide variety of functions including nutrient uptake, response to

environmental stress, adhesion, virulence, biofilm formation and antibiotic resistance

(Paulsen et al 2003, Bourgogne et al 2008). Integral membrane proteins are also important

42

in the initiation of signal transduction pathways, allowing the bacterial cell to adjust its

physiology to changes in the external environment (Solis & Cordwell 2011).

Enterococcus faecalis is a Gram-positive facultative anaerobe that is resistant to vancomycin

and as such represents a significant nosocomial burden. E. faecalis is used within the food

industry in certain cheeses and sausages and is a commensal organism within the

gastrointestinal tract (Fisher & Phillips 2009, Zehnder & Guggenheim 2009). However, it

has also been recovered from patients suffering endocarditis, bacteraemia, urinary tract

infections, wound infections and meningitis (Richards et al 2000). It is often present in teeth

with root canal fillings that have evidence of persistent infection (Siqueira & Rôças 2004).

E. faecalis demonstrates a remarkable ability to survive a wide range of environmental

conditions including the extremes of gastric acid and high pH used in dental medicaments

(Nakajo et al 2006). The complete genome sequence has been published by Paulsen et al

(2003) but only a fraction of the total 781 (approximately) membrane proteins have been

isolated and identified (http://www.cmbi.ru.nl/locatep-db/cgi-bin/locatepdb.py). Nine

membrane embedded proteins were identified in E. faecalis V583 by Bøhle et al (2011) and

64 in E. faecalis OG1X by Maddalo et al (2011), the latter being the most comprehensive

study of the membrane proteome to date. The diversity of function makes membrane proteins

potential targets for the development of drugs or medicaments, which may improve the

efficacy of current therapeutic strategies.

Proteomic studies of cell membrane proteins are hampered by their low abundance and the

hydrophobic nature of the trans-membrane domain (Speers et al 2007). Standard proteomic

approaches combining 1- or 2D-polyacrylamide gel electrophoresis (PAGE) and mass

spectrometry generally use strong chaotropic agents or strong detergents (traditionally SDS)

to solubilise membrane proteins which are ultimately poorly represented against highly

abundant cytoplasmic proteins. A number of fractionation protocols have therefore been

used to enrich for bacterial membrane proteins before identification by mass spectrometry

(Solis & Cordwell 2011).

Enrichment of membrane proteins is an obvious approach to significantly reduce sample

complexity and improve the resolution of the bacterial membrane proteome. This is typically

achieved by isolation of membranes following cell lysis and by differential centrifugation or

precipitation with cold sodium carbonate. Sodium carbonate linearises and precipitates

membranes which then allows solubilisation of peripheral and integral membrane proteins

43

in detergents (Solis & Cordwell 2011). These can then be separated using techniques such

as anion exchange chromatography (Maddalo et al 2011) and 1D-SDS-PAGE (Wolff et al

2008). While membrane enrichment reduces sample complexity, the associated downstream

separation steps can still produce losses of poorly solubilised and/or highly hydrophobic

membrane proteins. Proteins containing multiple transmembrane domains are particularly

difficult to recover and are rarely identified, if at all (Wolff et al 2008). Accordingly,

methods that reduce sample complexity without introducing sample-hungry fractionation

steps are highly desirable. Recently, the generation and isolation of transmembrane domain

(TMD) peptides using membrane shaving has been shown to complement other membrane

enrichment techniques (Speers et al 2007, (Wolff et al 2008). Briefly, membrane shaving

involves treating extracted membranes with proteinase-K to digest exposed hydrophilic

domains leaving behind only the membrane-embedded domains, which are then digested

using chymotrypsin. The transmembrane domain (TMD) peptides are then separated and

identified directly using mass spectrometry (Speers et al 2007).

Recently, Wolff et al (2008) used LC-MS/MS to compare 1D-SDS-PAGE, strong cation

exchange (SCX) chromatography and membrane shaving to resolve the membrane proteome

of Staphylococcus aureus. They identified 271 integral membrane proteins (IMPs) and found

1D-SDS-PAGE and membrane shaving approaches to be highly complementary. Membrane

shaving yielded almost exclusively IMPs (96.7%).

In this present study, the protocols used by Wolff et al (2008) have been adapted with the

aim of increasing the current resolution and identification of the membrane proteome of E.

faecalis.

2.3.3 Methods

2.3.3.1 Growth conditions

As per section 2.2.3.1 (page 33).

2.3.3.2 1D SDS-PAGE

The protein concentration of the cell-free lysate was determined using the Coomassie Plus

(Bradford) Assay Kit (Thermo Fisher Scientific) and membrane proteins were purified from

100 mg of crude protein. Following ultracentrifugation (100,000x g, 60 minutes, 4C) the

44

pellet was homogenised in 8 mL high salt buffer (20 m MTris-HCl, pH 7.5, 10 mM EDTA,

1M NaCl) containing Protease inhibitor and incubated for 30 minutes at 4C on a rotary

shaker. The solution was then ultracentrifuged (100,000x g, 60 min, 4C) and the pellet

homogenised in 8 mL/100 mM Na2CO3-HCl, pH 11, 10 mM EDTA, 100 mM NaCl.

Following ultracentrifugation, (100,000x g, 60 minutes, 4C) the pellet containing the

bacterial membrane was washed with 8 mL, 50 mM triethylammonium bicarbonate (TEAB)

pH7.8 buffer and then ultracentrifuged (100,000x g, 60 minutes, 4C) before the pellet was

homogenised in 500 μL/50 mM TEAB, pH 7.8 buffer. The protein concentration was

determined according to the Bradford Assay described above. An aliquot containing 20 μg

of the purified membrane protein was reduced with 4 mM Tributylphosphine (TBP)

(BioRad) at 50C for 30 minutes. Alkylation of the samples was performed with 10 mM

iodoacetamide (BioRad) in the dark for 30 minutes. The sample (500 uL) was then purified

using a 2D clean-up kit (BioRad) following the manufacturer’s instructions.

20 uL was loaded onto a Criterion TGX Precast gel (BioRad) and separation performed at

200 V constant voltage. After completion, the gel lane was cut into 12 equal sized pieces

and subjected to in-gel tryptic digestion. Briefly, the bands were reduced with 10 mM

dithiothreitol (DTT) in 100 mM ammonium bicarbonate. Alkylation of proteins was

performed using 2.75 mol iodoacetamide (IAA) in 100 mM ammonium bicarbonate.

Overnight digestion was performed using 100 ng of sequencing grade modified trypsin

(Promega Sydney, NSW Australia) in 5 mM ammonium bicarbonate containing 10%

acetonitrile (ACN). The digest was stopped by addition of 30 L of 1% formic acid followed

by 15 minutes in a sonicating water bath. The supernatant was kept and two further

extractions using 50 L of 1% formic acid in 50% ACN and 50 ul of 100% ACN with

sonication for 15 minutes were performed. For each gel piece, extracts were pooled. The

volumes of the resulting peptide extracts were reduced by vacuum centrifugation to

approximately 2 L then re-suspended with 0.1% TFA in 2% ACN to a total volume of ~10

L.

2.3.3.3 Membrane shaving

The protein concentration of the cell-free lysate was determined as described previously and

adjusted to 1 mg/mL-1 with saline. An aliquot containing 60 mg of protein was pelleted by

ultracentrifugation (100,000x g at 4C for 1 hour) and the membranes were washed in

phosphate buffered saline (PBS) followed by further ultra-centrifugation (100,000x g at 4C

45

for 1 hour). The pellet was carefully re-suspended in 1000 L of carbonate buffer (200 mM

Na2CO3 pH 11.0) using an insulin syringe to homogenise the pellet. The sample was

incubated on ice for 1 hour and homogenised every 15 minutes. The protein concentration

of the homogenised pellet was determined and the concentration adjusted to 1 mg/mL-1 with

carbonate buffer. With the sample at room temperature, solid urea (BioRad) was added to a

concentration of 8 M. Samples were reduced with 4 mM Tributylphosphine (TBP) (BioRad)

at 50C for 30 minutes. Alkylation of the samples was performed with 10 mM IAA in the

dark for 30 minutes. Proteinase K (Sigma-Aldrich) was then added to the sample in an

enzyme:protein ratio of 1:50 and incubated overnight at 35C on a shaker. An equal volume

of 10% ACN (Thermo Fisher Scientific) in water was added and the sample was cooled on

ice for 15 minutes. Samples were then ultracentrifuged (100,000x g at 4C for 1 hour) and

the supernatant was discarded and the pellet rinsed with 50 mM TEAB (pH 8.4 to 8.6) to

remove residual urea. Membranes were then pelleted by centrifugation (100,000x g) at 4C

for 1 hour.

The pellet was re-suspended in 200 l of TEAB 10 mM calcium chloride and 0.5% RapiGest

(Waters. Milford Massachusetts, USA). 4 g of chymotrypsin (Sigma-Aldrich) was added

and digestion performed for 6 hours at 30C (with shaking). RapiGest® was removed by

incubation in 0.25 M HCl solution (pH<2) for 45 minutes at 37C.

The sample was then centrifuged three times (20,000x g at 4C for 15 minutes) each time

collecting the supernatant containing peptides.

The resultant supernatant was then analysed with LC-MS/MS by staff at the Adelaide

Proteomics centre. Peptides were desalted and concentrated using C18 spin column (Thermo

(Pierce) Rockford, IL USA). Peptides were eluted using ACN:TFA:H2O (70:0.5:29.5, v/v)

and freeze dried. The lyophilised peptides were re-suspended using ACN:TFA:H2O

(2:0.1:97.9, v/v). The volumes of the resulting peptide extracts were reduced by vacuum

centrifugation to approximately 2 L then re-suspended with 0.1% TFA in 2% ACN to a

total volume of ~10 L.

2.3.3.4 Liquid chromatography - electrospray ionisation tandem mass spectrometry

Peptides were separated on an Ultimate 3000 HPLC system (Dionex) coupled to a LTQ

Orbitrap XL mass spectrometer (Thermo Fisher Scientific). Samples (5 uL) were injected

46

into a trapping column (Acclaim PepMap100, C18, pore size 100 Å, particle size 3 µm, 75

µm ID × 2 cm length) and then resolved on a separation column (Acclaim PepMap RSLC,

C18, pore size 100 Å, particle size 2 µm, 75 µm inner diameter (ID) × 15 cm length). The

HPLC solvent A was 2% ACN, 0.1% FA in water and solvent B was 80% ACN, 0.1% FA

in water. Peptides were eluted at 300 nL/min-1 flow rate with the following 100 minutes

gradient: 4% B for 10 min, gradient to 40% B over 50 min, gradient to 90% B in 20 min,

90% B for 10 min, gradient from 90% to 4% B in 30 s, 4% B for 19.5 minutes. The LTQ

Orbitrap XL instrument was operated in data-dependent mode to automatically switch

between full scan MS and MS/MS acquisition. Instrument control was through Thermo Tune

Plus and Xcalibur software (Thermo Scientific).

A full scan MS spectra (m/z = 300 to 1700) was acquired in the Orbitrap analyser and

resolution in the Orbitrap system was set to r = 60,000. The standard mass spectrometric

conditions for all experiments were spray voltage, 1.25 kV, no sheath and auxiliary gas flow,

heated capillary temperature, 200°C, predictive automatic gain control (AGC) enabled, and

an S-lens RF level of 50 to 60%. All unassigned charge states and charge state of +1 were

rejected. The six most intense peptide ions with charge states ≥2 and minimum signal

intensity of 1000 were sequentially isolated and fragmented in the high-pressure linear ion

trap by low energy CID. An activation q = 0.25, activation time of 30 ms and normalised

collision energy of 35% were used. The resulting fragment ions were scanned out in the low-

pressure ion trap at the “normal scan rate” (33,333 amu s-1) and recorded with the secondary

electron multipliers.

Raw data files were subjected to the Proteome Discoverer software (Thermo Scientific) to

set up the workflow, files were then submitted to MASCOT (Version 2.2; Matrix Science

Inc., Boston, USA, 2007) by the Proteome Discoverer Daemon (Thermo Scientific). Peak

lists in the range from 350 m/z to 5000 m/z were searched against the NCBInr database with

the enzyme setting of trypsin for the 1D gel pieces, and enzyme setting of chymotrypsin for

the membrane shaving samples. Protein identifications were made on the basis of having at

least two unique peptides. These unique peptides were required to have different sequences

or different variations of the same sequence, for example, containing a modified residue or

missed cleavage site. Multiple charge states were not considered as unique.

47

2.3.3.5 Protein analysis

The proteins identified from both 1D SDS-PAGE and membrane shaving isolation

techniques were searched using the Locate P database (http://www.cmbi.ru.nl/locatep-

db/cgi-bin/locatepdb.py) to determine the predicted localisation. The total number of

membrane-associated proteins and intracellular proteins were determined for each

membrane enrichment protocol and for proteins common to both techniques. The

membrane-associated proteins were then cross matched with the published results of Paulsen

et al (2003), Ruffuveille et al (2011), Maddalo et al (2011) and Bøhle et al (2011) for

comparison with previous identifications and predicted roles in biofilm formation, stress and

virulence.

The NCBI protein data base (http://www.ncbi.nlm.nih.gov) was searched using the gene

name derived from Locate P to obtain the FASTA format for each membrane associated

protein, which was then used to search with TMHMM Server v.2.0

(http://www.cbs.dtu.dk/services/TMHMM/) for a prediction of the number of

transmembrane helices and also searched with ExPASy ProtParam

(http://web.expasy.org/protparam/) for the GRAVY scores.

2.3.4 Results

A total of 513 proteins were identified with both 1D SDS-PAGE and membrane shaving

protocols. The predicted localisation of the proteins identified were categorised with both

LocateP and the LocateP prediction by SwissProt classification (Table 1). The IMPs include

LocateP predictions of Multi-transmembrane, Multi-transmembrane (lipid modified N-

termini) and N-terminally membrane anchored locations. For the purposes of this study, the

membrane-associated proteins include the Lipid-anchored locations in addition to IMPs

(Figure 3).

48

Predicted localisation

LocateP prediction by

SwissProt Classification 1D

SD

S

PA

GE

Sha

ving

1D &

S

havi

ng

No.

of

iden

tifi

ed

prot

eins

No.

in th

e E

. fae

cali

s V

583

geno

mea

Per

cent

of

pred

icte

d id

enti

fied

Multi-transmembrane Membrane 92 58 32 118 581 20

Multi-transmembrane

(lipid modified N-termini)

Membrane 3 1 1 3 7 43

N-terminally membrane anchored

Membrane 41 3 1 43 193 22

Lipid-anchor Extracellular 34 6 2 38 74 51LPxTG cell-wall

anchor Cell Wall 1 1 2 42 5

Secreted Extracellular 9 0 0 9 55 16Intracellular Cytoplasmic 299 1 300 2303 13

a Data from LocateP (Zhou et al 2008)

Table 1. Predicted localisation and number of identified membrane proteins using 1D-SDS-PAGE and membrane shaving.

Four hundred and seventy nine proteins were identified using 1D SDS-PAGE with 170 of

these predicted to be membrane-associated (35.5%) and 299 intracellular (62.4%). The

membrane shaving protocol yielded a total of 70 proteins with 68 (97%) predicted to be

membrane-associated, one intracellular (1.4%) and one attached to the cell wall (1.4%).

There were 36 membrane associated proteins that were common to both 1D SDS-PAGE and

membrane shaving approaches giving a total of 202 unique membrane-associated proteins.

This represents 24% of the total 855 predicted proteins (Zhou et al 2008) (Table 2). Of the

202 membrane-associated proteins recovered, 164 were IMPs which represent 21% of the

781 predicted IMPs. In addition to membrane-associated proteins, two proteins were

predicted to be located on the cell wall, one from each protocol, and there were nine secreted

proteins identified using 1D SDS-PAGE. In total, 213 proteins that were not cytosolic were

identified.

