A targeted proteomics toolkit for high-throughput absolute quantification of Escherichia coli proteins
Affiliation:
1. Lab of Biorefinery, Shanghai Advanced Research Institute, Chinese Academy of Sciences, No. 99 Haike Road, Pudong, Shanghai 201210, China;2. School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China;3. CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai 200031, China;4. University of Chinese Academy of Sciences, Beijing 100049, China;5. School of Food Science and Technology, Jiangnan University, Wuxi 214122, Jiangsu, China;1. Division of Medical Microbiology, Department of Pathology, University of Cape Town, South Africa;2. Division of Chemical & Systems Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa;3. Bacteriology Division, Centre for Enteric Diseases, National Institute for Communicable Diseases, Sandringham, Johannesburg, South Africa;4. Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa;5. Institute of Infectious Disease and Molecular Medicine (IDM), University of Cape Town, South Africa;6. MRC/NHLS/UCT Molecular Mycobacteriology Research Unit, DST/NRF Centre of Excellence for Biomedical TB Research, Division of Medical Microbiology, Department of Pathology, University of Cape Town, South Africa
Abstract:
Transformation of engineered Escherichia coli into a robust microbial factory is contingent on precise control of metabolism. Yet, the throughput of omics technologies used to characterize cell components has lagged far behind our ability to engineer novel strains. To expand the utility of quantitative proteomics for metabolic engineering, we validated and optimized targeted proteomics methods for over 400 proteins from more than 20 major pathways in E. coli metabolism. Complementing these methods, we constructed a series of synthetic genes to produce concatenated peptides (QconCAT) for absolute quantification of the proteins and made them available through the Addgene plasmid repository (www.addgene.org). To facilitate high sample throughput, we developed a fast, analytical-flow chromatography method using a 5.5-min gradient (10 min total run time). Overall this toolkit provides an invaluable resource for metabolic engineering by increasing sample throughput, minimizing development time and providing peptide standards for absolute quantification of E. coli proteins.