Automating proteome analysis: improvements in throughput, quality and accuracy of protein identification by peptide mass fingerprinting.
The use of robots has major effects on maximizing the proteomic workflow required in an increasing number of high-throughput projects and on increasing the quality of the data. In peptide mass finger printing (PMF), automation of steps downstream of two-dimensional gel electrophoresis is essential. To achieve this goal, the workflow must be fluid. We have developed tools using macros written in Microsoft Excel and Word to complete the automation of our platform. Additionally, because sample preparation is crucial for identification of proteins by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry, we optimized a sandwich method usable by any robot for spotting digests on a MALDI target. This procedure enables further efficient automated washing steps directly on the MALDI target. The success rate of PMF identification was evaluated for the automated sandwich method, and for the dried-droplet method implemented on the robot as recommended by the manufacturer. Of the two methods, the sandwich method achieved the highest identification success rate and sequence coverage of proteins.
Canelle
Ludovic
L
Laboratoire de Biochimie des Protéines et Protéomique, EA 3408, Université Paris 13, UFR SMBH Léonard de Vinci, Bobigny, France.
Pionneau
Cédric
C
Marie
Arul
A
Bousquet
Jordane
J
Bigeard
Jean
J
Lutomski
Didier
D
Kadri
Tewfik
T
Caron
Michel
M
Joubert-Caron
Raymonde
R
D003110:Colonic Neoplasms / Q000737:chemistry; D004591:Electrophoresis, Polyacrylamide Gel; D006801:Humans; D059630:Mesenchymal Stem Cells / Q000737:chemistry; D010449:Peptide Mapping / Q000379:methods*; D011506:Proteins / Q000737:chemistry*; D020543:Proteome / Q000032:analysis*; D015203:Reproducibility of Results; D012371:Robotics / Q000379:methods*; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
D011506:Proteins; D020543:Proteome