1
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Cheng ZH, Li J, Zhang H, Liu DF, Yu HQ. Influent, as opposed to activated sludge, is more suitable for SARS-CoV-2 surveillance in wastewater treatment plants. WATER RESEARCH 2024; 273:123038. [PMID: 39731841 DOI: 10.1016/j.watres.2024.123038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2024] [Revised: 11/07/2024] [Accepted: 12/23/2024] [Indexed: 12/30/2024]
Abstract
Wastewater surveillance programs based at wastewater treatment plants (WWTPs) have been widely implemented, becoming a crucial measure for public health. Recently, the scope of monitoring has expanded from influent wastewater to include primary settled solids and activated sludge. The effectiveness of monitoring primary settled solids has been widely validated, but the suitability of activated sludge as a monitoring target remains unclear. In this work, we investigated the total amount distribution coefficients of SARS-CoV-2 RNA in both solid and liquid fractions of influent and biological treatment process in WWTPs. Capitalizing on the strategic timing of policy adjustments in China, we conducted a quantitative analysis of the SARS-CoV-2 monitoring results over a three-month span during the first large-scale COVID-19 outbreak from three WWTPs in Hefei city, China. Importantly, in the monitoring of activated sludge, we observed a significant delayed effect, with the viral peak occurring 1 to 2 weeks later than in the influent. In addition, we also reveal a significant correlation between the abundance of SARS-CoV-2 in influent and urban resident behaviors, providing novel insights into the pandemic's dynamics. Collectively, this work demonstrates that influent sample is more appropriate for wastewater surveillance compared to sludge sample.
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Affiliation(s)
- Zhou-Hua Cheng
- Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei 230026, China
| | - Ji Li
- Jiangsu Key Laboratory of Anaerobic Biotechnology, School of Environment and Civil Engineering, Jiangnan University, Wuxi 214122, China
| | - Hui Zhang
- CECEP Guozhen Environmental Protection Technology Joint Stock Company, Hefei 230088, China
| | - Dong-Feng Liu
- Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei 230026, China.
| | - Han-Qing Yu
- Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei 230026, China.
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2
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Fu S, Zhang Y, Li Y, Zhang Z, Du C, Wang R, Peng Y, Yue Z, Xu Z, Hu Q. Estimating epidemic trajectories of SARS-CoV-2 and influenza A virus based on wastewater monitoring and a novel machine learning algorithm. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 951:175830. [PMID: 39197755 DOI: 10.1016/j.scitotenv.2024.175830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Revised: 08/20/2024] [Accepted: 08/25/2024] [Indexed: 09/01/2024]
Abstract
The COVID-19 pandemic has altered the circulation of non-SARS-CoV-2 respiratory viruses. In this study, we carried out wastewater surveillance of SARS-CoV-2 and influenza A virus (IAV) in three key port cities in China through real-time quantitative PCR (RT-qPCR). Next, a novel machine learning algorithm (MLA) based on Gaussian model and random forest model was used to predict the epidemic trajectories of SARS-CoV-2 and IAV. The results showed that from February 2023 to January 2024, three port cities experienced two waves of SARS-CoV-2 infection, which peaked in late-May and late-August 2023, respectively. Two waves of IAV were observed in the spring and winter of 2023, respectively with considerable variations in terms of onset/offset date and duration. Furthermore, we employed MLA to extract the key features of epidemic trajectories of SARS-CoV-2 and IAV from February 3rd, to October 15th, 2023, and thereby predicted the epidemic trends of SARS-CoV-2 and IAV from October 16th, 2023 to April 22nd, 2024, which showed high consistency with the observed values. These collective findings offer an important understanding of SARS-CoV-2 and IAV epidemics, suggesting that wastewater surveillance together with MLA emerges as a powerful tool for risk assessment of respiratory viral diseases and improving public health preparedness.
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Affiliation(s)
- Songzhe Fu
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Medicine, Northwest University, Xi'an 710069, China.
| | - Yixiang Zhang
- CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences, Shanghai, China; University of Chinese Academy of Sciences, Shanghai, China
| | - Yinghui Li
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Ziqiang Zhang
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Medicine, Northwest University, Xi'an 710069, China
| | - Chen Du
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Rui Wang
- College of Marine Science and Environment, Dalian Ocean University, Dalian 116023, China
| | - Yuejing Peng
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Zhijiao Yue
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Zheng Xu
- Southern University of Sciences and Technology Yantian Hospital, Shenzhen 518081, China; Institute of Biomedicine and Biotechnology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, Guangdong, China
| | - Qinghua Hu
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China.
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3
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Xing J, Gao H, Liu G, Cao X, Zhong J, Xu S, Li Y, Pang Y, Zhang G, Sun Y. Mapping the heterogeneous removal landscape of wastewater virome in effluents of different advanced wastewater treatment systems of swine farm. WATER RESEARCH 2024; 266:122446. [PMID: 39298901 DOI: 10.1016/j.watres.2024.122446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 09/08/2024] [Accepted: 09/12/2024] [Indexed: 09/22/2024]
Abstract
In advanced wastewater treatment plants on pig farms, meticulous design aims to eliminate intrinsic pollutants such as organic matter, heavy metals, and biological contaminants. In our field survey across Southern China, a notable disparity in wastewater treatment procedures among various farming facilities lies in the utilization of terminal chemical oxidation post-sedimentation tank. However, recent focus in wastewater surveillance has predominantly centered on antibiotic resistance genes, leaving the efficacy of virus removal in different effluent systems largely unexplored. To profile virus composition at the effluent, assess the virus elimination efficiency of chemical oxidation at the effluent end, and the potential environmental driver of virus abundance, we deployed a meta-transcriptomics approach to first determine the total virome in effluent specimens of terminal clean water tank system (CWT) and terminal chemical oxidation system (TCO) in Southern China pig farms, respectively. From these data, 172 viruses were identified, with a median reads per million (RPM) of 27,789 in CWT and 19,982 in TCO. Through the integration of analyses encompassing the co-occurrence patterns within viral communities, the ecology of viral diversity, and a comparative assessment of average variation degrees, we have empirically demonstrated that the procedure of TCO may perturb viral communities and diminish their abundance, particularly impacting RNA viral communities. However, despite the diminished abundance, pathogenic viruses such as PEDV and PRRSV persisted in the effluent following chemical deoxidation at a moderate RPM value, indicating a substantial in situ presence at effluent. Our environmental driver modeling, employing GLM and mantel tests, substantiated the intricate nature of virus community variation within the effluent, influenced heterogeneously by diverse factors. Notably, pond temperature emerged as the foremost determinant, while fishing farming exhibited a positive correlation with virus diversity (p < 0.05). This revelation of the cryptic persistence of virus communities in wastewater effluent expands our understanding of the varied responses of different virus categories to oxidation. Such insights transcend mere virus characterization, offering valuable implications for enhancing biosafety measures in farming practices and informing wastewater-based epidemiological surveillance.
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Affiliation(s)
- Jiabao Xing
- Key Laboratory of Zoonosis Prevention and Control of Guangdong Province, College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, PR China
| | - Han Gao
- Key Laboratory of Zoonosis Prevention and Control of Guangdong Province, College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, PR China
| | - Guangyu Liu
- Key Laboratory of Zoonosis Prevention and Control of Guangdong Province, College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, PR China
| | - Xinyu Cao
- Key Laboratory of Zoonosis Prevention and Control of Guangdong Province, College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, PR China
| | - Jianhao Zhong
- Key Laboratory of Zoonosis Prevention and Control of Guangdong Province, College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, PR China
| | - Sijia Xu
- Key Laboratory of Zoonosis Prevention and Control of Guangdong Province, College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, PR China
| | - Yue Li
- Key Laboratory of Zoonosis Prevention and Control of Guangdong Province, College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, PR China
| | - Yuwan Pang
- Institute of Agricultural Resources and Environmental Sciences, Guangdong Academy of Agricultural Sciences, Guangzhou, 510642, PR China.
| | - Guihong Zhang
- Key Laboratory of Zoonosis Prevention and Control of Guangdong Province, College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, PR China; Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, PR China.
| | - Yankuo Sun
- Key Laboratory of Zoonosis Prevention and Control of Guangdong Province, College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, PR China; Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, PR China.
