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Gorzalski A, Ambrosio FJ, Massic L, Scribner MR, Siao DD, Hua C, Dykema P, Schneider E, Njoku C, Libuit K, Sevinsky JR, Van Hooser S, Pandori M, Hess D. The use of whole-genome sequencing and development of bioinformatics to monitor overlapping outbreaks of Candida auris in southern Nevada. Front Public Health 2023; 11:1198189. [PMID: 37522005 PMCID: PMC10374848 DOI: 10.3389/fpubh.2023.1198189] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 06/06/2023] [Indexed: 08/01/2023] Open
Abstract
A Candida auris outbreak has been ongoing in Southern Nevada since August 2021. In this manuscript we describe the sequencing of over 200 C. auris isolates from patients at several facilities. Genetically distinct subgroups of C. auris were detected from Clade I (3 distinct lineages) and III (1 lineage). Open-source bioinformatic tools were developed and implemented to aid in the epidemiological investigation. The work herein compares three methods for C. auris whole genome analysis: Nullarbor, MycoSNP and a new pipeline TheiaEuk. We also describe a novel analysis method focused on elucidating phylogenetic linkages between isolates within an ongoing outbreak. Moreover, this study places the ongoing outbreaks in a global context utilizing existing sequences provided worldwide. Lastly, we describe how the generated results were communicated to the epidemiologists and infection control to generate public health interventions.
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Affiliation(s)
| | | | - Lauryn Massic
- Nevada State Public Health Laboratory, Reno, NV, United States
| | | | | | - Chi Hua
- Division of Disease Control and Health Statistics, Washington State Department of Health, Public Health Laboratories, Shoreline, WA, United States
| | - Phillip Dykema
- Division of Disease Control and Health Statistics, Washington State Department of Health, Public Health Laboratories, Shoreline, WA, United States
| | - Emily Schneider
- Division of Disease Control and Health Statistics, Washington State Department of Health, Public Health Laboratories, Shoreline, WA, United States
| | - Chidinma Njoku
- Nevada Department of Health and Human Services, Las Vegas, NV, United States
| | - Kevin Libuit
- Theiagen Consulting LLC, Highlands Ranch, CO, United States
| | | | | | - Mark Pandori
- Nevada State Public Health Laboratory, Reno, NV, United States
- Department of Pathology and Laboratory Medicine, University of Nevada, Reno School of Medicine, Reno, NV, United States
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, Reno, NV, United States
| | - David Hess
- Nevada State Public Health Laboratory, Reno, NV, United States
- Department of Pathology and Laboratory Medicine, University of Nevada, Reno School of Medicine, Reno, NV, United States
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2
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Chen NFG, Chaguza C, Gagne L, Doucette M, Smole S, Buzby E, Hall J, Ash S, Harrington R, Cofsky S, Clancy S, Kapsak CJ, Sevinsky J, Libuit K, Park DJ, Hemarajata P, Garrigues JM, Green NM, Sierra-Patev S, Carpenter-Azevedo K, Huard RC, Pearson C, Incekara K, Nishimura C, Huang JP, Gagnon E, Reever E, Razeq J, Muyombwe A, Borges V, Ferreira R, Sobral D, Duarte S, Santos D, Vieira L, Gomes JP, Aquino C, Savino IM, Felton K, Bajwa M, Hayward N, Miller H, Naumann A, Allman R, Greer N, Fall A, Mostafa HH, McHugh MP, Maloney DM, Dewar R, Kenicer J, Parker A, Mathers K, Wild J, Cotton S, Templeton KE, Churchwell G, Lee PA, Pedrosa M, McGruder B, Schmedes S, Plumb MR, Wang X, Barcellos RB, Godinho FMS, Salvato RS, Ceniseros A, Breban MI, Grubaugh ND, Gallagher GR, Vogels CBF. Development of an amplicon-based sequencing approach in response to the global emergence of mpox. PLoS Biol 2023; 21:e3002151. [PMID: 37310918 PMCID: PMC10263305 DOI: 10.1371/journal.pbio.3002151] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 05/05/2023] [Indexed: 06/15/2023] Open
Abstract
The 2022 multicountry mpox outbreak concurrent with the ongoing Coronavirus Disease 2019 (COVID-19) pandemic further highlighted the need for genomic surveillance and rapid pathogen whole-genome sequencing. While metagenomic sequencing approaches have been used to sequence many of the early mpox infections, these methods are resource intensive and require samples with high viral DNA concentrations. Given the atypical clinical presentation of cases associated with the outbreak and uncertainty regarding viral load across both the course of infection and anatomical body sites, there was an urgent need for a more sensitive and broadly applicable sequencing approach. Highly multiplexed amplicon-based sequencing (PrimalSeq) was initially developed for sequencing of Zika virus, and later adapted as the main sequencing approach for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Here, we used PrimalScheme to develop a primer scheme for human monkeypox virus that can be used with many sequencing and bioinformatics pipelines implemented in public health laboratories during the COVID-19 pandemic. We sequenced clinical specimens that tested presumptively positive for human monkeypox virus with amplicon-based and metagenomic sequencing approaches. We found notably higher genome coverage across the virus genome, with minimal amplicon drop-outs, in using the amplicon-based sequencing approach, particularly in