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Pell ME, Blankenship HM, Gaddy JA, Davies HD, Manning SD. Intrapartum antibiotic prophylaxis selects for mutators in group B streptococci among persistently colonized patients. bioRxiv 2024:2024.04.01.587590. [PMID: 38617326 PMCID: PMC11014637 DOI: 10.1101/2024.04.01.587590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Through vaginal colonization, GBS causes severe pregnancy outcomes including neonatal sepsis and meningitis. Although intrapartum antibiotic prophylaxis (IAP) has reduced early-onset disease rates, persistent GBS colonization has been observed in patients following prophylaxis. To determine whether IAP selects for genomic signatures that enhance GBS survival and persistence in the vaginal tract, whole-genome sequencing was performed on 97 isolates from 58 patients before (prenatal) and after (postpartum) IAP/childbirth. Core-gene mutation analysis identified 7,025 mutations between the paired isolates. Three postpartum isolates accounted for 98% of mutations and were classified as "mutators" because of point mutations within DNA repair systems. In vitro assays revealed stronger biofilms in two mutators. These findings suggest that antibiotics select for mutations that promote survival in vivo, which increases the likelihood of transmission to neonates. They also demonstrate how mutators can provide a reservoir of beneficial mutations that enhance fitness and genetic diversity in the GBS population.
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Affiliation(s)
- Macy E Pell
- Michigan State University, Department of Microbiology, Genetics, and Immunology (MGI), E. Lansing, MI
| | - Heather M Blankenship
- Michigan Department of Health and Human Services, Bureau of Laboratories, Division of Infectious Diseases, Lansing, MI
| | - Jennifer A Gaddy
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN
- Tennessee Valley Healthcare Systems, Department of Veterans Affairs, Nashville, TN
| | | | - Shannon D Manning
- Michigan State University, Department of Microbiology, Genetics, and Immunology (MGI), E. Lansing, MI
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Ghai RR, Straily A, Wineland N, Calogero J, Stobierski MG, Signs K, Blievernicht M, Torres-Mendoza Y, Waltenburg MA, Condrey JA, Blankenship HM, Riner D, Barr N, Schalow M, Goodrich J, Collins C, Ahmad A, Metz JM, Herzegh O, Straka K, Arsnoe DM, Duffiney AG, Shriner SA, Kainulainen MH, Carpenter A, Whitehill F, Wendling NM, Stoddard RA, Retchless AC, Uehara A, Tao Y, Li Y, Zhang J, Tong S, Barton Behravesh C. Epidemiologic and Genomic Evidence for Zoonotic Transmission of SARS-CoV-2 among People and Animals on a Michigan Mink Farm, United States, 2020. Viruses 2023; 15:2436. [PMID: 38140677 PMCID: PMC10747742 DOI: 10.3390/v15122436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 12/07/2023] [Accepted: 12/08/2023] [Indexed: 12/24/2023] Open
Abstract
Farmed mink are one of few animals in which infection with SARS-CoV-2 has resulted in sustained transmission among a population and spillback from mink to people. In September 2020, mink on a Michigan farm exhibited increased morbidity and mortality rates due to confirmed SARS-CoV-2 infection. We conducted an epidemiologic investigation to identify the source of initial mink exposure, assess the degree of spread within the facility's overall mink population, and evaluate the risk of further viral spread on the farm and in surrounding wildlife habitats. Three farm employees reported symptoms consistent with COVID-19 the same day that increased mortality rates were observed among the mink herd. One of these individuals, and another asymptomatic employee, tested positive for SARS-CoV-2 by real-time reverse transcription PCR (RT-qPCR) 9 days later. All but one mink sampled on the farm were positive for SARS-CoV-2 based on nucleic acid detection from at least one oral, nasal, or rectal swab tested by RT-qPCR (99%). Sequence analysis showed high degrees of similarity between sequences from mink and the two positive farm employees. Epidemiologic and genomic data, including the presence of F486L and N501T mutations believed to arise through mink adaptation, support the hypothesis that the two employees with SARS-CoV-2 nucleic acid detection contracted COVID-19 from mink. However, the specific source of virus introduction onto the farm was not identified. Three companion animals living with mink farm employees and 31 wild animals of six species sampled in the surrounding area were negative for SARS-CoV-2 by RT-qPCR. Results from this investigation support the necessity of a One Health approach to manage the zoonotic spread of SARS-CoV-2 and underscores the critical need for multifaceted public health approaches to prevent the introduction and spread of respiratory viruses on mink farms.
