Unified Workflow for the Rapid and In-Depth Characterization of Bacterial Proteomes

被引:14
作者
Abele, Miriam [1 ,2 ]
Doll, Etienne [3 ]
Bayer, Florian P. [2 ]
Lomp, Nina [1 ]
Meng, Chen
Neuhaus, Klaus [3 ,4 ]
Scherer, Siegfried [3 ]
Kuster, Bernhard [1 ,2 ]
Ludwig, Christina [1 ]
机构
[1] Tech Univ Munich, Bavarian Ctr Biomol Mass Spectrometry BayBioMS, Freising Weihenstephan, Germany
[2] Tech Univ Munich, Dept Prote & Bioanalyt, Freising Weihenstephan, Germany
[3] Tech Univ Munich, Dept Microbiol, Div Microbial Syst Ecol, D-85354 Freising Weihenstephan, Germany
[4] Tech Univ Munich, ZIEL Inst Food & Hlth, TUM Sch Life Sci, Core Facil Microbiome, Freising Weihenstephan, Germany
基金
欧盟地平线“2020”;
关键词
MASS-SPECTROMETRY; SAMPLE PREPARATION; IDENTIFICATION; EXTRACTION; PROTEINS; DIGESTION; PROTOCOL; ACID; DNA;
D O I
10.1016/j.mcpro.2023.100612
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Bacteria are the most abundant and diverse organisms among the kingdoms of life. Due to this excessive variance, finding a unified, comprehensive, and safe workflow for quantitative bacterial proteomics is challenging. In this study, we have systematically evaluated and optimized sample preparation, mass spectrometric data acquisition, and data analysis strategies in bacterial proteomics. We investigated workflow performances on six representative species with highly different physiologic properties to mimic bacterial diversity. The best sample preparation strategy was a cell lysis protocol in 100% trifluoroacetic acid followed by an in -solution digest. Peptides were separated on a 30 -min linear microflow liquid chromatography gradient and analyzed in data -independent acquisition mode. Data analysis was performed with DIA-NN using a predicted spectral library. Performance was evaluated according to the number of identified proteins, quantitative precision, throughput, costs, and biological safety. With this rapid workflow, over 40% of all encoded genes were detected per bacterial species. We demonstrated the general applicability of our workflow on a set of 23 taxonomically and physiologically diverse bacterial species. We could confidently identify over 45,000 proteins in the combined dataset, of which 30,000 have not been experimentally validated before. Our work thereby provides a valuable resource for the microbial scientific community. Finally, we grew Escherichia coli and Bacillus cereus in replicates under 12 different cultivation conditions to demonstrate the high -throughput suitability of the workflow. The proteomic workflow we present in this manuscript does not require any specialized equipment or commercial software and can be easily applied by other laboratories to support and accelerate the proteomic exploration of the bacterial kingdom.
引用
收藏
页数:17
相关论文
共 44 条
[1]   Comparison of three DNA extraction methods for Mycobacterium bovis, Mycobacterium tuberculosis and Mycobacterium avium subsp avium [J].
Amaro, A. ;
Duarte, E. ;
Amado, A. ;
Ferronha, H. ;
Botelho, A. .
LETTERS IN APPLIED MICROBIOLOGY, 2008, 47 (01) :8-11
[2]   Gene Ontology: tool for the unification of biology [J].
Ashburner, M ;
Ball, CA ;
Blake, JA ;
Botstein, D ;
Butler, H ;
Cherry, JM ;
Davis, AP ;
Dolinski, K ;
Dwight, SS ;
Eppig, JT ;
Harris, MA ;
Hill, DP ;
Issel-Tarver, L ;
Kasarskis, A ;
Lewis, S ;
Matese, JC ;
Richardson, JE ;
Ringwald, M ;
Rubin, GM ;
Sherlock, G .
NATURE GENETICS, 2000, 25 (01) :25-29
[3]   Principles of gene regulation quantitatively connect DNA to RNA and proteins in bacteria [J].
Balakrishnan, Rohan ;
Mori, Matteo ;
Segota, Igor ;
Zhang, Zhongge ;
Aebersold, Ruedi ;
Ludwig, Christina ;
Hwa, Terence .
SCIENCE, 2022, 378 (6624) :1066-+
[4]   UniProt: the universal protein knowledgebase in 2021 [J].
Bateman, Alex ;
Martin, Maria-Jesus ;
Orchard, Sandra ;
Magrane, Michele ;
Agivetova, Rahat ;
Ahmad, Shadab ;
Alpi, Emanuele ;
Bowler-Barnett, Emily H. ;
Britto, Ramona ;
Bursteinas, Borisas ;
Bye-A-Jee, Hema ;
Coetzee, Ray ;
Cukura, Austra ;
Da Silva, Alan ;
Denny, Paul ;
Dogan, Tunca ;
Ebenezer, ThankGod ;
Fan, Jun ;
Castro, Leyla Garcia ;
Garmiri, Penelope ;
Georghiou, George ;
Gonzales, Leonardo ;
Hatton-Ellis, Emma ;
Hussein, Abdulrahman ;
Ignatchenko, Alexandr ;
Insana, Giuseppe ;
Ishtiaq, Rizwan ;
Jokinen, Petteri ;
Joshi, Vishal ;
Jyothi, Dushyanth ;
Lock, Antonia ;
Lopez, Rodrigo ;
Luciani, Aurelien ;
Luo, Jie ;
Lussi, Yvonne ;
Mac-Dougall, Alistair ;
Madeira, Fabio ;
Mahmoudy, Mahdi ;
Menchi, Manuela ;
Mishra, Alok ;
Moulang, Katie ;
Nightingale, Andrew ;
Oliveira, Carla Susana ;
Pundir, Sangya ;
Qi, Guoying ;
Raj, Shriya ;
Rice, Daniel ;
Lopez, Milagros Rodriguez ;
Saidi, Rabie ;
Sampson, Joseph .