The 1D SDS-PAGE and membrane shaving protocols resulted in 58 and 25 proteins

respectively that were common to the membrane associated proteins identified by Maddalo

et al (2011) and Bohle et al (2011) with 15 proteins common to both protocols. Hence, 145

proteins were unique to the present study (Appendix 3).

49

Ballering et al (2009) described 68 genetic loci predicted to be involved in biofilm formation

by E. faecalis. The 1D-SDS-PAGE and membrane shaving protocols in the current study

identified the expression of four and five corresponding proteins respectively with two being

common to both protocols (Appendix 3).

Paulsen et al (2003) genomic study predicted 50 proteins played a role in the organism’s

stress response. In the present study, 12 and 6 proteins were identified using 1D SDS-PAGE

and membrane shaving respectively, with five identified in both protocols (Appendix 3).

Of the 148 proteins in E. faecalis implicated in virulence, (Paulsen et al 2003, Reffuveille et

al 2011) 28 and 7 were identified using 1D SDS-PAGE and membrane shaving respectively,

with two being common to both protocols. The physiological classification of identified

membrane associated proteins was determined by cross referencing with Paulsen et al

(2003), Wolff et al (2008), Maddalo et al (2011) and Reffuveille et al (2011). Of the 213

proteins with known function, the majority are involved with membrane transport (Table 2).

Function 1D SDS-PAGE

Membrane Shaving

Common to both Total

Percentage of all

membrane associated proteins

Transport & binding 40 33 16 57 26.76

Virulence 28 7 2 33 15.49Protein

translocation & processing

7 4 1 10 4.69

Stress 10 4 4 10 4.69Metabolism 7 7 3.29

Miscellaneous 10 0 10 4.69Cell

membrane/cell wall division

9 2 1 10 4.69

Unknown 57 16 7 76 35.68

Table 2. Physiological classification of the 213 membrane proteins identified from 1D-SDS-PAGE and membrane shaving protocols.

50

The 1D-SDS-PAGE protocol favoured the recovery of proteins with a smaller number of

TMDs, whereas the membrane shaving protocol was useful in recovering proteins within the

full range of 0 to 14 TMDs, but especially those with a higher number. The percentage of

proteins identified and the number of TMDs in relation to the isolation protocol is shown in

Figure 8.

Figure 8. Allocation of membrane associated proteins in respect to their number of TMDs using 1D-SDS-PAGE or membrane shaving.

The GRAVY scores (the sum of hydropathy values of all amino acids divided by the protein

length) given for proteins identified by 1D-SDS-PAGE and membrane shaving are shown

in Figure 9.

51

Figure 9. Frequency of GRAVY indices of membrane associated proteins recovered with 1D-SDS-PAGE and membrane shaving protocols.

2.3.5 Discussion

In the present study, the combined approaches of Na2CO3/1D-SDS-PAGE and membrane

shaving have identified approximately 24% of the theoretical membrane proteome of E.

faecalis V583. To our knowledge, this is the best recovery to date (Zhou et al 2008) and is

approximately twice that of previous reports (Maddalo et al 2011). Maintaining intact cells

as spheroplasts or cell lysis prior to membrane enrichment are the two main approaches used

to identify surface attached, secreted or cell membrane proteins. Bøhle et al (2011) employed

proteolytic shaving of the intact bacterial cells with trypsin and recovered 36 surface-located

proteins, of those with surface located/exposed domains, three (0.5%) were annotated as

integral membrane proteins. The low recovery was thought to be due to limited accessibility

of the proteins and the limited ability of trypsin to penetrate the cell wall (Bøhle et al 2011).

Alternatively the ability of trypsin to cleave sites in membrane proteins necessary for mass

spectrometry identification could also limit detection (Wolff et al 2008). In contrast to the

intact-cell methods, Maddalo et al (2011) lysed cells with a French Press before membrane

purification and enriched cell membranes by ultracentrifugation. In a similar fashion, this

method was used in the current study to create the crude membrane extract and the cell

membrane was precipitated using carbonate buffer as previously described (Eymann et al

2004, Speers et al 2007, Wolff et al 2008). Enrichment with sodium carbonate has been

52

shown to linearise and precipitate membranes, and allows solubilisation of peripheral and

transmembrane proteins in strong detergents (Solis & Cordwell 2011).

Membrane-embedded proteins are especially difficult to recover due to the hydrophobic

nature of the transmembrane domain. Following purification of the cell membrane, Maddalo

et al (2011) separated the proteins using anion exchange chromatography and identified

them by mass spectrometry. One hundred and two proteins were resolved with 64 (63%)

identified as membrane embedded. The authors predicted that they had experimentally

identified ~10% of the membrane embedded proteome of strain OG1X, which was the

largest recovery of such proteins at the time. The 102 proteins identified could be classified

as 64 membrane-embedded (63%), 9 lipoproteins (9%), 16 soluble components of

membrane proteins complexes (16%) and 13 were soluble with no predicted membrane

association (13%).

From in silico analysis, there are 781 predicted membrane-embedded proteins in the E.

faecalis V583 genome ((http://www.cmbi.ru.nl/locatep-db/cgi-bin/locatepdb.py) and in the

present study, the combined approaches resolved 21 percent (164 proteins). The 1D SDS-

PAGE approach resulted in a total number of 479 proteins identified with 170 being

membrane associated (35.5%) and 299 intracellular. This is a very similar result to Wolff et

al (2008) for S. aureus who reported 572 proteins with 179 being IMPs (31.3%).

In the present study two complementary membrane fractionation techniques were combined

to isolate and identify the highest number of membrane-associated proteins from E. faecalis.

Wolff et al (2008) identified 182 proteins in S. aureus using membrane shaving, of which

176 (96.7%) were determined to be IMPs. Recovery of IMPs using this protocol was much

lower with only 68 proteins recovered, however the proportion of proteins being IMPs was

similar (97%). The discrepancy in the total number of proteins identified could be due to the

mass spectrometry search parameters used, for example, setting the number of missed

cleavages. If the digest is not completely perfect and peptides remain with intact cleavage

sites, increasing the level of missed cleavages increases the number of calculated peptide

masses to be matched against the experimental data. However, this increases the number of

random matches and therefore reduces discrimination

(http://www.matrixscience.com/help/search_field_help.html). Wolff et al (2008) searched

with no enzyme specificity and with chymotrypsin allowing four missed cleavage sites. In

53

order to improve the reliability of identification, a search allowing two missed cleavages was

undertaken and an additional search only with chymotrypsin was also undertaken.

Highlighting the complimentary nature of the isolation protocols, 1D SDS-PAGE favoured

the recovery of proteins with a lower number of TMDs and negative GRAVY scores,

indicative of hydrophilic proteins. The protocol was superior for isolating N-terminally

membrane anchored (with usually 1 TMD) and Lipid-anchored proteins. Membrane shaving

was especially good at the recovery of proteins with a large number of TMDs and identified

predominantly hydrophobic proteins with a positive GRAVY score which demonstrates that

this approach is particularly suitable for the identification of very hydrophobic proteins and

is consistent with the analysis of S. aureus (Wolff et al 2008). In the present study, 1D-SDS-

PAGE produced the largest recovery of proteins in all cell locations including the

intracellular region. In contrast, membrane shaving recovered only one intracellular protein

with the majority predicted to be multi-transmembrane or N-terminally anchored to the

membrane (~89%). Proteinase K was used on purified membrane extracts

(ultracentrifugation and carbonate precipitation) thus targeting protein domains that are

surface exposed (Solis & Cordwell 2011). An acid-labile detergent (Rapigest) was then used

to dissolve the hydrophobic bilayer of the membrane and chymotrypsin added to further

digest the liberated membrane-spanning peptides, which were then analysed using LC-ESI

mass spectrometry.

The majority of the identified integral membrane proteins are described as being involved

in transport and binding proteins (28.2%). The high incidence of proteins dedicated to

transport and a large number of proteins with unknown function is a similar finding to

Maddalo et al (2011). This is also consistent with the large theoretical number of predicted

transport membrane proteins in the proteome (Paulsen et al 2003).

The total number of proteins expressed or recovered may vary according to the growth

conditions or protein extraction protocols and likely contributes to some of the differences

between the present study and other published studies. Sixty seven proteins identified in the

present study were common to Maddalo et al (2011) and Bøhle et al (2011). Ballering et al

(2009) carried out a comprehensive analysis of the genetic determinants of biofilm formation

in the core genome of E. faecalis. Of the 68 genes identified by Ballering et al (2009),

Maddalo et al (2011) identified six of these membrane proteins, whilst this study identified

nine.

54

Paulsen et al (2003) reported the complete genome sequence of E. faecalis V583 and

predicted 50 genes from the whole genome to have a potential role in the organism’s stress

response. This study identified one membrane protein associated with oxidative stress

[EF3257], eight for osmotic stress [EF0295, EF0568, EF0875, EF1493, EF1494, EF2612,

EF2613, EF2614] and three for metal-ion resistance [EF1519, EF1938, EF2623]. This

represents 24% of the predicted stress proteins. In addition to the virulence proteins

determined by Paulsen et al (2003), Reffuveille et al (2011) reviewed the identification of

lipoprotein-encoding genes and their potential involvement in virulence. Of the virulence-

related genes predicted to be surface exposed, this study identified thirty three. Growth

conditions in the present study could be considered ideal in terms of nutrient availability,

temperature and pH so it is perhaps not surprising that the recovery of proteins associated

with roles in stress or virulence was low.

A fundamental consideration in identifying membrane proteins is to limit the contamination

by highly abundant cytosolic proteins. The formation of spheroplasts was thought to reduce

cytosolic protein contamination. Seven of the 27 proteins recovered by Benachour et al

(2009) and 34 of the 69 recovered by Bøhle et al (2011) were identified as cytosolic proteins.

This may reflect the intra-cellular association of these proteins with the cell membrane, or

alternatively, may have been due to cell lysis prior to treatment with trypsin. The released

cytosolic proteins may then have re-associated with the cell envelope and escaped

proteolytic degradation. In this study, the 1D SDS-PAGE protocol resulted in 299

intracellular (cytosolic) proteins identified despite membrane precipitation. In contrast,

membrane shaving appeared to be an excellent method to reduce cytoplasmic contamination

as only one protein (EF021) was identified. EF021 is a 50S ribosomal protein, and is one of

the 33 cytosolic proteins identified by Bøhle et al (2011).

2.3.6 Conclusions

A workflow combining 1D-SDS-PAGE and membrane shaving was successful in the

recovery of integral membrane proteins from E. faecalis V583. Of the 202 membrane

associated proteins identified, 81% were membrane embedded and represents approximately

21 % of the predicted membrane-embedded proteome.

These protocols will form a basis for further research into E. faecalis by investigating protein

expression under different growth conditions and aid in the understanding of how E. faecalis

55

adapts to its environment. Whilst the techniques allow for greater purity of membrane

samples, they do not allow for comparison and quantification of protein expression.

56

2.4 Influence of Enterococcus faecalis V583 cell membrane protein expression on biofilm formation and metabolic responses to alkaline stress

NOTE: The cells recovered from Section 2.1 were used to determine cell membrane protein

expression to alkaline stress. For the purposes of maintaining standalone chapters, the

methods and results of Section 2.1 have been repeated.

2.4.1 Abstract

E. faecalis is commonly found in endodontic infections and can resist highly alkaline root

canal medicaments used in endodontic therapy leading to persistent apical periodontitis.

Here we describe the expression and role that cell membrane proteins play in extreme

alkaline conditions. E. faecalis V583 was grown in a chemostat at pH 8 and pH 11 at one-

tenth the organism’s relative maximum growth rate. Cells were lysed and membranes

fractionated by ultracentrifugation, homogenisation in carbonate buffer, and membrane

shaving. Isotope-coding protein labels were added at the peptide level to each sample and

then combined. The relative proportion of membrane proteins was identified using LC-ESI

mass spectrometry and MaxQuant analysis. Ratios of membrane proteins were log2

transformed, with proteins deviating by more than 1 SD of the mean considered to be up- or

down-regulated. Six proteins were up-regulated at pH 11 including EF0669 (polysaccharide

biosynthesis family), EF1927 (glycerol uptake facilitator) and EF0114 (glycosyl hydrolase).

Five proteins were down regulated including EF0108 (C4-dicarboxylate transporter),

EF1838 (PTS system IIC component), EF0456 (PTS system IID component), EF0022 (PTS

mannose-specific IID component). Growth at pH 11 produced biofilm formation and a shift

in metabolism towards glycerol utililisation. Collectively the protein expression was

consistent with a generalised stress response, in addition to creating a microenvironment that

would help facilitate the necessary membrane potential and proton motive force required for

survival in an extreme alkaline environment.

Keywords: Enterococcus faecalis, ICPL, Alkaline pH, Membrane shaving, Biofilm

57

2.4.2 Background

Enterococcus faecalis is a Gram-positive anaerobe that is found in milk products such as

cheese and in fermented sausages for raw consumption (Zehnder & Guggenheim 2009). It

is a common commensal organism in the gastrointestinal tract (surviving the pH extremes

of gastric acid) and the oral cavity (Sedgley et al 2004). The dental pulp is normally protected

from bacteria by dentine and enamel but may become infected subsequent to caries or

traumatic injuries to the tooth (Kakehashi et al 1966). The pulp has a limited capacity to

launch an effective immune response to invading bacteria and due to being enclosed by hard

tissues, inflammation results in an increased intrapulpal pressure, which may cause marked

pain for the patient. As a natural consequence of microbial infection, the pulp may become

necrotic with infectious microorganisms colonizing the main body of the root canal,

penetrating into the dentinal tubules, lateral canals or anastomoses, and ultimately resulting

in inflammation of the periapical tissues (apical periodontitis) (Moller et al 1981). These

microorganisms may then constitute a reservoir to maintain and sustain infection and re-

infection of the root canal system and surrounding tissues, protected from the host immune

cells, systemic antibiotics and root canal treatment (Athanassiadis et al 2007).

One of the fundamental goals in endodontics is the management of apical periodontitis by

using antimicrobial strategies with the outcome of endodontic therapy depending on the

reduction or elimination of microorganisms (Siqueira & Lopes 1999). Endodontic treatment

of a tooth with a severely inflamed, infected or necrotic pulp usually involves the chemo-

mechanical debridement of the canal(s) using metal files, irrigants such as sodium

hypochlorite and often inter-appointment medicaments such as calcium hydroxide (~pH

12.5 to 12.8) placed in the main root canal to help in the elimination of surviving bacteria

(Siqueira & Lopes 1999). The minimum recommended inter-appointment time should be no

less than 7 days, but longer periods have been considered desirable (3 to 4 weeks) to allow

penetration and to maximise hydroxyl ion concentration (from calcium hydroxide) in the

peripheral dentine (Nerwich et al 1993). Calcium hydroxide medicament kills bacteria by

direct contact through pH effects. The release and diffusion of hydroxyl ions, which are

highly oxidant free radicals, show extreme reactivity inducing lipid peroxidation and

consequently the destruction of the phospholipid component of bacterial cell walls (Siqueira

& Lopes 1999). In addition, cellular protein denaturation occurs by the breakdown of ionic

bonds, leading to suppression of enzyme activity and disruption of cellular metabolism,

inhibition of DNA replication by splitting DNA and the formation of free radicals inducing

58

lethal mutations (Siqueira & Lopes 1999). Calcium hydroxide is known to dramatically

reduce the bacterial load of the root canal system with survival of E. faecalis dropping to

0.001% at pH 11 and 0.00001% at pH 12 (Appelbe & Sedgley 2007). The combination of

other antimicrobial strategies aid in removing organic matter from the canal, such as pulp

tissue and in eliminating bacteria. Following the disinfection stages, the root canal is usually

obturated with gutta-percha and an appropriate sealer to prevent (or at least reduce) the

recontamination of the root canal system or the entry of periradicular fluid. Collectively the

stages of root canal treatment render the canal a hostile, nutrient depleted environment

making bacteria survival a challenge. However, even in this hostile environment, bacteria

can survive and lead to persistent apical periodontitis..

