improving the quality of protein samples for better data...
TRANSCRIPT
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Dr. André MatagneCentre for Protein Engineering
Protein Factory & Robotein facilitiesUNIVERSITY OF LIEGE
Joint initiative on the quality of recombinant proteins
Improving the quality of protein samples for better data reproducibility
Implementation of a standardized sample quality control workflow
Les Journées Jeunes Chercheurs Transfrontalières URCA, Reims, April 2nd, 3rd, 2019 - Some slides prepared by Bertrand Raynal, Pasteur Institute, Paris
– Some slides prepared by Mario Lebendiker, Hebrew University of Jerusalem
QC teams of ARBRE-MOBIEU and P4EUNick Berrow - Institute for research in Medicine, Barcelona, Spain (P4EU)
Maria Garcia-Alai - EMBL Hamburg, Germany (ARBRE-MOBIEU)
Stefan Knauer - Bayreuth University, Germany (ARBRE-MOBIEU)
Mario Lebendiker - Hebrew University of Jerusalem, Israel (P4EU)
Blanca Lopez-Mendez – University of Copenhagen, Denmark (ARBRE-MOBIEU)
Ario de Marco - University of Nova Gorica, Slovenia (P4EU and ARBRE-MOBIEU)
André Matagne – University of Liège, Belgium (ARBRE-MOBIEU
Annabel Parret - EMBL Hamburg, Germany (P4EU)
Bertrand Raynal - Pasteur Institute, Paris, France (ARBRE-MOBIEU)
Kim Remans - EMBL Heibelberg, Germany (P4EU)
Stephan Uebel - MPI for Biochemistry Munich, Germany (ARBRE-MOBIEU)
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Titel der Präsentation (Editierbar im Folienmaster), Ort, 18.04.2019 (Editierbar im Folienmaster)Sabine Suppmann, Biochemistry Core Facility 9th P4EU meeting, Nov30
Network of ca. 100 members form > 40 protein facilities, mainly but not exclusively in Europe
Started in 2010 (Hüseyin Besir, EMBL)
Share expertise and information
Exchange materials & protocols
New tools & technologies
Establish standards for P related work
Benchmarking and SOPs
Enable collaboration
Access to external facilities
Training of staff/usersfrom Hüseyin Besir, CTLS 2014
(2015)
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and the related COST Action
MOBIEU (Molecular Biophysics in Europe)
Topic: “Integrating Molecular Biophysics Approaches for Biology and
Healthcare” (Grant period 2016-2020)
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A large communityhas already joined
More than 135
resource labs/infrastructures/facilities
from 29 different european countries
working in very different contexts ,
some more "research topic oriented"
and others
more "technology oriented"
Dedicated website http://arbre-mobieu.eu/
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WG2Joint research projects
WG1Communication and
membership
WG3Training and human capacity
development
WG7External synergies
WG6Partnership with instrument
developers and manufacturing companies
WG5Transnational access to
instrumentation and expertise
WG4Optimization of data quality
7 working groups
+ a Short Term Scientific Mission (STSM)
coordination
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Joint initiative on the quality of recombinant proteins
Improving the time-efficiency and quality of your resultsImplementation of a standardized sample quality control workflow (guidelines, best practice recommendations)
CA15126
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• A lot of time is spent on poor quality samples
Improving the quality of the samples is essential to improve the quality (i.e. accuracy, reproducibility) of the results we produce
• The best experiments in the world will turn garbage in expensive garbage
Our analysis of the situation (as core facilities) in different European institutions
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The international position
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Tremendous Economic Impact
Freedman LP, Cockburn IM, Simcoe TS (2015) The Economics of Reproducibility in Preclinical Research. PLoS Biol 13(6): e1002165.(using 2012 data)
(56.4109)
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Improve experimental design/data analysis!
Improve QC and characterization of the‘protein’ samples
Educative and basic question: how much can I trust my protein? What should I know?
Check that we are working with:
the correct protein
that it is pure/homogeneous
have the right fold/activity
Report the results of each control in publications
Encourage more extensive use of supplementary data
Are we wasting 50% of pre-clinical researchbudget? What can we do?
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Did you check your sample? Researcher opinion!
• “I have no time…”
• “SEC? DLS? MS?... My boss thinks it is a waste of time…”
• “It is the way we have prepared samples in the lab for the last ten years…”
• “But some experiments have worked with this sample…”
• “I don’t know how to do it…”
• “I’ll do the experiment anyway, it may work…”
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The reality:Quoting people’s experience with not fully validated samples
• “We expressed a human protein in insect cells. By using SDS-PAGE followed byCoomasie blue staining, we observed a single protein band with a “correct” MM. Wesucceeded to crystallize it, and only then we “discovered” that we worked with adifferent target. It was an ubiquitous insect cell protein.”
