Bacterial Antimicrobial Resistance Reference Gene Database
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: MSV000085123
PROVIDER: PRJNA313047 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:TK6 cells were exposed to various perturbations and then the transcriptome profiles were collected at 4 hours to assemble a reference database to generate a Genotoxic / Nongenotoxic classifier using the nearest shrunken centroids method.
2015-05-01 | GSE58431 | GEO
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:TK6 cells were exposed to various perturbations and then the transcriptome profiles were collected at 4 hours to assemble a reference database to generate a Genotoxic / Nongenotoxic classifier using the nearest shrunken centroids method. TK6 cells were exposed to various perturbations and then the transcriptome profiles were collected at 4 hours to assemble a reference database to generate a Genotoxic / Nongenotoxic classifier using the nearest shrunken centroids method.
2015-05-01 | E-GEOD-58431 | biostudies-arrayexpress
Project description:IRdb: an insect resistance database
| PRJNA851028 | ENA
Project description:Antimicrobial Resistance Gene Sequencing
| PRJEB60945 | ENA
Project description:Universal antimicrobial resistance detection from clinical bacterial isolates using proteomics
| PRJEB39816 | ENA
Project description:Neisseria gonorrhoeae is the causative agent of gonorrhea, a leading sexually transmitted disease with severe complications on reproductive health. The U.S. Centers for Disease Control and Prevention has categorized the public health threat induced by N. gonorrhoeae as “urgent”, due to the ease of transmission and the fast emergence of multi-drug resistant strains. The need for development of vaccines and understanding the underlying factors leading to antibiotic resistance is of utmost importance. The proteomic profiles of the 14 WHO N. gonorrhoeae reference strains have been compared to the WHO F reference strain using a mass spectrometry with tandem mass tags (TMT) labeling to analyze the cell envelope and the cytoplasmic fractions extracted from each strain. Identifying novel vaccine candidates and proteomic signatures for antimicrobial resistance will further our understanding of N. gonorrhoeae proteotypes, in relationship to their respective genotypes and phenotypes, and provide deep insights that will impact the development of preventive and therapeutic tools to combat gonorrhea.
2018-12-19 | PXD008412 | Pride
Project description:Pesticides are widely used to protect growth of crops and prevent the spread of diseases. However, more and more pest insects have developed resistance to chemical pesticides along with the long-term application of the pesticides. It is very important to explore the molecular mechanisms of insecticide resistance not only for reversing the resistance in insects, but also for finding out new function targets of the insecticides. Recently, the next-generation sequence technique has become an effective tool to screen resistance genes and has developed transcriptome profiles of various species. However, a comprehensive database to collect these transcriptome data remains poorly developed. In this study, we constructed a database for insect resistance called IRdb, which contains gene count data from various insect species analyzed by a unified process. In addition to the gene data, IRdb also contains 430 unique resistance proteins (experimentally verified proteins manually extracted from literature). Users can discriminate the resistance proteins by submitting fasta sequence of proteins of interest, which can provide clues to detect resistance proteins. The application of resistance protein part in IRdb indicates the accuracy of prediction of IRdb by extracting CTD features and employing random forest. The database IRdb online web server (http://120.27.24.199:20609/) was provided for users to download the transcriptome and protein data for resistance of insects to insecticides and to predict potential resistance proteins.
2022-06-23 | GSE206463 | GEO
Project description:Bacterial evolution of antibiotic resistance frequently has deleterious side effects on microbial growth, virulence, and susceptibility to other antimicrobial agents. However, it is unclear how these trade-offs could be utilized for manipulating antibiotic resistance in the clinic, not least because the underlying molecular mechanisms are poorly understood. Using laboratory evolution, we demonstrate that clinically relevant resistance mutations in Escherichia coli constitutively rewire a large fraction of the transcriptome in a repeatable and stereotypic manner. Strikingly, lineages adapted to functionally distinct antibiotics and having no resistance mutations in common show a wide range of parallel gene expression changes that alter oxidative stress response, iron homeostasis, and the composition of the bacterial outer membrane and cell surface. These common physiological alterations are associated with changes in cell morphology and enhanced sensitivity to antimicrobial peptides. Finally, the constitutive transcriptomic changes induced by resistance mutations are largely distinct from those induced by antibiotic stresses in the wild-type. This indicates a limited role for genetic assimilation of the induced antibiotic stress response during resistance evolution. Our work suggests that diverse resistance mutations converge on similar global transcriptomic states that shape genetic susceptibility to antimicrobial compounds.
2023-01-26 | GSE223493 | GEO
Project description:FDA-CDC Antimicrobial Resistance Bank
| PRJNA294416 | ENA