Tracking cryptic SARS-CoV-2 lineages detected in NYC wastewater.
Tracking cryptic SARS-CoV-2 lineages detected in NYC wastewater.
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DOI:
10.1038/s41467-022-28246-3
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发表时间:
2022-02-03
影响因子:
16.6
通讯作者:
Dennehy JJ
中科院分区:
文献类型:
--
作者:
Smyth DS;Trujillo M;Gregory DA;Cheung K;Gao A;Graham M;Guan Y;Guldenpfennig C;Hoxie I;Kannoly S;Kubota N;Lyddon TD;Markman M;Rushford C;San KM;Sompanya G;Spagnolo F;Suarez R;Teixeiro E;Daniels M;Johnson MC;Dennehy JJ
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. To monitor the presence of novel SARS-CoV-2 variants in New York City, Smyth et al. perform deep-sequencing of the receptor binding domain of S protein in wastewater samples and find novel cryptic lineages containing mutations affecting ACE2-tropism and showing decreased neutralization by antibodies.
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影响因子:
64.8
作者:
Barnes CO;Jette CA;Abernathy ME;Dam KA;Esswein SR;Gristick HB;Malyutin AG;Sharaf NG;Huey-Tubman KE;Lee YE;Robbiani DF;Nussenzweig MC;West AP Jr;Bjorkman PJ
通讯作者:
Bjorkman PJ
影响因子:
48
作者:
Langmead, Ben;Salzberg, Steven L.
通讯作者:
Salzberg, Steven L.
影响因子:
5.4
作者:
Johnson MC;Lyddon TD;Suarez R;Salcedo B;LePique M;Graham M;Ricana C;Robinson C;Ritter DG
通讯作者:
Ritter DG
影响因子:
2.9
作者:
Kilgour, R. J.;Magle, S. B.;DiTullio, M.
通讯作者:
DiTullio, M.
影响因子:
17.1
作者:
Jones BE;Brown-Augsburger PL;Corbett KS;Westendorf K;Davies J;Cujec TP;Wiethoff CM;Blackbourne JL;Heinz BA;Foster D;Higgs RE;Balasubramaniam D;Wang L;Zhang Y;Yang ES;Bidshahri R;Kraft L;Hwang Y;Žentelis S;Jepson KR;Goya R;Smith MA;Collins DW;Hinshaw SJ;Tycho SA;Pellacani D;Xiang P;Muthuraman K;Sobhanifar S;Piper MH;Triana FJ;Hendle J;Pustilnik A;Adams AC;Berens SJ;Baric RS;Martinez DR;Cross RW;Geisbert TW;Borisevich V;Abiona O;Belli HM;de Vries M;Mohamed A;Dittmann M;Samanovic MI;Mulligan MJ;Goldsmith JA;Hsieh CL;Johnson NV;Wrapp D;McLellan JS;Barnhart BC;Graham BS;Mascola JR;Hansen CL;Falconer E
通讯作者:
Falconer E