higher PCR cycle threshold (Ct) (lower DNA titer) samples. Further testing demonstrated that Ct value correlated with the number of sequencing reads and influenced the percent genome coverage. To maximize genome coverage when resources are limited, we recommend selecting samples with a PCR Ct below 31 Ct and generating 1 million sequencing reads per sample. To support national and international public health genomic surveillance efforts, we sent out primer pool aliquots to 10 laboratories across the United States, United Kingdom, Brazil, and Portugal. These public health laboratories successfully implemented the human monkeypox virus primer scheme in various amplicon sequencing workflows and with different sample types across a range of Ct values. Thus, we show that amplicon-based sequencing can provide a rapidly deployable, cost-effective, and flexible approach to pathogen whole-genome sequencing in response to newly emerging pathogens. Importantly, through the implementation of our primer scheme into existing SARS-CoV-2 workflows and across a range of sample types and sequencing platforms, we further demonstrate the potential of this approach for rapid outbreak response.
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Affiliation(s)
- Nicholas F. G. Chen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Chrispin Chaguza
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Luc Gagne
- Massachusetts Department of Public Health, Jamaica Plain, Massachusetts, United States of America
| | - Matthew Doucette
- Massachusetts Department of Public Health, Jamaica Plain, Massachusetts, United States of America
| | - Sandra Smole
- Massachusetts Department of Public Health, Jamaica Plain, Massachusetts, United States of America
| | - Erika Buzby
- Massachusetts Department of Public Health, Jamaica Plain, Massachusetts, United States of America
| | - Joshua Hall
- Massachusetts Department of Public Health, Jamaica Plain, Massachusetts, United States of America
| | - Stephanie Ash
- Massachusetts Department of Public Health, Jamaica Plain, Massachusetts, United States of America
| | - Rachel Harrington
- Massachusetts Department of Public Health, Jamaica Plain, Massachusetts, United States of America
| | - Seana Cofsky
- Massachusetts Department of Public Health, Jamaica Plain, Massachusetts, United States of America
| | - Selina Clancy
- Massachusetts Department of Public Health, Jamaica Plain, Massachusetts, United States of America
| | - Curtis J. Kapsak
- Theiagen Genomics, Highlands Ranch, Colorado, United States of America
| | - Joel Sevinsky
- Theiagen Genomics, Highlands Ranch, Colorado, United States of America
| | - Kevin Libuit
- Theiagen Genomics, Highlands Ranch, Colorado, United States of America
| | - Daniel J. Park
- Broad Institute, Cambridge, Massachusetts, United States of America
| | - Peera Hemarajata
- Los Angeles County Public Health Laboratories, Downey, California, United States of America
| | - Jacob M. Garrigues
- Los Angeles County Public Health Laboratories, Downey, California, United States of America
| | - Nicole M. Green
- Los Angeles County Public Health Laboratories, Downey, California, United States of America
| | - Sean Sierra-Patev
- Rhode Island Department of Health, Rhode Island State Health Laboratory, Providence, Rhode Island, United States of America
| | - Kristin Carpenter-Azevedo
- Rhode Island Department of Health, Rhode Island State Health Laboratory, Providence, Rhode Island, United States of America
| | - Richard C. Huard
- Rhode Island Department of Health, Rhode Island State Health Laboratory, Providence, Rhode Island, United States of America
| | - Claire Pearson
- Connecticut Department of Public Health, Rocky Hill, Connecticut, United States of America
| | - Kutluhan Incekara
- Connecticut Department of Public Health, Rocky Hill, Connecticut, United States of America
| | - Christina Nishimura
- Connecticut Department of Public Health, Rocky Hill, Connecticut, United States of America
| | - Jian Ping Huang
- Connecticut Department of Public Health, Rocky Hill, Connecticut, United States of America
| | - Emily Gagnon
- Connecticut Department of Public Health, Rocky Hill, Connecticut, United States of America
| | - Ethan Reever
- Connecticut Department of Public Health, Rocky Hill, Connecticut, United States of America
| | - Jafar Razeq
- Connecticut Department of Public Health, Rocky Hill, Connecticut, United States of America
| | - Anthony Muyombwe
- Connecticut Department of Public Health, Rocky Hill, Connecticut, United States of America
| | - Vítor Borges
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Rita Ferreira
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Daniel Sobral
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Silvia Duarte
- Technology and Innovation Unit, Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Daniela Santos
- Technology and Innovation Unit, Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Luís Vieira
- Technology and Innovation Unit, Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - João Paulo Gomes
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
- Faculty of Veterinary Medicine, Lusófona University, Lisbon, Portugal
| | - Carly Aquino
- Delaware Public Health Laboratory, Smyrna, Delaware, United States of America
| | - Isabella M. Savino
- Delaware Public Health Laboratory, Smyrna, Delaware, United States of America
| | - Karinda Felton
