Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Mode of action characterization of antibiotics using expression profile fingerprints generated by RNA-sequencing technology

ABSTRACT: RNA-seq based transcriptome profiling allows a detailed molecular analysis of the E.coli transcriptome (~4200 genes) after perturbation with different antibiotics. Transcriptome fingerprints enable the identification of gene and pathway level responses to treatment to derive a mechanistic understanding of antibiotics mode of action and to differentiate antibiotics. For this goal, treatment has to be performed in a short time period and with sublethal concentrations of the antibiotics. Sublethal concentrations were chosen based on the EC90 concentration of the antibiotic necessary to change the cellular morphology compared to control conditions. Conclusions: Our study represents the first detailed analysis of E.coli transcriptomes after treatment with different antibiotics, with biologic replicates, generated by RNA-seq technology. The experimental design and data analysis reported here should provide a framework for comparative investigations of expression profiles of known and novel antibiotics. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

ORGANISM(S): Escherichia coli BW25113

PROVIDER: GSE110137 | GEO | 2019/03/25

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Next Generation Sequencing Facilitates Quantitative Analysis of E.coli, Wild Type and ΔrecA Transcriptomes

Project description:Purpose:Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived E.coli transcriptome profiling (RNA-seq) of Wild type and ΔrecA with or without antibiotics treatment. Methods:libraries with different indices were multiplexed and loaded on an Illumina HiSeq instrument, Sequencing was carried out using a 2x150bp paired-end (PE) configuration, image analysis and base calling were conducted by the HiSeq Control Software (HCS) + OLB + GAPipeline-1.6 (Illumina) on the HiSeq instrument. Main data analysis include Quality Control(Cutadapt), Mapping(Bowtie2 (v2.2.6)),Expression analysis(HTSeq (v0.6.1p1)), Differential expression analysis (DESeq2 Bioconductor package). Results:Using an optimized data analysis workflow, we mapped about 20 million sequence reads per sample to the E.coli genome, The treatment of ampicillin affected the transcriptomic profile of either in the wild type or the ΔrecA strain, compared with that of untreated control cells, with changes to the expression of 4373 and 4286 coding sequences, respectively. Analysis of only the genes with a log2 fold change (log2FC) of ≥ ± 2 showed that 161 and 248 genes were differentially expressed in the ampicillin-treated wild type and ΔrecA strains, respectively. Conclusions:Our study represents the detailed analysis of E.coli transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

2021-07-06 | GSE179434 | GEO

Sublethal concentrations of antibiotics cause shift to anaerobic metabolism in Listeria monocytogenes and induce phenotypes linked to antibiotic tolerance

Project description:The human pathogenic bacterium Listeria monocytogenes was exposed to antibiotics both during clinical treatment and as a saprophyte. As one of the keys to successful treatment is continued antibiotic sensitivity, the purpose of this study was to determine if exposure to sublethal antibiotic concentrations would affect the bacterial physiology and potentially induce tolerance to antibiotics. Transcriptomic analyses demonstrated that each of four antibiotics caused a compound-specific gene expression pattern related to (the) mode-of-action of the particular antibiotic. All four antibiotics caused the same changes in expression of several metabolic genes indicating a shift from aerobic to anaerobic metabolism driven by the induction of lmo1634 and the repression of alsA and lmo1992. This shift in metabolism could be a survival strategy in response to antibiotics and is further supported by the observation that a Îlmo1634 mutant was more sensitive to bactericidal antibiotics. The monocin locus encoding a cryptic prophage was induced by co-trimoxazole and repressed by ampicillin and gentamicin. This expression pattern correlated with the observed antibiotic-dependent biofilm formation, indicating a role of monocin in antibiotic-induced biofilm formation and a ÎlmaDCBA mutant confirmed this correlation. Thus, sublethal concentrations of antibiotics caused metabolic and physiological changes indicating that the organism is preparing to withstand lethal concentrations of antibiotics. Investigation of mRNA and sRNA expression profiles of L. monocytogenes EGD cells exposed to sublethal concentrations of four different antibiotics i.e. ampicillin, tetracycline, gentamicin and co-trimoxazole for 3h.

2016-06-01 | E-GEOD-65558 | biostudies-arrayexpress

Sublethal concentrations of antibiotics cause shift to anaerobic metabolism in Listeria monocytogenes and induce phenotypes linked to antibiotic tolerance

Project description:The human pathogenic bacterium Listeria monocytogenes was exposed to antibiotics both during clinical treatment and as a saprophyte. As one of the keys to successful treatment is continued antibiotic sensitivity, the purpose of this study was to determine if exposure to sublethal antibiotic concentrations would affect the bacterial physiology and potentially induce tolerance to antibiotics. Transcriptomic analyses demonstrated that each of four antibiotics caused a compound-specific gene expression pattern related to (the) mode-of-action of the particular antibiotic. All four antibiotics caused the same changes in expression of several metabolic genes indicating a shift from aerobic to anaerobic metabolism driven by the induction of lmo1634 and the repression of alsA and lmo1992. This shift in metabolism could be a survival strategy in response to antibiotics and is further supported by the observation that a Δlmo1634 mutant was more sensitive to bactericidal antibiotics. The monocin locus encoding a cryptic prophage was induced by co-trimoxazole and repressed by ampicillin and gentamicin. This expression pattern correlated with the observed antibiotic-dependent biofilm formation, indicating a role of monocin in antibiotic-induced biofilm formation and a ΔlmaDCBA mutant confirmed this correlation. Thus, sublethal concentrations of antibiotics caused metabolic and physiological changes indicating that the organism is preparing to withstand lethal concentrations of antibiotics.