In teeth that have been root filled, infection may persist due to inadequate microbial

elimination (Nair 2006) or due to reinfection of the root canal system usually as a result of

a defective coronal restoration or caries (Ray & Trope 1995). E. faecalis is more commonly

isolated from persistent infections compared to primary infections (89.6% versus 67.5%)

(Sedgley et al 2006) suggesting that it has the capacity to survive the chemo-mechanical

procedures (Yap et al 2014) and to survive in a nutrient limited environment (Sedgley et al

2005). In addition, it has been postulated that a virulence factor of E. faecalis in failed

endodontically treated teeth is the ability to invade dentinal tubules in the presence of human

serum and to adhere to collagen (Love 2001).

It remains uncertain as to whether there are specific survival mechanisms to alkaline stress

such as the activation of ion-transport systems to balance intracellular and external pH levels

(Evans et al 2002), intrinsic resistance, neutralisation of medicaments by bacterial cells, or

products, an alteration in gene expression to the specific changes in the environmental

condition (Siqueira & Lopes, 1999) or whether a more generalised adaptive survival

response occurs with a common set of proteins being expressed (Petrak et al 2008, Wang et

al 2009).

Biofilms are defined as matrix-enclosed bacterial populations adherent to each other and/or

to surfaces or interfaces encased in a matrix of extracellular polymeric substance (EPS), and

exhibiting altered growth phenotypes (Costerton et al 1995, Donlan and Costerton 2002).

Biofilm formation can be regarded as a generalised adaptation to environmental conditions

including an infected, pulpless root canal system (Nair 2006) and production has been shown

to increase with an increase in pH (Zilm & Rogers 2007, Hostacka et al 2010). Zilm and

59

Rogers (2007) found that elevated pH (greater than 8.2) produces a shift from a planktonic

lifestyle to the spontaneous flocculation and biofilm formation by F. nucleatum. The

protective strategies of biofilms include comparatively slow growth, reduced antibiotic

susceptibility, the uptake of large complex nutrient molecules, removal of potentially

harmful metabolic products, the exchange of genetic material and the transfer of virulence

factors, and the development of an appropriate physiochemical environment to facilitate

microbial survival (Stewart & Costerton 2001, Socransky & Haffajee 2002, Distel et al

2002). Dense biofilms of bacteria have been located within the dentinal tubules, isthmuses

and irregularities, which can protect bacteria deeper in the biofilm or deeper inside dentinal

tubules (Siqueira & Lopes 1999, Nair 2006).

Distel et al (2002) demonstrated that when E. faecalis was inoculated into roots medicated

with calcium hydroxide the canals became colonised by the cells, initially in short chains

which then developed into biofilms. This transformation may either be the normal growth

state (Seet et al 2012), or serve as a protective system to facilitate survival in the high pH

and/or limited nutrient environment. It has not been determined in the literature as to whether

this response to high pH is a generalised response to an extreme environment, similar to

those proposed for antibiotic resistance, or whether the increased pH triggers a different

biofilm response.

During balanced growth, the cell’s composition, size, metabolism and protein expression

respond to changes in growth rate (Mehmeti et al 2012). Many publications examining

protein expression in bacteria use an overnight planktonic culture, which in many cases does

not represent growth of the organism in vivo. Many bacteria grow in nature as a biofilm with

growth rate regulated by nutrient availability, however it is difficult to quantify changes in

protein expression that occur over a long period of time with the interaction of a number of

variables potentially having an impact on survival. A chemostat can be used in an attempt to

mimic environmental conditions such as reduced growth rates and changes in gene

expression can be observed following changes to the single environmental condition under

consideration.

Cytoplasmic membrane proteins play a crucial role in responding to stressful environmental

conditions including defence against antibiotics and other antimicrobial agents, signal

transduction, transport, binding, energy metabolism and biofilm production (Opsata et al

2010, Solis & Cordwell 2011). The regulation of bacterial metabolic pathways from glucose

60

to other carbohydrates can be influenced by changes in available energy sources, oxygen

concentration, growth rate, exposure to bacteriocins and toxins (Dressaire et al 2008,

Mehmeti et al 2012) which occurs in a complex and strain-dependent manner (Bizzini et al

2010).

Membrane-embedded proteins are especially difficult to study due to the innate

hydrophobicity of the transmembrane domain. A number of fractionation protocols have

been used to enrich for integral membrane proteins with membrane shaving showing the

greatest promise (Wolff et al 2008). Membrane shaving for E. faecalis was demonstrated to

be highly effective in Section 2.3, with 97% of the proteins identified being membrane

associated, 89% of which were integral membrane proteins.

In order to compare the protein expression of organisms grown in two or more different

conditions, labelling techniques such as isotope coding protein label (ICPL) can be

employed. ICPL is a non-isobaric technique in which N-hydroxysuccinimide (NHS) labels

the primary amine on lysine residues and the protein or peptide N-termini. The technique

therefore improves proteome coverage compared to ICAT protocols (Section 1.6), which

rely on labelling less abundant cysteine residues (Brunner et al 2010, Fleron et al 2010).

Quantification is determined by mass spectrometry by comparing the relative abundance of

differentially labelled peptides (Paradela et al 2010). Conventional ICPL protocols label

isotopically at the protein level and therefore samples can be combined to reduce technical

variance in downstream processes (Turvey et al 2014). However, for quantitative analysis,

labelling at the protein level has the disadvantage in that only 60 to 70% of the identified

proteins may be accurately quantified (Fleron et al 2010, Leroy et al 2010). This could be a

result of incomplete sighting of lysine containing peptides with LC-MS or possible ICPL

reactions with lysine residues altering the normal sequence sites to trypsin digest (Fleron et

al 2010). In order to overcome these technical issues, Fleron et al (2010) and Leroy et al

(2010) utilised ICPL labelling at the peptide level, but this has not been used to investigate

protein expression in E. faecalis.

In order to develop new treatment strategies to eradicate E. faecalis from persistent

endodontic infections, the mechanisms through which it can form biofilms and survive must

be understood and further research on E. faecalis biofilms may contribute to this

understanding (Distel et al 2002). The present study compared the membrane proteome

expression in E. faecalis grown at one-tenth the maximum growth rate (μrel) using continuous

61

culture set at a growth pH of 8 and 11. Membrane protein purification and protein expression

were performed using membrane shaving, chymotrypsin digest of the membrane fraction in

the presence of RapigestTm detergent and ICPL labelling. The aim of this study was to

identify and understand the role of cell membrane proteins associated with the adaptive

response to extreme alkaline conditions by E. faecalis.

2.4.3 Methods

2.4.3.1 Growth conditions

As per section 2.1.3 (page 25).

Cells from both pH 8 and pH 11 growth conditions were washed twice with saline (0.9%

w/v) at 4oC and were finally resuspended in 12 mL of ice cold saline. Cells were lysed by

two passes (60,000 kPa) through a SLM Aminco French Press (Thermo Fisher Scientific).

Endogenous proteinase activity was controlled by the addition of 100 L of bacterial

protease inhibitor cocktail (Sigma-Aldrich). Nucleic acids were then degraded by the

addition of Deoxyribonuclease I (2000 Units), Ribonuclease A (1000 Units) and MgCl2 (50

mM) and incubated on ice for 60 minutes. To separate unbroken cells, the suspension was

centrifuged twice (8,000x g at 4C for 5 minutes).

2.4.3.2 Membrane shaving

As per 2.3.3.3 (page 44) membrane shaving was conducted on both the pH 8 and pH 11

samples.

MALDI spectroscopy was performed by the staff at the Adelaide Proteomics Centre to

establish the relative concentration of peptides in both the pH 8 and pH 11 samples so that

pH 8 and 11 samples could be normalised when comparing protein expression.

2.4.3.3 Peptide ICPL labelling

Both pH 8 and pH 11 samples were lyophilised and the peptides resuspended in 30 L TEAB

(40 mM, pH 8.5). The samples were then vortexed for 30 sec and then sonicated for 5

minutes.

62

2 L of ICPL_0 label (Serva quadruplex kit) was added to the pH 8 sample and 2 L of

ICPL_6 label (Serva quadruplex kit) was added to the pH 11 sample and both were overlaid

with Argon. The samples were vortexed for 30 seconds and then sonicated for 1 minute

before incubation for 60 minutes at room temperature. A further 1 L of ICPL label was

added to each sample (0 and 6 respectively) and incubated for a further 60 minutes at room

temperature. 2L of STOP solution was added to each sample and incubated for 20 minutes

at room temperature. Equal volumes of sample pH 8 and sample pH 11 (with ICPL-labels)

were loaded into a Protein LoBind tube, mixed gently and then desalted and concentrated

using C18 spin column. Peptides were eluted using ACN:TFA:H2O (70:0.5:29.5, v/v) and

freeze-dried. The lyophilised peptides were re-suspended using ACN:TFA:H2O (2:0.1:97.9,

v/v). The volumes of the resulting peptide extracts were reduced by vacuum centrifugation

to approximately 2 L then re-suspended with 0.1% TFA in 2% ACN to a total volume of

~10 L.

2.4.3.4 Liquid chromatography - electrospray ionisation tandem mass spectrometry

Peptides were separated on an Ultimate 3000 HPLC system (Dionex) coupled to a LTQ

Orbitrap XL mass spectrometer (Thermo Fisher Scientific). Samples (5 uL) were injected

into a trapping column (Acclaim PepMap100, C18, pore size 100 Å, particle size 3 µm,

75µm ID × 2 cm length) and then resolved on a separation column (Acclaim PepMap RSLC,

C18, pore size 100 Å, particle size 2 µm, 75 µm inner diameter (ID) × 15 cm length). The

HPLC solvent A was 2% ACN, 0.1% FA in water and solvent B was 80% ACN, 0.1% FA

in water. Peptides were eluted at 300 nL/min-1 flow rate with the following 100 minutes

gradient: 4% B for 10 minutes, gradient to 40% B over 50 minutes, gradient to 90% B in 20

minutes, 90% B for 10 minutes, gradient from 90% to 4% B in 30 seconds, 4% B for 19.5

minutes. The LTQ Orbitrap XL instrument was operated in data-dependent mode to

automatically switch between full scan MS and MS/MS acquisition. Instrument control was

through Thermo Tune Plus and Xcalibur software (Thermo Fisher Scientific).

A full scan MS spectra (m/z = 300 to 1700) were acquired in the Orbitrap analyser and

resolution in the Orbitrap system was set to r = 60,000. The standard mass spectrometric

conditions for all experiments were spray voltage, 1.25 kV, no sheath and auxiliary gas flow,

heated capillary temperature, 200°C, predictive automatic gain control (AGC) enabled, and

an S-lens RF level of 50 to 60%. All unassigned charge states and charge state of +1 were

rejected. The 6 most intense peptide ions with charge states ≥2 and minimum signal intensity

63

of 1000 were sequentially isolated and fragmented in the high-pressure linear ion trap by

low-energy CID. An activation q = 0.25, activation time of 30 ms and normalised collision

energy of 35% were used. The resulting fragment ions were scanned out in the low-pressure

ion trap at the “normal scan rate” (33,333 amu s-1) and recorded with the secondary electron

multipliers.

Raw data files were subjected to the Proteome Discoverer software (Thermo Scientific) to

set up the workflow. Files were then submitted to MASCOT (Version 2.2 2007; Matrix

Science Inc, Boston USA) by the Proteome Discoverer Daemon (Thermo Fisher Scientific).

Peak lists in the range from 350 m/z to 5000 m/z were searched against the NCBInr database

with the enzyme setting of chymotrypsin. Protein identifications were made on the basis of

having at least two matching unique peptides. These unique peptides were required to have

different sequences or different variations of the same sequence, for example, containing a

modified residue or missed cleavage site. Multiple charge states were not considered as

unique.

2.4.3.5 Protein analysis

Data from the MASCOT search was searched through MAXQUANT (version 1.3.0.5). The

ICPL_6 labelled proteins from pH 11 conditions were designated as “H” (heavy)-labelled,

whilst ICPL_0 labelled proteins from pH 8 conditions were designated “L” (Light). The

search allowed for protein quantification on a single H/L count (i.e. just one peptide ratio)

and was restricted to ENTFA V583. The proteins were searched using the LocateP database

(http://www.cmbi.ru.nl/locatep-db/cgi-bin/locatepdb.py) to determine the predicted

localisation. The total number of membrane-associated proteins and intracellular proteins

were determined. The NCBI protein database (http://www.ncbi.nlm.nih.gov) was used to

obtain the FASTA format for each membrane-associated protein, which was then used to

search with ExPASy ProtParam (http://web.expasy.org/protparam/) for the GRAVY scores

(a measure of protein hydrophobicity).

The MAXQUANT H/L ratios of membrane-associated proteins were log2 transformed, and

the proteins that deviated by more than 1 standard deviation of the mean were considered to

be up- or down regulated.

64

2.4.4 Results

2.4.4.1 Continuous culture

As per section 2.1.4 (page 26).

2.4.4.2 ICPL labelling

A total of 136 proteins were identified and ~90% (123 proteins) with both an ICPL_6

(Heavy) and ICPL_0 (Light) label could be quantified between the pH 11 and pH 8 samples

(Appendix 4). The predicted localisation of the proteins identified was categorised with both

LocateP and the LocateP prediction by SwissProt classification (Table 3).

Predicted localisation

LocateP prediction by

SwissProt Classification

No. of identified proteins

No. of genes that encode E. faecalis

V583 genomea

Percent of predicted identified

Multi-transmembrane Membrane 72 581 12.4Multi-transmembrane

(lipid modified N-termini) Membrane 3 7 42.9

N-terminally membrane anchored Membrane 3 193 1.6

Lipid-anchor Extracellular 4 74 5.4LPxTG cell-wall anchor Cell Wall 1 42 2.4

Secreted Extracellular 2 55 3.6Intracellular Cytoplasmic 51 2303 2.2

a Data from LocateP (Zhou et al 2008)

Table 3. Predicted localisation and number of identified membrane proteins using membrane shaving.

Seventy-eight proteins were classified as integral membrane proteins (IMPs) (57.4%)

representing 10% of the predicted number (781) in the genome database (Paulsen et al 2003,

Zhou et al 2008) (http://www.cmbi.ru.nl/locatep-db/cgi-bin/locatepdb.py). The majority of

membrane associated proteins were involved with membrane transport (Figure 12).

65

Figure 12. Physiological classification of membrane proteins identified using membrane shaving.

The majority of proteins identified had a positive GRAVY score (the sum of hydropathy

values of all amino acids divided by the protein length), which provides a measure of protein

hydrophobicity (Figure 13).

Figure 13. Frequency of GRAVY indices of membrane associated proteins, positive gravy scores represent proteins that are hydrophobic in nature.

Comparing the abundance ratios between the two growth conditions, six proteins had a log2

H/L ratio (pH 11/pH 8) greater than 1SD of the mean: Phage tail protein EF2096 (3SD),

0

2

4

6

8

10

12

‐1.2 ‐1 ‐0.8 ‐0.6 ‐0.4 ‐0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4

No.ofProteins

GRAVY

DISTRIBUTIONOFGRAVYSCORES

66

Membrane protein EF1541 (1SD), Polysaccharide biosynthesis family protein EF0669

(2SD), Glycosyl hydrolase, family 20 EF0114 (4SD), Uncharacterised protein EF2938

(1SD), Glycerol uptake facilitator protein EF1927 (1SD). Whilst five proteins had a log2

ratio 1 SD less of the mean: PTS system IIC component EF838 (1D), PTS system IID

component EF0456 (2SD), Predicted nucleoside ABC transporter EF0177 (1SD), C4-

dicarboxylate transporter EF0108 (1SD), PTS system mannose-specific IID component

EF0022 (1SD) (Appendix 5).