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Affiliation(s)
- Ria R. Ghai
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
| | - Anne Straily
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
| | - Nora Wineland
- Michigan Department of Agriculture and Rural Development, Lansing, MI 48933, USA
| | - Jennifer Calogero
- Michigan Department of Agriculture and Rural Development, Lansing, MI 48933, USA
| | | | - Kimberly Signs
- Michigan Department of Health and Human Services, Lansing, MI 48909, USA
| | - Melissa Blievernicht
- Michigan Department of Agriculture and Rural Development, Lansing, MI 48933, USA
| | | | | | - Jillian A. Condrey
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
| | | | - Diana Riner
- Michigan Department of Health and Human Services, Lansing, MI 48909, USA
| | - Nancy Barr
- Michigan Department of Agriculture and Rural Development, Lansing, MI 48933, USA
| | - Michele Schalow
- Michigan Department of Agriculture and Rural Development, Lansing, MI 48933, USA
| | - Jarold Goodrich
- Michigan Department of Agriculture and Rural Development, Lansing, MI 48933, USA
| | - Cheryl Collins
- Michigan Department of Agriculture and Rural Development, Lansing, MI 48933, USA
| | - Ausaf Ahmad
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
| | - John Michael Metz
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
| | - Owen Herzegh
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
| | - Kelly Straka
- Michigan Department of Natural Resources, Lansing, MI 48909, USA
| | - Dustin M. Arsnoe
- U.S. Department of Agriculture Animal and Plant Health Inspection Service, Washington, DC 20250, USA
| | - Anthony G. Duffiney
- U.S. Department of Agriculture Animal and Plant Health Inspection Service, Washington, DC 20250, USA
| | - Susan A. Shriner
- U.S. Department of Agriculture Animal and Plant Health Inspection Service, Washington, DC 20250, USA
| | | | - Ann Carpenter
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
| | - Florence Whitehill
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
| | - Natalie M. Wendling
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
| | - Robyn A. Stoddard
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
| | - Adam C. Retchless
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
| | - Anna Uehara
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
| | - Ying Tao
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
| | - Yan Li
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
| | - Jing Zhang
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
| | - Suxiang Tong
- U.S. Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; (R.R.G.)
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Rodrigues JA, Blankenship HM, Cha W, Mukherjee S, Sloup RE, Rudrik JT, Soehnlen M, Manning SD. Pangenomic analyses of antibiotic-resistant Campylobacter jejuni reveal unique lineage distributions and epidemiological associations. Microb Genom 2023; 9:mgen001073. [PMID: 37526649 PMCID: PMC10483415 DOI: 10.1099/mgen.0.001073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 06/29/2023] [Indexed: 08/02/2023] Open
Abstract
Application of whole-genome sequencing (WGS) to characterize foodborne pathogens has advanced our understanding of circulating genotypes and evolutionary relationships. Herein, we used WGS to investigate the genomic epidemiology of Campylobacter jejuni, a leading cause of foodborne disease. Among the 214 strains recovered from patients with gastroenteritis in Michigan, USA, 85 multilocus sequence types (STs) were represented and 135 (63.1 %) were phenotypically resistant to at least one antibiotic. Horizontally acquired antibiotic resistance genes were detected in 128 (59.8 %) strains and the genotypic resistance profiles were mostly consistent with the phenotypes. Core-gene phylogenetic reconstruction identified three sequence clusters that varied in frequency, while a neighbour-net tree detected significant recombination among the genotypes (pairwise homoplasy index P<0.01). Epidemiological analyses revealed that travel was a significant contributor to pangenomic and ST diversity of C. jejuni, while some lineages were unique to rural counties and more commonly possessed clinically important resistance determinants. Variation was also observed in the frequency of lineages over the 4 year period with chicken and cattle specialists predominating. Altogether, these findings highlight the importance of geographically specific factors, recombination and horizontal gene transfer in shaping the population structure of C. jejuni. They also illustrate the usefulness of WGS data for predicting antibiotic susceptibilities and surveillance, which are important for guiding treatment and prevention strategies.
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Affiliation(s)
- Jose A. Rodrigues
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
| | - Heather M. Blankenship
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
- Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, Michigan, USA
| | - Wonhee Cha
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
- Present address: National Veterinary Institute, Uppsala, Sweden
| | - Sanjana Mukherjee
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
- Present address: Center for Global Health Science and Security, Georgetown University, Washington, USA
| | - Rebekah E. Sloup
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
| | - James T. Rudrik
- Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, Michigan, USA
| | - Marty Soehnlen
- Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, Michigan, USA
| | - Shannon D. Manning
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
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Pereira E, Conrad A, Tesfai A, Palacios A, Kandar R, Kearney A, Locas A, Jamieson F, Elliot E, Otto M, Kurdilla K, Tijerina M, Son I, Pettengill JB, Chen Y, Fox T, Lane C, Aguillon R, Huffman J, Sheau Fong Low M, Wise M, Edwards L, Bidol S, Blankenship HM, Rosen HE, Leclercq A, Lecuit M, Tourdjman M, Herber H, Singleton LS, Viazis S, Bazaco MC. Multinational Outbreak of Listeria monocytogenes Infections Linked to Enoki Mushrooms Imported from the Republic of Korea 2016-2020. J Food Prot 2023; 86:100101. [PMID: 37169291 PMCID: PMC10947956 DOI: 10.1016/j.jfp.2023.100101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 05/01/2023] [Accepted: 05/04/2023] [Indexed: 05/13/2023]
Abstract
Keeping the global food supply safe necessitates international collaborations between countries. Health and regulatory agencies routinely communicate during foodborne illness outbreaks, allowing partners to share investigational evidence. A 2016-2020 outbreak of Listeria monocytogenes infections linked to imported enoki mushrooms required a multinational collaborative investigation among the United States, Canada, Australia, and France. Ultimately, this outbreak included 48 ill people, 36 in the United States and 12 in Canada, and was linked to enoki mushrooms sourced from one manufacturer located in the Republic of Korea. Epidemiologic, laboratory, and traceback evidence led to multiple regulatory actions, including extensive voluntary recalls by three firms in the United States and one firm in Canada. In the United States and Canada, the Korean manufacturer was placed on import alert while other international partners provided information about their respective investigations and advised the public not to eat the recalled enoki mushrooms. The breadth of the geographic distribution of this outbreak emphasizes the global reach of the food industry. This investigation provides a powerful example of the impact of national and international coordination of efforts to respond to foodborne illness outbreaks and protect consumers. It also demonstrates the importance of fast international data sharing and collaboration in identifying and stopping foodborne outbreaks in the global community. Additionally, it is a meaningful example of the importance of food sampling, testing, and integration of sequencing results into surveillance databases.
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Affiliation(s)
- Evelyn Pereira
- Food and Drug Administration, College Park, Maryland, USA.
| | - Amanda Conrad
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
| | - Adiam Tesfai
- Food and Drug Administration, College Park, Maryland, USA
| | | | - Rima Kandar
- Public Health Agency of Canada, Ottawa, Ontario, Canada
| | - Ashley Kearney
- Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Annie Locas
- Canadian Food Inspection Agency, Ottawa, Ontario, Canada
| | - Fred Jamieson
- Canadian Food Inspection Agency, Ottawa, Ontario, Canada
| | - Elisa Elliot
- Food and Drug Administration, College Park, Maryland, USA
| | - Mark Otto
- Food and Drug Administration, College Park, Maryland, USA; Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Kerry Kurdilla
- Food and Drug Administration, College Park, Maryland, USA
| | - Mary Tijerina
- Food and Drug Administration, College Park, Maryland, USA
| | - Insook Son
- Food and Drug Administration, College Park, Maryland, USA
| | | | - Yi Chen
- Food and Drug Administration, College Park, Maryland, USA
| | - Teresa Fox
- Food and Drug Administration, College Park, Maryland, USA
| | - Chris Lane
- Food and Drug Administration, College Park, Maryland, USA
| | - Ryan Aguillon
- Food and Drug Administration, College Park, Maryland, USA
| | - Jasmine Huffman
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | | | - Matthew Wise
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Lauren Edwards
- Michigan Department of Agriculture and Rural Development, USA
| | - Sally Bidol
- Michigan Department of Health and Human Services, USA
| | | | | | - Alexandre Leclercq
- Institut Pasteur, Université Paris Cité, Inserm U1117, Biology of Infection Unit, Paris-F, France; Institut Pasteur, National Reference Centre and WHO Collaborating Centre Listeria, Paris-F, France
| | - Marc Lecuit
- Institut Pasteur, Université Paris Cité, Inserm U1117, Biology of Infection Unit, Paris-F, France; Institut Pasteur, National Reference Centre and WHO Collaborating Centre Listeria, Paris-F, France; Necker-Enfants Malades University Hospital, Division of Infectious Diseases and Tropical Medicine, APHP, Institut Imagine, Paris-F, France
| | | | - Hubert Herber
- Alert Unit, General Directorate for Competition Policy, Consumer Affairs and Fraud Control, French Ministry for the Economy and Finance, France
| | | | - Stelios Viazis
- Food and Drug Administration, College Park, Maryland, USA
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Blankenship HM, Dietrich SE, Burgess E, Wholehan J, Soehnlen M, Manning SD. Whole-Genome Sequencing of Shiga Toxin-Producing Escherichia coli for Characterization and Outbreak Investigation. Microorganisms 2023; 11:1298. [PMID: 37317272 DOI: 10.3390/microorganisms11051298] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 05/11/2023] [Accepted: 05/12/2023] [Indexed: 06/16/2023] Open
Abstract
Shiga toxin-producing Escherichia coli (STEC) causes high frequencies of foodborne infections worldwide and has been linked to numerous outbreaks each year. Pulsed-field gel electrophoresis (PFGE) has been the gold standard for surveillance until the recent transition to whole-genome sequencing (WGS). To further understand the genetic diversity and relatedness of outbreak isolates, a retrospective analysis of 510 clinical STEC isolates was conducted. Among the 34 STEC serogroups represented, most (59.6%) belonged to the predominant six non-O157 serogroups. Core genome single nucleotide polymorphism (SNP) analysis differentiated clusters of isolates with similar PFGE patterns and multilocus sequence types (STs). One serogroup O26 outbreak strain and another non-typeable (NT) strain, for instance, were identical by PFGE and clustered together by MLST; however, both were distantly related in the SNP analysis. In contrast, six outbreak-associated serogroup O5 strains clustered with five ST-175 serogroup O5 isolates, which were not part of the same outbreak as determined by PFGE. The use of high-quality SNP analyses enhanced the discrimination of these O5 outbreak strains into a single cluster. In all, this study demonstrates how public health laboratories can more rapidly use WGS and phylogenetics to identify related strains during outbreak investigations while simultaneously uncovering important genetic attributes that can inform treatment practices.
