Gut microbiota of higher vertebrates is host-specific. The number and diversity of the organisms residing within the gut ecosystem are defined by physiological and environmental factors, such as host genotype, habitat, and diet. Recently, culture-independent sequencing techniques have added a new dimension to the study of gut microbiota and the challenge to analyze the large volume of sequencing data is increasingly addressed by the development of novel computational tools and methods. Interestingly, gut microbiota maintains a constant relative abundance at operational taxonomic unit (OTU) levels and altered bacterial abundance has been associated with complex diseases such as symptomatic atherosclerosis, type 2 diabetes, obesity, and colorectal cancer. Therefore, the study of gut microbial population has emerged as an important field of research in order to ultimately achieve better health. In addition, there is a spontaneous, non-linear, and dynamic interaction among different bacterial species residing in the gut. Thus, predicting the influence of perturbed microbe–microbe interaction network on health can aid in developing novel therapeutics. Here, we summarize the population abundance of gut microbiota and its variation in different clinical states, computational tools available to analyze the pyrosequencing data, and gut microbe–microbe interaction networks.

As of August 6th, 2021, the World Health Organization has notified 200.8 million laboratory-confirmed infections and 4.26 million deaths from COVID-19, making it the worst pandemic since the 1918 flu. The main challenges in mitigating COVID-19 are effective vaccination, treatment, and agile containment strategies. In this review, we focus on the potential of Artificial Intelligence (AI) in COVID-19 surveillance, diagnosis, outcome prediction, drug discovery and vaccine development. With the help of big data, AI tries to mimic the cognitive capabilities of a human brain, such as problem-solving and learning abilities. Machine Learning(ML), a subset of AI, holds special promise for solving problems based on experiences gained from the curated data. Advances in AI methods have created an unprecedented opportunity for building agile surveillance systems using the deluge of real-time data generated within a short span of time. During the COVID-19 pandemic, many reports have discussed the utility of AI approaches in prioritization, delivery, surveillance, and supply chain of drugs, vaccines, and non-pharmaceutical interventions. This review will discuss the clinical utility of AI-based models and will also discuss limitations and challenges faced by AI systems, such as model generalizability, explainability, and trust as pillars for real-life deployment in healthcare.

SummaryAdhesion and invasion of Intestinal Epithelial Cells (IECs) are critical for the pathogenesis of Salmonella Typhi, the aetiological agent of human typhoid fever. While type three secretion system-1 (T3SS-1) is a major invasion apparatus of Salmonella, independent invasion mechanisms were described for non-typhoidal Salmonellae. Here, we show that T2942, an AIL-like protein of S. Typhi Ty2 strain, is required for adhesion and invasion of cultured IECs. That invasion was T3SS-1 independent was proved by ectopic expression of T2942 in the non-invasive E. coli BL21 and double-mutant Ty2 (Ty2Δt2942ΔinvG) strains. Laminin and fibronectin were identified as the host-binding partners of T2942 with higher affinity for laminin. Standalone function of T2942 was confirmed by cell adhesion of the recombinant protein, while the protein or anti-T2942 antiserum blocked adhesion/ invasion of S. Typhi, indicating specificity. A 20-amino acid extracellular loop was required for invasion, while several loop regions of T2942 contributed to adhesion. Further, T2942 cooperates with laminin-binding T2544 for adhesion and T3SS-1 for invasion. Finally, T2942 was required and synergistically worked with T3SS-1 for pathogenesis of S. Typhi in mice. Considering wide distribution of T2942 among clinical strains, the protein or the 20-mer peptide may be suitable for vaccine development.

Background: Phosphoserine phosphatase (PSP) is an essential enzyme involved in L-serine biosynthesis. Results: High throughput screen was performed to identify specific PSP inhibitors with activity against intracellular bacteria. Conclusion: Validation of PSP as a drug target would lead to identification of scaffolds with a novel mechanism. Significance: This is the first report demonstrating selective inhibition of M. tuberculosis PSP enzyme.

BackgroundFungal allergy is considered as serious health problem worldwide and is increasing at an alarming rate in the industrialized areas. Rhizopus oyzae is a ubiquitously present airborne pathogenic mold and an important source of inhalant allergens for the atopic population of India. Here, we report the biochemical and immunological features of its 44 kDa sero-reactive aspartic protease allergen, which is given the official designation ‘Rhi o 1’.MethodThe natural Rhi o 1 was purified by sequential column chromatography and its amino acid sequence was determined by mass spectrometry and N-terminal sequencing. Based on its amino acid sequence, the cDNA sequence was identified, cloned and expressed to produce recombinant Rhi o 1. The allergenic activity of rRhi o 1 was assessed by means of its IgE reactivity and histamine release ability. The biochemical property of Rhi o 1 was studied by enzyme assay. IgE-inhibition experiments were performed to identify its cross-reactivity with the German cockroach aspartic protease allergen Bla g 2. For precise characterization of the cross-reactive epitope, we used anti-Bla g 2 monoclonal antibodies for their antigenic specificity towards Rhi o 1. A homology based model of Rhi o 1 was built and mapping of the cross-reactive conformational epitope was done using certain in silico structural studies.ResultsThe purified natural nRhi o 1 was identified as an endopeptidase. The full length allergen cDNA was expressed and purified as recombinant rRhi o 1. Purified rRhi o 1 displayed complete allergenicity similar to the native nRhi o 1. It was recognized by the serum IgE of the selected mold allergy patients and efficiently induced histamine release from the sensitized PBMC cells. This allergen was identified as an active aspartic protease functional in low pH. The Rhi o 1 showed cross reactivity with the cockroach allergen Bla g 2, as it can inhibit IgE binding to rBla g 2 up to certain level. The rBla g 2 was also found to cross-stimulate histamine release from the effector cells sensitized with anti-Rhi o 1 serum IgE. This cross-reactivity was found to be mediated by a common mAb4C3 recognizable conformational epitope. Bioinformatic studies revealed high degree of structural resemblances between the 4C3 binding sites of both the allergens.Conclusion/SignificanceThe present study reports for the first time anew fungal aspartic protease allergen designated as Rhi o 1, which triggers IgE-mediated sensitization leading to various allergic diseases. Here we have characterized the recombinant Rhi o 1 and its immunological features including cross-reactive epitope information that will facilitate the component-resolved diagnosis of mold allergy.