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Transcriptome-Based Molecular Networks Uncovered Interplay Between Druggable Genes of CD8(+) T Cells and Changes in Immune Cell Landscape in Patients With Pulmonary Tuberculosis

BACKGROUND: Tuberculosis (TB) is a major infectious disease, where incomplete information about host genetics and immune responses is hindering the development of transformative therapies. This study characterized the immune cell landscape and blood transcriptomic profile of patients with pulmonary...

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Autores principales: Alsulaimany, Faten Ahmad, Zabermawi, Nidal M. Omer, Almukadi, Haifa, Parambath, Snijesh V., Shetty, Preetha Jayasheela, Vaidyanathan, Venkatesh, Elango, Ramu, Babanaganapalli, Babajan, Shaik, Noor Ahmad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8859411/
https://www.ncbi.nlm.nih.gov/pubmed/35198572
http://dx.doi.org/10.3389/fmed.2021.812857
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author Alsulaimany, Faten Ahmad
Zabermawi, Nidal M. Omer
Almukadi, Haifa
Parambath, Snijesh V.
Shetty, Preetha Jayasheela
Vaidyanathan, Venkatesh
Elango, Ramu
Babanaganapalli, Babajan
Shaik, Noor Ahmad
author_facet Alsulaimany, Faten Ahmad
Zabermawi, Nidal M. Omer
Almukadi, Haifa
Parambath, Snijesh V.
Shetty, Preetha Jayasheela
Vaidyanathan, Venkatesh
Elango, Ramu
Babanaganapalli, Babajan
Shaik, Noor Ahmad
author_sort Alsulaimany, Faten Ahmad
collection PubMed
description BACKGROUND: Tuberculosis (TB) is a major infectious disease, where incomplete information about host genetics and immune responses is hindering the development of transformative therapies. This study characterized the immune cell landscape and blood transcriptomic profile of patients with pulmonary TB (PTB) to identify the potential therapeutic biomarkers. METHODS: The blood transcriptome profile of patients with PTB and controls were used for fractionating immune cell populations with the CIBERSORT algorithm and then to identify differentially expressed genes (DEGs) with R/Bioconductor packages. Later, systems biology investigations (such as semantic similarity, gene correlation, and graph theory parameters) were implemented to prioritize druggable genes contributing to the immune cell alterations in patients with TB. Finally, real time-PCR (RT-PCR) was used to confirm gene expression levels. RESULTS: Patients with PTB had higher levels of four immune subpopulations like CD8(+) T cells (P = 1.9 × 10(−8)), natural killer (NK) cells resting (P = 6.3 × 10(−5)), monocytes (P = 6.4 × 10(−6)), and neutrophils (P = 1.6 × 10(−7)). The functional enrichment of 624 DEGs identified in the blood transcriptome of patients with PTB revealed major dysregulation of T cell-related ontologies and pathways (q ≤ 0.05). Of the 96 DEGs shared between transcriptome and immune cell types, 39 overlapped with TB meta-profiling genetic signatures, and their semantic similarity analysis with the remaining 57 genes, yielded 45 new candidate TB markers. This study identified 9 CD8(+) T cell-associated genes (ITK, CD2, CD6, CD247, ZAP70, CD3D, SH2D1A, CD3E, and IL7R) as potential therapeutic targets of PTB by combining computational druggability and co-expression (r(2) ≥ |0.7|) approaches. CONCLUSION: The changes in immune cell proportion and the downregulation of T cell-related genes may provide new insights in developing therapeutic compounds against chronic TB.
