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1.
Science ; 377(6609): 960-966, 2022 08 26.
Article in English | MEDLINE | ID: mdl-35881005

ABSTRACT

Understanding the circumstances that lead to pandemics is important for their prevention. We analyzed the genomic diversity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) early in the coronavirus disease 2019 (COVID-19) pandemic. We show that SARS-CoV-2 genomic diversity before February 2020 likely comprised only two distinct viral lineages, denoted "A" and "B." Phylodynamic rooting methods, coupled with epidemic simulations, reveal that these lineages were the result of at least two separate cross-species transmission events into humans. The first zoonotic transmission likely involved lineage B viruses around 18 November 2019 (23 October to 8 December), and the separate introduction of lineage A likely occurred within weeks of this event. These findings indicate that it is unlikely that SARS-CoV-2 circulated widely in humans before November 2019 and define the narrow window between when SARS-CoV-2 first jumped into humans and when the first cases of COVID-19 were reported. As with other coronaviruses, SARS-CoV-2 emergence likely resulted from multiple zoonotic events.


Subject(s)
COVID-19 , Pandemics , SARS-CoV-2 , Viral Zoonoses , Animals , COVID-19/epidemiology , COVID-19/transmission , COVID-19/virology , Computer Simulation , Genetic Variation , Genomics/methods , Humans , Molecular Epidemiology , Phylogeny , SARS-CoV-2/classification , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , Viral Zoonoses/epidemiology , Viral Zoonoses/virology
2.
Science ; 377(6609): 951-959, 2022 08 26.
Article in English | MEDLINE | ID: mdl-35881010

ABSTRACT

Understanding how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in 2019 is critical to preventing future zoonotic outbreaks before they become the next pandemic. The Huanan Seafood Wholesale Market in Wuhan, China, was identified as a likely source of cases in early reports, but later this conclusion became controversial. We show here that the earliest known COVID-19 cases from December 2019, including those without reported direct links, were geographically centered on this market. We report that live SARS-CoV-2-susceptible mammals were sold at the market in late 2019 and that within the market, SARS-CoV-2-positive environmental samples were spatially associated with vendors selling live mammals. Although there is insufficient evidence to define upstream events, and exact circumstances remain obscure, our analyses indicate that the emergence of SARS-CoV-2 occurred through the live wildlife trade in China and show that the Huanan market was the epicenter of the COVID-19 pandemic.


Subject(s)
COVID-19 , Pandemics , SARS-CoV-2 , Seafood , Viral Zoonoses , Animals , COVID-19/epidemiology , COVID-19/transmission , COVID-19/virology , China/epidemiology , Humans , SARS-CoV-2/isolation & purification , Seafood/virology , Viral Zoonoses/epidemiology , Viral Zoonoses/transmission , Viral Zoonoses/virology
3.
Nature ; 609(7925): 101-108, 2022 09.
Article in English | MEDLINE | ID: mdl-35798029

ABSTRACT

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing and/or sequencing capacity, which can also introduce biases1-3. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing4,5. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.


Subject(s)
COVID-19 , SARS-CoV-2 , Waste Water , Wastewater-Based Epidemiological Monitoring , COVID-19/epidemiology , COVID-19/transmission , COVID-19/virology , Humans , RNA, Viral/analysis , RNA, Viral/genetics , SARS-CoV-2/classification , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , Sequence Analysis, RNA , Waste Water/virology
4.
medRxiv ; 2022 Apr 04.
Article in English | MEDLINE | ID: mdl-35411350

ABSTRACT

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

5.
Nat Commun ; 12(1): 2044, 2021 04 06.
Article in English | MEDLINE | ID: mdl-33824330

ABSTRACT

Simple innate behavior is often described as hard-wired and largely inflexible. Here, we show that the avoidance of hot temperature, a simple innate behavior, contains unexpected plasticity in Drosophila. First, we demonstrate that hot receptor neurons of the antenna and their molecular heat sensor, Gr28B.d, are essential for flies to produce escape turns away from heat. High-resolution fly tracking combined with a 3D simulation of the thermal environment shows that, in steep thermal gradients, the direction of escape turns is determined by minute temperature differences between the antennae (0.1°-1 °C). In parallel, live calcium imaging confirms that such small stimuli reliably activate both peripheral thermosensory neurons and central circuits. Next, based on our measurements, we evolve a fly/vehicle model with two symmetrical sensors and motors (a "Braitenberg vehicle") which closely approximates basic fly thermotaxis. Critical differences between real flies and the hard-wired vehicle reveal that fly heat avoidance involves decision-making, relies on rapid learning, and is robust to new conditions, features generally associated with more complex behavior.


Subject(s)
Drosophila melanogaster/physiology , Taxis Response/physiology , Animals , Behavior, Animal , Choice Behavior , Drosophila melanogaster/genetics , Imaging, Three-Dimensional , Thermosensing/physiology
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