Boehm, A. B. | bioRxiv Science

bioRxiv2023

Tomato brown rugose fruit virus Mo gene is a novel microbial source tracking marker

Microbial source tracking (MST) identifies sources of fecal contamination in the environment using fecal host-associated markers. While there are numerous bacterial MST markers, there are few viral markers. Here we design and test novel viral MST markers based on tomato brown rugose fruit virus (ToBRFV) genomes. We assembled eight nearly complete genomes of ToBRFV from wastewater and stool samples from the San Francisco Bay Area in the United States of America. Next, we developed two novel probe-based RT-PCR assays based on conserved regions of the ToBRFV genome, and tested the markers sensitivities and specificities using human and non-human animal stool as well as wastewater. TheToBRFV markers are sensitive and specific; in human stool and wastewater, they are more prevalent and abundant than a currently used marker, the pepper mild mottle virus (PMMoV) coat protein (CP) gene. We applied the assays to detect fecal contamination in urban stormwater samples and found that the ToBRFV markers matched cross-assembly phage (crAssphage), an established viral MST marker, in prevalence across samples. Taken together, ToBRFV is a promising viral human-associated MST marker. ImportanceHuman exposure to fecal contamination in the environment can cause transmission of infectious diseases. Microbial source tracking (MST) can identify sources of fecal contamination so that contamination can be remediated and human exposures can be reduced. MST requires the use of fecal host-associated MST markers. Here we design and test novel MST markers from genomes of tomato brown rugose fruit virus (ToBRFV). The markers are sensitive and specific to human stool, and highly abundant in human stool and wastewater samples.

microbiology↗

bioRxiv2021

Transfer rate of enveloped and non-enveloped viruses between fingerpads and surfaces

Fomites can represent a reservoir for pathogens, which may be subsequently transferred from surfaces to skin. In this study we aim to understand how different factors (including virus type, surface type, time since last handwash, and direction of transfer) affect virus transfer rates, defined as the fraction of virus transferred, between fingerpads and fomites. To determine this, 360 transfer events were performed with 20 volunteers using Phi6 (a surrogate for enveloped viruses) and MS2 (a surrogate for non-enveloped viruses), and three clean surfaces (stainless steel, painted wood, and plastic). Considering all transfer events (all surfaces and both transfer directions combined), the mean transfer rates of Phi6 and MS2 were 0.17 and 0.26, respectively. Transfer of MS2 was significantly higher than Phi6 (P<0.05). Surface type was a significant factor that affected the transfer rate of Phi6: Phi6 is more easily transferred to and from stainless steel and plastic than to and from painted wood. Direction of transfer was a significant factor affecting MS2 transfer rates: MS2 is more easily transferred from surfaces to fingerpads than from fingerpads to surfaces. Data from these virus transfer events, and subsequent transfer rate distributions, provide information which can be used to refine quantitative microbial risk assessments. This study is the first to provide a large-scale data set of transfer events with a surrogate for enveloped viruses, which extends the reach of the study to the role of fomites in the transmission of human enveloped viruses like influenza and SARS-CoV-2. ImportanceThis study created the first large-scale data set for the transfer of enveloped viruses between skin and surfaces. The data set produced by this study provides information on modelling the distribution of enveloped and non-enveloped virus transfer rates, which can aid in the implementation of risk assessment models in the future. Additionally, enveloped and non enveloped viruses were applied to experimental surfaces in an equivalent matrix to avoid matrix effects, so results between different viral species can be directly compared without confounding effects of different matrices. Our results indicating how virus type, surface type, time since last handwash, and direction of transfer affect virus transfer rates can be used in decision-making processes to lower the risk of viral infection from transmission through fomites.

microbiology↗