12–17 Jul 2026
University of Graz
Europe/Vienna timezone

Targeting metabolic fluxes to prevent drug tolerance in Mycobacterium Tuberculosis under host-derived stress

15 Jul 2026, 08:30
20m
11.02 - HS (University of Graz)

11.02 - HS

University of Graz

130
Contributed Talk Systems Biology and Biochemical Networks Contributed Talks

Speaker

Tanishk Patodi (Indian Institute of Science, Bengaluru, India)

Description

Tuberculosis remains a major cause of death among infectious diseases despite the availability of multiple antibiotics against the causative agent Mycobacterium Tuberculosis (Mtb). Heterogeneity in Mtb population upon host infection prevents clearance of Mtb under antibiotic exposure. Mtb is known to differ in its redox environment, and the subpopulation with a reduced (oxidised) cytoplasmic environment is more tolerant (sensitive) to drugs. Handling such heterogeneity necessitates a protracted treatment and increases the chances of relapse. Cues from macrophages are known to influence the emergence of this population heterogeneity; however, the mechanisms underlying this process remain unclear.
In this study, we employed a genome-scale metabolic model of Mtb, \code{iEK1011_2.0}, to identify how individual bacilli reroute their metabolic pathways crucial for Mtb to become drug-tolerant under host-derived stress. We derived context-specific models for phenotype-specific sub-populations (i.e., tolerant and sensitive populations) using RNA-seq data and employed gene knockout strategies to target the metabolic changes responsible for the phenotypic transitions. Our systems-level analysis reveals metabolic changes that contribute to the spontaneous emergence of phenotypic heterogeneity in Mtb within infected macrophages and serves as a platform to identify novel potent interventional strategies.

Bibliography

@article{lopez-agudelo_systematic_2020,
title = {A systematic evaluation of {Mycobacterium} tuberculosis {Genome}-{Scale} {Metabolic} {Networks}},
volume = {16},
issn = {1553-7358},
doi = {10.1371/journal.pcbi.1007533},
language = {en},
number = {6},
urldate = {2026-01-20},
journal = {PLOS Computational Biology},
author = {López-Agudelo, Víctor A. and Mendum, Tom A. and Laing, Emma and Wu, HuiHai and Baena, Andres and Barrera, Luis F. and Beste, Dany J. V. and Rios-Estepa, Rigoberto},
month = jun,
year = {2020},
}

@article{mishra_targeting_2019,
title = {Targeting redox heterogeneity to counteract drug tolerance in replicating \textit{{Mycobacterium} tuberculosis}},
volume = {11},
issn = {1946-6234, 1946-6242},
doi = {10.1126/scitranslmed.aaw6635},
language = {en},
number = {518},
journal = {Science Translational Medicine},
author = {Mishra, Richa and Kohli, Sakshi and Malhotra, Nitish and Bandyopadhyay, Parijat and Mehta, Mansi and Munshi, MohamedHusen and Adiga, Vasista and Ahuja, Vijay Kamal and Shandil, Radha K. and Rajmani, Raju S. and Seshasayee, Aswin Sai Narain and Singh, Amit},
month = nov,
year = {2019},
}

Authors

Tanishk Patodi (Indian Institute of Science, Bengaluru, India) Garhima Arora (Translational Health Science and Technology Institute, Faridabad, India) Samrat Chatterjee (Translational Health Science and Technology Institute, Faridabad, India) Amit Singh (Indian Institute of Science, Bengaluru, India) Mohit Kumar Jolly (Indian Institute of Science, Bengaluru, India)

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