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4
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Yang S, Jiao Y, Dong Q, Li S, Xu C, Liu Y, Sun L, Huang X. Evaluating approach uncertainties of quantitative detection of SARS-CoV-2 in wastewater: Concentration, extraction and amplification. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 951:175285. [PMID: 39102960 DOI: 10.1016/j.scitotenv.2024.175285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 06/10/2024] [Accepted: 08/02/2024] [Indexed: 08/07/2024]
Abstract
Substantial uncertainties pose challenges to the accuracy of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) quantification in wastewater. We conducted a comprehensive evaluation of two concentration methods, three nucleic acid extraction methods, and the amplification performance of eight primer-probe sets. Our results showed that the two concentration methods exhibited similar recovery rates. Specifically, using a 30 kDa cut-off ultrafilter and a centrifugal force of 2500 g achieved the highest virus recovery rates (27.32 ± 8.06 % and 26.37 ± 7.77 %, respectively), with lower corresponding quantification uncertainties of 29.51 % and 29.47 % in ultrafiltration methods. Similarly, a 15 % PEG concentration with 1.5 M NaCl markedly improved virus recovery (26.76 ± 5.92 % and 28.47 ± 6.74 %, respectively), and reducing variation to 22.16 % and 23.66 % in the PEG precipitation method. Additionally, employing a vigorous bead-beating approach at 6 m/s during viral RNA extraction significantly increased RNA yield, with an efficiency reaching up to 82.18 %. Among the evaluated eight primer-probe sets, the E_Sarbeco primer-probe set provided the most stable and consistent quantitative results across various sample matrices. These findings are crucial for establishing robust viral quantification protocols and enhancing methodological precision for effective wastewater surveillance, enabling sensitive and precise detection of SARS-CoV-2.
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Affiliation(s)
- Shaolin Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 10084, China
| | - Yang Jiao
- Beijing Chaoyang Center for Disease Control and Prevention, Beijing 100021, China
| | - Qian Dong
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 10084, China
| | - Siqi Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 10084, China
| | - Chenyang Xu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 10084, China
| | - Yanchen Liu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 10084, China.
| | - Lingli Sun
- Beijing Chaoyang Center for Disease Control and Prevention, Beijing 100021, China.
| | - Xia Huang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 10084, China.
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5
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Yue Z, Shi X, Zhang H, Wu Z, Gao C, Wei B, Du C, Peng Y, Yang X, Lu J, Cheng Y, Zhou L, Zou X, Chen L, Li Y, Hu Q. The viral trends and genotype diversity of norovirus in the wastewater of Shenzhen, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 950:174884. [PMID: 39034007 DOI: 10.1016/j.scitotenv.2024.174884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 07/16/2024] [Accepted: 07/17/2024] [Indexed: 07/23/2024]
Abstract
Norovirus (NoV) is the primary cause of acute gastroenteritis (AGE) on a global scale. Numerous studies have demonstrated the immense potential of wastewater surveillance in monitoring the prevalence and spread of NoV within communities. This study employed a one-step reverse transcription-quantitative PCR to quantify NoV GI/GII in wastewater samples (n = 2574), which were collected once or twice a week from 38 wastewater treatment plants from March 2023 to February 2024 in Shenzhen. The concentrations of NoV GI and GII ranged from 5.0 × 104 to 1.7 × 106 copies/L and 4.1 × 105 to 4.5 × 106 copies/L, respectively. The concentrations of NoV GII were higher than those of NoV GI. Spearman's correlation analysis revealed a moderate correlation between the concentration of NoV in wastewater and the detection rates of NoV infections in sentinel hospitals. Baseline values were established for NoV concentrations in Shenzhen's wastewater, providing a crucial reference point for implementing early warning systems and nonpharmaceutical interventions to mitigate the impact of potential outbreaks. A total of 24 NoV genotypes were identified in 100 wastewater samples by sequencing. Nine genotypes of NoV GI were detected, with the major genotypes being GI.4 (38.6 %) and GI.3 (21.8 %); Fifteen genotypes of NoV GII were identified, with GII.4 (53.6 %) and GII.17 (26.0 %) being dominant. The trends in the relative abundance of NoV GI/GII were significantly different, and the trends in the relative abundance of NoV GII.4 over time were similar across all districts, suggesting a potential risk of cross-regional spread. Our findings underscore the effectiveness of wastewater surveillance in reflecting population-level NoV infections, capturing the diverse array of NoV genotypes, and utilizing NoV RNA in wastewater as a specific indicator to supplement clinical surveillance data, ultimately enhancing our ability to predict the timing and intensity of NoV epidemics.
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Affiliation(s)
- Zhijiao Yue
- Department of Public Health Laboratory Sciences, School of Public Health, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China; Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Xiuyuan Shi
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China; Southern University of Science and Technology, Shenzhen 518055, China
| | - Hailong Zhang
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Ziqi Wu
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Chenxi Gao
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China; Shanxi Medical University, Taiyuan 030001, China
| | - Bincai Wei
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China; Southern University of Science and Technology, Shenzhen 518055, China
| | - Chen Du
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Yuejing Peng
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China; BSL-3 Laboratory (Guangdong), Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Xi Yang
- Department of Public Health Laboratory Sciences, School of Public Health, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China; Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Jing Lu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Yanpeng Cheng
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Liping Zhou
- Peking University Shenzhen Hospital, Shenzhen 518036, China
| | - Xuan Zou
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Lili Chen
- Department of Public Health Laboratory Sciences, School of Public Health, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| | - Yinghui Li
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China.
| | - Qinghua Hu
- Department of Public Health Laboratory Sciences, School of Public Health, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China; Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China.
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6
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Li Y, Du C, Lv Z, Wang F, Zhou L, Peng Y, Li W, Fu Y, Song J, Jia C, Zhang X, Liu M, Wang Z, Liu B, Yan S, Yang Y, Li X, Zhang Y, Yuan J, Xu S, Chen M, Shi X, Peng B, Chen Q, Qiu Y, Wu S, Jiang M, Chen M, Tang J, Wang L, Hu L, Wei B, Xia Y, Ji JS, Wan C, Lu H, Zhang T, Zou X, Fu S, Hu Q. Rapid and extensive SARS-CoV-2 Omicron variant infection wave revealed by wastewater surveillance in Shenzhen following the lifting of a strict COVID-19 strategy. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 949:175235. [PMID: 39102947 DOI: 10.1016/j.scitotenv.2024.175235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Revised: 07/30/2024] [Accepted: 08/01/2024] [Indexed: 08/07/2024]
Abstract
Wastewater-based epidemiology (WBE) has emerged as a promising tool for monitoring the spread of COVID-19, as SARS-CoV-2 can be shed in the faeces of infected individuals, even in the absence of symptoms. This study aimed to optimize a prediction model for estimating COVID-19 infection rates based on SARS-CoV-2 RNA concentrations in wastewater, and reveal the infection trends and variant diversification in Shenzhen, China following the lifting of a strict COVID-19 strategy. Faecal samples (n = 4337) from 1204 SARS-CoV-2 infected individuals hospitalized in a designated hospital were analysed to obtain Omicron variant-specific faecal shedding dynamics. Wastewater samples from 6 wastewater treatment plants (WWTPs) and 9 pump stations, covering 3.55 million people, were monitored for SARS-CoV-2 RNA concentrations and variant abundance. We found that the viral load in wastewater increased rapidly in December 2022 in the two districts, demonstrating a sharp peak in COVID-19 infections in late-December 2022, mainly caused by Omicron subvariants BA.5.2.48 and BF.7.14. The prediction model, based on the mass balance between total viral load in wastewater and individual faecal viral shedding, revealed a surge in the cumulative infection rate from <0.1 % to over 70 % within three weeks after the strict COVID-19 strategy was lifted. Additionally, 39 cryptic SARS-CoV-2 variants were identified in wastewater, in addition to those detected through clinical surveillance. These findings demonstrate the effectiveness of WBE in providing comprehensive and efficient assessments of COVID-19 infection rates and identifying cryptic variants, highlighting its potential for monitoring emerging pathogens with faecal shedding.
