Impact of sample clarification by size exclusion on virus detection and diversity in wastewater-based epidemiology (preprint)

ABSTRACT The use of wastewater-based epidemiology (WBE) for early detection of virus circulation and response during the SARS-CoV-2 pandemic increased interest in and use of virus concentration protocols that are quick, scalable, and efficient. One such protocol involves sample clarification by size fractionation using either low-speed centrifugation to produce a clarified supernatant or membrane filtration to produce an initial filtrate depleted of solids, eukaryotes and bacterial present in wastewater (WW), followed by concentration of virus particles by ultrafiltration of the above. While this approach has been successful in identifying viruses from WW, it assumes that majority of the viruses of interest should be present in the fraction obtained by ultrafiltration of the initial filtrate, with negligible loss of viral particles and viral diversity. We used WW samples collected in a population of ∼700,000 in southwest USA between October 2019 and March 2021, targeting three non-enveloped viruses (enteroviruses [EV], canine picornaviruses [CanPV], and human adenovirus 41 [Ad41]), to evaluate whether size fractionation of WW prior to ultrafiltration leads to appreciable differences in the virus presence and diversity determined. We showed that virus presence or absence in WW samples in both portions (filter trapped solids [FTS] and filtrate) are not consistent with each other. We also found that in cases where virus was detected in both fractions, virus diversity (or types) captured either in FTS or filtrate were not consistent with each other. Hence, preferring one fraction of WW over the other can undermine the capacity of WBE to function as an early warning system and negatively impact the accurate representation of virus presence and diversity in a population.

Ubiquitin ligase RIPLET mediates polyubiquitination of RIG-I and LGP2 and regulates the innate immune responses to SARS-CoV-2 infection (preprint)

RIG-I, a cytoplasmic viral RNA sensor, is crucial for innate antiviral immune responses; however, there are controversies about the regulatory mechanism of RIG-I by several ubiquitin ligases and LGP2. This study revealed that the RIPLET ubiquitin ligase is a general activating factor for RIG-I signaling. In contrast, another ubiquitin ligase, TRIM25, activated RIG-I in a cell-type-specific manner. RIPLET and TRIM25 functions were modulated by accessory factors, such as ZCCH3C and NLRP12. Interestingly, we found an additional role of RIPLET in innate immune responses. RIPLET induced delayed polyubiquitination of LGP, resulting in the attenuation of excessive cytokine expression at the late phase. Moreover, RIPLET was involved in the innate immune responses against SARS-CoV-2 infection, a cause of the recent COVID-19 pandemic. Our data indicate that RIPLET fine-tunes innate immune responses via polyubiquitination of RIG-I and LGP2 against virus infection, including SARS-CoV-2.

A multiscale model suggests that a moderately weak inhibition of SARS-CoV-2 replication by type I IFN could accelerate the clearance of the virus (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible RNA virus that emerged in China at the end of 2019 and caused a large global outbreak. The interaction between SARS-CoV-2 and the immune response is complex because it is regulated by various processes taking part at the intracellular, tissue, and host levels. To gain a better understanding of the pathogenesis and progression of COVID-19, we formulate a multiscale model that integrate the main mechanisms which regulate the immune response to SARS-CoV-2 across multiple scales. The model describes the effect of type I interferon on the replication of SARS-CoV-2 inside cells. At the tissue level, we simulate the interactions between infected cells and immune cells using a hybrid agent-based representation. At the same time, we model the dynamics of virus spread and adaptive immune response in the host organism. After model validation, we demonstrate that a moderately weak inhibition of virus replication by type I IFN could elicit a strong adaptive immune response which accelerates the clearance of the virus. Furthermore, numerical simulations suggest that the deficiency of lymphocytes and not dendritic cells could lead to unfavourable outcomes in the elderly population.

High-throughput sequencing of SARS-CoV-2 in wastewater provides insights into circulating variants (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with >90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 5680 were "novel" SNVs that had not yet been identified in the global clinical-derived data as of 17th June 2020 (the day after our last wastewater sampling date). However, between 17th of June 2020 and 20th November 2020, almost half of the SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases.