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Stephenson A, Lastra L, Nguyen B, Chen YJ, Nivala J, Ceze L, Strauss K. Physical Laboratory Automation in Synthetic Biology. ACS Synth Biol 2023; 12:3156-3169. [PMID: 37935025 DOI: 10.1021/acssynbio.3c00345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2023]
Abstract
Synthetic Biology has overcome many of the early challenges facing the field and is entering a systems era characterized by adoption of Design-Build-Test-Learn (DBTL) approaches. The need for automation and standardization to enable reproducible, scalable, and translatable research has become increasingly accepted in recent years, and many of the hardware and software tools needed to address these challenges are now in place or under development. However, the lack of connectivity between DBTL modules and barriers to access and adoption remain significant challenges to realizing the full potential of lab automation. In this review, we characterize and classify the state of automation in synthetic biology with a focus on the physical automation of experimental workflows. Though fully autonomous scientific discovery is likely a long way off, impressive progress has been made toward automating critical elements of experimentation by combining intelligent hardware and software tools. It is worth questioning whether total automation that removes humans entirely from the loop should be the ultimate goal, and considerations for appropriate automation versus total automation are discussed in this light while emphasizing areas where further development is needed in both contexts.
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Affiliation(s)
- Ashley Stephenson
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States
- Microsoft Research, Redmond, Washington 98052, United States
| | - Lauren Lastra
- Microsoft Research, Redmond, Washington 98052, United States
| | - Bichlien Nguyen
- Microsoft Research, Redmond, Washington 98052, United States
| | - Yuan-Jyue Chen
- Microsoft Research, Redmond, Washington 98052, United States
| | - Jeff Nivala
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States
| | - Luis Ceze
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States
| | - Karin Strauss
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States
- Microsoft Research, Redmond, Washington 98052, United States
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2
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Rykachevsky A, Stepakov A, Muzyukina P, Medvedeva S, Dobrovolski M, Burnaev E, Severinov K, Savitskaya E. SCRAMBLER: A Tool for De Novo CRISPR Array Reconstruction and Its Application for Analysis of the Structure of Prokaryotic Populations. CRISPR J 2021; 4:673-685. [PMID: 34661428 DOI: 10.1089/crispr.2021.0012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
Abstract
CRISPR arrays are prokaryotic genomic loci consisting of repeat sequences alternating with unique spacers acquired from foreign nucleic acids. As one of the fastest-evolving parts of the genome, CRISPR arrays can be used to differentiate closely related prokaryotic lineages and track individual strains in prokaryotic communities. However, the assembly of full-length CRISPR arrays sequences remains a problem. Here, we developed SCRAMBLER, a tool that includes several pipelines for assembling CRISPR arrays from high-throughput short-read sequencing data. We assessed its performance with model data sets (Escherichia coli strains containing different CRISPR arrays and imitating prokaryotic communities of different complexities) and intestinal microbiomes of extant and extinct pachyderms. Evaluation of SCRAMBLER's performance using model data sets demonstrated its ability to assemble CRISPR arrays correctly from reads containing pairs of spacers, yielding a precision rate of >80% and a recall rate of 60-85% when checked against ground-truth data. Likewise, SCRAMBLER successfully assembled CRISPR arrays from the environmental samples, as attested by their matching with database entries. SCRAMBLER, an open-source software (github.com/biolab-tools/SCRAMBLER), can facilitate analysis of the composition and dynamics of CRISPR arrays in complex communities.
