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Comparative analyses of the variation of the transcriptome and proteome of Rhodobacter sphaeroides throughout growth.

ABSTRACT: BACKGROUND:In natural environments, bacteria must frequently cope with extremely scarce nutrients. Most studies focus on bacterial growth in nutrient replete conditions, while less is known about the stationary phase. Here, we are interested in global gene expression throughout all growth phases, including the adjustment to deep stationary phase. RESULTS:We monitored both the transcriptome and the proteome in cultures of the alphaproteobacterium Rhodobacter sphaeroides, beginning with the transition to stationary phase and at different points of the stationary phase and finally during exit from stationary phase (outgrowth) following dilution with fresh medium. Correlation between the transcriptomic and proteomic changes was very low throughout the growth phases. Surprisingly, even in deep stationary phase, the abundance of many proteins continued to adjust, while the transcriptome analysis revealed fewer adjustments. This pattern was reversed during the first 90?min of outgrowth, although this depended upon the duration of the stationary phase. We provide a detailed analysis of proteomic changes based on the clustering of orthologous groups (COGs), and compare these with the transcriptome. CONCLUSIONS:The low correlation between transcriptome and proteome supports the view that post-transcriptional processes play a major role in the adaptation to growth conditions. Our data revealed that many proteins with functions in transcription, energy production and conversion and the metabolism and transport of amino acids, carbohydrates, lipids, and secondary metabolites continually increased in deep stationary phase. Based on these findings, we conclude that the bacterium responds to sudden changes in environmental conditions by a radical and rapid reprogramming of the transcriptome in the first 90?min, while the proteome changes were modest. In response to gradually deteriorating conditions, however, the transcriptome remains mostly at a steady state while the bacterium continues to adjust its proteome. Even long after the population has entered stationary phase, cells are still actively adjusting their proteomes.

SUBMITTER: Bathke J

PROVIDER: S-EPMC6509803 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Comparative analyses of the variation of the transcriptome and proteome of Rhodobacter sphaeroides throughout growth.

Bathke Jochen J Konzer Anne A Remes Bernhard B McIntosh Matthew M Klug Gabriele G

BMC genomics 20190509 1

<h4>Background</h4>In natural environments, bacteria must frequently cope with extremely scarce nutrients. Most studies focus on bacterial growth in nutrient replete conditions, while less is known about the stationary phase. Here, we are interested in global gene expression throughout all growth phases, including the adjustment to deep stationary phase.<h4>Results</h4>We monitored both the transcriptome and the proteome in cultures of the alphaproteobacterium Rhodobacter sphaeroides, beginning ...[more]

PMID: 31072330

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Project description:BackgroundMicrobial cell factories are usually engineered and employed for cultivations that combine product synthesis with growth. Such a strategy inevitably invests part of the substrate pool towards the generation of biomass and cellular maintenance. Hence, engineering strains for the formation of a specific product under non-growth conditions would allow to reach higher product yields. In this respect, isoprenoid biosynthesis represents an extensively studied example of growth-coupled synthesis with rather unexplored potential for growth-independent production. Rhodobacter sphaeroides is a model bacterium for isoprenoid biosynthesis, either via the native 2-methyl-d-erythritol 4-phosphate (MEP) pathway or the heterologous mevalonate (MVA) pathway, and for poly-β-hydroxybutyrate (PHB) biosynthesis.ResultsThis study investigates the use of this bacterium for growth-independent production of isoprenoids, with amorpha-4,11-diene as reporter molecule. For this purpose, we employed the recently developed Cas9-based genome editing tool for R. sphaeroides to rapidly construct single and double deletion mutant strains of the MEP and PHB pathways, and we subsequently transformed the strains with the amorphadiene producing plasmid. Furthermore, we employed 13C-metabolic flux ratio analysis to monitor the changes in the isoprenoid metabolic fluxes under different cultivation conditions. We demonstrated that active flux via both isoprenoid pathways while inactivating PHB synthesis maximizes growth-coupled isoprenoid synthesis. On the other hand, the strain that showed the highest growth-independent isoprenoid yield and productivity, combined the plasmid-based heterologous expression of the orthogonal MVA pathway with the inactivation of the native MEP and PHB production pathways.ConclusionsApart from proposing a microbial cell factory for growth-independent isoprenoid synthesis, this work provides novel insights about the interaction of MEP and MVA pathways under different growth conditions.

