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Brochu HN, Song K, Zhang Q, Zeng Q, Shafi A, Robinson M, Humphrey J, Croy B, Peavy L, Perera M, Parker S, Pruitt J, Munroe J, Ghatti R, Urban TJ, Harris AB, Alfego D, Norvell B, Levandoski M, Krueger B, Williams JD, Boles D, Nye MB, Dale SE, Sapeta M, Petropoulos CJ, Meltzer J, Eisenberg M, Cohen O, Letovsky S, Iyer LK. A program for real-time surveillance of SARS-CoV-2 genetics. Sci Rep 2024; 14:20249. [PMID: 39215120 PMCID: PMC11364650 DOI: 10.1038/s41598-024-70697-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Accepted: 08/20/2024] [Indexed: 09/04/2024] Open
Abstract
The COVID-19 pandemic brought forth an urgent need for widespread genomic surveillance for rapid detection and monitoring of emerging SARS-CoV-2 variants. It necessitated design, development, and deployment of a nationwide infrastructure designed for sequestration, consolidation, and characterization of patient samples that disseminates de-identified information to public authorities in tight turnaround times. Here, we describe our development of such an infrastructure, which sequenced 594,832 high coverage SARS-CoV-2 genomes from isolates we collected in the United States (U.S.) from March 13th 2020 to July 3rd 2023. Our sequencing protocol ('Virseq') utilizes wet and dry lab procedures to generate mutation-resistant sequencing of the entire SARS-CoV-2 genome, capturing all major lineages. We also characterize 379 clinically relevant SARS-CoV-2 multi-strain co-infections and ensure robust detection of emerging lineages via simulation. The modular infrastructure, sequencing, and analysis capabilities we describe support the U.S. Centers for Disease Control and Prevention national surveillance program and serve as a model for rapid response to emerging pandemics at a national scale.
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Affiliation(s)
- Hayden N Brochu
- Labcorp Center for Excellence in Data Science, AI and Bioinformatics, Burlington, NC, 27215, USA
| | - Kuncheng Song
- Labcorp Center for Excellence in Data Science, AI and Bioinformatics, Burlington, NC, 27215, USA
| | - Qimin Zhang
- Labcorp Center for Excellence in Data Science, AI and Bioinformatics, Burlington, NC, 27215, USA
| | - Qiandong Zeng
- Labcorp Center for Excellence in Data Science, AI and Bioinformatics, Burlington, NC, 27215, USA
| | - Adib Shafi
- Labcorp Center for Excellence in Data Science, AI and Bioinformatics, Burlington, NC, 27215, USA
| | - Matthew Robinson
- Labcorp Center for Excellence in Data Science, AI and Bioinformatics, Burlington, NC, 27215, USA
| | - Jake Humphrey
- Labcorp Center for Excellence in Data Science, AI and Bioinformatics, Burlington, NC, 27215, USA
| | - Bobbi Croy
- Labcorp Information Technology, Burlington, NC, 27215, USA
| | - Lydia Peavy
- Labcorp Research and Development, Burlington, NC, 27215, USA
| | - Minoli Perera
- Labcorp Research and Development, Burlington, NC, 27215, USA
| | - Scott Parker
- Labcorp Research and Development, Burlington, NC, 27215, USA
| | - John Pruitt
- Labcorp Research and Development, Burlington, NC, 27215, USA
| | - Jason Munroe
- Labcorp Consumer Genetics Department, Burlington, NC, 27215, USA
| | | | - Thomas J Urban
- Labcorp Research and Development, Burlington, NC, 27215, USA
| | - Ayla B Harris
- Labcorp Research and Development, Burlington, NC, 27215, USA
| | - David Alfego
- Labcorp Center for Excellence in Data Science, AI and Bioinformatics, Burlington, NC, 27215, USA
| | - Brian Norvell
- Labcorp Research and Development, Burlington, NC, 27215, USA
| | - Michael Levandoski
- Labcorp Research and Development, Burlington, NC, 27215, USA
- Q2 Solutions, an IQVIA Business, Durham, NC, 27703, USA
| | - Brian Krueger
- Labcorp Research and Development, Burlington, NC, 27215, USA
- BaseX Scientific, LLC, Chapel Hill, NC, 27516, USA
| | | | - Deborah Boles
- Labcorp Research and Development, Burlington, NC, 27215, USA
| | - Melinda B Nye
- Labcorp Center for Esoteric Testing, Burlington, NC, 27215, USA
| | - Suzanne E Dale
- Labcorp Center for Esoteric Testing, Burlington, NC, 27215, USA
| | - Michael Sapeta
- Labcorp Center for Esoteric Testing, Burlington, NC, 27215, USA
| | | | | | | | - Oren Cohen
- Labcorp Drug Development, Burlington, NC, 27215, USA
- Fortrea Inc, Durham, NC, 27703, USA
| | - Stanley Letovsky
- Labcorp Center for Excellence in Data Science, AI and Bioinformatics, Burlington, NC, 27215, USA
| | - Lakshmanan K Iyer
- Labcorp Center for Excellence in Data Science, AI and Bioinformatics, Burlington, NC, 27215, USA.