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Affiliation(s)
- Yinghui Li
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Chen Du
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Ziquan Lv
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Fuxiang Wang
- Department of Infectious Diseases, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, China
| | - Liping Zhou
- Peking University Shenzhen Hospital, Shenzhen, China
| | - Yuejing Peng
- BSL-3 Laboratory (Guangdong), Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Wending Li
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Yulin Fu
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Jiangteng Song
- Water Ecology and Environment Division, Shenzhen Ecology and Environment Bureau, Shenzhen, China
| | - Chunyan Jia
- Water Ecology and Environment Division, Shenzhen Ecology and Environment Bureau, Shenzhen, China
| | - Xin Zhang
- Water Ecology and Environment Division, Shenzhen Ecology and Environment Bureau, Shenzhen, China
| | - Mujun Liu
- Futian District Water Authority, Shenzhen, China
| | - Zimiao Wang
- Futian District Water Authority, Shenzhen, China
| | - Bin Liu
- Futian District Water Authority, Shenzhen, China
| | - Shulan Yan
- Nanshan District Water Authority, Shenzhen, China
| | - Yuxiang Yang
- Nanshan District Water Authority, Shenzhen, China
| | - Xueyun Li
- Futian District Center for Disease Control and Prevention, Shenzhen, China
| | - Yong Zhang
- Futian District Center for Disease Control and Prevention, Shenzhen, China
| | - Jianhui Yuan
- Nanshan District Center for Disease Control and Prevention, Shenzhen, China
| | - Shikuan Xu
- Nanshan District Center for Disease Control and Prevention, Shenzhen, China
| | - Miaoling Chen
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Xiaolu Shi
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Bo Peng
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Qiongcheng Chen
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Yaqun Qiu
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Shuang Wu
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Min Jiang
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Miaomei Chen
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Jinzhen Tang
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Lei Wang
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Lulu Hu
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Bincai Wei
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China
| | - Yu Xia
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - John S Ji
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Chengsong Wan
- BSL-3 Laboratory (Guangdong), Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Hongzhou Lu
- Department of Infectious Diseases, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, China.
| | - Tong Zhang
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Hong Kong, China.
| | - Xuan Zou
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China.
| | - Songzhe Fu
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Medicine, Northwest University, Xi'an, China.
| | - Qinghua Hu
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China.
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7
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Farkas K, Fletcher J, Oxley J, Ridding N, Williams RC, Woodhall N, Weightman AJ, Cross G, Jones DL. Implications of long-term sample storage on the recovery of viruses from wastewater and biobanking. WATER RESEARCH 2024; 265:122209. [PMID: 39126986 DOI: 10.1016/j.watres.2024.122209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 07/31/2024] [Accepted: 08/01/2024] [Indexed: 08/12/2024]
Abstract
Wastewater-based monitoring has been widely implemented worldwide for the tracking of SARS-CoV-2 outbreaks and other viral diseases. In many surveillance programmes, unprocessed and processed wastewater samples are often frozen and stored for long periods of time in case the identification and tracing of an emerging health threat becomes necessary. However, extensive sample bioarchives may be difficult to maintain due to limitations in ultra-freezer capacity and associated cost. Furthermore, the stability of viruses in such samples has not been systematically investigated and hence the usefulness of bioarchives is unknown. In this study, we assessed the stability of SARS-CoV-2, influenza viruses, noroviruses and the faecal indicator virus, crAssphage, in raw wastewater and purified nucleic aacid extracts stored at -80 °C for 6-24 months. We found that the isolated viral RNA and DNA showed little signs of degradation in storage over 8-24 months, whereas extensive decay viral and loss of qPCR signal was observed during the storage of raw unprocessed wastewater. The most stable viruses were noroviruses and crAssphage, followed by SARS-CoV-2 and influenza A virus. Based on our findings, we conclude that bioarchives comprised of nucleic acid extracts derived from concentrated wastewater samples may be archived long-term, for at least two years, whereas raw wastewater samples may be discarded after one year.
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Affiliation(s)
- Kata Farkas
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK.
| | - Jessica Fletcher
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK
| | - James Oxley
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK
| | - Nicola Ridding
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK
| | - Rachel C Williams
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK
| | - Nick Woodhall
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK
| | - Andrew J Weightman
- School of Biosciences, Cardiff University, Museum Avenue, Cardiff, CF10 3AX, UK
| | - Gareth Cross
- Science Evidence Advice Division, Health and Social Services Group, Welsh Government, Cathays Park, Cardiff, CF10 3NQ, UK
| | - Davey L Jones
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK
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8
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Nema RK, Singh S, Singh AK, Sarma DK, Diwan V, Tiwari RR, Mondal RK, Mishra PK. Protocol for detection of pathogenic enteric RNA viruses by regular monitoring of environmental samples from wastewater treatment plants using droplet digital PCR. SCIENCE IN ONE HEALTH 2024; 3:100080. [PMID: 39525942 PMCID: PMC11546125 DOI: 10.1016/j.soh.2024.100080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Accepted: 10/09/2024] [Indexed: 11/16/2024]
Abstract
Background The present comprehensive protocol is focused on the detection of pathogenic enteric RNA viruses, explicitly focusing on norovirus genogroup Ⅱ (GⅡ), astrovirus, rotavirus, Aichi virus, sapovirus, hepatitis A and E viruses in wastewater treatment plants through droplet digital PCR (ddPCR). Enteric viruses are of significant public health concern, as they are the leading cause of diseases like gastroenteritis. Regular monitoring of environmental samples, particularly from wastewater treatment plants, is crucial for early detection and control of these viruses. This research aims to improve the understanding of the prevalence and dynamics of enteric viruses in urban India and will serve as a model for similar studies in other regions. Our protocol's objective is to establish a novel ddPCR-based methodology for the detection and molecular characterization of enteric viruses present in wastewater samples sourced from Bhopal, India. Our assay is capable of accurately quantifying virus concentrations without standard curves, minimizing extensive optimization, and enhancing sensitivity and precision, especially for low-abundance targets. Methods The study involves fortnightly collecting and analyzing samples from nine wastewater treatment plants over two years, ensuring comprehensive coverage and consistent data. Our study innovatively applies ddPCR to simultaneously detect and quantify enteric viruses in wastewater, a more advanced technique. Additionally, we will employ next-generation sequencing for detailed viral genome identification in samples tested positive for pathogenic viruses. Conclusion This study will aid in understanding these viruses' genetic diversity and mutation rates, which is crucial for developing tailored intervention strategies. The findings will be instrumental in shaping public health responses and improving epidemiological surveillance, especially in localities heaving sewage networks.
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Affiliation(s)
- Ram Kumar Nema
- Division of Environmental Biotechnology Genetics and Molecular Biology, ICMR-National Institute for Research in Environmental Health, Bhopal 462030, India
| | - Surya Singh
- Division of Environmental Monitoring and Exposure Assessment (Water & Soil), ICMR-National Institute for Research in Environmental Health, Bhopal 462030, India
| | - Ashutosh Kumar Singh
- Division of Environmental Biotechnology Genetics and Molecular Biology, ICMR-National Institute for Research in Environmental Health, Bhopal 462030, India
| | - Devojit Kumar Sarma
- Division of Environmental Biotechnology Genetics and Molecular Biology, ICMR-National Institute for Research in Environmental Health, Bhopal 462030, India
| | - Vishal Diwan
- Division of Environmental Monitoring and Exposure Assessment (Water & Soil), ICMR-National Institute for Research in Environmental Health, Bhopal 462030, India
| | - Rajnarayan R. Tiwari
- ICMR - National Institute for Research in Environmental Health, Bhopal 462030, India
| | - Rajesh Kumar Mondal
- Division of Microbiology, Immunology & Pathology, ICMR-National Institute for Research in Environmental Health, Bhopal 462030, India
| | - Pradyumna Kumar Mishra
- Division of Environmental Biotechnology Genetics and Molecular Biology, ICMR-National Institute for Research in Environmental Health, Bhopal 462030, India
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9
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Chaqroun A, Bertrand I, Wurtzer S, Moulin L, Boni M, Soubies S, Boudaud N, Gantzer C. Assessing infectivity of emerging enveloped viruses in wastewater and sewage sludge: Relevance and procedures. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 943:173648. [PMID: 38825204 DOI: 10.1016/j.scitotenv.2024.173648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 05/27/2024] [Accepted: 05/28/2024] [Indexed: 06/04/2024]
Abstract
The emergence of SARS-CoV-2 has heightened the need to evaluate the detection of enveloped viruses in the environment, particularly in wastewater, within the context of wastewater-based epidemiology. The studies published over the past 80 years focused primarily on non-enveloped viruses due to their ability to survive longer in environmental matrices such as wastewater or sludge compared to enveloped viruses. However, different enveloped viruses survive in the environment for different lengths of time. Therefore, it is crucial to be prepared to assess the potential infectious risk that may arise from future emerging enveloped viruses. This will require appropriate tools, notably suitable viral concentration methods that do not compromise virus infectivity. This review has a dual purpose: first, to gather all the available literature on the survival of infectious enveloped viruses, specifically at different pH and temperature conditions, and in contact with detergents; second, to select suitable concentration methods for evaluating the infectivity of these viruses in wastewater and sludge. The methodology used in this data collection review followed the systematic approach outlined in the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines. Concentration methods cited in the data gathered are more tailored towards detecting the enveloped viruses' genome. There is a lack of suitable methods for detecting infectious enveloped viruses in wastewater and sludge. Ultrafiltration, ultracentrifugation, and polyethylene glycol precipitation methods, under specific/defined conditions, appear to be relevant approaches. Further studies are necessary to validate reliable concentration methods for detecting infectious enveloped viruses. The choice of culture system is also crucial for detection sensitivity. The data also show that the survival of infectious enveloped viruses, though lower than that of non-enveloped ones, may enable environmental transmission. Experimental data on a wide range of enveloped viruses is required due to the variability in virus persistence in the environment.
