Bacterial Fitness Landscapes Stratify Based on Proteome Allocation Associated with Discrete Aero-types
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PROVIDER: PRJNA689602 | ENA |
REPOSITORIES: ENA
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Project description:The fitness landscape is a concept commonly used to describe evolution towards optimal phenotypes. It can be reduced to mechanistic detail using genome-scale models (GEMs) from systems biology. We use recently developed GEMs of Metabolism and protein Expression (ME-models) to study the distribution of Escherichia coli phenotypes on the rate-yield plane. We found that the measured phenotypes distribute non-uniformly to form a highly stratified fitness landscape. Systems analysis of ME-model simulations suggest that this stratification results from discrete ATP generation strategies. Accordingly, we define "aero-types", a phenotypic trait that characterizes how a balanced proteome can achieve a given growth rate by modulating 1) the relative utilization of oxidative phosphorylation, glycolysis, and fermentation pathways; and 2) the differential employment of electron-transport-chain enzymes. This global, quantitative, and mechanistic systems biology interpretation of fitness landscape formed upon proteome allocation offers a fundamental understanding of bacterial physiology and evolution dynamics.
2021-01-05 | GSE164236 | GEO
Project description: Not available
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Project description:Protein synthesis is costly and the proteome size is constrained. Using a genome-scale computational model of proteome allocation together with absolute proteomics data sets from many growth environments, we determine how these fundamental limitations constrain growth and fitness in Escherichia coli. First, we show that the observed variation in growth rates across environments is largely determined by the expression of protein not utilized for growth in a given environment. We then elucidate the overall transcriptional regulatory logic that underlies the expression of unused protein. We systematically classify the unused proteome into segments devoted to environmental readiness and stress resistance functions. While expression of these proteome segments incurs a fitness cost of decreased growth in a fixed environment, they provide fitness benefits in a changing environment. Thus, the systems biology of the prokaryotic proteome can be quantitatively understood based on resource allocation to growth, environmental readiness, and stress resistance functions.
2018-08-01 | GSE72020 | GEO
Project description:Bacteria regulate their cellular resource allocation to enable their fast growth-adaptation to a variety of environmental niches. We studied the ribosomal allocation, growth and expression profile of two sets of fast-growing mutants of Escherichia coli K-12 MG1655. Mutants with 3 copies of the stronger ribosomal RNA operons grew faster than the wild-type strain in minimal media and show similar phenotype to previously studied rpoB mutants. All of them displayed increased ribosomal content, a longer diauxic shift and a reduced activity of the aceBAK operon, indicative of repressed gluconeogenic pathways. Transcriptomic profiles of fast-growing mutants showed common downregulation of hedging functions and upregulated growth functions. Proteome allocation estimations showed an increase in the growth-related proteome for fast-growing strains, but not an increased cellular budget for recombinant protein production. These results show that two different regulatory perturbations (rRNA promoters or rpoB mutations) increasing ribosomal allocation optimize the proteome for growth with a concomitant fitness cost.
2022-02-21 | GSE180830 | GEO
Project description:Engineering resource allocation in biological systems is an ongoing challenge. Organisms allocate resources for ensuring survival, reducing the productivity of synthetic biology functions. Here we present a novel approach for engineering the resource allocation of Escherichia coli by rationally modifying its transcriptional regulatory network. Our method (ReProMin) identifies the minimal set of genetic interventions that maximises the savings in cell resources. To this end, we categorized Transcription Factors according to the essentiality of its targets and we used proteomic data to rank them. We designed the combinatorial removal of TFs that maximise the release of resources. Our resulting strain containing only three mutations, theoretically releasing 0.5% of its proteome, had higher proteome budget, increased production of an engineered metabolic pathway and showed that the regulatory interventions are highly specific. This approach shows that combining proteomic and regulatory data is an effective way of optimizing strains using conventional molecular methods.
