OHEJP CARE Campylobacter
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB48148 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| CAKJTY01.dat.gz | Other | |||
| CAKJTY01.fasta.gz | Fasta.gz | |||
| CAKJTY01.master.dat | Other | |||
| CAKJTZ01.dat.gz | Other |
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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>
| phs001260 | dbGaP
Project description:Commercial probiotic bacteria must be tested for acquired antibiotic resistance elements to avoid potential transfer to pathogens. The European Food Safety Authority recommends testing resistance using microdilution culture techniques previously used to establish inhibitory thresholds for the Bifidobacterium genus. Many Bifidobacterium animalis subsp. lactis strains exhibit increased resistance to tetracycline, historically attributed to the ribosomal protection gene tet(W). However, some strains that harbor genetically identical tet(W) genes show various inhibition levels suggesting that other genetic elements also contribute to observed differences. Here, we adapted several molecular assays to confirm the inhibition of B. animalis subsp. lactis strains Bl-04 and HN019, and employed RNA-seq to assess the transcriptional differences related to genomic polymorphisms. We detected specific stress responses to the antibiotic by correlating ATP concentration to viable genome copies from droplet digital PCR, and found that the bacteria were still metabolically active in high drug concentrations. Transcriptional analyses revealed that several polymorphic regions, particularly a novel multi-drug efflux transporter, were differentially expressed between the strains in each experimental condition, likely having phenotypic effects. We also found that the tet(W) gene was up-regulated only during sub-inhibitory tetracycline concentrations, while two novel tetracycline resistance genes were up-regulated at high concentrations. Furthermore, many genes involved in amino acid metabolism and transporter function were up-regulated while genes for complex carbohydrate utilization, protein metabolism, and CRISPR-Cas systems were down-regulated. These results provide high-throughput means for assessing antibiotic resistance and determine the genetic network that contributes to the global tetracycline response between two highly related probiotic strains.
2018-09-27 | GSE117878 | GEO
Project description:Understanding constraints which shape antibiotic resistance is key for predicting and controlling drug resistance. Here, we performed high-throughput laboratory evolution of Escherichia coli. The transcriptome, resistance, and genomic profiles for the evolved strains in 48 environments were quantitatively analyzed. By analyzing the quantitative datasets through interpretable machine learning techniques, the emergence of low dimensional phenotypic states within the 192 strains was observed. Further analysis revealed the underlying biological processes responsible for the distinct states. We also report a novel constraint which leads to decelerated evolution. These findings bridge the genotypic, gene expression, and drug resistance space, and lead to a comprehensive understanding of constraints for antibiotic resistance.
2020-10-12 | GSE137348 | GEO
Project description:Tuberculosis (TB) is one of the deadliest infectious disorders in the world. To effectively TB manage, an essential step is to gain insight into the lineage of Mycobacterium tuberculosis (MTB) strains and the distribution of drug resistance. Although the Campania region is declared a cluster area for the infection, to contribute to the effort to understand TB evolution and transmission, still poorly known, we have generated a dataset of 159 genomes of MTB strains, from Campania region collected during 2018-2021, obtained from the analysis of whole genome sequence data. The results show that the most frequent MTB lineage is the 4 according for 129 strains (81.11%). Regarding drug resistance, 139 strains (87.4%) were classified as multi susceptible, while the remaining 20 (12.58%) showed drug resistance. Among the drug-resistance strains, 8 were isoniazid-resistant MTB (HR-MTB), 7 were resistant only to one antibiotic (3 were resistant only to ethambutol and 3 isolate to streptomycin while one isolate showed resistance to fluoroquinolones), 4 multidrug-resistant MTB, while only one was classified as pre-extensively drug-resistant MTB (pre-XDR). This dataset expands the existing available knowledge on drug resistance and evolution of MTB, contributing to further TB-related genomics studies to improve the management of TB infection.
2023-11-17 | E-MTAB-13058 | biostudies-arrayexpress
Project description:Cationic antimicrobial peptides (CAPs) are promising novel alternatives to conventional antibacterial agents, but the overlap in resistance mechanisms between small-molecule antibiotics and CAPs is unknown. Does evolution of antibiotic resistance decrease (cross-resistance) or increase (collateral sensitivity) susceptibility to CAPs? We systematically addressed this issue by studying the susceptibilities of a comprehensive set of antibiotic resistant Escherichia coli strains towards 24 antimicrobial peptides. Strikingly, antibiotic resistant bacteria frequently showed collateral sensitivity to CAPs, while cross-resistance was relatively rare. We identified clinically relevant multidrug resistance mutations that simultaneously elevate susceptibility to certain CAPs. Transcriptome and chemogenomic analysis revealed that such mutations frequently alter the lipopolysaccharide composition of the outer cell membrane and thereby increase the killing efficiency of membrane-interacting antimicrobial peptides. Furthermore, we identified CAP-antibiotic combinations that rescue the activity of existing antibiotics and slow down the evolution of resistance to antibiotics. Our work provides a proof of principle for the development of peptide based antibiotic adjuvants that enhance antibiotic action and block evolution of resistance.
