Rakesh Kumar Mishra

Human pluripotent stem cells (hPSCs), comprising embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs), have emerged as a versatile platform connecting developmental biology with disease modelling, drug discovery, and regenerative medicine. Their capacity for indefinite self-renewal and differentiation into derivatives of all three germ layers provides an essentially renewable source of human cells that are otherwise inaccessible from patients. In this review, we discuss the biological principles governing hPSC identity, with emphasis on the transcriptional, epigenetic, metabolic, and extracellular signalling networks that regulate pluripotency and the distinct features of naive and primed states. We further examine culture systems for maintaining pluripotency and directed differentiation strategies for generating lineage-specific cell types. The application of hPSCs to disease modelling and therapeutic discovery is considered through two-dimensional cellular models and increasingly sophisticated three-dimensional organoids and organoid-on-chip systems, which provide progressively greater tissue complexity and physiological relevance. We also highlight the integration of CRISPR-based genome editing with hPSC platforms to generate isogenic disease models, establish genotype–phenotype relationships, identify therapeutic targets, and enable precise correction of disease-associated variants. Finally, we review the emerging clinical applications of hPSC-derived cell therapies and clinical translation, which remains constrained by challenges related to genomic stability, cellular heterogeneity and maturation, immune compatibility, tumorigenicity, manufacturing, and scalability. Addressing these challenges through improved differentiation, quality control, genome engineering, and scalable manufacturing will be essential for translating the broad potential of hPSCs into safe, reproducible, and accessible clinical therapies.

Ultraconserved non-coding elements (UCEs) exhibit near-perfect sequence conservation across vertebrate genomes, implying severe evolutionary constraint and essential biological functions. Near the vertebrate Hoxd complex, a master regulator of axial patterning and limb morphogenesis, three Conserved Regions (CR1, CR2, and CR3), each longer than 200 bp, show exceptional sequence conservation and drive robust regulatory activity in transient reporter assays. To investigate their endogenous in vivo functions, we used CRISPR-Cas9 genome editing to generate a series of deletions of varying sizes spanning CR2 and CR3, individually and in combination, within hoxd complex in zebrafish. Screening thousands of founder embryos revealed a clear size and conservation-dependent relationship between deletion extent and viability: complete deletion of core CR2, CR3, or the combined CR2/3 loci could not be transmitted through the germline, whereas the smaller and least-conserved deletion, a 626-bp subregion of CR2, was the only allele to yield a stable, homozygous-viable line. Our results indicate that the core ultraconserved sequences are developmentally indispensable, whereas flanking, less conserved sequences can be removed without consequence. Detailed phenotypic and molecular characterization of the mutant embryos revealed normal primary and secondary body axis formation, intact somite segmentation, and unperturbed craniofacial and pectoral fin development. Expression of hoxd complex genes showed no significant change in mutant embryos by RNA-ISH or RT-qPCR, although RT-qPCR revealed a consistent, modest upward trend at 24 and 48 hpf, raising the possibility that the deleted subregion normally contributes a weak repression of overall hoxd complex genes transcription. While this study reveals some functional aspects of ultraconserved elements, much more remains to be uncovered.

The spillover of pathogenic organisms across the livestock-environmental interface is a major OneHealth concern. To investigate the co-occurrence, antimicrobial resistance profiles, and genomic characteristics of ESBL-E. coli in healthy migratory sheep flocks and associated farm environments, a cross-sectional study was conducted in South Karnataka, India. 9124 animals from 60 farms were included in the study, and 701 samples from sheep and environmental were analysed, during 2023-2025. The occurrence of ESBL-E. coli was comparable in sheep and environmental samples, and exhibited high multidrug resistance patterns. Whole-genome-sequencing and comparative genomic analysis of ESBL-E. coli isolates revealed substantial diversity in antimicrobial resistance genes including resistance-nodulation-cell division family efflux pumps, alterations in β-lactam target proteins such as penicillin-binding proteins, and a wide range of β-lactamase genes, including CTX-M, TEM, DHA, AmpC, and SHV variants. Several plasmid replicon types were detected in both sheep and environmental isolates, suggesting potential plasmid-mediated horizontal gene transfer at the livestock-environment interface. Notably, phenotypic resistance to imipenem was detected in 16.6% of sheep isolates, and stx genes were identified in 19% of isolates, raising additional public health concerns. Overall, the detection of multidrug-resistant ESBL-E. coli in migratory sheep and their surrounding environments, together with shared resistomes, plasmids, and lineages, underscores the role of small non-sedentary ruminants as overlooked nodes in AMR dissemination and highlights the need for targeted OneHealth surveillance strategies.

