Mining large-scale response networks reveals ‘topmost activities’ in Mycobacterium tuberculosis infection
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Mycobacterium tuberculosis owes its high pathogenic potential to its ability to evade host immune responses and thrive inside the macrophage. The outcome of infection is largely determined by the cellular response comprising a multitude of molecular events. The complexity and inter-relatedness in the processes makes it essential to adopt systems approaches to study them. In this work, we construct a comprehensive network of infection-related processes in a human macrophage comprising 1888 proteins and 14,016 interactions. We then compute response networks based on available gene expression profiles corresponding to states of health, disease and drug treatment. We use a novel formulation for mining response networks that has led to identifying highest activities in the cell. Highest activity paths provide mechanistic insights into pathogenesis and response to treatment. The approach used here serves as a generic framework for mining dynamic changes in genome-scale protein interaction networks.
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The fight of the host against the pathogen in M. tuberculosis infection involves several levels including containment of the microbe, generation of radicals and a hostile acidic environment, deprivation from essential nutrients, formation of anti-mycobacterial peptides and cytokines, and cell damage and suicidal activities of macrophages and PMNs such as autophagy, necroptosis, or efferocytosis to
“the fight of the host against the pathogen in M. tuberculosis infection involves several levels including containment of the microbe, generation of radicals and a hostile, acidic environment, deprivation from essential nutrients, formation of anti-mycobacterial peptides and cytokines which strengthen host responses by attracting other immune cells, down to cell damage and suicidal activities of MO”
From Macrophage defense mechanisms against intracellular bacteria (2015) · cites this paper as [3]
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Pal, S., & Chandra, N. R. (2024) · Springer eBooks · doi:10.1007/978-3-031-65986-7_9 · Cited by 2 · see citing works
Self-citationBanerjee, U., Chedere, A., Padaki, R., Mohan, A., Sambaturu, N., Singh, A., & Chandra, N. R. (2023) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.3c00845 · Cited by 1 · see citing works
Self-citationMvubu, N. E. (2016) · ResearchSpace (University of KwaZulu-Natal)
Banerjee, U., Borbora, S. M., Guha, M., Yadav, V., Sanjay, V., Singh, A., Balaji, K. N., & Chandra, N. R. (2024) · Immunology · doi:10.1111/imm.13781
Self-citationPrasanna, A., Anand, C., Sunitha, B. S., Prasannan, P., Arjun, P., Upadhyay, S., Bankoti, N., & Chandra, N. R. (2025) · Dysphagia · doi:10.1007/s00455-025-10890-8
Self-citation
- Authors
- Sambarey, A., Prashanthi, K., & Chandra, N.
- Affiliations
- Indian Institute of Science Bangalore (IN)
- Corresponding author
- Chandra, Nagasuma
- Venue
- Scientific Reports
- Published
- 2013-07-29
- Volume
- 3
- Issue
- 1
- Pages
- 2302-2302
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC3725478
- OpenAlex
- W1971528695
- Cited by
- 31
- References
- 71
- Citations by year
- 2025: 1 · 2024: 2 · 2023: 2 · 2022: 2 · 2021: 2 · 2020: 2 · 2019: 2 · 2017: 6 · 2016: 5 · 2015: 4 · 2014: 3
- FWCI
- 1.79
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Scientific Reports (publishedVersion, cc-by-nc-sa)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion, cc-by-nc-sa)
- PubMed (publishedVersion)
- NOT FOUND REPOSITORY (Indian Institute of Science Bangalore) (acceptedVersion)
- Funders
- Indian Institute of Science
- Department of Biotechnology, Ministry of Science and Technology, India
- Department of Science and Technology, Ministry of Science and Technology, India
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Health Sciences › Medicine › Infectious Diseases › Tuberculosis Research and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- Mycobacterium tuberculosis, tuberculosis pathogenesis, macrophage response, protein-protein interaction network, response networks, gene expression profiles, drug response, host immune evasion, network mining
- MeSH terms
- Humans, Macrophages, Models, Biological, Mycobacterium tuberculosis, Tuberculosis, Gene Regulatory Networks, Data Mining, Transcriptome, Protein Interaction Maps
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