- Delaware Public Health Laboratory, Smyrna, Delaware, United States of America
| | - Moneeb Bajwa
- Delaware Public Health Laboratory, Smyrna, Delaware, United States of America
| | - Nyjil Hayward
- Delaware Public Health Laboratory, Smyrna, Delaware, United States of America
| | - Holly Miller
- Delaware Public Health Laboratory, Smyrna, Delaware, United States of America
| | - Allison Naumann
- Delaware Public Health Laboratory, Smyrna, Delaware, United States of America
| | - Ria Allman
- Delaware Public Health Laboratory, Smyrna, Delaware, United States of America
| | - Neel Greer
- Delaware Public Health Laboratory, Smyrna, Delaware, United States of America
| | - Amary Fall
- Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Heba H. Mostafa
- Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Martin P. McHugh
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom
- School of Medicine, University of St Andrews, St Andrews, United Kingdom
| | - Daniel M. Maloney
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom
- Institute of Ecology and Evolution, University of Edinburgh, Edinburgh, United Kingdom
| | - Rebecca Dewar
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom
| | - Juliet Kenicer
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom
| | - Abby Parker
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom
| | - Katharine Mathers
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom
| | - Jonathan Wild
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom
| | - Seb Cotton
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom
| | - Kate E. Templeton
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom
| | - George Churchwell
- Florida Department of Health, Bureau of Public Health Laboratories, Jacksonville, Florida, United States of America
| | - Philip A. Lee
- Florida Department of Health, Bureau of Public Health Laboratories, Jacksonville, Florida, United States of America
| | - Maria Pedrosa
- Florida Department of Health, Bureau of Public Health Laboratories, Jacksonville, Florida, United States of America
| | - Brenna McGruder
- Florida Department of Health, Bureau of Public Health Laboratories, Jacksonville, Florida, United States of America
| | - Sarah Schmedes
- Florida Department of Health, Bureau of Public Health Laboratories, Jacksonville, Florida, United States of America
| | - Matthew R. Plumb
- Minnesota Department of Health, Public Health Laboratory, St. Paul, Minnesota, United States of America
| | - Xiong Wang
- Minnesota Department of Health, Public Health Laboratory, St. Paul, Minnesota, United States of America
| | - Regina Bones Barcellos
- Centro Estadual de Vigilância em Saúde, Secretaria Estadual da Saúde do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Fernanda M. S. Godinho
- Centro Estadual de Vigilância em Saúde, Secretaria Estadual da Saúde do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Richard Steiner Salvato
- Centro Estadual de Vigilância em Saúde, Secretaria Estadual da Saúde do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Aimee Ceniseros
- Idaho Bureau of Laboratories, Boise, Idaho, United States of America
| | - Mallery I. Breban
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Nathan D. Grubaugh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, United States of America
| | - Glen R. Gallagher
- Massachusetts Department of Public Health, Jamaica Plain, Massachusetts, United States of America
- Rhode Island Department of Health, Rhode Island State Health Laboratory, Providence, Rhode Island, United States of America
| | - Chantal B. F. Vogels
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
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Gorzalski AJ, Kerwin H, Verma S, Hess DC, Sevinsky J, Libuit K, Vlasova-St Louis I, Siao D, Siao L, Buñuel D, Van Hooser S, Pandori MW. Rapid Lineage Assignment of Severe Acute Respiratory Syndrome Coronavirus 2 Cases through Automated Library Preparation, Sequencing, and Bioinformatic Analysis. J Mol Diagn 2023; 25:191-196. [PMID: 36754279 PMCID: PMC9902282 DOI: 10.1016/j.jmoldx.2023.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 01/06/2023] [Accepted: 01/12/2023] [Indexed: 02/10/2023] Open
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has provided a stage to illustrate that there is considerable value in obtaining rapid, whole-genome-based information about pathogens. This article describes the utility of a commercially available, automated severe acute respiratory syndrome associated coronavirus 2 (SARS-CoV-2) library preparation, genome sequencing, and a bioinformatics analysis pipeline to provide rapid, near-real-time SARS-CoV-2 variant description. This study evaluated the turnaround time, accuracy, and other quality-related parameters obtained from commercially available automated sequencing instrumentation, from analysis of continuous clinical samples obtained from January 1, 2021, to October 6, 2021. This analysis included a base-by-base assessment of sequencing accuracy at every position in the SARS-CoV-2 chromosome using two commercially available methods. Mean turnaround time, from the receipt of a specimen for SARS-CoV-2 testing to the availability of the results, with lineage assignment, was <3 days. Accuracy of sequencing by one method was 100%, although certain sites on the genome were found repeatedly to have been sequenced with varying degrees of read error rate.