• “We expressed a yeast protein. SDS-PAGE showed a single bandwith the expected MM. We performed interaction studies andcould not reproduce our previous data. Followoing an analysis bymass spectrometry, we discovered that we were missing 4 aminoacids at one end that were essential for the interaction.”
• “I have done many unsuccessful tests of crystallization with myprotein. I finally decided to do a simple quality test. I noticed thatthe protein was not homogenous in the buffer I used forpurification. After buffer optimization, I obtained an homogenousprotein that did crystallize.”
• “Many people came to our Facility with the aim to crystallize theirprotein after unsuccessful and costly trials with other groups. After ashort talk, we discover that they never check mass homogeneity(aggregation state) nor charge homogeneity.”
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Our proposal (P4EU/ARBRE MOBIEU consensus)
- Reproducibility
- Sample optimization
- Initial sample assessment
• Purity• Integrity• Homogeneity/dispersity
• Homogeneity• Solubility• Time stability• Storage
- Activity assessment
- Minimal information to be known
• Protein name, origin, sequence (i.e. protein identity)
• Storage conditions (Buffer, T°….)• Concentration (how it was measured!!)
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Our proposal
Protein identity and production parameters protein name and complete sequence, by providing a
NCBI or UniProt accession number, cloning strategy and the source of the DNA (species)
expression vector and host strain, including the tags and cleavage sites used, with the complete sequence of the final protein (or sufficient details to derive it)
Expression and purification conditions, described in full details for possible reproduction
Protein concentrationSpecifying the method used for quantification and the molar extinction coefficient at 280 nm, if applicable
Storage conditionsi.e. final buffer composition (pH, buffer, salts and additives), storage temperature or lyophilization conditions
The minimal information that needs to be provided or known
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The minimal quality control parameters
Homogeneity/dispersitychecked preferably by Size Exclusion Chromatography (SEC) and/or dynamic Light Scattering (DLS) or by SEC with Multi Angle Light Scattering (SEC-MALS), Flow Field-Flow Fractionation (F4), F4-MALS or analytical ultracentrifugation (AUC)
Identity and integritychecked preferably by intact protein mass (MS), peptide mass fingerprint (MS), or Edman sequencing
PurityChecked by SDS-PAGE, Capillary Electrophoresis (e.g. LabChip GXII), Reverse Phase LC or Mass Spectrometry
Our proposal
10 20 30
100
200
300
400
500
600
Ab
so
rba
nc
e (
Au
)
Time (min)
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UV spectrum between 240 nm and 340 nm Mandatory if protein binds nucleic acidsNucleic acid content and general protein fitness/quality
Batch-to-batch consistency Mandatory if more than one batch is to be usedUse some of the methods listed for minimal QC
Conformational stability/folding stateChecked by Circular Dichroism(CD), Differential Scanning Calorimetry (DSC),NMR, Fourier Transform InfraRed (FTIR)
Homogeneity (e.g. isoforms)Checked by analytical Ion Exchange Chromatography (IEX), analytical Hydrophobic Interaction Chromatography (HIC), Isoelectric Focusing (IEF)
Protein competent fraction, i.e. the relative amount of active protein Measured as specific activity, by active-site titration or other suitable methods (to measure biological activity)
Optimization of storage conditionsLong term stability, activity assay, DLS or thermal shift assay
Extended quality control parameters
Our proposal
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The minimum quality control relies on five methods only:
• SDS-PAGE
• UV-Visible spectrophotometry
• Mass spectrometry
• Size exclusion chromatography
• Dynamic light scattering
Minimum quality control guideline
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Collection of experimental data in order to provide a statistical basis
31 institutions
47 laboratories
186 samples
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0 10 20 30 40 50 60 70
Archae
Artificial
Bacterial
Bovine
Horseshoe crab
Human
Insect
Jellyfish
Lama
Mouse
Phages
Other
Plant
Plasmodium
Platyhelminthes
Protozoa
Viral
Yeast
Type of sample
0 20 40 60 80 100 120 140
Secreted
Cytoplasmic
Membrane protein without any trans-membrane domain (Ecto domain or
intracellular domain)
Membrane protein including part or all ofthe trans-membrane domain
Other
Samples are mainly of human and bacterialorigin. The majority of them corresponds to cytoplasmic proteins
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The guideline: minimal information that needs to be provided or known
0,00% 20,00% 40,00% 60,00% 80,00% 100,00%
Full peptidic sequence
NCBI or Uniprot ascession nuber
Cloning strategy
Theoretical extinction coefficient
Measured extinction coefficient
0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
Bacterial
Cell Free
Insect
Mammalian
Natural source
Synthetic
Yeast
Other:
Known informations on the sample Knowledge of the system of production
< 100%
~80%
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Knowledge of the storing conditions
0% 20% 40% 60%
280nm with cuvette spectrophotometer
280nm with Nanodrop
Amino Acid Analysis
Fourier Transform InfraRed (Direct detect...)