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Affiliation(s)
- Heather M Blankenship
- Bureau of Laboratories, Michigan Department of Health and Human Services, Lansing, MI 48824, USA
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824, USA
| | - Stephen E Dietrich
- Bureau of Laboratories, Michigan Department of Health and Human Services, Lansing, MI 48824, USA
| | - Elizabeth Burgess
- Bureau of Laboratories, Michigan Department of Health and Human Services, Lansing, MI 48824, USA
| | - Jason Wholehan
- Bureau of Laboratories, Michigan Department of Health and Human Services, Lansing, MI 48824, USA
| | - Marty Soehnlen
- Bureau of Laboratories, Michigan Department of Health and Human Services, Lansing, MI 48824, USA
| | - Shannon D Manning
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824, USA
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Abstract
Whole-genome sequencing has become a preferred method for studying bacterial plasmids, as it is generally assumed to capture the entire genome. However, long-read genome assemblers have been shown to sometimes miss plasmid sequences - an issue that has been associated with plasmid size. The purpose of this study was to investigate the relationship between plasmid size and plasmid recovery by the long-read-only assemblers, Flye, Raven, Miniasm, and Canu. This was accomplished by determining the number of times each assembler successfully recovered 33 plasmids, ranging from 1919 to 194 062 bp in size and belonging to 14 bacterial isolates from six bacterial genera, using Oxford Nanopore long reads. These results were additionally compared to plasmid recovery rates by the short-read-first assembler, Unicycler, using both Oxford Nanopore long reads and Illumina short reads. Results from this study indicate that Canu, Flye, Miniasm, and Raven are prone to missing plasmid sequences, whereas Unicycler was successful at recovering 100 % of plasmid sequences. Excluding Canu, most plasmid loss by long-read-only assemblers was due to failure to recover plasmids smaller than 10 kb. As such, it is recommended that Unicycler be used to increase the likelihood of plasmid recovery during bacterial genome assembly.
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Affiliation(s)
- Jared Johnson
- Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, MI, 48906, USA
| | - Marty Soehnlen
- Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, MI, 48906, USA
| | - Heather M Blankenship
- Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, MI, 48906, USA
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7
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Brito AF, Semenova E, Dudas G, Hassler GW, Kalinich CC, Kraemer MUG, Ho J, Tegally H, Githinji G, Agoti CN, Matkin LE, Whittaker C, Howden BP, Sintchenko V, Zuckerman NS, Mor O, Blankenship HM, de Oliveira T, Lin RTP, Siqueira MM, Resende PC, Vasconcelos ATR, Spilki FR, Aguiar RS, Alexiev I, Ivanov IN, Philipova I, Carrington CVF, Sahadeo NSD, Branda B, Gurry C, Maurer-Stroh S, Naidoo D, von Eije KJ, Perkins MD, van Kerkhove M, Hill SC, Sabino EC, Pybus OG, Dye C, Bhatt S, Flaxman S, Suchard MA, Grubaugh ND, Baele G, Faria NR. Global disparities in SARS-CoV-2 genomic surveillance. Nat Commun 2022; 13:7003. [PMID: 36385137 PMCID: PMC9667854 DOI: 10.1038/s41467-022-33713-y] [Citation(s) in RCA: 58] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Accepted: 09/29/2022] [Indexed: 11/17/2022] Open
Abstract
Genomic sequencing is essential to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments, vaccines, and guide public health responses. To investigate the global SARS-CoV-2 genomic surveillance, we used sequences shared via GISAID to estimate the impact of sequencing intensity and turnaround times on variant detection in 189 countries. In the first two years of the pandemic, 78% of high-income countries sequenced >0.5% of their COVID-19 cases, while 42% of low- and middle-income countries reached that mark. Around 25% of the genomes from high income countries were submitted within 21 days, a pattern observed in 5% of the genomes from low- and middle-income countries. We found that sequencing around 0.5% of the cases, with a turnaround time <21 days, could provide a benchmark for SARS-CoV-2 genomic surveillance. Socioeconomic inequalities undermine the global pandemic preparedness, and efforts must be made to support low- and middle-income countries improve their local sequencing capacity.