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Affiliation(s)
| | | | - Subhash Verma
- Department of Microbiology and Immunology, University of Nevada-Reno, School of Medicine, Reno, Nevada
| | - David C Hess
- Nevada State Public Health Laboratory, Reno, Nevada; Department of Pathology and Laboratory Medicine, University of Nevada-Reno, School of Medicine, Reno, Nevada
| | | | | | | | | | - Lauren Siao
- Nevada State Public Health Laboratory, Reno, Nevada
| | - Diego Buñuel
- Nevada State Public Health Laboratory, Reno, Nevada
| | | | - Mark W Pandori
- Nevada State Public Health Laboratory, Reno, Nevada; Department of Microbiology and Immunology, University of Nevada-Reno, School of Medicine, Reno, Nevada; Department of Pathology and Laboratory Medicine, University of Nevada-Reno, School of Medicine, Reno, Nevada.
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4
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Lumpe J, Gumbleton L, Gorzalski A, Libuit K, Varghese V, Lloyd T, Tadros F, Arsimendi T, Wagner E, Stephens C, Sevinsky J, Hess D, Pandori M. GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking): A methodology to rapidly leverage whole genome sequencing of bacterial isolates for clinical identification. PLoS One 2023; 18:e0277575. [PMID: 36795668 PMCID: PMC9934365 DOI: 10.1371/journal.pone.0277575] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 10/29/2022] [Indexed: 02/17/2023] Open
Abstract
Whole genome sequencing (WGS) of clinical bacterial isolates has the potential to transform the fields of diagnostics and public health. To realize this potential, bioinformatic software that reports identification results needs to be developed that meets the quality standards of a diagnostic test. We developed GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking) using k-mer based strategies for identification of bacteria based on WGS reads. GAMBIT incorporates this algorithm with a highly curated searchable database of 48,224 genomes. Herein, we describe validation of the scoring methodology, parameter robustness, establishment of confidence thresholds and the curation of the reference database. We assessed GAMBIT by way of validation studies when it was deployed as a laboratory-developed test in two public health laboratories. This method greatly reduces or eliminates false identifications which are often detrimental in a clinical setting.
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Affiliation(s)
- Jared Lumpe
- Independent Researcher, Meriden, Connecticut, United States of America
- * E-mail: (JL); (MP); (DH)
| | - Lynette Gumbleton
- Nevada State Public Health Laboratory, Reno, NV, United States of America
| | - Andrew Gorzalski
- Nevada State Public Health Laboratory, Reno, NV, United States of America
| | - Kevin Libuit
- Theiagen Consulting LLC, Highlands Ranch, CO, United States of America
| | - Vici Varghese
- Alameda County Department of Public Health, Oakland, CA, United States of America
| | - Tyler Lloyd
- Alameda County Department of Public Health, Oakland, CA, United States of America
| | - Farid Tadros
- Biology Department, Santa Clara University, Santa Clara, CA, United States of America
| | - Tyler Arsimendi
- Biology Department, Santa Clara University, Santa Clara, CA, United States of America
| | - Eileen Wagner
- Theiagen Consulting LLC, Highlands Ranch, CO, United States of America
| | - Craig Stephens
- Biology Department, Santa Clara University, Santa Clara, CA, United States of America
| | - Joel Sevinsky
- Theiagen Consulting LLC, Highlands Ranch, CO, United States of America
| | - David Hess
- Nevada State Public Health Laboratory, Reno, NV, United States of America
- Biology Department, Santa Clara University, Santa Clara, CA, United States of America
- Department of Pathology and Laboratory Medicine, University of Nevada, Reno School of Medicine, Reno, NV, United States of America
- * E-mail: (JL); (MP); (DH)
| | - Mark Pandori
- Nevada State Public Health Laboratory, Reno, NV, United States of America