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spelling pubmed-88594112022-02-22 Transcriptome-Based Molecular Networks Uncovered Interplay Between Druggable Genes of CD8(+) T Cells and Changes in Immune Cell Landscape in Patients With Pulmonary Tuberculosis Alsulaimany, Faten Ahmad Zabermawi, Nidal M. Omer Almukadi, Haifa Parambath, Snijesh V. Shetty, Preetha Jayasheela Vaidyanathan, Venkatesh Elango, Ramu Babanaganapalli, Babajan Shaik, Noor Ahmad Front Med (Lausanne) Medicine BACKGROUND: Tuberculosis (TB) is a major infectious disease, where incomplete information about host genetics and immune responses is hindering the development of transformative therapies. This study characterized the immune cell landscape and blood transcriptomic profile of patients with pulmonary TB (PTB) to identify the potential therapeutic biomarkers. METHODS: The blood transcriptome profile of patients with PTB and controls were used for fractionating immune cell populations with the CIBERSORT algorithm and then to identify differentially expressed genes (DEGs) with R/Bioconductor packages. Later, systems biology investigations (such as semantic similarity, gene correlation, and graph theory parameters) were implemented to prioritize druggable genes contributing to the immune cell alterations in patients with TB. Finally, real time-PCR (RT-PCR) was used to confirm gene expression levels. RESULTS: Patients with PTB had higher levels of four immune subpopulations like CD8(+) T cells (P = 1.9 × 10(−8)), natural killer (NK) cells resting (P = 6.3 × 10(−5)), monocytes (P = 6.4 × 10(−6)), and neutrophils (P = 1.6 × 10(−7)). The functional enrichment of 624 DEGs identified in the blood transcriptome of patients with PTB revealed major dysregulation of T cell-related ontologies and pathways (q ≤ 0.05). Of the 96 DEGs shared between transcriptome and immune cell types, 39 overlapped with TB meta-profiling genetic signatures, and their semantic similarity analysis with the remaining 57 genes, yielded 45 new candidate TB markers. This study identified 9 CD8(+) T cell-associated genes (ITK, CD2, CD6, CD247, ZAP70, CD3D, SH2D1A, CD3E, and IL7R) as potential therapeutic targets of PTB by combining computational druggability and co-expression (r(2) ≥ |0.7|) approaches. CONCLUSION: The changes in immune cell proportion and the downregulation of T cell-related genes may provide new insights in developing therapeutic compounds against chronic TB. Frontiers Media S.A. 2022-02-07 /pmc/articles/PMC8859411/ /pubmed/35198572 http://dx.doi.org/10.3389/fmed.2021.812857 Text en Copyright © 2022 Alsulaimany, Zabermawi, Almukadi, Parambath, Shetty, Vaidyanathan, Elango, Babanaganapalli and Shaik. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Alsulaimany, Faten Ahmad
Zabermawi, Nidal M. Omer
Almukadi, Haifa
Parambath, Snijesh V.
Shetty, Preetha Jayasheela
Vaidyanathan, Venkatesh
Elango, Ramu
Babanaganapalli, Babajan
Shaik, Noor Ahmad
Transcriptome-Based Molecular Networks Uncovered Interplay Between Druggable Genes of CD8(+) T Cells and Changes in Immune Cell Landscape in Patients With Pulmonary Tuberculosis
title Transcriptome-Based Molecular Networks Uncovered Interplay Between Druggable Genes of CD8(+) T Cells and Changes in Immune Cell Landscape in Patients With Pulmonary Tuberculosis
title_full Transcriptome-Based Molecular Networks Uncovered Interplay Between Druggable Genes of CD8(+) T Cells and Changes in Immune Cell Landscape in Patients With Pulmonary Tuberculosis
title_fullStr Transcriptome-Based Molecular Networks Uncovered Interplay Between Druggable Genes of CD8(+) T Cells and Changes in Immune Cell Landscape in Patients With Pulmonary Tuberculosis
title_full_unstemmed Transcriptome-Based Molecular Networks Uncovered Interplay Between Druggable Genes of CD8(+) T Cells and Changes in Immune Cell Landscape in Patients With Pulmonary Tuberculosis
title_short Transcriptome-Based Molecular Networks Uncovered Interplay Between Druggable Genes of CD8(+) T Cells and Changes in Immune Cell Landscape in Patients With Pulmonary Tuberculosis
title_sort transcriptome-based molecular networks uncovered interplay between druggable genes of cd8(+) t cells and changes in immune cell landscape in patients with pulmonary tuberculosis
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8859411/
https://www.ncbi.nlm.nih.gov/pubmed/35198572
http://dx.doi.org/10.3389/fmed.2021.812857
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