scholarly journals The Escherichia coli transcriptome mostly consists of independently regulated modules

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Anand V. Sastry ◽  
Ye Gao ◽  
Richard Szubin ◽  
Ying Hefner ◽  
Sibei Xu ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Transcriptional Regulatory Network ◽  
Transcriptional Regulators ◽  
Specific Gene ◽  
E Coli ◽  
Gene Sets ◽  
Transcriptional Regulatory ◽  
Genetic Perturbations ◽  
Function Discovery ◽  
Multiple Strains

AbstractUnderlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome.

scholarly journals The Escherichia coli Transcriptome Mostly Consists of Independently Regulated Modules

2019 ◽  
Author(s):  
Anand V. Sastry ◽  
Ye Gao ◽  
Richard Szubin ◽  
Ying Hefner ◽  
Sibei Xu ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Transcriptional Regulatory Network ◽  
Transcriptional Regulators ◽  
Specific Gene ◽  
Gene Sets ◽  
Underlying Principle ◽  
Transcriptional Regulatory ◽  
Genetic Perturbations ◽  
Function Discovery ◽  
Multiple Strains

AbstractUnderlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we applied unsupervised learning to a compendium of high-quality Escherichia coli RNA-seq datasets to identify 70 statistically independent signals that modulate the expression of specific gene sets. We show that 50 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals was validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provided: (1) a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations, (2) a guide to gene and regulator function discovery, and (3) a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation forms an underlying principle that describes the composition of a model prokaryotic transcriptome.

scholarly journals Antibiotic tolerance is associated with a broad and complex transcriptional response in E. coli

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Heather S. Deter ◽  
Tahmina Hossain ◽  
Nicholas C. Butzin
Keyword(s):  
Transcriptional Regulatory Network ◽  
Transcriptional Response ◽  
Regulatory Proteins ◽  
Health Concern ◽  
Transcriptional Networks ◽  
Antibiotic Tolerance ◽  
Multiple Gene ◽  
E Coli ◽  
Transcriptional Regulatory ◽  
Antibiotic Efficacy

AbstractAntibiotic treatment kills a large portion of a population, while a small, tolerant subpopulation survives. Tolerant bacteria disrupt antibiotic efficacy and increase the likelihood that a population gains antibiotic resistance, a growing health concern. We examined how E. coli transcriptional networks changed in response to lethal ampicillin concentrations. We are the first to apply transcriptional regulatory network (TRN) analysis to antibiotic tolerance by leveraging existing knowledge and our transcriptional data. TRN analysis shows that gene expression changes specific to ampicillin treatment are likely caused by specific sigma and transcription factors typically regulated by proteolysis. These results demonstrate that to survive lethal concentration of ampicillin specific regulatory proteins change activity and cause a coordinated transcriptional response that leverages multiple gene systems.

scholarly journals In Vivo mRNA Profiling of Uropathogenic Escherichia coli from Diverse Phylogroups Reveals Common and Group-Specific Gene Expression Profiles

mBio ◽  
2014 ◽  
Vol 5 (4) ◽  
Author(s):  
Piotr Bielecki ◽  
Uthayakumar Muthukumarasamy ◽  
Denitsa Eckweiler ◽  
Agata Bielecka ◽  
Sarah Pohl ◽  
...  
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Specific Gene ◽  
Content Type ◽  
E Coli ◽  
Human Host ◽  
Tract Infections

ABSTRACTmRNA profiling of pathogens during the course of human infections gives detailed information on the expression levels of relevant genes that drive pathogenicity and adaptation and at the same time allows for the delineation of phylogenetic relatedness of pathogens that cause specific diseases. In this study, we used mRNA sequencing to acquire information on the expression ofEscherichia colipathogenicity genes during urinary tract infections (UTI) in humans and to assign the UTI-associatedE. coliisolates to different phylogenetic groups. Whereas thein vivogene expression profiles of the majority of genes were conserved among 21E. colistrains in the urine of elderly patients suffering from an acute UTI, the specific gene expression profiles of the flexible genomes was diverse and reflected phylogenetic relationships. Furthermore, genes transcribedin vivorelative to laboratory media included well-described virulence factors, small regulatory RNAs, as well as genes not previously linked to bacterial virulence. Knowledge on relevant transcriptional responses that drive pathogenicity and adaptation of isolates to the human host might lead to the introduction of a virulence typing strategy into clinical microbiology, potentially facilitating management and prevention of the disease.IMPORTANCEUrinary tract infections (UTI) are very common; at least half of all women experience UTI, most of which are caused by pathogenicEscherichia colistrains. In this study, we applied massive parallel cDNA sequencing (RNA-seq) to provide unbiased, deep, and accurate insight into the nature and the dimension of the uropathogenicE. coligene expression profile during an acute UTI within the human host. This work was undertaken to identify key players in physiological adaptation processes and, hence, potential targets for new infection prevention and therapy interventions specifically aimed at sabotaging bacterial adaptation to the human host.

