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Chen X, Balliew J, Bauer CX, Deegan J, Gitter A, Hanson BM, Maresso AW, Tisza MJ, Troisi CL, Rios J, Mena KD, Boerwinkle E, Wu F. RBD amplicon sequencing of wastewater reveals patterns of variant emergence and evolution. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.12.24310301. [PMID: 39040200 PMCID: PMC11261926 DOI: 10.1101/2024.07.12.24310301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 07/24/2024]
Abstract
Rapid evolution of SARS-CoV-2 has resulted in the emergence of numerous variants, posing significant challenges to public health surveillance. Clinical genome sequencing, while valuable, has limitations in capturing the full epidemiological dynamics of circulating variants in the general population. This study utilized receptor-binding domain (RBD) amplicon sequencing of wastewater samples to monitor the SARS-CoV-2 community dynamics and evolution in El Paso, TX. Over 17 months, we identified 91 variants and observed waves of dominant variants transitioning from BA.2 to BA.2.12.1, BA.4&5, BQ.1, and XBB.1.5. Our findings demonstrated early detection of variants and identification of unreported outbreaks, while showing strong consistency with clinical genome sequencing data at the local, state, and national levels. Alpha diversity analyses revealed significant periodical variations, with the highest diversity observed in winter and the outbreak lag phases, likely due to lower competition among variants before the outbreak growth phase. The data underscores the importance of low transmission periods for rapid mutation and variant evolution. This study highlights the effectiveness of integrating RBD amplicon sequencing with wastewater surveillance in tracking viral evolution, understanding variant emergence, and enhancing public health preparedness.
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Affiliation(s)
- Xingwen Chen
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - John Balliew
- El Paso Water Utility, El Paso, TX, United States
| | - Cici X Bauer
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Jennifer Deegan
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Anna Gitter
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Blake M Hanson
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Anthony W Maresso
- TAILOR Labs, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Michael J Tisza
- The Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Catherine L Troisi
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Janelle Rios
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Kristina D Mena
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Eric Boerwinkle
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Fuqing Wu
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
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Gao P, Fan Y, Kong X, Zhang R, Chen L, Jiang Y, Liu Y, Zhao M, Deng G, Cao Y, Ma L. A novel assay based on DNA melting temperature for multiplexed identification of SARS-CoV-2 and influenza A/B viruses. Front Microbiol 2023; 14:1249085. [PMID: 38173675 PMCID: PMC10762780 DOI: 10.3389/fmicb.2023.1249085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 11/20/2023] [Indexed: 01/05/2024] Open
Abstract
Introduction The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and influenza viruses can cause respiratory illnesses with similar clinical symptoms, making their differential diagnoses challenging. Additionally, in critically ill SARS-CoV-2-infected patients, co-infections with other respiratory pathogens can lead to severe cytokine storm and serious complications. Therefore, a method for simultaneous detection of SARS-CoV-2 and influenza A and B viruses will be clinically beneficial. Methods We designed an assay to detect five gene targets simultaneously via asymmetric PCR-mediated melting curve analysis in a single tube. We used specific probes that hybridize to corresponding single-stranded amplicons at low temperature and dissociate at high temperature, creating different detection peaks representing the targets. The entire reaction was conducted in a closed tube, which minimizes the risk of contamination. The limit of detection, specificity, precision, and accuracy were determined. Results The assay exhibited a limit of detection of <20 copies/μL for SARS-CoV-2 and influenza A and <30 copies/μL for influenza B, with high reliability as demonstrated by a coefficient of variation for melting temperature of <1.16% across three virus concentrations. The performance of our developed assay and the pre-determined assay showed excellent agreement for clinical samples, with kappa coefficients ranging from 0.98 (for influenza A) to 1.00 (for SARS-CoV-2 and influenza B). No false-positive, and no cross-reactivity was observed with six common non-influenza respiratory viruses. Conclusion The newly developed assay offers a straightforward, cost-effective and nucleic acid contamination-free approach for simultaneous detection of the SARS-CoV-2, influenza A, and influenza B viruses. The method offers high analytical sensitivity, reliability, specificity, and accuracy. Its use will streamline testing for co-infections, increase testing throughput, and improve laboratory efficacy.
