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1.
Giovanetti, M.; Slavov, S. N.; Fonseca, V.; Wilkinson, E.; Tegally, H.; Patané, J. S. L.; Viala, V. L.; San, E. J.; Rodrigues, E. S.; Santos, E. V.; Aburjaile, F.; Xavier, J.; Fritsch, H.; Adelino, T. E. R.; Pereira, F.; Leal, A.; Iani, F. C. M.; de Carvalho Pereira, G.; Vazquez, C.; Sanabria, G. M. E.; Oliveira, E. C.; Demarchi, L.; Croda, J.; Dos Santos Bezerra, R.; Paola Oliveira de Lima, L.; Martins, A. J.; Renata Dos Santos Barros, C.; Marqueze, E. C.; de Souza Todao Bernardino, J.; Moretti, D. B.; Brassaloti, R. A.; de Lello Rocha Campos Cassano, R.; Mariani, Pdsc, Kitajima, J. P.; Santos, B.; Proto-Siqueira, R.; Cantarelli, V. V.; Tosta, S.; Nardy, V. B.; Reboredo de Oliveira da Silva, L.; Gómez, M. K. A.; Lima, J. G.; Ribeiro, A. A.; Guimarães, N. R.; Watanabe, L. T.; Barbosa Da Silva, L.; da Silva Ferreira, R.; da Penha, M. P. F.; Ortega, M. J.; de la Fuente, A. G.; Villalba, S.; Torales, J.; Gamarra, M. L.; Aquino, C.; Figueredo, G. P. M.; Fava, W. S.; Motta-Castro, A. R. C.; Venturini, J.; do Vale Leone de Oliveira, S. M.; Gonçalves, C. C. M.; do Carmo Debur Rossa, M.; Becker, G. N.; Giacomini, M. P.; Marques, N. Q.; Riediger, I. N.; Raboni, S.; Mattoso, G.; Cataneo, A. D.; Zanluca, C.; Duarte Dos Santos, C. N.; Assato, P. A.; Allan da Silva da Costa, F.; Poleti, M. D.; Lesbon, J. C. C.; Mattos, E. C.; Banho, C. A.; Sacchetto, L.; Moraes, M. M.; Grotto, R. M. T.; Souza-Neto, J. A.; Nogueira, M. L.; Fukumasu, H.; Coutinho, L. L.; Calado, R. T.; Neto, R. M.; Bispo de Filippis, A. M.; Venancio da Cunha, R.; Freitas, C.; Peterka, C. R. L.; de Fátima Rangel Fernandes, C.; Navegantes, W.; do Carmo Said, R. F.; Campelo de, A. E. Melo C. F.; Almiron, M.; Lourenço, J.; de Oliveira, T.; Holmes, E. C.; Haddad, R.; Sampaio, S. C.; Elias, M. C.; Kashima, S.; Junior de Alcantara, L. C.; Covas, D. T..
Nat Microbiol ; 2022.
Article in English | PubMed | ID: covidwho-1991610

ABSTRACT

The high numbers of COVID-19 cases and deaths in Brazil have made Latin America an epicentre of the pandemic. SARS-CoV-2 established sustained transmission in Brazil early in the pandemic, but important gaps remain in our understanding of virus transmission dynamics at a national scale. We use 17,135 near-complete genomes sampled from 27 Brazilian states and bordering country Paraguay. From March to November 2020, we detected co-circulation of multiple viral lineages that were linked to multiple importations (predominantly from Europe). After November 2020, we detected large, local transmission clusters within the country. In the absence of effective restriction measures, the epidemic progressed, and in January 2021 there was emergence and onward spread, both within and abroad, of variants of concern and variants under monitoring, including Gamma (P.1) and Zeta (P.2). We also characterized a genomic overview of the epidemic in Paraguay and detected evidence of importation of SARS-CoV-2 ancestor lineages and variants of concern from Brazil. Our findings show that genomic surveillance in Brazil enabled assessment of the real-time spread of emerging SARS-CoV-2 variants.

2.
Acs Es&T Water ; : 11, 2022.
Article in English | Web of Science | ID: covidwho-1927041

ABSTRACT

Wastewater-based epidemiology is now widely used as an indirect tool to monitor the spread of SARS-CoV-2. In this study, five different sample matrices representing diverse phases of the wastewater treatment process were collected during the second wave of SARS-CoV-2 from two wastewater treatment plants (WWTPs) serving the Civil Hospital and Sacca Fisola island in Venice, Italy. Positive SARS-CoV-2 detections occurred at both WWTPs, and data on viral genome detection rate and quantification suggest that the pellet (i.e., the particulate resulting from the influent) is a sensitive matrix that permits reliable assessment of infection prevalence while reducing time to results. On the contrary, analysis of post-treatment matrices provides evidence of the decontamination efficacy of both WWTPs. Finally, direct sequencing of wastewater samples enabled us to identify B.1.177 and B.1.160 as the prevalent SARS-CoV-2 lineages circulating in Venice at the time of sampling. This study confirmed the suitability of wastewater testing for studying SARS-CoV-2 circulation and established a simplified workflow for the prompt detection and characterization of the virus.

3.
Giovanetti, M.; Slavov, S. N.; Fonseca, V.; Wilkinson, E.; Tegally, H.; Patané, J. S. L.; Viala, V. L.; San, J. E.; Rodrigues, E. S.; Vieira Santos, E.; Aburjaile, F.; Xavier, J.; Fritsch, H.; Ribeiro Adelino, T. E.; Pereira, F.; Leal, A.; Campos de Melo Iani, F.; de Carvalho Pereira, G.; Vazquez, C.; Mercedes Estigarribia Sanabria, G.; de Oliveira, E. C.; Demarchi, L.; Croda, J.; Dos Santos Bezerra, R.; Oliveira de Lima, L. P.; Martins, A. J.; Dos Santos Barros, C. R.; Marqueze, E. C.; de Souza Todao Bernardino, J.; Moretti, D. B.; Brassaloti, R. A.; de Lello Rocha Campos Cassano, R.; Drummond Sampaio Corrêa Mariani, P.; Kitajima, J. P.; Santos, B.; Proto-Siqueira, R.; Cantarelli, V. V.; Tosta, S.; Brandão Nardy, V.; Reboredo de Oliveira da Silva, L.; Astete Gómez, M. K.; Lima, J. G.; Ribeiro, A. A.; Guimarães, N. R.; Watanabe, L. T.; Barbosa Da Silva, L.; da Silva Ferreira, R.; MP, F. da Penha, Ortega, M. J.; Gómez de la Fuente, A.; Villalba, S.; Torales, J.; Gamarra, M. L.; Aquino, C.; Martínez Figueredo, G. P.; Fava, W. S.; Motta-Castro, A. R. C.; Venturini, J.; do Vale Leone de Oliveira, S. M.; Cavalheiro Maymone Gonçalves, C.; Debur Rossa, M. D. C.; Becker, G. N.; Presibella, M. M.; Marques, N. Q.; Riediger, I. N.; Raboni, S.; Coelho, G. M.; Cataneo, A. H. D.; Zanluca, C.; Dos Santos, C. N. D.; Assato, P. A.; Allan da Silva da Costa, F.; Poleti, M. D.; Chagas Lesbon, J. C.; Mattos, E. C.; Banho, C. A.; Sacchetto, L.; Moraes, M. M.; Tommasini Grotto, R. M.; Souza-Neto, J. A.; Nogueira, M. L.; Fukumasu, H.; Coutinho, L. L.; Calado, R. T.; Neto, R. M.; Bispo de Filippis, A. M.; Venancio da Cunha, R.; Freitas, C.; Leonel Peterka, C. R.; Rangel Fernandes, C. F.; de Araújo, W. N.; do Carmo Said, R. F.; Almiron, M.; Campelo de Albuquerque, E. Melo C. F.; Lourenço, J.; de Oliveira, T.; Holmes, E. C.; Haddad, R.; Sampaio, S. C.; Elias, M. C.; Kashima, S.; de Alcantara, L. C. J.; Covas, D. T..
PubMed; 2022.
Preprint in English | PubMed | ID: ppcovidwho-332259

ABSTRACT

Brazil has experienced some of the highest numbers of COVID-19 cases and deaths globally and from May 2021 made Latin America a pandemic epicenter. Although SARS-CoV-2 established sustained transmission in Brazil early in the pandemic, important gaps remain in our understanding of virus transmission dynamics at the national scale. Here, we describe the genomic epidemiology of SARS-CoV-2 using near-full genomes sampled from 27 Brazilian states and a bordering country - Paraguay. We show that the early stage of the pandemic in Brazil was characterised by the co-circulation of multiple viral lineages, linked to multiple importations predominantly from Europe, and subsequently characterized by large local transmission clusters. As the epidemic progressed under an absence of effective restriction measures, there was a local emergence and onward international spread of Variants of Concern (VOC) and Variants Under Monitoring (VUM), including Gamma (P.1) and Zeta (P.2). In addition, we provide a preliminary genomic overview of the epidemic in Paraguay, showing evidence of importation from Brazil. These data reinforce the usefulness and need for the implementation of widespread genomic surveillance in South America as a toolkit for pandemic monitoring that provides a means to follow the real-time spread of emerging SARS-CoV-2 variants with possible implications for public health and immunization strategies.

4.
Journal and Proceedings of the Royal Society of New South Wales ; 154(Part 2):161-181, 2021.
Article in English | Scopus | ID: covidwho-1728220

ABSTRACT

This transcript comes from a presentation Professor Holmes gave on 31 March 2021, at the NSW Science & Research Breakfast Seminar Series, hosted by Hugh Durrant-Whyte, FRSN. See https://attend.mediahouse.com.au/breakfast-series/view/Professor-Edward-Holmes © 2021,Journal and Proceedings of the Royal Society of New South Wales. All Rights Reserved.

5.
Methods in Ecology and Evolution ; 12(8):1498-1507, 2021.
Article in English | Web of Science | ID: covidwho-1706798

ABSTRACT

1. Phylodynamic models use pathogen genome sequence data to infer epidemiological dynamics. With the increasing genomic surveillance of pathogens, especially during the SARS-CoV-2 pandemic, new practical questions about their use are emerging. 2. One such question focuses on the inclusion of un-sequenced case occurrence data alongside sequenced data to improve phylodynamic analyses. This approach can be particularly valuable if sequencing efforts vary over time. 3. Using simulations, we demonstrate that birth-death phylodynamic models can employ occurrence data to eliminate bias in estimates of the basic reproductive number due to misspecification of the sampling process. In contrast, the coalescent exponential model is robust to such sampling biases, but in the absence of a sampling model it cannot exploit occurrence data. Subsequent analysis of the SARS-CoV-2 epidemic in the northwest USA supports these results. 4. We conclude that occurrence data are a valuable source of information in combination with birth-death models. These data should be used to bolster phylodynamic analyses of infectious diseases and other rapidly spreading species in the future.

6.
Embo Journal ; 39(24):23, 2020.
Article in English | Web of Science | ID: covidwho-1059806

ABSTRACT

COVID-19 is characterized by dysregulated immune responses, metabolic dysfunction and adverse effects on the function of multiple organs. To understand host responses to COVID-19 pathophysiology, we combined transcriptomics, proteomics, and metabolomics to identify molecular markers in peripheral blood and plasma samples of 66 COVID-19-infected patients experiencing a range of disease severities and 17 healthy controls. A large number of expressed genes, proteins, metabolites, and extracellular RNAs (exRNAs) exhibit strong associations with various clinical parameters. Multiple sets of tissue-specific proteins and exRNAs varied significantly in both mild and severe patients suggesting a potential impact on tissue function. Chronic activation of neutrophils, IFN-I signaling, and a high level of inflammatory cytokines were observed in patients with severe disease progression. In contrast, COVID-19-infected patients experiencing milder disease symptoms showed robust T-cell responses. Finally, we identified genes, proteins, and exRNAs as potential biomarkers that might assist in predicting the prognosis of SARS-CoV-2 infection. These data refine our understanding of the pathophysiology and clinical progress of COVID-19. SYNOPSIS image Proteomics, metabolomics and RNAseq data map immune responses in COVID-19 patients with different disease severity, revealing molecular makers associated with disease progression and alterations of tissue-specific proteins. A multi-omics profiling of the host response to SARS-CoV2 infection in 66 clinically diagnosed and laboratory confirmed COVID-19 patients and 17 uninfected controls. Significant correlations between multi-omics data and key clinical parameters. Alteration of tissue-specific proteins and exRNAs. Enhanced activation of immune responses is associated with COVID-19 pathogenesis. Biomarkers to predict COVID-19 clinical outcomes pending clinical validation as prospective marker.

7.
Nature Medicine ; 26(9):1398-1404, 2020.
Article in English | CAB Abstracts | ID: covidwho-974973

ABSTRACT

In January 2020, a novel betacoronavirus (family Coronaviridae), named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified as the etiological agent of a cluster of pneumonia cases occurring in Wuhan City, Hubei Province, China. The disease arising from SARS-CoV-2 infection, coronavirus disease 2019 (COVID-19), subsequently spread rapidly causing a worldwide pandemic. Here we examine the added value of near real-time genome sequencing of SARS-CoV-2 in a subpopulation of infected patients during the first 10 weeks of COVID-19 containment in Australia and compare findings from genomic surveillance with predictions of a computational agent-based model (ABM). Using the Australian census data, the ABM generates over 24 million software agents representing the population of Australia, each with demographic attributes of an anonymous individual. It then simulates transmission of the disease over time, spreading from specific infection sources, using contact rates of individuals within different social contexts. We report that the prospective sequencing of SARS-CoV-2 clarified the probable source of infection in cases where epidemiological links could not be determined, significantly decreased the proportion of COVID-19 cases with contentious links, documented genomically similar cases associated with concurrent transmission in several institutions and identified previously unsuspected links. Only a quarter of sequenced cases appeared to be locally acquired and were concordant with predictions from the ABM. These high-resolution genomic data are crucial to track cases with locally acquired COVID-19 and for timely recognition of independent importations once border restrictions are lifted and trade and travel resume.

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