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2
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Aravind Kumar N, Aradhana S, Harleen, Vishnuraj MR. SARS-CoV-2 in digital era: Diagnostic techniques and importance of nucleic acid quantification with digital PCRs. Rev Med Virol 2023; 33:e2471. [PMID: 37529971 DOI: 10.1002/rmv.2471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 07/04/2023] [Accepted: 07/12/2023] [Indexed: 08/03/2023]
Abstract
Studies related to clinical diagnosis and research of SARS-CoV-2 are important in the current pandemic era. Although molecular biology has emphasised the importance of qualitative analysis, quantitative analysis with nucleic acids in relation to SARS-CoV-2 needs to be clearly emphasised, which can provide perspective for viral dynamic studies of SARS-CoV-2. In this regard, the requirement and utilization of digital PCR in COVID-19 research has substantially increased during the pandemic, necessitating the aggregation of its cardinal applications and future scopes. Hence, this meta-review comprehensively addresses and emphasises the importance of nucleic acid quantification of SARS-CoV-2 RNA with digital PCR (dPCR). Various quantitative techniques of clinical significance like immunological, proteomic and nucleic acid-based diagnosis and quantification, have been comparatively discussed. Furthermore, the core part of the article focusses on the working principle and advantages of digital PCR, along with its applications in COVID-19 research. Several important applications like viral load quantitation, environmental surveillance and assay validation have been extensively investigated and discussed. Certain key future scopes of clinical importance, like mortality prediction, viral/variant-symbiosis, and antiviral studies were also identified, suggesting several possible digital PCR applications in COVID-19 research.
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Affiliation(s)
- N Aravind Kumar
- Meat Species Identification Laboratory, ICAR - National Meat Research Institute, Hyderabad, Telangana, India
| | - S Aradhana
- Department of Biotechnology, School of Bio Sciences & Technology (SBST), Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - Harleen
- Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana, India
| | - M R Vishnuraj
- Meat Species Identification Laboratory, ICAR - National Meat Research Institute, Hyderabad, Telangana, India
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3
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Sobkowiak B, Haghmaram P, Prystajecky N, Zlosnik JEA, Tyson J, Hoang LMN, Colijn C. The utility of SARS-CoV-2 genomic data for informative clustering under different epidemiological scenarios and sampling. INFECTION, GENETICS AND EVOLUTION : JOURNAL OF MOLECULAR EPIDEMIOLOGY AND EVOLUTIONARY GENETICS IN INFECTIOUS DISEASES 2023; 113:105484. [PMID: 37531976 DOI: 10.1016/j.meegid.2023.105484] [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: 05/18/2023] [Revised: 07/25/2023] [Accepted: 07/30/2023] [Indexed: 08/04/2023]
Abstract
OBJECTIVES Clustering pathogen sequence data is a common practice in epidemiology to gain insights into the genetic diversity and evolutionary relationships among pathogens. We can find groups of cases with a shared transmission history and common origin, as well as identifying transmission hotspots. Motivated by the experience of clustering SARS-CoV-2 cases using whole genome sequence data during the COVID-19 pandemic to aid with public health investigation, we investigated how differences in epidemiology and sampling can influence the composition of clusters that are identified. METHODS We performed genomic clustering on simulated SARS-CoV-2 outbreaks produced with different transmission rates and levels of genomic diversity, along with varying the proportion of cases sampled. RESULTS In single outbreaks with a low transmission rate, decreasing the sampling fraction resulted in multiple, separate clusters being identified where intermediate cases in transmission chains are missed. Outbreaks simulated with a high transmission rate were more robust to changes in the sampling fraction and largely resulted in a single cluster that included all sampled outbreak cases. When considering multiple outbreaks in a sampled jurisdiction seeded by different introductions, low genomic diversity between introduced cases caused outbreaks to be merged into large clusters. If the transmission and sampling fraction, and diversity between introductions was low, a combination of the spurious break-up of outbreaks and the linking of closely related cases in different outbreaks resulted in clusters that may appear informative, but these did not reflect the true underlying population structure. Conversely, genomic clusters matched the true population structure when there was relatively high diversity between introductions and a high transmission rate. CONCLUSION Differences in epidemiology and sampling can impact our ability to identify genomic clusters that describe the underlying population structure. These findings can help to guide recommendations for the use of pathogen clustering in public health investigations.
