Multiscale dissection of bacterial proteome optimization

The quantitative composition of proteomes results from biophysical and biochemical selective pressures acting under system-level resource allocation constraints. The nature and strength of these evolutionary driving forces remain obscure. Through the development of analytical tools and precision measurement platforms spanning biological scales, we found evidence of optimization in bacterial gene expression programs. We compared protein synthesis rates across distant lineages and found tight conservation of in-pathway enzyme expression stoichiometry, suggesting generic selective pressures on expression setpoints. Beyond conservation, we used high-resolution transcriptomics to identify numerous examples of stoichiometry preserving cis-elements compensation in pathway operons. Genome-wide mapping of transcription termination sites also led to the discovery of a phylogenetically widespread mode of bacterial gene expression, 'runaway transcription', whereby RNA polymerases are functionally uncoupled from pioneering ribosomes on mRNAs. To delineate biophysical rationales underlying these pressures, we formulated a parsimonious ribosome allocation model capturing the trade-off between reaction flux and protein production cost. The model correctly predicts the expression hierarchy of key translation factors. We then directly measured the quantitative relationship between expression and fitness for specific translation factors in the Gram-positive species Bacillus subtilis. These precision measurements confirmed that endogenous expression maximizes growth rate. Idiosyncratic transcriptional changes in regulons were however observed away from endogenous expression. The resulting physiological burdens sharpened the fitness landscapes. Spurious system-level responses to targeted expression perturbations, called 'regulatory entrenchment', thus exacerbate the requirement for precisely set expression stoichiometry.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Physics

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2020

Author dc:creator

• Lalanne, Jean-Benoît.

Advisor dc:contributor.advisor

• Gene-Wei Li and Jeff Gore.

• Physics.

Statement dc:rights

• MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/130217

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/130217