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Affiliation(s)
- Anderson F Brito
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
- Instituto Todos pela Saúde, São Paulo, SP, Brazil.
| | | | - Gytis Dudas
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Gabriel W Hassler
- Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Chaney C Kalinich
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
- Yale School of Medicine, Yale University, New Haven, CT, USA
| | | | - Joses Ho
- GISAID Global Data Science Initiative, Munich, Germany
- Bioinformatics Institute & ID Labs, Agency for Science Technology and Research, Singapore, Singapore
| | - Houriiyah Tegally
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - George Githinji
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
- Department of Biochemistry and Biotechnology, Pwani University, Kilifi, Kenya
| | - Charles N Agoti
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
- School of Health and Human Sciences, Pwani University, Kilifi, Kenya
| | - Lucy E Matkin
- Department of Biology, University of Oxford, Oxford, UK
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | | | | | | | | | | | | | | | | | - Benjamin P Howden
- Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
| | - Vitali Sintchenko
- Sydney Institute for Infectious Diseases, The University of Sydney, Sydney, NSW, Australia
- Institute of Clinical Pathology and Medical Research, NSW Health Pathology, Westmead, NSW, Australia
| | - Neta S Zuckerman
- Central Virology Laboratory, Israel Ministry of Health, Sheba Medical Center, Ramat Gan, Israel
| | - Orna Mor
- Central Virology Laboratory, Israel Ministry of Health, Sheba Medical Center, Ramat Gan, Israel
| | - Heather M Blankenship
- Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, MI, USA
| | - Tulio de Oliveira
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
- Department of Global Health, University of Washington, Seattle, WA, USA
| | - Raymond T P Lin
- National Centre for Infectious Diseases, Singapore, Singapore
| | - Marilda Mendonça Siqueira
- Laboratory of Respiratory Viruses and Measles, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - Paola Cristina Resende
- Laboratory of Respiratory Viruses and Measles, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - Ana Tereza R Vasconcelos
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Fernando R Spilki
- Feevale University, Institute of Health Sciences, Novo Hamburgo, RS, Brazil
| | - Renato Santana Aguiar
- Laboratório de Biologia Integrativa, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- Instituto D'Or de Pesquisa e Ensino (IDOR), Rio de Janeiro, Brazil
| | - Ivailo Alexiev
- National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria
| | - Ivan N Ivanov
- National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria
| | - Ivva Philipova
- National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria
| | - Christine V F Carrington
- Department of Preclinical Sciences, Faculty of Medical Sciences, The University of the West Indies, St. Augustine, Trinidad and Tobago
| | - Nikita S D Sahadeo
- Department of Preclinical Sciences, Faculty of Medical Sciences, The University of the West Indies, St. Augustine, Trinidad and Tobago
| | - Ben Branda
- GISAID Global Data Science Initiative, Munich, Germany
| | - Céline Gurry
- GISAID Global Data Science Initiative, Munich, Germany
| | - Sebastian Maurer-Stroh
- GISAID Global Data Science Initiative, Munich, Germany
- Bioinformatics Institute & ID Labs, Agency for Science Technology and Research, Singapore, Singapore
- National Centre for Infectious Diseases, Singapore, Singapore
| | - Dhamari Naidoo
- Health Emergencies Programme, World Health Organization Regional Office for South-East Asia, New Delhi, India
| | - Karin J von Eije
- Department of Medical Microbiology and Infection Prevention, Division of Clinical Virology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Emerging Diseases and Zoonoses Unit, Health Emergencies Programme, World Health Organization, Geneva, Switzerland
| | - Mark D Perkins
- Emerging Diseases and Zoonoses Unit, Health Emergencies Programme, World Health Organization, Geneva, Switzerland
| | - Maria van Kerkhove
- Emerging Diseases and Zoonoses Unit, Health Emergencies Programme, World Health Organization, Geneva, Switzerland
| | | | - Ester C Sabino
- Instituto Todos pela Saúde, São Paulo, SP, Brazil
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Oliver G Pybus
- Department of Biology, University of Oxford, Oxford, UK
- Royal Veterinary College, Hawkshead, UK
| | | | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Seth Flaxman
- Department of Computer Science, University of Oxford, Oxford, UK
| | - Marc A Suchard
- Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 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
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Nuno R Faria
- Department of Biology, University of Oxford, Oxford, UK.
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK.
