29 juin 2017 next generation...
TRANSCRIPT
http://icim.marseille.inserm.fr/spip.php?article97
IPC - CRCM - Marseille
Mélange de protéomes: étude du Microbiote
Imagerie par spectrométrie de masse
Echange Hydrogène Deutérium
Protéomique Top Down
Marquage isobarique
Glycoprotéomique
Protéomique ciblée
Interactome
Next generation proteomics
VIIIème Rencontre du réseau des plates-formes protéomiques
de la région Provence Alpes Côte d’Azur
29 Juin 2017
Nos soutiens académiques
Nos soutiens privés
PROTEOPACA 2017
Sommaire
Programme 6 Résumé des conférences. - Stéphane AUDEBERT, CRCM, Marseille. 9 - Julien PELTIER, Newcastle University, UK. 10 - Nicolas AUTRET – Somalogic 11 - Séga NDIAYE – Thermo-Scientific 12 - Julia CHAMOT-ROOKE, Institut Pasteur, Paris. 13 - Jean-Baptiste VINCENDET – Sciex 14 - Mourad FERHAT – Promega 15 - Céline HENRY, INRA PAPPSO, Jouy-en-Josas. 16 - Sébastien BRIER, Institut Pasteur, Paris. 17 - Luc CAMOIN, CRCM, Marseille. 18 - Thibaut LEGER, Institut Jacques Monod, Paris. 19 - Anaïs BAUDOT, I2M, Marseille. 20 - Angeline KERNALLEGUEN, CRO2, Marseille. 21
Liste des inscrits. 22
29 Juin 2017
6
Résumés des conférences
PROTEOPACA 2017
Stéphane Audebert Marseille Protéomique,
Centre de Recherche en Cancérologie de Marseille
INSERM U1068 - CNRS UMR7258 - Aix-Marseille
Université UM105
Marseille, France
Interactome: new tools for protein complexes identification
The Proteomic platform at CRCM emerged from Jean-Paul Borg’s team that works for
several years in the field of protein-protein interactions, cell polarity and its deregulation
in cancer development. Our platform developed a very strong expertise in the discovery of
novel protein-protein interactions and identification of protein complexes using affinity-
purification mass spectrometry (AP-MS) approaches. I will illustrate my talk with a few
examples of protein complexes identified by immunoprecipitation, pulldown, or peptides
pulldown these last years and will present the last strategies we favour since more
efficient precipitation tools called nanobodies are available. New strategies as BirA or
APEX approaches allowing the identification of low affinity or transient partners will also
be presented.
Besides biochemical development, improvement of mass spectrometers with higher scan
speed, higher sensitivity and dynamic range as well as choice of quantitative strategies
allow us to go deeper and faster into the proteomes to detect low abundant interactors.
References
- Audebert S, et al. Mammalian Scribble forms a tight complex with the betaPIX exchange factor. Curr
Biol. (2004).
- Puvirajesinghe TM, et al. Identification of p62/SQSTM1 as a component of non-canonical Wnt
VANGL2-JNK signalling in breast cancer. Nat Commun. (2016).
- Daulat A.M., et al. PRICKLE1 contributes to cancer cell dissemination through its interaction with
mTORC2. Developmental Cell, (2016).
- Cartier-Michaud A, et al. Genetic, structural, and chemical insights into the dual function of GRASP55
in germ cell Golgi remodeling and JAM-C polarized localization during spermatogenesis. PLoS Genet.
(2017).
- Belotti E, et al. The human PDZome: a gateway to PSD95-Disc large-zonula occludens (PDZ)-mediated
functions. Mol Cell Proteomics. (2013).
- Daou P, et al. Essential and nonredundant roles for Diaphanous formins in cortical microtubule capture
and directed cell migration. Mol Biol Cell. (2014).
- Verdier-Pinard P, et al. Septin 9_i2 is downregulated in tumors, impairs cancer cell migration and alters
subnuclear actin filaments. Sci Rep. (2017).