Bradford assay
BCA assay
Lowry assay
Refractometry
Not performed
other
0,00% 20,00% 40,00% 60,00% 80,00% 100,00% 120,00%
Final buffer composition
Storage Temperature
Lyophilisation condition
Not known
Knowledge of the concentration, and method used for [P] determination
The guideline: minimal information that needs to be provided or known
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Method used for control of purity
The guideline: minimal quality control parameters
3.3%
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The guideline: minimal quality control parameters
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The guideline: minimal quality control parameters
Thus, only 67% of the samples were tested for identityand/or integrity and, out of these, 21% (ca. 1 out of 5) gave masses or sequences that did not correspond to the anticipated values
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31%
69%
Failed at least one of the tests
failed
passed
Out of those samples that have been tested for the three criteria (i.e. purity, homogenity and identity), 1/3 did not pass the three controls (i.e. failed at least one of the minimal tests)
The guideline: minimal quality control parameters
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0% 5% 10% 15% 20% 25% 30% 35% 40%
Antibody production
Biochemical studies
Molecular Biophysics
Structural determination
In vivo studies
Cellular biology
HTS
Downstream application The outcome of downstream applications was known for 130 out of the 186 samples
Among these 130 samples, we consideredthose that were tested for the 3 criteria (i.e. putity, homogeneity, integrity) and that failedat least one of them:26% failed in the downstream application;53% suceeded only partly;21% fully succeeded in the downstreamapplication.
In conclusion, only 1/5 did fully succeed in downstream applications
The guideline: minimal quality control parameters
Failed one of the minimal test
Failed Succeed partly Succeed
53%
21% 26%
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Correlation between favourable QC results and "satisfactory" results obtained in downstreamapplications.
Out of these 130 samples, among those that passed the three criteria (i.e. putity, homogeneity, integrity), 74% yielded satisfactory results, 20% suceeded only patially and 6% failed in the downstream application.In contrast, most (ca. 80%) of the samples that failed one or more of the minimal QC tests didnot give satisfactory results in downstream applications.
The guideline: minimal quality control parameters
6%20%
26% 21%
53%
74%
69%
31%
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So what is our proposal?
Guidelines with minimal information that needs to be known before using a protein
Our guidelines are the result from the collective expertise of ca. 150 laboratories
lay the groundwork for the standardization and reproducibility of data in any laboratory that produces recombinant proteins
encourage the whole scientific community to implement this QC methodology
raise awareness amongst colleagues and collaborators
reverse the trend for less and less information available in mainsteam journals on theproduction and purification of laboratory reagents
lobby editors to encourage/oblige more extensive use of supplementary data, and report the results of each check-point in research papers
improve reproducibility between labs + increase confidence in published data
Identity HomogeneityPurity Integrity
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“When papers are written and data are presented in public it
looks like everything is just perfect, and that is not what
science is.
Science is an imperfect human activity that we try to do as
best we can.”
Bjorn Olsen, Harvard cell biologist.
Slide from Dr. Mario Lebendiker , WOLFSON CENTRE FOR APPLIED STRUCTURAL BIOLOGY, The ProteinPurification Facility, HEBREW UNIVERSITY OF JERUSALEM - PEGS Europe in Lisbon, November 3rd 2016
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References on the subject
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The QC team of ARBRE/MOBIEU and P4EU
Nick Berrow - Institute for research in Medicine, Barcelona, Spain (P4EU)
Maria Garcia-Alai - EMBL Hamburg, Germany (ARBRE-MOBIEU)
Stefan Knauer - Bayreuth University, Germany (ARBRE-MOBIEU)
Mario Lebendiker - Hebrew University of Jerusalem, Israel (P4EU)
Blanca Lopez-Mendez - University of Copenhagen, Denmark (ARBRE-MOBIEU)
Ario de Marco - University of Nova Gorica, Slovenia (P4EU and ARBRE-MOBIEU)
André Matagne - University of Liège, Belgium (ARBRE-MOBIEU)
Annabel Parret - EMBL Hamburg, Germany (P4EU)
Bertrand Raynal - Pasteur Institute, Paris, France (ARBRE-MOBIEU)
Kim Remans - EMBL Heibelberg (P4EU)
Stephan Uebel - Max-Planck Institute for Biochemistry, Munich (ARBRE-MOBIEU)
In representation of:
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Acknowledgement (merci!!!)