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Affiliation(s)
| | - Pouya Haghmaram
- Department of Mathematics, Simon Fraser University, Burnaby, Canada
| | - Natalie Prystajecky
- BC Centre for Disease Control Public Health Laboratory, BC Centre for Disease Control, Vancouver, Canada; Department of Pathology and Laboratory Medicine, Faculty of Medicine, University of British Columbia, Canada
| | - James E A Zlosnik
- BC Centre for Disease Control Public Health Laboratory, BC Centre for Disease Control, Vancouver, Canada
| | - John Tyson
- BC Centre for Disease Control Public Health Laboratory, BC Centre for Disease Control, Vancouver, Canada
| | - Linda M N Hoang
- BC Centre for Disease Control Public Health Laboratory, BC Centre for Disease Control, Vancouver, Canada; Department of Pathology and Laboratory Medicine, Faculty of Medicine, University of British Columbia, Canada
| | - Caroline Colijn
- Department of Mathematics, Simon Fraser University, Burnaby, Canada
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4
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Zheng P, Zhou C, Ding Y, Liu B, Lu L, Zhu F, Duan S. Nanopore sequencing technology and its applications. MedComm (Beijing) 2023; 4:e316. [PMID: 37441463 PMCID: PMC10333861 DOI: 10.1002/mco2.316] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 05/29/2023] [Accepted: 05/31/2023] [Indexed: 07/15/2023] Open
Abstract
Since the development of Sanger sequencing in 1977, sequencing technology has played a pivotal role in molecular biology research by enabling the interpretation of biological genetic codes. Today, nanopore sequencing is one of the leading third-generation sequencing technologies. With its long reads, portability, and low cost, nanopore sequencing is widely used in various scientific fields including epidemic prevention and control, disease diagnosis, and animal and plant breeding. Despite initial concerns about high error rates, continuous innovation in sequencing platforms and algorithm analysis technology has effectively addressed its accuracy. During the coronavirus disease (COVID-19) pandemic, nanopore sequencing played a critical role in detecting the severe acute respiratory syndrome coronavirus-2 virus genome and containing the pandemic. However, a lack of understanding of this technology may limit its popularization and application. Nanopore sequencing is poised to become the mainstream choice for preventing and controlling COVID-19 and future epidemics while creating value in other fields such as oncology and botany. This work introduces the contributions of nanopore sequencing during the COVID-19 pandemic to promote public understanding and its use in emerging outbreaks worldwide. We discuss its application in microbial detection, cancer genomes, and plant genomes and summarize strategies to improve its accuracy.