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10
Julien Peltier Institute for Cell and Molecular Biosciences (ICAMB)
Faculty of Medical Sciences, Newcastle University
Newcastle Upon Tyne, NE2 4HH
Thermal profiling of Breast cancer cells reveals proteasomal
activation by CDK4/6 inhibitor Palbociclib [1]
Palbociclib (Ibrance®, Pfizer) is a recent drug approved by the FDA for phase III clinical
trials in treating estrogen-receptor-positive and HER2-negative breast cancer. In vitro,
palbociclib, a selective inhibitor of CDK4 and CDK6, was shown to reduce cellular
proliferation of breast cancer cell lines by blocking progression of cells from G1 into S
phase of the cell cycle. While the primary targets of palbociclib have been deciphered, the
molecular mechanisms leading to off-targets effects as well as drug resistance are not
known. To identify new palbociclib protein targets we applied a Cellular Thermal Shift
Assay and a quantitative proteomic analysis (MS-CeTSA) that works under the
assumption that protein-drug interaction stabilises proteins thus, leading to an increase in
thermostability. MCF-7 breast cancer cells were cultured under palbociclib treatment or
DMSO and heated from 37°C to 68°C. Supernatants from 10 different temperatures were
collected for quantitative proteomic analysis using Tandem Mass Tag (TMT-10plex) on an
Orbitrap Fusion Tribrid instrument. The calculated fold changes, as a function of
temperature, follow a sigmoidal trend reflecting the thermal stability of proteins and their
disappearance with increasing temperature.
Large scale proteomic analysis on the Orbitrap Fusion Tribrid instrument allowed the
identification and the quantification of 38,498 peptides corresponding to 5,516 proteins.
As expected, CDK4 and CDK6, the molecular targets of palbociclib were among the 10
most-changing proteins and showed a shift in the temperature (∆tm) of 4.9°C and 3.7°C.
Validation by WB-CeTSA confirmed CDK4/6 stabilisation. Interestingly, classification of
identified protein kinases according to the calculated ∆tm revealed new potential targets of
palbociclib such as CAMK2D, AKT1 and MTOR proteins. Preliminary validation in-vitro
indicated that the MTOR-PI3K signalling pathway may be impaired by the action of
palbociclib. In addition, the MS-CeTSA also revealed a stabilisation of several
proteasomal proteins of the 20S core proteasome through the inhibition of the proteasome-
associated scaffolding protein ECM29. Taken together, these data suggest that off-targets
effects during palbociclib treatment may positively participate in the global response by
blocking tumor progression from G1 into S phase of the cell cycle.
References [1] *Peltier J, *Miettinen T, Härtlova A, Gierliński M, †Björklund M. and †Trost M, Thermal profiling of Breast
cancer cells reveals proteasomal activation by CDK4/6 inhibitor Palbociclib, Nat Commun, Under revision.
Nicolas Autret, PhD
SomaLogic, Ltd.
Regional Manager, Southern Europe
SOMAmers: use of modified aptamers as a new proteomics tool
for unprecedented multiplex assay - the SOMAscan
Even though proteins are the targets of 95% of all known drugs, and downstream of
both genetics and the environment, proteomics has failed to generate even a fraction of the
excitement that drives the genomics revolution. This has been justifiable until now
because large scale, high throughput, highly multiplexed protein measurements have not
been possible.
With the availability of the SOMAscan 1.3k assay, using modified DNA-based
reagents which form highly specific complexes with proteins, we have re-purposed genetic
technologies to measure proteins at unprecedented scale and performance: sub-picogram
simultaneous detection of thousands of proteins with high precision and tiny volumes of
sample.
Examples from cancer, neurological disorders up to cardiovascular diseases will be
shown of how the individual novel reagents as well as the SOMAscan assay are being
used to uncover new biology, validate new targets and deliver actionable information for
medical practice and drug development.
