Human pathogens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA628576 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Mycobacterium abscessus [M. abscessus (sensu lato) or M. abscessus group] comprises three closely related taxa with taxonomic status under revision: M. abscessus sensu stricto, M. bolletii and M. massiliense. We describe here a simple, robust and cost effective PCR-based method for distinguishing among M. abscessus, M. massiliense and bolletii. Based on the M. abscessus ATCC 19977T genome, discriminatory regions were identified between M. abscessus and M. massiliense from array-based comparative genomic hybridization. A typing scheme using PCR primers designed for four of these locations was applied to 46 well-characterized clinical isolates comprising 29 M. abscessus, 15 M. massiliense and 2 M. bolletii previously identified by multi-target sequencing. Interestingly, 2 isolates unequivocally identified as M. massiliense were shown to have a full length erm(41) instead of the expected gene deletion and showed inducible clarithromycin resistance after 14 days. We propose using this PCR-based typing scheme combined with erm(41) PCR for a straightforward identification of M. abscessus, M. massiliense and M. bolletii and assessment of inducible clarithromycin resistance. This method can be easily implemented into a routine workflow providing subspecies level identification within 24 hours of isolation of M. abscessus group.
2013-07-17 | GSE43629 | GEO
Project description:Mycobacterium abscessus [M. abscessus (sensu lato) or M. abscessus group] comprises three closely related taxa with taxonomic status under revision: M. abscessus sensu stricto, M. bolletii and M. massiliense. We describe here a simple, robust and cost effective PCR-based method for distinguishing among M. abscessus, M. massiliense and bolletii. Based on the M. abscessus ATCC 19977T genome, discriminatory regions were identified between M. abscessus and M. massiliense from array-based comparative genomic hybridization. A typing scheme using PCR primers designed for four of these locations was applied to 46 well-characterized clinical isolates comprising 29 M. abscessus, 15 M. massiliense and 2 M. bolletii previously identified by multi-target sequencing. Interestingly, 2 isolates unequivocally identified as M. massiliense were shown to have a full length erm(41) instead of the expected gene deletion and showed inducible clarithromycin resistance after 14 days. We propose using this PCR-based typing scheme combined with erm(41) PCR for a straightforward identification of M. abscessus, M. massiliense and M. bolletii and assessment of inducible clarithromycin resistance. This method can be easily implemented into a routine workflow providing subspecies level identification within 24 hours of isolation of M. abscessus group. Two-color CGH with 4 independent Mycobacterium clinical isolates and the M massiliense type strain (CCUG 48898) labeled with Cy3 were cohybridized with the M abscessus type strain (ATCC 19977) labeled with Cy5 on a tiling array designed against the M abscessus type strain
2013-07-17 | E-GEOD-43629 | biostudies-arrayexpress
Project description:With the global increase in the use of carbapenems, several gram-negative bacteria have acquired carbapenem resistance, thereby limiting treatment options. Klebsiella pneumoniae is one of such notorious pathogen that is being widely studied to find novel resistance mechanisms and drug targets. These antibiotic-resistant clinical isolates generally harbor many genetic alterations, and identification of causal mutations will provide insights into the molecular mechanisms of antibiotic resistance. We propose a method to prioritize mutated genes responsible for antibiotic resistance, in which mutated genes that also show significant expression changes among their functionally coupled genes become more likely candidates. For network-based analyses, we developed a genome-scale co-functional network of K. pneumoniae genes, KlebNet (www.inetbio.org/klebnet). Using KlebNet, we could reconstruct functional modules for antibiotic-resistance, and virulence, and retrieved functional association between them. With complementation assays with top candidate genes, we could validate a gene for negative regulation of meropenem resistance and four genes for positive regulation of virulence in Galleria mellonella larvae. Therefore, our study demonstrated the feasibility of network-based identification of genes required for antimicrobial resistance and virulence of human pathogenic bacteria with genomic and transcriptomic profiles from antibiotic-resistant clinical isolates.