- Alameda County Department of Public Health, Oakland, CA, United States of America
- Department of Pathology and Laboratory Medicine, University of Nevada, Reno School of Medicine, Reno, NV, United States of America
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, Reno, NV, United States of America
- * E-mail: (JL); (MP); (DH)
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5
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Chen NF, Chaguza C, Gagne L, Doucette M, Smole S, Buzby E, Hall J, Ash S, Harrington R, Cofsky S, Clancy S, Kapsak CJ, Sevinsky J, Libuit K, Park DJ, Hemarajata P, Garrigues JM, Green NM, Sierra-Patev S, Carpenter-Azevedo K, Huard RC, Pearson C, Incekara K, Nishimura C, Huang JP, Gagnon E, Reever E, Razeq J, Muyombwe A, Borges V, Ferreira R, Sobral D, Duarte S, Santos D, Vieira L, Gomes JP, Aquino C, Savino IM, Felton K, Bajwa M, Hayward N, Miller H, Naumann A, Allman R, Greer N, Fall A, Mostafa HH, McHugh MP, Maloney DM, Dewar R, Kenicer J, Parker A, Mathers K, Wild J, Cotton S, Templeton KE, Churchwell G, Lee PA, Pedrosa M, McGruder B, Schmedes S, Plumb MR, Wang X, Barcellos RB, Godinho FM, Salvato RS, Ceniseros A, Breban MI, Grubaugh ND, Gallagher GR, Vogels CB. Development of an amplicon-based sequencing approach in response to the global emergence of human monkeypox virus. medRxiv 2023:2022.10.14.22280783. [PMID: 36299420 PMCID: PMC9603838 DOI: 10.1101/2022.10.14.22280783] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
The 2022 multi-country monkeypox (mpox) outbreak concurrent with the ongoing COVID-19 pandemic has further highlighted the need for genomic surveillance and rapid pathogen whole genome sequencing. While metagenomic sequencing approaches have been used to sequence many of the early mpox infections, these methods are resource intensive and require samples with high viral DNA concentrations. Given the atypical clinical presentation of cases associated with the outbreak and uncertainty regarding viral load across both the course of infection and anatomical body sites, there was an urgent need for a more sensitive and broadly applicable sequencing approach. Highly multiplexed amplicon-based sequencing (PrimalSeq) was initially developed for sequencing of Zika virus, and later adapted as the main sequencing approach for SARS-CoV-2. Here, we used PrimalScheme to develop a primer scheme for human monkeypox virus that can be used with many sequencing and bioinformatics pipelines implemented in public health laboratories during the COVID-19 pandemic. We sequenced clinical samples that tested presumptive positive for human monkeypox virus with amplicon-based and metagenomic sequencing approaches. We found notably higher genome coverage across the virus genome, with minimal amplicon drop-outs, in using the amplicon-based sequencing approach, particularly in higher PCR cycle threshold (lower DNA titer) samples. Further testing demonstrated that Ct value correlated with the number of sequencing reads and influenced the percent genome coverage. To maximize genome coverage when resources are limited, we recommend selecting samples with a PCR cycle threshold below 31 Ct and generating 1 million sequencing reads per sample. To support national and international public health genomic surveillance efforts, we sent out primer pool aliquots to 10 laboratories across the United States, United Kingdom, Brazil, and Portugal. These public health laboratories successfully implemented the human monkeypox virus primer scheme in various amplicon sequencing workflows and with different sample types across a range of Ct values. Thus, we show that amplicon based sequencing can provide a rapidly deployable, cost-effective, and flexible approach to pathogen whole genome sequencing in response to newly emerging pathogens. Importantly, through the implementation of our primer scheme into existing SARS-CoV-2 workflows and across a range of sample types and sequencing platforms, we further demonstrate the potential of this approach for rapid outbreak response.