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Affiliation(s)
- Ahlam Chaqroun
- Université de Lorraine, CNRS, LCPME, F-54000 Nancy, France
| | | | | | | | - Mickael Boni
- French Armed Forces Biomedical Research Institute, 91220 Brétigny-sur-Orge, France
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10
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Tang L, Guo Z, Lu X, Zhao J, Li Y, Yang K. Wastewater multiplex PCR amplicon sequencing revealed community transmission of SARS-CoV-2 lineages during the outbreak of infection in Chinese Mainland. Heliyon 2024; 10:e35332. [PMID: 39166043 PMCID: PMC11334792 DOI: 10.1016/j.heliyon.2024.e35332] [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: 09/15/2023] [Revised: 07/18/2024] [Accepted: 07/26/2024] [Indexed: 08/22/2024] Open
Abstract
During the COVID-19, wastewater-based epidemiology (WBE) has become a powerful epidemic surveillance tool widely used worldwide. However, the development and application of this technology in Chinese Mainland are relatively lagging. Herein, we for the first time monitored the community circulation of SARS-CoV-2 lineages using WBE methods in Chinese Mainland. During the peak period of infection outbreak at the end of 2022, six precious sewage samples were collected from the manhole in the student dormitory area on Wangjiang Campus of Sichuan University. RT-qPCR revealed that the six sewage samples were all positive for SARS-CoV-2 RNA. Multiplex PCR amplicon sequencing of the sewage samples reflected the local transmission of SARS-CoV-2 variants. The results of two deconvolution methods indicate that the main virus lineages have clear evolutionary genetic correlations. Furthermore, the sampling time is consistent with the timeline of concern for these virus lineages, as well as the timeline of uploading the nucleic acid sequences from the corresponding lineages in Sichuan to the database. These results demonstrate the reliability of the sewage sequencing results. Multiplex PCR amplicon sequencing is by far the most powerful analytical tool of WBE, enabling quantitative detection of virus lineages transmission and evolution at the community level.
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Affiliation(s)
| | | | - Xiaoyi Lu
- Department of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu, 610065, China
| | - Junqiao Zhao
- Department of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu, 610065, China
| | - Yonghong Li
- Department of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu, 610065, China
| | - Kun Yang
- Department of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu, 610065, China
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11
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Panneerselvam S, Manayan Parambil A, Jayaram A, Varamballi P, Mukhopadhyay C, Jagadesh A. Surveillance of influenza A and B viruses from community and hospital wastewater treatment plants. ENVIRONMENTAL MICROBIOLOGY REPORTS 2024; 16:e13317. [PMID: 39171887 PMCID: PMC11339856 DOI: 10.1111/1758-2229.13317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 07/12/2024] [Indexed: 08/23/2024]
Abstract
Influenza virus is a well-known pathogen that can cause epidemics and pandemics. Several surveillance methods are being followed to monitor the transmission patterns and spread of influenza in the community. Wastewater-based Epidemiology (WBE) can serve as an additional tool to detect the presence of influenza viruses. The current study primarily focuses on surveillance of Influenza A and Influenza B in wastewater treatment plant (WWTP) samples. A total of 100 wastewater samples were collected in July (n = 50) and August (n = 50) 2023 from four different WWTPs in Manipal and Udupi, district of Karnataka, India. The WWTP samples were processed and tested by Real-Time reverse transcriptase PCR (RT-PCR). The data generated was analysed in comparison with the clinical Influenza cases. Of the 100 samples, 18 (18%) tested positive for Influenza A virus and 2 (2%) tested positive for Influenza B virus, with a viral load ranging 1.4 x 102-2.2 x 103 gc/L for influenza A virus and 5.2 x 103-7.7 x 103gc/L for influenza B virus. On correlating the WWTP positivity with clinical case, it was found that influenza clinical cases and virus positivity in wastewater increased simultaneously, emphasizing WBE as a concurrent method for monitoring influenza virus activity.
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Affiliation(s)
- Sneka Panneerselvam
- Manipal Institute of VirologyManipal Academy of Higher EducationManipalIndia
| | | | - Anup Jayaram
- Manipal Institute of VirologyManipal Academy of Higher EducationManipalIndia
| | - Prasad Varamballi
- Manipal Institute of VirologyManipal Academy of Higher EducationManipalIndia
| | | | - Anitha Jagadesh
- Manipal Institute of VirologyManipal Academy of Higher EducationManipalIndia
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12
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Zhang Z, He F, Yi L, Deng Z, Wang R, Shen L, Fu S. Wastewater surveillance together with metaviromic data revealed the unusual resurgence of infectious diseases after the first wave of the COVID-19 outbreak. JOURNAL OF HAZARDOUS MATERIALS 2024; 473:134635. [PMID: 38772110 DOI: 10.1016/j.jhazmat.2024.134635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 04/01/2024] [Accepted: 05/15/2024] [Indexed: 05/23/2024]
Abstract
How to address public health priorities after COVID-19 is becoming a critical task. To this end, we conducted wastewater surveillance for six leading pathogens, namely, SARS-CoV-2, norovirus, rotavirus, influenza A virus (IAV), enteroviruses and respiratory syncytial virus (RSV), in Nanchang city from January to April 2023. Metaviromic sequencing was conducted at the 1st, 4th, 7th, 9th, 12th and 14th weeks to reveal the dynamics of viral pathogens that were not covered by qPCR. Amplicon sequencing of the conserved region of norovirus GI and GII and the rotavirus and region encoding nonstructural protein of RSV was also conducted weekly. The results showed that after a rapid decrease in SARS-CoV-2 sewage concentrations occurred in January 2023, surges of norovirus, rotavirus, IAV and RSV started at the 6th, 7th, 8th and 11th weeks, respectively. The dynamics of the sewage concentrations of norovirus, rotavirus, IAV and RSV were consistent with the off-season resurgence of the above infectious diseases. Notably, peak sewage concentrations of norovirus GI, GII, rotavirus, IAV and RSV were found at the 6th, 3rd, 7th, 7th and 8th weeks, respectively. Astroviruses also resurge after the 7th week, as revealed by metaviromic data, suggesting that wastewater surveillance together with metaviromic data provides an essential early warning tool for revealing patterns of infectious disease resurgence.
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Affiliation(s)
- Ziqiang Zhang
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Medicine, Northwest University, Xi'an 710069, China
| | - Fenglan He
- The Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang 330038, Jiangxi, China
| | - Liu Yi
- The Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang 330038, Jiangxi, China
| | - Zhiqiang Deng
- The Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang 330038, Jiangxi, China
| | - Rui Wang
- Key Laboratory of Environment Controlled Aquaculture (KLECA), Ministry of Education, Dalian Ocean University, Dalian 116023, China
| | - Lixin Shen
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Medicine, Northwest University, Xi'an 710069, China.
| | - Songzhe Fu
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Medicine, Northwest University, Xi'an 710069, China.
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13
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Xu X, Deng Y, Ding J, Tang Q, Lin Y, Zheng X, Zhang T. High-resolution and real-time wastewater viral surveillance by Nanopore sequencing. WATER RESEARCH 2024; 256:121623. [PMID: 38657304 DOI: 10.1016/j.watres.2024.121623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 03/27/2024] [Accepted: 04/15/2024] [Indexed: 04/26/2024]
Abstract
Wastewater genomic sequencing stands as a pivotal complementary tool for viral surveillance in populations. While long-read Nanopore sequencing is a promising platform to provide real-time genomic data, concerns over the sequencing accuracy of the earlier Nanopore versions have somewhat restrained its widespread application in wastewater analysis. Here, we evaluate the latest improved version of Nanopore sequencing (R10.4.1), using SARS-CoV-2 as the model infectious virus, to demonstrate its effectiveness in wastewater viral monitoring. By comparing amplicon lengths of 400 bp and 1200 bp, we revealed that shorter PCR amplification is more suitable for wastewater samples due to viral genome fragmentation. Utilizing mock wastewater samples, we validated the reliability of Nanopore sequencing for variant identification by comparing it with Illumina sequencing results. The strength of Nanopore sequencing in generating real-time genomic data for providing early warning signals was also showcased, indicating that as little as 0.001 Gb of data can provide accurate results for variant prevalence. Our evaluation also identified optimal alteration frequency cutoffs (>50 %) for precise mutation profiling, achieving >99 % precision in detecting single nucleotide variants (SNVs) and insertions/deletions (indels). Monitoring two major wastewater treatment plants in Hong Kong from September 2022 to April 2023, covering over 4.5 million population, we observed a transition in dominant variants from BA.5 to XBB lineages, with XBB.1.5 being the most prevalent variants. Mutation detection also highlighted the potential of wastewater Nanopore sequencing in uncovering novel mutations and revealed links between signature mutations and specific variants. This study not only reveals the environmental implications of Nanopore sequencing in SARS-CoV-2 surveillance but also underscores its potential in broader applications including environmental health monitoring of other epidemic viruses, which could significantly enhance the field of wastewater-based epidemiology.
