Whole genome sequencing of Mycobacterium abscessus isolates
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB14002 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR1413170_1.fastq.gz | Fastqsanger.gz | |||
| ERR1413170_2.fastq.gz | Fastqsanger.gz | |||
| ERR1413180_1.fastq.gz | Fastqsanger.gz | |||
| ERR1413180_2.fastq.gz | Fastqsanger.gz | |||
| ERR1413190_1.fastq.gz | Fastqsanger.gz |
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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
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2016-03-02 | E-GEOD-78787 | biostudies-arrayexpress
Project description:Tuberculosis (TB) is still a major global health challenge, killing over 1.5 million people each year, and hence, there is a need to identify and develop novel treatments for Mycobacterium tuberculosis (M. tuberculosis). The prevalence of infections caused by nontuberculous mycobacteria (NTM) is also increasing and has overtaken TB cases in the United States and much of the developed world. Mycobacterium abscessus (M. abscessus) is one of the most frequently encountered NTM and is difficult to treat. We describe the use of drug-disease association using a semantic knowledge graph approach combined with machine learning models that has enabled the identification of several molecules for testing anti-mycobacterial activity. We established that niclosamide (M. tuberculosis IC90 2.95 μM; M. abscessus IC90 59.1 μM) and tribromsalan (M. tuberculosis IC90 76.92 μM; M. abscessus IC90 147.4 μM) inhibit M. tuberculosis and M. abscessus in vitro. To investigate the mode of action, we determined the transcriptional response of M. tuberculosis and M. abscessus to both compounds in axenic log phase, demonstrating a broad effect on gene expression that differed from known M. tuberculosis inhibitors. Both compounds elicited transcriptional responses indicative of respiratory pathway stress and the dysregulation of fatty acid metabolism. Further testing against drug-resistant isolates and other NTM is warranted to clarify the usefulness of these repurposed drugs for mycobacteria.
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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.
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Project description:Human macrophages are a natural host of many mycobacterium species, including Mycobacterium abscessus (M. abscessus), an emerging pathogen affecting patients with lung diseases and immunocompromised individuals. There are few available treatments and the search for effective antibiotics against M. abscessus has been hindered by the lack of a tractable in vitro intracellular model of infection. Here, we established a reliable model for M. abscessus infection using human pluripotent stem cell-derived macrophages (hPSC-macrophages). hPSC differentiation permitted a reproducible generation of functional human macrophages that were highly susceptible to M. abscessus infection. Electron microscopy demonstrated that M. abscessus was present in the vacuoles of hPSC-macrophages. RNA-sequencing analysis revealed a time dependent host cell response to M. abscessus, with differing gene and protein expression patterns observed at 3-hours, 24-hours and 48-hours post-infection. Culture of engineered tdTOMATO-expressing hPSC-macrophages with GFP-expressing M. abscessus enabled rapid and image-based high-throughput analysis of intracellular infection and quantitative assessment of antibiotic resistance and efficacy. Our study describes the first hPSC-based model for M. abscessus infection, which represents a novel platform for studying M. abscessus-host interaction and an accessible tool for drug discovery.
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