Deciphering Tuberculous Meningitis: From Clinical Challenges to Novel Models and Pathogenic Pathways.

During and after the COVID-19 pandemic,Tuberculosis (TB) has reestablished with higher figures due to interruptions in the Directly Observed Treatment Short course (DOTS) despite underreporting. The rising consequences would have extended to extra-pulmonary forms of TB as well, including Tuberculous Meningitis (TBM). Considering the fact that TBM is the most dangerous and worst form of TB, we found the need to scan the literature to highlight various aspects of TBM. Epidemiology of TBM is proportionally less frightening, but the consequent mortalities and morbidities are more alarming than pulmonary TB. Here, we address critical research gaps in Tuberculous Meningitis that warrant further investigations. The highlighted aspects encompass a comprehensive understanding of TBM's clinical presentation and improved diagnostic tools for timely detection, the exploration of innovative chemotherapies and surgical interventions, the unraveling of the role of the blood-brain barrier in disease onset, investigating of the contributions of various brain cells to TBM development, deciphering the complex inflammatory response, exploring the involvement of Matrix Metalloproteinases in tissue damage, delving into host-pathogen genetics influencing susceptibility, utilizing robust in-vivo and in-vitro models for mechanistic insights, and more importantly between TBM and SARS-COVID-19 are discussed. Addressing these gaps will substantially advance our understanding of TBM's complex pathogenesis, contributing to more effective diagnostic, therapeutic, and preventive strategies against this debilitating disease.

Genetic Association Studies in Host-Pathogen Interaction Analysis.

Studying host-pathogen interactions at a molecular level has always been technically challenging. Identifying the different biochemical and genetic pathways involved in the different stages of infection traditionally require complex molecular biology tools and often the use of costly animal models. In this chapter, we illustrate a complementary approach to address host-pathogen interactions, taking advantage of the natural interindividual genetic diversity. The application of genetic association studies allows us to identify alleles involved in infection progression or resistance. Thus, this strategy may be useful to unravel new molecular pathways underlying host-pathogen interactions. Here we present the general steps that might be followed to plan, execute, and analyze a population-based study in order to identify genetic variants affecting human exposition to pathogens.

Genetic Association Studies in Host-Pathogen Interaction Analysis.

Studying host-pathogen interactions at a molecular level has been always technically challenging. Identifying the different biochemical and genetic pathways involved in the different stages of infection traditionally require complex molecular biology tools and often the use of costly animal models. In this chapter we illustrate a complementary approach to address host-pathogen interactions, taking advantage of the natural interindividual genetic diversity. The application of genetic association studies allows us to identify alleles involved in infection progression or resistance. Thus, this strategy may be useful to unravel new molecular pathways underlying host-pathogen interactions. Here we present the general steps that might be followed to plan, execute, and analyze a population-based study in order to identify genetic variants affecting human exposition to pathogens.

Utilizing Genomics to Study Entomopathogenicity in the Fungal Phylum Entomophthoromycota: A Review of Current Genetic Resources.

The order Entomophthorales, which formerly contained c.280 species, has recently been recognized as a separate phylum, Entomophthoromycota, consisting of three recognized classes and six families. Many genera in this group contain obligate insect-pathogenic species with narrow host ranges, capable of producing epizootics in natural insect populations. Available sequence information from the phylum Entomophthoromycota can be classified into three main categories: first, partial gene regions (exons+introns) used for phylogenetic inference; second, protein coding gene regions obtained using degenerate primers, expressed sequence tag methodology or de novo transcriptome sequencing with molecular function inferred by homology analysis; and third, primarily forthcoming whole-genome sequencing data sets. Here we summarize the current genetic resources for Entomophthoromycota and identify research areas that are likely to be significantly advanced from the availability of new whole-genome resources.