Enabling accurate and early detection of recently emerged SARS-CoV-2 variants of concern in wastewater.

As clinical testing declines, wastewater monitoring can provide crucial surveillance on the emergence of SARS-CoV-2 variant of concerns (VoCs) in communities. In this paper we present QuaID, a novel bioinformatics tool for VoC detection based on quasi-unique mutations. The benefits of QuaID are three-fold: (i) provides up to 3-week earlier VoC detection, (ii) accurate VoC detection (>95% precision on simulated benchmarks), and (iii) leverages all mutational signatures (including insertions & deletions).

Analysis of bronchoalveolar lavage fluid metatranscriptomes among patients with COVID-19 disease.

To better understand the potential relationship between COVID-19 disease and hologenome microbial community dynamics and functional profiles, we conducted a multivariate taxonomic and functional microbiome comparison of publicly available human bronchoalveolar lavage fluid (BALF) metatranscriptome samples amongst COVID-19 (n = 32), community acquired pneumonia (CAP) (n = 25), and uninfected samples (n = 29). We then performed a stratified analysis based on mortality amongst the COVID-19 cohort with known outcomes of deceased (n = 10) versus survived (n = 15). Our overarching hypothesis was that there are detectable and functionally significant relationships between BALF microbial metatranscriptomes and the severity of COVID-19 disease onset and progression. We observed 34 functionally discriminant gene ontology (GO) terms in COVID-19 disease compared to the CAP and uninfected cohorts, and 21 GO terms functionally discriminant to COVID-19 mortality (q < 0.05). GO terms enriched in the COVID-19 disease cohort included hydrolase activity, and significant GO terms under the parental terms of biological regulation, viral process, and interspecies interaction between organisms. Notable GO terms associated with COVID-19 mortality included nucleobase-containing compound biosynthetic process, organonitrogen compound catabolic process, pyrimidine-containing compound biosynthetic process, and DNA recombination, RNA binding, magnesium and zinc ion binding, oxidoreductase activity, and endopeptidase activity. A Dirichlet multinomial mixtures clustering analysis resulted in a best model fit using three distinct clusters that were significantly associated with COVID-19 disease and mortality. We additionally observed discriminant taxonomic differences associated with COVID-19 disease and mortality in the genus Sphingomonas, belonging to the Sphingomonadacae family, Variovorax, belonging to the Comamonadaceae family, and in the class Bacteroidia, belonging to the order Bacteroidales. To our knowledge, this is the first study to evaluate significant differences in taxonomic and functional signatures between BALF metatranscriptomes from COVID-19, CAP, and uninfected cohorts, as well as associating these taxa and microbial gene functions with COVID-19 mortality. Collectively, while this data does not speak to causality nor directionality of the association, it does demonstrate a significant relationship between the human microbiome and COVID-19. The results from this study have rendered testable hypotheses that warrant further investigation to better understand the causality and directionality of host-microbiome-pathogen interactions.

Infectious Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Exhaled Aerosols and Efficacy of Masks During Early Mild Infection.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemiology implicates airborne transmission; aerosol infectiousness and impacts of masks and variants on aerosol shedding are not well understood. METHODS: We recruited coronavirus disease 2019 (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 2 visits 2 days apart. We quantified and sequenced viral RNA, cultured virus, and assayed serum samples for anti-spike and anti-receptor binding domain antibodies. RESULTS: We enrolled 49 seronegative cases (mean days post onset 3.8 ±â€…2.1), May 2020 through April 2021. We detected SARS-CoV-2 RNA in 36% of fine (≤5 µm), 26% of coarse (>5 µm) aerosols, and 52% of fomite samples overall and in all samples from 4 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. CONCLUSIONS: SARS-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.

SeqScreen: accurate and sensitive functional screening of pathogenic sequences via ensemble learning.

The COVID-19 pandemic has emphasized the importance of accurate detection of known and emerging pathogens. However, robust characterization of pathogenic sequences remains an open challenge. To address this need we developed SeqScreen, which accurately characterizes short nucleotide sequences using taxonomic and functional labels and a customized set of curated Functions of Sequences of Concern (FunSoCs) specific to microbial pathogenesis. We show our ensemble machine learning model can label protein-coding sequences with FunSoCs with high recall and precision. SeqScreen is a step towards a novel paradigm of functionally informed synthetic DNA screening and pathogen characterization, available for download at www.gitlab.com/treangenlab/seqscreen .

Categorizing Sequences of Concern by Function To Better Assess Mechanisms of Microbial Pathogenesis.