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Affiliation(s)
- Xiaoqing Xu
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong Special Administrative Region
| | - Yu Deng
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong Special Administrative Region
| | - Jiahui Ding
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong Special Administrative Region
| | - Qinling Tang
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong Special Administrative Region
| | - Yunqi Lin
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong Special Administrative Region
| | - Xiawan Zheng
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong Special Administrative Region
| | - Tong Zhang
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong Special Administrative Region; School of Public Health, The University of Hong Kong, Pokfulam Road, Hong Kong Special Administrative Region.
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14
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Zheng X, Zhao K, Xue B, Deng Y, Xu X, Yan W, Rong C, Leung K, Wu JT, Leung GM, Peiris M, Poon LLM, Zhang T. Tracking diarrhea viruses and mpox virus using the wastewater surveillance network in Hong Kong. WATER RESEARCH 2024; 255:121513. [PMID: 38555782 DOI: 10.1016/j.watres.2024.121513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 03/14/2024] [Accepted: 03/23/2024] [Indexed: 04/02/2024]
Abstract
The wastewater surveillance network successfully established for COVID-19 showed great potential to monitor other infectious viruses, such as norovirus, rotavirus and mpox virus. In this study, we established and validated detection methods for these viruses in wastewater. We developed a supernatant-based method to detect RNA viruses from wastewater samples and applied it to the monthly diarrhea viruses (norovirus genogroup I & II, and rotavirus) surveillance in wastewater treatment plants (WWTPs) at a city-wide level for 16 months. Significant correlations were observed between the diarrhea viruses concentrations in wastewater and detection rates in faecal specimens by clinical surveillance. The highest norovirus concentration in wastewater was obtained in winter, consistent with the seasonal pattern of norovirus outbreak in Hong Kong. Additionally, we established a pellet-based method to monitor DNA viruses in wastewater and detected weak signals for mpox virus in wastewater from a WWTP serving approximately 16,700 people, when the first mpox patient in Hong Kong was admitted to the hospital within the catchment area. Genomic sequencing provided confirmatory evidence for the validity of the results. Our findings emphasized the efficacy of the wastewater surveillance network in WWTPs as a cost-effective tool to track the transmission trend of diarrhea viruses and to provide sensitive detection of novel emerging viruses such as mpox virus in low-prevalence areas. The developed methods and surveillance results provide confidence for establishing robust wastewater surveillance programs to control infectious diseases in the post-pandemic era.
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Affiliation(s)
- Xiawan Zheng
- Environmental Microbiome Engineering and Biotechnology Lab, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Keyue Zhao
- Environmental Microbiome Engineering and Biotechnology Lab, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Bingjie Xue
- Environmental Microbiome Engineering and Biotechnology Lab, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Yu Deng
- Environmental Microbiome Engineering and Biotechnology Lab, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Xiaoqing Xu
- Environmental Microbiome Engineering and Biotechnology Lab, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Weifu Yan
- Environmental Microbiome Engineering and Biotechnology Lab, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Chao Rong
- Environmental Microbiome Engineering and Biotechnology Lab, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Kathy Leung
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Sassoon Road, Hong Kong, China; Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Hong Kong, China; The University of Hong Kong - Shenzhen Hospital, Shenzhen, China
| | - Joseph T Wu
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Sassoon Road, Hong Kong, China; Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Hong Kong, China; The University of Hong Kong - Shenzhen Hospital, Shenzhen, China
| | - Gabriel M Leung
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Sassoon Road, Hong Kong, China; Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Hong Kong, China
| | - Malik Peiris
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Sassoon Road, Hong Kong, China; HKU-Pasteur Research Pole, The University of Hong Kong, Sassoon Road, Hong Kong, China; Centre For Immunology and Infection (C2i), Hong Kong Science Park, Hong Kong, China
| | - Leo L M Poon
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Sassoon Road, Hong Kong, China; HKU-Pasteur Research Pole, The University of Hong Kong, Sassoon Road, Hong Kong, China; Centre For Immunology and Infection (C2i), Hong Kong Science Park, Hong Kong, China
| | - Tong Zhang
- Environmental Microbiome Engineering and Biotechnology Lab, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China; School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Sassoon Road, Hong Kong, China; Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau, Hong Kong, China.
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15
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Du C, Peng Y, Lyu Z, Yue Z, Fu Y, Yao X, Tang J, Luo G, Gao C, Fang S, Shi X, Wan C, Li Y, Hu Q. Early Detection of the Emerging SARS-CoV-2 BA.2.86 Lineage Through Wastewater Surveillance Using a Mediator Probe PCR Assay - Shenzhen City, Guangdong Province, China, 2023. China CDC Wkly 2024; 6:332-338. [PMID: 38736992 PMCID: PMC11082055 DOI: 10.46234/ccdcw2024.063] [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: 12/22/2023] [Accepted: 04/02/2024] [Indexed: 05/14/2024] Open
Abstract
Introduction The emergence of the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron sublineage, BA.2.86, has sparked global public health concerns for its potential heightened transmissibility and immune evasion. Utilizing data from Shenzhen's city-wide wastewater surveillance system, we highlight the presence of the BA.2.86 lineage in Shenzhen. Methods A mediator probe polymerase chain reaction (PCR) assay was developed to detect the BA.2.86 lineage in wastewater by targeting a specific mutation (Spike: A264D). Between September 19 and December 10, 2023, 781 wastewater samples from 38 wastewater treatment plants (WWTPs) and 9 pump stations in ten districts of Shenzhen were examined. Through multiple short-amplicon sequencing, three positive samples were identified. Results The BA.2.86 lineage was identified in the wastewater of Futian and Nanshan districts in Shenzhen on December 2, 2023. From December 2 to 10, a total of 21 BA.2.86-positive wastewater samples were found across 6 districts (Futian, Nanshan, Longhua, Baoan, Longgang, and Luohu) in Shenzhen. The weighted average viral load of the BA.2.86 lineage in Shenzhen's wastewater was 43.5 copies/L on December 2, increased to 219.8 copies/L on December 4, and then decreased to approximately 100 copies/L on December 6, 8, and 10. Conclusions The mediator probe PCR assay, designed for swift detection of low viral concentrations of the BA.2.86 lineage in wastewater samples, shows promise for detecting different SARS-CoV-2 variants. Wastewater surveillance could serve as an early detection system for promptly identifying specific SARS-CoV-2 variants as they emerge.