Project description:The relationships between the levels of transcripts and the levels of the proteins they encode have not been examined comprehensively in mammals, although previous work in plants and yeast suggest a surprisingly modest correlation. We have examined this issue using a genetic approach in which natural variations were used to perturb both transcript levels and protein levels among inbred strains of mice. We quantified over 5,000 peptides and over 22,000 transcripts in livers of 97 inbred and recombinant inbred strains and focused on the 7,185 most heritable transcripts and 486 most reliable proteins. The transcript levels were quantified by microarray analysis in three replicates and the proteins were quantified by Liquid Chromatography-Mass Spectrometry using O(18)-reference-based isotope labeling approach. We show that the levels of transcripts and proteins correlate significantly for only about half of the genes tested, with an average correlation of 0.27, and the correlations of transcripts and proteins varied depending on the cellular location and biological function of the gene. We examined technical and biological factors that could contribute to the modest correlation. For example, differential splicing clearly affects the analyses for certain genes; but, based on deep sequencing, this does not substantially contribute to the overall estimate of the correlation. We also employed genome-wide association analyses to map loci controlling both transcript and protein levels. Surprisingly, little overlap was observed between the protein- and transcript-mapped loci. We have typed numerous clinically relevant traits among the strains, including adiposity, lipoprotein levels, and tissue parameters. Using correlation analysis, we found that a low number of clinical trait relationships are preserved between the protein and mRNA gene products and that the majority of such relationships are specific to either the protein levels or transcript levels. Surprisingly, transcript levels were more strongly correlated with clinical traits than protein levels. In light of the widespread use of high-throughput technologies in both clinical and basic research, the results presented have practical as well as basic implications.

Project description:BackgroundThe genus Rhodobacter contains purple nonsulfur bacteria found mostly in freshwater environments. Representative strains of two Rhodobacter species, R. capsulatus and R. sphaeroides, have had their genomes fully sequenced and both have been the subject of transcriptional profiling studies. Gene co-expression networks can be used to identify modules of genes with similar expression profiles. Functional analysis of gene modules can then associate co-expressed genes with biological pathways, and network statistics can determine the degree of module preservation in related networks. In this paper, we constructed an R. capsulatus gene co-expression network, performed functional analysis of identified gene modules, and investigated preservation of these modules in R. capsulatus proteomics data and in R. sphaeroides transcriptomics data.ResultsThe analysis identified 40 gene co-expression modules in R. capsulatus. Investigation of the module gene contents and expression profiles revealed patterns that were validated based on previous studies supporting the biological relevance of these modules. We identified two R. capsulatus gene modules preserved in the protein abundance data. We also identified several gene modules preserved between both Rhodobacter species, which indicate that these cellular processes are conserved between the species and are candidates for functional information transfer between species. Many gene modules were non-preserved, providing insight into processes that differentiate the two species. In addition, using Local Network Similarity (LNS), a recently proposed metric for expression divergence, we assessed the expression conservation of between-species pairs of orthologs, and within-species gene-protein expression profiles.ConclusionsOur analyses provide new sources of information for functional annotation in R. capsulatus because uncharacterized genes in modules are now connected with groups of genes that constitute a joint functional annotation. We identified R. capsulatus modules enriched with genes for ribosomal proteins, porphyrin and bacteriochlorophyll anabolism, and biosynthesis of secondary metabolites to be preserved in R. sphaeroides whereas modules related to RcGTA production and signalling showed lack of preservation in R. sphaeroides. In addition, we demonstrated that network statistics may also be applied within-species to identify congruence between mRNA expression and protein abundance data for which simple correlation measurements have previously had mixed results.

Dataset Information

Comparative analyses of the variation of the transcriptome and proteome of Rhodobacter sphaeroides throughout growth.

Publications

Comparative analyses of the variation of the transcriptome and proteome of Rhodobacter sphaeroides throughout growth.

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