2.4.5 Discussion

The experimental model using ICPL means that only peptides that are labelled with either

heavy or light isotopes are included in the comparative analysis, and only proteins identified

at pH 11 matched to proteins expressed at pH 8 were investigated further. The ratio of the

ion intensities represented the relative abundance of the protein in the original samples.

Within the membrane shaving protocol, proteinase-K almost exclusively yields peptides

from the exposed hydrophilic domains in membrane proteins (e.g. loops), while

chymotrypsin cleaves at the carboxy terminus of phenylalanine, tyrosine and tryptophan and

is effective at cutting the hydrophobic domains found in trans-membrane proteins. The

majority of the identified proteins had a positive GRAVY score (Figure 11), which is

consistent with the hydrophobic nature of transmembrane proteins and the efficacy of the

membrane shaving protocol.

From in silico analysis, there are 781 predicted membrane-embedded proteins of E. faecalis

V583 (http://www.cmbi.ru.nl/locatep-db/cgi-bin/locatepdb.py) and in the present study the

combined approaches of membrane shaving, ICPL and LC-MS and quantification with

MAXQUANT protocols resolved approximately 10%. This is a comparatively good result

considering proteins needed to be present in both pH 8 and pH 11 growth conditions, and is

consistent with the findings of Maddalo et al (2011). Maddalo et al (2011) identified ~10%

of the membrane embedded proteome of strain OG1X, being the largest recovery of such

proteins to date. As a membrane shaving protocol preselects for only membrane-associated

proteins, the intracellular proteins identified were not included in comparative analysis

between the pH 8 and pH 11 growth conditions.

67

The efficacy of calcium hydroxide medicament in vivo can be reduced by a decrease in

hydroxyl ion concentration due to the buffering effect of dentine as well as the low solubility

and diffusibility of calcium hydroxide from the medicament paste, making a rapid rise in pH

levels difficult to achieve (Siqueira & Lopes 1999). The maximum pH level that is achieved

throughout the tooth root is thought to be ~pH 9 to 10 (Nerwich et al 1993). This current

study design ensured that the E. faecalis cells were exposed to a constant pH 11 by the

controlled addition of KOH to the chemostat, thereby allowing investigation of the direct

chemical effect on the cells over a long period of time. The maximum growth rate decreased

from 1.0 hour at pH 8, to 7.7 hours at pH 11. This reduction is consistent with pH being the

most important variable of growth in enterococcus species (Fisher & Phillips 2009).

Sampling of the chemostat occurred after 10 generations (117 hours for pH 8 and 770 hours

for pH 11) in which the bacterial populations would have reached steady state and there had

been sufficient time for the cells to adapt to the growth conditions.

There was a dramatic change in the phenotypic appearance of the culture at pH 11 compared

to pH 8, with aggregation of the cells and evidence of an extracellular capsule encasing

bacterial cells (Figure 2). Collectively, these observations are consistent with the formation

of floating biofilms (flocs) which are not attached to an interface, but which share the

characteristics of biofilms (Zilm & Rogers 2007, Flemming & Wingender 2010). The change

in phenotype is consistent with the SEM observations made by Distel et al (2002) of E.

faecalis exposed to a calcium hydroxide medicament for 77 days.

In this study the up-regulation of polysaccharide biosynthesis family protein (EF0669) was

observed (Figure 14), This most likely has a physiological role in the export of teichoic acid

associated with cell wall/membrane/envelope biogenesis

(http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi).

68

Figure 14. Predicted interaction of E. faecalis cell membrane proteins up- and down-regulated at pH 11.

Shankar et al (2002) examined the genomes of two different strains of antibiotic resistant E.

faecalis and found that virulence determinants were clustered on a large pathogenicity island

(PAI) of approximately 150 kb, which varies only slightly between strains. Of note, EF0669

is homologous to EF0559, which is encoded in the pathogenicity island and therefore

associated with virulence.

In most biofilms the extracellular matrix accounts for approximately 90% of the dry mass

with the extracellular polymeric substances (EPS) consisting of polysaccharides, proteins,

nucleic acids and lipids (Flemming & Wingender 2010). The production and composition of

extracellular polymeric substances is not generic amongst bacteria and is dependent on the

microflora in the milieu (mono or multi-species), as well as the environmental conditions

including nutrient supply, oxygen tension, pH, type of surface attachment, period of growth.

Some of these factors will have variation even within the biofilm structure, e.g. nutrient

availability, oxygen tension and pH.

EPS forms the scaffold for the overall architecture of the biofilm and is responsible for

adhesion and cohesion within the biofilm (Flemming & Wingender 2010). Gram-positive

69

organisms have a thick and rigid cell wall that covers the cytoplasmic membrane and is

heavily cross-linked between peptidoglycan strands (Solis & Cordwell 2011). External to

the peptidoglycan layer, some bacteria secrete further material, which is normally of a

polysaccharide nature as a capsule or is totally dissociated from the cell as amorphous slime

(Sutherland 2007).

Thurlow et al (2009) demonstrated that serotype C (which includes strain V583) and D

serotypes of E. faecalis produce capsular polysaccharides which attach to the peptidoglycan

layer. Determining the composition of an EPS is technically difficult, however Hancock and

Gilmore (2002) identified the capsular carbohydrates most commonly expressed by clinical

isolates to be glycerol, phosphate, glucose and galactose residues. Based on their results,

polysaccharide produced by E. faecalis V583 can be classified as a heteropolysaccharide

(HePS) from lactic acid bacteria (LAB) (De Vuyst & de Vin 2007) with glycerol and

phosphate groups attached to the carbohydrate backbone. Heteropolysaccharides are formed

from two or more sugars, although they rarely contain more than three or four (Sutherland

2007).

Apart from immobilizing cells, EPS has an additional function, which includes incorporating

extracellular enzymes such as hydrolases and lyases, thereby creating a versatile external

‘digestive system’ allowing the dissolution and uptake of nutrients from lysed cells and the

EPS itself (Flemming & Wingender 2010). Glycosyl hydrolase (EF0114) is a matrix-

degrading enzyme (N-acetyl-β-hexosamindase) encoded by the dspB locus. Glycosidases

from pathogens can degrade host glycoproteins, e.g. human immunoglobulin G (IgG),

thereby protecting the bacteria from the immune response (Garbe et al 2014). The ability of

E. faecalis to release glycans from RNaseB (high-mannose glycoprotein) has been ascribed

to the protein EF0114 of E. faecalis V583 with potential activity targeting N-linked glycans

(Collin & Fischetti 2004, Bøhle et al 2011).

The glycosyl hydrolase EF0114 is an endoglycosidase (EndoE) that contains two enzymatic

domains. The α domain contains a family 18 glycosyl hydrolase (GH18) motif while the β

domain contains a family 20 glycosyl hydrolase (GH2O) motif (Collin & Fischetti 2004).

GH18 hydrolyses the polymer of beta-1,4-linked N-acetylglucosamine (GlcNAc) and GH2O

(Beta-N-acetylhexosaminidases) catalyses the removal of beta-1,4-linked N-acetyl-D-

hexosamine residues from the non-reducing ends of N-acetyl-beta-D-hexosaminides

including N-acetylglucosides and N-acetylgalactosides. The GH2O enzymes also include

70

dispersin B (40 kDa glycoside hydrolase produced by the periodontal pathogen,

Aggregatibacter actinomyecetemcomitans which is involved in biofilm dispersion

http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi?seqinput=NP_813917.1).

The function of glycosyl hydrolase in the current study cannot definitively be determined,

but as there are no immunological cells present, the role is more likely to be either degrading

EPS components for nutrient uptake or involvement in biofilm dispersion - the final step in

the life cycle of a biofilm (Flemming & Wingender 2010, Rendueles & Ghigo 2012). The

net outcome of dispersion can enable colonisation of other niches or rescue of bacteria

trapped in the nutrient- and oxygen-deprived matrix (Rendueles & Ghigo 2012).

The most striking observation in this study at pH 11 is that two proteins associated with

nutrient acquisition (glycosyl hydrolase and glycerol uptake facilitator) were up-regulated

whilst the proteins associated with the PTS system and associated glucose metabolism were

down-regulated even though glucose was available for uptake by the PTS (Figure 14).

Carbon catabolite repression (CCR) occurs when sugars such as glucose, fructose, or sucrose

are available in sufficient quantity that the synthesis of enzymes necessary for the transport

and metabolism of less favourable carbon sources are repressed (Deutscher et al 2006).

Regulation is often determined by the concentration of glycolytic intermediates. Glycerol

kinase is responsible for the phosphorylation of glycerol during uptake. The dominant

mechanism for glycerol kinase (Figure 14) repression results from allosteric inhibition by

the glycolytic intermediate, fructose 1,6 bisphosphate (FBP) (Brückner & Titgemeyer 2002).

A major role in carbon catabolite repression is undertaken by the bacterial

phosphoenolpyruvate phosphotransferase system (PEP:PTS), which catalyses the uptake

and phosphorylation of a wide range of carbohydrates (Brückner & Titgemeyer 2002,

Deutscher et al 2006) (Figure 14).

The PEP system phosphorylates a number of hexoses including N-acetylmannosamine,

glucose, mannose, glucosamine, and N-acetylglucosamine (Deutscher et al 2006) with the

mannose PTS being the major uptake system for mannose and glucose in bacteria (Figure

14) (Postma et al 1993). In E. faecalis, phosphate produced by the enzymatic action of

enzyme I (EI) on phosphoenolpyruvate (PEP) are donated to glycerol kinase by an

intermediate histidine containing protein (HPr) (Maurer et al 2001). When glucose is

71

available, the phosphates generated by EI from PEP are used to phosphorylate glucose,

thereby depleting available phosphate for glycerol kinase and rendering it inactive. In

addition, if glucose is available the concentration of FBP will be high and this will

allosterically repress glycerol kinase. When glucose is not available, the phosphate generated

by PEP and EI leads to the phosphorylation of HPr which then donates the phosphate group

to glycerol kinase resulting in the phosphorylation and uptake of glycerol (Figure 14).

The carbohydrate specificity of the PTS system resides in the enzyme IIs (EIIs) which

consist of an integral membrane domain (Deutscher et al 2006). In this study the PTS

mannose specific IID protein (EF0022), PTS system IIC component (EF1838) and PTS

system IID component (EF0456) were all down regulated at pH 11 by more than 1SD of the

mean, suggestive of a shift away from PEP:PTS carbohydrate uptake. The imposed growth

rate was set at one-tenth relative to the maximum growth rate for pH 8 and pH 11 conditions,

and therefore the relative nutritient availability provided by Todd Hewitt Broth was the same

for the different pH conditions under investigation. The altered membrane protein expression

between samples grown at pH 11 and pH 8 are therefore due to the change in pH rather than

a change in nutrient availability.

Glycerol can be an important energy source for pathogenic bacteria and enters cells by

energy-independent facilitated diffusion. Amongst the genes implicated in glycerol

metabolism, three are grouped into an operon coding for glycerol kinase (GlpK), glycerol-P

oxidase (GlpO), and the glycerol diffusion facilitator protein (GlpF1)(glycerol uptake

facilitator) (Bizzini et al 2010). Glycerol facilitator (GlpF) catalyses the equilibration of

glycerol gradients across the cytoplasmic membrane and the subsequent metabolism of

glycerol allows a net (steady state) flux of glycerol into the cell (Deutscher et al 2006).

Glycerol is phosphorylated by glycerol kinase to yield glycerol-3-phophate which is then

oxidised to dihydroxyacetone phosphate, an intermediate of the glycolytic pathway, by

glycerol 3-phosphate oxidase and reversibly isomerised to glyceraldehyde 3-phosphate

(Figure 14) (Bizzini et al 2010).

Glycerol forms one of the repeating units of the extracellular polysaccharide of E. faecalis

(Hancock & Gilmore 2002) with additional potential sources of glycerol coming from the

recycling of lysed cells within the biofilm matrix (Flemming & Wingender 2010).

72

With the up-regulation of the glycosyl hydrolase protein (EF0114) at pH 11 it is likely that

glycerol would potentially be released from the extracellular polysaccharide matrix and be

available for ATP synthesis. Under the principals of carbon catabolite repression, glycerol

metabolism would be repressed by the availability of PTS substrates. Indeed, Deutscher et

al (1993) demonstrated that when E. faecalis is grown in a glycerol containing medium,

GlpK (glycerol kinase) synthesis was induced, however if glucose or mannitol was added to

the medium containing glycerol, the synthesis of GlpK was strongly repressed. The results

from the present study show that at pH 11, some proteins associated with the Man-PTS

systems were down-regulated (suggesting inhibition) whilst the glycerol uptake facilitator

was up-regulated.

Bizzini et al (2010) reported that E. faecalis V583 did not grow on glycerol in aerobic

conditions. Opsata et al (2010) reported a similar finding in which E. faecalis V583 produced

acid from glucose but did not show detectable acid production from glycerol. Bizinni et al

(2010) concluded that strain V583 has an unknown defect in glycerol catabolism although it

is equipped with the entire set of genes. Opposed to the concept of a defect in glycerol

metabolism, Opsata et al (2010) investigated four bacteriocin resistant mutants of E.

faecalis. Two spontaneous mutants were obtained after exposure to the bacteriocin, pediocin

PA-1. Bacteriocins are peptides or proteins which have antimicrobial action against other

bacteria by permeabilisation of the cell membrane using specific membrane targets such as

the mannose phosphotransferase system with the IIC and IID components involved as

receptors (Figure 14) (Opsata et al 2010, Kjos et al 2011).

A third spontaneous mutant obtained by selecting colonies resistant to 2-deoxyglucose (2-

DG - a glycolytic inhibitor) was found to also be resistant to pediocin PA-1. A fourth was

obtained by constructing a strain with an inactivated mannose PTS operon mpt. When the

pediocin resistant mutants were grown in a glucose medium, the mutants showed reduced

glucose consumption but metabolised glycerol quickly. Transcriptional analysis revealed the

most pronounced effects in the pediocin resistant mutants were the strong reduction in gene

expression of the mannose PTS operon.

The combined up-regulation of glycosyl hydrolase family 20 (EF0114) and glycerol uptake

facilitator (EF1927) plus the down-regulation of mannose PEP:PTS was observed in the

mutant strains resistant to bacteriocin reported by Opsata et al (2010). A similar protein

expression was shown in the present study to alkaline pH. This indicates that regulation of

73

these proteins could be part of a more generalised stress response rather than a specific

response to increased pH. The association with a coordinated stress response is strengthened

by EF0022 (PTS Mannose-specific IID) being homologous to the PTS mannose specific IID

component protein EF0553 found in the pathogenicity island of E. faecalis V583 (Shankar

et al 2002).

Whilst the down regulation in the PEP:PTS could be a result of a general stress response

similar to that seen for bacteriocin resistance, it may reflect an adaption to a specific

ecological niche resulting in the choice of an alternative carbohydrate (Brückner &

Titgemeyer 2002).

C4 dicarboxylate transporter (EF0108) was down-regulated in this study. C4- dicarboxylates

(e.g. succinate, fumarate, and malate) and the C4- dicarboxylic amino acid, aspartate are

metabolised by bacteria under aerobic and anaerobic conditions. In the absence of a

functional citric acid cycle, fumarate is used as an electron acceptor during anaerobic

respiration (Janausch et al 2002). The most widely studied C4- dicarboxylate carriers are

those of Escherichia coli, consisting of four different secondary carriers (DcuA, DcuB,

DcuC, and DCtA), which have different roles in uptake, antiport, and efflux of C4-

dicarboxylates (Zientz et al 1999). During glucose fermentation by E. coli, DcuC is an efflux

carrier, expressed with relatively high activities but repressed in the presence of oxygen.