Wastewater-based surveillance has emerged as a powerful tool for monitoring microbial diversity, antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs). In this study, wastewater samples collected from March 2022 to March 2024 from 19 locations in four metropolitan cities of India were profiled using shotgun metagenomics. Taxonomic abundance and beta diversity analyses revealed significant differences in microbial community compositions, with city-specific clustering; suggesting distinct local environmental influences. However, such distinct clusters were not evident with the ARGs. A high proportion of potentially novel metagenome-assembled genomes (MAGs) (53-70%) were identified on reconstructing the microbial genomes from the metagenomic data. ARGs conferring resistance to antibiotics such as tetracyclines and beta-lactams showed higher association with MGEs in contrast to macrolide resistance genes. Microbial co-occurrence network analysis revealed a city-specific structure and higher contribution of ARGs from specific communities of microbes. These findings underscore the complex interplay between microbial diversity, ARG dissemination, and MGEs in wastewater environments, emphasizing the need for continued surveillance, for designing appropriate mitigation strategies towards curbing the spread of antimicrobial resistance.

Background: One Health is a collaborative approach that can be used to evaluate and enhance the fields of human, animal, and environmental health and to emphasize their sectoral interconnectedness. Empirical evaluation of the One Health performance of a country in the form of an index, provides direction for actionable interventions such as targeted funding, prioritized resource allocation, rigorous data management, and evidence-based policy decisions. These efforts, along with public engagement and awareness on disease management; environmental degradation, and preparedness toward disease outbreaks, contribute to strengthening global health security. Thus, developing a One Health Index (OHI) calculator for India is a significant step toward evidence-based One Health governance in the context of low-and middle-income countries. Objective: This study aimed to (1) develop a OHI Calculator for India using efficient and user-friendly weighting methods and demonstrate the calculation of the OHI; (2) develop India-specific datasets through secondary data collection from reliable data sources; and (3) determine data gaps for policy stewardship. Methods: We proposed a OHI calculator to measure the OHI from an Indian context by adopting the Global One Health Index framework that comprises 3 categories: 13 key indicators, 57 indicators, and 216 subindicators. Secondary data collection was conducted to create a dataset for specific to India from reliable sources. For measuring OHI, we demonstrated two mathematical weighting methods: an efficient expert-based rating using fuzzy extent analysis and a modified entropy-based weightage method. Results: We demonstrate the step-by-step OHI calculation by determining indicator scores using both fuzzy extent analysis and modified entropy-based weightage method. Through secondary data collection an India-specific dataset was created using reliable sources. For the datasets from India, data for 156/216 subindicators were available, while that for the remaining 60 indicators were unavailable. Further, a pilot correlation analysis was performed between 20 indicator scores and relevant budget allocations for the years 2022‐2023, 2023‐2024, and 2024‐2025. It was found that increases in the budget allocation across consecutive years improved indicator scores or better performance and vice versa. Conclusions: The demonstrated OHI calculator has the potential to serve as a governance tool while promoting data transparency and ethical data management. There is a need for a collaborative data federation approach to resolve data gaps, including incomplete, missing, or unavailable data. Further, the correlation analysis between budgetary allocation and performance of indicators provides empirical evidence for policymakers to improve intersectoral communication, multistakeholder engagement, concerted interventions, and informed policy decisions for resource allocation.

Organisms detect harmful environmental conditions and employ strategies to protect themselves. Additionally, they can communicate these experiences to the next generation or beyond through non-DNA sequence-based mechanisms, known as intergenerational or transgenerational epigenetic inheritance, respectively. Using a specialist larval parasitoid, Leptopilina boulardi, and its host, Drosophila melanogaster, we demonstrate that parental experience of parasitic stress leads to increased survivability in the immediate offspring of the host. Furthermore, we observe that this increased survivability in response to parasitic stress is transmitted transgenerationally when the grandparents, but not the parents, have been exposed to the parasitoid. This increased survivability is primarily inherited through male parents, with one form of effect being enhanced immune priming at the larval stage. Our study suggests that stress exposure during the pre-adult stage of the host provides lifetime benefits for its progeny, enabling them to better cope with future parasitic attacks.