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Affiliation(s)
- Nicholas F.G. Chen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Chrispin Chaguza
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Luc Gagne
- Massachusetts Department of Public Health, Boston, MA, USA
| | | | - Sandra Smole
- Massachusetts Department of Public Health, Boston, MA, USA
| | - Erika Buzby
- Massachusetts Department of Public Health, Boston, MA, USA
| | - Joshua Hall
- Massachusetts Department of Public Health, Boston, MA, USA
| | - Stephanie Ash
- Massachusetts Department of Public Health, Boston, MA, USA
| | | | - Seana Cofsky
- Massachusetts Department of Public Health, Boston, MA, USA
| | - Selina Clancy
- Massachusetts Department of Public Health, Boston, MA, USA
| | | | | | | | | | | | | | - Nicole M. Green
- Los Angeles County Public Health Laboratories, Downey, CA, USA
| | - Sean Sierra-Patev
- Rhode Island Department of Health, Rhode Island State Health Laboratory, Providence, RI, USA
| | | | - Richard C. Huard
- Rhode Island Department of Health, Rhode Island State Health Laboratory, Providence, RI, USA
| | - Claire Pearson
- Connecticut Department of Public Health, Rocky Hill, CT, USA
| | | | | | - Jian Ping Huang
- Connecticut Department of Public Health, Rocky Hill, CT, USA
| | - Emily Gagnon
- Connecticut Department of Public Health, Rocky Hill, CT, USA
| | - Ethan Reever
- Connecticut Department of Public Health, Rocky Hill, CT, USA
| | - Jafar Razeq
- Connecticut Department of Public Health, Rocky Hill, CT, USA
| | | | - Vítor Borges
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Rita Ferreira
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Daniel Sobral
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Silvia Duarte
- Technology and Innovation Unit, Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Daniela Santos
- Technology and Innovation Unit, Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Luís Vieira
- Technology and Innovation Unit, Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - João Paulo Gomes
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal,Faculty of Veterinary Medicine, Lusófona University, Lisbon, Portugal
| | - Carly Aquino
- Delaware Public Health Laboratory, Smyrna, DE, USA
| | | | | | - Moneeb Bajwa
- Delaware Public Health Laboratory, Smyrna, DE, USA
| | | | - Holly Miller
- Delaware Public Health Laboratory, Smyrna, DE, USA
| | | | - Ria Allman
- Delaware Public Health Laboratory, Smyrna, DE, USA
| | - Neel Greer
- Delaware Public Health Laboratory, Smyrna, DE, USA
| | - Amary Fall
- Johns Hopkins School of Medicine, Baltimore, MD, USA
| | | | - Martin P. McHugh
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, UK,School of Medicine, University of St Andrews, St Andrews, UK
| | - Daniel M. Maloney
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, UK,Institute of Ecology and Evolution, University of Edinburgh, Edinburgh, UK
| | - Rebecca Dewar
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, UK
| | - Juliet Kenicer
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, UK
| | - Abby Parker
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, UK
| | - Katharine Mathers
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, UK
| | - Jonathan Wild
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, UK
| | - Seb Cotton
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, UK
| | - Kate E. Templeton
- Viral Genotyping Reference Laboratory Edinburgh, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, UK
| | - George Churchwell
- Florida Department of Health, Bureau of Public Health Laboratories, Jacksonville, FL, USA
| | - Philip A. Lee
- Florida Department of Health, Bureau of Public Health Laboratories, Jacksonville, FL, USA
| | - Maria Pedrosa
- Florida Department of Health, Bureau of Public Health Laboratories, Jacksonville, FL, USA
| | - Brenna McGruder
- Florida Department of Health, Bureau of Public Health Laboratories, Jacksonville, FL, USA
| | - Sarah Schmedes
- Florida Department of Health, Bureau of Public Health Laboratories, Jacksonville, FL, USA
| | - Matthew R. Plumb
- Minnesota Department of Health, Public Health Laboratory, St. Paul, MN, USA
| | - Xiong Wang
- Minnesota Department of Health, Public Health Laboratory, St. Paul, MN, USA
| | - Regina Bones Barcellos
- Centro Estadual de Vigilância em Saúde, Secretaria Estadual da Saúde do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Fernanda M.S. Godinho
- Centro Estadual de Vigilância em Saúde, Secretaria Estadual da Saúde do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Richard Steiner Salvato
- Centro Estadual de Vigilância em Saúde, Secretaria Estadual da Saúde do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | | | - Mallery I. Breban
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Nathan D. Grubaugh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA,Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA
| | - Glen R. Gallagher
- Massachusetts Department of Public Health, Boston, MA, USA,Rhode Island Department of Health, Rhode Island State Health Laboratory, Providence, RI, USA
| | - Chantal B.F. Vogels
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
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6
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Gorzalski AJ, Boyles C, Sepcic V, Verma S, Sevinsky J, Libuit K, Van Hooser S, Pandori MW. Rapid repeat infection of SARS-CoV-2 by two highly distinct delta-lineage viruses. Diagn Microbiol Infect Dis 2022; 104:115747. [PMID: 35843112 PMCID: PMC9217632 DOI: 10.1016/j.diagmicrobio.2022.115747] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 06/01/2022] [Accepted: 06/15/2022] [Indexed: 11/30/2022]
Abstract
An instance of sequential infection of an individual with, firstly, the Delta variant and secondly a Delta-sub-lineage has been identified. The individual was found positive for the AY.26 lineage 22 days after being found positive for the Delta [B.1.617.2] variant. The viruses associated with the cases showed dramatic genomic difference, including 31 changes that resulted in deletions or amino acid substitutions. Seven of these differences were observed in the Spike protein. The patient in question was between 30 and 35 years old and had no underlying health conditions. Though singular, this case illustrates the possibility that infection with the Delta variant may not itself be fully protective against a population of SARS-CoV-2 variants that are becoming increasingly diverse.
