1
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Wurtzer S, Guilbaud R, Levert M, Fagour N, Le Hingrat Q, Descamps D, Tarantola A, Grellet S, Londinsky N, Moskovoy JM, Mouchel JM, Charpentier C, Moulin L. BA.2.86 variant emergence and spread dynamics through wastewater monitoring in Paris, France. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 917:170355. [PMID: 38281649 DOI: 10.1016/j.scitotenv.2024.170355] [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: 11/27/2023] [Revised: 01/19/2024] [Accepted: 01/20/2024] [Indexed: 01/30/2024]
Abstract
Numerous SARS-CoV-2 variants are emerging as the epidemic continues, inducing new waves of contamination. In July 2023, a new variant named BA.2.86 was identified, raising concerns about its potential for viral escape, even in an immune population. The reduction in patient-centered testing and the identification of variants by sequencing means that we are now blind to the spread of this new variant. The aim of this study was to track the signature of this variant in wastewater in Paris, France. This variant showed a very rapid spread, highly correlated with national flash studies involving sequencing of clinical samples, but with a moderate impact on virus circulation. This easy-to-implement approach enabled us to monitor the emergence and spread of this new variant in real time at low cost.
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Affiliation(s)
- Sébastien Wurtzer
- Eau de Paris. DRDQE - R&D Dept., 33 avenue Jean Jaurès, FR-94200 Ivry sur Seine, France; OBEPINE SIG, Paris, France.
| | - Romane Guilbaud
- Service de Virologie, Université Paris Cité, INSERM, IAME, UMR 1137, AP-HP, Hôpital Bichat-Claude Bernard, F-75018, France
| | - Morgane Levert
- Eau de Paris. DRDQE - R&D Dept., 33 avenue Jean Jaurès, FR-94200 Ivry sur Seine, France; Paris Sorbonne Universite, CNRS, EPHE, UMR 7619 Metis, F-75005 Paris, France
| | - Nathalie Fagour
- Eau de Paris. DRDQE - R&D Dept., 33 avenue Jean Jaurès, FR-94200 Ivry sur Seine, France
| | - Quentin Le Hingrat
- Service de Virologie, Université Paris Cité, INSERM, IAME, UMR 1137, AP-HP, Hôpital Bichat-Claude Bernard, F-75018, France
| | - Diane Descamps
- Service de Virologie, Université Paris Cité, INSERM, IAME, UMR 1137, AP-HP, Hôpital Bichat-Claude Bernard, F-75018, France
| | - Arnaud Tarantola
- Santé publique France en Île-de-France, Direction des Régions, 12 rue du Val d'Osne, FR-94415 Saint-Maurice, France
| | - Sophie Grellet
- Santé publique France en Île-de-France, Direction des Régions, 12 rue du Val d'Osne, FR-94415 Saint-Maurice, France
| | - Nicolas Londinsky
- Ville de Paris, Direction de la propreté et de l'eau, Service technique de l'eau et de l'assainissement, 27 rue du Commandeur, FR-75014 Paris, France
| | - Jean-Michel Moskovoy
- SIAM - STV, Avenue de la Courtilliere, FR-77400 Saint Thibault des vignes, France
| | - Jean-Marie Mouchel
- Paris Sorbonne Universite, CNRS, EPHE, UMR 7619 Metis, F-75005 Paris, France; OBEPINE SIG, Paris, France
| | - Charlotte Charpentier
- Service de Virologie, Université Paris Cité, INSERM, IAME, UMR 1137, AP-HP, Hôpital Bichat-Claude Bernard, F-75018, France
| | - Laurent Moulin
- Eau de Paris. DRDQE - R&D Dept., 33 avenue Jean Jaurès, FR-94200 Ivry sur Seine, France; OBEPINE SIG, Paris, France
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2
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Ding J, Xu X, Deng Y, Zheng X, Zhang T. Circulation of SARS-CoV-2 Omicron sub-lineages revealed by multiplex genotyping RT-qPCR assays for sewage surveillance. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 904:166300. [PMID: 37591390 DOI: 10.1016/j.scitotenv.2023.166300] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 08/09/2023] [Accepted: 08/12/2023] [Indexed: 08/19/2023]
Abstract
Sewage surveillance has proven to be an essential complementary tool to clinical diagnosis in combating the COVID-19 pandemic by tracking the spread of the SARS-CoV-2 virus and evaluating infection levels in populations. With the striking spreading and continuous evolution of SARS-CoV-2 Omicron VOC that characterized with higher transmissibility and potential immune evasion, there is an urgent need for the rapid surveillance of this prevalent strain and its sub-lineages in sewage. In this study, based on three multiplex allele-specific (AS) RT-qPCR assays, we established a rapid and high-throughput detection workflow for the simultaneous discrimination of Omicron sub-lineages BA.2.2, BA.2.12.1, BA.4 and BA.5 (hereafter referred to as BA.4/BA.5) to