Dataset Information

Transcriptome RNA Sequencing Data Set of Differential Gene Expression in Escherichia coli BW25113 Wild-Type and slyA Mutant Strains.

ABSTRACT: Escherichia coli laboratory strains remain instrumental for the development of tools and techniques in molecular microbiology. The transcriptional regulator SlyA, associated with host-derived oxidative stress, antibiotic resistance, and virulence, is prominent in Enterobacteriaceae Here, we announce a transcriptome data set detailing the global gene expression in E. coli BW25113 and its slyA mutant.

SUBMITTER: Ojo O

PROVIDER: S-EPMC8142576 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundSeveral serious vegetable-associated outbreaks of enterohemorrhagic Escherichia coli (EHEC) infections have occurred during the last decades. In this context, vegetables have been suggested to function as secondary reservoirs for EHEC strains. Increased knowledge about the interaction of EHEC with plants including gene expression patterns in response to plant-derived compounds is required. In the current study, EHEC O157:H7 strain Sakai, EHEC O157:H- strain 3072/96, and the EHEC/enteroaggregative E. coli (EAEC) hybrid O104:H4 strain C227-11φcu were grown in lamb's lettuce medium and in M9 minimal medium to study the differential transcriptional response of these strains to plant-derived compounds with RNA-Seq technology.ResultsMany genes involved in carbohydrate degradation and peptide utilization were similarly upregulated in all three strains, suggesting that the lamb's lettuce medium provides sufficient nutrients for proliferation. In particular, the genes galET and rbsAC involved in galactose metabolism and D-ribose catabolism, respectively, were uniformly upregulated in the investigated strains. The most prominent differences in shared genome transcript levels were observed for genes involved in the expression of flagella. Transcripts of all three classes of the flagellar hierarchy were highly abundant in strain C227-11φcu. Strain Sakai expressed only genes encoding the basal flagellar structure. In addition, both strains showed increased motility in presence of lamb's lettuce extract. Moreover, strain 3072/96 showed increased transcription activity for genes encoding the type III secretion system (T3SS) including effectors, and was identified as a powerful biofilm-producer in M9 minimal medium.ConclusionThe current study provides clear evidence that EHEC and EHEC/EAEC strains are able to adjust their gene expression patterns towards metabolization of plant-derived compounds, demonstrating that they may proliferate well in a plant-associated environment. Moreover, we propose that flagella and other surface structures play a fundamental role in the interaction of EHEC and EHEC/EAEC with plants.

Project description:It is generally recognized that proteins constitute the key cellular component in shaping microbial phenotypes. Due to limited cellular resources and space, optimal allocation of proteins is crucial for microbes to facilitate maximum proliferation rates while allowing a flexible response to environmental changes. To account for the growth condition-dependent proteome in the constraint-based metabolic modeling of Escherichia coli, we consolidated a coarse-grained protein allocation approach with the explicit consideration of enzymatic constraints on reaction fluxes. Besides representing physiologically relevant wild-type phenotypes and flux distributions, the resulting protein allocation model (PAM) advances the predictability of the metabolic responses to genetic perturbations. A main driver of mutant phenotypes was ascribed to inherited regulation patterns in protein distribution among metabolic enzymes. Moreover, the PAM correctly reflected metabolic responses to an augmented protein burden imposed by the heterologous expression of green fluorescent protein. In summary, we were able to model the effects of important and frequently applied metabolic engineering approaches on microbial metabolism. Therefore, we want to promote the integration of protein allocation constraints into classical constraint-based models to foster their predictive capabilities and application for strain analysis and engineering purposes.IMPORTANCE Predictive metabolic models are important, e.g., for generating biological knowledge and designing microbes with superior performance for target compound production. Yet today's whole-cell models either show insufficient predictive capabilities or are computationally too expensive to be applied to metabolic engineering purposes. By linking the inherent genotype-phenotype relationship to a complete representation of the proteome, the PAM advances the accuracy of simulated phenotypes and intracellular flux distributions of E. coli Being equally computationally lightweight as classical stoichiometric models and allowing for the application of established in silico tools, the PAM and related simulation approaches will foster the use of a model-driven metabolic research. Applications range from the investigation of mechanisms of microbial evolution to the determination of optimal strain design strategies in metabolic engineering, thus supporting basic scientists and engineers alike.

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Transcriptome RNA Sequencing Data Set of Differential Gene Expression in Escherichia coli BW25113 Wild-Type and slyA Mutant Strains.

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