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Affiliation(s)
| | | | - Victoria Sepcic
- Nevada Department of Health and Human Services, Department of Public and Behavioral Health, Carson City, NV, USA
| | - Subhash Verma
- Department of Microbiology and Immunology, University of Nevada, School of Medicine, Reno, NV, USA
| | | | | | | | - Mark W Pandori
- Nevada State Public Health Laboratory, Reno, NV, USA; Department of Pathology and Laboratory Medicine, University of Nevada, School of Medicine, Reno, NV, USA.
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7
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Gangiredla J, Rand H, Benisatto D, Payne J, Strittmatter C, Sanders J, Wolfgang WJ, Libuit K, Herrick JB, Prarat M, Toro M, Farrell T, Strain E. GalaxyTrakr: a distributed analysis tool for public health whole genome sequence data accessible to non-bioinformaticians. BMC Genomics 2021; 22:114. [PMID: 33568057 PMCID: PMC7877046 DOI: 10.1186/s12864-021-07405-8] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 01/22/2021] [Indexed: 12/12/2022] Open
Abstract
Background Processing and analyzing whole genome sequencing (WGS) is computationally intense: a single Illumina MiSeq WGS run produces ~ 1 million 250-base-pair reads for each of 24 samples. This poses significant obstacles for smaller laboratories, or laboratories not affiliated with larger projects, which may not have dedicated bioinformatics staff or computing power to effectively use genomic data to protect public health. Building on the success of the cloud-based Galaxy bioinformatics platform (http://galaxyproject.org), already known for its user-friendliness and powerful WGS analytical tools, the Center for Food Safety and Applied Nutrition (CFSAN) at the U.S. Food and Drug Administration (FDA) created a customized ‘instance’ of the Galaxy environment, called GalaxyTrakr (https://www.galaxytrakr.org), for use by laboratory scientists performing food-safety regulatory research. The goal was to enable laboratories outside of the FDA internal network to (1) perform quality assessments of sequence data, (2) identify links between clinical isolates and positive food/environmental samples, including those at the National Center for Biotechnology Information sequence read archive (https://www.ncbi.nlm.nih.gov/sra/), and (3) explore new methodologies such as metagenomics. GalaxyTrakr hosts a variety of free and adaptable tools and provides the data storage and computing power to run the tools. These tools support coordinated analytic methods and consistent interpretation of results across laboratories. Users can create and share tools for their specific needs and use sequence data generated locally and elsewhere. Results In its first full year (2018), GalaxyTrakr processed over 85,000 jobs and went from 25 to 250 users, representing 53 different public and state health laboratories, academic institutions, international health laboratories, and federal organizations. By mid-2020, it has grown to 600 registered users and processed over 450,000 analytical jobs. To illustrate how laboratories are making use of this resource, we describe how six institutions use GalaxyTrakr to quickly analyze and review their data. Instructions for participating in GalaxyTrakr are provided. Conclusions GalaxyTrakr advances food safety by providing reliable and harmonized WGS analyses for public health laboratories and promoting collaboration across laboratories with differing resources. Anticipated enhancements to this resource will include workflows for additional foodborne pathogens, viruses, and parasites, as well as new tools and services.
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Affiliation(s)
- Jayanthi Gangiredla
- Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, 20708, Laurel, MD, USA.
| | - Hugh Rand
- Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, 20740, College Park, MD, USA
| | | | - Justin Payne
- Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, 20740, College Park, MD, USA
| | - Charles Strittmatter
- Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, 20740, College Park, MD, USA
| | | | - William J Wolfgang
- Wadsworth Center, New York State Department of Health, NY, 12201, Albany, USA
| | - Kevin Libuit
- Division of Consolidated Laboratory Services, Department of General Services, VA, 23219, Richmond, USA.,Libuit Scientific LLC, 23219, Richmond, VA, USA
| | - James B Herrick
- Center for Genome and Metagenome Studies, James Madison University, 22807, Harrisonburg, VA, USA
| | - Melanie Prarat
- Animal Disease Diagnostic Laboratory, Ohio Department of Agriculture, 43068, Reynoldsburg, Ohio, USA
| | - Magaly Toro
- Laboratorio de Microbiología y Probióticos, Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Chile, Santiago, Chile
| | - Thomas Farrell
- Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, 20740, College Park, MD, USA
| | - Errol Strain
- Center for Veterinary Medicine, U.S. Food and Drug Administration, MD, 20708, Laurel, USA