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Affiliation(s)
- Anton Rykachevsky
- Center for Computational and Data-Intensive Science and Engineering and Rutgers, State University of New Jersey, Piscataway, USA
| | - Alexander Stepakov
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Institute of Gene Biology, Russian Academy of Sciences, Moscow, Russia; Rutgers, State University of New Jersey, Piscataway, USA
| | - Polina Muzyukina
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia; Rutgers, State University of New Jersey, Piscataway, USA
| | - Sofia Medvedeva
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia; Rutgers, State University of New Jersey, Piscataway, USA
| | - Mark Dobrovolski
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia; Rutgers, State University of New Jersey, Piscataway, USA
| | - Evgeny Burnaev
- Center for Computational and Data-Intensive Science and Engineering and Rutgers, State University of New Jersey, Piscataway, USA
| | - Konstantin Severinov
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia; Rutgers, State University of New Jersey, Piscataway, USA.,Laboratory of Genetic Regulation of Prokaryotic Mobile Genetic Elements, Institute of Molecular Genetics of National Research Center "Kurchatov Institute," Moscow, Russia; and Rutgers, State University of New Jersey, Piscataway, USA.,Waksman Institute, Rutgers, State University of New Jersey, Piscataway, USA
| | - Ekaterina Savitskaya
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia; Rutgers, State University of New Jersey, Piscataway, USA
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3
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Genomic population structure associated with repeated escape of Salmonella enterica ATCC14028s from the laboratory into nature. PLoS Genet 2021; 17:e1009820. [PMID: 34570761 PMCID: PMC8496778 DOI: 10.1371/journal.pgen.1009820] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 10/07/2021] [Accepted: 09/10/2021] [Indexed: 11/19/2022] Open
Abstract
Salmonella enterica serovar Typhimurium strain ATCC14028s is commercially available from multiple national type culture collections, and has been widely used since 1960 for quality control of growth media and experiments on fitness (“laboratory evolution”). ATCC14028s has been implicated in multiple cross-contaminations in the laboratory, and has also caused multiple laboratory infections and one known attempt at bioterrorism. According to hierarchical clustering of 3002 core gene sequences, ATCC14028s belongs to HierCC cluster HC20_373 in which most internal branch lengths are only one to three SNPs long. Many natural Typhimurium isolates from humans, domesticated animals and the environment also belong to HC20_373, and their core genomes are almost indistinguishable from those of laboratory strains. These natural isolates have infected humans in Ireland and Taiwan for decades, and are common in the British Isles as well as the Americas. The isolation history of some of the natural isolates confirms the conclusion that they do not represent recent contamination by the laboratory strain, and 10% carry plasmids or bacteriophages which have been acquired in nature by HGT from unrelated bacteria. We propose that ATCC14028s has repeatedly escaped from the laboratory environment into nature via laboratory accidents or infections, but the escaped micro-lineages have only a limited life span. As a result, there is a genetic gap separating HC20_373 from its closest natural relatives due to a divergence between them in the late 19th century followed by repeated extinction events of escaped HC20_373. Clades of closely related bacteria exist in nature. Individual isolates from such clades are often distinguishable by genomic sequencing because genomic sequence differences can be acquired over a few years due to neutral drift and natural selection. The evolution of laboratory strains is often largely frozen, physically due to storage conditions and genetically due to long periods of storage. Thus, laboratory strains can normally be readily distinguished from natural isolates because they show much less diversity. However, laboratory strain ATCC14028s shows modest levels of sequence diversity because it has been shipped around the world to multiple laboratories and is routinely used for analyses of laboratory evolution. Closely related natural isolates also exist, but their genetic diversity is not dramatically greater at the core genome level. Indeed, many scientists doubt that such isolates are natural, and interpret them as undetected contamination by the laboratory strain. We present data indicating that ATCC14028s has repeatedly escaped from the laboratory through inadvertent contamination of the environment, infection of technical staff and deliberate bioterrorism. The escapees survive in nature long enough that some acquire mobile genomic elements by horizontal gene transfer, but eventually they go extinct. As a result, even extensive global databases of natural isolates lack closely related isolates whose ancestors diverged from ATCC14028s within the last 100 years.