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Séga NDIAYE Life Sciences MS Proteomics Sales Specialist
Chromatography and Mass Spectrometry
Thermo Fisher Scientific.
New innovations implemented on the Q Exactive HF mass
spectrometer.
Orbitrap-based mass spectrometers are increasingly being used for many different
applications. Each application imposes special requirements on the mass spectrometer.
Modern mass spectrometers have improved sensitivity, accuracy, high resolution, and/or
increased scanning speed. These directly result in significant benefits for applications such
as proteomics, environmental and food safety, metabolomics, lipidomics and many more.
Though we have come these far, further technical improvements or next-generation mass
spectrometers are desired by the mass spectrometric community. To further address
existing and new requirements from a broad field of applications, new technological
developments and performance improvements on the existing Thermo Scientific™ Q
Exactive™ HF instrument were undertaken.
We made both hardware and software changes to enhance the performance of the Q
Exactive HF instrument. A brighter ion source interface was realized by replacing the
heated capillary with a modified design with higher throughput, and replacing the S-lens
with an ion funnel for improved ion transmission. To accommodate both changes, the
fore-vacuum system was adapted for higher pumping capacity. Furthermore, the bent
flatapole was modified in order to maintain correct operating pressure and minimize
unwanted solvent cluster formation. Further changes were aimed at reducing the overhead
time between scans.
Tabiwang N. Array; Eugen Damoc; Erik Couzijn; Jens Grote; Oliver Lange; Christian Thoeing; Kerstin
Strupat; Catherina Crone; Anastassios Giannakopulos; Thomas Moehring and Alexander Harder
Thermo Fisher Scientific, Bremen, GERMANY
Julia Chamot-Rooke Mass Spectrometry for Biology Unit
Department of Structural Biology and Chemistry
Institut Pasteur, CNRS
Paris, France
Top-down proteomics: the next step in clinical microbiology. In the last decade, the introduction of MALDI-TOF Mass Spectrometry (MS) for rapid microbial
identification has revolutionized the field of clinical microbiology. The approach has been widely
embraced by hospitals as it is faster, more accurate, and less expensive than conventional
phenotypic or genotypic methods. However, it suffers from important limitations. The
discriminatory power of the technique is insufficient to differentiate closely related bacteria or
sub-species and more importantly resistance and virulence cannot be addressed. There is
therefore a crucial need for innovative analytical approaches allowing an efficient and more
accurate bacterial identification based on protein analysis.
Top-down proteomics is an emerging technology based on the analysis of intact proteins using
very high-resolution mass spectrometry [1]. It provides the highest molecular precision for
analyzing primary structures by examining proteins in their intact state, leading to more
straightforward and reliable results than the classical bottom-up approach based on protein
enzymatic digestion.
Top-down proteomics is particularly suited to the analysis of bacterial proteins, which are of
small size (< 30 kDa) and produced in large amount by bacterial pathogens [2,3].
In order to use top-down proteomics for clinical microbiology applications [4], we set up an
integrated platform in which all steps have been carefully optimized: bacterial lysis, protein
extraction, LC-MS/MS analysis of intact proteins and data processing. For this last point, a new
software tool, which branches from an existing one [5], but tailored towards top-down proteomics
data, has been developed. This new software, based on machine learning, can rapidly cluster the
thousands of MS/MS spectra obtained in top-down LC-MS/MS experiments, compare datasets
obtained from various bacterial pathogens and identify discriminative spectra.
Using this integrated top-down platform, we show that it is now possible to differentiate closely-
related pathogens that are impossible to distinguish with MALDI-TOF MS, in only a few hours
after bacterial culture. We also highlight the great potential of top-down approaches to delineate
complete protein sequences (including C-terminal and N-terminal extremities) and detect single
nucleotide polymorphisms. References
[1] Proteoform: a single term describing protein complexity. L.M. Smith, N. L. Kelleher and the Consortium for
Top-Down Proteomics, Nature Methods (2013).
