Dataset Information

Gene expression analysis of E. coli strains provides insights into the role of gene regulation in diversification

ABSTRACT: Escherichia coli spans a genetic continuum from enteric strains to several phylogenetically distinct, atypical lineages that are rare in humans, but more common in extra-intestinal environments. To investigate the link between gene regulation, phylogeny and diversification in this species, we analyzed global gene expression profiles of four strains representing distinct evolutionary lineages, including a well-studied laboratory strain, a typical commensal (enteric) strain and two environmental strains. RNA-Seq was employed to compare the whole transcriptomes of strains grown under batch, chemostat and starvation conditions. Highly differentially expressed genes showed a significantly lower nucleotide sequence identity compared with other genes, indicating that gene regulation and coding sequence conservation are directly connected. Overall, distances between the strains based on gene expression profiles were largely dependent on the culture condition and did not reflect phylogenetic relatedness. Expression differences of commonly shared genes (all four strains) and E. coli core genes were consistently smaller between strains characterized by more similar primary habitats. For instance, environmental strains exhibited increased expression of stress defense genes under carbon-limited growth and entered a more pronounced survival-like phenotype during starvation compared with other strains, which stayed more alert for substrate scavenging and catabolism during no-growth conditions. Since those environmental strains show similar genetic distance to each other and to the other two strains, these findings cannot be simply attributed to genetic relatedness but suggest physiological adaptations. Our study provides new insights into ecologically relevant gene-expression and underscores the role of (differential) gene regulation for the diversification of the model bacterial species.

ORGANISM(S): Escherichia coli

PROVIDER: GSE77325 | GEO | 2016/02/06

SECONDARY ACCESSION(S): PRJNA310115

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Escherichia coliÂ spans a genetic continuum from enteric strains to several phylogenetically distinct, atypical lineages that are rare in humans, but more common in extra-intestinal environments. To investigate the link between gene regulation, phylogeny and diversification in this species, we analyzed global gene expression profiles of four strains representing distinct evolutionary lineages, including a well-studied laboratory strain, a typical commensal (enteric) strain and two environmental strains. RNA-Seq was employed to compare the whole transcriptomes of strains grown under batch, chemostat and starvation conditions. Highly differentially expressed genes showed a significantly lower nucleotide sequence identity compared with other genes, indicating that gene regulation and coding sequence conservation are directly connected. Overall, distances between the strains based on gene expression profiles were largely dependent on the culture condition and did not reflect phylogenetic relatedness. Expression differences of commonly shared genes (all four strains) andÂ E. coliÂ core genes were consistently smaller between strains characterized by more similar primary habitats. For instance, environmental strains exhibited increased expression of stress defense genes under carbon-limited growth and entered a more pronounced survival-like phenotype during starvation compared with other strains, which stayed more alert for substrate scavenging and catabolism during no-growth conditions. Since those environmental strains show similar genetic distance to each other and to the other two strains, these findings cannot be simply attributed to genetic relatedness but suggest physiological adaptations. Our study provides new insights into ecologically relevant gene-expression and underscores the role of (differential) gene regulation for the diversification of the model bacterial species. Four E.coli strains, laboratory strain K12 (MG1655), a commensal model strain (IAI1), a soil-isolated strain (TW11588-Clade IV), and a freshwater-isolated strain (TW09308âClade V) were used. Each strain was grown on a minimal growth medium (Ihssen and Egli, 2004) in three treatment modes: chemostat, batch, and starvation. Cells from batch culture were collected when reaching steady-state. For starvation, the medium flow was stopped during steady-state and bacteria were collected after 4âh.

