High-Throughput Large-Scale Targeted Proteomics Assays for Quantifying Pathway Proteins in Pseudomonas putida KT2440

Author:

Gao Yuqian,Fillmore Thomas L.,Munoz Nathalie,Bentley Gayle J.,Johnson Christopher W.,Kim Joonhoon,Meadows Jamie A.,Zucker Jeremy D.,Burnet Meagan C.,Lipton Anna K.,Bilbao Aivett,Orton Daniel J.,Kim Young-Mo,Moore Ronald J.,Robinson Errol W.,Baker Scott E.,Webb-Robertson Bobbie-Jo M.,Guss Adam M.,Gladden John M.,Beckham Gregg T.,Magnuson Jon K.,Burnum-Johnson Kristin E.

Abstract

Targeted proteomics is a mass spectrometry-based protein quantification technique with high sensitivity, accuracy, and reproducibility. As a key component in the multi-omics toolbox of systems biology, targeted liquid chromatography-selected reaction monitoring (LC-SRM) measurements are critical for enzyme and pathway identification and design in metabolic engineering. To fulfill the increasing need for analyzing large sample sets with faster turnaround time in systems biology, high-throughput LC-SRM is greatly needed. Even though nanoflow LC-SRM has better sensitivity, it lacks the speed offered by microflow LC-SRM. Recent advancements in mass spectrometry instrumentation significantly enhance the scan speed and sensitivity of LC-SRM, thereby creating opportunities for applying the high speed of microflow LC-SRM without losing peptide multiplexing power or sacrificing sensitivity. Here, we studied the performance of microflow LC-SRM relative to nanoflow LC-SRM by monitoring 339 peptides representing 132 enzymes in Pseudomonas putida KT2440 grown on various carbon sources. The results from the two LC-SRM platforms are highly correlated. In addition, the response curve study of 248 peptides demonstrates that microflow LC-SRM has comparable sensitivity for the majority of detected peptides and better mass spectrometry signal and chromatography stability than nanoflow LC-SRM.

Funder

Bioenergy Technologies Office

Publisher

Frontiers Media SA

Subject

Biomedical Engineering,Histology,Bioengineering,Biotechnology

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