[2] Posttranslational Modification of Pili upon Cell Contact Triggers N. meningitidis Dissemination. J. Chamot-
Rooke et al., Science, (2011).
[3] Complete posttranslational modification mapping of pathogenic Neisseria meningitidis pilins requires top-down
mass spectrometry. J. Gault et al., Proteomics (2014).
[4] Top-down proteomics in the study of microbial pathogenicity. J. Gault et al. in MALDI-TOF and Tandem MS
for Clinical Microbiology, Wiley (2017).
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Jean Baptiste VINCENDET Life Sciences Holdings France SAS
SCIEX.
High Throughput 1h injection SWATH : Enabling the path to
Personalized Medicine with Industrialized and Integrated Omics.
Enabling industrialized Proteomics makes possible the fast and very reproducible
quantitative and qualitative analysis of 100s of samples. Thus it makes possible to analyze
in a reasonable time frame big patient cohorts and to get the most of them. Additionally,
integrating other omics sciences in the same environment opens the door to a more
comprehensive biology view of the samples.
14
Mourad FERHAT, PhD, MBA Promega France.
Product manager, cellular analysis and Proteomics
Overcoming Key Challenges of Protein Mass Spectrometry
Sample Preparation
Bottom-up proteomics is widely accepted as a primary method to characterize
proteins. To ensure efficient protein analysis researchers must optimize key steps in the
workflow to avoid potential pitfalls such as poor protein sample preparation and
inconsistent LC-MS instrument performance. In this presentation, we will:
• Investigate the cause of incomplete trypsin digestion and solution to this problem.
• Discuss the advantage of alternative proteases for mass spec protein analysis.
• Review the impact of mass spec compatible surfactants on protein digestion in gel and
protein extraction from animal tissues.
• Detail new reference mass spec protein and peptide materials designed to optimize
protein sample preparation steps and monitor key instrument performance parameters
The presentation should prove valuable to any researcher using bottom-up proteomics, and
who is concerned with improving protein mass spec sample preparation and mass spec
instrument performance.
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Céline HENRY PAPPSO, Micalis Institute, INRA, AgroParisTech,
Université Paris-Saclay,
78350 Jouy-en-Josas, France
The winning trio in Metaproteomic : 75 cm column, Orbitrap
Fusion™ Lumos™ Tribrid™ and
X !TandemPipeline
Bottom-up approach was fully used in quantitative proteomics strategy. The last
development in shotgun approach was mentioned in the article «The one hour yeast
proteome» (Hebert et al (2014)), in which 3,977 proteins were identified (1,3 hours of run,
35 cm column, Orbitrap Fusion™Tribrid™). This let us to imagine what we could be able
to achieve if we could improve the column size and the time of run with a fast and
sensitive mass spectrometer.
PAPPSO platform works since a long time with complex samples in the Metaproteomic
field, using 50 cm column with sensitive mass spectrometers (Juste, C., et al. (2014)).
Metaproteomic samples are extremely complex and have a particular dynamic range, that
makes the mass spectrometry analysis more difficult than with others samples. Recently
outfitted with an Orbitrap Fusion™ Lumos™ Tribrid™, we have used 75 cm column
(Thermo Scientific) to improve the number of identified peptides while keeping an
acceptable run time.
Different methods of sample preparations with patient heart disease were tested. This new
column allowed us to improve by 30 to 50 % the number of identified proteins.
The results will be discussed with X!TandemPipeline (Langella, O. et al. (2017)), a house
made software and designed to perform protein inference and to manage the redundancy
of peptides identification results after the database search. This software, free and open
source is the only one able to deal with very large raw data sets and huge database,
yielding possible the treatment of hundreds of complex samples in a short time.
A new generation mass spectrometer, a longer column and efficient analysis software have
made available the microbiota analyses of more than 500 patients. This big cohort, allows
us to have a better comprehension of the metabolism among ill individuals in order to
discover future therapeutics targets against metabolic disorders.
