Nonsystematic Reporting Biases of the SARS-CoV-2 Variant Mu Could Impact Our Understanding of the Epidemiological Dynamics of Emerging Variants

Developing a timely and effective response to emerging SARS-CoV-2 variants of concern (VOCs) is of paramount public health importance. Global health surveillance does not rely on genomic data alone to identify concerning variants when they emerge. Instead, methods that utilize genomic data to estimate the epidemiological dynamics of emerging lineages have the potential to serve as an early warning system. However, these methods assume that genomic data are uniformly reported across circulating lineages. In this study, we analyze differences in reporting delays among SARS-CoV-2 VOCs as a plausible explanation for the timing of the global response to the former VOC Mu. Mu likely emerged in South America in mid-2020, where its circulation was largely confined. In this study, we demonstrate that Mu was designated as a VOC ∼1 year after it emerged and find that the reporting of genomic data for Mu differed significantly than that of other VOCs within countries, states, and individual laboratories. Our findings suggest that nonsystematic biases in the reporting of genomic data may have delayed the global response to Mu. Until they are resolved, the surveillance gaps that affected the global response to Mu could impede the rapid and accurate assessment of future emerging variants

Nasal Host Response-Based Screening for Undiagnosed Respiratory Viruses: A Pathogen Surveillance and Detection Study

BACKGROUND: Symptomatic patients who test negative for common viruses are an important possible source of unrecognised or emerging pathogens, but metagenomic sequencing of all samples is inefficient because of the low likelihood of finding a pathogen in any given sample. We aimed to determine whether nasopharyngeal CXCL10 screening could be used as a strategy to enrich for samples containing undiagnosed viruses. METHODS: In this pathogen surveillance and detection study, we measured CXCL10 concentrations from nasopharyngeal swabs from patients in the Yale New Haven health-care system, which had been tested at the Yale New Haven Hospital Clinical Virology Laboratory (New Haven, CT, USA). Patients who tested negative for a panel of respiratory viruses using multiplex PCR during Jan 23-29, 2017, or March 3-14, 2020, were included. We performed host and pathogen RNA sequencing (RNA-Seq) and analysis for viral reads on samples with CXCL10 higher than 1 ng/mL or CXCL10 testing and quantitative RT-PCR (RT-qPCR) for SARS-CoV-2. We used RNA-Seq and cytokine profiling to compare the host response to infection in samples that were virus positive (rhinovirus, seasonal coronavirus CoV-NL63, or SARS-CoV-2) and virus negative (controls). FINDINGS: During Jan 23-29, 2017, 359 samples were tested for ten viruses on the multiplex PCR respiratory virus panel (RVP). 251 (70%) were RVP negative. 60 (24%) of 251 samples had CXCL10 higher than 150 pg/mL and were identified for further analysis. 28 (47%) of 60 CXCL10-high samples were positive for seasonal coronaviruses. 223 (89%) of 251 samples were PCR negative for 15 viruses and, of these, CXCL10-based screening identified 32 (13%) samples for further analysis. Of these 32 samples, eight (25%) with CXCL10 concentrations higher than 1 ng/mL and sufficient RNA were selected for RNA-Seq. Microbial RNA analysis showed the presence of influenza C virus in one sample and revealed RNA reads from bacterial pathobionts in four (50%) of eight samples. Between March 3 and March 14, 2020, 375 (59%) of 641 samples tested negative for 15 viruses on the RVP. 32 (9%) of 375 samples had CXCL10 concentrations ranging from 100 pg/mL to 1000 pg/mL and four of those were positive for SARS-CoV-2. CXCL10 elevation was statistically significant, and a distinguishing feature was found in 28 (8%) of 375 SARS-CoV-2-negative samples versus all four SARS-CoV-2-positive samples (p=4·4 × 10 INTERPRETATION: These results confirm CXCL10 as a robust nasopharyngeal biomarker of viral respiratory infection and support host response-based screening followed by metagenomic sequencing of CXCL10-high samples as a practical approach to incorporate clinical samples into pathogen discovery and surveillance efforts. FUNDING: National Institutes of Health, the Hartwell Foundation, the Gruber Foundation, Fast Grants for COVID-19 research from the Mercatus Center, and the Huffman Family Donor Advised Fund

Lineage Abundance Estimation for SARS-CoV-2 in Wastewater Using Transcriptome Quantification Techniques

