Using Omics to Study Leprosy, Tuberculosis, and Other Mycobacterial Diseases

Abstract

Mycobacteria are members of the Actinomycetales order, and they are classified into one family, Mycobacteriaceae. More than 20 mycobacterial species cause disease in humans. The Mycobacterium group, called the Mycobacterium tuberculosis complex (MTBC), has nine closely related species that cause tuberculosis in animals and humans. TB can be detected worldwide and one-fourth of the world’s population is contaminated with tuberculosis. According to the WHO, about two million dies from it, and more than nine million people are newly infected with TB each year. Mycobacterium tuberculosis (M. tuberculosis) is the most potential causative agent of tuberculosis and prompts enormous mortality and morbidity worldwide due to the incompletely understood pathogenesis of human tuberculosis. Moreover, modern diagnostic approaches for human tuberculosis are inefficient and have many lacks, while MTBC species can modulate host immune response and escape host immune attacks to sustain in the human body. “Multi-omics” strategies such as genomics, transcriptomics, proteomics, metabolomics, and deep sequencing technologies could be a comprehensive strategy to investigate the pathogenesis of mycobacterial species in humans and offer significant discovery to find out biomarkers at the early stage of disease in the host. Thus, in this review, we attempt to understand an overview of the mission of “omics” approaches in mycobacterial pathogenesis, including tuberculosis, leprosy, and other mycobacterial diseases.

Advancing personalized medicine for tuberculosis through the application of immune profiling

“…By using the high throughput sequencing technique, both genomics and epigenomics facilitate huge reference genome databases for shotgun analysis with a static link to the organism. However, besides the need for high-performance machine installation, genome reconstruction by bioinformatic software also requires advanced training and troubleshooting, disregarding the fact that many sequenced elements' activity cannot be fully identified (Chu et al, 2021;Ahamad et al, 2022).…”

“…Unlike traditional PCR, which only amplifies a limited number of genes simultaneously, currently used transcriptomic techniques such as RNA-sequencing (RNA-seq) and microarray can quantify the entire transcriptome or the large-scale targeted analysis of most well-known genes. However, aside from handling errors during the long process of RNA extraction and sequencing, there is an undeniable disadvantage: RNA polymorphism is not always reflected in protein translation and functional expression (Chu et al, 2021;Ahamad et al, 2022).…”

“…This technology is also helpful for discovering metabolism-centric biomarkers for TB (Long et al, 2022). However, the variation of metabolites is unavoidable, which may lead to several sampling artifacts and fluctuations (Chu et al, 2021;Ahamad et al, 2022). Additionally, metabolite and protein annotation is not always robust, the quantitative information is often limited, quality assurance/quality control (QA/QC) is troublesome, the cost is high, and the technical requirements are affordable only for specialized laboratories.…”

“…However, immunomics creates a complicated scenario because it studies and manipulates the genes and proteins involved in immunologic functioning and the complex cellular microenvironment. The future of immunomics lies in the continued pursuit of validation of immunologic markers correlated with clinical outcomes, which is now limited, and many technologies are still in their infancy (Tremoulet and Albani, 2005;Chu et al, 2021;Ahamad et al, 2022). In other words, this is a chance to build up a platform worthy of investment, which only requires intense studies and improvement but has several advantages the previous one lack.…”

Diagnostic biomarkers for active tuberculosis: progress and challenges

“…The multi‐omics approach includes simultaneously evaluating different types of biomarkers, offering a comprehensive view of genotype–phenotype relationships in TB pathogenesis, and possibly generating accurate biomarkers. Besides being comprehensive, it is an unbiased method (Ahamad et al , 2022 ). A recent study used three different modalities and integrated omics analysis comparing PLWH with and without incident TB.…”