Project description:<p>The study of antimicrobial resistance (AMR) in infectious diarrhea has generally been limited to cultivation, antimicrobial susceptibility testing and targeted PCR assays. When individual strains of significance are identified, whole genome shotgun (WGS) sequencing of important clones and clades is performed. Genes that encode resistance to antibiotics have been detected in environmental, insect, human and animal metagenomes and are known as "resistomes". While metagenomic datasets have been mined to characterize the healthy human gut resistome in the Human Microbiome Project and MetaHIT and in a Yanomani Amerindian cohort, directed metagenomic sequencing has not been used to examine the epidemiology of AMR. Especially in developing countries where sanitation is poor, diarrhea and enteric pathogens likely serve to disseminate antibiotic resistance elements of clinical significance. Unregulated use of antibiotics further exacerbates the problem by selection for acquisition of resistance. This is exemplified by recent reports of multiple antibiotic resistance in Shigella strains in India, in Escherichia coli in India and Pakistan, and in nontyphoidal Salmonella (NTS) in South-East Asia. We propose to use deep metagenomic sequencing and genome level assembly to study the epidemiology of AMR in stools of children suffering from diarrhea. Here the epidemiology component will be surveillance and analysis of the microbial composition (to the bacterial species/strain level where possible) and its constituent antimicrobial resistance genetic elements (such as plasmids, integrons, transposons and other mobile genetic elements, or MGEs) in samples from a cohort where diarrhea is prevalent and antibiotic exposure is endemic. The goal will be to assess whether consortia of specific mobile antimicrobial resistance elements associate with species/strains and whether their presence is enhanced or amplified in diarrheal microbiomes and in the presence of antibiotic exposure. This work could potentially identify clonal complexes of organisms and MGEs with enhanced resistance and the potential to transfer this resistance to other enteric pathogens.</p> <p>We have performed WGS, metagenomic assembly and gene/protein mapping to examine and characterize the types of AMR genes and transfer elements (transposons, integrons, bacteriophage, plasmids) and their distribution in bacterial species and strains assembled from DNA isolated from diarrheal and non-diarrheal stools. The samples were acquired from a cohort of pediatric patients and controls from Colombia, South America where antibiotic use is prevalent. As a control, the distribution and abundance of AMR genes can be compared to published studies where resistome gene lists from healthy cohort sequences were compiled. Our approach is more epidemiologic in nature, as we plan to identify and catalogue antimicrobial elements on MGEs capable of spread through a local population and further we will, where possible, link mobile antimicrobial resistance elements with specific strains within the population.</p>

Project description:It is widely believed that, owing to the limitation of nutrients in natural environments, bacteria spend most of their life in a non-growing state. However, despite its major clinical and ecological implications, very little is known about what determines the phenotype of starved bacteria, in particular what controls the concentration of different gene products inside the cells. Using microfluidics and quantitative fluorescence microscopy, we monitored growth and gene expression in many independent E. coli lineages as we switched them from exponential growth to starvation. We observed that all cells stopped growing immediately and that no cell death occurred for more than two days. At the same time, gene expression undergoes a dramatic remodeling upon entry into starvation in a promoter-dependent manner. Some promoters, including ribosomal protein promoters, arrest gene expression immediately, others show a slow exponential decay of expression on a 10 h time scale, while a third category exhibits a transient burst of activity before decaying exponentially. Remarkably, the time dynamics of these changes are highly homogeneous across single cells. In addition, we demonstrated that the gene expression response does not qualitatively depend on the dynamics of starvation entry. Combining the observed time-dependent protein production and decay rates, we showed with mathematical modeling that a delay between growth arrest and shutdown of gene expression allows a massive increase in the concentration of certain proteins without requiring an upregulation of their expression. Moreover, protein concentrations deep in starvation appeared to be mainly determined by the expression dynamics during the first 10 h of starvation. Finally, we established that this expression program at the onset of starvation is critical for cell viability. In particular, by inhibiting gene expression during different periods of starvation, we were able to show that the tolerance to stress after 2 days is determined by gene expression occurring during the first 10 h, which thus constitutes a preventive response. These results provide a starting point for quantitative studies of cell maintenance and the emergence of specific phenotypes when nutrients become scarce.

Dataset Information

Gene expression analysis of E. coli strains provides insights into the role of gene regulation in diversification

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets