Anvita Gupta Malhotra

Clinical surveillance for respiratory viruses such as severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and influenza A underestimates community transmission due to limited detection of asymptomatic infections and high resource requirements. Wastewater‐based surveillance (WWS) provides a cost‐effective, noninvasive approach for population‐level monitoring. This study evaluated the concordance between wastewater and clinical surveillance for detection and genetic characterization of SARS‐CoV‐2 and influenza A. Fortnightly wastewater samples ( n = 649) were collected from March 2022 to June 2023 across 11 sewage treatment plants in Bhopal, India. Samples were concentrated using polyethylene glycol precipitation, followed by RNA extraction and reverse transcription‐polymerase chain reaction (RT‐PCR) detection of SARS‐CoV‐2 and influenza A. RT‐PCR‐positive samples underwent viral subtyping and whole genome sequencing. Clinical surveillance data were analyzed concurrently, and temporal trends and phylogenetic relationships were assessed. SARS‐CoV‐2 RNA was detected in 10 influent wastewater samples during April 2023, coinciding with a surge in reported COVID‐19 cases. Influenza A RNA was detected in 32 wastewater samples, with trends aligning with seasonal influenza activity. Wastewater surveillance captured subtype transitions from H1N1pdm09 to H3N2 and identified persistent H1N1 circulation beyond its period of clinical predominance. Whole genome sequencing identified SARS‐CoV‐2 Omicron sub‐lineages XBB.1 and XBB.1.16, matching variants circulating in patients. Phylogenetic analyses showed close clustering of wastewater‐derived and clinical viral genomes, with no evidence of novel lineages. All treated effluent samples tested negative. WWS provided sensitive, near real‐time insights into community transmission of SARS‐CoV‐2 and influenza A, demonstrating strong temporal and genomic concordance with clinical data. WWS represents a valuable complementary surveillance tool for early outbreak detection, particularly in resource‐limited settings.

Background: Respiratory droplets are the main way in which the COVID-19 pandemic’s causal agent, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), spreads. Angiotensin-converting enzyme 2 (ACE2) receptors, especially in lung cells, allow the virus to enter host cells. However, ACE2 expression in intestinal cells has sparked worries about possible fecal transfer, particularly in poor-sanitation areas like India. Methods: Between July 2021 and July 2024, clinical (nasopharyngeal, saliva, and stool samples) and sewage samples were collected from outpatient departments and sewage treatment plants (STPs), respectively, from the high-population-density area under study in order to investigate SARS-CoV-2 transmission. Results: This proof-of-concept study analyzed clinical samples from n = 60 COVID-19-positive patients at a central Indian tertiary care hospital and n = 156 samples from hospital STPs. Variants of SARS-CoV-2 were found using qRT-PCR and Next-Generation Sequencing (NGS). Of the n = 37 qRT-PCR-positive patients who gave their assent, 30% had stool samples that tested positive for viral RNA. In 70% of positive NP and 65% of positive saliva samples, along with two stool samples from immunocompromised patients, the live virus was identified using Vero E6 cell lines. Although 18% of the tests reported qRT-PCR-positive results, no live virus was detected in sewage samples despite NGS validation. The detection of SARS-CoV-2 in the absence of confirmed clinical cases may indicate the silent circulation of the virus within the community, suggesting that sewage surveillance can serve as an early warning system before an outbreak occurs. Conclusions: These findings provide critical insights into the importance of continuous environmental surveillance, silent virus circulation, changes in viral epidemiology throughout the years, and strategies to mitigate coronavirus outbreaks.

Dengue fever remains a significant public health concern in tropical regions, including Central India, where outbreaks are frequent and associated with high morbidity and mortality. This study investigated the dynamics of dengue virus transmission and evolution in Central India from 2019 to 2023, focusing on the emergence of new strains and their impact on outbreak patterns. For this, 40 mosquito pools and 300 patient samples were recruited for the study. Phylogenetic and Bayesian evolutionary analyses performed on CPrM region and whole genome sequences generated by Sanger and Illumina sequencing, respectively, revealed the emergence and predominance of a novel DENV-2 genotype IV lineage III strain in the 2019 and 2023 outbreaks, which displaced the previously circulating DENV-1 genotype responsible for the 2016–2017 outbreak. Despite pre-existing DENV-1 neutralizing antibodies in the community (67 healthy volunteers), the novel DENV-2 strain exhibited higher viral loads and a greater reproduction number (R0), contributing to rapid disease spread. Molecular clock and Shannon entropy analyses suggest that DENV evolution occurred within the mosquito vector, driven by natural selection. Our findings highlight the importance of continuous DENV surveillance, including genetic characterization in both vectors and hosts, to understand viral evolution and predict future outbreaks. Rapid urbanization and inadequate sanitation in densely populated regions like India create ideal breeding grounds for mosquitoes, facilitating the introduction and establishment of novel DENV strains. Interrupting the vector–DENV–host cycle through targeted interventions is crucial for effective dengue control.

Despite advancements in treatment protocols, cancer is one of the leading cause of deaths worldwide. Therefore, there is a need to identify newer and personalized therapeutic targets along with screening technologies to combat cancer. With the advent of pan-omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, and lipidomics, the scientific community has witnessed an improved molecular and metabolomic understanding of various diseases, including cancer. In addition, three-dimensional (3-D) disease models have been efficiently utilized for understanding disease pathophysiology and as screening tools in drug discovery. An integrated approach utilizing pan-omics technologies and 3-D in vitro tumor models has led to improved understanding of the intricate network encompassing various signalling pathways and molecular cross-talk in solid tumors. In the present review, we underscore the current trends in omics technologies and highlight their role in understanding genotypic-phenotypic co-relation in cancer with respect to 3-D in vitro tumor models. We further discuss the challenges associated with omics technologies and provide our outlook on the future applications of these technologies in drug discovery and precision medicine for improved management of cancer. Graphical Abstract

Objective Microbiological confirmation of tuberculosis (TB) in pediatric cases is challenging due to its paucibacillary nature and difficulty in specimen collection. This study aimed to validate stool as an alternative sample for the diagnosis of pediatric pulmonary TB via Xpert MTB/RIF (Xpert) assay. Materials and Methods This cross-sectional study included 75 pediatric patients up to 10 years of age with signs and symptoms suggestive of TB. From each recruited patient, pulmonary and stool samples were collected in a sterile container. The collected samples were subjected to Ziehl-Neelsen staining, BACTEC MGIT 960 culture (MGIT), Xpert, and in-house multiplex polymerase chain reaction for TB diagnosis. Results About 13.33% (10/75) of the pulmonary samples and, of them, 50% (5/75) of the stool samples were positive by Xpert assay. The sensitivity and specificity of Xpert assay with stool and pulmonary samples were 50 (95% confidence interval [CI]: 18.71–81.29%) and 100% (95% CI: 94.48–100%), respectively. Conclusion The Xpert assay on stool samples showed limited sensitivity and good specificity in the diagnosis of pulmonary TB. Therefore, it can be proposed as an alternative screening sample to diagnose TB in pediatric cases for which getting a respiratory sample is extremely difficult. However, further studies with greater number of samples and multiple baseline variables are required to support our findings. Strategies to optimize stool Xpert assay should be performed to enhance the sensitivity of this method to detect Mycobacterium tuberculosis in children.

Setting: Tuberculosis Research Laboratory, Division of Clinical Microbiology and Molecular Medicine, Department of Laboratory Medicine, All India Institute of Medical Sciences, and the National Institute of Tuberculosis and Respiratory Diseases (NITRD), both situated in New Delhi.Objectives: We aimed to identify the distribution of various genotypes of M. tuberculosis among HIV-positive and HIV-negative patients suspected of having Tuberculosis, seen at the National Institute of Tuberculosis and Respiratory Diseases, New Delhi, which is a tertiary care dedicated TB hospital.Patients and methods: Genotyping by Spoligotyping and 24 loci MIRU-VNTR was performed and analyzed using SITVITWEB and MIRU-VNTRplus. Drug susceptibility patterns were also analyzed.Results: A total of 503 subjects who were PTB/EPTB suspected were recruited and 287 were culture positive. Among them, 276 had growth of Mycobacterium tuberculosis (MTB) and in 11 patients non-tuberculous mycobacteria (NTM) were grown. The isolation rate of NTM was predominantly from HIV positive [10 of 130 (7.6%)] patients. Of the total isolates of MTB, 156 (56.5%) were from HIV negative patients and 120 (43.5%) were from HIV positive patients. All 276 M. tuberculosis isolates were genotyped and tested for drug susceptibility patterns. The CAS genotype was most predominant [153 (55.4%)], followed by Beijing lineage [44 (15.9%)], East African India [25 (9.1%)] and others [54 (19.6%)]. Beijing genotype was significantly more common in HIV positive patients (22.5%) than in HIV negative patients (10.9%). In MIRU-VNTR analysis, clustering was found to be more frequent in CAS strains irrespective of HIV status. In the HIV positive group, spoligotyping could differentiate various genotypes in 90% of isolates and MIRU-VNTR analysis in 84.2% of isolates. The clustering of various MTB strains was more associated with drug resistance.Conclusion: The Beijing lineage was predominant in HIV-TB coinfected cases, even though the Central Asian Strain (CAS) was overall more predominant in the region.

Precise reasons for severe manifestation of SARS-CoV-2 remain unanswered, and efforts have been focused on respiratory system management. Demonstration of unequivocal presence of SARS-CoV-2 in vital body organs by cadaver autopsy was the only way to prove multi-organ involvement. Hence, the primary objective of the study was to determine presence of the SARS-CoV-2 in various organs of patients succumbing to SARS-CoV-2 infection. A total of 246 samples from different organs of 21 patients who died due to severe COVID-19 illness were investigated by qRT-PCR, and SARS-CoV-2 was detected in 181 (73.57%) samples and highest positivity of SARS-CoV-2 being (expectedly) found in nasopharynx (90.4%) followed by bilateral lungs (87.30%), peritoneal fluid (80%), pancreas (72.72%), bilateral kidneys (68.42%), liver (65%) and even in brain (47.2%). The deceased patients were categorized to three subgroups based upon the extent of organs in which SARS-CoV-2 was detected by qRT-PCR (high intensity ≥80%, intermediate intensity = 65–80% and low intensity ≤65% organs involvement). It was conclusively established that SARS-CoV-2 has the property of invasion beyond lungs and even crosses the blood–brain barrier, resulting in multi-system disease; this is probably the reason behind cytokine storm, though it is not clear whether organ damage is due to direct injury caused by the virus or result of inflammatory assault. Significant inverse correlation was found between the Ct value of lung samples and number of organs involved, implying that higher viral load in lungs is directly proportionate to involvement of extrapulmonary organs and patients with higher viral load in respiratory secretions should be monitored more closely for any warning signs and the treatment strategies should also address involvement of other organs for better outcome, because lungs, though the primary site of infection, are not the only organ system responsible for pathogenesis of systemic illness.