track their community circulation in Hong Kong. All primer-probe sets in the multiplex assays could correctly discriminate and quantitate their target genotypes with high sensitivity and specificity, even when multiple variants co-existed in the sewage samples. Using the established multiplex assays, the trends of SARS-CoV-2 total viral load and variant dynamics in influent samples collected from 11 wastewater treatment plants (WWTPs) during June 2022 and September 2022, aligned with the clinical data, successfully unveiling the swift emergence and predominance of Omicron BA.4/BA.5 in Hong Kong. The study highlights the feasibility and applicability of multiplex RT-qPCR assays for monitoring epidemic trends and tracking variant displacement dynamics in sewage samples, providing a more rapid, high-throughput and cost-effective alternative to enhance the current sewage surveillance system.
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Affiliation(s)
- Jiahui Ding
- 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
| | - 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
| | - 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
| | - 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.
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Maréchal V, Maday Y, Wallet C, Cluzel N, Borde C. Wastewater-based epidemiology: Retrospective, current status, and future prospects. Anaesth Crit Care Pain Med 2023; 42:101251. [PMID: 37236316 DOI: 10.1016/j.accpm.2023.101251] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 05/22/2023] [Indexed: 05/28/2023]
Affiliation(s)
- Vincent Maréchal
- Sorbonne Université, INSERM, Centre de Recherche Saint-Antoine, F-75012 Paris, France; Groupement d'Intérêt Scientifique OBEPINE.
| | - Yvon Maday
- Sorbonne Université, CNRS, Université de Paris Cité, Laboratoire Jacques-Louis Lions (LJLL), F-75005 Paris, France; Groupement d'Intérêt Scientifique OBEPINE
| | - Clémentine Wallet
- Université de Strasbourg, Unit 7292, DHPI, IUT Louis Pasteur, Schiltigheim, France; Groupement d'Intérêt Scientifique OBEPINE
| | - Nicolas Cluzel
- Sorbonne Université, Maison des Modélisations Ingénieries et Technologies (SUMMIT), 75005 Paris, France; Groupement d'Intérêt Scientifique OBEPINE
| | - Chloé Borde
- Sorbonne Université, INSERM, Centre de Recherche Saint-Antoine, F-75012 Paris, France; Groupement d'Intérêt Scientifique OBEPINE
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4
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Rafique Q, Rehman A, Afghan MS, Ahmad HM, Zafar I, Fayyaz K, Ain Q, Rayan RA, Al-Aidarous KM, Rashid S, Mushtaq G, Sharma R. Reviewing methods of deep learning for diagnosing COVID-19, its variants and synergistic medicine combinations. Comput Biol Med 2023; 163:107191. [PMID: 37354819 PMCID: PMC10281043 DOI: 10.1016/j.compbiomed.2023.107191] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 05/28/2023] [Accepted: 06/19/2023] [Indexed: 06/26/2023]
Abstract
The COVID-19 pandemic has necessitated the development of reliable diagnostic methods for accurately detecting the novel coronavirus and its variants. Deep learning (DL) techniques have shown promising potential as screening tools for COVID-19 detection. In this study, we explore the realistic development of DL-driven COVID-19 detection methods and focus on the fully automatic framework using available resources, which can effectively investigate various coronavirus variants through modalities. We conducted an exploration and comparison of several diagnostic techniques that are widely used and globally validated for the detection of COVID-19. Furthermore, we explore review-based studies that provide detailed information on synergistic medicine combinations for the treatment of COVID-19. We recommend DL methods that effectively reduce time, cost, and complexity, providing valuable guidance for utilizing available synergistic combinations in clinical and research settings. This study also highlights the implication of innovative diagnostic technical and instrumental strategies, exploring public datasets, and investigating synergistic medicines using optimised DL rules. By summarizing these findings, we aim to assist future researchers in their endeavours by providing a comprehensive overview of the implication of DL techniques in COVID-19 detection and treatment. Integrating DL methods with various diagnostic approaches holds great promise in improving the accuracy and efficiency of COVID-19 diagnostics, thus contributing to effective control and management of the ongoing pandemic.