However, inactivation of dcuC significantly increased the fumarate:succinate exchange and

a subsequent increase in the uptake of fumarate by the alternative carriers DcuA and DcuB

carriers (Zientz et al 1999). Searching for the individual carriers in the NCBI

(http://www.ncbi.nlm.nih.gov) and UniProt (http://www.uniprot.org) databases revealed

that only the DcuC carrier seems to be associated with E. faecalis. Whilst direct comparisons

to E.coli must be interpreted with caution, it is possible that the down regulation of EF0108

is an adaptive response to increase the uptake of succinate, which has been shown to play a

role in the creation of the electrical potential difference of the membrane (Kaim & Dimroth

1999).

Von Ballmoos et al (2008) provided an excellent description of the role of ATP synthase

which produces the majority of ATP for the cell. F0F1 ATP synthases are nano-sized rotary

engines with the F0 component in the membrane and the F1 component in the cytoplasm

connected with a rotor (c-ring). Whilst the MaxQuant results in this study predicted EF2610

(F0F1 ATP synthase) to have an intracellular location, there is a membrane component to

74

this protein, which was up-regulated at pH 11. ATP synthase can convert energy stored in

the transmembrane ion gradient into torque causing mechanical rotation of the rotary engine,

which is then converted into the chemical bond energy of ATP from ADP and inorganic

phosphate. In the reverse mode, (ATPase) F1 converts the energy of ATP hydrolysis into

torque causing the F0 motor to pump ions out of the cell. The energy stored in the

transmembrane ion gradient has two components: the ion concentration difference (ΔpH or

ΔpNa+) and the electrical potential difference ΔΨ, which are thermodynamically equivalent

(Kaim & Dimroth 1999) and collectively termed the electrochemical gradient. Usually ATP

synthase operates in the ATP synthesis direction but a low membrane potential is a kinetic

challenge. In addition, the rapid proton capture at the external membrane surface may

concentrate the protons close to the membrane making ATP synthesis energetically feasible

in a high pH environment (von Ballmoos et al 2008). Historically it was thought that ATP

could be synthesised by ATP synthase entirely by ΔpH (Jagendorf & Uribe 1966). However,

Kaim and Dimroth (1999) provided conclusive evidence that a transmembrane voltage is

indispensable for generation of the rotational torque required and cannot be replaced by large

ΔpH or ΔpNa+. Kaim and Dimroth (1998a, 1998b) demonstrated that ATP synthesis was

equally effective with succinate, malonate or maleinate but not with fumarate. In order to

improve the efficacy of both succinate and ATP synthase, it would be desirable to have a

higher concentration of H+ ions on the external surface of the cell.

Upon consideration of the phenotypic changes seen at pH 11 and the physiological roles of

the proteins that were up and down regulated it is proposed that cellular aggregation and the

extracellular polymeric substance coating the cells can act to trap protons near the cell

surface in a microenvironment. This would increase the proton motive force and also

concentrate and acidify succinate, thereby creating the electrical potential difference with an

overall greater transmembrane ion gradient, which would facilitate ATP production by ATP

synthase. The role of secondary cell wall polymers in Bacillus, such as teichuronic acid and

teichuronopeptide, against an alkaline challenge has been assigned to their cation binding

capability, thereby increasing the concentration of H+ ions (Padan et al 2005). The extension

of this effect to the formation of EPS and flocs therefore seems conceivable.

The proton motive force can also be increased by interaction of the bacterial cell with a

surface that has a negative charge. As two surfaces with ionisable surface groups approach

each other, a counterion concentration increases in the solution between the two surfaces,

which for negatively charge surfaces results in an increased concentration of H+ ions (Hong

75

& Brown 2010). This then creates a decrease in the cell surface pH and an increase in ATP

production (Hong & Brown 2010). Whilst the authors were looking at the ionic charge of

surfaces such as crushed and ground glass beads, the alkaline environment in the chemostat

would have caused amino acids present in the EPS to becoming negatively charged. This

possibly could have an effect on the electrostatic potential of the cell, which in turn could

have an additive effect on cellular bioenergetics.

2.4.6 Conclusion

Comparisons of the membrane protein profiles between E. faecalis grown at an imposed

slow growth rate in continuous culture at pH 11 compared to pH 8 resulted in a limited

number of up- and down regulated proteins. Collectively the membrane proteins seem to be

involved in the formation of a protective capsule/EPS that protects the cell from the

destructive OH- ions whilst at the same time concentrating H+ ions and substrates required

for the electrochemical gradient close to the cell membrane (Figure 12). The production of

the EPS is facilitated by an increase in polysaccharide biosynthesis, a shift to glycerol

metabolism as the favoured carbohydrate source with an associated down regulation of the

PTS system:nutrient acquisition via the actions of glycosyl hydrolase and glycerol uptake

facilitator. The roles of membrane proteins in this coordinated response to increased pH have

not been previously reported and may help explain the adaptation of a sub-population of

cells to an extreme alkaline pH and therefore survival of E. faecalis whilst in the presence

of the medicaments used in endodontic therapy.

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Chapter 3. Overall Discussion

The stress response of bacteria to alkaline pH is complex, adaptive and contributes to

virulence and persistence in the environment. Most studies investigating the stress response

have grown bacteria in a planktonic state, or if a biofilm model was used, short periods of

time have been utilised (usually in the order of days to a week). This is in stark contrast to

the nutrient depleted environment that would occur clinically. E. faecalis has been shown to

survive for over a year in root canals ex vivo that had been obturated (Sedgley et al 2005).

The examination of gene expression to increased alkaline conditions coding for intracellular

proteins (Appelbe & Sedgley 2007), or the identification of proteins released into the

extracellular culture (Chávez de Paz et al 2007) have been used to investigate the adaptive

or stress responses of E. faecalis. However to our knowledge the role that cell membrane

proteins play has not been investigated previously.

The aims of this research project were to determine the effect of an extreme alkaline pH on

growth rate, morphology and cell membrane protein expression of E. faecalis.

The first study compared the maximum growth rates in pH 8 and pH 11 conditions. Having

established the maximum growth at pH 8 using continuous culture, the growth rate was

reduced to one tenth of the maximum and sampling commenced after ten generations.

However at pH 11, it was difficult to establish the maximum growth rate using the chemostat

by tipping out most of the contents of the vessel chamber and rapidly filling it with pH

adjusted media. The most likely reason for this is that survival would have dramatically

decreased at the elevated pH (Appleble & Sedgely 2007). Subsequently the time required to

have seen an increase in optical density would have been too great. Alternatively the

maximum growth rate at pH 11 was determined by transferring, 30 mL of the growth

medium was transferred to sterile tubes, adjusting the pH to 11 with the controlled addition

of KOH and then inoculating them with 3 mL of E. faecalis V583 recovered from the

chemostat in which the growth conditions had been maintained at pH 11 for approximately

six weeks.

E. faecalis is classified as being neutrophilic with its optimum growth in the range of pH 7

to 7.5 (Flahaut et al 2007). The results from Chapter 2.1 have demonstrated that a shift from

growth at pH 8, to the extreme alkaline pH 11 resulted in continued survival, albeit at a

reduced maximum growth rate. In order to mimic in-vivo conditions E. faecalis was grown

77

at an imposed growth rate of one tenth the maximum growth rate determined for pH 8 and

pH 11. SEM analysis revealed that neither the imposed growth rate nor a pH of 8 had an

impact on the morphology of the cells, compared to those commonly reported in batch

culture (Chávez de Paz et al 2007). The cocci were round, connected into small chains and

in clumps with evidence of cell division. There was however a dramatic change in the

phenotypic appearance at an imposed slow growth rate and pH 11 with evidence of cellular

aggregation, floc formation and capsule formation. The relative growth rate was kept

constant between growth at pH 8 and pH 11 ensuring that the effects observed are solely

related to an increased pH rather than a change of nutrient supply. In addition, the

aggregation observed is most likely due to the effects of pH rather than the imposed limited

growth rate as a similar finding was reported by Chávez de Paz et al (2007) who

demonstrated aggregation of E. faecalis in both planktonic and biofilm states at exposure to

pH 10.5 for only 4 hours. The SEM images of E. faecalis at pH 11 clearly showed that in

addition to aggregation there had been the production of extracellular polymeric substances.

This is consistent with the extrusion of cellular proteins, slime / capsule production on the

bacteria envelope and/or a shift to biofilm formation (Zilm & Rogers 2007, Chávez de Paz

et al 2007). Bacteria recovered from root canal infections have greater potential to resist

alkaline stress if grown as a biofilm compared to planktonic culture (Chávez de Pas et al

2007). It is known that cell membranes play a role in the production and/or transport of

proteins to the extracellular matrix and a main aim of this research project was to establish

which cell membrane proteins play a role in the adaption of E. faecalis to survive the extreme

alkaline conditions and what role the cell membrane proteins play in the high pH phenotype.

In order to establish an appropriate protocol for the recovery of membrane proteins, batch

grown cells were used and formed the basis of Section 2.2. The initial intention was to

separate the cell membranes from the intracellular contents following cell lysis with a French

Press, and then use either fractionation of the membrane proteins with 1D-SDS-PAGE or in-

solution trypsin digestion before identification and quantitative comparisons with isotope

labelling, mass spectrometry and software analysis. Unfortunately it became obvious very

quickly that the recovery of membrane proteins was hampered by the overwhelming amount

of intracellular proteins with both approaches (Appendix 2). On searching the proteomic

literature a number of enrichment protocols have been reported, each seemingly with

advantages and disadvantages. Wolff et al (2008) established that 1D-SDS-PAGE and

membrane shaving were the most complementary techniques for the isolation of membrane

proteins of the Gram-positive S. aureus. The 1D-SDS and shaving protocols had not been

78

utilised on E. faecalis and required verification before any further proteomic studies were

undertaken on samples that would be difficult and time consuming to collect. This formed

the basis for the experiments in Section 2.3. The fractionation techniques proved to be highly

complementary, but in particular the membrane-shaving protocol improved the resolution of

IMPs, which are notoriously difficult to recover due to their innate hydrophobic nature. Due

to the very low survival of cells at pH 11, and the small number of proteins that can be

recovered from the membrane, only the membrane shaving protocol was used to study the

cell membrane protein profile most likely to be involved in the phenotypic changes and

differences in growth observed at different pH.

Quantative proteomic comparison of two or more samples requires differential labelling so

that the relative peaks/areas can be identified using mass spectrometry. There are a variety

of labelling techniques reported in the literature with ICPL seeming to overcome many of

the limitations of other techniques such as ICAT and iTRAQ. The next most important

decision was whether to label the samples at either the protein or peptide level. Whilst

labelling at the protein level is easier to track the progression of the proteins within the

workflow, a number of protein identifications can be “lost”. As IMP’s are low in number

and difficult to recover the decision was made to opt for labelling at the peptide level to

increase the chances of identification and subsequent quantification.

Accurate quantification of the H/L ratio is dependent on equal loading of labelled samples.

50 mg of crude extract from both the pH 8 and pH 11 samples were re-adjusted after

carbonate enrichment and before proteinase-K and chymotrypsin digests. Prior to ICPL-

labelling the relative peptide concentrations from each sample pH was performed by MALDI

spectroscopy and it was determined that the proportions were close to 1:1 (Appendix 6).

The experimental model using ICPL means that only peptides that have either a heavy or

light isotope attached are included in the comparative analysis between pH 8 and 11. The

ratio of the ion intensities represents the relative abundance of the protein in the original

samples. Approximately 90% of the proteins identified were quantified which is slightly

lower than the >95% reported previously (Fleron et al 2010, Leroy et al 2010) (Appendix

7). There was an equal labelling efficiency between the samples ICPL_0 and ICPL_6

(Appendix 8). Leroy et al (2010) developed an optimised post-digest protocol by increasing

the buffer capacity of the labelling solution, the reactant/substrate ratio and the reaction time

allowed. This suggests that further refinement of the post-digest ICPL-labelling protocol is

79

warranted in future experiments. The recovery and identification of IMPs is hampered by

the hydrophobic nature of these proteins and the relative absence of the lysine and arginine

targets for tryptic cleavage, which are mainly absent in the transmembrane domain and more

common in exposed hydrophilic domains (Fischer et al 2006). Paradela et al (2010) noted

that there is a significant set of proteins that are only identified and quantified when

particular proteases (endoGluC or trypsin) were used. Utilisation of several proteases could

increase the total number of proteins identified, a finding verified by Leroy et al (2010).

Proteinase-K almost exclusively yields peptides from exposed hydrophilic domains in

membrane proteins e.g. loops. Chymotrypsin cleaves at the carboxy terminus of

Phenylalanine-Tyrosine-Tryptophan (FYW) and is effective at cutting the hydrophobic

domains found in trans-membrane proteins. It is possible that a cleavage at both hydrophilic

and hydrophobic amino acids could have facilitated an increase in protein identification.

Fischer and Poetsch (2006) suggest that two different digestions, one with chymotrypsin and

one with trypsin/cyanogen bromide appear attractive if high sequence coverage is desired.

This warrants further investigation in studying the E. faecalis proteome.

The quantification software analysed the ratio of heavy to light labelled samples only,

therefore proteins that were expressed at only pH 8 or pH 11 were not considered.

The results of Section 2.4 related well to the membrane shaving strategy utilised in Section

2.3. A greater number of proteins were identified and predicted to be located in the multi-

transmembrane region (72 versus 58) and multi-transmembrane (lipid modified N-termini)

region (3 versus 1), the same number in the N-terminally membrane anchored region (3) and

LPxTG cell-wall anchor region (1), and slightly less in the lipid anchored region (4 versus

6). There were a greater number of intracellular proteins isolated in Chapter 3 compared to

membrane shaving in Chapter 2 (51 versus 1). This may be due to an association of these

proteins with the cell membrane, which is possible as they were present in both the pH 8 and

pH 11 samples or it may be due to incomplete fractionation of the membrane proteins.

Alternatively, changes in pH can also trigger release of cytosolic proteins to the extracellular

location. Identification of certain cytoplasmic proteins that have been released from the cell

have been used as markers, reflecting a highly coordinated physiological regulation to the

environment (Chávez de Paz et al 2007).

80

As a membrane shaving protocol selects only membrane-associated proteins, the

intracellular proteins identified were not included in the comparative analysis between pH 8

and pH 11.

Of the 82 membrane-associated proteins identified in the ICPL study, 48 were also recovered

in Chapter 2 (1D SDS-PAGE and membrane shaving), 36 of which were isolated with the

membrane shaving protocol. Considering that there are predicted to be 855 membrane-

associated genes in the genome database (Paulsen et al 2003, Zhou et al 2008), there is a

high correlation between the experiments in both chapters and this provides some validation

to the protein identifications in both studies. A further indication of validity can be derived

by the majority of the identified proteins having a positive GRAVY score, which is a

measure of increased hydrophobicity. Integral membrane proteins are predominantly

hydrophobic and the majority of the proteins identified had multiple trans-membrane

domains (TMDs), which once again supports the membrane location of thr proteins

identified.

In Section 2.4, as only ~10% of the predicted membrane proteins were recovered, care must

be taken when interpreting comparisons between the two samples. The additional 90% of

cell membrane proteins could either not be expressed in the growth conditions, or the protein

recovery techniques were incomplete. As a threshold level, only proteins that showed a

labelling ratio (H/L) greater than or less than 1SD of the mean were considered up- or down

regulated. This produced a limited number of proteins which could be considered to play an

important role in the shift to different growth conditions.

The function and possible interactions of these proteins were discussed in Section 2.4.

3.1 Proteins implicated in biofilm formation

Microorganisms grown in biofilms are phenotypically and physiologically different from the

same microorganism grown in liquid culture, and both alkaline and acidic environments can

signal cellular stress responses than can increase survival (Chávez de Paz et al 2007).