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Affiliation(s)
- Chen Du
- Shenzhen Center for Disease Control and Prevention, Shenzhen City, Guangdong Province, China
| | - Yuejing Peng
- BSL-3 Laboratory (Guangdong), Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou City, Guangdong Province, China
| | - Ziquan Lyu
- Shenzhen Center for Disease Control and Prevention, Shenzhen City, Guangdong Province, China
| | - Zhijiao Yue
- Department of Public Health Laboratory Sciences, School of Public Health, Hengyang Medical School, University of South China, Hengyang City, Hunan Province, China
| | - Yulin Fu
- Shenzhen Center for Disease Control and Prevention, Shenzhen City, Guangdong Province, China
| | - Xiangjie Yao
- Shenzhen Center for Disease Control and Prevention, Shenzhen City, Guangdong Province, China
| | - Jinzhen Tang
- Shenzhen Center for Disease Control and Prevention, Shenzhen City, Guangdong Province, China
| | - Guixian Luo
- Shenzhen Center for Disease Control and Prevention, Shenzhen City, Guangdong Province, China
| | - Chenxi Gao
- School of Public Health, Shanxi Medical University, Taiyuan City, Shanxi Province, China
| | - Shisong Fang
- Shenzhen Center for Disease Control and Prevention, Shenzhen City, Guangdong Province, China
| | - Xiaolu Shi
- Shenzhen Center for Disease Control and Prevention, Shenzhen City, Guangdong Province, China
| | - Chengsong Wan
- BSL-3 Laboratory (Guangdong), Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou City, Guangdong Province, China
| | - Yinghui Li
- Shenzhen Center for Disease Control and Prevention, Shenzhen City, Guangdong Province, China
| | - Qinghua Hu
- Shenzhen Center for Disease Control and Prevention, Shenzhen City, Guangdong Province, China
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16
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Azuma T, Matsunaga N, Ohmagari N, Kuroda M. Development of a High-Throughput Analytical Method for Antimicrobials in Wastewater Using an Automated Pipetting and Solid-Phase Extraction System. Antibiotics (Basel) 2024; 13:335. [PMID: 38667011 PMCID: PMC11605239 DOI: 10.3390/antibiotics13040335] [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: 03/04/2024] [Revised: 04/01/2024] [Accepted: 04/03/2024] [Indexed: 12/01/2024] Open
Abstract
Antimicrobial resistance (AMR) has emerged and spread globally. Recent studies have also reported the presence of antimicrobials in a wide variety of aquatic environments. Conducting a nationwide monitoring survey of AMR in the environment to elucidate its status and to assess its impact on ecosystems and human health is of social importance. In this study, we developed a novel high-throughput analysis (HTA) system based on a 96-well plate solid-phase extraction (SPE), using automated pipetting and an SPE pre-treatment system. The effectiveness of the system as an HTA for antimicrobials in environmental water was verified by comparing it with a conventional manual analytical system in a domestic hospital over a period of two years and four months. The results of the manual analysis and HTA using a combination of automated pipetting and SPE systems were generally consistent, and no statistically significant difference was observed (p > 0.05) between the two systems. The agreement ratios between the measured concentrations based on the conventional and HTA methods were positively correlated with a correlation coefficient of r = 0.99. These results indicate that HTA, which combines automated pipetting and an SPE pre-treatment system for rapid, high-volume analysis, can be used as an effective approach for understanding the environmental contamination of antimicrobials at multiple sites. To the best of our knowledge, this is the first report to present the accuracy and agreement between concentrations based on a manual analysis and those measured using HTA in hospital wastewater. These findings contribute to a comprehensive understanding of antimicrobials in aquatic environments and assess the ecological and human health risks associated with antimicrobials and antimicrobial-resistant bacteria to maintain the safety of aquatic environments.
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Affiliation(s)
- Takashi Azuma
- Department of Pharmacy, Osaka Medical and Pharmaceutical University, Takatsuki 569-1094, Japan
| | - Nobuaki Matsunaga
- AMR Clinical Reference Center, National Center for Global Health and Medicine, Tokyo 162-8655, Japan; (N.M.); (N.O.)
| | - Norio Ohmagari
- AMR Clinical Reference Center, National Center for Global Health and Medicine, Tokyo 162-8655, Japan; (N.M.); (N.O.)
- Disease Control and Prevention Center, National Center for Global Health and Medicine, Tokyo 162-8655, Japan
| | - Makoto Kuroda
- Pathogen Genomics Center, National Institute of Infectious Diseases, Tokyo 162-8640, Japan
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17
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Malla B, Shrestha S, Haramoto E. Optimization of the 5-plex digital PCR workflow for simultaneous monitoring of SARS-CoV-2 and other pathogenic viruses in wastewater. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 913:169746. [PMID: 38159741 DOI: 10.1016/j.scitotenv.2023.169746] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 12/21/2023] [Accepted: 12/26/2023] [Indexed: 01/03/2024]
Abstract
Wastewater-based epidemiology is a valuable tool for monitoring pathogenic viruses in the environment, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19). While quantitative polymerase chain reaction (qPCR) is widely used for pathogen surveillance in wastewater, it can be affected by inhibition and is limited to relative quantification. Digital PCR (dPCR) offers potential solutions to these limitations. In this study, a 5-plex dPCR workflow was optimized for the simultaneous detection of SARS-CoV-2, influenza A virus, enteroviruses (EnV), and noroviruses of genogroups I (NoV-GI) and GII (NoV-GII) in wastewater samples. Wastewater samples (n = 36) were collected from a wastewater treatment plant in Japan between August and October 2022. The optimization included the evaluation of singleplex and 5-plex dPCR assays, and two different concentration methods, extraction kits, and dPCR approaches. The performance of singleplex and 5-plex dPCR assays showed comparable linearity and reliability, with the 5-plex assays showing greater efficiency. The polyethylene glycol (PEG) precipitation method showed better performance over the centrifugation method, two-step reverse transcription (RT)-dPCR over the one-step RT-dPCR, and AllPrep PowerViral DNA/RNA Kit showed better performance than the QIAamp Viral RNA Mini Kit. The optimal workflow therefore included PEG precipitation, the AllPrep PowerViral DNA/RNA Kit, and two-step RT-dPCR. This workflow was selected to monitor the presence of SARS-CoV-2 and other pathogenic viruses in wastewater samples in a 5-plex dPCR approach, yielding promising results. SARS-CoV-2 RNA was detected in the majority of samples, with NoV-GI, NoV-GII, and EnV also being detected. The successful optimization and application of the 5-plex dPCR assay for pathogen surveillance in wastewater offers significant benefits, including enhanced community health assessment and more effective responses to public health threats.
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Affiliation(s)
- Bikash Malla
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Sadhana Shrestha
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Eiji Haramoto
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan.
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Dehghan Banadaki M, Torabi S, Rockward A, Strike WD, Noble A, Keck JW, Berry SM. Simple SARS-CoV-2 concentration methods for wastewater surveillance in low resource settings. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168782. [PMID: 38000737 PMCID: PMC10842712 DOI: 10.1016/j.scitotenv.2023.168782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 11/18/2023] [Accepted: 11/20/2023] [Indexed: 11/26/2023]
Abstract
Wastewater-based epidemiology (WBE) measures pathogens in wastewater to monitor infectious disease prevalence in communities. Due to the high dilution of pathogens in sewage, a concentration method is often required to achieve reliable biomarker signals. However, most of the current concentration methods rely on expensive equipment and labor-intensive processes, which limits the application of WBE in low-resource settings. Here, we compared the performance of four inexpensive and simple concentration methods to detect SARS-CoV-2 in wastewater samples: Solid Fraction, Porcine Gastric Mucin-conjugated Magnetic Beads, Calcium Flocculation-Citrate Dissolution (CFCD), and Nanotrap® Magnetic Beads (NMBs). The NMBs and CFCD methods yielded the highest concentration performance for SARS-CoV-2 (∼16-fold concentration and ∼ 41 % recovery) and require <45 min processing time. CFCD has a relatively low consumable cost (<$2 per four sample replicates). All methods can be performed with basic laboratory equipment and minimal electricity usage which enables further application of WBE in remote areas and low resource settings.
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Affiliation(s)
| | - Soroosh Torabi
- Department of Mechanical Engineering, College of Engineering, University of Kentucky, United States
| | - Alexus Rockward
- Department of Biomedical Engineering, College of Engineering, University of Kentucky, United States
| | - William D Strike
- Department of Biomedical Engineering, College of Engineering, University of Kentucky, United States
| | - Ann Noble
- Department of Mechanical Engineering, College of Engineering, University of Kentucky, United States
| | - James W Keck
- WWAMI School of Medicine, University of Alaska Anchorage, United States
| | - Scott M Berry
- Department of Mechanical Engineering, College of Engineering, University of Kentucky, United States; Department of Biomedical Engineering, College of Engineering, University of Kentucky, United States.
