Deciphering drug discovery and microbial pathogenesis research in tuberculosis during the two decades of postgenomic era using entity mining approach

Arch Microbiol. 2023 Dec 28;206(1):46. doi: 10.1007/s00203-023-03776-6.

Abstract

We examined literature on Mycobacterium tuberculosis (Mtb) subsequent to its genome release, spanning years 1999-2020. We employed scientometric mapping, entity mining, visualization techniques, and PubMed and PubTator databases. Most popular keywords, most active research groups, and growth in quantity of publications were determined. By gathering annotations from the PubTator, we determined direction of research in the areas of drug hypersensitivity, drug resistance (AMR), and drug-related side effects. Additionally, we examined the patterns in research on Mtb metabolism and various forms of tuberculosis, including skin, brain, pulmonary, extrapulmonary, and latent tuberculosis. We discovered that 2011 had the highest annual growth rate of publications, at 19.94%. The USA leads the world in publications with 18,038, followed by China with 14,441, and India with 12,158 publications. Studies on isoniazid and rifampicin resistance showed an enormous increase. Non-tuberculous mycobacteria also been the subject of more research in effort to better understand Mtb physiology and as model organisms. Researchers also looked at co-infections like leprosy, hepatitis, plasmodium, HIV, and other opportunistic infections. Host perspectives like immune response, hypoxia, and reactive oxygen species, as well as comorbidities like arthritis, cancer, diabetes, and kidney disease etc. were also looked at. Symptomatic aspects like fever, coughing, and weight loss were also investigated. Vitamin D has gained popularity as a supplement during illness recovery, however, the interest of researchers declined off late. We delineated dominant researchers, journals, institutions, and leading nations globally, which is crucial for aligning ongoing and evolving landscape of TB research efforts. Recognising the dominant patterns offers important information about the areas of focus for current research, allowing biomedical scientists, clinicians, and organizations to strategically coordinate their efforts with the changing priorities in the field of tuberculosis research.

Keywords: Entity mining; Mycobacterium tuberculosis; Postgenomic era; Research trends; Scientometric mapping; Text mining; Tuberculosis.

MeSH terms

  • Drug Discovery
  • Humans
  • Isoniazid
  • Mycobacterium tuberculosis* / genetics
  • Opportunistic Infections*
  • Tuberculosis* / drug therapy

Substances

  • Isoniazid