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Affiliation(s)
- Qandeel Rafique
- Department of Internal Medicine, Sahiwal Medical College, Sahiwal, 57040, Pakistan.
| | - Ali Rehman
- Department of General Medicine Govt. Eye and General Hospital Lahore, 54000, Pakistan.
| | - Muhammad Sher Afghan
- Department of Internal Medicine District Headquarter Hospital Faislaabad, 62300, Pakistan.
| | - Hafiz Muhamad Ahmad
- Department of Internal Medicine District Headquarter Hospital Bahawalnagar, 62300, Pakistan.
| | - Imran Zafar
- Department of Bioinformatics and Computational Biology, Virtual University Pakistan, 44000, Pakistan.
| | - Kompal Fayyaz
- Department of National Centre for Bioinformatics, Quaid-I-Azam University Islamabad, 45320, Pakistan.
| | - Quratul Ain
- Department of Chemistry, Government College Women University Faisalabad, 03822, Pakistan.
| | - Rehab A Rayan
- Department of Epidemiology, High Institute of Public Health, Alexandria University, 21526, Egypt.
| | - Khadija Mohammed Al-Aidarous
- Department of Computer Science, College of Science and Arts in Sharurah, Najran University, 51730, Saudi Arabia.
| | - Summya Rashid
- Department of Pharmacology & Toxicology, College of Pharmacy, Prince Sattam Bin Abdulaziz University, P.O. Box 173, Al-Kharj, 11942, Saudi Arabia.
| | - Gohar Mushtaq
- Center for Scientific Research, Faculty of Medicine, Idlib University, Idlib, Syria.
| | - Rohit Sharma
- Department of Rasashastra and Bhaishajya Kalpana, Faculty of Ayurveda, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India.
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5
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Fuzzen M, Harper NBJ, Dhiyebi HA, Srikanthan N, Hayat S, Bragg LM, Peterson SW, Yang I, Sun JX, Edwards EA, Giesy JP, Mangat CS, Graber TE, Delatolla R, Servos MR. An improved method for determining frequency of multiple variants of SARS-CoV-2 in wastewater using qPCR assays. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 881:163292. [PMID: 37030387 PMCID: PMC10079313 DOI: 10.1016/j.scitotenv.2023.163292] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 03/17/2023] [Accepted: 03/31/2023] [Indexed: 06/01/2023]
Abstract
Wastewater-based surveillance has become an effective tool around the globe for indirect monitoring of COVID-19 in communities. Variants of Concern (VOCs) have been detected in wastewater by use of reverse transcription polymerase chain reaction (RT-PCR) or whole genome sequencing (WGS). Rapid, reliable RT-PCR assays continue to be needed to determine the relative frequencies of VOCs and sub-lineages in wastewater-based surveillance programs. The presence of multiple mutations in a single region of the N-gene allowed for the design of a single amplicon, multiple probe assay, that can distinguish among several VOCs in wastewater RNA extracts. This approach which multiplexes probes designed to target mutations associated with specific VOC's along with an intra-amplicon universal probe (non-mutated region) was validated in singleplex and multiplex. The prevalence of each mutation (i.e. VOC) is estimated by comparing the abundance of the targeted mutation with a non-mutated and highly conserved region within the same amplicon. This is advantageous for the accurate and rapid estimation of variant frequencies in wastewater. The N200 assay was applied to monitor frequencies of VOCs in wastewater extracts from several communities in Ontario, Canada in near real time from November 28, 2021 to January 4, 2022. This includes the period of the rapid replacement of the Delta variant with the introduction of the Omicron variant in these Ontario communities in early December 2021. The frequency estimates using this assay were highly reflective of clinical WGS estimates for the same communities. This style of qPCR assay, which simultaneously measures signal from a non-mutated comparator probe and multiple mutation-specific probes contained within a single qPCR amplicon, can be applied to future assay development for rapid and accurate estimations of variant frequencies.