17
Sébastien Brier Department of Structural Biology and Chemistry
Mass Spectrometry for Biology Unit, CITECH, CNRS USR
2000,
Institut Pasteur, Paris, France
Probing hydrogen exchange in proteins by mass spectrometry
Hydrogen/Deuterium eXchange measured by Mass Spectrometry (HDX-MS) is a
powerful tool to probe the structure and dynamics of proteins in solution. Significant
improvements in the past decade have resulted in the technology becoming an invaluable
resource in both the academic and pharmaceutical sector. In particular, the implementation
of robotics for sample handling and preparation, and the automation of the labor intensive
data processing step have greatly expedited current HDX-MS strategies.
In this talk, a brief introduction to the technology will be presented, along with the
major advances which have led to the streamline HDX-MS workflow which is
commercially available today. As an example, two applications will be discussed.
Specifically, the use of HDX-MS for both epitope mapping and to probe conformational
changes associated with small ligand binding in a human integral membrane protein will
described in detail.
References [1] Wales T.E, and Engen J.R. Hydrogen exchange mass spectrometry for the analysis of protein
dynamics, Mass Spectrom. Rev., 25(1), 2006: 158-70
[2] Ahn J., and Engen J.R. The use of hydrogen/deuterium exchange mass spectrometry in epitope
mapping, Chemistry Today, 31 (1), 2013: 25-28
[3] Malito E., et al. Defining a protective epitope on factor H binding protein, a key meningococcal
virulence factor and vaccine antigen, PNAS, 110(9), 2013: 3304-09
[4] Canul-Tec J.C., Reda A., et al. Structure and allosteric inhibition of excitatory amino acid transporter
1, Nature, 544, 2017: 446-51
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Luc Camoin Marseille Protéomique,
Centre de Recherche en Cancérologie de Marseille
INSERM U1068 - CNRS UMR7258 - Aix-Marseille
Université UM105
Marseille, France
Clinical Proteomics: identification of potential biomarkers
The determination of differences in relative protein abundance is a critical aspect of
proteomics research that is increasingly used to answer diverse biological questions.
However, detection of differences between two or more physiological/pathological states
of a biological system is among the most challenging technical tasks in proteomics.
In my lecture I will briefly describe differents quantitative proteomics analysis that we will
develop in different projects associated with cancer research. Firstly, I will discuss how a
serological biomarker may be used for the selection of patients in colorectal cancer (1).
Secondly, I will show how targeted quantitative proteomics can be used to profile breast
cancer tumors to predict the efficacy of targeted therapies (2).
References [1] Guerin M, Gonçalves A, Toiron Y, Baudelet E, Audebert S, Boyer JB, Borg JP, Camoin L. How may
targeted proteomics complement genomic data in breast cancer? Expert Rev Proteomics. 2016 Nov 4; 14:
43-54
[2] Peltier J, Roperch JP, Audebert S, Borg JP, Camoin L. Quantitative proteomic analysis exploring
progression of colorectal cancer: Modulation of the serpin family. J Proteomics. 2016 Aug 2;148: 139-
148
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Thibaut Léger Institut Jacques Monod, UMR7592
Université Paris Diderot/CNRS,
Sorbonne Paris Cité, FRANCE
The metacaspase Mca1p as a link between proteolysis, apoptosis
and glycosylation in the human pathogenic yeast Candida albicans
Candida albicans is a commensal fungus of the gut flora, mucous and epithelia and an
opportunistic human pathogen causing benign infections, such as oral or genital
candidiasis, and more severe life-threatening systemic infections, particularly in
immunocompromised patients. An understanding of the pathways giving rise to cell death