Ballering et al (2009) described 68 genetic loci predicted to be involved in biofilm formation

by E. faecalis. Whilst the number that are intracellular or membrane-associated are

unknown, two corresponding membrane proteins were expressed in this study EF0910

(peptide ABC transporter permease) and EF2380 (probable permease), both of which had a

81

lower H/L ratio than the mean, but did not reach the 1SD threshold. Peptide ABC transporter

permeases are membrane transport proteins that facilitate the diffusion of peptides in or out

of the cell by passive transport. Why these proteins would have reduced expression in the

pH 11 samples cannot be determined with this study.

The proteins EF0114 (Glycosyl hydrolase) and EF0669 (Polysaccharide biosynthesis) are

not listed by Ballering et al (2009) as being implicated in biofilm formation, but were up-

regulated in this present study. It is not possible to determine whether these particular

proteins would have a role in biofilm or peptidoglycan production/turnover. However, it

seems conceivable that there are additional, but as yet un-reported, proteins associated with

the transition to the biofilm state.

3.2 Correlation between metabolism and peptidoglycan turnover

STRING is a database of known and predicted protein interactions (http://string-db.org).

Through text-mining, the EF0669 (Polysaccharide biosynthesis family protein) which was

up-regulated at pH 11 is thought to have an interaction with EF0694 (PTS system fructose-

specific family, IIBC component), which was identified in the MaxQuant data (Figure 15).

This interaction provides evidence of the linkage of production of EPS (via Glucose-1-P)

and the glycolytic pathway in glycerol metabolism.

82

Figure 15. Known and predicted associations for EF0669 determined with String. (http://string-db.org/newstring_cgi/show_network_section.pl?identifier=226185.EF0669 version 9.1 leuS (leucyl-tRNA synthetase), murE (UDP-N-acetylmuramoylalanyl-D-glutamate—L-lysine ligase).

3.3 Correlation to bacteriocin resistance

In the transcriptional analysis of E. faecalis mutants which were resistant to the bacteriocin

pediocin PA-1, there was a strong reduction in gene expression of the mannose PEP:PTS

operon (EF0019-EF0022) (Opsata et al 2010). The PTS mannose specific IID EF0022

protein was also down regulated in the current study study at pH 11 samples by more than

1SD. EF0456 (another PTS mannose-specific IID component) protein was up-regulated in

the study by Opsata et al (2010) but down regulated more than 1SD in this study, and

similarly for EF0108 (C4 dicarboxylate transporter). Other proteins that were down-

regulated in this study and presented by Opsata et al (2010) but that did not reach the 1SD

threshold included EF0020 PTS mannose specific IIAB protein, and EF0021 (PTS mannose

specific protein), both of which are likely to interact with EF0022. EF0020 has an

intracellular location and although the membrane shaving protocol is designed to fractionate

membrane associated proteins, it was expressed in and recovered from both the pH 8 and pH

11 samples and is likely to have a strong association to the membrane. EF0021 is located on

the membrane as a multi transmembrane lipid N-terminally anchored. In addition EF0717

83

(PTS system fructose specific II ABC component) was also in common with the current

study and has a multi transmembrane location.

In contrast to the down-regulated proteins reported by Opsata et al (2010), EF 0636 (Na+/H+

antiporter protein) had a trend to being up-regulated (but not as much as to reach the 1SD

threshold). This could be explained by the alkaline pH. Appelbe and Sedgley (2007)

considered the expression of a selective range of genes to increasing pH. They reported that

the Na+/H+ antiporter (napA) was the only membrane protein gene studied and was found to

be unregulated at pH 10 but down- regulated at pH 7 and 11. The authors suggested that

once the internal pH of the cells had stabilised and the cells adapted, the increased expression

of napA may have no longer been necessary.

Glycosyl hydrolase family 20 (EF0114) and Glycosyl uptake facilitator (EF1927) were up-

regulated (greater than 1 SD) membrane associated proteins also found in the study by

Opsata et al (2010). Others that did not reach the 1SD threshold included EF3108 (peptide

ABC transporter) and EF0958 (PTS system IIABC component), EF0077 (an uncharacterised

protein) and EF1344 (Sugar ABC transporter). The following proteins were up-regulated in

Opsata et al (2010) but with a trend to being down regulated in the current study (but that

did not reach the 1SD threshold): EF0097 (Regulatory protein), EF1529 (PTS sys II C

component), EF1802 (PTS sys IID), EF1901 (Divalent metal cation transport), EF2213 (PTS

sys II BC component), EF3327 (citrate transporter) and EFA0067 (PTS system II ABC).

Collectively there is a strong relationship between this study and that of Opsata et al (2010).

Many proteins that were up-regulated in Opsata et al (2010) seem to show a greater

consistency, with an overall PEP:PTS controlled mechanism to induce glycerol metabolism.

This could be likely as glycerol would be a component of the EPS and the up-regulation of

glycosyl hydrolase would release this as an alternative energy source to substrates taken up

by the PEP:PTS.

3.4 Membrane proteins associated with stress response

Paulsen et al (2003), from their genomic study, predicted 50 proteins to play a role in the

organism’s stress response. In the present study four were identified, with none of them

being regulated by the imposed threshold of 1SD of the mean. Three had a reduced H/L

ratio: EF3257 (oxidoreductase, pyridine nucleotide-disulfide family), EF2623 (cadmium-

84

translocating P-type ATPase), and EF1938 (cation-transporting ATPase) and one had a

greater H/L ratio EF1494 (Na+/H+ antiporter).

3.5 Future Studies

Following the preliminary results of this thesis, future studies should be directed at

investigating the role in survival of the differentially expressed membrane proteins. In

particular - EF0114 (putative glycosyl hydrolase) and EF1927 (glycerol uptake facilitator

protein) appear to be implicated in biofilm turnover and nutrient acquisition.

3.5.1 Construct and characterise individual markerless deletion mutants of EF0114 and EF1927 and a double-knockout mutant

To address the cellular and molecular role of EF0114 and EF1927 in the survival of E.

faecalis, the creation of non-polar deletions in EF0114 and EF1927 in E. faecalis V583 by

allelic exchange mutagenesis as previously described (Gebhard et al., 2014) could be

considered. Putative EF0114 mutants, EF1927 mutants and the double-knockout

EF0114/EF1927 mutants could be confirmed by PCR and Southern hybridisation analysis

(Gebhard et al., 2014). It is hypothesised that the mutants will be less likely to form a biofilm

compared to wild-type strains and would therefore be more vulnerable to pH stress and

nutrient-depleted environments. The ability of the mutant to produce a biofilm at high

growth pH could also be tested using biofilm assays as previously described (Toledo-Arana

et al 2001, Hancock & Perego 2004, Wilson et al 2015).

3.5.2 Determine regulation of EF0114 and EF1927 gene expression

To study further the EF0114 and EF1927 expression in response to extreme alkaline pH,

confirmation of the proposed EF0114 and EF1927 gene organisation using RT-PCR with

primers that anneal to EF0114 or EF1927 and genes flanking them as previously described

(Gauntlett et al., 2008, Shaaly et al., 2013) could be investigated. RNA could be isolated

from batch grown cultures in pH11 and pH7conditions and the transcriptional start site of

EF0114 and EF1927 mapped by 5’RACE (rapid amplification of cDNA ends) as previously

described (Robson et al., 2009, Shaaly et al., 2013). Transcriptional fusions using promoter

EF0114 and EF1927 fusions to lacZ coud be constructed and measured (β-galactosidase

activity) as previously described (Gebhard et al., 2014). A study of the changes in EF0114

and EF1927 promoter activity under a variety of environmental conditions and challenges

85

to different compounds (e.g., pH, nutrient deprivation,) would be useful to determine

precisely what signals lead to activation (or repression) of EF0114 and EF1927 gene

expression. These studies would complement the characterisation studies with the ΔEF0114,

ΔEF1927 and ΔEF0114/EF1927 mutant strains, and point to the cellular and molecular roles

of these genes.

86

Chapter 4. Overall Conclusion

It has been previously established that E. faecalis is commonly recovered from root canals

with persistent infection and that whilst the survival of E. faecalis when exposed to high pH

is reduced markedly, a small population has the ability to persist. The main survival strategy

has been principally attributed to the effective use of proteins associated with proton pumps.

As membrane proteins play an important role in the survival mechanisms of bacteria, the

aim of this thesis was to investigate the change in expression of cell membrane proteins

when E. faecalis is grown at a biologically relevant growth rate and at an extreme alkaline

pH. With the use of continuous culture, optimisation of a membrane shaving protocol and

the use of ICPL labelling, this thesis has demonstrated that additional membrane proteins

play a role in a survival strategy, with a limited number identified as being up- or down-

regulated.

Following an extensive search of the literature, it became apparent that a subset of the

membrane proteins identified have roles in peptidoglycan/biofilm turnover and a shift from

glucose to glycerol metabolism. A similar metabolic shift has been reported in mutants that

are resistance to bacteriocins and lead to the conclusion that one of the responses to an

extreme alkaline is part of a generalised stress response mediated by the down-regulation in

the PEP:PTS system, whilst another is the shift to biofilm formation with the production of

extracellular polysaccharides. It is proposed that the EPS and cellular aggregation had the

additional benefit of increasing the cellular membrane electrochemical gradient in extremely

alkaline conditions. Bacteriocins are known to target the IIC and IID receptors of the Man-

PEP:PTS, but what remains unclear is the signal pathways that cause the down-regulation

of the PEP:PTS system in extreme pH. Potentially it is more energetically efficient for the

cells to utilise glycerol if available. To our knowledge this is the first study to report the cell

membrane response of E. faecalis V583 grown at a biologically relevant growth rate to a

high alkaline environment. Collectively these findings can help explain some additional

adaptational responses to those already determined such as the up-regulation of ATPase and

proton pumps. The fact that a small population of E. faecalis is able to survive an extreme

alkaline environment should not be used as a reason to abolish the use of calcium hydroxide

as an inter-appointment medicament, rather additional antimicrobial strategies should be

developed and employed to aid in the ultimate goal of elimination of microorganisms from

the root canal system. Following the findings within this thesis, the use of molecular and

microbiological platforms can now be used to develop inhibitors to those membrane proteins

87

that are implicated in biofilm formation. Targeting membrane proteins is an attractive

alternative to antibiotic use and has the potential for new drug development for use in

endodontics and beyond.

88

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Appendix 1

Maximum growth curve of E. faecalis in THB media adjusted to pH 11.

Td = ln2/D, where Td is the doubling time and D the Dilution rate.

D= 0.69/7.7

= 0.09 h-1 (μmax)

If the dilution rate is set to 0.1 μrel, then the flow (F) required to achieve this relative growth

rate in a chemostat chamber of 365mL volume is calculated by:

D = F/vol

μmax D = 0.09 h-1

0.1μrel D =0.009 h-1

F = 0.009 x 365

= 3.3 mL/hr -1

y=0.0397x‐ 0.6646R²=0.9819

‐0.7

‐0.6

‐0.5

‐0.4

‐0.3

‐0.2

‐0.1

00 5 10 15

LogOD560

time(hrs)

pH11OD560

Series1

Linear(Series1)

Linear(Series1)

97

Appendix 2

Identification of E.faecalis membrane proteins from the most highly resolved 1D-SDS-

PAGE gel bands and LC-ESI mass spectrometry.

L-lactate dehydrogenase 1 OS=Enterococcus faecalis GN=ldh1 PE=3 SV=1 - [LDH1_ENTFA]

Elongation factor Tu OS=Enterococcus faecalis GN=tuf PE=3 SV=1 - [EFTU_ENTFA]

Seryl-tRNA synthetase 1 OS=Enterococcus faecalis GN=serS1 PE=3 SV=1 - [SYS1_ENTFA]

UDP-N-acetylglucosamine 1-carboxyvinyltransferase 1 OS=Staphylococcus saprophyticus subsp.

saprophyticus (strain ATCC 15305 / DSM 20229) GN=murA1 PE=3 SV=1 - [MURA1_STAS1]

The proteins identified were all predicted to have a cytoplasmic localisation.

Identification of E.faecalis membrane proteins using in-solution digestion and LC-ESI

mass spectrometry.

ORB120817-01 12-072-3 SH (batch grown E. faecalis V583)

Description

Elongation factor Tu OS=Enterococcus faecalis GN=tuf PE=3 SV=1 - [EFTU_ENTFA]

L-lactate dehydrogenase 1 OS=Enterococcus faecalis GN=ldh1 PE=3 SV=1 - [LDH1_ENTFA]

Cell division protein ftsZ OS=Enterococcus faecalis GN=ftsZ PE=3 SV=2 - [FTSZ_ENTFA]

30S ribosomal protein S3 OS=Enterococcus faecalis GN=rpsC PE=3 SV=1 - [RS3_ENTFA]

Arginine deiminase OS=Enterococcus faecalis GN=arcA PE=3 SV=1 - [ARCA_ENTFA]

50S ribosomal protein L19 OS=Enterococcus faecalis GN=rplS PE=3 SV=1 - [RL19_ENTFA]

30S ribosomal protein S5 OS=Enterococcus faecalis GN=rpsE PE=3 SV=1 - [RS5_ENTFA]

50S ribosomal protein L14 OS=Enterococcus faecalis GN=rplN PE=3 SV=1 - [RL14_ENTFA]

30S ribosomal protein S13 OS=Enterococcus faecalis GN=rpsM PE=3 SV=1 - [RS13_ENTFA]

30S ribosomal protein S4 OS=Enterococcus faecalis GN=rpsD PE=3 SV=1 - [RS4_ENTFA]

Uridylate kinase OS=Enterococcus faecalis GN=pyrH PE=1 SV=1 - [PYRH_ENTFA]

50S ribosomal protein L5 OS=Enterococcus faecalis GN=rplE PE=3 SV=1 - [RL5_ENTFA]

98

Elongation factor Tu OS=Ureaplasma parvum serovar 3 (strain ATCC 27815 / 27 / NCTC 11736)

GN=tuf PE=3 SV=1 - [EFTU_UREP2]

6-phosphofructokinase OS=Enterococcus faecalis GN=pfkA PE=3 SV=1 - [K6PF_ENTFA]

Cell division protein ftsA OS=Enterococcus faecalis GN=ftsA PE=3 SV=2 - [FTSA_ENTFA]

60 kDa chaperonin OS=Enterococcus faecalis GN=groL PE=3 SV=2 - [CH60_ENTFA]

50S ribosomal protein L6 OS=Enterococcus faecalis GN=rplF PE=3 SV=1 - [RL6_ENTFA]

50S ribosomal protein L4 OS=Enterococcus faecalis GN=rplD PE=3 SV=1 - [RL4_ENTFA]

30S ribosomal protein S2 OS=Enterococcus faecalis GN=rpsB PE=3 SV=1 - [RS2_ENTFA]

50S ribosomal protein L2 OS=Enterococcus faecalis GN=rplB PE=3 SV=1 - [RL2_ENTFA]

50S ribosomal protein L3 OS=Enterococcus faecalis GN=rplC PE=3 SV=1 - [RL3_ENTFA]

50S ribosomal protein L22 OS=Enterococcus faecalis GN=rplV PE=3 SV=1 - [RL22_ENTFA]

30S ribosomal protein S12 OS=Enterococcus faecalis GN=rpsL PE=3 SV=1 - [RS12_ENTFA]

DNA-directed RNA polymerase subunit beta' OS=Enterococcus faecalis GN=rpoC PE=3 SV=1 -

[RPOC_ENTFA]

Enolase OS=Enterococcus faecalis GN=eno PE=1 SV=1 - [ENO_ENTFA]

30S ribosomal protein S9 OS=Enterococcus faecalis GN=rpsI PE=3 SV=1 - [RS9_ENTFA]