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Affiliation(s)
- Meghan Fuzzen
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
| | | | - Hadi A Dhiyebi
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Nivetha Srikanthan
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Samina Hayat
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Leslie M Bragg
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Shelley W Peterson
- One-Health Division, Wastewater Surveillance Unit, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB R3E 3M4, Canada
| | - Ivy Yang
- Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON M5S 3E5, Canada
| | - J X Sun
- Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON M5S 3E5, Canada
| | - Elizabeth A Edwards
- Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON M5S 3E5, Canada
| | - John P Giesy
- Department of Veterinary Biomedical Sciences and Toxicology Centre, University of Saskatchewan, Saskatoon, SK S7N 5B3, Canada; Department of Environmental Sciences, Baylor University, Waco, TX, USA; Department of Zoology and Center for Integrative Toxicology, Michigan State University, East Lansing, MI, USA
| | - Chand S Mangat
- One-Health Division, Wastewater Surveillance Unit, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB R3E 3M4, Canada
| | - Tyson E Graber
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario K1H 8L1, Canada
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
| | - Mark R Servos
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada
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6
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Feng S, Owens SM, Shrestha A, Poretsky R, Hartmann EM, Wells G. Intensity of sample processing methods impacts wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 876:162572. [PMID: 36871720 PMCID: PMC9984232 DOI: 10.1016/j.scitotenv.2023.162572] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 02/18/2023] [Accepted: 02/27/2023] [Indexed: 06/01/2023]
Abstract
Wastewater SARS-CoV-2 surveillance has been deployed since the beginning of the COVID-19 pandemic to monitor the dynamics in virus burden in local communities. Genomic surveillance of SARS-CoV-2 in wastewater, particularly efforts aimed at whole genome sequencing for variant tracking and identification, are still challenging due to low target concentration, complex microbial and chemical background, and lack of robust nucleic acid recovery experimental procedures. The intrinsic sample limitations are inherent to wastewater and are thus unavoidable. Here, we use a statistical approach that couples correlation analyses to a random forest-based machine learning algorithm to evaluate potentially important factors associated with wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes, with a specific focus on the breadth of genome coverage. We collected 182 composite and grab wastewater samples from the Chicago area between November 2020 to October 2021. Samples were processed using a mixture of processing methods reflecting different homogenization intensities (HA + Zymo beads, HA + glass beads, and Nanotrap), and were sequenced using one of the two library preparation kits (the Illumina COVIDseq kit and the QIAseq DIRECT kit). Technical factors evaluated using statistical and machine learning approaches include sample types, certain sample intrinsic features, and processing and sequencing methods. The results suggested that sample processing methods could be a predominant factor affecting sequencing outcomes, and library preparation kits was considered a minor factor. A synthetic SARS-CoV-2 RNA spike-in experiment was performed to validate the impact from processing methods and suggested that the intensity of the processing methods could lead to different RNA fragmentation patterns, which could also explain the observed inconsistency between qPCR quantification and sequencing outcomes. Overall, extra attention should be paid to wastewater sample processing (i.e., concentration and homogenization) for sufficient and good quality SARS-CoV-2 RNA for downstream sequencing.
