Early introductions and transmission of SARS-CoV-2 variant B.1.1.7 in the United States.

The emergence and spread of SARS-CoV-2 lineage B.1.1.7, first detected in the United Kingdom, has become a global public health concern because of its increased transmissibility. Over 2,500 COVID-19 cases associated with this variant have been detected in the United States (US) since December 2020, but the extent of establishment is relatively unknown. Using travel, genomic, and diagnostic data, we highlight that the primary ports of entry for B.1.1.7 in the US were in New York, California, and Florida. Furthermore, we found evidence for many independent B.1.1.7 establishments starting in early December 2020, followed by interstate spread by the end of the month. Finally, we project that B.1.1.7 will be the dominant lineage in many states by mid- to late March. Thus, genomic surveillance for B.1.1.7 and other variants urgently needs to be enhanced to better inform the public health response.

Coast-to-Coast Spread of SARS-CoV-2 during the Early Epidemic in the United States.

The novel coronavirus SARS-CoV-2 was first detected in the Pacific Northwest region of the United States in January 2020, with subsequent COVID-19 outbreaks detected in all 50 states by early March. To uncover the sources of SARS-CoV-2 introductions and patterns of spread within the United States, we sequenced nine viral genomes from early reported COVID-19 patients in Connecticut. Our phylogenetic analysis places the majority of these genomes with viruses sequenced from Washington state. By coupling our genomic data with domestic and international travel patterns, we show that early SARS-CoV-2 transmission in Connecticut was likely driven by domestic introductions. Moreover, the risk of domestic importation to Connecticut exceeded that of international importation by mid-March regardless of our estimated effects of federal travel restrictions. This study provides evidence of widespread sustained transmission of SARS-CoV-2 within the United States and highlights the critical need for local surveillance.

Diverse functional autoantibodies in patients with COVID-19.

COVID-19 manifests with a wide spectrum of clinical phenotypes that are characterized by exaggerated and misdirected host immune responses1-6. Although pathological innate immune activation is well-documented in severe disease1, the effect of autoantibodies on disease progression is less well-defined. Here we use a high-throughput autoantibody discovery technique known as rapid extracellular antigen profiling7 to screen a cohort of 194 individuals infected with SARS-CoV-2, comprising 172 patients with COVID-19 and 22 healthcare workers with mild disease or asymptomatic infection, for autoantibodies against 2,770 extracellular and secreted proteins (members of the exoproteome). We found that patients with COVID-19 exhibit marked increases in autoantibody reactivities as compared to uninfected individuals, and show a high prevalence of autoantibodies against immunomodulatory proteins (including cytokines, chemokines, complement components and cell-surface proteins). We established that these autoantibodies perturb immune function and impair virological control by inhibiting immunoreceptor signalling and by altering peripheral immune cell composition, and found that mouse surrogates of these autoantibodies increase disease severity in a mouse model of SARS-CoV-2 infection. Our analysis of autoantibodies against tissue-associated antigens revealed associations with specific clinical characteristics. Our findings suggest a pathological role for exoproteome-directed autoantibodies in COVID-19, with diverse effects on immune functionality and associations with clinical outcomes.

A ~40-kb flavi-like virus does not encode a known error-correcting mechanism.

It is commonly held that there is a fundamental relationship between genome size and error rate, manifest as a notional "error threshold" that sets an upper limit on genome sizes. The genome sizes of RNA viruses, which have intrinsically high mutation rates due to a lack of mechanisms for error correction, must therefore be small to avoid accumulating an excessive number of deleterious mutations that will ultimately lead to population extinction. The proposed exceptions to this evolutionary rule are RNA viruses from the order Nidovirales (such as coronaviruses) that encode error-correcting exonucleases, enabling them to reach genome lengths greater than 40 kb. The recent discovery of large-genome flavi-like viruses (Flaviviridae), which comprise genomes up to 27 kb in length yet seemingly do not encode exonuclease domains, has led to the proposal that a proofreading mechanism is required to facilitate the expansion of nonsegmented RNA virus genomes above 30 kb. Herein, we describe a ~40 kb flavi-like virus identified in a Haliclona sponge metatranscriptome that does not encode a known exonuclease. Structural analysis revealed that this virus may have instead captured cellular domains associated with nucleic acid metabolism that have not been previously found in RNA viruses. Phylogenetic inference placed this virus as a divergent pesti-like lineage, such that we have provisionally termed it "Maximus pesti-like virus." This virus represents an instance of a flavi-like virus achieving a genome size comparable to that of the Nidovirales and demonstrates that RNA viruses have evolved multiple solutions to overcome the error threshold.