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
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Brito AF, Semenova E, Dudas G, Hassler GW, Kalinich CC, Kraemer MU, Ho J, Tegally H, Githinji G, Agoti CN, Matkin LE, Whittaker C, Howden BP, Sintchenko V, Zuckerman NS, Mor O, Blankenship HM, de Oliveira T, Lin RTP, Siqueira MM, Resende PC, Vasconcelos ATR, Spilki FR, Aguiar RS, Alexiev I, Ivanov IN, Philipova I, Carrington CVF, Sahadeo NSD, Gurry C, Maurer-Stroh S, Naidoo D, von Eije KJ, Perkins MD, van Kerkhove M, Hill SC, Sabino EC, Pybus OG, Dye C, Bhatt S, Flaxman S, Suchard MA, Grubaugh ND, Baele G, Faria NR. Global disparities in SARS-CoV-2 genomic surveillance. medRxiv 2021:2021.08.21.21262393. [PMID: 34462754 PMCID: PMC8404891 DOI: 10.1101/2021.08.21.21262393] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Genomic sequencing provides critical information to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments and vaccines, and guide public health responses. To investigate the spatiotemporal heterogeneity in the global SARS-CoV-2 genomic surveillance, we estimated the impact of sequencing intensity and turnaround times (TAT) on variant detection in 167 countries. Most countries submit genomes >21 days after sample collection, and 77% of low and middle income countries sequenced <0.5% of their cases. We found that sequencing at least 0.5% of the cases, with a TAT <21 days, could be a benchmark for SARS-CoV-2 genomic surveillance efforts. Socioeconomic inequalities substantially impact our ability to quickly detect SARS-CoV-2 variants, and undermine the global pandemic preparedness.
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Affiliation(s)
- Anderson F. Brito
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA
- Instituto Todos pela Saúde, São Paulo, São Paulo, Brazil
| | - Elizaveta Semenova
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA
- Department of Mathematics, Imperial College London, London, UK
| | - Gytis Dudas
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
| | - Gabriel W. Hassler
- Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Chaney C. Kalinich
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA
- Yale School of Medicine, Yale University, New Haven, Connecticut, USA
| | | | - Joses Ho
- GISAID Global Data Science Initiative, Munich, Germany
- Bioinformatics Institute & ID Labs, Agency for Science Technology and Research, Singapore, Singapore
| | - Houriiyah Tegally
- KwaZulu–Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, University of KwaZulu–Natal, Durban, South Africa
| | - George Githinji
- KEMRI-Wellcome Trust Research Programme, Kenya
- Department of Biochemistry and Biotechnology, Pwani University, Kenya
| | | | - Lucy E. Matkin
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, United Kingdom
| | | | | | | | | | - Benjamin P Howden
- Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
| | - Vitali Sintchenko
- Sydney Institute for Infectious Diseases, The University of Sydney, Sydney, New South Wales, Australia
- Institute of Clinical Pathology and Medical Research, NSW Health Pathology, Westmead, New South Wales 2145, Australia
| | - Neta S. Zuckerman
- Central Virology Laboratory, Israel Ministry of Health, Sheba Medical Center, Israel
| | - Orna Mor
- Central Virology Laboratory, Israel Ministry of Health, Sheba Medical Center, Israel
| | - Heather M Blankenship
- Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, Michigan, USA
| | - Tulio de Oliveira
- KwaZulu–Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, University of KwaZulu–Natal, Durban, South Africa
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
- Department of Global Health, University of Washington, Seattle, Washington, USA
| | | | | | | | | | - Fernando R. Spilki
- Feevale University, Institute of Health Sciences, Novo Hamburgo, Rio Grande do Sul, Brazil
| | - Renato Santana Aguiar
- Laboratório de Biologia Integrativa, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- Instituto D’Or de Pesquisa e Ensino (IDOR), Rio de Janeiro, Brazil
| | - Ivailo Alexiev
- National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria
| | - Ivan N. Ivanov
- National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria
| | - Ivva Philipova
- National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria
| | - Christine V. F. Carrington
- Department of Preclinical Sciences, Faculty of Medical Sciences, The University of the West Indies, St. Augustine, Trinidad and Tobago
| | - Nikita S. D. Sahadeo
- Department of Preclinical Sciences, Faculty of Medical Sciences, The University of the West Indies, St. Augustine, Trinidad and Tobago
| | - Céline Gurry
- GISAID Global Data Science Initiative, Munich, Germany
| | - Sebastian Maurer-Stroh
- GISAID Global Data Science Initiative, Munich, Germany
- Bioinformatics Institute & ID Labs, Agency for Science Technology and Research, Singapore, Singapore
- National Centre for Infectious Diseases, Singapore
| | - Dhamari Naidoo
