Ontology highlight
ABSTRACT:
PROVIDER: PRJNA888038 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| SRR21875703_1.fastq.gz | Fastqsanger.gz | |||
| SRR21875703_2.fastq.gz | Fastqsanger.gz | |||
| SRR21875704_1.fastq.gz | Fastqsanger.gz | |||
| SRR21875704_2.fastq.gz | Fastqsanger.gz |
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Project description:Is there a universal genetically programmed defense providing tolerance to antibiotics when bacteria grow as biofilms? A comparison between biofilms of three different bacterial species by transcriptomic and metabolomic approaches uncovered no evidence of one. Single-species biofilms of three bacterial species (Pseudomonas aeruginosa, Staphylococcus aureus, and Acinetobacter baumannii) were grown in vitro for three days then challenged with respective antibiotics (ciprofloxacin, daptomycin, tigecycline) for an additional 24 h. All three microorganisms displayed reduced susceptibility in biofilms compared to planktonic cultures. Global transcriptomic profiling of gene expression comparing biofilm to planktonic and antibiotic-treated biofilm to untreated biofilm was performed. Extracellular metabolites including 18 amino acids, glucose, lactate, acetate, formate, and ethanol were measured to characterize the utilization of carbon sources between biofilms, treated biofilms, and planktonic cells. While all three bacteria exhibited a species-specific signature of stationary phase, no conserved gene, gene set, or common functional pathway could be identified that changed consistently across the three microorganisms. Across the three species, glucose consumption was increased in biofilms compared to planktonic cells and alanine and aspartic acid utilization were decreased in biofilms compared to planktonic cells. The reasons for these changes were not readily apparent in the transcriptomes. No common shift in the utilization pattern of carbon sources was discerned when comparing untreated to antibiotic-exposed biofilms. Overall, our measurements do not support the existence of a common genetic or biochemical basis for biofilm tolerance against antibiotics. Rather, there are likely myriad genes, proteins, and metabolic pathways that influence the physiological state of microorganisms in biofilms contributing to antibiotic tolerance. The Staphylococcus aureus microarray data from the study described above is deposited here.
2021-10-18 | GSE185864 | GEO
Project description:Is there a universal genetically programmed defense providing tolerance to antibiotics when bacteria grow as biofilms? A comparison between biofilms of three different bacterial species by transcriptomic and metabolomic approaches uncovered no evidence of one. Single-species biofilms of three bacterial species (Pseudomonas aeruginosa, Staphylococcus aureus, and Acinetobacter baumannii) were grown in vitro for three days then challenged with respective antibiotics (ciprofloxacin, daptomycin, tigecycline) for an additional 24 h. All three microorganisms displayed reduced susceptibility in biofilms compared to planktonic cultures. Global transcriptomic profiling of gene expression comparing biofilm to planktonic and antibiotic-treated biofilm to untreated biofilm was performed. Extracellular metabolites including 18 amino acids, glucose, lactate, acetate, formate, and ethanol were measured to characterize the utilization of carbon sources between biofilms, treated biofilms, and planktonic cells. While all three bacteria exhibited a species-specific signature of stationary phase, no conserved gene, gene set, or common functional pathway could be identified that changed consistently across the three microorganisms. Across the three species, glucose consumption was increased in biofilms compared to planktonic cells and alanine and aspartic acid utilization were decreased in biofilms compared to planktonic cells. The reasons for these changes were not readily apparent in the transcriptomes. No common shift in the utilization pattern of carbon sources was discerned when comparing untreated to antibiotic-exposed biofilms. Overall, our measurements do not support the existence of a common genetic or biochemical basis for biofilm tolerance against antibiotics. Rather, there are likely myriad genes, proteins, and metabolic pathways that influence the physiological state of microorganisms in biofilms contributing to antibiotic tolerance. The Acinetobacter baumannii microarray data from the study described above is deposited here.
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Project description:In this study we examined an anaerobic digester reactor fed with cellulose in order to identify cellulose degrading microorganisms using a culture independent approach. A metagenome was linked to the newly synthesized proteins involved by cellulose, by investigation of labelled proteins (Protein-SIP). The study aims at identifying microorganisms involved in the degradation of plant-based biomass.
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2010-05-06 | E-GEOD-20073 | biostudies-arrayexpress
Project description:Host-pathogen interactions are of great importance in understanding the pathogenesis of infectious microorganisms. We developed in vitro models to study porcine respiratory tract pathogens using an immortalized epithelial cell line, the St. Jude Porcine Lung (SJPL) cell line. In conditions where cytotoxicity was absent or low, the transcriptomic profile of A. pleuropneumoniae after contact with the porcine lung epithelial cells was determined using DNA microarrays. Genes such as tadB, rcpA, members of a putative adhesion locus, and a gene with high homology to the Hsf autotransporter adhesin of Haemophilus influenzae were upregulated as well as genes pgaBC involved in biofilm biosynthesis, while capsular polysaccharide-associated genes were downregulated. Samples from A. pleuropneumoniae grown by either adhesion to SJPL cells or planktonic growth over SJPK cells were combined with samples from A. pleuropneumoniae grown in DMEM medium and co-hybridized on the microarray. Four hybridizations were conducted for each sample combination type. Microarray analysis was carried out using the TM4 Suite of softwares (TIGR) and the SAM algorithm, using a false discovery rate (FDR) value of 0%. For the planktonic and adhesion experiments, Cy5 signal (test) was compared to Cy3 signal (control) in order to obtain a list of significant differentially expressed genes. In order to obtain the list of differentially expressed genes between planktonic growth and adhesion, log2 ratios were compared in TM4 also using the SAM algorithm. Functional classification was performed using TIGR’s Comprehensive Microbial Resource.
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