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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.
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Prueba de COVID-19 , COVID-19 , Modelos Biológicos , SARS-CoV-2 , COVID-19/genética , COVID-19/mortalidad , COVID-19/transmisión , Femenino , Humanos , Masculino , SARS-CoV-2/genética , SARS-CoV-2/metabolismo , SARS-CoV-2/patogenicidad , Estados Unidos/epidemiologíaRESUMEN
The emergence of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in late 2020 and early 2021 raised alarm worldwide because of their potential for increased transmissibility and immune evasion. Elucidating the evolutionary and epidemiologic dynamics among novel SARS-CoV-2 variants is essential for understanding the trajectory of the coronavirus disease pandemic. We describe the interplay between B.1.1.7 (Alpha) and B.1.526 (Iota) variants in New York State, USA, during December 2020-April 2021 through phylogeographic analyses, space-time scan statistics, and cartographic visualization. Our results indicate that B.1.526 probably evolved in New York City, where it was displaced as the dominant lineage by B.1.1.7 months after its initial appearance. In contrast, B.1.1.7 became dominant earlier in regions with fewer B.1.526 infections. These results suggest that B.1.526 might have delayed the initial spread of B.1.1.7 in New York City. Our combined spatiotemporal methodologies can help disentangle the complexities of shifting SARS-CoV-2 variant landscapes.
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COVID-19 , SARS-CoV-2 , COVID-19/epidemiología , COVID-19/virología , Humanos , New York/epidemiología , Ciudad de Nueva York/epidemiología , Análisis Espacio-TemporalRESUMEN
Recently emerged SARS-CoV-2 variants have greater potential than earlier variants to cause vaccine breakthrough infections. During emergence of the Delta and Omicron variants, a matched case-control analysis used a viral genomic sequence dataset linked with demographic and vaccination information from New York, USA, to examine associations between virus lineage and patient vaccination status, patient age, vaccine type, and time since vaccination. Case-patients were persons infected with the emerging virus lineage, and controls were persons infected with any other virus lineage. Infections in fully vaccinated and boosted persons were significantly associated with the Omicron lineage. Odds of infection with Omicron relative to Delta generally decreased with increasing patient age. A similar pattern was observed with vaccination status during Delta emergence but was not significant. Vaccines offered less protection against Omicron, thereby increasing the number of potential hosts for emerging variants.
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COVID-19 , Vacunas Virales , Anticuerpos Antivirales , COVID-19/epidemiología , COVID-19/prevención & control , Vacunas contra la COVID-19 , Humanos , New York/epidemiología , SARS-CoV-2/genéticaRESUMEN
Of 379 severe acute respiratory syndrome coronavirus 2 samples collected in New York, USA, we detected 86 Omicron variant sequences containing Delta variant mutation P681R. Probable explanations were co-infection with 2 viruses or contamination/amplification artifact. Repeated library preparation with fewer cycles showed the P681R calls were artifactual. Unusual mutations should be interpreted with caution.
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COVID-19 , SARS-CoV-2 , Artefactos , Humanos , Mutación , New York/epidemiología , SARS-CoV-2/genéticaRESUMEN
FliA is a broadly conserved σ factor that directs transcription of genes involved in flagellar motility. We previously identified FliA-transcribed genes in Escherichia coli and Salmonella enterica serovar Typhimurium, and we showed that E. coli FliA transcribes many unstable, noncoding RNAs from intragenic promoters. Here, we show that FliA in S Typhimurium also directs the transcription of large numbers of unstable, noncoding RNAs from intragenic promoters, and we identify two previously unreported FliA-transcribed protein-coding genes. One of these genes, sdiA, encodes a transcription factor that responds to quorum-sensing signals produced by other bacteria. We show that FliA-dependent transcription of sdiA is required for SdiA activity, highlighting a regulatory link between flagellar motility and intercellular communication.IMPORTANCE Initiation of bacterial transcription requires association of a σ factor with the core RNA polymerase to facilitate sequence-specific recognition of promoter elements. FliA is a widely conserved σ factor that directs transcription of genes involved in flagellar motility. We previously showed that Escherichia coli FliA transcribes many unstable, noncoding RNAs from promoters within genes. Here, we demonstrate the same phenomenon in Salmonella Typhimurium. We also show that S Typhimurium FliA directs transcription of the sdiA gene, which encodes a transcription factor that responds to quorum-sensing signals produced by other bacteria. FliA-dependent transcription of sdiA is required for transcriptional control of SdiA target genes, highlighting a regulatory link between flagellar motility and intercellular communication.