Simple sequence repeats (SSRs) are tandem repetitions of 1-6 bp DNA motifs at least 12 bp long. Certain length-enriched SSRs function as enhancers/silencers, enhancer blockers and barriers in a mammalian cell line. However, whether SSRs have similar cis-regulatory functions in vivo and their underlying mechanisms are unknown. To address this, we looked for SSR-binding proteins and investigated if SSRs function as enhancer blockers in vivo . We developed a novel Drosophila assay to assess enhancer blocker activity in vivo and to circumvent the low throughput and position effects seen in traditional enhancer blocker assays. Our assay uses endogenous vestigial gene enhancers, which, when blocked, result in easily scorable wing phenotypes increasing throughput. The attP-attB-based recombination system to integrate test fragments at specific site avoids positional effects. Furthermore, using EMSAs and DNA pull-downs followed by LC-MS/MS, we show that SSRs bind to proteins in a sequence-specific manner and identify 33 unique SSR-binding proteins. One of these proteins, D1, was enriched in several SSRs, viz., AAT ₁₄ , AAAT ₁₀ , AAAAT ₈ , AATAT ₉ , AAAG ₁₃ and AAAAG ₁₁ . Using our novel vestigial in vivo enhancer blocker assay, we show for the first time that AT-rich SSRs function as enhancer blockers in a D1-dependent manner in Drosophila .

The detection of diverse pathogens and chemical compounds in community wastewater facilitates the monitoring of public health trends of emerging diseases and health conditions. During the COVID-19 pandemic, detection of viral RNA in wastewater assisted in monitoring the infection rates in different geographies and this drew attention to the method of wastewater-based epidemiology (WBE). In contrast to individual clinical testing, WBE offers an affordable, population-wide overview of the infection status of a community including asymptomatic carriers and those without access to healthcare facilities. To understand the community status of the infections caused by respiratory syncytial virus, SARS-CoV-2 and influenza virus subtypes in the monsoon season in Vijayawada city in the state of Andhra Pradesh in India, we longitudinally analyzed wastewater samples once a week between July-August 2024 from 7 sewage treatment plants in the city. The data obtained from the multiplexed RT-qPCR was used to calculate the viral loads in the wastewater samples at the city level and the proportion of population shedding the virus was estimated. All three viruses RSV A+B, SARS-CoV-2 and Influenza A+B were detected in the wastewater during our sampling period. Amongst the three viruses, the city had the largest load of SARS-CoV-2 RNA in the wastewater followed by RSV A+B and Influenza A+B. The study demonstrates the potential of utilizing wastewater surveillance system coupled to multiplexed RT-PCR to understand the population level dynamics of co-existence of multiple pathogens during the monsoon season in the urban settings.

BACKGROUND One Health is a collaborative approach that can be used to evaluate and enhance the sectors of human health, animal health and environmental health and emphasize their sectoral interconnectedness. Empirical evaluation of the one health performance of a country in the form of an index provides direction for actionable interventions such as targeted funding; prioritized resource allocation; rigorous data management and evidence-based policy decisions, amid other efforts such as public engagement and awareness of disease management; environmental degradation and preparedness towards disease outbreaks and thereby strengthening global health security. Thus, developing a One Health Index (OHI) Calculator for India is a significant step towards evidence-based one health governance in the context of low-and middle-income countries. OBJECTIVE a) To develop a One Health Index Calculator for India with efficient and ease of use weighting methods and demonstrate the calculation of the One Health Index. b) To develop India- country-specific datasets through secondary data collection from reliable data sources. c) To determine the data gaps for policy stewardship. METHODS We propose a One Health Index calculator to measure the One Health Index from an Indian context by adopting the Global One Health Index framework that comprises of 3 categories, 13 key indicators, 57 indicators and 216 sub-indicators. A secondary data collection was conducted to create a dataset for India from reliable sources. For measuring OHI, we have demonstrated two mathematical weightage methods, an efficient expert-based rating using Fuzzy Extent Analysis (FEA) and Modified Entropy-based Method (MEWM). RESULTS We demonstrate the step-by-step OHI calculation by determining indicator scores using both FEA and MEWM weightage methods. Through secondary data collection an India- country- specific dataset has been created from reliable sources. From the datasets for India, the indicator values for 156 out of 216 sub-indicators were found available, while there was lack of data for the remaining 60 indicators. Further, a pilot correlation analysis was performed between 20 indicator scores and the relevant budget allocations for the years 2022-2023, 2023-2024, and 2024-2025. It was found that the increase in the budget over consecutive years has shown an increase in indicator score or better performance and vice versa. CONCLUSIONS The demonstrated OHI calculator has the scope to serve as a governance tool, while promoting data transparency and ethical data management. There is a need for a collaborative data federation approach that can resolve data gaps in the form of incomplete, missing and unavailable data. Further the scope of performing correlation analysis between budgetary allocation and performance of indicators gives empirical evidence for policymakers to improve intersectoral communication, multi-stakeholder engagement, concerted interventions, and informed policy decisions for resource allocation.