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Affiliation(s)
- Shuchen Feng
- Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL, USA
| | - Sarah M Owens
- Biosciences Division, Argonne National Laboratory, Lemont, IL, USA
| | - Abhilasha Shrestha
- Department of Environmental and Occupation Health Sciences, School of Public Health, University of Illinois Chicago, Chicago, IL, USA
| | - Rachel Poretsky
- Department of Biological Sciences, University of Illinois Chicago, Chicago, IL, USA
| | - Erica M Hartmann
- Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL, USA
| | - George Wells
- Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL, USA.
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7
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Pernet O, Weisenhaus M, Stafylis C, Williams C, Campan M, Pettersson J, Green N, Lee DM, Thomas PD, Ward P, Hu H, Klausner JD, Kovacs AAZ. SARS-CoV-2 viral variants can rapidly be identified for clinical decision making and population surveillance using a high-throughput digital droplet PCR assay. Sci Rep 2023; 13:7612. [PMID: 37165019 PMCID: PMC10170421 DOI: 10.1038/s41598-023-34188-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 04/25/2023] [Indexed: 05/12/2023] Open
Abstract
Epidemiologic surveillance of circulating SARS-CoV-2 variants is essential to assess impact on clinical outcomes and vaccine efficacy. Whole genome sequencing (WGS), the gold-standard to identify variants, requires significant infrastructure and expertise. We developed a digital droplet polymerase chain reaction (ddPCR) assay that can rapidly identify circulating variants of concern/interest (VOC/VOI) using variant-specific mutation combinations in the Spike gene. To validate the assay, 800 saliva samples known to be SARS-CoV-2 positive by RT-PCR were used. During the study (July 2020-March 2022) the assay was easily adaptable to identify not only existing circulating VAC/VOI, but all new variants as they evolved. The assay can discriminate nine variants (Alpha, Beta, Gamma, Delta, Eta, Epsilon, Lambda, Mu, and Omicron) and sub-lineages (Delta 417N, Omicron BA.1, BA.2). Sequence analyses confirmed variant type for 124/124 samples tested. This ddPCR assay is an inexpensive, sensitive, high-throughput assay that can easily be adapted as new variants are identified.
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Affiliation(s)
- Olivier Pernet
- Department of Pediatrics, Maternal, Child and Adolescent Center for Infectious Diseases and Virology, University of Southern California, Los Angeles, CA, USA.
| | - Maia Weisenhaus
- Department of Pediatrics, Maternal, Child and Adolescent Center for Infectious Diseases and Virology, University of Southern California, Los Angeles, CA, USA
| | - Chrysovalantis Stafylis
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Christopher Williams
- Department of Preventive Medicine, Division of Bioinformatics, University of Southern California, Los Angeles, CA, USA
| | - Mihaela Campan
- Department of Pathology & Laboratory Medicine in Keck, University of Southern California, Los Angeles, CA, USA
| | - Jonas Pettersson
- Department of Pathology & Laboratory Medicine in Keck, University of Southern California, Los Angeles, CA, USA
| | - Nicole Green
- Los Angeles County Department of Public Health, Los Angeles, CA, USA
| | - David M Lee
- Department of Pediatrics, Maternal, Child and Adolescent Center for Infectious Diseases and Virology, University of Southern California, Los Angeles, CA, USA
| | - Paul D Thomas
- Department of Preventive Medicine, Division of Bioinformatics, University of Southern California, Los Angeles, CA, USA
| | - Pamela Ward
- Department of Pathology & Laboratory Medicine in Keck, University of Southern California, Los Angeles, CA, USA
| | - Howard Hu
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Jeffrey D Klausner
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Andrea A Z Kovacs
- Department of Pediatrics, Maternal, Child and Adolescent Center for Infectious Diseases and Virology, University of Southern California, Los Angeles, CA, USA
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
- Department of Pathology & Laboratory Medicine in Keck, University of Southern California, Los Angeles, CA, USA
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8