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Proteínas Bacterianas/metabolismo , Proteínas Bacterianas/fisiología , Salmonella typhimurium/fisiología , Factor sigma/metabolismo , Transactivadores/fisiología , Proteínas Bacterianas/genética , ARN Polimerasas Dirigidas por ADN , Regulación Bacteriana de la Expresión Génica , Regiones Promotoras Genéticas , Unión Proteica , Percepción de Quorum , Factor sigma/genética , Transactivadores/genética , Transactivadores/metabolismoRESUMEN
Fast and effective methods are needed for sequencing of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome to track genetic mutations and to identify new and emerging variants during the ongoing pandemic. The objectives were to assess the performance of the SARS-CoV-2 AmpliSeq research panel and S5 plug-in analysis tools for whole-genome sequencing analysis of SARS-CoV-2 and to compare the results with those obtained with the MiSeq-based ARTIC analysis pipeline, using metrics such as depth, coverage, and concordance of single-nucleotide variant (SNV) calls. A total of 191 clinical specimens and a single cultured isolate were extracted and sequenced with AmpliSeq technology and analysis tools. Of the 191 clinical specimens, 83 (with threshold cycle [CT] values of 15.58 to 32.54) were also sequenced using an Illumina MiSeq-based method with the ARTIC analysis pipeline, for direct comparison. A total of 176 of the 191 clinical specimens sequenced on the S5XL system and prepared using the SARS-CoV-2 research panel had nearly complete coverage (>98%) of the viral genome, with an average depth of 5,031×. Similar coverage levels (>98%) were observed for 81/83 primary specimens that were sequenced with both methods tested. The sample with the lowest viral load (CT value of 32.54) achieved 89% coverage using the MiSeq method and failed to sequence with the AmpliSeq method. Consensus sequences produced by each method were identical for 81/82 samples in areas of equal coverage, with a single difference present in one sample. The AmpliSeq approach is as effective as the Illumina-based method using ARTIC v3 amplification for sequencing SARS-CoV-2 directly from patient specimens across a range of viral loads (CT values of 15.56 to 32.54 [median, 22.18]). The AmpliSeq workflow is very easily automated with the Ion Chef and S5 instruments and requires less training and experience with next-generation sequencing sample preparation than the Illumina workflow.
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COVID-19 , SARS-CoV-2 , Genoma Viral/genética , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , Pandemias , Secuenciación Completa del GenomaRESUMEN
The DNA binding of most Escherichia coli Transcription Factors (TFs) has not been comprehensively mapped, and few have models that can quantitatively predict binding affinity. We report the global mapping of in vivo DNA binding for 139 E. coli TFs using ChIP-Seq. We used these data to train BoltzNet, a novel neural network that predicts TF binding energy from DNA sequence. BoltzNet mirrors a quantitative biophysical model and provides directly interpretable predictions genome-wide at nucleotide resolution. We used BoltzNet to quantitatively design novel binding sites, which we validated with biophysical experiments on purified protein. We have generated models for 125 TFs that provide insight into global features of TF binding, including clustering of sites, the role of accessory bases, the relevance of weak sites, and the background affinity of the genome. Our paper provides new paradigms for studying TF-DNA binding and for the development of biophysically motivated neural networks.
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The emergence of recombinant viruses is a threat to public health, as recombination may integrate variant-specific features that together result in escape from treatment or immunity. The selective advantages of recombinant SARS-CoV-2 isolates over their parental lineages remain unknown. We identified a Delta-Omicron (AY.45-BA.1) recombinant in an immunosuppressed transplant recipient treated with monoclonal antibody Sotrovimab. The single recombination breakpoint is located in the spike N-terminal domain adjacent to the Sotrovimab binding site. While Delta and BA.1 are sensitive to Sotrovimab neutralization, the Delta-Omicron recombinant is highly resistant. To our knowledge, this is the first described instance of recombination between circulating SARS-CoV-2 variants as a functional mechanism of resistance to treatment and immune escape.