To identify sequences with a role in microbial pathogenesis, we assessed the adequacy of their annotation by existing controlled vocabularies and sequence databases. Our goal was to regularize descriptions of microbial pathogenesis for improved integration with bioinformatic applications. Here, we review the challenges of annotating sequences for pathogenic activity. We relate the categorization of more than 2,750 sequences of pathogenic microbes through a controlled vocabulary called Functions of Sequences of Concern (FunSoCs). These allow for an ease of description by both humans and machines. We provide a subset of 220 fully annotated sequences in the supplemental material as examples. The use of this compact (∼30 terms), controlled vocabulary has potential benefits for research in microbial genomics, public health, biosecurity, biosurveillance, and the characterization of new and emerging pathogens.

Direct comparison of RT-ddPCR and targeted amplicon sequencing for SARS-CoV-2 mutation monitoring in wastewater.

Over the course of the COVID-19 pandemic, variants of SARS-CoV-2 have emerged that are more contagious and more likely to cause breakthrough infections. Targeted amplicon sequencing approach is a gold standard for identification and analysis of variants. However, when applied to environmental samples such as wastewater, it remains unclear how sensitive this method is for detecting variant-associated mutations in environmental samples. Here we directly compare a targeted amplicon sequencing approach (using ARTIC v3; hereafter referred to as sequencing) with RT-ddPCR quantification for the detection of five mutations that are characteristic of variants of concern (VoCs) in wastewater samples. In total, 547 wastewater samples were analyzed using both methods in parallel. When we observed positive mutation detections by RT-ddPCR, 42.6% of the detection events were missed by sequencing, due to negative detection or the limited read coverage at the mutation position. Further, when sequencing reported negative or depth-limited mutation detections, 26.7% of those events were instead positive detections by RT-ddPCR, highlighting the relatively poor sensitivity of sequencing. No or weak associations were observed between quantitative measurements of target mutations determined by RT-ddPCR and sequencing. These findings caution the use of quantitative measurements of SARS-CoV-2 variants in wastewater samples determined solely based on sequencing.

Rescuing low frequency variants within intra-host viral populations directly from Oxford Nanopore sequencing data.

Infectious disease monitoring on Oxford Nanopore Technologies (ONT) platforms offers rapid turnaround times and low cost. Tracking low frequency intra-host variants provides important insights with respect to elucidating within-host viral population dynamics and transmission. However, given the higher error rate of ONT, accurate identification of intra-host variants with low allele frequencies remains an open challenge with no viable computational solutions available. In response to this need, we present Variabel, a novel approach and first method designed for rescuing low frequency intra-host variants from ONT data alone. We evaluate Variabel on both synthetic data (SARS-CoV-2) and patient derived datasets (Ebola virus, norovirus, SARS-CoV-2); our results show that Variabel can accurately identify low frequency variants below 0.5 allele frequency, outperforming existing state-of-the-art ONT variant callers for this task. Variabel is open-source and available for download at: www.gitlab.com/treangenlab/variabel .

Limited genomic reconstruction of SARS-CoV-2 transmission history within local epidemiological clusters.

A detailed understanding of how and when severe acute respiratory syndrome coronavirus 2 (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 forty-nine SARS-CoV-2 patient samples from ten local clusters in NW Spain 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 one to two 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.

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

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.

Role of miR-2392 in driving SARS-CoV-2 infection.

MicroRNAs (miRNAs) are small non-coding RNAs involved in post-transcriptional gene regulation that have a major impact on many diseases and provide an exciting avenue toward antiviral therapeutics. From patient transcriptomic data, we determined that a circulating miRNA, miR-2392, is directly involved with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) machinery during host infection. Specifically, we show that miR-2392 is key in driving downstream suppression of mitochondrial gene expression, increasing inflammation, glycolysis, and hypoxia, as well as promoting many symptoms associated with coronavirus disease 2019 (COVID-19) infection. We demonstrate that miR-2392 is present in the blood and urine of patients positive for COVID-19 but is not present in patients negative for COVID-19. These findings indicate the potential for developing a minimally invasive COVID-19 detection method. Lastly, using in vitro human and in vivo hamster models, we design a miRNA-based antiviral therapeutic that targets miR-2392, significantly reduces SARS-CoV-2 viability in hamsters, and may potentially inhibit a COVID-19 disease state in humans.

Natural tannin extracts supplementation for COVID-19 patients (TanCOVID): a structured summary of a study protocol for a randomized controlled trial.

