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1.
PLoS Pathog ; 18(10): e1010636, 2022 10.
Artigo em Inglês | MEDLINE | ID: mdl-36240259

RESUMO

Wastewater-based epidemiology (WBE) is an effective way of tracking the appearance and spread of SARS-COV-2 lineages through communities. Beginning in early 2021, we implemented a targeted approach to amplify and sequence the receptor binding domain (RBD) of SARS-COV-2 to characterize viral lineages present in sewersheds. Over the course of 2021, we reproducibly detected multiple SARS-COV-2 RBD lineages that have never been observed in patient samples in 9 sewersheds located in 3 states in the USA. These cryptic lineages contained between 4 to 24 amino acid substitutions in the RBD and were observed intermittently in the sewersheds in which they were found for as long as 14 months. Many of the amino acid substitutions in these lineages occurred at residues also mutated in the Omicron variant of concern (VOC), often with the same substitutions. One of the sewersheds contained a lineage that appeared to be derived from the Alpha VOC, but the majority of the lineages appeared to be derived from pre-VOC SARS-COV-2 lineages. Specifically, several of the cryptic lineages from New York City appeared to be derived from a common ancestor that most likely diverged in early 2020. While the source of these cryptic lineages has not been resolved, it seems increasingly likely that they were derived from long-term patient infections or animal reservoirs. Our findings demonstrate that SARS-COV-2 genetic diversity is greater than what is commonly observed through routine SARS-CoV-2 surveillance. Wastewater sampling may more fully capture SARS-CoV-2 genetic diversity than patient sampling and could reveal new VOCs before they emerge in the wider human population.


Assuntos
COVID-19 , SARS-CoV-2 , Animais , Humanos , SARS-CoV-2/genética , Águas Residuárias , COVID-19/epidemiologia , Variação Genética
2.
medRxiv ; 2022 Jun 03.
Artigo em Inglês | MEDLINE | ID: mdl-35677072

RESUMO

Wastewater-based epidemiology (WBE) is an effective way of tracking the appearance and spread of SARS-COV-2 lineages through communities. Beginning in early 2021, we implemented a targeted approach to amplify and sequence the receptor binding domain (RBD) of SARS-COV-2 to characterize viral lineages present in sewersheds. Over the course of 2021, we reproducibly detected multiple SARS-COV-2 RBD lineages that have never been observed in patient samples in 9 sewersheds located in 3 states in the USA. These cryptic lineages contained between 4 to 24 amino acid substitutions in the RBD and were observed intermittently in the sewersheds in which they were found for as long as 14 months. Many of the amino acid substitutions in these lineages occurred at residues also mutated in the Omicron variant of concern (VOC), often with the same substitution. One of the sewersheds contained a lineage that appeared to be derived from the Alpha VOC, but the majority of the lineages appeared to be derived from pre-VOC SARS-COV-2 lineages. Specifically, several of the cryptic lineages from New York City appeared to be derived from a common ancestor that most likely diverged in early 2020. While the source of these cryptic lineages has not been resolved, it seems increasingly likely that they were derived from immunocompromised patients or animal reservoirs. Our findings demonstrate that SARS-COV-2 genetic diversity is greater than what is commonly observed through routine SARS-CoV-2 surveillance. Wastewater sampling may more fully capture SARS-CoV-2 genetic diversity than patient sampling and could reveal new VOCs before they emerge in the wider human population. Author Summary: During the COVID-19 pandemic, wastewater-based epidemiology has become an effective public health tool. Because many infected individuals shed SARS-CoV-2 in feces, wastewater has been monitored to reveal infection trends in the sewersheds from which the samples were derived. Here we report novel SARS-CoV-2 lineages in wastewater samples obtained from 3 different states in the USA. These lineages appeared in specific sewersheds intermittently over periods of up to 14 months, but generally have not been detected beyond the sewersheds in which they were initially found. Many of these lineages may have diverged in early 2020. Although these lineages share considerable overlap with each other, they have never been observed in patients anywhere in the world. While the wastewater lineages have similarities with lineages observed in long-term infections of immunocompromised patients, animal reservoirs cannot be ruled out as a potential source.

4.
Nat Commun ; 13(1): 635, 2022 02 03.
Artigo em Inglês | MEDLINE | ID: mdl-35115523

RESUMO

Tracking SARS-CoV-2 genetic diversity is strongly indicated because diversifying selection may lead to the emergence of novel variants resistant to naturally acquired or vaccine-induced immunity. To monitor New York City (NYC) for the presence of novel variants, we deep sequence most of the receptor binding domain coding sequence of the S protein of SARS-CoV-2 isolated from the New York City wastewater. Here we report detecting increasing frequencies of novel cryptic SARS-CoV-2 lineages not recognized in GISAID's EpiCoV database. These lineages contain mutations that had been rarely observed in clinical samples, including Q493K, Q498Y, E484A, and T572N and share many mutations with the Omicron variant of concern. Some of these mutations expand the tropism of SARS-CoV-2 pseudoviruses by allowing infection of cells expressing the human, mouse, or rat ACE2 receptor. Finally, pseudoviruses containing the spike amino acid sequence of these lineages were resistant to different classes of receptor binding domain neutralizing monoclonal antibodies. We offer several hypotheses for the anomalous presence of these lineages, including the possibility that these lineages are derived from unsampled human COVID-19 infections or that they indicate the presence of a non-human animal reservoir.


Assuntos
SARS-CoV-2/genética , SARS-CoV-2/isolamento & purificação , Águas Residuárias/virologia , Microbiologia da Água , Adulto , Idoso , Animais , Anticorpos Monoclonais/imunologia , Anticorpos Neutralizantes/imunologia , Anticorpos Antivirais/imunologia , COVID-19/virologia , Feminino , Variação Genética , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Masculino , Camundongos , Pessoa de Meia-Idade , Mutação , Cidade de Nova Iorque , Ligação Proteica , Ratos , Glicoproteína da Espícula de Coronavírus/imunologia , Adulto Jovem
5.
PLoS One ; 16(9): e0257454, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34555079

RESUMO

The following protocol describes our workflow for processing wastewater with the goal of detecting the genetic signal of SARS-CoV-2. The steps include pasteurization, virus concentration, RNA extraction, and quantification by RT-qPCR. We include auxiliary steps that provide new users with tools and strategies that will help troubleshoot key steps in the process. This protocol is one of the safest, cheapest, and most reproducible approaches for the detection of SARS-CoV-2 RNA in wastewater. Owing to a pasteurization step, it is safe for use in a BSL2 facility. In addition to making the protocol safe for the personnel involved, pasteurization had the added benefit of increasing the SARS-CoV-2 genetic signal. Furthermore, the RNA obtained using this protocol can be sequenced using both Sanger and Illumina sequencing technologies. The protocol was adopted by the New York City Department of Environmental Protection in August 2020 to monitor SARS-CoV-2 prevalence in wastewater in all five boroughs of the city. In the future, this protocol could be used to detect a variety of other clinically relevant viruses in wastewater and serve as a foundation of a wastewater surveillance strategy for monitoring community spread of known and emerging viral pathogens.


Assuntos
RNA Viral/genética , SARS-CoV-2/genética , Águas Residuárias/virologia , COVID-19/virologia , Custos e Análise de Custo/economia , Humanos , Cidade de Nova Iorque , Prevalência , Reação em Cadeia da Polimerase em Tempo Real/economia , Reação em Cadeia da Polimerase em Tempo Real/métodos
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