Ontology highlight
ABSTRACT:
PROVIDER: PRJNA735778 | ENA |
REPOSITORIES: ENA
Similar Datasets
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:Antimicrobial resistance (AMR) is an increasing challenge for therapy and management of bacterial infections. Currently, antimicrobial resistance detection relies on phenotypic assays, which are performed independently of species identification. On the contrary, phenotypic prediction from molecular data using genomics is gaining interest in clinical microbiology and might become a serious alternative in the future. Although, in general protein analysis should be superior to genomics for phenotypic prediction, no untargeted proteomics workflow specifically related to AMR detection has been proposed so far. In this study, we present a universal proteomics workflow to detect the bacterial species and antimicrobial resistance related proteins in the absence of secondary antibiotic cultivation in less than 4 h from a primary culture. The method was validated using a sample cohort of 7 bacterial species and 11 AMR determinants represented by 13 protein isoforms which resulted in a sensitivity of 92 % (100 % with vancomycin inference) and a specificity of 100 % with respect to AMR determinants. This proof-of concept study demonstrates the high potential of untargeted proteomics for clinical microbiology.
2021-11-25 | PXD022425 | Pride
Project description:Antimicrobial resistance (AMR) has become a serious public and economic threat. The rate of bacteria acquiring AMR surpasses the rate of new antibiotics discovery, projecting more deadly AMR infections in the future. The Pathogen Box is an open-source library of drug-like compounds that can be screened for antibiotic activity. We have screened molecules of the Pathogen Box against Vibrio cholerae, the cholera-causing pathogen, and successfully identified two compounds, MMV687807 and MMV675968, that inhibit growth. RNA-seq analyses of V. cholerae after incubation with each compound revealed that both compounds affect cellular functions on multiple levels including carbon metabolism, iron homeostasis, and biofilm formation. In addition, whole-genome sequencing analysis of spontaneous resistance mutants identified an efflux system that confers resistance to MMV687807. We also identified that the dihydrofolate reductase is the likely target of MMV675968 suggesting it acts as an analog of trimethoprim but with a minimum inhibitory concentration (MIC) 14-fold lower than trimethoprim in molar concentration. In summary, these two compounds that effectively inhibit V. cholerae and other bacteria may lead to the development of new antibiotics for better treatment of the cholera disease.
2021-11-18 | GSE185596 | GEO
Project description:Antimicrobial resistance (AMR) is a pandemic spread across multiple infectious disease microbes. To provide a new tool to study AMR, here we develop a Klebsiella pneumoniae cell-free gene expression (CFE) system. To characterise the system, we use proteomics to compare this to a Escherichia coli MG1655 CFE model, to identify relative differences and unique proteins. Then we use this native CFE system to profile antimicrobial activity in comparison to whole cell inhibition, to reveal host differences in IC50/MIC50 values. Finally, we use the CFE tool to study AMR variants, at a proof-of-concept level. As an exemplar, we show that RpoB H526L confers a 58-fold increase in CFE resistance to rifampicin – a common genotype frequently observed in rifampicin-resistant Mycobacterium tuberculosis clinical isolates. In summary, we provide a cell-free synthetic biology strategy for the profiling of antibiotic sensitivity and resistance from K. pneumoniae. While initial processing requires Biosafety Level 2, the final extracts are non-living and suitable for long-term storage, and potentially transfer to a Biosafety Level 1 lab. This bioassay has potential uses for early-stage host-specific antimicrobial development and the testing of AMR variants for structure-activity relationship studies. The data reposited is label-free high-resolution LC-MS proteomics data performed to characterise the proteins in cell-free extract of K. pneumoniae ATCC 13882 and compare to that of E. coli MG1655 to identify common and unique proteins. We also characterised the proteins of K. pneumoniae clinically resistant isolates ST258-T1b and NJST258-1, and compared them to K. pneumoniae ATCC 13882 laboratory strain.
2023-11-29 | PXD046861 | Pride
Project description:Antimicrobial resistance (AMR) is a pandemic spread across multiple infectious disease microbes. To provide a new tool to study AMR, here we develop a Klebsiella pneumoniae cell-free gene expression (CFE) system. To characterise the system, we use proteomics to compare this to a Escherichia coli MG1655 CFE model, to identify relative differences and unique proteins. Then we use this native CFE system to profile antimicrobial activity in comparison to whole cell inhibition, to reveal host differences in IC50/MIC50 values. Finally, we use the CFE tool to study AMR variants, at a proof-of-concept level. As an exemplar, we show that RpoB H526L confers a 58-fold increase in CFE resistance to rifampicin – a common genotype frequently observed in rifampicin-resistant Mycobacterium tuberculosis clinical isolates. In summary, we provide a cell-free synthetic biology strategy for the profiling of antibiotic sensitivity and resistance from K. pneumoniae. While initial processing requires Biosafety Level 2, the final extracts are non-living and suitable for long-term storage, and potentially transfer to a Biosafety Level 1 lab. This bioassay has potential uses for early-stage host-specific antimicrobial development and the testing of AMR variants for structure-activity relationship studies. The data reposited is label-free high-resolution LC-MS proteomics data performed to characterise the proteins in cell-free extract of K. pneumoniae ATCC 13882 and compare to that of E. coli MG1655 to identify common and unique proteins. We also characterised the proteins of K. pneumoniae clinically resistant isolates ST258-T1b and NJST258-1, and compared them to K. pneumoniae ATCC 13882 laboratory strain.
2023-11-29 | PXD046864 | Pride
Project description:Antimicrobial resistance (AMR) poses a threat to global health and the economy. Rifampicin resistant Mycobacterium tuberculosis accounts for a third of the global AMR burden. Gaining the upper hand on AMR requires a deeper understanding of the physiology of resistance. AMR often results in the erosion of normal cell function: a fitness cost. Identifying intervention points in the mechanisms underpinning the cost of resistance in M. tuberculosis could play a pivotal role in strengthening future treatment regimens. We used a collection of M. tuberculosis strains providing an evolutionary and phylogenetic snapshot of rifampicin resistance and subjected them to genome-wide transcriptomic and proteomic profiling to identify key perturbations of normal physiology. We found that a rifampicin resistance-conferring mutation in RpoB imparts considerable gene expression changes, many of which are mitigated by a compensatory mutation in RpoC. However, our data also provide evidence for pervasive epistasis: the same resistance mutation imposed a different fitness cost and functionally unrelated changes to gene expression in clinical strains from unrelated genetic backgrounds. Rather than functional changes in specific pathways, our data suggest that the fitness cost of rifampicin resistance stems from a misallocation of resources: the greater the departure from the wild type baseline proteome investment, the greater the fitness cost of rifampicin resistance in a given strain. We summarize these observations in the “Burden of Expression” hypothesis of fitness cost and provide evidence that it can be used for suppressing the emergence of rifampicin resistance.
2021-03-12 | PXD011568 | Pride