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.
Allet
Nadia
N
GeneProt Inc., Meyrin, Switzerland.
Barrillat
Nicolas
N
Baussant
Thierry
T
Boiteau
Celia
C
Botti
Paolo
P
Bougueleret
Lydie
L
Budin
Nicolas
N
Canet
Denis
D
Carraud
Stéphanie
S
Chiappe
Diego
D
Christmann
Nicolas
N
Colinge
Jacques
J
Cusin
Isabelle
I
Dafflon
Nicolas
N
Depresle
Benoît
B
Fasso
Irène
I
Frauchiger
Pascal
P
Gaertner
Hubert
H
Gleizes
Anne
A
Gonzalez-Couto
Eduardo
E
Jeandenans
Catherine
C
Karmime
Abderrahim
A
Kowall
Thomas
T
Lagache
Sophie
S
Mahé
Eve
E
Masselot
Alexandre
A
Mattou
Hassan
H
Moniatte
Marc
M
Niknejad
Anne
A
Paolini
Marianne
M
Perret
Frédéric
F
Pinaud
Nicolas
N
Ranno
Frédéric
F
Raimondi
Sylvain
S
Reffas
Samia
S
Regamey
Pierre-Olivier
PO
Rey
Pierre-Antoine
PA
Rodriguez-Tomé
Patricia
P
Rose
Keith
K
Rossellat
Gérald
G
Saudrais
Cédric
C
Schmidt
Camille
C
Villain
Matteo
M
Zwahlen
Catherine
C
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