Transcriptional regulatory network analysis of developing human erythroid progenitors reveals patterns of coregulation and potential transcriptional regulators

2006 ◽  
Vol 28 (1) ◽  
pp. 114-128 ◽  
Author(s):  
M. A. Keller ◽  
S. Addya ◽  
R. Vadigepalli ◽  
B. Banini ◽  
K. Delgrosso ◽  
...  
Keyword(s):  
Network Analysis ◽  
Blood Cell ◽  
Regulatory Network ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
Expression Patterns ◽  
Transcriptional Regulators ◽  
Erythroid Progenitors ◽  
Hematopoietic Stem ◽  
Transcriptional Regulatory

Deciphering the molecular basis for human erythropoiesis should yield information benefiting studies of the hemoglobinopathies and other erythroid disorders. We used an in vitro erythroid differentiation system to study the developing red blood cell transcriptome derived from adult CD34+ hematopoietic progenitor cells. mRNA expression profiling was used to characterize developing erythroid cells at six time points during differentiation ( days 1, 3, 5, 7, 9, and 11). Eleven thousand seven hundred sixty-three genes (20,963 Affymetrix probe sets) were expressed on day 1, and 1,504 genes, represented by 1,953 probe sets, were differentially expressed (DE) with 537 upregulated and 969 downregulated. A subset of the DE genes was validated using real-time RT-PCR. The DE probe sets were subjected to a cluster metric and could be divided into two, three, four, five, or six clusters of genes with different expression patterns in each cluster. Genes in these clusters were examined for shared transcription factor binding sites (TFBS) in their promoters by comparing enrichment of each TFBS relative to a reference set using transcriptional regulatory network analysis. The sets of TFBS enriched in genes up- and downregulated during erythropoiesis were distinct. This analysis identified transcriptional regulators critical to erythroid development, factors recently found to play a role, as well as a new list of potential candidates, including Evi-1, a potential silencer of genes upregulated during erythropoiesis. Thus this transcriptional regulatory network analysis has yielded a focused set of factors and their target genes whose role in differentiation of the hematopoietic stem cell into distinct blood cell lineages can be elucidated.

scholarly journals Machine learning uncovers independently regulated modules in the Bacillus subtilis transcriptome

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Kevin Rychel ◽  
Anand V. Sastry ◽  
Bernhard O. Palsson
Keyword(s):  
Machine Learning ◽  
Bacillus Subtilis ◽  
Biofilm Formation ◽  
Transcriptional Regulatory Network ◽  
Population Level ◽  
Cellular Functions ◽  
Fundamental Interest ◽  
Gene Sets ◽  
Transcriptional Regulatory ◽  
Dependent Activity

AbstractThe transcriptional regulatory network (TRN) of Bacillus subtilis coordinates cellular functions of fundamental interest, including metabolism, biofilm formation, and sporulation. Here, we use unsupervised machine learning to modularize the transcriptome and quantitatively describe regulatory activity under diverse conditions, creating an unbiased summary of gene expression. We obtain 83 independently modulated gene sets that explain most of the variance in expression and demonstrate that 76% of them represent the effects of known regulators. The TRN structure and its condition-dependent activity uncover putative or recently discovered roles for at least five regulons, such as a relationship between histidine utilization and quorum sensing. The TRN also facilitates quantification of population-level sporulation states. As this TRN covers the majority of the transcriptome and concisely characterizes the global expression state, it could inform research on nearly every aspect of transcriptional regulation in B. subtilis.

scholarly journals Draft Genome Sequence of Escherichia Phage PGN829.1, Active against Highly Drug-Resistant Uropathogenic Escherichia coli