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19
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Li Y, Miyani B, Faust RA, David RE, Xagoraraki I. A broad wastewater screening and clinical data surveillance for virus-related diseases in the metropolitan Detroit area in Michigan. Hum Genomics 2024; 18:14. [PMID: 38321488 PMCID: PMC10845806 DOI: 10.1186/s40246-024-00581-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 01/24/2024] [Indexed: 02/08/2024] Open
Abstract
BACKGROUND Periodic bioinformatics-based screening of wastewater for assessing the diversity of potential human viral pathogens circulating in a given community may help to identify novel or potentially emerging infectious diseases. Any identified contigs related to novel or emerging viruses should be confirmed with targeted wastewater and clinical testing. RESULTS During the COVID-19 pandemic, untreated wastewater samples were collected for a 1-year period from the Great Lakes Water Authority Wastewater Treatment Facility in Detroit, MI, USA, and viral population diversity from both centralized interceptor sites and localized neighborhood sewersheds was investigated. Clinical cases of the diseases caused by human viruses were tabulated and compared with data from viral wastewater monitoring. In addition to Betacoronavirus, comparison using assembled contigs against a custom Swiss-Prot human virus database indicated the potential prevalence of other pathogenic virus genera, including: Orthopoxvirus, Rhadinovirus, Parapoxvirus, Varicellovirus, Hepatovirus, Simplexvirus, Bocaparvovirus, Molluscipoxvirus, Parechovirus, Roseolovirus, Lymphocryptovirus, Alphavirus, Spumavirus, Lentivirus, Deltaretrovirus, Enterovirus, Kobuvirus, Gammaretrovirus, Cardiovirus, Erythroparvovirus, Salivirus, Rubivirus, Orthohepevirus, Cytomegalovirus, Norovirus, and Mamastrovirus. Four nearly complete genomes were recovered from the Astrovirus, Enterovirus, Norovirus and Betapolyomavirus genera and viral species were identified. CONCLUSIONS The presented findings in wastewater samples are primarily at the genus level and can serve as a preliminary "screening" tool that may serve as indication to initiate further testing for the confirmation of the presence of species that may be associated with human disease. Integrating innovative environmental microbiology technologies like metagenomic sequencing with viral epidemiology offers a significant opportunity to improve the monitoring of, and predictive intelligence for, pathogenic viruses, using wastewater.
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Affiliation(s)
- Yabing Li
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI, 48823, USA
| | - Brijen Miyani
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI, 48823, USA
| | - Russell A Faust
- Oakland County Health Division, 1200 Telegraph Rd, Pontiac, MI, 48341, USA
| | - Randy E David
- School of Medicine, Wayne State University, Detroit, MI, 48282, USA
| | - Irene Xagoraraki
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI, 48823, USA.
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20
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El Soufi G, Di Jorio L, Gerber Z, Cluzel N, Van Assche J, Delafoy D, Olaso R, Daviaud C, Loustau T, Schwartz C, Trebouet D, Hernalsteens O, Marechal V, Raffestin S, Rousset D, Van Lint C, Deleuze JF, Boni M, Rohr O, Villain-Gambier M, Wallet C. Highly efficient and sensitive membrane-based concentration process allows quantification, surveillance, and sequencing of viruses in large volumes of wastewater. WATER RESEARCH 2024; 249:120959. [PMID: 38070350 DOI: 10.1016/j.watres.2023.120959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 11/29/2023] [Accepted: 11/30/2023] [Indexed: 01/03/2024]
Abstract
Wastewater-based epidemiology is experiencing exponential development. Despite undeniable advantages compared to patient-centered approaches (cost, anonymity, survey of large populations without bias, detection of asymptomatic infected peoples…), major technical limitations persist. Among them is the low sensitivity of the current methods used for quantifying and sequencing viral genomes from wastewater. In situations of low viral circulation, during initial stages of viral emergences, or in areas experiencing heavy rains, the extremely low concentrations of viruses in wastewater may fall below the limit of detection of the current methods. The availability during crisis and the cost of the commercial kits, as well as the requirement of expensive materials such as high-speed centrifuge, can also present major blocks to the development of wastewater-based epidemiological survey, specifically in low-income countries. Thereby, highly sensitive, low cost and standardized methods are still needed, to increase the predictability of the viral emergences, to survey low-circulating viruses and to make the results from different labs comparable. Here, we outline and characterize new protocols for concentrating and quantifying SARS-CoV-2 from large volumes (500 mL-1 L) of untreated wastewater. In addition, we report that the methods are applicable for monitoring and sequencing. Our nucleic acid extraction technique (the routine C: 5 mL method) does not require sophisticated equipment such as automatons and is not reliant on commercial kits, making it readily available to a broader range of laboratories for routine epidemiological survey. Furthermore, we demonstrate the efficiency, the repeatability, and the high sensitivity of a new membrane-based concentration method (MBC: 500 mL method) for enveloped (SARS-CoV-2) and non-enveloped (F-specific RNA phages of genogroup II / FRNAPH GGII) viruses. We show that the MBC method allows the quantification and the monitoring of viruses in wastewater with a significantly improved sensitivity compared to the routine C method. In contexts of low viral circulation, we report quantifications of SARS-CoV-2 in wastewater at concentrations as low as 40 genome copies per liter. In highly diluted samples collected in wastewater treatment plants of French Guiana, we confirmed the accuracy of the MBC method compared to the estimations done with the routine C method. Finally, we demonstrate that both the routine C method processing 5 mL and the MBC method processing 500 mL of untreated wastewater are both compatible with SARS-CoV-2 sequencing. We show that the quality of the sequence is correlated with the concentration of the extracted viral genome. Of note, the quality of the sequences obtained with some MBC processed wastewater was improved by dilutions or enzyme substitutions suggesting the presence of specific enzyme inhibitors in some wastewater. To the best of our knowledge, our MBC method is one of the first efficient, sensitive, and repeatable method characterized for SARS-CoV-2 quantification and sequencing from large volumes of wastewater.
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Affiliation(s)
- G El Soufi
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France; CNRS, IPHC, UMR 7178, Université de Strasbourg, Strasbourg F-67000, France
| | - L Di Jorio
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France
| | - Z Gerber
- CEA, Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, Evry 91057, France
| | - N Cluzel
- Maison des Modélisations Ingénieries et Technologies (SUMMIT), Sorbonne Université, Paris 75005, France
| | - J Van Assche
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France
| | - D Delafoy
- CEA, Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, Evry 91057, France
| | - R Olaso
- CEA, Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, Evry 91057, France
| | - C Daviaud
- CEA, Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, Evry 91057, France
| | - T Loustau
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France
| | - C Schwartz
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France
| | - D Trebouet
- CNRS, IPHC, UMR 7178, Université de Strasbourg, Strasbourg F-67000, France
| | - O Hernalsteens
- Department of Molecular Biology (DBM), Service of Molecular Virology, Université Libre de Bruxelles (ULB), Gosselies 6041, Belgium
| | - V Marechal
- INSERM, Centre de Recherche Saint-Antoine, Sorbonne Université, Paris 75012, France; OBEPINE Consortium, Paris, France
| | - S Raffestin
- Institut Pasteur de la Guyane, French Guiana, Cayenne 97300, France; OBEPINE Consortium, Paris, France
| | - D Rousset
- Institut Pasteur de la Guyane, French Guiana, Cayenne 97300, France; OBEPINE Consortium, Paris, France
| | - C Van Lint
- Department of Molecular Biology (DBM), Service of Molecular Virology, Université Libre de Bruxelles (ULB), Gosselies 6041, Belgium
| | - J F Deleuze
- CEA, Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, Evry 91057, France
| | - M Boni
- French Armed Forces Biomedical Research Institute, 91220 Brétigny-sur-Orge, France; OBEPINE Consortium, Paris, France
| | - O Rohr
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France; OBEPINE Consortium, Paris, France.
| | - M Villain-Gambier
- CNRS, IPHC, UMR 7178, Université de Strasbourg, Strasbourg F-67000, France
| | - C Wallet
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France; OBEPINE Consortium, Paris, France
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21
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Yan T, Zheng R, Li Y, Sun S, Zeng X, Yue Z, Liao Y, Hu Q, Xu Y, Li Q. Epidemiological Insights into the Omicron Outbreak via MeltArray-Assisted Real-Time Tracking of SARS-CoV-2 Variants. Viruses 2023; 15:2397. [PMID: 38140638 PMCID: PMC10748191 DOI: 10.3390/v15122397] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 12/05/2023] [Accepted: 12/07/2023] [Indexed: 12/24/2023] Open
Abstract
The prolonged course of the COVID-19 pandemic necessitates sustained surveillance of emerging variants. This study aimed to develop a multiplex real-time polymerase chain reaction (rt-PCR) suitable for the real-time tracking of Omicron subvariants in clinical and wastewater samples. Plasmids containing variant-specific mutations were used to develop a MeltArray assay. After a comprehensive evaluation of both analytical and clinical performance, the established assay was used to detect Omicron variants in clinical and wastewater samples, and the results were compared with those of next-generation sequencing (NGS) and droplet digital PCR (ddPCR). The MeltArray assay identified 14 variant-specific mutations, enabling the detection of five Omicron sublineages (BA.2*, BA.5.2*, BA.2.75*, BQ.1*, and XBB.1*) and eight subvariants (BF.7, BN.1, BR.2, BQ.1.1, XBB.1.5, XBB.1.16, XBB.1.9, and BA.4.6). The limit of detection (LOD) of the assay was 50 copies/reaction, and no cross-reactivity was observed with 15 other respiratory viruses. Using NGS as the reference method, the clinical evaluation of 232 swab samples exhibited a clinical sensitivity of > 95.12% (95% CI 89.77-97.75%) and a specificity of > 95.21% (95% CI, 91.15-97.46%). When used to evaluate the Omicron outbreak from late 2022 to early 2023, the MeltArray assay performed on 1408 samples revealed that the epidemic was driven by BA.5.2* (883, 62.71%) and BF.7 (525, 37.29%). Additionally, the MeltArray assay demonstrated potential for estimating variant abundance in wastewater samples. The MeltArray assay is a rapid and scalable method for identifying SARS-CoV-2 variants. Integrating this approach with NGS and ddPCR will improve variant surveillance capabilities and ensure preparedness for future variants.