Evidence for an ancient aquatic origin of the RNA viral order Articulavirales.

The emergence of previously unknown disease-causing viruses in mammals is in part the result of a long-term evolutionary process. Reconstructing the deep phylogenetic histories of viruses helps identify major evolutionary transitions and contextualizes the emergence of viruses in new hosts. We used a combination of total RNA sequencing and transcriptome data mining to extend the diversity and evolutionary history of the RNA virus order Articulavirales, which includes the influenza viruses. We identified instances of Articulavirales in the invertebrate phylum Cnidaria (including corals), constituting a novel and divergent family that we provisionally named the "Cnidenomoviridae." We further extended the evolutionary history of the influenza virus lineage by identifying four divergent, fish-associated influenza-like viruses, thereby supporting the hypothesis that fish were among the first hosts of influenza viruses. In addition, we substantially expanded the phylogenetic diversity of quaranjaviruses and proposed that this genus be reclassified as a family-the "Quaranjaviridae." Within this putative family, we identified a novel arachnid-infecting genus, provisionally named "Cheliceravirus." Notably, we observed a close phylogenetic relationship between the Crustacea- and Chelicerata-infecting "Quaranjaviridae" that is inconsistent with virus-host codivergence. Together, these data suggest that the Articulavirales has evolved over at least 600 million years, first emerging in aquatic animals. Importantly, the evolution of the Articulavirales was likely shaped by multiple aquatic-terrestrial transitions and substantial host jumps, some of which are still observable today.

Through an ecological lens: An ecosystem-based approach to zoonotic risk assessment: An ecosystem-based approach to zoonotic risk assessment.

Public health strategies to mitigate the emergence of novel pathogenic viruses should implement longitudinal metagenomic surveillance of ecosystems experiencing biodiversity changes to identify generalist viruses.

DengueSeq: a pan-serotype whole genome amplicon sequencing protocol for dengue virus.

BACKGROUND: The increasing burden of dengue virus on public health due to more explosive and frequent outbreaks highlights the need for improved surveillance and control. Genomic surveillance of dengue virus not only provides important insights into the emergence and spread of genetically diverse serotypes and genotypes, but it is also critical to monitor the effectiveness of newly implemented control strategies. Here, we present DengueSeq, an amplicon sequencing protocol, which enables whole-genome sequencing of all four dengue virus serotypes. RESULTS: We developed primer schemes for the four dengue virus serotypes, which can be combined into a pan-serotype approach. We validated both approaches using genetically diverse virus stocks and clinical specimens that contained a range of virus copies. High genome coverage (>95%) was achieved for all genotypes, except DENV2 (genotype VI) and DENV 4 (genotype IV) sylvatics, with similar performance of the serotype-specific and pan-serotype approaches. The limit of detection to reach 70% coverage was 10-100 RNA copies/µL for all four serotypes, which is similar to other commonly used primer schemes. DengueSeq facilitates the sequencing of samples without known serotypes, allows the detection of multiple serotypes in the same sample, and can be used with a variety of library prep kits and sequencing instruments. CONCLUSIONS: DengueSeq was systematically evaluated with virus stocks and clinical specimens spanning the genetic diversity within each of the four dengue virus serotypes. The primer schemes can be plugged into existing amplicon sequencing workflows to facilitate the global need for expanded dengue virus genomic surveillance.

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.

Real-time public health communication of local SARS-CoV-2 genomic epidemiology.