is required, to improve our comprehension and control of the process of apoptosis in this
pathogen. The metacaspase Mca1p has been described as a key protease for apoptosis in
C. albicans but little is known about its cleavage specificity and substrates. To
characterize its functions, we subjected wild-type and mca1-deletion strains to the quorum
sensing molecule farnesol and then studied the early phase of apoptosis release in
innovative quantitative proteomics, glycoproteomics and glycomics experiments. The
combination of the deletion and the farnesol molecule led to the strong overexpression of
proteins implicated in the general stress. We found the Mca1p cleavage specificity “K/R”
in P1 and D/E in P2 and identified 57 potential substrates of Mca1p, implicated in protein
folding, protein aggregate resolubilization, glycolysis, glycosylation machinery and a
number of mitochondrial functions. By several glycoproteomics approaches, we identified
76 glycosylations (17 N- and 58 O-glycosylations), 100 sites of N-glycosylations and we
showed a general increase in the O-glycosylation of proteins in the deleted strains treated
with farnesol. Our findings highlight new roles of the metacaspase in amplifying cell death
processes by degrading several major Heat Shock Proteins, by contributing significantly to
the control of mitochondria biogenesis and degradation, by affecting several critical
protein quality control systems and altering the protein glycosylation machinery. These
findings open up unexpected new possibilities for developing targeted inhibitors of C.
albicans growth.
References 1. Leger T. et al. The Metacaspase (Mca1p) Restricts O-glycosylation During Farnesol-induced
Apoptosis in Candida albicans. Molecular & cellular proteomics (2016): MCP 15, 2308-2323
2. Leger T. et al. Label-Free Quantitative Proteomics in Yeast. Methods Mol Biol (2016) 1361, 289-307
3. Leger T. et al. The metacaspase (Mca1p) has a dual role in farnesol-induced apoptosis in Candida
albicans. Molecular & cellular proteomics (2015): MCP 14, 93-108
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Anaïs Baudot I2M,
AMU-CNRS,
Marseille, France
Bioinformatics and interactome in proteomics, application to
prostate cancer cell lines
Networks, in which the nodes represent proteins, and the edges different categories of
interactions, are widely used in proteomics. They are useful for instance to visualize
discovered physical interactions by drawing interactome data. They can also picture
functional interactions, derived from other –omics data, such as gene or protein
expression. Finally, they can be used to integrate different type of large-scale data, such as
proteomics and phosphoproteomics. In any cases, the obtained networks are large and
complex, and call for the development of new tools and approaches to extract the
functional knowledge they contain [1-3].
Following the interactomics [4], proteomics and phosphoproteomics data we have
generated to study prostate cancer cell lines and their resistance behaviors, I will present
different application of these network-based bioinformatics approaches.
References [1] Spinelli L, Gambette P, Chapple CE, Robisson B, Baudot A, Garreta H, Tichit L, Guénoche A, Brun
C (2013) Clust&See: A Cytoscape plugin for the identification, visualization and manipulation of
network clusters. BioSystems 113: 91–95.
[2] Didier G, Brun C, Baudot A (2015) Identifying Communities from Multiplex Biological Networks.
PeerJ 3: 1–9.
[3] Valdeolivas A, Tichit L, Navarro C, Perrin S, Odelin G, Levy N, Cau P, Remy E, Baudot A (2017)
Random Walk With Restart On Multiplex And Heterogeneous Biological Networks. bioRxiv.
[4] Katsogiannou et al. (2014) The Functional Landscape of Hsp27 Reveals New Cellular Processes such
as DNA Repair and Alternative Splicing and Proposes Novel Anticancer Targets. Mol Cell Proteomics
13: 3585–3601.