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Bhowmick S, Jing T, Wang W, Zhang EY, Zhang F, Yang Y. In Silico Protein Folding Prediction of COVID-19 Mutations and Variants. Biomolecules 2022; 12:1665. [PMID: 36359015 PMCID: PMC9688002 DOI: 10.3390/biom12111665] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 11/08/2022] [Accepted: 11/09/2022] [Indexed: 08/27/2023] Open
Abstract
With its fast-paced mutagenesis, the SARS-CoV-2 Omicron variant has threatened many societies worldwide. Strategies for predicting mutagenesis such as the computational prediction of SARS-CoV-2 structural diversity and its interaction with the human receptor will greatly benefit our understanding of the virus and help develop therapeutics against it. We aim to use protein structure prediction algorithms along with molecular docking to study the effects of various mutations in the Receptor Binding Domain (RBD) of the SARS-CoV-2 and its key interactions with the angiotensin-converting enzyme 2 (ACE-2) receptor. The RBD structures of the naturally occurring variants of SARS-CoV-2 were generated from the WUHAN-Hu-1 using the trRosetta algorithm. Docking (HADDOCK) and binding analysis (PRODIGY) between the predicted RBD sequences and ACE-2 highlighted key interactions at the Receptor-Binding Motif (RBM). Further mutagenesis at conserved residues in the Original, Delta, and Omicron variants (P499S and T500R) demonstrated stronger binding and interactions with the ACE-2 receptor. The predicted T500R mutation underwent some preliminary tests in vitro for its binding and transmissibility in cells; the results correlate with the in-silico analysis. In summary, we suggest conserved residues P499 and T500 as potential mutation sites that could increase the binding affinity and yet do not exist in nature. This work demonstrates the use of the trRosetta algorithm to predict protein structure and future mutations at the RBM of SARS-CoV-2, followed by experimental testing for further efficacy verification. It is important to understand the protein structure and folding to help develop potential therapeutics.
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Affiliation(s)
| | | | | | | | | | - Yanmin Yang
- Department of Neurology and Neurological Sciences, School of Medicine, Stanford University, 1201 Welch Road, MSLS, P259, Stanford, CA 94305, USA
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9
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Boni M, Gorgé O, Mullot JU, Wurtzer S, Moulin L, Maday Y, Obépine G, Canini F, Chantre M, Teyssou R, Maréchal V, Janvier F, Tournier JN. [The French Armed Forces Biomedical Research Institute (IRBA) and wastewater-based epidemiology: Applicability and relevance in armed forces]. BULLETIN DE L'ACADEMIE NATIONALE DE MEDECINE 2022; 206:1011-1021. [PMID: 36778592 PMCID: PMC9906811 DOI: 10.1016/j.banm.2022.04.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 04/29/2022] [Indexed: 11/19/2022]
Abstract
The French Armed Forces Biomedical Research Institute (IRBA) deeply involved in research on SARS-COV-2, participated in the creation of the Obépine sentinel network in charge of detecting, qualifying and quantifying the virus genome in wastewater in France. During this pandemic, wastewater-based epidemiology has proven to be a first class public health tool for assessing viral dynamics in populations and environment. Obépine has also conducted research demonstrating the low infectivity of faeces and wastewater and allowed for early detection of epidemic waves linked to new variants. The IRBA has adapted this powerful tool to the monitoring of viral infections on board the aircraft carrier Charles-de-Gaulle in order to get an operational system for anticipation after the first local outbreak in 2020. The presence of this surveillance and anticipation tool has allowed a better management of SARS-CoV-2 contingent introductions on board during stopovers or crewmembers entries. The combination of a mandatory vaccination protocol and the surveillance of viral circulation in black waters has made it possible to identify and locate cases, and thus to continue the operational mission in the COVID-19 environment while limiting the spread and preserving the health of the crew. This innovative tool can easily be redirected to the search for any other pathogens in blackwater or even, in the long term, to ensure health surveillance of any military establishment, at sea or on land, in France or on overseas bases.