30S ribosomal protein S10 OS=Enterococcus faecalis GN=rpsJ PE=3 SV=1 - [RS10_ENTFA]

50S ribosomal protein L21 OS=Enterococcus faecalis GN=rplU PE=3 SV=1 - [RL21_ENTFA]

Elongation factor G OS=Enterococcus faecalis GN=fusA PE=3 SV=1 - [EFG_ENTFA]

Trigger factor OS=Enterococcus faecalis GN=tig PE=3 SV=1 - [TIG_ENTFA]

30S ribosomal protein S11 OS=Enterococcus faecalis GN=rpsK PE=3 SV=1 - [RS11_ENTFA]

Septation ring formation regulator EzrA OS=Enterococcus faecalis GN=ezrA PE=3 SV=1 -

[EZRA_ENTFA]

50S ribosomal protein L1 OS=Enterococcus faecalis GN=rplA PE=3 SV=1 - [RL1_ENTFA]

50S ribosomal protein L17 OS=Enterococcus faecalis GN=rplQ PE=3 SV=1 - [RL17_ENTFA]

Glyceraldehyde-3-phosphate dehydrogenase OS=Streptococcus pyogenes GN=gap PE=1 SV=2 -

[G3P_STRPY]

ATP-dependent Clp protease ATP-binding subunit ClpE OS=Lactococcus lactis subsp. lactis GN=clpE

PE=2 SV=1 - [CLPE_LACLA]

DNA-directed RNA polymerase subunit alpha OS=Enterococcus faecalis GN=rpoA PE=3 SV=1 -

[RPOA_ENTFA]

99

Serine hydroxymethyltransferase OS=Enterococcus faecalis GN=glyA PE=3 SV=1 - [GLYA_ENTFA]

DNA-directed RNA polymerase subunit beta OS=Enterococcus faecalis GN=rpoB PE=3 SV=1 -

[RPOB_ENTFA]

50S ribosomal protein L18 OS=Enterococcus faecalis GN=rplR PE=3 SV=1 - [RL18_ENTFA]

Phosphate import ATP-binding protein PstB 2 OS=Enterococcus faecalis GN=pstB2 PE=3 SV=1 -

[PSTB2_ENTFA]

ATP synthase subunit beta OS=Enterococcus faecalis GN=atpD PE=3 SV=1 - [ATPB_ENTFA]

GTPase Der OS=Enterococcus faecalis GN=der PE=3 SV=1 - [DER_ENTFA]

Ribonuclease Y OS=Enterococcus faecalis GN=rny PE=3 SV=1 - [RNY_ENTFA]

Foldase protein prsA OS=Enterococcus faecalis GN=prsA PE=3 SV=1 - [PRSA_ENTFA]

Chaperone protein DnaK OS=Enterococcus faecalis GN=dnaK PE=2 SV=1 - [DNAK_ENTFA]

Protein RecA OS=Enterococcus faecalis GN=recA PE=3 SV=2 - [RECA_ENTFA]

Translation initiation factor IF-2 OS=Enterococcus faecalis GN=infB PE=3 SV=1 - [IF2_ENTFA]

V-type sodium ATPase subunit K OS=Enterococcus hirae GN=ntpK PE=1 SV=1 - [NTPK_ENTHR]

rRNA adenine N-6-methyltransferase OS=Clostridium perfringens GN=ermBP PE=3 SV=1 -

[ERM1_CLOPE]

ATP-dependent Clp protease proteolytic subunit OS=Enterococcus faecalis GN=clpP PE=3 SV=1 -

[CLPP_ENTFA]

Ribosome-associated factor Y OS=Streptococcus pyogenes serotype M6 GN=M6_Spy1371 PE=1 SV=1

- [RAFY_STRP6]

Ornithine carbamoyltransferase, catabolic OS=Enterococcus faecalis GN=arcB PE=3 SV=1 -

[OTCC_ENTFA]

30S ribosomal protein S19 OS=Enterococcus faecalis GN=rpsS PE=3 SV=1 - [RS19_ENTFA]

50S ribosomal protein L10 OS=Enterococcus faecalis GN=rplJ PE=3 SV=1 - [RL10_ENTFA]

50S ribosomal protein L33 3 OS=Enterococcus faecalis GN=rpmG3 PE=3 SV=1 - [RL333_ENTFA]

30S ribosomal protein S6 OS=Enterococcus faecalis GN=rpsF PE=3 SV=1 - [RS6_ENTFA]

Probable RNA methyltransferase Daro_1157 OS=Dechloromonas aromatica (strain RCB)

GN=Daro_1157 PE=3 SV=1 - [Y1157_DECAR]

Probable GTP-binding protein EngB OS=Enterococcus faecalis GN=engB PE=3 SV=1 -

[ENGB_ENTFA]

100

Ribosome maturation factor rimP OS=Clostridium beijerinckii (strain ATCC 51743 / NCIMB 8052)

GN=rimP PE=3 SV=1 - [RIMP_CLOB8]

30S ribosomal protein S17 OS=Enterococcus faecalis GN=rpsQ PE=3 SV=1 - [RS17_ENTFA]

Glycine dehydrogenase [decarboxylating] OS=Bradyrhizobium japonicum GN=gcvP PE=3 SV=1 -

[GCSP_BRAJA]

V-type ATP synthase alpha chain OS=Enterococcus faecalis GN=atpA PE=3 SV=2 - [VATA_ENTFA]

30S ribosomal protein S18 OS=Enterococcus faecalis GN=rpsR PE=3 SV=1 - [RS18_ENTFA]

DNA primase OS=Neisseria meningitidis serogroup A GN=dnaG PE=3 SV=1 - [PRIM_NEIMA]

101

Appendix 3

E.faecalis membrane-associated proteins identified following membrane shaving or

1D-SDS-PAGE and LC-ESI mass spectrometry.

Protein in 1D gel bands common to the membrane shaving protocol are highlighted in bold:

(M) Proteins identified by Maddalo et al (2011)

(B) Proteins identified by Bøhle et al (2011)

(Bio) Proteins reported to be involved in biofilm formation (Ballering et al 2009)

(S) Proteins reported to be involved in stress as reported by (P) Paulsen et al (2003)

(V) Proteins reported to be involved in virulence as reported by (P) Paulsen et al (2003) and

(R) Reffuveille et al (2011).

102

103

104

105

106

Appendix 4

Identification and quantification of proteins identified from samples following

membrane shaving, ICPL labelling (pH 11 -Heavy and pH 8 -Light), LC-ESI mass

spectrometry and MaxQuant analysis.

Fasta headers Ratio H/L

Log2

>P00766 SWISS-PROT:P00766 Chymotrypsinogen A - Bos taurus (Bovine). 1.0142 0.0203

>P02672 SWISS-PROT:P02672 (Bos taurus) Fibrinogen alpha chain precursor

NaN

>P20930 SWISS-PROT:P20930 Tax_Id=9606 Gene_Symbol=FLG Filaggrin NaN

>Q0VBK2 TREMBL:Q0VBK2;Q8C1M7 Tax_Id=10090 Gene_Symbol=Krt80 Keratin 80

4.5524

>Q3ZBD7 SWISS-PROT:Q3ZBD7 (Bos taurus) Glucose-6-phosphate isomerase

NaN

>tr|H7C705|H7C705_ENTFA Membrane protein, putative OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0516 PE=4 SV=1

EF0516 @Multi-transmembrane

0.072697

-3.7819

>sp|P0DM31|ENO_ENTFA Enolase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=eno PE=3 SV=1

EF1961 Intracellular 0.39653

-1.3344

>tr|Q82YN1|Q82YN1_ENTFA Aggregation substance PrgB OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=prgB PE=4 SV=1;>tr|Q839L6|Q839L6_ENTFA Aggregation substance PrgB OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0149 PE=4 SV=1;>sp|P1795

EF_B0011 @LPxTG Cell-wall anchored

0.033415

-4.9033

>sp|P23530|PT1_ENTFA Phosphoenolpyruvate-protein phosphotransferase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=ptsI PE=1 SV=2

EF0710 Intracellular 0.32079

-1.6402

>sp|P37062|NAPE_ENTFA NADH peroxidase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=npr PE=1 SV=2

EF1211 Intracellular 0.67521

-0.5665

>sp|Q47758|DDL_ENTFA D-alanine--D-alanine ligase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=ddl PE=3 SV=2

EF0843 Intracellular 0.19876

-2.3309

>tr|Q820V7|Q820V7_ENTFA Crp/FNR family transcriptional regulator OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0107 PE=4 SV=1

EF0107 Intracellular 0.072235

-3.7911

>tr|Q82YR5|Q82YR5_ENTFA PTS system, IIABC components OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_A0067 PE=4 SV=1

EFA0067 @Multi-transmembrane

0.058294

-4.1005

>tr|Q82YU8|Q82YU8_ENTFA Pheromone shutdown protein TraB OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=traB-1 PE=4 SV=1

EFA0002 multi-transmembrane

0.079048

-3.6611

>sp|Q82YV1|YIDC_ENTFA Membrane protein insertase YidC OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=yidC PE=3 SV=1

EF3331 multi-trans Lipid modified N-termini

0.075636

-3.7247

>tr|Q82YV5|Q82YV5_ENTFA Citrate transporter OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3327 PE=4 SV=1

EF3327 multi-transmembrane

0.16191

-2.6267

>tr|Q82YY6|Q82YY6_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3295 PE=4 SV=1

EF3295 multi-transmembrane

0.16144

-2.6309

>tr|Q82YZ7|Q82YZ7_ENTFA ATP-dependent Clp protease, ATP-binding subunit ClpC OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=clpC PE=3 SV=1

EF3282 Intracellular 0.016 -5.9657

>tr|Q82Z22|Q82Z22_ENTFA Oxidoreductase, pyridine nucleotide-disulfide family OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3257 PE=4 SV=1

EF3257 multi-transmembrane

0.08396

-3.5741

>sp|Q82Z41|RPOC_ENTFA DNA-directed RNA polymerase subunit beta OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=rpoC PE=3 SV=1

EF3237 Intracellular 0.21037

-2.2489

>tr|Q82Z45|Q82Z45_ENTFA Dps family protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3233 PE=3 SV=1

EF3233 Intracellular 0.20564

-2.2818

>tr|Q82Z82|Q82Z82_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3188 PE=4 SV=1

EF3188 Intracellular NaN

>sp|Q82ZA2|MUTS_ENTFA DNA mismatch repair protein MutS OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=mutS PE=3 SV=1

EF3167 Intracellular 17.147 4.0998

>tr|Q82ZB8|Q82ZB8_ENTFA CDP-diacylglycerol--glycerol-3-phosphate 3-phosphatidyltransferase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=pgsA PE=3 SV=1

EF3148 multi-transmembrane

0.11136

-3.1666

107

>tr|Q82ZE6|Q82ZE6_ENTFA DAK2 domain protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3114 PE=4 SV=1

EF3114 Intracellular 0.77226

-0.3728

>tr|Q82ZF2|Q82ZF2_ENTFA Peptide ABC transporter permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3108 PE=3 SV=1

EF3108 multi-transmembrane

0.2601 -1.9428

>tr|Q82ZH8|Q82ZH8_ENTFA Acetyltransferase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3079 PE=4 SV=1

EF3079 Intracellular NaN

>sp|Q82ZJ1|RS15_ENTFA 30S ribosomal protein S15 OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=rpsO PE=3 SV=1

EF3065 Intracellular 0.73759

-0.4391

>tr|Q82ZN9|Q82ZN9_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3011 PE=1 SV=1

EF3011 Intracellular 0.733 -0.4481

>tr|Q82ZV7|Q82ZV7_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2940 PE=4 SV=1

EF2940 Intracellular 21.192 4.4054

>tr|Q82ZV9|Q82ZV9_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2938 PE=4 SV=1

EF2938 multi-transmembrane

0.68974

-0.5358

>tr|Q830J2|Q830J2_ENTFA Small hydrophobic molecule transporter OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2790 PE=4 SV=1

EF2790 multi-transmembrane

0.16187

-2.6270

>tr|Q830S5|Q830S5_ENTFA Conserved domain protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2697 PE=4 SV=1

EF2697 multi-transmembrane

0.2021 -2.3068

>tr|Q830W1|Q830W1_ENTFA Membrane protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2657 PE=4 SV=1

EF2657 multi-transmembrane

0.12742

-2.9723

>tr|Q830X1|Q830X1_ENTFA GntP family permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2647 PE=4 SV=1

EF2647 multi-transmembrane

0.48367

-1.0479

>tr|Q830Z1|Q830Z1_ENTFA Cadmium-translocating P-type ATPase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=cadA PE=3 SV=1

EF2623 multi-transmembrane

0.1157 -3.1115

>sp|Q831A3|ATPA_ENTFA ATP synthase subunit alpha OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=atpA PE=3 SV=1

EF2610 Intracellular 19.412 4.2788

>tr|Q831G3|Q831G3_ENTFA Phage integrase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2546 PE=4 SV=1

EF2546 Intracellular NaN

>tr|Q831R5|Q831R5_ENTFA PTS system IIBC component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2435 PE=4 SV=1

EF2435 multi-transmembrane

0.069858

-3.8394

>tr|Q831T6|Q831T6_ENTFA HD domain protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2413 PE=4 SV=1

EF2413 multi-transmembrane

0.10615

-3.2358

>sp|Q831U3|SYGB_ENTFA Glycine--tRNA ligase beta subunit OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=glyS PE=3 SV=1

EF2406 Intracellular 0.35237

-1.5048

>sp|Q831U9|RS2_ENTFA 30S ribosomal protein S2 OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=rpsB PE=3 SV=1

EF2398 Intracellular 0.56002

-0.8364

>tr|Q831W9|Q831W9_ENTFA Amino acid permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2377 PE=4 SV=1

EF2377 multi-transmembrane

0.084883

-3.5583

>tr|Q832G0|Q832G0_ENTFA PTS system IID component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2269 PE=4 SV=1

EF2269 multi-transmembrane

NaN

>tr|Q832L3|Q832L3_ENTFA PTS system, IIBC components OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2213 PE=4 SV=1

EF2213 multi-transmembrane

0.084387

-3.5668

>tr|Q832L7|Q832L7_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2209 PE=4 SV=1

EF2209 secretory(released with CS)

0.50157

-0.9954

>tr|Q832P2|Q832P2_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2179 PE=4 SV=1

EF2179 multi-transmembrane

0.45117

-1.1482

>sp|Q832R4|Y2154_ENTFA UPF0397 protein EF_2154 OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2154 PE=3 SV=1

EF2154 multi-transmembrane

0.060692

-4.0423

>tr|Q832X2|Q832X2_ENTFA Phage tail protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2096 PE=4 SV=1

EF2096 multi-transmembrane

16.003 4.0002

>tr|Q832Z3|Q832Z3_ENTFA ABC transporter, permease protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2075 PE=3 SV=1

EF2075 multi-transmembrane

0.18702

-2.4187355

>tr|Q832Z4|Q832Z4_ENTFA ABC transporter ATP-binding protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2074 PE=3 SV=1

EF2074 Intracellular 0.21429

-2.2223

>tr|Q833A6|Q833A6_ENTFA Cytochrome d ubiquinol oxidase, subunit I OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=cydA PE=4 SV=1

EF2061 multi-transmembrane

0.13989

-2.8376

>tr|Q833A7|Q833A7_ENTFA Cytochrome d ubiquinol oxidase, subunit II OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=cydB PE=4 SV=1

EF2060 multi-transmembrane

0.19673

-2.3457

>tr|Q833A9|Q833A9_ENTFA Transport ATP-binding protein CydD, putative OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2058 PE=4 SV=1

EF2058 multi-transmembrane

0.098574

-3.3426

>sp|Q833I2|SYD_ENTFA Aspartate--tRNA ligase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=aspS PE=3 SV=1