2018-03-29 | GSE96706 | GEO
Project description:The rise of antibiotic resistance in many bacterial pathogens has been driven by the spread of a few successful strains, suggesting that some bacteria are genetically pre-disposed to evolving resistance. We tested this hypothesis by challenging a diverse set of 222 strains of Staphylococcus aureus with the antibiotic ciprofloxacin in a large-scale evolution experiment. Surprisingly, we found that a single efflux pump, norA, causes widespread variation in evolvability across the diversity of S. aureus. In most lineages of S. aureus, elevated norA expression potentiated evolution by increasing the fitness benefit provided by resistance mutations in DNA topoisomerase under ciprofloxacin treatment. Amplification of norA provided a further mechanism of rapid evolution, but this was restricted to strains from CC398. Crucially, chemically inhibiting NorA effectively prevented the evolution of resistance across the diversity of S. aureus. Our study shows that the underlying genetic diversity of pathogenic bacteria plays a key role in shaping resistance evolution. Understanding this link makes it possible to predict which strains are likely to evolve resistance and to optimize inhibitor use to prevent this outcome.
2020-07-05 | GSE150762 | GEO
Project description:Pseudomonas aeruginosa is a major opportunistic pathogen causing a wide range of infections and one of the most problematic bacteria regarding antibiotic resistance, with an increasing incidence of multidrug and extensively-drug resistant strains, including resistance to last resource antibiotics such as carbapenems. Resistances are often due to complex interplays of naturally and acquired resistance mechanisms which are enhanced by its remarkably large regulatory network. Thus, the use of non-targeted shotgun methodologies such as mass spectrometry-based proteomics is crucial to understand these interplays and to reveal possible strain and species-specific novel mechanisms of antibiotic resistance. The aim of this study was to determine the proteomic response of two carbapenem-resistant and extensively-drug-resistant P. aeruginosa strains to subminimal inhibitory concentrations (sub-MICs) of meropenem. The strains belonged to high-risk clones ST235 and ST395, one carrying a class 1 integron-encoded VIM-4 metallo-β-lactamase and one carrying no acquired antibiotic resistance genes. Each strain was cultivated with three different sub-MICs of meropenem, and a quantitative shotgun proteomic approach was applied, using tandem mass tag (TMT) isobaric labeling followed by nano-liquid chromatography tandem-mass spectrometry, to determine significantly up- or down-regulated proteins and enriched groups of proteins and pathways. Cultivation of both strains with ½ and ¼ of the MIC, resulted in hundreds of differentially regulated proteins, including several β-lactamases, transport-related proteins (including multiple porins and efflux pumps), proteins associated with peptidoglycan metabolism and cell wall organization and dozens of regulatory proteins. Remarkably, all components of the H1 type VI secretion system were up-regulated in one of the strains. Enrichment analyses revealed that multiple metabolic pathways were affected. Additionally, numerous proteins of unknown function were also differentially-regulated in each strain. In conclusion, high subminimal-inhibitory concentrations of meropenem cause massive changes in the proteomes of carbapenem-resistant P. aeruginosa strains, involving a wide range of common and strain-specific mechanisms and proteins, many still uncharacterized which might potentially play a role in the susceptibility of P. aeruginosa to meropenem.
2023-01-05 | PXD034987 | Pride
Project description:Mortality in Escherichia coli bloodstream infections: antibiotic resistance still does not make it.
| PRJEB35745 | ENA
Project description:Abstract from paper: "For many years, infectious disease modelers have used agent-based models to study the spread of viruses, but the models were too computationally intensive to fully replicate even in vitro experiments. Now, with technological advancements and accessible software, agent-based models can be used to their full potential. In this work, we created an agent-based model that expresses viral transmission and diffusion, can manipulate and track individual cells, and can be fit to real experimental data in a timely manner due to acceleration of computation with graphics processing units (GPUs). The use of GPUs allows simulations to run on desktop computers in a few minutes or hours, while still simulating an accurate number of cells to replicate infection experiments. This model can now be used to study in-host infections quickly, so that in the event of an outbreak or epidemic a treatment plan and course of action can be developed in less time."
2023-01-04 | MODEL2301010001 | BioModels
Project description:The evolution of antibiotic resistance is a clear example of adaptation by natural selection. Although a number of mutations contributing to the resistance have been identified, the relationship between the mutations and the related phenotypic changes responsible for the resistance has yet to be fully elucidated. To better characterize phenotype-genotype mapping for drug resistance, we performed parallel laboratory evolution of Escherichia coli under the selection of single antibiotics and after 90 days propagation obtained resistant strains. We find that an acquisition of resistance to one drug drastically changes the resistance and susceptibility to other drugs. Based on transcriptome data of these strains, we demonstrated that the resistances could be quantitatively predicted by the expression changes of a small number of genes. Whole-genome resequencing analysis provided several candidate mutations contributing to the resistances, while phenotype-genotype mapping was suggested to be complex and included various mutations that caused similar phenotypic changes. The integration of transcriptome and genome data enables us to extract essential phenotypic changes for drug resistances. To examine the contribution of the gene expression changes to the antibiotic resistances, transcriptome of the parent strain (duplicated) and 40 resistant strains (4 parallel-evolved resistant strains for 10 antibiotics) were analyzed.
2014-09-17 | E-GEOD-59408 | biostudies-arrayexpress