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Affiliation(s)
- Peijie Zheng
- Department of Clinical MedicineSchool of MedicineZhejiang University City CollegeHangzhouChina
| | - Chuntao Zhou
- Department of Clinical MedicineSchool of MedicineZhejiang University City CollegeHangzhouChina
| | - Yuemin Ding
- Department of Clinical MedicineSchool of MedicineZhejiang University City CollegeHangzhouChina
- Institute of Translational Medicine, School of MedicineZhejiang University City CollegeHangzhouChina
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineZhejiang University City CollegeHangzhouChina
| | - Bin Liu
- Department of Clinical MedicineSchool of MedicineZhejiang University City CollegeHangzhouChina
| | - Liuyi Lu
- Department of Clinical MedicineSchool of MedicineZhejiang University City CollegeHangzhouChina
| | - Feng Zhu
- Department of Clinical MedicineSchool of MedicineZhejiang University City CollegeHangzhouChina
| | - Shiwei Duan
- Department of Clinical MedicineSchool of MedicineZhejiang University City CollegeHangzhouChina
- Institute of Translational Medicine, School of MedicineZhejiang University City CollegeHangzhouChina
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineZhejiang University City CollegeHangzhouChina
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5
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Silva TDS, Salvato RS, Gregianini TS, Gomes IA, Pereira EC, de Oliveira E, de Menezes AL, Barcellos RB, Godinho FM, Riediger I, Debur MDC, de Oliveira CM, Ribeiro-Rodrigues R, Miyajima F, Dias FS, Abbud A, do Monte-Neto R, Calzavara-Silva CE, Siqueira MM, Wallau GL, Resende PC, Fernandes GDR, Alves P. Molecular characterization of a new SARS-CoV-2 recombinant cluster XAG identified in Brazil. Front Med (Lausanne) 2022; 9:1008600. [PMID: 36250091 PMCID: PMC9554242 DOI: 10.3389/fmed.2022.1008600] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 09/02/2022] [Indexed: 11/13/2022] Open
Abstract
Recombination events have been described in the Coronaviridae family. Since the beginning of the SARS-CoV-2 pandemic, a variable degree of selection pressure has acted upon the virus, generating new strains with increased fitness in terms of viral transmission and antibody scape. Most of the SC2 variants of concern (VOC) detected so far carry a combination of key amino acid changes and indels. Recombination may also reshuffle existing genetic profiles of distinct strains, potentially giving origin to recombinant strains with altered phenotypes. However, co-infection and recombination events are challenging to detect and require in-depth curation of assembled genomes and sequencing reds. Here, we present the molecular characterization of a new SARS-CoV-2 recombinant between BA.1.1 and BA.2.23 Omicron lineages identified in Brazil. We characterized four mutations that had not been previously described in any of the recombinants already identified worldwide and described the likely breaking points. Moreover, through phylogenetic analysis, we showed that the newly named XAG lineage groups in a highly supported monophyletic clade confirmed its common evolutionary history from parental Omicron lineages and other recombinants already described. These observations were only possible thanks to the joint effort of bioinformatics tools auxiliary in genomic surveillance and the manual curation of experienced personnel, demonstrating the importance of genetic, and bioinformatic knowledge in genomics.
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Affiliation(s)
| | | | | | | | | | - Eneida de Oliveira
- Laboratório Municipal de Referência, Setor de Biologia Molecular, Belo Horizonte, Brazil
| | - André Luiz de Menezes
- Laboratório Municipal de Referência, Setor de Biologia Molecular, Belo Horizonte, Brazil
| | | | | | - Irina Riediger
- Laboratório Central de Saúde Pública do Estado do Paraná, Curitiba, Brazil
| | | | | | | | | | | | | | | | | | | | - Gabriel Luz Wallau
- Instituto Aggeu Magalhães, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | | | | | - Pedro Alves
- Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Brazil
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6
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Lueking R, Clark AE, Narasimhan M, Mahimainathan L, Muthukumar A, Larsen CP, SoRelle JA. SARS-CoV-2 coinfections with variant genomic lineages identified by multiplex fragment analysis. Front Genet 2022; 13:942713. [PMID: 36226173 PMCID: PMC9549124 DOI: 10.3389/fgene.2022.942713] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 08/04/2022] [Indexed: 11/13/2022] Open
Abstract
Immunocompromised patients can experience prolonged SARS-CoV-2 infections in the setting of a lack of protectivity immunity despite vaccination. As circulating SARS-CoV-2 strains become more heterogeneous, concomitant infection with multiple SARS-CoV-2 variants has become an increasing concern. Immunocompromised patient populations represent potential reservoirs for the emergence of novel SARS-CoV-2 variants through mutagenic change or coinfection followed by recombinatory events. Identification of SARS-CoV-2 coinfections is challenging using traditional next generation sequencing pipelines; however, targeted genotyping approaches can facilitate detection. Here we describe five COVID-19 cases caused by coinfection with different SARS-CoV-2 variants (Delta/Omicron BA.1 and Omicron BA.1/BA.2) as identified by multiplex fragment analysis.
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Affiliation(s)
- Richard Lueking
- Department of Internal Medicine, Division of Infectious Diseases and Geographic Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Andrew E. Clark
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Madhusudhanan Narasimhan
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Lenin Mahimainathan
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Alagarraju Muthukumar
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Christian P. Larsen
- Department of Internal Medicine, Division of Infectious Diseases and Geographic Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Jeffrey A. SoRelle
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, United States
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