NUCLEIC ACIDS RESEARCH, 2021, 49 (D1) :D480-D489
[5]   The quantitative proteome of a human cell line [J].
Beck, Martin ;
Schmidt, Alexander ;
Malmstroem, Johan ;
Claassen, Manfred ;
Ori, Alessandro ;
Szymborska, Anna ;
Herzog, Franz ;
Rinner, Oliver ;
Ellenberg, Jan ;
Aebersold, Ruedi .
MOLECULAR SYSTEMS BIOLOGY, 2011, 7
[6]   Identification of 7 000-9 000 Proteins from Cell Lines and Tissues by Single-Shot Microflow LC-MS/MS [J].
Bian, Yangyang ;
The, Matthew ;
Giansanti, Piero ;
Mergner, Julia ;
Zheng, Runsheng ;
Wilhelm, Mathias ;
Boychenko, Alexander ;
Kuster, Bernhard .
ANALYTICAL CHEMISTRY, 2021, 93 (25) :8687-8692
[7]   Robust Microflow LC-MS/MS for Proteome Analysis: 38 000 Runs and Counting [J].
Bian, Yangyang ;
Bayer, Florian P. ;
Chang, Yun-Chien ;
Meng, Chen ;
Hoefer, Stefanie ;
Deng, Nan ;
Zheng, Runsheng ;
Boychenko, Oleksandr ;
Kuster, Bernhard .
ANALYTICAL CHEMISTRY, 2021, 93 (08) :3686-3690
[8]   Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC-MS/MS [J].
Bian, Yangyang ;
Zheng, Runsheng ;
Bayer, Florian P. ;
Wong, Cassandra ;
Chang, Yun-Chien ;
Meng, Chen ;
Zolg, Daniel P. ;
Reinecke, Maria ;
Zecha, Jana ;
Wiechmann, Svenja ;
Heinzlmeir, Stephanie ;
Scherr, Johannes ;
Hemmer, Bernhard ;
Baynham, Mike ;
Gingras, Anne-Claude ;
Boychenko, Oleksandr ;
Kuster, Bernhard .
NATURE COMMUNICATIONS, 2020, 11 (01)
[9]   Improving Proteome Coverage for Small Sample Amounts: An Advanced Method for Proteomics Approaches with Low Bacterial Cell Numbers [J].
Blankenburg, Sascha ;
Hentschker, Christian ;
Nagel, Anna ;
Hildebrandt, Petra ;
Michalik, Stephan ;
Dittmar, Denise ;
Surmann, Kristin ;
Voelker, Uwe .
PROTEOMICS, 2019, 19 (23)
[10]   The Gene Ontology resource: enriching a GOld mine [J].
Carbon, Seth ;
Douglass, Eric ;
Good, Benjamin M. ;
Unni, Deepak R. ;
Harris, Nomi L. ;
Mungall, Christopher J. ;
Basu, Siddartha ;
Chisholm, Rex L. ;
Dodson, Robert J. ;
Hartline, Eric ;
Fey, Petra ;
Thomas, Paul D. ;
Albou, Laurent-Philippe ;
Ebert, Dustin ;
Kesling, Michael J. ;
Mi, Huaiyu ;
Muruganujan, Anushya ;
Huang, Xiaosong ;
Mushayahama, Tremayne ;
LaBonte, Sandra A. ;
Siegele, Deborah A. ;
Antonazzo, Giulia ;
Attrill, Helen ;
Brown, Nick H. ;
Garapati, Phani ;
Marygold, Steven J. ;
Trovisco, Vitor ;
Dos Santos, Gil ;
Falls, Kathleen ;
Tabone, Christopher ;
Zhou, Pinglei ;
Goodman, Joshua L. ;
Strelets, Victor B. ;
Thurmond, Jim ;
Garmiri, Penelope ;
Ishtiaq, Rizwan ;
Rodriguez-Lopez, Milagros ;
Acencio, Marcio L. ;
Kuiper, Martin ;
Laegreid, Astrid ;
Logie, Colin ;
Lovering, Ruth C. ;
Kramarz, Barbara ;
Saverimuttu, Shirin C. C. ;
Pinheiro, Sandra M. ;
Gunn, Heather ;
Su, Renzhi ;
Thurlow, Katherine E. ;
Chibucos, Marcus ;
Giglio, Michelle .
NUCLEIC ACIDS RESEARCH, 2021, 49 (D1) :D325-D334