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Just How Fast Can Bacteria Grow? It Depends.

Proteomics Data Validate Bacterial Growth Model

Proteomics data from EMSL allowed scientists to map the abundance of 900 proteins identified in wild-type E. coli compared with E. coli that had been adapted for growth on either lactate or glycerol media.

Bacteria are among the fastest reproducing organisms in the world, doubling every four to twenty minutes. Some fast-growing bacteria such as pathogenic strains of E. coli can sicken and kill us; other fast-growing bacteria in a subsurface environment can be used to gobble up chemical contaminants, leaving clean soil behind. But whether bacteria are harmful or helpful, scientists need to be able to reliably predict how they will reproduce and grow in a particular environment.

Proteomic research at EMSL is helping validate a bacterial model and is providing insights into the key proteins and metabolic pathways that are essential for encouraging and discouraging bacterial growth in a changing environment.

Internationally renowned researcher Bernhard Palsson and other researchers from the University of California San Diego led a team of scientists from EMSL, the University of Heidelberg, and the German Cancer Research Center to study how E. coli bacteria changed and evolved from one environment to another in a laboratory setting. The team then compared proteomics, genomic, and metabolic data from the study with a computational model for bacterial growth.

One of the key pieces of information was data generated using EMSL’s unique high-throughput proteomics capability. Using high-performance liquid chromatography coupled to mass spectrometry, the team gathered data on how the bacteria changed their protein profile as they grew and reproduced in different mediums. The scientists found that the data and model were correlated to a surprising degree (over 98% in some cases), validating the model’s ability to predict the growth of E. coli bacteria under specific conditions. 

Scientific Impact: Being able to model the growth of E. coli will help scientists begin to develop reliable metabolic models for other more complex organisms. This work will also provide key insights into the best ways of integrating different complex datasets to more accurately predict how organisms respond to their environments at the molecular level. Watch a related video interview with EMSL's Kim Hixson, http://www.youtube.com/watch?v=JSf6sN_5frM&feature=related.

Societal Impact: Development of biological models will help scientists understand how organisms change their genetic make-up and gene and protein expression so that engineers can use better use biological organisms to improve our environment and health.

Reference:  Lewis, N.E., K.K. Hixson, T.M. Conrad, J.A. Lerman, P. Charusanti, A.D. Polpitiya, J.N. Adkins, G. Schramm, S.O. Purvine, D. Lopez-Ferrer, K.K. Weitz, R. Eils, R. König, R.D. Smith, and B.Ø. Palsson. “Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models.” Molecular Systems Biology 6:390; doi 10.1038/msb.2010.47.

Acknowledgement:  A portion of this work was performed at EMSL, a national user facility located at the Pacific Northwest National Laboratory, using capabilities developed under support from the National Institutes of Health National Center for Research Resources and the DOE Office of Biological and Environmental Research. The work was also funded in part by a Fulbright fellowship and grants from the National Science Foundation and National Institutes of Health.

Released: November 29, 2010