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M’ikanatha NM, Jacques R, Faucette D, Lisa D, Libuit K, Tate H. 1436. Use of Whole Genome Sequencing to Characterize Antimicrobial-resistant S almonella Berta Isolates from Clinical and Retail Meat Sources. Open Forum Infect Dis 2020. [PMCID: PMC7777209 DOI: 10.1093/ofid/ofaa439.1617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Background Antimicrobial resistance (AMR) in foodborne pathogens of animal origin, including non-typhoidal Salmonella (NTS) are a public health concern. Pennsylvania conducts integrated surveillance for AMR in NTS isolates from human and animal sources in collaboration with the National Antimicrobial Resistance Monitoring System (NARMS). Methods During 2009-2014, Salmonella enterica isolates from various types of meat purchased from randomly selected retail outlets in southeastern Pennsylvania were analyzed by pulsed-field gel electrophoresis (PFGE). We compared PFGE patterns from meat with clinical isolates in the Pennsylvania surveillance database. All meat isolates and a subset of matched clinical isolates were tested for susceptibility to antimicrobial agents. Eleven isolates with indistinguishable PFGE patterns were analyzed by whole genome sequencing (WGS). Sequence data were uploaded to the FDA’s GalaxyTrakr platform for quality assessment, genome assembly, AMR gene detection, and phylogenetic inference via single-nucleotide polymorphism (SNP) analysis. Results PFGE patterns of 86 (48.6%) of 177 meat isolates had PFGE matches to 1,665 clinical isolates; 40 distinct PFGE patterns were represented among the shared patterns. Seventeen (43%) of the 40 shared PFGE patterns (with ≥1 isolate(s) from both sources) were considered multi-drug resistant (MDR). Among the 48 S. Berta pattern JAXX01.0001 isolates, 5 (10.9%) and 2 (100%) from human and meat sources respectively were MDR including resistance to amoxicillin and ceftriaxone. WGS analysis of one isolate from ground turkey meat (PNUSAS061602) was genetically related to clinical isolates including two within 9 and 11 SNPs [Figure]. Presence of genes that hydrolyze extended spectrum cephalosporins (ESC), [blaCMY, blaHERA, or blaTEM], was identified in eight (two meat and six clinical) isolates. One meat isolate was resistant to six antibiotics including ceftriaxone. Figure 2. Single nucleotide polymorphism (SNP) distance matrix showing relatedness in non-typhoidal Salmonella isolates from retail meat (n=2) and human (n=9) sources — Pennsylvania, 2010-2014. One S Berta from retail meat was separated from two clinical two clinical isolates by 9 and 11 SNPs. Second isolate from meat was separated from those associated with human infections by 14 (n=1), 17 (n=1) and ≥20 (n=7). ![]()
Conclusion WGS analysis revealed clinically relevant ESCs genes in closely related S. Berta isolates from human and animal sources. Presence of these genes in NTS highlights the need for enhanced One-Health surveillance and judicious use of antibiotics in humans and food-animal production. Disclosures All Authors: No reported disclosures
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Affiliation(s)
| | | | - David Faucette
- Pennsylvania Department of Health, Harrisburg, Pennsylvania
| | - Dettinger Lisa
- Pennsylvania Department of Health, Harrisburg, Pennsylvania
| | - Kevin Libuit
- Virginia Department of General Services, Richmond, Virginia
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9
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Fahrenfeld N, Knowlton K, Krometis LA, Hession WC, Xia K, Lipscomb E, Libuit K, Green BL, Pruden A. Effect of manure application on abundance of antibiotic resistance genes and their attenuation rates in soil: field-scale mass balance approach. Environ Sci Technol 2014; 48:2643-50. [PMID: 24483241 DOI: 10.1021/es404988k] [Citation(s) in RCA: 151] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
The development of models for understanding antibiotic resistance gene (ARG) persistence and transport is a critical next step toward informing mitigation strategies to prevent the spread of antibiotic resistance in the environment. A field study was performed that used a mass balance approach to gain insight into the transport and dissipation of ARGs following land application of manure. Soil from a small drainage plot including a manure application site, an unmanured control site, and an adjacent stream and buffer zone were sampled for ARGs and metals before and after application of dairy manure slurry and a dry stack mixture of equine, bovine, and ovine manure. Results of mass balance suggest growth of bacterial hosts containing ARGs and/or horizontal gene transfer immediately following slurry application with respect to ermF, sul1, and sul2 and following a lag (13 days) for dry-stack-amended soils. Generally no effects on tet(G), tet(O), or tet(W) soil concentrations were observed despite the presence of these genes in applied manure. Dissipation rates were fastest for ermF in slurry-treated soils (logarithmic decay coefficient of -3.5) and for sul1 and sul2 in dry-stack-amended soils (logarithmic decay coefficients of -0.54 and -0.48, respectively), and evidence for surface and subsurface transport was not observed. Results provide a mass balance approach for tracking ARG fate and insights to inform modeling and limiting the transport of manure-borne ARGs to neighboring surface water.
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Affiliation(s)
- Nicole Fahrenfeld
- Department of Civil and Environmental Engineering, Rutgers, The State University of New Jersey , Piscataway, New Jersey 08854, United States
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