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Background: The emergence of recombinant viruses is a threat to public health. Recombination of viral variants may combine variant-specific features that together catalyze viral escape from treatment or immunity. The selective advantages of recombinant SARS-CoV-2 isolates over their parental lineages remain unknown. Methods: Multi-method amplicon and metagenomic sequencing of a clinical swab and the in vitro grown virus allowed for high-confidence detection of a novel recombinant variant. Mutational, phylogeographic, and structural analyses determined features of the recombinant genome and spike protein. Neutralization assays using infectious as well as pseudotyped viruses and point mutants thereof defined the recombinant's sensitivity to a panel of monoclonal antibodies and sera from vaccinated and/or convalescent individuals. Results: A novel Delta-Omicron SARS-CoV-2 recombinant was identified in an unvaccinated, immunosuppressed kidney transplant recipient treated with monoclonal antibody Sotrovimab. The recombination breakpoint is located in the spike N-terminal domain, adjacent to the Sotrovimab quaternary binding site, and results in a 5'-Delta AY.45 and a 3'-Omicron BA.1 mosaic spike protein. Delta and BA.1 are sensitive to Sotrovimab neutralization, whereas the Delta-Omicron recombinant is highly resistant to Sotrovimab, both with and without the RBD resistance mutation E340D. Conclusions: Recombination between circulating SARS-CoV-2 variants can functionally contribute to immune escape. It is critical to validate phenotypes of mosaic viruses and monitor immunosuppressed COVID-19 patients treated with monoclonal antibodies for the selection of recombinant and immune escape variants. (Funded by NYU, the National Institutes of Health, and others).
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SARS-CoV-2 variants shaped the second year of the COVID-19 pandemic and the discourse around effective control measures. Evaluating the threat posed by a new variant is essential for adapting response efforts when community transmission is detected. In this study, we compare the dynamics of two variants, Alpha and Iota, by integrating genomic surveillance data to estimate the effective reproduction number (Rt) of the variants. We use Connecticut, United States, in which Alpha and Iota co-circulated in 2021. We find that the Rt of these variants were up to 50% larger than that of other variants. We then use phylogeography to show that while both variants were introduced into Connecticut at comparable frequencies, clades that resulted from introductions of Alpha were larger than those resulting from Iota introductions. By monitoring the dynamics of individual variants throughout our study period, we demonstrate the importance of routine surveillance in the response to COVID-19.
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COVID-19 , SARS-CoV-2 , COVID-19/epidemiología , Genómica , Humanos , Pandemias , SARS-CoV-2/genética , Estados Unidos/epidemiologíaRESUMEN
Emerging SARS-CoV-2 variants have shaped the second year of the COVID-19 pandemic and the public health discourse around effective control measures. Evaluating the public health threat posed by a new variant is essential for appropriately adapting response efforts when community transmission is detected. However, this assessment requires that a true comparison can be made between the new variant and its predecessors because factors other than the virus genotype may influence spread and transmission. In this study, we develop a framework that integrates genomic surveillance data to estimate the relative effective reproduction number (R t ) of co-circulating lineages. We use Connecticut, a state in the northeastern United States in which the SARS-CoV-2 variants B.1.1.7 and B.1.526 co-circulated in early 2021, as a case study for implementing this framework. We find that the R t of B.1.1.7 was 6-10% larger than that of B.1.526 in Connecticut in the midst of a COVID-19 vaccination campaign. To assess the generalizability of this framework, we apply it to genomic surveillance data from New York City and observe the same trend. Finally, we use discrete phylogeography to demonstrate that while both variants were introduced into Connecticut at comparable frequencies, clades that resulted from introductions of B.1.1.7 were larger than those resulting from B.1.526 introductions. Our framework, which uses open-source methods requiring minimal computational resources, may be used to monitor near real-time variant dynamics in a myriad of settings.
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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 2500 COVID-19 cases associated with this variant have been detected in the US since December 2020, but the extent of establishment is relatively unknown. Using travel, genomic, and diagnostic data, we highlight the primary ports of entry for B.1.1.7 in the US and locations of possible underreporting of B.1.1.7 cases. 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.