- Health Emergencies Programme, World Health Organization Regional Office for South-East Asia, New Delhi, India
| | - Karin J von Eije
- Department of Medical Microbiology and Infection Prevention, Division of Clinical Virology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Emerging Diseases and Zoonoses Unit, Health Emergencies Programme, World Health Organization, Geneva, Switzerland
| | - Mark D. Perkins
- Emerging Diseases and Zoonoses Unit, Health Emergencies Programme, World Health Organization, Geneva, Switzerland
| | - Maria van Kerkhove
- Emerging Diseases and Zoonoses Unit, Health Emergencies Programme, World Health Organization, Geneva, Switzerland
| | | | - Ester C. Sabino
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Oliver G. Pybus
- Department of Zoology, University of Oxford, Oxford, United Kingdom
- Royal Veterinary College, Hawkshead, United Kingdom
| | - Christopher Dye
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
- The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, United Kingdom
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Seth Flaxman
- Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Marc A. Suchard
- Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Nathan D. Grubaugh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, USA
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Nuno R. Faria
- Department of Zoology, University of Oxford, Oxford, United Kingdom
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
- Sydney Institute for Infectious Diseases, The University of Sydney, Sydney, New South Wales, Australia
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
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Blankenship HM, Mosci RE, Dietrich S, Burgess E, Wholehan J, McWilliams K, Pietrzen K, Benko S, Gatesy T, Rudrik JT, Soehnlen M, Manning SD. Population structure and genetic diversity of non-O157 Shiga toxin-producing Escherichia coli (STEC) clinical isolates from Michigan. Sci Rep 2021; 11:4461. [PMID: 33627701 PMCID: PMC7904848 DOI: 10.1038/s41598-021-83775-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Accepted: 02/01/2021] [Indexed: 01/31/2023] Open
Abstract
Non-O157 STEC are increasingly linked to foodborne infections, yet little is known about the diversity and molecular epidemiology across locations. Herein, we used whole genome sequencing to examine genetic variation in 894 isolates collected from Michigan patients between 2001 and 2018. In all, 67 serotypes representing 69 multilocus sequence types were identified. Serotype diversity increased from an average of four (2001-2006) to 17 (2008-2018) serotypes per year. The top six serogroups reported nationally caused > 60% of infections in 16 of the 18 years; serogroups O111 and O45 were associated with hospitalization as were age ≥ 65 years, diarrhea with blood and female sex. Phylogenetic analyses of seven multilocus sequence typing (MLST) loci identified three clades as well as evidence of parallel evolution and recombination. Most (95.5%) isolates belonged to one clade, which could be further differentiated into seven subclades comprising isolates with varying virulence gene profiles and serotypes. No association was observed between specific clades and the epidemiological data, suggesting that serogroup- and serotype-specific associations are more important predictors of disease outcomes than lineages defined by MLST. Molecular epidemiological studies of non-O157 STEC are important to enhance understanding of circulating strain distributions and traits, genetic variation, and factors that may impact disease risk and severity.
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Affiliation(s)
- Heather M Blankenship
- Department of Microbiology and Molecular Genetics, Michigan State University, 1129 Farm Lane, East Lansing, MI, 48824, USA
- Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, MI, 48906, USA
| | - Rebekah E Mosci
- Department of Microbiology and Molecular Genetics, Michigan State University, 1129 Farm Lane, East Lansing, MI, 48824, USA
| | - Stephen Dietrich
- Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, MI, 48906, USA
| | - Elizabeth Burgess
- Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, MI, 48906, USA
| | - Jason Wholehan
- Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, MI, 48906, USA
| | - Karen McWilliams
- Michigan Department of Agriculture and Rural Development, East Lansing, MI, 48823, USA
| | - Karen Pietrzen
- Michigan Department of Agriculture and Rural Development, East Lansing, MI, 48823, USA
| | - Scott Benko
- Michigan Department of Agriculture and Rural Development, East Lansing, MI, 48823, USA
| | - Ted Gatesy
- Michigan Department of Agriculture and Rural Development, East Lansing, MI, 48823, USA
| | - James T Rudrik
- Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, MI, 48906, USA
| | - Marty Soehnlen
- Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, MI, 48906, USA
| | - Shannon D Manning
- Department of Microbiology and Molecular Genetics, Michigan State University, 1129 Farm Lane, East Lansing, MI, 48824, USA.