OBJECTIVES: This research aims to study the efficacy of tannins co-supplementation on disease duration, severity and clinical symptoms, microbiota composition and inflammatory mediators in SARS-CoV2 patients. TRIAL DESIGN: This is a prospective, double-blind, randomized, placebo-controlled, parallel-group trial to evaluate the efficacy of the administration of the dietary supplement ARBOX, a molecular blend of quebracho and chestnut tannins extract and Vit B12, in patients affected by COVID-19. PARTICIPANTS: 18 years of age or older, admitted to Hospital de Clinicas Jose de San Martin, Buenos Aires University (Argentina), meeting the definition of "COVID-19 confirmed case" ( https://www.argentina.gob.ar/salud/coronavirus-COVID-19/definicion-de-caso ). Inclusion Criteria Participants are eligible to be included in the study if the following criteria apply: 1. Any gender 2. ≥18 years old 3. Informed consent for participation in the study 4. Virological diagnosis of SARS-CoV-2 infection (real-time PCR) Exclusion Criteria Participants are excluded from the study if any of the following criteria apply: 1. Pregnant and lactating patients 2. Patients who cannot take oral therapy (with severe cognitive decline, assisted ventilation, or impaired consciousness) 3. Hypersensitivity to polyphenols 4. Patients already in ICU or requiring mechanical ventilation 5. Patients already enrolled in other clinical trials 6. Decline of consent INTERVENTION AND COMPARATOR: Experimental: TREATED ARM Participants will receive a supply of 28 -- 390 mg ARBOX capsules for 14 days. Patients will be supplemented with 2 capsules of ARBOX per day. Placebo Comparator: CONTROL ARM Participants will receive placebo supply for 14 days. The placebo will be administered with the identical dose as described for the test product. All trial participants will receive standard therapy, which includes: Antipyretics or Lopinavir / Ritonavir, Azithromycin and Hydroxychloroquine, as appropriate (treatment currently recommended by the department of Infectious Diseases of the Hospital de Clínicas that could undergo to modifications). In addition, if necessary: supplemental O2, non-invasive ventilation, antibiotic therapy. MAIN OUTCOMES: Primary Outcome Measures: Time to hospital discharge, defined as the time from first dose of ARBOX to hospital discharge [ Time Frame: Throughout the Study (Day 0 to Day 28) ] Secondary Outcome Measures: 28-day all-cause mortality [ Time Frame: Throughout the Study (Day 0 to Day 28) ]-proportion Invasive ventilation on day 28 [ Time Frame: Throughout the Study (Day 0 to Day 28) ]-proportion Level of inflammation parameters and cytokines [ Time Frame: day 1-14 ] -mean difference Difference in fecal intestinal microbiota composition and intestinal permeability [ Time Frame: day 1-14 ] Negativization of COVID-PCR at day 14 [ Time Frame: day 14 ]-proportion RANDOMIZATION: Potential study participants were screened for eligibility 24 hours prior to study randomization. Patients were randomly assigned via computer-generated random numbering (1:1) to receive standard treatment coupled with tannin or standard treatment plus placebo (control group). BLINDING (MASKING): Study personnel and participants are blinded to the treatment allocation, as both ARBOX and placebo were packed in identical containers. Thus, all the used capsules had identical appearance. NUMBERS TO BE RANDOMIZED (SAMPLE SIZE): Considering an alpha error of 5%, a power of 80% a sample size of 70 patients per branch was estimated. 140 patients in total. TRIAL STATUS: The protocol version is number V2, dated May 23, 2020. The first patient, first visit was on June 12, 2020; the recruitment end date was October 6, 2020. The protocol was not submitted earlier because the enrollment of some patients took place after the closure of the recruitment on the clinicaltrials platform. In fact, due to the epidemiological conditions, due to the decrease of the cases in Argentina during the summer period, the recruitment stopped t before reaching the number of 140 patients (as indicated in the webpage). However, since there was a new increase in cases, the enrolment was resumed in order to reach the number of patients initially planned in the protocol. The final participant was recruited on February 14, 2021. TRIAL REGISTRATION: ClinicalTrials.gov, number: NCT04403646 , registered on May 27th, 2020. FULL PROTOCOL: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

SARS-CoV-2 genomic diversity and the implications for qRT-PCR diagnostics and transmission.

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 lineages that have spread throughout the world. In this study, we investigated 129 RNA-seq data sets and 6928 consensus genomes to contrast the intra-host and inter-host diversity of SARS-CoV-2. Our analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights intra-host single nucleotide variant (iSNV) and SNP similarity, albeit with differences in C > U 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 insertions and deletions contribute to 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.

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

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.