Genomic epidemiology can provide a unique, real-time understanding of SARS-CoV-2 transmission patterns. Yet the potential for genomic analyses to guide local policy and community-based behavioral decisions is limited because they are often oriented towards specially trained scientists and conducted on a national or global scale. Here, we propose a new paradigm: Phylogenetic analyses performed on a local level (municipal, county, or state), with results communicated in a clear, timely, and actionable manner to strengthen public health responses. We believe that presenting results rapidly, and tailored to a non-expert audience, can serve as a template for effective public health response to COVID-19 and other emerging viral diseases.

Detection of SARS-CoV-2 RNA by multiplex RT-qPCR.

The current quantitative reverse transcription PCR (RT-qPCR) assay recommended for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing in the United States requires analysis of 3 genomic targets per sample: 2 viral and 1 host. To simplify testing and reduce the volume of required reagents, we devised a multiplex RT-qPCR assay to detect SARS-CoV-2 in a single reaction. We used existing N1, N2, and RP primer and probe sets by the Centers for Disease Control and Prevention, but substituted fluorophores to allow multiplexing of the assay. The cycle threshold (Ct) values of our multiplex RT-qPCR were comparable to those obtained by the single assay adapted for research purposes. Low copy numbers (≥500 copies/reaction) of SARS-CoV-2 RNA were consistently detected by the multiplex RT-qPCR. Our novel multiplex RT-qPCR improves upon current single diagnostics by saving reagents, costs, time, and labor.

Longitudinal Immune Profiling of a Severe Acute Respiratory Syndrome Coronavirus 2 Reinfection in a Solid Organ Transplant Recipient.

BACKGROUND: The underlying immunologic deficiencies enabling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection are currently unknown. We describe deep longitudinal immune profiling of a transplant recipient hospitalized twice for coronavirus disease 2019 (COVID-19). METHODS: A 66-year-old male renal transplant recipient was hospitalized with COVID-19 March 2020 then readmitted to the hospital with COVID-19 233 days after initial diagnosis. Virologic and immunologic investigations were performed on samples from the primary and secondary infections. RESULTS: Whole viral genome sequencing and phylogenetic analysis revealed that viruses causing both infections were caused by distinct genetic lineages without evidence of immune escape mutations. Longitudinal comparison of cellular and humoral responses during primary SARS-CoV-2 infection revealed that this patient responded to the primary infection with low neutralization titer anti-SARS-CoV-2 antibodies that were likely present at the time of reinfection. CONCLUSIONS: The development of neutralizing antibodies and humoral memory responses in this patient failed to confer protection against reinfection, suggesting that they were below a neutralizing titer threshold or that additional factors may be required for efficient prevention of SARS-CoV-2 reinfection. Development of poorly neutralizing antibodies may have been due to profound and relatively specific reduction in naive CD4 T-cell pools. Seropositivity alone may not be a perfect correlate of protection in immunocompromised patients.

Evaluation of saliva self-collection devices for SARS-CoV-2 diagnostics.

BACKGROUND: There is an urgent need to expand testing for SARS-CoV-2 and other respiratory pathogens as the global community struggles to control the COVID-19 pandemic. Current diagnostic methods can be affected by supply chain bottlenecks and require the assistance of medical professionals, impeding the implementation of large-scale testing. Self-collection of saliva may solve these problems, as it can be completed without specialized training and uses generic materials. METHODS: We observed 30 individuals who self-collected saliva using four different collection devices and analyzed their feedback. Two of these devices, a funnel and bulb pipette, were used to evaluate at-home saliva collection by 60 individuals. SARS-CoV-2-spiked saliva samples were subjected to temperature cycles designed to simulate the conditions the samples might be exposed to during the summer and winter seasons and sensitivity of detection was evaluated. RESULTS: All devices enabled the safe, unsupervised self-collection of saliva. The quantity and quality of the samples received were acceptable for SARS-CoV-2 diagnostic testing, as determined by human RNase P detection. There was no significant difference in SARS-CoV-2 nucleocapsid gene (N1) detection between the freshly spiked samples and those incubated with the summer and winter profiles. CONCLUSION: We demonstrate inexpensive, generic, buffer free collection devices suitable for unsupervised and home saliva self-collection.

Effect of HIV Antibody VRC01 on Viral Rebound after Treatment Interruption.

