The use of the multidimensional protein identification technology (MudPIT) to analyze plasma proteome of astronauts collected before, during, and after spaceflights

Author(s):  
D. Martin ◽  
G. Makedonas ◽  
B. Crucian ◽  
T. Peanlikhit ◽  
K. Rithidech
2020 ◽  
Vol 31 (7) ◽  
pp. 1440-1447
Author(s):  
Nan Zhang ◽  
Xiaojing Liu ◽  
Shuaixin Gao ◽  
Catherine Chiulan Wong

PROTEOMICS ◽  
2006 ◽  
Vol 6 (1) ◽  
pp. 301-311 ◽  
Author(s):  
Emmanuelle M. Bayer ◽  
Andrew R. Bottrill ◽  
John Walshaw ◽  
Marielle Vigouroux ◽  
Mike J. Naldrett ◽  
...  

2002 ◽  
Vol 74 (7) ◽  
pp. 1650-1657 ◽  
Author(s):  
Michael P. Washburn ◽  
Ryan Ulaszek ◽  
Cosmin Deciu ◽  
David M. Schieltz ◽  
John R. Yates

2008 ◽  
Vol 75 (2) ◽  
pp. 366-373 ◽  
Author(s):  
Janet R. Donaldson ◽  
Bindu Nanduri ◽  
Shane C. Burgess ◽  
Mark L. Lawrence

ABSTRACT Listeria monocytogenes is a gram-positive, food-borne pathogen that causes disease in both humans and animals. There are three major genetic lineages of L. monocytogenes and 13 serovars. To further our understanding of the differences that exist between different genetic lineages/serovars of L. monocytogenes, we analyzed the global protein expression of the serotype 1/2a strain EGD and the serotype 4b strain F2365 during early-stationary-phase growth at 37°C. Using multidimensional protein identification technology with electrospray ionization tandem mass spectrometry, we identified 1,754 proteins from EGD and 1,427 proteins from F2365, of which 1,077 were common to both. Analysis of proteins that had significantly altered expression between strains revealed potential biological differences between these two L. monocytogenes strains. In particular, the strains differed in expression of proteins involved in cell wall physiology and flagellar biosynthesis, as well as DNA repair proteins and stress response proteins.


2006 ◽  
Vol 1111 (2) ◽  
pp. 175-191 ◽  
Author(s):  
Qinhua Cindy Ru ◽  
Luwang Andy Zhu ◽  
Richard A. Katenhusen ◽  
Jordan Silberman ◽  
Henry Brzeski ◽  
...  

2021 ◽  
Author(s):  
Andrea Fossati ◽  
Alicia L. Richards ◽  
Kuei-Ho Chen ◽  
Devan Jaganath ◽  
Adithya Cattamanchi ◽  
...  

AbstractRapid and consistent protein identification across large clinical cohorts is an important goal for clinical proteomics. With the development of data-independent technologies (DIA/SWATH-MS), it is now possible to analyze hundreds of samples with great reproducibility and quantitative accuracy. However, this technology benefits from empirically derived spectral libraries that define the detectable set of peptides and proteins. Here we apply a simple and accessible tip-based workflow for the generation of spectral libraries to provide a comprehensive overview on the plasma proteome in individuals with and without active tuberculosis (TB). To boost protein coverage, we utilized non-conventional proteases such as GluC and AspN together with the gold standard trypsin, identifying more than 30,000 peptides mapping to 3,309 proteins. Application of this library to quantify plasma proteome differences in TB infection recovered more than 400 proteins in 50 minutes of MS-acquisition, including diagnostic Mycobacterium tuberculosis (Mtb) proteins that have previously been detectable primarily by antibody-based assays and intracellular proteins not previously described to be in plasma.


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