2019-11-30 | GSE134335 | GEO
Project description:Regulatory perturbations of ribosome allocation in bacteria reshape the growth proteome with a trade-off in adaptation capacity
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Project description:Cells usually respond to changing growth conditions with a change in the specific growth rate (μ) and adjustment of their proteome to adapt and maintain metabolic efficiency. Description of the principles behind proteome resource allocation is thus important for understanding metabolic regulation in responce to changing specific growth rate. We analysed the allocation dynamics of Escherichia coli proteome resources into different metabolic processes in response to changing μ. E. coli was grown on minimal and defined rich media in steady state continuous cultures at different μ and characterised by absolute quantitative LC-MS/MS based proteomics. We detected slowly growing cells investing more proteome resources in energy generation and carbohydrate transport and metabolism whereas for achieving faster growth cells needed to devote most resources to translation and processes closely related to the protein synthesis pipeline. Furthermore, down-regulation of energy generation and carbohydrate metabolism proteins with faster growth displayed very similar expression dynamics with the global transcriptional regulator CRP (cyclic AMP receptor protein), pointing to a dominant protein resource allocating role for this protein. Our data also suggest that acetate overflow may be the result of global proteome resource optimisation as cells saved proteome resources by switching from fully respiratory to respiro-fermentative growth. The presented results give a quantitative overview how E. coli adjusts its proteome to achieve faster growthin response to perturbations in μ. Quantitative understanding of proteome resource allocation could contribute to the design of more efficient cell factories through proteome optimisation towards proteins related to target molecule synthesis.
2015-02-27 | PXD001594 | Pride
Project description:In recent years, more attention in systems biology has been given to the concept of protein constraints and the cell’s necessity to allocate its proteome between important processes. From this point of view, attempts to elucidate cellular maximum capacity of growth as a function of protein availability has been investigated. Elucidating the possibility of optimizing cell proliferation, by tailoring proteome allocation. To experimentally investigate this concept further we cultivated Saccharomyces cerevisiae in bioreactors with or without amino acid supplementation and performed proteomics to analyze global changes in proteome allocation, during anaerobic as well as aerobic growth on glucose. Analysis of proteomic data implies that proteome mass is mainly being re-allocated from amino acid biosynthetic processes into translation, in regard to absolute levels of change, accompanied by an increased growth rate during supplementation. Similar findings were obtained from both aerobic and anaerobic cultivations, and subsequently independent of the two examined metabolic states. Indicating the possibility of increasing growth rate through freeing up proteome mass and increasing proteome allocation towards translational machinery.
2020-08-05 | PXD018361 | Pride
Project description:A central aim of cell biology is to understand the strategy of gene expression in response to the environment. Here we study gene expression response to metabolic challenges in exponentially growing Escherichia coli using mass spectrometry. Despite enormous complexity in the details of the underlying regulatory network, we find that the proteome partitions into several coarse-grained sectors, with each sector’s total mass abundance exhibiting positive or negative linear relations with the growth rate. The growth-rate dependent components of the proteome fractions comprise about half of the proteome by mass, and their mutual dependencies can be characterized by a simple flux model involving only two effective parameters. The success and apparent generality of this model arises from tight coordination between proteome partition and metabolism, suggesting a principle for resource-allocation in proteome economy of the cell. This strategy of global gene regulation should serve as a basis for future studies on gene expression and constructing synthetic biological circuits. Coarse-graining may be an effective approach to derive predictive phenomenological models for other ‘omics’ studies.
2015-02-12 | PXD001467 | Pride
Project description:Identifying the signals that regulate the survival, lineage allocation and specification of pancreas progenitors will help elucidate the embryonic origins of pancreas dysfunction and provide important cues for the efficient conversion of pluripotent stem cells into fully functional β cells. Several transcription factors regulating the conversion of the early pancreatic progenitors into terminally differentiated cells have been identified but extracellular signals regulating pancreas development are less well understood. Using a combination of genetic approaches, organotypic cultures of embryonic pancreata and genomics we have found that sphingosine-1-phosphate signalling through plays a key role in this process. S1p signalling stabilizes the Hippo pathway effector YAP to promote progenitor survival, acinar and endocrine specification. Endocrine cell specification relies on Gai subunits revealing an unexpected dependence of lineage specification on selected intracellular signalling components. Independently of YAP stabilization, S1p signalling attenuates Notch levels, thus regulating lineage allocation. These findings identify S1p signalling as a key pathway coordinating cell survival, lineage allocation and specification during pancreas development.
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