Lipidomic insights to understand membrane dynamics in response to vanillin in Mycobacterium smegmatis

Sharma, Sharda; Hameed, Saif; Fatima, Zeeshan

doi:10.1007/s10123-019-00099-9

Cited by 8 publications

(4 citation statements)

References 32 publications

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“…Ultra performance liquid chromatography-electrospray ionization and mass spectrometry (UPLC-ESI-MS) was used to characterize the impact of the antimycobacterial vanillin on various lipid extracts from M. smegmatis . The treatment of M. smegmatis cells with vanillin changed the composition of specific lipid classes, causing a disruption in cell membrane homeostasis [90] . Specifically, vanillin caused an overall increase in total lipids, but a decrease in keto-, α-, and methoxy-mycolic acids, which are abundant in the M. tb.…”

Section: Examples Of Metabolomics In Antitubercular Drug Discoverymentioning

confidence: 99%

Deciphering the mechanism of action of antitubercular compounds with metabolomics

Sakallioglu

Barletta

Dussault

et al. 2021

Computational and Structural Biotechnology Journal

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Section: Examples Of Metabolomics In Antitubercular Drug Discoverymentioning

confidence: 99%

Deciphering the mechanism of action of antitubercular compounds with metabolomics

Sakallioglu

Barletta

Dussault

et al. 2021

Computational and Structural Biotechnology Journal

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“…Whole genome sequencing (WGS) has been used to differentiate between relapse and re-infection cases, find mutations which enable drug resistance, and track transmission events. Furthermore, WGS can inform on antibiotic susceptibility of MTB via public databases of given drug resistance [14,15] Another advantage of WGS is its ability to reduce the wait period by identifying the organism within 72 hours. Furthermore, MTB genome can be sequenced directly from uncultured sputum sample which is beneficial for clinically relevant time frame.…”

Section: Application Of Omics In Tuberculosis Diagnosticsmentioning

confidence: 99%

“…Similarly, metabolomics and lipidomics demonstrated its relevancy in studies which explain mode of action of new compounds. A recent study led by Sharma et al demonstrated interaction between genomic and functionality in which impact of the natural antimycobacterial compound vanillin in M. smegmatis was mapped, found that vanillin changes the composition of fatty acids causing disruption of cell membrane homeostasis [14].…”

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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“…Sharma et al demonstrated the role for lipidomics in mechanism of action studies by mapping the impact of the natural antimycobacterial compound vanillin in M. smegmatis. The authors observed that vanillin changes the composition of fatty acids, glycolipids, glycerophospholipids and saccharolipids causing disruption of cell membrane homeostasis [108]. Similarly, lipidomic analysis has been instrumental in investigating the consequences of M.tb drug-resistance conferring mutations to well-characterized anti-TB drugs [109].…”

Section: Mode Of Actionmentioning

confidence: 99%

Multi-Omics Technologies Applied to Tuberculosis Drug Discovery

et al. 2020

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Multi-omics strategies are indispensable tools in the search for new anti-tuberculosis drugs. Omics methodologies, where the ensemble of a class of biological molecules are measured and evaluated together, enable drug discovery programs to answer two fundamental questions. Firstly, in a discovery biology approach, to find new targets in druggable pathways for target-based investigation, advancing from target to lead compound. Secondly, in a discovery chemistry approach, to identify the mode of action of lead compounds derived from high-throughput screens, progressing from compound to target. The advantage of multi-omics methodologies in both of these settings is that omics approaches are unsupervised and unbiased to a priori hypotheses, making omics useful tools to confirm drug action, reveal new insights into compound activity, and discover new avenues for inquiry. This review summarizes the application of Mycobacterium tuberculosis omics technologies to the early stages of tuberculosis antimicrobial drug discovery.

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Lipidomic insights to understand membrane dynamics in response to vanillin in Mycobacterium smegmatis

Cited by 8 publications

References 32 publications

Deciphering the mechanism of action of antitubercular compounds with metabolomics

Deciphering the mechanism of action of antitubercular compounds with metabolomics

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

Multi-Omics Technologies Applied to Tuberculosis Drug Discovery

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