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Achtman M, Zhou Z, Alikhan NF, Tyne W, Parkhill J, Cormican M, Chiou CS, Torpdahl M, Litrup E, Prendergast DM, Moore JE, Strain S, Kornschober C, Meinersmann R, Uesbeck A, Weill FX, Coffey A, Andrews-Polymenis H, Curtiss 3rd R, Fanning S. Genomic diversity of Salmonella enterica -The UoWUCC 10K genomes project. Wellcome Open Res 2021; 5:223. [PMID: 33614977 PMCID: PMC7869069 DOI: 10.12688/wellcomeopenres.16291.2] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/25/2021] [Indexed: 12/31/2022] Open
Abstract
Background: Most publicly available genomes of Salmonella enterica are from human disease in the US and the UK, or from domesticated animals in the US. Methods: Here we describe a historical collection of 10,000 strains isolated between 1891-2010 in 73 different countries. They encompass a broad range of sources, ranging from rivers through reptiles to the diversity of all S. enterica isolated on the island of Ireland between 2000 and 2005. Genomic DNA was isolated, and sequenced by Illumina short read sequencing. Results: The short reads are publicly available in the Short Reads Archive. They were also uploaded to EnteroBase, which assembled and annotated draft genomes. 9769 draft genomes which passed quality control were genotyped with multiple levels of multilocus sequence typing, and used to predict serovars. Genomes were assigned to hierarchical clusters on the basis of numbers of pair-wise allelic differences in core genes, which were mapped to genetic Lineages within phylogenetic trees. Conclusions: The University of Warwick/University College Cork (UoWUCC) project greatly extends the geographic sources, dates and core genomic diversity of publicly available S. enterica genomes. We illustrate these features by an overview of core genomic Lineages within 33,000 publicly available Salmonella genomes whose strains were isolated before 2011. We also present detailed examinations of HC400, HC900 and HC2000 hierarchical clusters within exemplar Lineages, including serovars Typhimurium, Enteritidis and Mbandaka. These analyses confirm the polyphyletic nature of multiple serovars while showing that discrete clusters with geographical specificity can be reliably recognized by hierarchical clustering approaches. The results also demonstrate that the genomes sequenced here provide an important counterbalance to the sampling bias which is so dominant in current genomic sequencing.
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Affiliation(s)
- Mark Achtman
- Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK
| | - Zhemin Zhou
- Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK
| | | | - William Tyne
- Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK
| | - Julian Parkhill
- Department of Veterinary Medicine, University of Cambridge, Cambridge, CB3 0ES, UK
| | - Martin Cormican
- National Salmonella, Shigella and Listeria Reference Laboratory, Galway, H91 YR71, Ireland
| | - Chien-Shun Chiou
- Central Regional Laboratory, Center for Diagnostics and Vaccine Development, Centers for Disease Control, Taichung, None, Taiwan
| | - Mia Torpdahl
- Statens Serum Institut, Copenhagen S, DK-2300, Denmark
| | - Eva Litrup
- Statens Serum Institut, Copenhagen S, DK-2300, Denmark
| | - Deirdre M. Prendergast
- Backweston complex, Department of Agriculture, Food and the Marine (DAFM), Celbridge, Co. Kildare, W23 X3PH, Ireland
| | - John E. Moore
- Northern Ireland Public Health Laboratory, Department of Bacteriology, Belfast City Hospital, Belfast, BT9 7AD, UK
| | - Sam Strain
- Animal Health and Welfare NI, Dungannon, BT71 6JT, UK
| | - Christian Kornschober
- Institute for Medical Microbiology and Hygiene, Austrian Agency for Health and Food Safety (AGES), Graz, 8010, Austria
| | - Richard Meinersmann
- US National Poultry Research Center, USDA Agricultural Research Service, Athens, GA, 30605, USA
| | - Alexandra Uesbeck
- Institute for Medical Microbiology, Immunology, and Hygiene, University of Cologne, Cologne, 50935, Germany
| | - François-Xavier Weill
- Unité des bactéries pathogènes entériques, Institut Pasteur, Paris, cedex 15, France
| | - Aidan Coffey
- Cork Institute of Technology, Cork, T12P928, Ireland
| | - Helene Andrews-Polymenis
- Dept. of Microbial Pathogenesis and Immunology, College of Medicine Texas A&M University, Bryan, TX, 77807, USA
| | - Roy Curtiss 3rd
- Dept. of Infectious Diseases & Immunology, College of Veterinary Medicine, University of Florida, Gainesville, Florida, 32611, USA
| | - Séamus Fanning
- UCD-Centre for Food Safety, University College Dublin, Dublin, D04 N2E5, Ireland
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5