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Angéline KERNALLÉGUEN Inserm, CRO2, UMR_S 911, PIT2,
Faculty of Pharmacy,
Marseille, France
Drugs distribution profile in the hair by MALDI imaging
Already widely demonstrated, hair strands analysis documents punctual or regular
consumption of drugs of abuse (DOA). With the introduction of the Matrix Assisted Laser
Desorption Ionization mass spectrometry (MALDI), new opportunities appear, such as
high-throughput profiling and drugs monitoring [1]. Mass spectrometry imaging (MSI)
coupled to MALDI offers the unique possibility to map with high spatial resolution several
tens of species into only one intact hair [2–4]. Current conventional and destructive
methods (GC-MS, LC-MS) usually require a great amount of hair samples to ensure the
identification of various DOA families, which is not compatible with low hair availability
case.
In this presentation, a brief introduction to the MALDI technology will be done, followed
to a discussion on the pitfalls to avoid in hair samples preparation. To conclude, several
drugs distribution profiles by MALDI imaging in various MS stage will be discussed.
References [1] Vogliardi S, Favretto D, Frison G, Maietti S, Viel G, Seraglia R, et al. Validation of a fast screening
method for the detection of cocaine in hair by MALDI-MS. Anal Bioanal Chem. (2010); 396(7):2435–40.
[2] Poetzsch M, Steuer AE, Roemmelt AT, Baumgartner MR, Kraemer T. Single Hair Analysis of Small
Molecules Using MALDI-Triple Quadrupole MS Imaging and LC-MS/MS: Investigations on
Opportunities and Pitfalls. Anal Chem. (2014); 86 (23):11758–65.
[3] Kamata T, Shima N, Sasaki K, Matsuta S, Takei S, Katagi M, et al. Time-Course Mass Spectrometry
Imaging for Depicting Drug Incorporation into Hair. Anal Chem. (2015); 87(11):5476–81.
[4] Beasley E, Francese S, Bassindale T. Detection and Mapping of Cannabinoids in Single Hair Samples
through Rapid Derivatization and Matrix-Assisted Laser Desorption Ionization Mass Spectrometry. Anal
Chem. (2016); 88(20):10328–34.
ABOUSERHALDAOU Pascale Thermofisher scientific [email protected] ALMERAS Lionel IRBA [email protected] AUDEBERT Stéphane - Intervenant CRCM-MaP [email protected] AUTRET Nicolas - Intervenant SOMALOGIC [email protected] BAUDOT Anaïs - Intervenante I2M [email protected] BEBIEN-LAWRENCE Magali CIML [email protected] BELGHAZI Maya CRN2M-MaP [email protected] BIRG Françoise CRCM [email protected] BOUGIS Pierre CRN2M-MaP [email protected] BRES Anne-Sophie GE Healthcare [email protected]
BRIER Sébastien - Intervenant Institut Pasteur [email protected] BROUSSE Carine CRCM-TrGET [email protected] BRUSCHI Mireille IMM-CNRS [email protected] BUHOT-ROCHE Blandine GE Healthcare [email protected] CABANTOUS Sandrine INSERM [email protected] CAMOIN Luc - Intervenant CRCM-MaP [email protected] CAU Pierre ProGeLife [email protected] CHAMOT ROOKE Julia - Intervenante Institut Pasteur [email protected] CSATETS Francis IBDM [email protected] DAULAT Avais CRCM [email protected]
Liste des participants
PROTEOPACA 2017
22
DESCHANEL Louis Thermofisher scientific [email protected] DE SEPULVEDA Paulo CRCM [email protected] DEBAYLE Delphine IPMC [email protected] DUBOIS Cécile IRSN [email protected] EL KOULALI Khadija CRCM [email protected] FERHAT Mourad - Intervenant PROMEGA [email protected] FERRACCI Geraldine CRN2M-MaP [email protected] FOURQUET Patrick CRCM-MaP [email protected] FRELON Sandrine IRSN [email protected] GAUTHIER Laurent INNATE PHARMA [email protected] GAY Anne-Sophie IPMC-CNRS [email protected] GONTERO MEUNIER Brigitte BIP2-MaP [email protected]