BACKGROUND: The discovery of potent and broadly neutralizing antibodies (bNAbs) against human immunodeficiency virus (HIV) has made passive immunization a potential strategy for the prevention and treatment of HIV infection. We sought to determine whether passive administration of VRC01, a bNAb targeting the HIV CD4-binding site, can safely prevent or delay plasma viral rebound after the discontinuation of antiretroviral therapy (ART). METHODS: We conducted two open-label trials (AIDS Clinical Trials Group [ACTG] A5340 and National Institutes of Health [NIH] 15-I-0140) of the safety, side-effect profile, pharmacokinetic properties, and antiviral activity of VRC01 in persons with HIV infection who were undergoing interruption of ART. RESULTS: A total of 24 participants were enrolled, and one serious alcohol-related adverse event occurred. Viral rebound occurred despite plasma VRC01 concentrations greater than 50 µg per milliliter. The median time to rebound was 4 weeks in the A5340 trial and 5.6 weeks in the NIH trial. Study participants were more likely than historical controls to have viral suppression at week 4 (38% vs. 13%, P=0.04 by a two-sided Fisher's exact test in the A5340 trial; and 80% vs. 13%, P<0.001 by a two-sided Fisher's exact test in the NIH trial) but the difference was not significant at week 8. Analyses of virus populations before ART as well as before and after ART interruption showed that VRC01 exerted pressure on rebounding virus, resulting in restriction of recrudescent viruses and selection for preexisting and emerging antibody neutralization-resistant virus. CONCLUSIONS: VRC01 slightly delayed plasma viral rebound in the trial participants, as compared with historical controls, but it did not maintain viral suppression by week 8. In the small number of participants enrolled in these trials, no safety concerns were identified with passive immunization with a single bNAb (VRC01). (Funded by the National Institute of Allergy and Infectious Diseases and others; ACTG A5340 and NIH 15-I-0140 ClinicalTrials.gov numbers, NCT02463227 and NCT02471326 .).

A virus associated with the zoonotic pathogen Plasmodium knowlesi causing human malaria is a member of a diverse and unclassified viral taxon.

Apicomplexa are single-celled eukaryotes that can infect humans and include the mosquito-borne parasite Plasmodium, the cause of malaria. Increasing rates of drug resistance in human-only Plasmodium species are reducing the efficacy of control efforts and antimalarial treatments. There are also rising cases of P. knowlesi, the only zoonotic Plasmodium species that causes severe disease and death in humans. Thus, there is a need to develop additional innovative strategies to combat malaria. Viruses that infect non-Plasmodium spp. Disease-causing protozoa have been shown to affect pathogen life cycle and disease outcomes. However, only one virus (Matryoshka RNA virus 1) has been identified in Plasmodium, and none have been identified in zoonotic Plasmodium species. The rapid expansion of the known RNA virosphere using structure- and artificial intelligence-based methods suggests that this dearth is due to the divergent nature of RNA viruses that infect protozoa. We leveraged these newly uncovered data sets to explore the virome of human-infecting Plasmodium species collected in Sabah, east (Borneo) Malaysia. We identified a highly divergent RNA virus in two human-infecting P. knowlesi isolates that is related to the unclassified group 'ormycoviruses'. By characterising fifteen additional ormycoviruses identified in the transcriptomes of arthropods we show that this group of viruses exhibits a complex ecology at the arthropod-mammal interface. Through the application of artificial intelligence methods, we then demonstrate that the ormycoviruses are part of a diverse and unclassified viral taxon. This is the first observation of an RNA virus in a zoonotic Plasmodium species. By linking small-scale experimental data to large-scale virus discovery advances, we characterise the diversity and genomic architecture of an unclassified viral taxon. This approach should be used to further explore the virome of disease-causing Apicomplexa and better understand how protozoa-infecting viruses may affect parasite fitness, pathobiology, and treatment outcomes.

Incorporating variant frequencies data into short-term forecasting for COVID-19 cases and deaths in the USA: a deep learning approach.