Effectively monitoring the spread of SARS-CoV-2 mutants is essential to efforts to counter the ongoing pandemic. Predicting lineage abundance from wastewater, however, is technically challenging. We show that by sequencing SARS-CoV-2 RNA in wastewater and applying algorithms initially used for transcriptome quantification, we can estimate lineage abundance in wastewater samples. We find high variability in signal among individual samples, but the overall trends match those observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in mutant prevalence in situations where clinical sequencing is unavailable

Comparative Usutu and West Nile virus transmission potential by local Culex pipiens mosquitoes in north-western Europe

Originating from Africa, Usutu virus (USUV) first emerged in Europe in 2001. This mosquito-borne flavivirus caused high mortality rates in its bird reservoirs, which strongly resembled the introduction of West Nile virus (WNV) in 1999 in the United States. Mosquitoes infected with USUV incidentally transmit the virus to other vertebrates, including humans, which can result in neuroinvasive disease. USUV and WNV co-circulate in parts of southern Europe, but the distribution of USUV extends into central and northwestern Europe. In the field, both viruses have been detected in the northern house mosquito Culex pipiens, of which the potential for USUV transmission is unknown. To understand the transmission dynamics and assess the potential spread of USUV, we determined the vector competence of C. pipiens for USUV and compared it with the well characterized WNV. We show for the first time that northwestern European mosquitoes are highly effective vectors for USUV, with infection rates of 11% at 18. °C and 53% at 23. °C, which are comparable with values obtained for WNV. Interestingly, at a high temperature of 28. °C, mosquitoes became more effectively infected with USUV (90%) than with WNV (58%), which could be attributed to barriers in the mosquito midgut. Small RNA deep sequencing of infected mosquitoes showed for both viruses a strong bias for 21-nucleotide small interfering (si)RNAs, which map across the entire viral genome both on the sense and antisense strand. No evidence for viral PIWI-associated RNA (piRNA) was found, suggesting that the siRNA pathway is the major small RNA pathway that targets USUV and WNV infection in C. pipiens mosquitoes

Accelerated SARS-CoV-2 Intrahost Evolution Leading to Distinct Genotypes During Chronic Infection

The chronic infection hypothesis for novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant emergence is increasingly gaining credence following the appearance of Omicron. Here, we investigate intrahost evolution and genetic diversity of lineage B.1.517 during a SARS-CoV-2 chronic infection lasting for 471 days (and still ongoing) with consistently recovered infectious virus and high viral genome copies. During the infection, we find an accelerated virus evolutionary rate translating to 35 nucleotide substitutions per year, approximately 2-fold higher than the global SARS-CoV-2 evolutionary rate. This intrahost evolution results in the emergence and persistence of at least three genetically distinct genotypes, suggesting the establishment of spatially structured viral populations continually reseeding different genotypes into the nasopharynx. Finally, we track the temporal dynamics of genetic diversity to identify advantageous mutations and highlight hallmark changes for chronic infection. Our findings demonstrate that untreated chronic infections accelerate SARS-CoV-2 evolution, providing an opportunity for the emergence of genetically divergent variants

Tracking smell loss to identify healthcare workers with SARS-CoV-2 infection

Introduction Healthcare workers (HCW) treating COVID-19 patients are at high risk for infection and may also spread infection through their contact with vulnerable patients. Smell loss has been associated with SARS-CoV-2 infection, but it is unknown whether monitoring for smell loss can be used to identify asymptomatic infection among high risk individuals. In this study we sought to determine if tracking smell sensitivity and loss using an at-home assessment could identify SARS-CoV-2 infection in HCW. Methods and findings We performed a prospective cohort study tracking 473 HCW across three months to determine if smell loss could predict SARS-CoV-2 infection in this high-risk group. HCW subjects completed a longitudinal, behavioral at-home assessment of olfaction with household items, as well as detailed symptom surveys that included a parosmia screening questionnaire, and real-time quantitative polymerase chain reaction testing to identify SARS-CoV-2 infection. Our main measures were the prevalence of smell loss in SARS-CoV-2-positive HCW versus SARS-CoV- 2-negative HCW, and timing of smell loss relative to SARS-CoV-2 test positivity. SARS-CoV-2 was identified in 17 (3.6%) of 473 HCW. HCW with SARS-CoV-2 infection were more likely to report smell loss than SARS-CoV-2-negative HCW on both the at-home assessment and the screening questionnaire (9/17, 53% vs 105/456, 23%, P < .01). 6/9 (67%) of SARS-CoV-2-positive HCW reporting smell loss reported smell loss prior to having a positive SARS-CoV-2 test, and smell loss was reported a median of two days before testing positive. Neurological symptoms were reported more frequently among SARS-CoV-2-positive HCW who reported smell loss compared to those without smell loss (9/9, 100% vs 3/8, 38%, P < .01). Conclusions In this prospective study of HCW, self-reported changes in smell using two different measures were predictive of SARS-CoV-2 infection. Smell loss frequently preceded a positive test and was associated with neurological symptoms

Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19.

