Mycobacterium intracellulare
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA339271 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR10098937_1.fastq.gz | Fastqsanger.gz | |||
| SRR10098937_2.fastq.gz | Fastqsanger.gz | |||
| SRR10053763_1.fastq.gz | Fastqsanger.gz | |||
| SRR10053763_2.fastq.gz | Fastqsanger.gz | |||
| SRR10120000_1.fastq.gz | Fastqsanger.gz |
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Project description:A comparative genomic approach was used to identify large sequence polymorphisms among Mycobacterium avium isolates obtained from a variety of host species. DNA microarrays were used as a platform for comparing mycobacteria field isolates with the sequenced bovine isolate Mycobacterium avium subsp. paratuberculosis (Map) K10. ORFs were classified as present or divergent based on the relative fluorescent intensities of the experimental samples compared to Map K10 DNA. Map isolates cultured from cattle, bison, sheep, goat, avian, and human sources were hybridized to the Map microarray. Three large deletions were observed in the genomes of four Map isolates obtained from sheep and four clusters of ORFs homologous to sequences in the Mycobacterium avium subsp. avium (Maa) 104 genome were identified as being present in these isolates. One of these clusters encodes glycopeptidolipid biosynthesis enzymes. One of the Map sheep isolates had a genome profile similar to a group of Mycobacterium avium subsp. silvaticum (Mas) isolates which included four independent laboratory stocks of the organism traditionally identified as Maa strain 18. Genome diversity in Map appears to be mostly restricted to large sequence polymorphisms that are often associated with mobile genetic elements. Keywords: Comparative genomic hybridization
2007-04-27 | GSE7622 | GEO
Project description:A comparative genomic approach was used to identify large sequence polymorphisms among Mycobacterium avium isolates obtained from a variety of host species. DNA microarrays were used as a platform for comparing mycobacteria field isolates with the sequenced bovine isolate Mycobacterium avium subsp. paratuberculosis (Map) K10. ORFs were classified as present or divergent based on the relative fluorescent intensities of the experimental samples compared to Map K10 DNA. Map isolates cultured from cattle, bison, sheep, goat, avian, and human sources were hybridized to the Map microarray. Three large deletions were observed in the genomes of four Map isolates obtained from sheep and four clusters of ORFs homologous to sequences in the Mycobacterium avium subsp. avium (Maa) 104 genome were identified as being present in these isolates. One of these clusters encodes glycopeptidolipid biosynthesis enzymes. One of the Map sheep isolates had a genome profile similar to a group of Mycobacterium avium subsp. silvaticum (Mas) isolates which included four independent laboratory stocks of the organism traditionally identified as Maa strain 18. Genome diversity in Map appears to be mostly restricted to large sequence polymorphisms that are often associated with mobile genetic elements. Keywords: Comparative genomic hybridization Each isolate was competitively hybridized against Map K10 with a minimum of 2 dye flip hybridizations per isolate.
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Project description:We focused on how Mycobacterium avium subsp. paratuberculosis influences the subsequent host response to investigate the host immunopathology accompanying the host anti-mycobacterial immune response during Mycobacterium avium subsp. paratuberculosis infection in spleen of mice.
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Project description:We focused on how Mycobacterium avium subsp. paratuberculosis influences the subsequent host response to investigate the host immunopathology accompanying the host anti-mycobacterial immune response during Mycobacterium avium subsp. paratuberculosis infection in spleen of mice. We analyzed altered transcription in the spleen of mice at 3, 6, and 12 weeks following Mycobacterium avium subsp. paratuberculosis infection.
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Project description:Mycobacterium intracellulare 3387 Genome sequencing
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Project description:Mycobacterium avium complex (MAC), including Mycobacterium avium and Mycobacterium intracellulare (MI), accounts for a significant portion of nontuberculous mycobacterial lung disease affecting immunocompromised and lung structural disease patients. Adapting pathogens to a host-induced hostile environment is critical to establishing infection and persistence within the host. However, the cellular and molecular mechanisms of stress response for MAC still need to be elucidated. In this study, we analyzed the transcriptional profile of MI under acidic and oxidative stress conditions using RNA-seq. At the transcriptome level, 80 genes were shown [FC] ≥2.0 and p <0.05 under oxidative stress with 10 mM hydrogen peroxide. In detail, 77 genes were upregulated, while 3 genes were downregulated. Also, 878 genes were shown [FC] ≥2.0 and p <0.05 under acidic stress with pH 4.5. Among these genes, 339 were upregulated, while 539 were downregulated. Functional analysis revealed the activation of several pathways, including nitrogen and sulfur metabolism, under acidic stress conditions. On the contrary, oxidative stress conditions activated DNA replication and repair pathways. Our data demonstrate the activation of nitrogen and sulfur metabolism in MAC infection, which could be crucial for persistence and survival under stress conditions encountered within the host during infection. In conclusion, this study suggests the importance of stress responses in MAC pathogenesis and identifies potential therapeutic target pathways.
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Project description:Detection of species-specific proteotypic peptides for accurate and easy characterization of infectious non-tuberculous mycobacteria such as Mycobacterium avium subsp. paratuberculosis, Mycobacterium marinum and Mycobacterium vaccae is essential. Therefore, we carried out reanalysis of publicly available M. avium subsp. paratuberculosis, M. marinum and M. vaccae proteomic dataset PXD027444, PXD003766 and PASS00954 by proteome database search and followed by spectral library generation. The raw DDA data were searched against their respective reference proteome databases using Proteome Discoverer and FragPipe. The resulting peptide spectrum matches were converted into a spectral library using BiblioSpec.
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