Crykey: Comprehensive Identification of SARS-CoV-2 Cryptic Mutations in Wastewater (preprint)

We present Crykey, a computational tool for identifying SARS-CoV-2 cryptic mutations from wastewater. While previous exist for identifying cryptic mutations in specific regions of the SARS-CoV-2 genome, there is a need for computational tools capable of tracking cryptic mutations across the entire genome and at scale. Crykey fills this gap and leverages the co-occurrence of single nucleotide variants on the same read combined with variant frequency information. We evaluated Crykey on SARS-CoV-2 sequences from 3175 wastewater samples and more than 14000 clinical samples. Our results are threefold, we show: 1) Crykey can accurately identify cryptic lineages that are rare or missing in existing databases ; 2) the emergence of cryptic lineage can be related to increased transmission rates in the communities, and 3) some cryptic lineages in wastewater mirror intra-host low frequency co-occurring variants in individuals. In summary, Crykey facilitates rapid and comprehensive identification of SARS-CoV-2 cryptic mutations in wastewater samples.

Olivar: fully automated and variant aware primer design for multiplex tiled amplicon sequencing of pathogen genomes (preprint)

Tiled amplicon sequencing has served as an essential tool for tracking the spread and evolution of SARS-CoV-2 in real-time directly from environmental and clinical samples. Over 14 million SARS-CoV-2 genomes are now available on GISAID, most sequenced and assembled via tiled amplicon sequencing. While computational tools for tiled amplicon design exist, they require downstream manual optimization both computationally and experimentally, which is slow, laborious, and costly. Here, we present Olivar, the first open-source computational tool capable of fully automating the design of tiled amplicons by integrating SNPs, non-specific amplification, etc. into a "risk score" for each single nucleotide of the target genome. Oli- var evaluates thousands sets of possible tiled amplicons and minimizes primer dimer in parallel. In a direct in-silico com- parison with PrimalScheme, we show that Olivar has fewer SNPs overlapping with primers and predicted PCR byproducts. We also compared Olivar head-to-head with ARTIC v4.1, the most widely used tiled amplicons for SARS-CoV-2 sequencing. We next tested Olivar on real wastewater samples and found that our automated approach had up to 3-fold higher map- ping rates compared to ARTIC v4.1 while retaining similar coverage. To the best of our knowledge, Olivar represents the first open-source, fully automated design tool that simultaneously evaluates and optimizes risks of known primer design issues for robust tiled amplicon sequencing. Olivar is available as a web application at https://olivar.rice.edu/. Olivar can also be installed locally as a command line tool with Bioconda. Source code, installation guide and usage are available at https: //gitlab.com/treangenlab/olivar.

Enhanced Detection of Recently Emerged SARS-CoV-2 Variants of Concern in Wastewater (preprint)

SARS-CoV-2 RNA shedding in stool enabled wastewater surveillance for the genetic material of the virus. With the emergence of novel variants of concern and interest it becomes increasingly important to track arrival and spread of these variants. However, most current approaches rely on the manually curated lists of mutations phenotypically associated with the variants of concern. The resulting data has many overlaps between distinct variants leading to less specific characterization of complex sample mixtures that result from wastewater monitoring. In our work we propose a simple and specific method for characterization of wastewater samples by introducing the concept of quasi-unique mutations. Our approach is data driven and results in earlier detection and higher resolution of variants of concern emergence patterns in wastewater data. ImportanceWastewater-based epidemiology has emerged as a powerful tool for public health response to the SARS-CoV-2 pandemic. As wastewater is a pooled, community sample of all persons contributing to the waste stream, there are several challenges in using sequencing information from wastewater samples to detect variants. Wastewater typically will consist of fragmented genomes from multiple, circulating variants. While it is straightforward to call the mutations present in a wastewater sample, it is more challenging to call the presence of variants that are defined by a set of characteristic mutations, particularly when mutations are shared among many circulating variants. Hence, we present a novel approach for screening for variants of concern in wastewater. Our computational approach introduces the concept of a "quasi-unique mutation" corresponding to a given PANGO lineage. We show that our method enables detection of the emergence of variants of concern in communities, providing a new approach for wastewater-based epidemiology of SARS-CoV-2.