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Affiliation(s)
- M Boni
- Institut de recherche biomédicale des armées, 1, place Valérie-André, 91220 Brétigny-sur-Orge, France
- Groupement d'intérêt scientifique Obépine, France
| | - O Gorgé
- Institut de recherche biomédicale des armées, 1, place Valérie-André, 91220 Brétigny-sur-Orge, France
| | - J-U Mullot
- Laboratoire d'analyses de surveillance et d'expertise de la Marine, 83000 Toulon, France
- Laboratoire d'analyses de surveillance et d'expertise de la Marine, 83000 Toulon, France
| | - S Wurtzer
- Eau de Paris, département de recherche, développement et qualité de l'eau, 33, avenue Jean-Jaurès, 94200 Ivry-sur-Seine, France
- Groupement d'intérêt scientifique Obépine, France
| | - L Moulin
- Eau de Paris, département de recherche, développement et qualité de l'eau, 33, avenue Jean-Jaurès, 94200 Ivry-sur-Seine, France
- Groupement d'intérêt scientifique Obépine, France
| | - Y Maday
- Sorbonne Université, CNRS, Université de Paris, Laboratoire Jacques-Louis Lions (LJLL), Institut universitaire de France, 75005 Paris, France
- Groupement d'intérêt scientifique Obépine, France
| | - Gis Obépine
- Groupement d'intérêt scientifique Obépine, France
| | - F Canini
- Institut de recherche biomédicale des armées, 1, place Valérie-André, 91220 Brétigny-sur-Orge, France
- École du Val-de-Grâce, 75005 Paris, France
| | - M Chantre
- Institut de recherche biomédicale des armées, 1, place Valérie-André, 91220 Brétigny-sur-Orge, France
| | - R Teyssou
- Institut de recherche biomédicale des armées, 1, place Valérie-André, 91220 Brétigny-sur-Orge, France
- École du Val-de-Grâce, 75005 Paris, France
- Groupement d'intérêt scientifique Obépine, France
| | - V Maréchal
- Sorbonne Université, Inserm, Centre de recherche Saint-Antoine, 75012 Paris, France
- Groupement d'intérêt scientifique Obépine, France
| | - F Janvier
- Hôpital d'instruction des armées Sainte-Anne, service de microbiologie et hygiène hospitalière, 83000 Toulon, France
| | - J-N Tournier
- Institut de recherche biomédicale des armées, 1, place Valérie-André, 91220 Brétigny-sur-Orge, France
- École du Val-de-Grâce, 75005 Paris, France
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Early Detection of SARS-CoV-2 Omicron BA.4 and BA.5 in German Wastewater. Viruses 2022; 14:v14091876. [PMID: 36146683 PMCID: PMC9503272 DOI: 10.3390/v14091876] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/21/2022] [Accepted: 08/22/2022] [Indexed: 11/17/2022] Open
Abstract
Wastewater-based SARS-CoV-2 epidemiology (WBE) has been established as an important tool to support individual testing strategies. The Omicron sub-variants BA.4/BA.5 have spread globally, displacing the preceding variants. Due to the severe transmissibility and immune escape potential of BA.4/BA.5, early monitoring was required to assess and implement countermeasures in time. In this study, we monitored the prevalence of SARS-CoV-2 BA.4/BA.5 at six municipal wastewater treatment plants (WWTPs) in the Federal State of North Rhine-Westphalia (NRW, Germany) in May and June 2022. Initially, L452R-specific primers/probes originally designed for SARS-CoV-2 Delta detection were validated using inactivated authentic viruses and evaluated for their suitability for detecting BA.4/BA.5. Subsequently, the assay was used for RT-qPCR analysis of RNA purified from wastewater obtained twice a week at six WWTPs. The occurrence of L452R carrying RNA was detected in early May 2022, and the presence of BA.4/BA.5 was confirmed by variant-specific single nucleotide polymorphism PCR (SNP-PCR) targeting E484A/F486V and NGS sequencing. Finally, the mutant fractions were quantitatively monitored by digital PCR, confirming BA.4/BA.5 as the majority variant by 5 June 2022. In conclusion, the successive workflow using RT-qPCR, variant-specific SNP-PCR, and RT-dPCR demonstrates the strength of WBE as a versatile tool to rapidly monitor variants spreading independently of individual test capacities.
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