Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

RNA-seq analysis of Mycobacterium avium TMC724 vs. M. avium 104 non-coding and coding transcriptome

ABSTRACT: Deep sequencing was implemented to study the transcriptional landscape of Mycobacterium avium TMC724. High-resolution transcriptome analysis identified the transcription start points for 652 genes. One third of these coincided with the start codons and therefore belong to leaderless transcripts, whereas the rest of the transcripts had 5' UTRs with the mean length of 83 nt. In addition, the 5' UTRs of 6 genes contained SAM-IV and Ykok types of riboswitches. 87 antisense RNAs and 9 intergenic small RNAs were mapped. Four of the revealed intergenic small RNAs, including igMAV_1034-1035 expressed at a very high level, have no homologs in M. tuberculosis, whilst M. avium lacks several intergenic sRNAs present in M. tuberculosis. Among those, MTS479 and MTS1338 are of special interest due to their possible implication in pathogenesis. Elucidation of differences in the repertoire of intergenic sRNAs between the two mycobacterial species may improve our understanding of mycobacterial diseases pathogenesis. Transcriptional profile of Mycobacterium avium TMC724, grown at 37M-BM-0C in Dubos broth until mid-logarithmic growth phase

ORGANISM(S): Mycobacterium avium

SUBMITTER: Dmitriy Ignatov

PROVIDER: E-GEOD-46281 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:Background: Mycobacterium avium subspecies paratuberculosis (MPTb) is the causative agent of Johne’s disease, an intestinal disease of ruminants with major economic consequences. MPTb bacilli are phagocytosed by host macrophages upon exposure where they persist, resulting in lengthy subclinical phases of infection that can lead to immunopathology and disease dissemination. Consequently, analysis of the macrophage transcriptome in response to MPTb infection can provide valuable insights into the molecular mechanisms that underlie Johne’s disease. Here, we investigate pan-genomic gene expression in bovine monocyte-derived macrophages (MDM) purified from seven age-matched non-related females, in response to in vitro infection with MPTb (multiplicity of infection 2:1) at intervals of 2 hours, 6 hours and 24 hours post-infection. Results: Differentially expressed genes were identified by comparing the transcriptomes of the infected MDM to the control MDM at each time point (adjusted P-value threshold ≤ 0.10). 1,050 differentially expressed unique genes were identified 2 hours post-infection, with 974 and 84 differentially expressed unique genes detected 6 hours and 24 hours post-infection, respectively. Furthermore, in the infected MDM the number of upregulated genes exceeded the number of downregulated genes at each time point, with the fold-change in expression for the upregulated genes markedly higher than that for the downregulated genes. Conclusions: Inspection and systems analysis of the differentially expressed genes revealed changes in the expression profiles of genes involved in the inflammatory response, cell signalling pathways and apoptosis. The transcriptional changes associated with cellular signalling and the inflammatory response may reflect different immuno-modulatory mechanisms that underlie host-pathogen interactions during infection. Affymetrix GeneChip® Bovine Genome Arrays were used to examine gene expression of bovine monocyte-derived macrophages (MDM) after in vitro challenge with Mycobacterium avium subspecies paratuberculosis across a time series of 2 hr, 6 hr and 24 hr post-challenge. A 0 hr control treatment was also generated and seven different age-matched female Holstein-Friesian cattle were used for each time-point/treatment combination for a total of 49 microarrays, one of which was excluded from analysis since it did not pass quality control.

Dataset Information

RNA-seq analysis of Mycobacterium avium TMC724 vs. M. avium 104 non-coding and coding transcriptome

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets