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Shelton K, Deshpande GN, Sanchez GJ, Vogel JR, Miller AC, Florea G, Jeffries ER, De Leόn KB, Stevenson B, Kuhn KG. Real-Time Monitoring of SARS-CoV-2 Variants in Oklahoma Wastewater through Allele-Specific RT-qPCR. Microorganisms 2024; 12:2001. [PMID: 39458310 PMCID: PMC11509313 DOI: 10.3390/microorganisms12102001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2024] [Revised: 09/27/2024] [Accepted: 09/30/2024] [Indexed: 10/28/2024] Open
Abstract
During the COVID-19 pandemic, wastewater surveillance was used to monitor community transmission of SARS-CoV-2. As new genetic variants emerged, the need for timely identification of these variants in wastewater became an important focus. In response to increased reports of Omicron transmission across the United States, the Oklahoma Wastewater Surveillance team utilized allele-specific RT-qPCR assays to detect and differentiate variants, such as Omicron, from other variants found in wastewater in Oklahoma. The PCR assays showed presence of the Omicron variant in Oklahoma on average two weeks before official reports, which was confirmed through genomic sequencing of selected wastewater samples. Through continued surveillance from November 2021 to January 2022, we also demonstrated the transition from prevalence of the Delta variant to prevalence of the Omicron variant in local communities. We further assessed how this transition correlated with certain demographic factors characterizing each community. Our results highlight RT-qPCR assays as a rapid, simple, and cost-effective method for monitoring the community spread of SARS-CoV-2 genetic variants in wastewater. Additionally, they demonstrate that specific demographic factors such as ethnic composition and household income can correlate with the timing of SARS-CoV-2 variant introduction and spread.
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Affiliation(s)
- Kristen Shelton
- School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73071, USA; (K.S.); (G.J.S.); (J.R.V.); (A.C.M.)
| | - Gargi N. Deshpande
- Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA;
| | - Gilson J. Sanchez
- School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73071, USA; (K.S.); (G.J.S.); (J.R.V.); (A.C.M.)
| | - Jason R. Vogel
- School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73071, USA; (K.S.); (G.J.S.); (J.R.V.); (A.C.M.)
| | - A. Caitlin Miller
- School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73071, USA; (K.S.); (G.J.S.); (J.R.V.); (A.C.M.)
| | - Gabriel Florea
- Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA;
| | - Erin R. Jeffries
- School of Biological Sciences, University of Oklahoma, Norman, OK 73019, USA; (E.R.J.); (K.B.D.L.); (B.S.)
| | - Kara B. De Leόn
- School of Biological Sciences, University of Oklahoma, Norman, OK 73019, USA; (E.R.J.); (K.B.D.L.); (B.S.)
| | - Bradley Stevenson
- School of Biological Sciences, University of Oklahoma, Norman, OK 73019, USA; (E.R.J.); (K.B.D.L.); (B.S.)
- Earth and Planetary Science, Northwestern University, Evanston, IL 60208, USA
| | - Katrin Gaardbo Kuhn
- Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA;
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Carmo dos Santos M, Cerqueira Silva AC, dos Reis Teixeira C, Pinheiro Macedo Prazeres F, Fernandes dos Santos R, de Araújo Rolo C, de Souza Santos E, Santos da Fonseca M, Oliveira Valente C, Saraiva Hodel KV, Moraes dos Santos Fonseca L, Sampaio Dotto Fiuza B, de Freitas Bueno R, Bittencourt de Andrade J, Aparecida Souza Machado B. Wastewater surveillance for viral pathogens: A tool for public health. Heliyon 2024; 10:e33873. [PMID: 39071684 PMCID: PMC11279281 DOI: 10.1016/j.heliyon.2024.e33873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 06/03/2024] [Accepted: 06/28/2024] [Indexed: 07/30/2024] Open
Abstract
A focus on water quality has intensified globally, considering its critical role in sustaining life and ecosystems. Wastewater, reflecting societal development, profoundly impacts public health. Wastewater-based epidemiology (WBE) has emerged as a surveillance tool for detecting outbreaks early, monitoring infectious disease trends, and providing real-time insights, particularly in vulnerable communities. WBE aids in tracking pathogens, including viruses, in sewage, offering a comprehensive understanding of community health and lifestyle habits. With the rise in global COVID-19 cases, WBE has gained prominence, aiding in monitoring SARS-CoV-2 levels worldwide. Despite advancements in water treatment, poorly treated wastewater discharge remains a threat, amplifying the spread of water-, sanitation-, and hygiene (WaSH)-related diseases. WBE, serving as complementary surveillance, is pivotal for monitoring community-level viral infections. However, there is untapped potential for WBE to expand its role in public health surveillance. This review emphasizes the importance of WBE in understanding the link between viral surveillance in wastewater and public health, highlighting the need for its further integration into public health management.
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Affiliation(s)
- Matheus Carmo dos Santos
- SENAI Institute of Innovation (ISI) in Health Advanced Systems (CIMATEC ISI SAS), SENAI CI-MATEC, Salvador, 41650-010, Bahia, Brazil
| | - Ana Clara Cerqueira Silva
- SENAI Institute of Innovation (ISI) in Health Advanced Systems (CIMATEC ISI SAS), SENAI CI-MATEC, Salvador, 41650-010, Bahia, Brazil
| | - Carine dos Reis Teixeira
- SENAI Institute of Innovation (ISI) in Health Advanced Systems (CIMATEC ISI SAS), SENAI CI-MATEC, Salvador, 41650-010, Bahia, Brazil
| | - Filipe Pinheiro Macedo Prazeres
- SENAI Institute of Innovation (ISI) in Health Advanced Systems (CIMATEC ISI SAS), SENAI CI-MATEC, Salvador, 41650-010, Bahia, Brazil
| | - Rosângela Fernandes dos Santos
- SENAI Institute of Innovation (ISI) in Health Advanced Systems (CIMATEC ISI SAS), SENAI CI-MATEC, Salvador, 41650-010, Bahia, Brazil
| | - Carolina de Araújo Rolo
- SENAI Institute of Innovation (ISI) in Health Advanced Systems (CIMATEC ISI SAS), SENAI CI-MATEC, Salvador, 41650-010, Bahia, Brazil
| | - Emanuelle de Souza Santos
- SENAI Institute of Innovation (ISI) in Health Advanced Systems (CIMATEC ISI SAS), SENAI CI-MATEC, Salvador, 41650-010, Bahia, Brazil
| | - Maísa Santos da Fonseca
- SENAI Institute of Innovation (ISI) in Health Advanced Systems (CIMATEC ISI SAS), SENAI CI-MATEC, Salvador, 41650-010, Bahia, Brazil
| | - Camila Oliveira Valente
- SENAI Institute of Innovation (ISI) in Health Advanced Systems (CIMATEC ISI SAS), SENAI CI-MATEC, Salvador, 41650-010, Bahia, Brazil
| | - Katharine Valéria Saraiva Hodel
- SENAI Institute of Innovation (ISI) in Health Advanced Systems (CIMATEC ISI SAS), SENAI CI-MATEC, Salvador, 41650-010, Bahia, Brazil
| | - Larissa Moraes dos Santos Fonseca
- SENAI Institute of Innovation (ISI) in Health Advanced Systems (CIMATEC ISI SAS), SENAI CI-MATEC, Salvador, 41650-010, Bahia, Brazil
| | - Bianca Sampaio Dotto Fiuza
- SENAI Institute of Innovation (ISI) in Health Advanced Systems (CIMATEC ISI SAS), SENAI CI-MATEC, Salvador, 41650-010, Bahia, Brazil
| | - Rodrigo de Freitas Bueno
- Federal University of ABC. Center of Engineering, Modelling and Applied Social Sciences (CECS), Santo Andre, São Paulo, Brazil
| | - Jailson Bittencourt de Andrade
- University Center SENAI CIMATEC, SENAI CIMATEC, Salvador, 41650-010, Bahia, Brazil
- Centro Interdisciplinar de Energia e Ambiente – CIEnAm, Federal University of Bahia, Salvador, 40170-115, Brazil
| | - Bruna Aparecida Souza Machado
- SENAI Institute of Innovation (ISI) in Health Advanced Systems (CIMATEC ISI SAS), SENAI CI-MATEC, Salvador, 41650-010, Bahia, Brazil
- University Center SENAI CIMATEC, SENAI CIMATEC, Salvador, 41650-010, Bahia, Brazil
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Liu Y, Sapoval N, Gallego-García P, Tomás L, Posada D, Treangen TJ, Stadler LB. Crykey: Rapid Identification of SARS-CoV-2 Cryptic Mutations in Wastewater. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.16.23291524. [PMID: 37986916 PMCID: PMC10659477 DOI: 10.1101/2023.06.16.23291524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
We present Crykey, a computational tool for rapidly identifying cryptic mutations of SARS-CoV-2. Specifically, we identify co-occurring single nucleotide mutations on the same sequencing read, called linked-read mutations, that are rare or entirely missing in existing databases, and have the potential to represent novel cryptic lineages found in wastewater. While previous approaches exist for identifying cryptic linked-read mutations from specific regions of the SARS-CoV-2 genome, there is a need for computational tools capable of efficiently tracking cryptic mutations across the entire genome and for tens of thousands of samples and with increased scrutiny, given their potential to represent either artifacts or hidden SARS-CoV-2 lineages. Crykey fills this gap by identifying rare linked-read mutations that pass stringent computational filters to limit the potential for artifacts. We evaluate the utility of Crykey on >3,000 wastewater and >22,000 clinical samples; our findings are three-fold: i) we identify hundreds of cryptic mutations that cover the entire SARS-CoV-2 genome, ii) we track the presence of these cryptic mutations across multiple wastewater treatment plants and over a three years of sampling in Houston, and iii) we find a handful of cryptic mutations in wastewater mirror cryptic mutations in clinical samples and investigate their potential to represent real cryptic lineages. In summary, Crykey enables large-scale detection of cryptic mutations representing potential cryptic lineages in wastewater.
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Affiliation(s)
- Yunxi Liu
- Department of Computer Science, Rice University, Houston, TX, 77005, USA
| | - Nicolae Sapoval
- Department of Computer Science, Rice University, Houston, TX, 77005, USA
| | - Pilar Gallego-García
- CINBIO, Universidade de Vigo, 36310 Vigo, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
| | - Laura Tomás
- CINBIO, Universidade de Vigo, 36310 Vigo, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
| | - David Posada
- CINBIO, Universidade de Vigo, 36310 Vigo, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
- Department of Biochemistry, Genetics, and Immunology, Universidade de Vigo, 36310 Vigo, Spain
| | - Todd J. Treangen
- Department of Computer Science, Rice University, Houston, TX, 77005, USA
| | - Lauren B. Stadler
- Department of Civil and Environmental Engineering, Rice University, Houston, TX, 77005, USA
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