2018-06-10 | GSE115539 | GEO
Project description:<p>The Nex-StoCT and ACMG recommend that validation of an NGS-based diagnostic test include performance test characteristics for assay accuracy, analytical sensitivity and specificity, reproducibility and repeatability. To measure these parameters for the GEDi capture and sequencing test, 4 samples (three randomly selected patient samples and the NA12878 HapMap sample) were prepared and sequenced in triplicate on each of three separate days. We also performed WES and SNP array genotyping analyses of these 4 samples using Agilent V4+UTR whole exome enrichment kit and Illumina Omni 2.5 SNP arrays, respectively.</p>
| phs000798 | dbGaP
Project description:Antibiotic resistance (AR) is one of the greatest threats to global health and is associated with higher treatment costs, longer hospital stays, and increased mortality. Current gold standard antibiotic susceptibility tests (AST) are dependent on organism growth rates resulting in prolonged diagnostic answers for slow growing organisms. Changes in the cellular transcriptome can be instantaneous in the presence of stressors such as antibiotic pressure. Here, we demonstrate that relative quantification of the recA gene in response to breakpoint concentrations of ciprofloxacin is an indicator of pathogen susceptibly. For this purpose, we developed seven duplex RT-qPCR assays targeting the recA and 16S rRNA gene, as response and housekeeping genes respectively, for biothreat and ESKAPE pathogens. Surrogate biothreat agents Y. pestis and B. anthracis saw increases in relative recA gene expression, independent of growth rate after 15 minutes of exposure to ciprofloxacin with maximal expression seen after 60 minutes. Treatment with doxycycline also demonstrated an increase in relative recA fold changes compared to no treatment controls. Final evaluation of all seven duplex assays tested across 125 strains, including Tier 1 pathogens, from broth culture demonstrated an overall categorical agreement compared to gold standard microbroth dilution of 97.56% with major error (ME) rates of 1.59% and very major error (VME) rates of 3.23%. Testing on pathogen strains commonly associated with urinary tract infections in contrived clinical sample sets demonstrated an overall categorical agreement of 95.8% with a ME rate of 0.0% and VME rate of 7.69%. These data indicate that relative quantification of a single highly conserved gene accurately predicts susceptibility for multiple bacterial species in response to ciprofloxacin.
2024-02-07 | GSE241489 | GEO
Project description:Heinemann2005 - Genome-scale reconstruction
of Staphylococcus aureus (iMH551)
This model is described in the article:
In silico genome-scale
reconstruction and validation of the Staphylococcus aureus
metabolic network.
Heinemann M, Kümmel A,
Ruinatscha R, Panke S.
Biotechnol. Bioeng. 2005 Dec; 92(7):
850-864
Abstract:
A genome-scale metabolic model of the Gram-positive,
facultative anaerobic opportunistic pathogen Staphylococcus
aureus N315 was constructed based on current genomic data,
literature, and physiological information. The model comprises
774 metabolic processes representing approximately 23% of all
protein-coding regions. The model was extensively validated
against experimental observations and it correctly predicted
main physiological properties of the wild-type strain, such as
aerobic and anaerobic respiration and fermentation. Due to the
frequent involvement of S. aureus in hospital-acquired
bacterial infections combined with its increasing antibiotic
resistance, we also investigated the clinically relevant
phenotype of small colony variants and found that the model
predictions agreed with recent findings of proteome analyses.
This indicates that the model is useful in assisting future
experiments to elucidate the interrelationship of bacterial
metabolism and resistance. To help directing future studies for
novel chemotherapeutic targets, we conducted a large-scale in
silico gene deletion study that identified 158 essential
intracellular reactions. A more detailed analysis showed that
the biosynthesis of glycans and lipids is rather rigid with
respect to circumventing gene deletions, which should make
these areas particularly interesting for antibiotic
development. The combination of this stoichiometric model with
transcriptomic and proteomic data should allow a new quality in
the analysis of clinically relevant organisms and a more
rationalized system-level search for novel drug targets.
This model is hosted on
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and identified by:
MODEL1507180072.
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2015-07-30 | MODEL1507180072 | BioModels
Project description:We present evidence of mechanistically diverse allosteric relays converging on a few peptidyltransferase center (PTC) nucleotides, and propose a general model of antibiotic resistance mediated by these ARE-ABCFs
2021-04-29 | GSE162168 | GEO
Project description:Machine learning approaches offer the potential to systematically identify transcriptional regulatory interactions from a compendium of microarray expression profiles. However, experimental validation of the performance of these methods at the genome scale has remained elusive. Here we assess the global performance of four existing classes of inference algorithms using 445 Escherichia coli Affymetrix arrays and 3,216 known E. coli regulatory interactions from RegulonDB. We also developed and applied the context likelihood of relatedness (CLR) algorithm, a novel extension of the relevance networks class of algorithms. CLR demonstrates an average precision gain of 36% relative to the next-best performing algorithm. At a 60% true positive rate, CLR identifies 1,079 regulatory interactions, of which 338 were in the previously known network and 741 were novel predictions. We tested the predicted interactions for three transcription factors with chromatin immunoprecipitation, confirming 21 novel interactions and verifying our RegulonDB-based performance estimates. CLR also identified a regulatory link providing central metabolic control of iron transport, which we confirmed with real-time quantitative PCR. The compendium of expression data compiled in this study, coupled with RegulonDB, provides a valuable model system for further improvement of network inference algorithms using experimental data. Experiment Overall Design: To explore pathways of particular importance to antibiotic resistance, we assayed 121 conditions using 266 microarrays, including more than 50 genetic perturbations (overexpression or knockout) during norfloxacin-induced DNA damage response, overexpression of the ccdB toxin, and growth to stationary phase on low and high glucose
2008-06-15 | E-GEOD-6836 | biostudies-arrayexpress