Meta analysis of host transcriptome in pulmonary tuberculosis


Identification: Gautam-Anuradha


Description

Meta analysis of host transcriptome in pulmonary tuberculosis
1. Anuradha Gautam
National Institute of Biomedical Genomics
Kalyani India
2. Saroj K. Mohapatra, MD
Assistant Professor
National Institute of Biomedical Genomics
Kalyani India
3. Bhaswati Pandit, PhD
Associate Professor
National Institute of Biomedical Genomics
Kalyani India

HYPOTHESIS: Development of tuberculosis is driven by the interaction of human host and M.tuberculosis. This interaction is known to dysregulate the expression of host genes and the study of these genes from whole blood can help identify active cellular pathways and compartments contributing to the dysregulation. 

METHODS: 
1. Selection of datasets: Whole blood host transcriptomic datasets of treatment naive TB patients without the co-infection of HIV and healthy controls were identified from GEO, ArrayExpress and NCBI.
2. Identification of Differentially Expressed Genes (DEGs): Quality control was performed for the normalized datasets.‘t’ test was performed on common genes to identify the DEGs. Up and downregulated genes have LFC greater than 0.26 or less than -0.26 at FDR corrected p value of 0.05.
3. Pathway analysis: Over representation analysis (ORA) was performed on DEGs with clusterProfiler package in R
4. Identification of miRNA targets from the DEGs: list of DEGs were submitted to Enrichr and miRNA targetting DEGs were found, interactions were visualized with miRNet.
5. Identification of active cellular compartments:ENCODE ChIP-seq experiment data was visualized using UCSC genome browser (hg19) to identify the presence of epigenetic activating marks (H3K4me3 and H3K27Ac) around regulatory elements characterized by Genehancer and EPD promoter database.
RESULTS: Pathway analysis was done for 239 upregulated genes and 83 downregulated genes with LFC greater than 0.26 or less than -0.26 respectively and an FDR corrected p value of 0.05. These DEGs showed enrichment of innate immune response, interferon response and response to virus pathways in GO, KEGG and WikiPathways. Non-genomic actions of 1,25 vitamin D3 and pathway for the human immune response to TB and sepsis was enriched in WikiPathways. Among the downregulated genes, adaptive immune pathways involving T cell receptor signalling and leukocyte differentiation were enriched for both GO and KEGG pathways. hsa-miR-146a-5p was found to have targets within the upregulated genes: STAT1, IFITM3, IFITM1, SAMDL9, S100A12,RSAD2,IFI44,EPSTI1 and TRIM22.Further increasing the LFC cutoff, 19 upregulated genes (LFC>1) and two downregulated genes (LFC<-1) were identified. Upregulated genes DHRS9, ANKRD22, TNFAIP6, CARD17 and KCNJ15 had activating epigenetic marks around their promoters exclusively in the myeloid lineage cells.13 genes had at least one of the two activation marks (H3K4me3 and H3K27Ac) in neutrophils, and 14 genes had either one or both activation marks in CD14+ monocytes accounting for two of themost numbers of genes with activation marks in any cell subset.
CONCLUSION: More innate immune pathways are enriched within the upregulated genes, while adaptive immune pathways are enriched within the downregulated genes. miR146a-5p which targets STAT1, is known to be involved in chemoattraction of neutophils by bronchial epithelial cells and upregulation of IL6 production by macrophages and monocyte migration. Since, majority of the top upregulated genes has an activation mark in the neutrophils and CD14+ monocytes, this interaction of the miRNA and upregulated genes, might impact recruitment of myeloid cells in TB.   

Acknowledgements: The completion of this work has been supported by the National Institute of Biomedical Genomics and UGC, GOI. 

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