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Achtman M, Zhou Z, Alikhan NF, Tyne W, Parkhill J, Cormican M, Chiou CS, Torpdahl M, Litrup E, Prendergast DM, Moore JE, Strain S, Kornschober C, Meinersmann R, Uesbeck A, Weill FX, Coffey A, Andrews-Polymenis H, Curtiss 3rd R, Fanning S. Genomic diversity of Salmonella enterica -The UoWUCC 10K genomes project. Wellcome Open Res 2020; 5:223. [PMID: 33614977 PMCID: PMC7869069 DOI: 10.12688/wellcomeopenres.16291.1] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/15/2020] [Indexed: 01/25/2023] Open
Abstract
Background: Most publicly available genomes of Salmonella enterica are from human disease in the US and the UK, or from domesticated animals in the US. Methods: Here we describe a historical collection of 10,000 strains isolated between 1891-2010 in 73 different countries. They encompass a broad range of sources, ranging from rivers through reptiles to the diversity of all S. enterica isolated on the island of Ireland between 2000 and 2005. Genomic DNA was isolated, and sequenced by Illumina short read sequencing. Results: The short reads are publicly available in the Short Reads Archive. They were also uploaded to EnteroBase, which assembled and annotated draft genomes. 9769 draft genomes which passed quality control were genotyped with multiple levels of multilocus sequence typing, and used to predict serovars. Genomes were assigned to hierarchical clusters on the basis of numbers of pair-wise allelic differences in core genes, which were mapped to genetic Lineages within phylogenetic trees. Conclusions: The University of Warwick/University College Cork (UoWUCC) project greatly extends the geographic sources, dates and core genomic diversity of publicly available S. enterica genomes. We illustrate these features by an overview of core genomic Lineages within 33,000 publicly available Salmonella genomes whose strains were isolated before 2011. We also present detailed examinations of HC400, HC900 and HC2000 hierarchical clusters within exemplar Lineages, including serovars Typhimurium, Enteritidis and Mbandaka. These analyses confirm the polyphyletic nature of multiple serovars while showing that discrete clusters with geographical specificity can be reliably recognized by hierarchical clustering approaches. The results also demonstrate that the genomes sequenced here provide an important counterbalance to the sampling bias which is so dominant in current genomic sequencing.
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Affiliation(s)
- Mark Achtman
- Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK
| | - Zhemin Zhou
- Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK
| | | | - William Tyne
- Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK
| | - Julian Parkhill
- Department of Veterinary Medicine, University of Cambridge, Cambridge, CB3 0ES, UK
| | - Martin Cormican
- National Salmonella, Shigella and Listeria Reference Laboratory, Galway, H91 YR71, Ireland
| | - Chien-Shun Chiou
- Central Regional Laboratory, Center for Diagnostics and Vaccine Development, Centers for Disease Control, Taichung, None, Taiwan
| | - Mia Torpdahl
- Statens Serum Institut, Copenhagen S, DK-2300, Denmark
| | - Eva Litrup
- Statens Serum Institut, Copenhagen S, DK-2300, Denmark
| | - Deirdre M. Prendergast
- Backweston complex, Department of Agriculture, Food and the Marine (DAFM), Celbridge, Co. Kildare, W23 X3PH, Ireland
| | - John E. Moore
- Northern Ireland Public Health Laboratory, Department of Bacteriology, Belfast City Hospital, Belfast, BT9 7AD, UK
| | - Sam Strain
- Animal Health and Welfare NI, Dungannon, BT71 6JT, UK
| | - Christian Kornschober
- Institute for Medical Microbiology and Hygiene, Austrian Agency for Health and Food Safety (AGES), Graz, 8010, Austria
| | - Richard Meinersmann
- US National Poultry Research Center, USDA Agricultural Research Service, Athens, GA, 30605, USA
| | - Alexandra Uesbeck
- Institute for Medical Microbiology, Immunology, and Hygiene, University of Cologne, Cologne, 50935, Germany
| | - François-Xavier Weill
- Unité des bactéries pathogènes entériques, Institut Pasteur, Paris, cedex 15, France
| | - Aidan Coffey
- Cork Institute of Technology, Cork, T12P928, Ireland
| | - Helene Andrews-Polymenis
- Dept. of Microbial Pathogenesis and Immunology, College of Medicine Texas A&M University, Bryan, TX, 77807, USA
| | - Roy Curtiss 3rd
- Dept. of Infectious Diseases & Immunology, College of Veterinary Medicine, University of Florida, Gainesville, Florida, 32611, USA
| | - Séamus Fanning
- UCD-Centre for Food Safety, University College Dublin, Dublin, D04 N2E5, Ireland
