Genetic characterization of human herpesvirus type 1: Full-length genome sequence of strain obtained from an encephalitis case from India.

BACKGROUND & OBJECTIVES: Human herpes simplex virus 1 (HSV-1) is the most common cause of sporadic encephalitis in humans that contributes to >10 per cent of the encephalitis cases occurring worldwide. Availability of limited full genome sequences from a small number of isolates resulted in poor understanding of host and viral factors responsible for variable clinical outcome. In this study genetic relationship, extent and source of recombination using full-length genome sequence derived from a newly isolated HSV-1 isolate was studied in comparison with those sampled from patients with varied clinical outcome. METHODS: Full genome sequence of HSV-1 isolated from cerebrospinal fluid (CSF) of a patient with acute encephalitis syndrome (AES) by inoculation in baby hamster kidney-21 (BHK-21) cells was determined using next-generation sequencing (NGS) technology. Phylogenetic analysis of the newly generated sequence in comparison with 33 additional full-length genomes defined genetic relationship with worldwide distributed strains. The bootscan and similarity plot analysis defined recombination crossovers and similarities between newly isolated Indian HSV-1 with six Asian and a total of 34 worldwide isolated strains. RESULTS: Mapping of 376,332 reads amplified from HSV-1 DNA by NGS generated full-length genome of 151,024 bp from newly isolated Indian HSV-1. Phylogenetic analysis classified worldwide distributed strains into three major evolutionary lineages correlating to their geographic distribution. Lineage 1 containing strains were isolated from America and Europe; lineage 2 contained all the strains from Asian countries along with the North American KOS and RE strains whereas the South African isolates were distributed into two groups under lineage 3. Recombination analysis confirmed events of recombination in Indian HSV-1 genome resulting from mixing of different strains evolved in Asian countries. INTERPRETATION & CONCLUSIONS: Our results showed that the full-length genome sequence generated from an Indian HSV-1 isolate shared close genetic relationship with the American KOS and Chinese CR38 strains which belonged to the Asian genetic lineage. Recombination analysis of Indian isolate demonstrated multiple recombination crossover points throughout the genome. This full-length genome sequence amplified from the Indian isolate would be helpful to study HSV evolution, genetic basis of differential pathogenesis, host-virus interactions and viral factors contributing towards differential clinical outcome in human infections.

Wastewater surveillance of severe acute respiratory syndrome coronavirus-2 in open drains of two Indian megacities captures evolutionary lineage transitions: a zonation approach.

Wastewater-based environmental surveillance (WBES) has been proven as proxy tool for monitoring nucleic acids of pathogens shed by infected population before clinical outcomes. The poor sewershed network of low to middle-income countries (LMICs) leads to most of the wastewater flow through open drains. We studied the effectiveness of WBES using open drain samples to monitor the emergence of the SARS-CoV-2 variants in 2 megacities of India having dense population through zonation approach. Samples from 28 locations spanned into 5 zones of Pune region, Maharashtra, India, were collected on a weekly basis during October 2021 to July 2022. Out of 1115 total processed samples, 303 (~ 27%) tested positive for SARS-CoV-2. The periodical rise and fall in the percentage positivity of the samples was found to be in sync with the abundance of SARS-CoV-2 RNA and the reported COVID-19 active cases for Pune city. Sequencing of the RNA obtained from wastewater samples confirmed the presence of SARS-CoV-2. Of 337 sequences, lineage identification for 242 samples revealed 265 distinct SARS-CoV-2 variants including 10 highly transmissible ones. Importantly, transition from Delta to Omicron variant could be detected in wastewater samples 2 weeks prior to any clinically reported Omicron cases in India. Thus, this study demonstrates the usefulness of open drain samples for real-time monitoring of a viral pathogen's evolutionary dynamics and could be implemented in LMICs.

Genomic surveillance reveals early detection and transition of delta to omicron lineages of SARS-CoV-2 variants in wastewater treatment plants of Pune, India.

The COVID-19 pandemic has emphasized the urgency for rapid public health surveillance methods to detect and monitor the transmission of infectious diseases. The wastewater-based epidemiology (WBE) has emerged as a promising tool for proactive analysis and quantification of infectious pathogens within a population before clinical cases emerge. In the present study, we aimed to assess the trend and dynamics of SARS-CoV-2 variants using a longitudinal approach. Our objective included early detection and monitoring of these variants to enhance our understanding of their prevalence and potential impact. To achieve our goals, we conducted real-time quantitative polymerase chain reaction (RT-qPCR) and Illumina sequencing on 442 wastewater (WW) samples collected from 10 sewage treatment plants (STPs) in Pune city, India, spanning from November 2021 to April 2022. Our comprehensive analysis identified 426 distinct lineages representing 17 highly transmissible variants of SARS-CoV-2. Notably, fragments of Omicron variant were detected in WW samples prior to its first clinical detection in Botswana. Furthermore, we observed highly contagious sub-lineages of the Omicron variant, including BA.1 (~28%), BA.1.X (1.0-72%), BA.2 (1.0-18%), BA.2.X (1.0-97.4%) BA.2.12 (0.8-0.25%), BA.2.38 (0.8-1.0%), BA.2.75 (0.01-0.02%), BA.3 (0.09-6.3%), BA.4 (0.24-0.29%), and XBB (0.01-21.83%), with varying prevalence rates. Overall, the present study demonstrated the practicality of WBE in the early detection of SARS-CoV-2 variants, which could help track future outbreaks of SARS-CoV-2. Such approaches could be implicated in monitoring infectious agents before they appear in clinical cases.

A tale of two waves: Delineating diverse genomic and transmission landscapes driving the COVID-19 pandemic in Pune, India.

BACKGROUND: Modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Tracking variants of concern (VOC) is integral to understanding the evolution of SARS-CoV-2 in space and time, both at the local level and global context. This potentially generates actionable information when integrated with epidemiological outbreak data. METHODS: A city-wide network of researchers, clinicians, and pathology diagnostic laboratories was formed for genome surveillance of COVID-19 in Pune, India. The genomic landscapes of 10,496 sequenced samples of SARS-CoV-2 driving peaks of infection in Pune between December-2020 to March-2022, were determined. As a modern response to the pandemic, a "band of five" outbreak data analytics approach was used. This integrated the genomic data (Band 1) of the virus through molecular phylogenetics with key outbreak data including sample collection dates and case numbers (Band 2), demographics like age and gender (Band 3-4), and geospatial mapping (Band 5). RESULTS: The transmission dynamics of VOCs in 10,496 sequenced samples identified B.1.617.2 (Delta) and BA(x) (Omicron formerly known as B.1.1.529) variants as drivers of the second and third peaks of infection in Pune. Spike Protein mutational profiling during pre and post-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified a highly divergent BA.1 from Pune in addition to recombinant X lineages, XZ, XQ, and XM. CONCLUSIONS: The band of five outbreak data analytics approach, which integrates five different types of data, highlights the importance of a strong surveillance system with high-quality meta-data for understanding the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. These findings have important implications for pandemic preparedness and could be critical tools for understanding and responding to future outbreaks.