2018 ◽  
Vol 7 (20) ◽  
Author(s):  
Naveen Chaudhary ◽  
Balvinder Mohan ◽  
Neelam Taneja
Keyword(s):  
Escherichia Coli ◽  
Genome Sequence ◽  
Tertiary Care ◽  
Draft Genome ◽  
Uropathogenic Escherichia Coli ◽  
North India ◽  
Drug Resistant ◽  
Content Type ◽  
E Coli ◽  
Multiple Strains

The Escherichia phage PGN829.1 was isolated from sewage of a tertiary care referral hospital in North India. It lyses multiple strains of highly drug-resistant uropathogenic E. coli.

scholarly journals Bacillus subtilis and Escherichia coli essential genes and minimal cell factories after one decade of genome engineering

Microbiology ◽  
2014 ◽  
Vol 160 (11) ◽  
pp. 2341-2351 ◽  
Author(s):  
Mario Juhas ◽  
Daniel R. Reuß ◽  
Bingyao Zhu ◽  
Fabian M. Commichau
Keyword(s):  
Escherichia Coli ◽  
Bacillus Subtilis ◽  
Essential Gene ◽  
Building Blocks ◽  
Essential Genes ◽  
Minimal Cell ◽  
E Coli ◽  
Cell Factories ◽  
Gene Sets ◽  
K 12

Investigation of essential genes, besides contributing to understanding the fundamental principles of life, has numerous practical applications. Essential genes can be exploited as building blocks of a tightly controlled cell ‘chassis’. Bacillus subtilis and Escherichia coli K-12 are both well-characterized model bacteria used as hosts for a plethora of biotechnological applications. Determination of the essential genes that constitute the B. subtilis and E. coli minimal genomes is therefore of the highest importance. Recent advances have led to the modification of the original B. subtilis and E. coli essential gene sets identified 10 years ago. Furthermore, significant progress has been made in the area of genome minimization of both model bacteria. This review provides an update, with particular emphasis on the current essential gene sets and their comparison with the original gene sets identified 10 years ago. Special attention is focused on the genome reduction analyses in B. subtilis and E. coli and the construction of minimal cell factories for industrial applications.

scholarly journals Bacterial Two-Hybrid Analysis of Interactions between Region 4 of the ς70 Subunit of RNA Polymerase and the Transcriptional Regulators Rsd from Escherichia coli and AlgQ from Pseudomonas aeruginosa

2001 ◽  
Vol 183 (21) ◽  
pp. 6413-6421 ◽  
Author(s):  
Simon L. Dove ◽  
Ann Hochschild
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Pseudomonas Aeruginosa ◽  
Amino Acid ◽  
Rna Polymerase ◽  
Amino Acid Substitution ◽  
Transcriptional Regulators ◽  
Binding Motif ◽  
E Coli ◽  
Two Hybrid

ABSTRACT A number of transcriptional regulators mediate their effects through direct contact with the ς70 subunit ofEscherichia coli RNA polymerase (RNAP). In particular, several regulators have been shown to contact a C-terminal portion of ς70 that harbors conserved region 4. This region of ς contains a putative helix-turn-helix DNA-binding motif that contacts the −35 element of ς70-dependent promoters directly. Here we report the use of a recently developed bacterial two-hybrid system to study the interaction between the putative anti-ς factor Rsd and the ς70 subunit of E. coli RNAP. Using this system, we found that Rsd can interact with an 86-amino-acid C-terminal fragment of ς70 and also that amino acid substitution R596H, within region 4 of ς70, weakens this interaction. We demonstrated the specificity of this effect by showing that substitution R596H does not weaken the interaction between ς and two other regulators shown previously to contact region 4 of ς70. We also demonstrated that AlgQ, a homolog of Rsd that positively regulates virulence gene expression inPseudomonas aeruginosa, can contact the C-terminal region of the ς70 subunit of RNAP from this organism. We found that amino acid substitution R600H in ς70 fromP. aeruginosa, corresponding to the R596H substitution in E. coli ς70, specifically weakens the interaction between AlgQ and ς70. Taken together, our findings suggest that Rsd and AlgQ contact similar surfaces of RNAP present in region 4 of ς70 and probably regulate gene expression through this contact.

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