In vitro and in silico processes to identify differentially expressed proteins.
We present an integrated proteomics platform designed for performing differential analyses. Since reproducible results are essential for comparative studies, we explain how we improved reproducibility at every step of our laboratory processes, e.g. by taking advantage of the powerful laboratory information management system we developed. The differential capacity of our platform is validated by detecting known markers in a real sample and by a spiking experiment. We introduce an innovative two-dimensional (2-D) plot for displaying identification results combined with chromatographic data. This 2-D plot is very convenient for detecting differential proteins. We also adapt standard multivariate statistical techniques to show that peptide identification scores can be used for reliable and sensitive differential studies. The interest of the protein separation approach we generally apply is justified by numerous statistics, complemented by a comparison with a simple shotgun analysis performed on a small volume sample. By introducing an automatic integration step after mass spectrometry data identification, we are able to search numerous databases systematically, including the human genome and expressed sequence tags. Finally, we explain how rigorous data processing can be combined with the work of human experts to set high quality standards, and hence obtain reliable (false positive < 0.35%) and nonredundant protein identifications.
GeneProt Inc., Meyrin, Switzerland.
Nadia
N
Allet
Nicolas
N
Barrillat
Thierry
T
Baussant
Celia
C
Boiteau
Paolo
P
Botti
Lydie
L
Bougueleret
Nicolas
N
Budin
Denis
D
Canet
Stéphanie
S
Carraud
Diego
D
Chiappe
Nicolas
N
Christmann
Jacques
J
Colinge
Isabelle
I
Cusin
Nicolas
N
Dafflon
Benoît
B
Depresle
Irène
I
Fasso
Pascal
P
Frauchiger
Hubert
H
Gaertner
Anne
A
Gleizes
Eduardo
E
Gonzalez-Couto
Catherine
C
Jeandenans
Abderrahim
A
Karmime
Thomas
T
Kowall
Sophie
S
Lagache
Eve
E
Mahé
Alexandre
A
Masselot
Hassan
H
Mattou
Marc
M
Moniatte
Anne
A
Niknejad
Marianne
M
Paolini
Frédéric
F
Perret
Nicolas
N
Pinaud
Frédéric
F
Ranno
Sylvain
S
Raimondi
Samia
S
Reffas
Pierre-Olivier
PO
Regamey
Pierre-Antoine
PA
Rey
Patricia
P
Rodriguez-Tomé
Keith
K
Rose
Gérald
G
Rossellat
Cédric
C
Saudrais
Camille
C
Schmidt
Matteo
M
Villain
Catherine
C
Zwahlen
D001826:Body Fluids / Q000737:chemistry*; D002845:Chromatography / Q000295:instrumentation / Q000379:methods; D019295:Computational Biology; D016208:Databases, Factual; D020869:Gene Expression Profiling; D006801:Humans; D019451:Information Management / Q000295:instrumentation / Q000379:methods*; D013058:Mass Spectrometry / Q000295:instrumentation / Q000379:methods; D010455:Peptides / Q000032:analysis; D011506:Proteins / Q000032:analysis* / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results; D014584:User-Computer Interface
D010455:Peptides; D011506:Proteins