Infectious SARS-CoV-2 in Exhaled Aerosols and Efficacy of Masks During Early Mild Infection (preprint)

BackgroundSARS-CoV-2 epidemiology implicates airborne transmission; aerosol infectiousness and impacts of masks and variants on aerosol shedding are not well understood. MethodsWe recruited COVID-19 cases to give blood, saliva, mid-turbinate and fomite (phone) swabs, and 30-minute breath samples while vocalizing into a Gesundheit-II, with and without masks at up to two visits two days apart. We quantified and sequenced viral RNA, cultured virus, and assayed sera for anti-spike and anti-receptor binding domain antibodies. ResultsWe enrolled 49 seronegative cases (mean days post onset 3.8 {+/-}2.1), May 2020 through April 2021. We detected SARS-CoV-2 RNA in 45% of fine ([≤]5 {micro}m), 31% of coarse (>5 {micro}m) aerosols, and 65% of fomite samples overall and in all samples from four alpha-variant cases. Masks reduced viral RNA by 48% (95% confidence interval [CI], 3 to 72%) in fine and by 77% (95% CI, 51 to 89%) in coarse aerosols; cloth and surgical masks were not significantly different. The alpha variant was associated with a 43-fold (95% CI, 6.6 to 280-fold) increase in fine aerosol viral RNA, compared with earlier viruses, that remained a significant 18-fold (95% CI, 3.4 to 92-fold) increase adjusting for viral RNA in saliva, swabs, and other potential confounders. Two fine aerosol samples, collected while participants wore masks, were culture-positive. ConclusionSARS-CoV-2 is evolving toward more efficient aerosol generation and loose-fitting masks provide significant but only modest source control. Therefore, until vaccination rates are very high, continued layered controls and tight-fitting masks and respirators will be necessary. Key PointsO_LICases exhale infectious viral aerosols C_LIO_LISARS-CoV-2 evolution favors more efficient aerosol generation. C_LIO_LILoose-fitting masks moderately reduce viral RNA aerosol. C_LIO_LIVentilation, filtration, UV air sanitation, and tight-fitting masks are needed to protect vulnerable people in public-facing jobs and indoor spaces. C_LI

Limited genomic reconstruction of SARS-CoV-2 transmission history within local epidemiological clusters (preprint)

A detailed understanding of how and when SARS-CoV-2 transmission occurs is crucial for designing effective prevention measures. Other than contact tracing, genome sequencing provides information to help infer who infected whom. However, the effectiveness of the genomic approach in this context depends on both (high enough) mutation and (low enough) transmission rates. Today, the level of resolution that we can obtain when describing SARS-CoV-2 outbreaks using just genomic information alone remains unclear. In order to answer this question, we sequenced 49 SARS-CoV-2 patient samples from ten local clusters for which partial epidemiological information was available, and inferred transmission history using genomic variants. Importantly, we obtained high-quality genomic data, sequencing each sample twice and using unique barcodes to exclude cross-sample contamination. Phylogenetic and cluster analyses showed that consensus genomes were generally sufficient to discriminate among independent transmission clusters. However, levels of intrahost variation were low, which prevented in most cases the unambiguous identification of direct transmission events. After filtering out recurrent variants across clusters, the genomic data were generally compatible with the epidemiological information but did not support specific transmission events over possible alternatives. We estimated the effective transmission bottleneck size to be 1-2 viral particles for sample pairs whose donor-recipient relationship was likely. Our analyses suggest that intrahost genomic variation in SARS-CoV-2 might be generally limited and that homoplasy and recurrent errors complicate identifying shared intrahost variants. Reliable reconstruction of direct SARS-CoV-2 transmission based solely on genomic data seems hindered by a slow mutation rate, potential convergent events, and technical artifacts. Detailed contact tracing seems essential in most cases to study SARS-CoV-2 transmission at high resolution.

The Great Deceiver: miR-2392's Hidden Role in Driving SARS-CoV-2 Infection (preprint)

MicroRNAs (miRNAs) are small non-coding RNAs involved in post-transcriptional gene regulation that have a major impact on many diseases and provides an exciting avenue towards antiviral therapeutics. From patient transcriptomic data, we have discovered a circulating miRNA, miR-2392, that is directly involved with SARS-CoV-2 machinery during host infection. Specifically, we found that miR-2392 was key in driving downstream suppression of mitochondrial gene expression, increasing inflammation, glycolysis, and hypoxia as well as promoting many symptoms associated with COVID-19 infection. We demonstrate miR-2392 is present in the blood and urine of COVID-19 patients tested, but not detected in COVID-19 negative patients. These findings indicate the potential for developing a novel, minimally invasive, COVID-19 detection method. Lastly, using both in vitro human and in vivo hamster models, we have developed a novel miRNA-based antiviral therapeutic targeting miR-2392 that significantly reduces SARS-CoV-2 viability and may potentially inhibit a COVID-19 disease state in the host.

Hidden genomic diversity of SARS-CoV-2: implications for qRT-PCR diagnostics and transmission (preprint)

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 clades that have spread throughout the world. In this study, we investigated over 7,000 SARS-CoV-2 datasets to unveil both intrahost and interhost diversity. Our intrahost and interhost diversity analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights iSNV and SNP similarity, albeit with high variability in C>T changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of small indels fuel the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.