Gloria G Guerrero M¹*, Rogelio Hernández-Pando², Juan Manuel Favela-Hernández³, Aurora-Martinez-Romero³

¹Universidad Autónoma de Zacatecas, "Francisco García Salinas". Unidad Académica de Ciencias Biológicas. Zacatecas, Zac. México
²Instituto Nacional de Ciencias Medicas y Nutrición, Salvador Subirán. Departamento de Patología. Lab de Patología Experimental, Tlalpan. Cdad de México. México
³Universidad Juárez del Estado de Durango. Facultad de Ciencias Químicas. Gómez Palacio, Durango. Méxic

*Corresponding Author: Gloria G Guerrero M, Universidad Autónoma de Zacatecas, Unidad Académica de Ciencias Biológicas. Zacatecas, Zac, Mexico.

Received: December 02, 2025; Published: December 26, 2025

Abstract

Tuberculosis caused by mycobacteria(s) of the complex of Mycobacterium tuberculosis (MTBC) nowadays represents a problem in public health. The scenery is worsened by comorbidities and the rise in multidrug-resistant strains (MDR). Despite this, recent reports have highlighted the emergence of high-throughput alternatives to potentiate diagnostic and more effective treatment, such as omics technologies. Indeed, current Omics technologies allow a deep analysis of the dynamics of gene expression, proteins, and metabolites The gene expression profiles along with the type of blood samples versus stools and sputum can make a difference in the diagnosis because they represent a window into the molecular signature of cell tissue or organ-specific. The integration of omics data with artificial intelligence methodologies (i.e., machine learning, deep learning, big data analytics, and neural networks) can generate algorithms as a biological language model to evaluate, and predict embed numerical representation of the data generated from omics technologies addressing the host-pathogen interface. The objective of the present review is to pinpoint how the omics technologies has been contributing to the dissection and understanding on this. At the same time, emphasize the use of AI to accelerate this. This review was based on searches and data from the PubMed database from 2020 to 2025. The result was a landscape of the milestones of omics and AI in TB. These advances in both or individually can support and potentiate enormously the diagnostic and treatment in TB.

Keywords: Mycobacterium tuberculosis,Omics Technologies,Host Innate and Cellular Immune Response,Artificial Intelligenc

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Citation

Citation: Gloria G Guerrero M., et al. “Omics and Artificial Intelligence Addressing Host Immune Response in TB".Acta Scientific Microbiology 9.1 (2026): 02-24.

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Copyright: © 2026 Gloria G Guerrero M., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.