Dysregulated immune responses against the SARS-CoV-2 virus are instrumental in severe COVID-19. However, the immune signatures associated with immunopathology are poorly understood. Here we use multi-omics single-cell analysis to probe the dynamic immune responses in hospitalized patients with stable or progressive course of COVID-19, explore V(D)J repertoires, and assess the cellular effects of tocilizumab. Coordinated profiling of gene expression and cell lineage protein markers shows that S100

Multiplex qPCR Discriminates Variants of Concern to Enhance Global Surveillance of SARS-CoV-2

With the emergence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants that may increase transmissibility and/or cause escape from immune responses, there is an urgent need for the targeted surveillance of circulating lineages. It was found that the B.1.1.7 (also 501Y.V1) variant, first detected in the United Kingdom, could be serendipitously detected by the Thermo Fisher TaqPath COVID-19 PCR assay because a key deletion in these viruses, spike Δ69-70, would cause a spike gene target failure (SGTF) result. However, a SGTF result is not definitive for B.1.1.7, and this assay cannot detect other variants of concern (VOC) that lack spike Δ69-70, such as B.1.351 (also 501Y.V2), detected in South Africa, and P.1 (also 501Y.V3), recently detected in Brazil. We identified a deletion in the ORF1a gene (ORF1a Δ3675-3677) in all 3 variants, which has not yet been widely detected in other SARS-CoV-2 lineages. Using ORF1a Δ3675-3677 as the primary target and spike Δ69-70 to differentiate, we designed and validated an open-source PCR assay to detect SARS-CoV-2 VOC. Our assay can be rapidly deployed in laboratories around the world to enhance surveillance for the local emergence and spread of B.1.1.7, B.1.351, and P.1

Comparative transmissibility of SARS-CoV-2 variants Delta and Alpha in New England, USA.

The SARS-CoV-2 Delta variant rose to dominance in mid-2021, likely propelled by an estimated 40%-80% increased transmissibility over Alpha. To investigate if this ostensible difference in transmissibility is uniform across populations, we partner with public health programs from all six states in New England in the United States. We compare logistic growth rates during each variant\u27s respective emergence period, finding that Delta emerged 1.37-2.63 times faster than Alpha (range across states). We compute variant-specific effective reproductive numbers, estimating that Delta is 63%-167% more transmissible than Alpha (range across states). Finally, we estimate that Delta infections generate on average 6.2 (95% CI 3.1-10.9) times more viral RNA copies per milliliter than Alpha infections during their respective emergence. Overall, our evidence suggests that Delta\u27s enhanced transmissibility can be attributed to its innate ability to increase infectiousness, but its epidemiological dynamics may vary depending on underlying population attributes and sequencing data availability

Comparative Transmissibility of SARS-CoV-2 Variants Delta and Alpha in New England, USA

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant quickly rose to dominance in mid-2021, displacing other variants, including Alpha. Studies using data from the United Kingdom and India estimated that Delta was 40-80% more transmissible than Alpha, allowing Delta to become the globally dominant variant. However, it was unclear if the ostensible difference in relative transmissibility was due mostly to innate properties of Delta\u27s infectiousness or differences in the study populations. To investigate, we formed a partnership with SARS-CoV-2 genomic surveillance programs from all six New England US states. By comparing logistic growth rates, we found that Delta emerged 37-163% faster than Alpha in early 2021 (37% Massachusetts, 75% New Hampshire, 95% Maine, 98% Rhode Island, 151% Connecticut, and 163% Vermont). We next computed variant-specific effective reproductive numbers and estimated that Delta was 58-120% more transmissible than Alpha across New England (58% New Hampshire, 68% Massachusetts, 76% Connecticut, 85% Rhode Island, 98% Maine, and 120% Vermont). Finally, using RT-PCR data, we estimated that Delta infections generate on average ∼6 times more viral RNA copies per mL than Alpha infections. Overall, our evidence indicates that Delta\u27s enhanced transmissibility could be attributed to its innate ability to increase infectiousness, but its epidemiological dynamics may vary depending on the underlying immunity and behavior of distinct populations