ABSTRACT
Throughout the course of the ongoing SARS-CoV-2 pandemic there has been a need for approaches that enable rapid monitoring of public health using an unbiased and minimally invasive means. A major way this has been accomplished is through the regular assessment of wastewater samples by qRT-PCR to detect the prevalence of viral nucleic acid with respect to time and location. Further expansion of SARS-CoV-2 wastewater monitoring efforts to include the detection of variants of interest/concern through next-generation sequencing has enhanced the understanding of the SARS-CoV-2 outbreak. In this report, we detail the results of a collaborative effort between public health and metropolitan wastewater management authorities and the University of Louisville to monitor the SARS-CoV-2 pandemic through the monitoring of aggregate wastewater samples over a period of 28 weeks. Through the use of next-generation sequencing approaches the polymorphism signatures of Variants of Concern/Interest were evaluated to determine the likelihood of their prevalence within the community on the basis of their relative dominance within sequence datasets. Our data indicate that wastewater monitoring of water quality treatment centers and smaller neighborhood-scale catchment areas is a viable means by which the prevalence and genetic variation of SARS-CoV-2 within a metropolitan community of approximately one million individuals may be monitored, as our efforts detected the introduction and emergence of variants of concern in the city of Louisville. Importantly, these efforts confirm that regional emergence and spread of variants of interest/concern may be detected as readily in aggregate wastewater samples as compared to the individual wastewater sheds. Furthermore, the information gained from these efforts enabled targeted public health efforts including increased outreach to at-risk communities and the deployment of mobile or community-focused vaccination campaigns.
ABSTRACT
Key elements for viral pathogenesis include viral strains, viral load, co-infection, and host responses. Several studies analyzing these factors in the function of disease severity of have been published; however, no studies have shown how all of these factors interplay within a defined cohort. To address this important question, we sought to understand how these four key components interplay in a cohort of COVID-19 patients. We determined the viral loads and gene expression using high throughput sequencing and various virological methods. We found that viral loads in the upper respiratory tract in COVID-19 patients at an early phase of infection vary widely. While the majority of nasopharyngeal (NP) samples have a viral load lower than the limit of detection of infectious viruses, there are samples with an extraordinary amount of SARS-CoV-2 RNA and a high viral titer. No specific viral factors were identified that are associated with high viral loads. Host gene expression analysis showed that viral loads were strongly correlated with cellular antiviral responses. Interestingly, however, COVID-19 patients who experience mild symptoms have a higher viral load than those with severe complications, indicating that naso-pharyngeal viral load may not be a key factor of the clinical outcomes of COVID-19. The metagenomics analysis revealed that the microflora in the upper respiratory tract of COVID-19 patients with high viral loads were dominated by SARS-CoV-2, with a high degree of dysbiosis. Finally, we found a strong inverse correlation between upregulation of interferon responses and disease severity. Overall our study suggests that a high viral load in the upper respiratory tract may not be a critical factor for severe symptoms; rather, dampened antiviral responses may be a critical factor for a severe outcome from the infection.