BACKGROUND: Since the US reported its first COVID-19 case on January 21, 2020, the science community has been applying various techniques to forecast incident cases and deaths. To date, providing an accurate and robust forecast at a high spatial resolution has proved challenging, even in the short term. METHOD: Here we present a novel multi-stage deep learning model to forecast the number of COVID-19 cases and deaths for each US state at a weekly level for a forecast horizon of 1-4 weeks. The model is heavily data driven, and relies on epidemiological, mobility, survey, climate, demographic, and SARS-CoV-2 variant frequencies data. We implement a rigorous and robust evaluation of our model-specifically we report on weekly performance over a one-year period based on multiple error metrics, and explicitly assess how our model performance varies over space, chronological time, and different outbreak phases. FINDINGS: The proposed model is shown to consistently outperform the CDC ensemble model for all evaluation metrics in multiple spatiotemporal settings, especially for the longer-term (3 and 4 weeks ahead) forecast horizon. Our case study also highlights the potential value of variant frequencies data for use in short-term forecasting to identify forthcoming surges driven by new variants. INTERPRETATION: Based on our findings, the proposed forecasting framework improves upon the available state-of-the-art forecasting tools currently used to support public health decision making with respect to COVID-19 risk. FUNDING: This work was funded the NSF Rapid Response Research (RAPID) grant Award ID 2108526 and the CDC Contract #75D30120C09570.

Transcriptome mining extends the host range of the Flaviviridae to non-bilaterians.

The flavivirids (family Flaviviridae) are a group of positive-sense RNA viruses that include well-documented agents of human disease. Despite their importance and ubiquity, the timescale of flavivirid evolution is uncertain. An ancient origin, spanning millions of years, is supported by their presence in both vertebrates and invertebrates and by the identification of a flavivirus-derived endogenous viral element in the peach blossom jellyfish genome (Craspedacusta sowerbii, phylum Cnidaria), implying that the flaviviruses arose early in the evolution of the Metazoa. To date, however, no exogenous flavivirid sequences have been identified in these hosts. To help resolve the antiquity of the Flaviviridae, we mined publicly available transcriptome data across the Metazoa. From this, we expanded the diversity within the family through the identification of 32 novel viral sequences and extended the host range of the pestiviruses to include amphibians, reptiles, and ray-finned fish. Through co-phylogenetic analysis we found cross-species transmission to be the predominate macroevolutionary event across the non-vectored flavivirid genera (median, 68 per cent), including a cross-species transmission event between bats and rodents, although long-term virus-host co-divergence was still a regular occurrence (median, 23 per cent). Notably, we discovered flavivirus-like sequences in basal metazoan species, including the first associated with Cnidaria. This sequence formed a basal lineage to the genus Flavivirus and was closer to arthropod and crustacean flaviviruses than those in the tamanavirus group, which includes a variety of invertebrate and vertebrate viruses. Combined, these data attest to an ancient origin of the flaviviruses, likely close to the emergence of the metazoans 750-800 million years ago.

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.

Method versatility in RNA extraction-free PCR detection of SARS-CoV-2 in saliva samples.

Early in the pandemic, a simple, open-source, RNA extraction-free RT-qPCR protocol for SARS-CoV-2 detection in saliva was developed and made widely available. This simplified approach (SalivaDirect) requires only sample treatment with proteinase K prior to PCR testing. However, feedback from clinical laboratories highlighted a need for a flexible workflow that can be seamlessly integrated into their current health and safety requirements for the receiving and handling of potentially infectious samples. To address these varying needs, we explored additional pre-PCR workflows. We built upon the original SalivaDirect workflow to include an initial incubation step (95 °C for 30 min, 95 °C for 5 min or 65 °C for 15 min) with or without addition of proteinase K. The limit of detection for the workflows tested did not significantly differ from that of the original SalivaDirect workflow. When tested on de-identified saliva samples from confirmed COVID-19 individuals, these workflows also produced comparable virus detection and assay sensitivities, as determined by RT-qPCR analysis. Exclusion of proteinase K did not negatively affect the sensitivity of the assay. The addition of multiple heat pretreatment options to the SalivaDirect protocol increases the accessibility of this cost-effective SARS-CoV-2 test as it gives diagnostic laboratories the flexibility to implement the workflow which best suits their safety protocols.

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.