GRANJEAUD Samuel CRCM-MaP [email protected] GUERIN Mathilde CRCM-MaP [email protected] GUIGONIS Jean-Marie Faculté de Médecine Nice [email protected] HENRY Céline - Intervenante PAPPSO [email protected] HUTINEL Olivier ABSciex [email protected] IMBERT Isabelle CNRS AFMB [email protected] JHUMKA Anissa IBDM [email protected] KELLER Lionel Thermo Fisher Scientific [email protected] KERNALLEGUEN Angéline - Intervenante FACULTE PHARMACIE PIT2-MaP [email protected] KHANTANE Sabrina Thermofisher scientific [email protected] KUZMIC Mira IRSN [email protected] LAN Wenjun CRCM [email protected]
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LEBRUN Régine IMM-MaP [email protected] LEE Lara CRCM [email protected] LEGER Thibaut - Intervenant Institut Jacques Monod [email protected] LEGOUPIL Thierry SHIMADZU [email protected] LELLOUCH Anne-marie IBDM [email protected] LEQUEUE Charlotte CRCM [email protected] LLOUBES roland IMM-CNRS [email protected] LOPEZ Sophie CRCM [email protected] MAGLIANO Marc INRA [email protected] MALAPERT Pascale IBDM [email protected] MANSUELLE Pascal IMM-MaP [email protected] MAO Qiyan IBDM [email protected]
MARFISI Claude Bruker [email protected] MASSEY-HARROCHE Dominique IBDM [email protected] MEHUL Bruno GALDERMA [email protected] MIGNOT Florian PROMEGA France [email protected] MOAL Stéphane Cell Signaling [email protected] MONDIELLI Grégoire CRN2M [email protected] MOQRICH Aziz IBDM [email protected] NDIAYE Séga – Intervenant Thermofisher scientific [email protected] NORMANNO Davide CRCM [email protected] NUCCIO Christopher FACULTE PHARMACIE PIT2 [email protected] OUNOUGHENE Youcef CIML [email protected] PASQUIER Eddy CRCM [email protected]
24
PELTIER Julien - Intervenant Newcastle University [email protected] PICLIN Nadége GE Healthcare [email protected] POPHILLAT Matthieu CRCM-MaP [email protected] POPOVIC Luksa CRCM [email protected] PYR dit Ruys Sébastien IRSN [email protected] RESCH Sylvain SHIMADZU [email protected] RISSO-MOREAU DE FAVE Christine UCAPolytech Nice-Sophia [email protected] ROCCHI Palma CRCM [email protected] ROSSI Benjamin INNATE PHARMA [email protected] RUMINSKI Kilian CIML [email protected] SANTOS Catarina IBDM [email protected] SAVARD-CHAMBARD GAS Sandra INNATE PHARMA [email protected] 25
SCHEMBRI Thérèse FACULTE PHARMACIE PIT2 [email protected] SEASSAU Aurelie INRA PACA [email protected] SEBBAGH Michael CRCM [email protected] SILVIERA de MORAIS Ana Theresa AFMB Lab, Polytech [email protected] SILVEIRA WAGNER Monica CRCM [email protected] TERRAL Guillaume INNATE PHARMA [email protected] TINLAND Marie-France CRCM TOIRON YVES IPC/CRCM-MaP [email protected] VILLARD claude UMR INSERM 911 [email protected] VINCENDET Jean-Baptiste - Intervenant ABSciex [email protected]
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PROTEOPACA 2017
Organisation
Plateforme protéomique CRCM-IPC
Directeur Jean-Paul Borg
Comité local d’organisation :
Audebert Stéphane
Borg Jean-Paul Camoin Luc
Fourquet Patrick Granjeaud Samuel Pophillat Matthieu
Avec le soutien de Michel Baccini; Françoise Birg; François Coulier; Valérie Depraetère; Laurence Duvivier; Amandine Gazull; Laurence
Laloum; Claude Roux; Marie-France Tinland et Patrice Viens.
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PROTEOPACA 2017