Multi-Omics Technologies Applied to Tuberculosis Drug Discovery

Goff, Aaron; Cantillon, Daire; Wildner, Leticia Murano; Waddell, Simon J.

doi:10.3390/app10134629

Cited by 29 publications

(19 citation statements)

References 112 publications

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“…Metabolomics is a useful approach for finding new targets for antituberculosis drugs and understanding compounds’ mode of action ( Tuyiringire et al, 2018 ). By analyzing the network of metabolites and the interactions between them, it is possible to obtain knowledge about the cell processes ( Goff et al, 2020 ). de Carvalho et al (2010) supplemented M. tuberculosis cultures with 13C-labeled carbon substrates and then analyzed the metabolites by LC-MS, proving that Mycobacteria can catabolize multiple carbon sources simultaneously.…”

Section: Identification Of the Drug Target And Determination Of Its Mmentioning

confidence: 99%

Early Drug Development and Evaluation of Putative Antitubercular Compounds in the -Omics Era

et al. 2021

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Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium tuberculosis. According to the WHO, the disease is one of the top 10 causes of death of people worldwide. Mycobacterium tuberculosis is an intracellular pathogen with an unusually thick, waxy cell wall and a complex life cycle. These factors, combined with M. tuberculosis ability to enter prolonged periods of latency, make the bacterium very difficult to eradicate. The standard treatment of TB requires 6–20months, depending on the drug susceptibility of the infecting strain. The need to take cocktails of antibiotics to treat tuberculosis effectively and the emergence of drug-resistant strains prompts the need to search for new antitubercular compounds. This review provides a perspective on how modern -omic technologies facilitate the drug discovery process for tuberculosis treatment. We discuss how methods of DNA and RNA sequencing, proteomics, and genetic manipulation of organisms increase our understanding of mechanisms of action of antibiotics and allow the evaluation of drugs. We explore the utility of mathematical modeling and modern computational analysis for the drug discovery process. Finally, we summarize how -omic technologies contribute to our understanding of the emergence of drug resistance.

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Section: Identification Of the Drug Target And Determination Of Its Mmentioning

confidence: 99%

Early Drug Development and Evaluation of Putative Antitubercular Compounds in the -Omics Era

et al. 2021

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“…This has provided us with framework for potential medication targets. Moreover, manipulation of gene functions has shed light on pathways essential to MTB in various microenvironments emphasizing targets for drug breakthroughs [7].…”

Section: Application Of Omics In Tuberculosis Treatmentmentioning

confidence: 99%

Risk management of infectious disease using multidimensional Omics: Molecular diagnostic and personal care of tuberculosis

Buzimkic¹,

Heck²,

Kim³

2021

GSC Biol. and Pharm. Sci.

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Tuberculosis (TB) is one of the top 10 leading causes of death worldwide responsible for over 1.5 million deaths annually. It is caused by hazardous biological pathogen (i.e., Mycobacterium tuberculosis (MTB)) with single infectious agent, surpassing even HIV/AIDS. Roughly one-quarter of the world's population has latent TB, meaning that people have been infected by tuberculosis bacteria but have not yet developed the disease. Patients with active tuberculosis on average infect five to fifteen other people via airborne droplets. Once infected, people with HIV are 19 times more likely to develop active tuberculosis which has almost 100% mortality for this group, if not treated properly. Comparatively, 45% of HIV negative people will die if they develop active tuberculosis and are not adequately medicated. This is concerning since 95% of cases and deaths are in developing countries, where treatments and diagnosis may not be timely. Additionally, current detection methods do not distinguish active tuberculosis from a cleared or latent infection while microbiological culture of mycobacteria is slow. However, medical discoveries and newly developed technologies allowed for unification of disciplines incorporating omics into everyday biological research. The goal of this short review is to demonstrate ways in which field of multidimensional Omics could contributed to the advanced detection of infectious disease by improving accuracy and quality of patient care by implementing molecular based detection of pathogen (i.e., antigenicity and metabolomics tools) as well as personal care with follow-up monitoring care (i.e., immunogenicity and vaccinomics tools) in the diagnosis, treatment, and prevention of tuberculosis.

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“…Three papers describe state-of-the-art approaches to TB drug discovery. The first one by van Wijk and co-authors deals with quantitative pharmacology models including machine learning and artificial intelligence [18]; the second one by Bruch and colleagues discusses structure-and target-based approaches to TB drug design [19]; the last one explores the -omics technologies and how they have been exploited so far in TB drug discovery [20].…”

Section: The Present Special Issue On "Tuberculosis Drug Discovery Anmentioning

confidence: 99%

Editorial on Special Issue “Tuberculosis Drug Discovery and Development 2019”

2020

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Multi-Omics Technologies Applied to Tuberculosis Drug Discovery

Cited by 29 publications

References 112 publications

Early Drug Development and Evaluation of Putative Antitubercular Compounds in the -Omics Era

Early Drug Development and Evaluation of Putative Antitubercular Compounds in the -Omics Era

Risk management of infectious disease using multidimensional Omics: Molecular diagnostic and personal care of tuberculosis

Editorial on Special Issue “Tuberculosis Drug Discovery and Development 2019”

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