EF1970 Intracellular 4.0235 2.0084

>sp|Q833J0|TPIS_ENTFA Triosephosphate isomerase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=tpiA PE=3 SV=1

EF1962 Intracellular NaN

108

>tr|Q833K9|Q833K9_ENTFA Cation-transporting ATPase, E1-E2 family OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1938 PE=3 SV=1

EF1938 multi-transmembrane

0.10043

-3.3157

>tr|Q833L8|Q833L8_ENTFA Glycerol uptake facilitator protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=glpF PE=3 SV=1

EF1927 multi-transmembrane

0.71856

-0.4768

>tr|Q833P3|Q833P3_ENTFA Divalent metal cation transporter MntH OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=mntH PE=3 SV=1

EF1901 multi-transmembrane

0.1167 -3.0991

>sp|RL19_ENTFA 50S ribosomal protein L19 OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=rplS PE=3 SV=1

EF1898 Intracellular 0.1541 -2.6980

>tr|Q833U0|Q833U0_ENTFA PTS system IIC component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1838 PE=4 SV=1

EF1838 multi-transmembrane

0.037888

-4.7221

>tr|Q833W5|Q833W5_ENTFA General stress protein A OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=gspA-1 PE=4 SV=1

EF1810 Intracellular NaN

>tr|Q833X3|Q833X3_ENTFA PTS system IID component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1802 PE=4 SV=1

EF1802 multi-transmembrane

0.068453

-3.8687

>tr|Q833X5|Q833X5_ENTFA Ig-like domain (Group 4) family protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1800 PE=4 SV=1

EF1800 secretory(released with CS)

0.9608 -0.0576

>sp|Q834A7|SECA_ENTFA Protein translocase subunit SecA OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=secA PE=3 SV=1

EF1763 Intracellular 1.0793 0.1100

>tr|Q834B2|Q834B2_ENTFA Phosphate ABC transporter, permease PstA OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1757 PE=3 SV=1

EF1757 multi-transmembrane

0.12781

-2.9679

>sp|Q834C0|LGT_ENTFA Prolipoprotein diacylglyceryl transferase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=lgt PE=3 SV=1

EF1748 multi-transmembrane

0.078991

-3.6621

>tr|Q834D9|Q834D9_ENTFA Uracil permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1720 PE=4 SV=1

EF1720 multi-transmembrane

0.14546

-2.7813

>tr|Q834J3|Q834J3_ENTFA Membrane protein, putative OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1657 PE=4 SV=1

EF1657 multi-transmembrane

0.46832

-1.0944

>tr|Q834N0|Q834N0_ENTFA DNA topoisomerase 4 subunit A OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=parC PE=3 SV=1

EF1614 Intracellular 0.16268

-2.6198

>tr|Q834N1|Q834N1_ENTFA Formate acetyltransferase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=pflB PE=3 SV=1

EF1613 Intracellular 0.21435

-2.2219

>tr|Q834N6|Q834N6_ENTFA Cardiolipin synthase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1608 PE=3 SV=1

EF1608 multi-transmembrane

0.40662

-1.2982

>tr|Q834Q6|Q834Q6_ENTFA Cysteine synthase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=cysK PE=3 SV=1

EF1584 Intracellular NaN

>tr|Q834S3|Q834S3_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1560 PE=4 SV=1

EF1560 Intracellular 0.21932

-2.1888

>tr|Q834T7|Q834T7_ENTFA LysM domain protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1546 PE=4 SV=1

EF1546 N-Terminally anchored(No CS)

0.066148

-3.9181

>tr|Q834U2|Q834U2_ENTFA Membrane protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1541 PE=4 SV=1

EF1541 multi-transmembrane

1.3641 0.4479

>tr|Q834V2|Q834V2_ENTFA PTS system, IIC component, putative OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1529 PE=4 SV=1

EF1529 multi-transmembrane

0.12373

-3.0147

>tr|Q834Y3|Q834Y3_ENTFA V-type ATPase, subunit K OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1494 PE=3 SV=1

EF1494 multi-transmembrane

0.11227

-3.1549

>sp|Q835G1|G6PI_ENTFA Glucose-6-phosphate isomerase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=pgi PE=3 SV=1

EF1416 Intracellular 0.24676

-2.0188

>tr|Q835G2|Q835G2_ENTFA Glutamate dehydrogenase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=gdhA PE=3 SV=1

EF1415 Intracellular 0.22441

-2.1557

>tr|Q835H4|Q835H4_ENTFA Colicin V production family protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1403 PE=4 SV=1

EF1403 multi-transmembrane

0.21887

-2.1918

>tr|Q835K1|Q835K1_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1376 PE=4 SV=1

EF1376 multi-transmembrane

0.24866

-2.0077

>tr|Q835K7|Q835K7_ENTFA Drug resistance MFS transporter OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1370 PE=4 SV=1

EF1370 multi-transmembrane

0.071447

-3.8069

>tr|Q835M4|Q835M4_ENTFA Pyruvate dehydrogenase (Acetyl-transferring) E1 component, alpha subunit OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=pdhA PE=4 SV=1

EF1353 Intracellular 0.38256

-1.3862

>tr|Q835N2|Q835N2_ENTFA Sugar ABC transporter sugar-binding protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1345 PE=4 SV=1

EF1345 Lipid anchored NaN

>tr|Q835N3|Q835N3_ENTFA Sugar ABC transporter permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1344 PE=3 SV=1

EF1344 multi-transmembrane

0.17773

-2.4922

>sp|Q835R7|DNAK_ENTFA Chaperone protein DnaK OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=dnaK PE=3 SV=1

EF1308 Intracellular 0.36296

-1.4621

109

>tr|Q835Y0|Q835Y0_ENTFA Glycosyl hydrolase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1238 PE=4 SV=1

EF1238 Intracellular 0.88887

-0.1699

>tr|Q836A9|Q836A9_ENTFA CCS family citrate carrier protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1207 PE=4 SV=1

EF1207 multi-transmembrane

0.053083

-4.2356

>tr|Q836B0|Q836B0_ENTFA Malate dehydrogenase, decarboxylating OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1206 PE=3 SV=1

EF1206 Intracellular 0.10005

-3.3212

>tr|Q836E7|Q836E7_ENTFA Fructose-bisphosphate aldolase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=fba PE=4 SV=1

EF1167 Intracellular 1.6982 0.7640

>tr|Q836E8|Q836E8_ENTFA YitT family protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1166 PE=4 SV=1

EF1166 multi-transmembrane

0.072398

-3.7879

>tr|Q836Q1|Q836Q1_ENTFA Mn2+/Fe2+ transporter OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1057 PE=4 SV=1

EF1057 multi-transmembrane

0.2247 -2.1539

>tr|Q836R2|Q836R2_ENTFA Pyruvate kinase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=pyk PE=3 SV=1

EF1046 Intracellular 0.32995

-1.5996

>tr|Q836U9|Q836U9_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1006 PE=4 SV=1

EF1006 N-Terminally anchored(No CS)

0.19972

-2.3239

>tr|Q836V5|Q836V5_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0998 PE=3 SV=1

EF0998 Intracellular 0.57795

-0.7909

>tr|Q836Y6|Q836Y6_ENTFA PTS system, IIABC components OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0958 PE=4 SV=1

EF0958 multi-transmembrane

0.32656

-1.6145

>tr|Q837A3|Q837A3_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0940 PE=4 SV=1

EF0940 multi-transmembrane

0.10793

-3.2118

>tr|Q837D3|Q837D3_ENTFA Peptide ABC transporter permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0910 PE=3 SV=1

EF0910 multi-transmembrane

0.088689

-3.4951

>tr|Q837D4|Q837D4_ENTFA Peptide ABC transporter permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0909 PE=3 SV=1

EF0909 multi-transmembrane

0.090092

-3.4724

>tr|Q837D6|Q837D6_ENTFA Peptide ABC transporter peptide-binding protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0907 PE=1 SV=1

EF0907 Lipid anchored 0.15352

-2.7035

>tr|Q837E3|Q837E3_ENTFA Aldehyde-alcohol dehydrogenase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=adhE PE=4 SV=1

EF0900 Intracellular 0.50738

-0.9788

>sp|Q837G9|KUP_ENTFA Probable potassium transport system protein kup OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=kup PE=3 SV=1

EF0872 multi-transmembrane

0.13056

-2.9372

>tr|Q837M0|Q837M0_ENTFA PTS system IIC component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0816 PE=4 SV=1

EF0816 multi-transmembrane

NaN

>sp|Q837R0|CLPP_ENTFA ATP-dependent Clp protease proteolytic subunit OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=clpP PE=3 SV=1

EF0771 Intracellular 0.079263

-3.6572

>tr|Q837W1|Q837W1_ENTFA PTS system fructose-specific family, IIABC component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0717 PE=4 SV=1

EF0717 multi-transmembrane

0.067327

-3.8926

>sp|ef0715|TIG_ENTFA Trigger factor OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=tig PE=3 SV=1

EF0715 Intracellular 0.20125

-2.3129

>tr|Q837X7|Q837X7_ENTFA Acetyltransferase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0698 PE=4 SV=1

EF0698 Intracellular NaN

>tr|Q837Y1|Q837Y1_ENTFA PTS system fructose-specific family, IIBC component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0694 PE=4 SV=1

EF0694 multi-transmembrane

0.14066

-2.8297

>tr|Q838A3|Q838A3_ENTFA Polysaccharide biosynthesis family protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0669 PE=4 SV=1

EF0669 multi-transmembrane

5.1847 2.3742

>tr|Q838D4|Q838D4_ENTFA Na+/H+ antiporter OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=nhaC-2 PE=4 SV=1

EF0636 multi-transmembrane

0.43277

-1.2083

>tr|Q838D5|Q838D5_ENTFA Amino acid permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0635 PE=4 SV=1

EF0635 multi-transmembrane

0.21012

-2.2507

>tr|Q838G6|Q838G6_ENTFA Lipoprotein, putative OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0501 PE=4 SV=1

EF0501 Lipid anchored 0.16964

-2.5594

>tr|Q838J1|Q838J1_ENTFA PTS system IID component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0456 PE=4 SV=1

EF0456 multi-transmembrane

0.047351

-4.4004

>tr|Q838K6|Q838K6_ENTFA Di-/tripeptide transporter OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0440 PE=3 SV=1

EF0440 multi-transmembrane

0.15007

-2.7362

>tr|Q838Z0|Q838Z0_ENTFA PTS system, IIC component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0292 PE=4 SV=1

EF0292 multi-transmembrane

0.069477

-3.8473

>tr|Q839B1|Q839B1_ENTFA ATP-dependent zinc metalloprotease FtsH OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=ftsH PE=3 SV=1

EF0265 multi-transmembrane

0.17125

-2.5458

110

>tr|Q839C8|Q839C8_ENTFA Amino acid ABC transporter amino acid-binding/permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0247 PE=4 SV=1

EF0247 multi-transmembrane

0.35538

-1.4925

>tr|Q839D7|Q839D7_ENTFA Membrane protein, putative OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0235 PE=4 SV=1

EF0235 multi-transmembrane

0.26829

-1.8981

>tr|Q839E4|Q839E4_ENTFA Protein translocase subunit SecY OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=SecY PE=3 SV=1

EF0227 multi-transmembrane

0.11158

-3.1638

>sp|Q839F7|RL16_ENTFA 50S ribosomal protein L16 OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=rplP PE=3 SV=1

EF0213 Intracellular 0.14185

-2.8175

>sp|Q839G3|RL4_ENTFA 50S ribosomal protein L4 OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=rplD PE=3 SV=1

EF0207 Intracellular 0.051672

-4.2744

>sp|Q839G8|EFTU_ENTFA Elongation factor Tu OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=tuf PE=3 SV=1

EF0201 Intracellular 0.32755

-1.6102

>sp|Q839G9|EFG_ENTFA Elongation factor G OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=fusA PE=3 SV=1

EF0200 Intracellular 0.37521

-1.4142

>tr|Q839I5|Q839I5_ENTFA ABC transporter permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0180 PE=4 SV=1

EF0180 multi-transmembrane

0.098503

-3.3436

>tr|Q839I6|Q839I6_ENTFA ABC transporter, permease protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0179 PE=4 SV=1

EF0179 multi-transmembrane

NaN

>tr|Q839I8|Q839I8_ENTFA Basic membrane protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0177 PE=4 SV=1

EF0177 Lipid anchored 0.035342

-4.8224

>tr|Q839P8|Q839P8_ENTFA Glycosyl hydrolase, family 20 OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0114 PE=4 SV=1

EF0114 N-Terminally anchored(No CS)

59.515 5.8951

>tr|Q839Q4|Q839Q4_ENTFA C4-dicarboxylate transporter OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0108 PE=4 SV=1

EF0108 multi-transmembrane

0.045102

-4.4706

>sp|Q839Q5|OTCC_ENTFA Ornithine carbamoyltransferase, catabolic OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=arcB PE=3 SV=1

EF0105 Intracellular 0.33526

-1.5766

>tr|Q839R1|Q839R1_ENTFA Regulatory protein PfoR OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0097 PE=4 SV=1

EF0097 multi-trans Lipid modified N-termini

0.11155

-3.1642

>tr|Q839S9|Q839S9_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0077 PE=4 SV=1

EF0077 multi-transmembrane

0.26825

-1.8983

>sp|Q839V7|SYE_ENTFA Glutamate--tRNA ligase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=gltX PE=3 SV=1

EF0043 Intracellular 0.11727

-3.0920

>tr|Q839W8|Q839W8_ENTFA ABC transporter permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0032 PE=4 SV=1

EF0032 multi-transmembrane

0.43277

-1.2083

>tr|Q839X7|Q839X7_ENTFA PTS system mannose-specific IID component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0022 PE=4 SV=1

EF0022 multi-transmembrane

0.03762

-4.7323

>tr|Q839X8|Q839X8_ENTFA PTS system mannose-specific IIC component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0021 PE=4 SV=1

EF0021 multi-trans Lipid modified N-termini

0.11907

-3.0701

>tr|Q839X9|Q839X9_ENTFA PTS system mannose-specific IIAB component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0020 PE=4 SV=1

EF0020 Intracellular 0.035382

-4.8208

>sp|Q839Z5|DNAA_ENTFA Chromosomal replication initiator protein DnaA OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=dnaA PE=3 SV=1

EF0001 Intracellular NaN

>sp|Q93K67|ARCA_ENTFA Arginine deiminase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=arcA PE=3 SV=1

EF0104 Intracellular 0.3216 -1.6366

>sp|Q9RPP2|EEP_ENTFA Probable protease eep OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=eep PE=3 SV=2

EF2380 multi-transmembrane

0.12031

-3.0551

>tr|Q835Y6|Q835Y6_ENTFA ABC transporter permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1232 PE=3 SV=1

EF1232 multi-transmembrane

0.17978

-2.4756

111

Appendix 5

Abundance ratio of ICPL labeled proteins identified from pH 11 (intensity H) and pH

8 (intensity L) samples using MaxQuant and represented with Perseus software.

112

Appendix 6

Determination of relative sample concentrations between pH 8 and pH 11 samples

Prior to ICPL-labelling the relative peptide concentrations from each sample pH was

performed by matrix assisted laser desorption ionisation (MALDI) spectroscopy.

Comparative concentrations of pH 8 and pH 11 samples.

113

Appendix 7

Relative abundance of labeled proteins from the original pH 8 and p H11 samples

Log scale ratio of sum of unlabeled N-termini species to the sum of labeled N-termini

Species.

114

Appendix 8

Log scale ICPL_0 intensity versus ICPL_6 intensity. By plotting ICPL_0 intensity

versus ICPL_6 intensity indicated that there was similar labelling efficiency between

the groups.