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Affiliation(s)
- Ting Yan
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China; (T.Y.); (S.S.); (Y.L.)
| | - Rongrong Zheng
- Xiamen Centre for Disease Control and Prevention, Xiamen 361021, China; (R.Z.); (X.Z.)
| | - Yinghui Li
- Shenzhen Centre for Disease Control and Prevention, Shenzhen 518055, China; (Y.L.); (Z.Y.); (Q.H.)
| | - Siyang Sun
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China; (T.Y.); (S.S.); (Y.L.)
| | - Xiaohong Zeng
- Xiamen Centre for Disease Control and Prevention, Xiamen 361021, China; (R.Z.); (X.Z.)
| | - Zhijiao Yue
- Shenzhen Centre for Disease Control and Prevention, Shenzhen 518055, China; (Y.L.); (Z.Y.); (Q.H.)
| | - Yiqun Liao
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China; (T.Y.); (S.S.); (Y.L.)
| | - Qinghua Hu
- Shenzhen Centre for Disease Control and Prevention, Shenzhen 518055, China; (Y.L.); (Z.Y.); (Q.H.)
| | - Ye Xu
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China; (T.Y.); (S.S.); (Y.L.)
| | - Qingge Li
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China; (T.Y.); (S.S.); (Y.L.)
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22
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Fu S, Zhang Y, Wang R, Deng Z, He F, Jiang X, Shen L. Longitudinal wastewater surveillance of four key pathogens during an unprecedented large-scale COVID-19 outbreak in China facilitated a novel strategy for addressing public health priorities-A proof of concept study. WATER RESEARCH 2023; 247:120751. [PMID: 37918201 DOI: 10.1016/j.watres.2023.120751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 10/12/2023] [Accepted: 10/17/2023] [Indexed: 11/04/2023]
Abstract
Wastewater-based epidemiology (WBE) is a promising tool for monitoring the spread of SARS-CoV-2 and other pathogens, providing a novel public health strategy to combat disease. In this study, we first analysed nationwide reports of infectious diseases and selected Salmonella, norovirus, and influenza A virus (IAV) as prioritized targets apart from SARS-CoV-2 for wastewater surveillance. Next, the decay rates of Salmonella, norovirus, and IAV in wastewater at various temperatures were established to obtain corrected pathogen concentrations in sewage. We then monitored the concentrations of these pathogens in wastewater treatment plant (WWTP) influents in three cities, establishing a prediction model to estimate the number of infected individuals based on the mass balance between total viral load in sewage and individual viral shedding. From October 2022 to March 2023, we conducted multipathogen wastewater surveillance (MPWS) in a WWTP serving one million people in Xi'an City, monitoring the concentration dynamics of SARS-CoV-2, Salmonella, norovirus, and IAV in sewage. The infection peaks of each pathogen were different, with Salmonella cases and sewage concentration declining from October to December 2022 and only occasionally detected thereafter. The SARS-CoV-2 concentration rapidly increased from December 5th, peaked on December 26th, and then quickly decreased until the end of the study. Norovirus and IAV were detected in wastewater from January to March 2023, peaking in February and March, respectively. We used the prediction models to estimate the rate of SARS-CoV-2 infection in Xi'an city, with nearly 90 % of the population infected in urban regions. There was no significant difference between the predicted and actual number of hospital admissions for IAV. We also accurately predicted the number of norovirus cases relative to the reported cases. Our findings highlight the importance of wastewater surveillance in addressing public health priorities, underscoring the need for a novel workflow that links the prediction results of populations with public health interventions and allocation of medical resources at the community level. This approach would prevent medical resource panic squeezes, reduce the severity and mortality of patients, and enhance overall public health outcomes.
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Affiliation(s)
- Songzhe Fu
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Medicine, Northwest University, Xi'an 710069, China.
| | - Yixiang Zhang
- CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences, Shanghai, China; University of Chinese Academy of Sciences, Shanghai, China
| | - Rui Wang
- College of Marine Science and Environment, Dalian Ocean University, Dalian, China; Key Laboratory of Environment Controlled Aquaculture (KLECA), Ministry of Education, Dalian 116023, China
| | - Zhiqiang Deng
- The Collaboration Unit for Field Epidemiology of State Key Laboratory for Infectious Disease Prevention and Control, Nanchang Center for Disease Control and Prevention, Nanchang, China
| | - Fenglan He
- The Collaboration Unit for Field Epidemiology of State Key Laboratory for Infectious Disease Prevention and Control, Nanchang Center for Disease Control and Prevention, Nanchang, China
| | - Xiaotong Jiang
- College of Marine Science and Environment, Dalian Ocean University, Dalian, China; Key Laboratory of Environment Controlled Aquaculture (KLECA), Ministry of Education, Dalian 116023, China
| | - Lixin Shen
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Medicine, Northwest University, Xi'an 710069, China.
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23
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Xu X, Deng Y, Ding J, Zheng X, Wang C, Wang D, Liu L, Gu H, Peiris M, Poon LLM, Zhang T. Wastewater genomic sequencing for SARS-CoV-2 variants surveillance in wastewater-based epidemiology applications. WATER RESEARCH 2023; 244:120444. [PMID: 37579567 DOI: 10.1016/j.watres.2023.120444] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 08/01/2023] [Accepted: 08/02/2023] [Indexed: 08/16/2023]
Abstract
Wastewater-based epidemiology (WBE) has been widely used as a complementary approach to SARS-CoV-2 clinical surveillance. Wastewater genomic sequencing could provide valuable information on the genomic diversity of SARS-CoV-2 in the surveyed population. However, reliable detection and quantification of variants or mutations remain challenging. In this study, we used mock wastewater samples created by spiking SARS-CoV-2 variant standard RNA into wastewater RNA to evaluate the impacts of sequencing throughput on various aspects such as genome coverage, mutation detection, and SARS-CoV-2 variant deconvolution. We found that wastewater datasets with sequencing throughput greater than 0.5 Gb yielded reliable results in genomic analysis. In addition, using in silico mock datasets, we evaluated the performance of the adopted pipeline for variant deconvolution. By sequencing 86 wastewater samples covering more than 6 million people over 7 months, we presented two use cases of wastewater genomic sequencing for surveying COVID-19 in Hong Kong in WBE applications, including the replacement of Delta variants by Omicron variants, and the prevalence and development trends of three Omicron sublineages. Importantly, the wastewater genomic sequencing data were able to reveal the variant trends 16 days before the clinical data did. By investigating mutations of the spike (S) gene of the SARS-CoV-2 virus, we also showed the potential of wastewater genomic sequencing in identifying novel mutations and unique alleles. Overall, our study demonstrated the crucial role of wastewater genomic surveillance in providing valuable insights into the emergence and monitoring of new SARS-CoV-2 variants and laid a solid foundation for the development of genomic analysis methodologies for WBE of other novel emerging viruses in the future.
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Affiliation(s)
- Xiaoqing Xu
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Yu Deng
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Jiahui Ding
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Xiawan Zheng
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Chunxiao Wang
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Dou Wang
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Lei Liu
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Haogao Gu
- Li Ka Shing Faculty of Medicine, School of Public Health, The University of Hong Kong, Sassoon Road, Hong Kong SAR, China
| | - Malik Peiris
- Li Ka Shing Faculty of Medicine, School of Public Health, The University of Hong Kong, Sassoon Road, Hong Kong SAR, China; HKU-Pasteur Research Pole, The University of Hong Kong, Sassoon Road, Hong Kong SAR, China
| | - Leo L M Poon
- Li Ka Shing Faculty of Medicine, School of Public Health, The University of Hong Kong, Sassoon Road, Hong Kong SAR, China; HKU-Pasteur Research Pole, The University of Hong Kong, Sassoon Road, Hong Kong SAR, China
| | - Tong Zhang
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China.
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