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Affiliation(s)
- Peng Gao
- Department of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China
| | - Yanyan Fan
- Laboratory of Clinical Microbiology and Infectious Diseases, Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Xiaomu Kong
- Department of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China
| | - Rui Zhang
- National Center for Clinical Laboratories, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Lida Chen
- Department of Blood Transfusion, China-Japan Friendship Hospital, Beijing, China
| | - Yongwei Jiang
- Department of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China
| | - Yi Liu
- Department of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China
| | - Meimei Zhao
- Department of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China
| | - Guoxiong Deng
- Department of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China
| | - Yongtong Cao
- Department of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China
| | - Liang Ma
- Department of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China
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Banada PP, Green R, Streck D, Kurvathi R, Reiss R, Banik S, Daivaa N, Montalvan I, Jones R, Marras SAE, Chakravorty S, Alland D. An expanded RT-PCR melting temperature coding assay to rapidly identify all known SARS-CoV-2 variants and sub-variants of concern. Sci Rep 2023; 13:21927. [PMID: 38081834 PMCID: PMC10713575 DOI: 10.1038/s41598-023-48647-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 11/29/2023] [Indexed: 12/18/2023] Open
Abstract
The continued emergence of vaccine-resistant SARS-CoV-2 variants of concern (VOC) requires specific identification of each VOC as it arises. Here, we report an expanded version of our previously described sloppy molecular beacon (SMB) melting temperature (Tm) signature-based assay for VOCs, now modified to include detection of Delta (B.1.617.2) and Omicron (B.1.1.529) sub-variants. The SMB-VOC assay targets the signature codons 501, 484 and 452 in the SARS-CoV-2 spike protein which we show can specifically detect and differentiate all known VOCs including the Omicron subvariants (BA.1, BA.2, BA.2.12.1, BA.4/BA.5). The limit of detection (LOD) of the assay was 20, 22 and 36 genomic equivalents (GE) per reaction with the Delta, Omicron BA.1 and BA.2 respectively. Clinical validation of the 3-codon assay in the LC480 instrument showed the assay detected 94% (81/86) of the specimens as WT or VOCs and 6% (5/86) of the tests producing indeterminate results compared to sequencing. Sanger sequencing also failed for four samples. None of the specimens were incorrectly identified as WT or as a different VOC by our assay. Thus, excluding specimens with indeterminant results, the assay was 100% sensitive and 100% specific compared to Sanger sequencing for variant identification. This new assay concept can be easily expanded to add newer variants and can serve as a robust diagnostic tool for selecting appropriate monoclonal antibody therapy and rapid VOC surveillance.
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Affiliation(s)
- Padmapriya P Banada
- Rutgers New Jersey Medical School, Public Health Research Institute, Newark, NJ, USA.
| | - Raquel Green
- Rutgers New Jersey Medical School, Public Health Research Institute, Newark, NJ, USA
| | - Deanna Streck
- Institute of Genomic Medicine, Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Rohini Kurvathi
- Institute of Genomic Medicine, Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Robert Reiss
- Division of Infectious Diseases, Department of Medicine, Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Sukalyani Banik
- Rutgers New Jersey Medical School, Public Health Research Institute, Newark, NJ, USA
| | - Naranjargal Daivaa
- Rutgers New Jersey Medical School, Public Health Research Institute, Newark, NJ, USA
| | | | | | - Salvatore A E Marras
- Rutgers New Jersey Medical School, Public Health Research Institute, Newark, NJ, USA
| | - Soumitesh Chakravorty
- Rutgers New Jersey Medical School, Public Health Research Institute, Newark, NJ, USA
- Cepheid, Sunnyvale, CA, USA
| | - David Alland
- Rutgers New Jersey Medical School, Public Health Research Institute, Newark, NJ, USA.
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