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Rodrigues JA, Blankenship HM, Cha W, Mosci R, Manning SD. 1199. Phylogenomic analysis of Campylobacter jejuni isolated from gastroenteritis cases in Michigan. Open Forum Infect Dis 2020. [PMCID: PMC7776441 DOI: 10.1093/ofid/ofaa439.1384] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Background C. jejuni is the leading cause of bacterial gastroenteritis worldwide. It has been classified as a serious antibiotic resistant threat, causing 13,000 hospitalizations and 120 deaths annually. Our goal was to describe the diversity of clinical C. jejuni using phylogenomics and classify resistance mechanisms. Methods Isolates were collected via sentinel surveillance at four hospitals, and demographic and clinical data were obtained. DNA was extracted and sequenced. Raw reads were processed with Trimmomatic and quality checked with FastQC. De novo genome assembly was performed in Spades. Assembled genomes were filtered for quality and completeness; samples of 1.4-2.1MB were annotated in Prokka followed by pangenome and phylogenetic analyses. Multilocus sequence typing loci and virulence and antibiotic resistance genes were extracted from each genome. Results Among the 214 C. jejuni isolates recovered, 86 unique sequence types (STs) were identified; five were novel STs with unique allele combinations. ST353 (8.3%: n=18), ST982 (7.4%: n=16), ST50 (5.1 %: n=11) and ST48 (5.1%: n=11) were the most prevalent STs identified, while the majority (50.1%: n=50) of STs were singletons. The pangenome analysis identified 8781, 615, and 1169 total, core, and shell core genes, respectively, which grouped the isolates into three major clades. Most isolates belonged to clade 1. A neighbor-net analysis detected significant recombination among all 86 STs (pairwise homoplasy index p=< 0.00001) and evidence of horizontal gene transfer across clades. The beta-lactamase gene, blaOXA-605, was the most common resistance gene identified (58.8%: n=125) followed by tet(O) (56.0%: n=121), which mediate resistance to beta-lactams and tetracyclines, respectively. Resistance phenotypes were confirmed using microbroth dilution. Conclusion: Together, these data demonstrate that the C. jejuni population is highly diverse and carries important resistance determinants. The phylogenomic analyses also provide insight into the evolution of this major foodborne pathogen. Future work will focus on identifying molecular and epidemiological factors associated with specific strain types and resistance and virulence profiles circulating in Michigan. Disclosures All Authors: No reported disclosures
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Affiliation(s)
| | - Heather M Blankenship
- Michigan State University/Michigan Department of Health and Human Services, East Lansing, Michigan
| | - Wonhee Cha
- Michigan State University, East Lansing, Michigan
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Blankenship HM, Mosci RE, Phan Q, Fontana J, Rudrik JT, Manning SD. Genetic Diversity of Non-O157 Shiga Toxin-Producing Escherichia coli Recovered From Patients in Michigan and Connecticut. Front Microbiol 2020; 11:529. [PMID: 32300338 PMCID: PMC7145412 DOI: 10.3389/fmicb.2020.00529] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [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: 12/13/2019] [Accepted: 03/11/2020] [Indexed: 12/16/2022] Open
Abstract
Shiga toxin-producing Escherichia coli (STEC) are important foodborne pathogens and non-O157 serotypes have been gradually increasing in frequency. The non-O157 STEC population is diverse and is often characterized using serotyping and/or multilocus sequence typing (MLST). Although spacers within clustered regularly interspaced repeat (CRISPR) regions were shown to comprise horizontally acquired DNA elements, this region does not actively acquire spacers in STEC. Hence, it is useful for further characterizing non-O157 STEC and examining relationships between strains. Our study goal was to evaluate the genetic relatedness of 41 clinical non-O157 isolates identified in Michigan between 2001 and 2005 while comparing to 114 isolates from Connecticut during an overlapping time period. Whole genome sequencing (WGS) was performed, and sequences were extracted for serotyping, MLST and CRISPR analysis. Phylogenetic analysis of MLST and CRISPR data was performed using the Neighbor joining and unweighted pair group method with arithmetic mean (UPGMA) algorithms, respectively. In all, 29 serogroups were identified; eight were unique to Michigan and 13 to Connecticut. “Big-six” serogroup frequencies were similar by state (Michigan: 73.2%, Connecticut: 81.6%), though STEC O121 was not found in Michigan. The distribution of sequence types (STs) and CRISPR profiles was also similar across states. Interestingly, big-six serogroups such as O103 and O26, grouped into different STs located on distinct branches of the phylogeny, further confirming that serotyping alone is not adequate for evaluating strain relatedness. Comparatively, the CRISPR analysis identified 361 unique spacers that grouped into 80 different CRISPR profiles. CRISPR spacers 231 and 317 were isolated from 79.2% (n = 118) and 59.1% (n = 88) of strains, respectively, regardless of serogroup and ST. Spacer profiles clustered according to the MLST analysis, though some discrepancies were noted. Indeed, use of both MLST and CRISPR typing enhanced the discriminatory power when compared to the use of each tool separately. These data highlight the genetic diversity of clinical STEC from different locations and show that CRISPR profiling can be used alongside MLST to discriminate related strains. Use of targeted sequencing approaches are particularly helpful for sites without WGS capabilities and can help define which strains require additional characterization using more discriminatory methods.
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Affiliation(s)
- Heather M Blankenship
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, United States
| | - Rebekah E Mosci
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, United States
| | - Quyen Phan
- Connecticut Department of Public Health, Hartford, CT, United States
| | - John Fontana
- Connecticut Department of Public Health, Hartford, CT, United States
| | - James T Rudrik
- Bureau of Laboratories, Michigan Department of Health and Human Services, Lansing, MI, United States
| | - Shannon D Manning
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, United States
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