2016-06-01 | GSE65558 | GEO

Profile of mRNA transcriptomes of E. coli affected by antifungal agent ciclopirox

Project description:Purpose: The identification of genes and regulatory pathways involved in the susceptibility to ciclopirox activity Methods: mRNA profiles of ciclopirox treatment in wild-type strain using Illumina sequencing. Results: Using an optimized data analysis workflow, we mapped about 1 million sequence reads per sample to the E. coli K-12 genome and identified 4,290 transcripts in wild-type with our without sublethal concentration of ciclopirox (12.5 ug/mL). Overall, this is the first genome-wide level analysis of ciclopirox as an antibacterial against Gram-negative bacteria and shown that >13 pathways were affected by ciclopirox with the change of expression level of >10 genes. Data analysis with CLRNASeq showed some differently expressed transcripts by ciclopirox treatment. Conclusions: Our study represents the first detailed analysis of ciclopirox-affected transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

2020-02-05 | GSE110854 | GEO

RNAseq analysis of tissue and primary cell transcriptomes from wild type and Beclin 2 KO mice.

Project description:Our study represents the first detailed analysis of WT vs Beclin 2 KO cell/tissue transcriptomes, with biologic replicates, generated by RNA-seq technology. RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

2021-03-06 | GSE111539 | GEO

Sublethal Concentrations of Carbapenems Alter Cell Morphology and Genomic Expression of Klebsiella pneumoniae Biofilms

Project description:K. pneumoniae, a Gram-negative bacterium, is normally associated with pneumonia in patients with weakened immune systems. However, it is also a prevalent nosocomial infectious agent that can be found in infected surgical sites and combat wounds. Many of these clinical strains display multi-drug resistance. We have worked with a clinical strain of K. pneumoniae that was initially isolated from a wound of an injured soldier. This strain demonstrated resistance to many commonly used antibiotics, but sensitivity to carbapenems. This isolate was capable of forming biofilms in vitro, contributing to its increased antibiotic resistance and impaired clearance. We were interested in determining how sublethal concentrations of carbapenem treatment specifically affect K. pneumoniae biofilms both in morphology and genomic expression. Scanning electron microscopy showed striking morphological differences between untreated and treated biofilms, including rounding, blebbing, and dimpling of treated cells. Comparative transcriptome analysis using RNA sequencing technology identified a large number of open reading frames (ORFs) differentially regulated in response to carbapenem treatment at 2 and 24 hours. ORFs upregulated with carbapenem treatment included genes involved in resistance, antiporters, and autoinducers. ORFs downregulated included metal transporters, membrane biosynthesis proteins, and motility proteins. Quantitative real time PCR validated the general trend of some of these differentially regulated ORFs. Treating K. pneumoniae biofilms with sublethal concentrations of carbapenems induced a wide-range of phenotypic and gene expression changes. This study reveals some of the mechanisms underlying how sublethal amounts of carbapenems could affect the overall fitness and pathogenic potential of K. pneumoniae biofilm cells.

2015-01-01 | GSE62045 | GEO

Investigations of the effects of subMIC antibiotics on the P. aeruginosa transcriptome

Project description:Antibiotics in low concentrations may have an array of effects. We have exposed growing P. aeruginosa cells to different classes of antibiotics in order to investigate this hypothesis. We have used DNA microarrays to investigate the effect of low concentrations of antibiotics (azithromycin, ceftazidime and ciprofloxacin) on the gene expression of P. aeruginosa aiming to elucidate general trends. Keywords: Treatment with antibiotics

2008-02-28 | GSE8953 | GEO

Project description:E.coli antibiotics tolerance

| PRJNA602113 | ENA

Transcriptome responses to sublethal concentration of abamectin in Tetranychus truncatus analyzed by deep-sequencing

Project description:Purpose: In order to clarify the molecular response mechanism of Tetranychus truncatus to sublethal concentrations of abamectin. Methods: We sequenced the transcriptome of Tetranychus truncatus treated with sublethal concentration of abamectin and control. Results: we provide a comprehensive transcriptome resource for Tetranychus truncatus derived from treating with sublethal concentration abamectin and control. Conclusions: The new genomic resources and data that we present in this study for Tetranychus truncatus will substantially facilitate molecular studies of underlying mechanisms involved in abamectin resistance.

2021-12-16 | GSE115441 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of osteogenic differentiation treated with metformin

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to determine the differentially expressed genes of osteogenic differentiation after treatment with metformin by using NGS-derived transcriptome profiling (RNA-seq) Methods: Osteogenic mRNA profiles of MC3T3-E1 cells treated in osteogenic medium and in osteogenic medium with metformin, in triplicate, using Illumina instrument. Results: Using an optimized data analysis workflow, the data reveals 1946 up-regulated and 1544 down-regulated genes after metformin treatment. Conclusions: Our study represents the first detailed analysis of osteogenic transcriptomes after metformin treatment, with biologic replicates, generated by RNA-seq technology. We conclude that RNA-seq based transcriptome characterization would contribute the target prediction and drug discovery.

2022-03-11 | GSE198254 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data