Introduction
The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has had a significant global impact, leading to widespread health and economic challenges. Effective monitoring and surveillance of the virus are crucial for understanding its spread and evolution, as well as informing public health strategies. In resource-limited countries like Nepal, where access to clinical testing and genomic sequencing facilities may be limited, alternative approaches like environmental surveillance can play a vital role in tracking the pandemic.
Recent research has demonstrated the feasibility of using community-distributed rapid antigen tests (RATs) to sustain SARS-CoV-2 genomic surveillance. In this article, we present the findings of a study conducted in the Kathmandu Valley, Nepal, that leveraged sewage samples to establish a genomic-based environmental surveillance system for monitoring the spread and evolution of SARS-CoV-2.
Methodology
Sample Collection and Processing
The study was conducted in selected areas of the Kathmandu Valley, Nepal, from June to December 2020. Sewage samples were collected from 22 designated catchment sites across three wards (Balkumari, Sankhamul, and Gwarko) in the Lalitpur Metropolitan City. Previous research had mapped the sewage lines in these areas, allowing for targeted sample collection.
Grab samples (50 ml) were collected during the morning hours (7:00 AM to 9:00 AM) using an automated robotic pump. The samples were transported to the laboratory under a cold chain (2-8°C) and processed immediately. Each sample was pasteurized at 60°C for 90 minutes to inactivate any virus, followed by differential centrifugation to segregate the virus from the sewage sludge.
Viral Detection and Quantification
The viral RNA was extracted from the processed samples, and a diagnostic real-time PCR (RT-qPCR) assay targeting the envelope, nucleoprotein, and ORF1 genes was used to detect and quantify the presence of SARS-CoV-2. The viral load data was then converted to RNA copies per liter of sewage and used to estimate the prevalence of SARS-CoV-2 within the catchment areas, as described in previous studies.
Genomic Sequencing and Analysis
Samples that tested positive for SARS-CoV-2 were further processed for whole-genome sequencing using two different platforms: Oxford Nanopore Technologies’ (ONT) MinION and Illumina’s MiSeq. The ARTIC PCR protocol was used to amplify the SARS-CoV-2 genome, and the sequencing libraries were prepared accordingly for each platform.
The raw sequencing data was processed, and consensus genome sequences were generated using bioinformatics pipelines optimized for the respective sequencing technologies. The consensus sequences were then analyzed to identify mutations and lineages using the CoV-GLUE tool, which compares the sequences against the SARS-CoV-2 reference genome and the global GISAID database.
Results
Of the 22 sewage samples collected, SARS-CoV-2 was detected in 15 sites using the RT-qPCR assay. The average viral load across these positive sites was 40,613.83 RNA copies per ml, with the Gwarko ward having a higher average viral load of 72,712.5 copies per ml compared to Sankhamul’s 24,564.5 copies per ml.
Based on the viral load data, the estimated mean SARS-CoV-2 prevalence rates were 3.5 per 1,000 persons in the Sankhamul catchment area and 0.6 per 1,000 persons in the Gwarko catchment area. One site in Sankhamul (SA2) had the highest estimated prevalence of 11.36 per 1,000 persons, while a site in Gwarko (GW15) had the lowest estimated prevalence of 0.11 per 1,000 persons.
Whole-genome sequencing of the SARS-CoV-2 samples was successful for 12 out of the 15 positive sites. The consensus sequences obtained from the MinION and MiSeq platforms showed high similarity, with 99.96% to 100% identity. The lineage analysis revealed the circulation of B.1 (16.7%), B.1.36 (33.3%), and B.1.1 (50.0%) lineages in the Kathmandu Valley during the study period.
The genomic analysis identified a total of 47 unique nucleotide mutations across the 12 sequenced samples, with more than half being non-synonymous or deletion mutations. The most frequent mutation observed was the spike D614G, which has been associated with increased viral infectivity. Other notable mutations included S477N, A570S, and K1073N in the spike gene, as well as V55G, T223I, and P267L in the ORF3a gene.
Discussion
This study demonstrates the feasibility of using sewage-based environmental surveillance to track the spread and evolution of SARS-CoV-2 in a dense urban community like the Kathmandu Valley. The combination of RT-qPCR and whole-genome sequencing approaches provided valuable insights into the viral load, prevalence estimates, and circulating lineages within the community.
The detection of SARS-CoV-2 in 15 out of the 22 sampled sites, along with the estimated prevalence rates, highlights the potential of this approach to identify hotspots and guide targeted public health interventions. The genomic analysis revealed the circulation of several SARS-CoV-2 lineages, including some with notable mutations, underscoring the importance of ongoing surveillance to monitor viral evolution.
In resource-limited settings like Nepal, where access to clinical testing and advanced genomic sequencing facilities may be limited, environmental surveillance using sewage samples can offer a cost-effective and scalable alternative for tracking the pandemic. The use of portable sequencing platforms, such as the ONT MinION, can further enhance the feasibility of this approach by providing rapid, on-site genomic surveillance capabilities.
It is important to note that the quality of sequencing data from environmental samples may be variable due to factors such as sample degradation and low viral loads. In our study, while the consensus sequences obtained from the MinION and MiSeq platforms were highly similar, some samples had lower sequencing coverage, which limited the ability to assign lineages with high confidence. This highlights the need for careful interpretation and the potential value of complementing environmental surveillance with targeted clinical genomic sequencing to validate and corroborate the findings.
Stanley Park High School is committed to supporting the local community’s health and well-being. By sharing the insights from this study, we aim to raise awareness about the potential of sewage-based surveillance in monitoring the spread of SARS-CoV-2 and informing public health responses, particularly in resource-limited settings. We encourage our students and families to stay informed and engage with local health authorities to contribute to the collective effort in combating the COVID-19 pandemic.