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Zhou Z, Alikhan NF, Mohamed K, Fan Y, Achtman M. The EnteroBase user's guide, with case studies on Salmonella transmissions, Yersinia pestis phylogeny, and Escherichia core genomic diversity. Genome Res 2020; 30:138-152. [PMID: 31809257 PMCID: PMC6961584 DOI: 10.1101/gr.251678.119] [Citation(s) in RCA: 500] [Impact Index Per Article: 125.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2019] [Accepted: 12/03/2019] [Indexed: 01/08/2023]
Abstract
EnteroBase is an integrated software environment that supports the identification of global population structures within several bacterial genera that include pathogens. Here, we provide an overview of how EnteroBase works, what it can do, and its future prospects. EnteroBase has currently assembled more than 300,000 genomes from Illumina short reads from Salmonella, Escherichia, Yersinia, Clostridioides, Helicobacter, Vibrio, and Moraxella and genotyped those assemblies by core genome multilocus sequence typing (cgMLST). Hierarchical clustering of cgMLST sequence types allows mapping a new bacterial strain to predefined population structures at multiple levels of resolution within a few hours after uploading its short reads. Case Study 1 illustrates this process for local transmissions of Salmonella enterica serovar Agama between neighboring social groups of badgers and humans. EnteroBase also supports single nucleotide polymorphism (SNP) calls from both genomic assemblies and after extraction from metagenomic sequences, as illustrated by Case Study 2 which summarizes the microevolution of Yersinia pestis over the last 5000 years of pandemic plague. EnteroBase can also provide a global overview of the genomic diversity within an entire genus, as illustrated by Case Study 3, which presents a novel, global overview of the population structure of all of the species, subspecies, and clades within Escherichia.
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Gymoese P, Kiil K, Torpdahl M, Østerlund MT, Sørensen G, Olsen JE, Nielsen EM, Litrup E. WGS based study of the population structure of Salmonella enterica serovar Infantis. BMC Genomics 2019; 20:870. [PMID: 31730461 PMCID: PMC6858691 DOI: 10.1186/s12864-019-6260-6] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Accepted: 11/05/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Salmonella Infantis (S. Infantis) is one of the most frequent Salmonella serovars isolated from human cases of salmonellosis and the most detected serovar from animal and food sources in Europe. The serovar is commonly associated with poultry and there is increasing concern over multidrug resistant clones spreading worldwide, as the dominating clones are characterized by presence of large plasmids carrying multiple resistance genes. Increasing the knowledge of the S. Infantis population and evolution is important for understanding and preventing further spread. In this study, we analysed a collection of strains representing different decades, sources and geographic locations. We analysed the population structure and the accessory genome, in particular we identified prophages with a view to understand the role of prophages in relation to the evolution of this serovar. RESULTS We sequenced a global collection of 100 S. Infantis strains. A core-genome SNP analysis separated five strains in e-Burst Group (eBG) 297 with a long branch. The remaining strains, all in eBG31, were divided into three lineages that were estimated to have separated approximately 150 years ago. One lineage contained the vast majority of strains. In five of six clusters, no obvious correlation with source or geographical locations was seen. However, one cluster contained mostly strains from human and avian sources, indicating a clone with preference for these sources. The majority of strains within this cluster harboured a pESI-like plasmid with multiple resistance genes. Another lineage contained three genetic clusters with more rarely isolated strains of mainly animal origin, possibly less sampled or less infectious clones. Conserved prophages were identified in all strains, likely representing bacteriophages which integrated into the chromosome of a common ancestor to S. Infantis. We also saw that some prophages were specific to clusters and were probably introduced when the clusters were formed. CONCLUSIONS This study analysed a global S. Infantis population and described its genetic structure. We hypothesize that the population has evolved in three separate lineages, with one more successfully emerging lineage. We furthermore detected conserved prophages present in the entire population and cluster specific prophages, which probably shaped the population structure.
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Affiliation(s)
- Pernille Gymoese
- Department of Bacteria, Parasites and Fungi, Statens Serum Institut, Copenhagen, Artillerivej 5 Denmark
| | - Kristoffer Kiil
- Department of Bacteria, Parasites and Fungi, Statens Serum Institut, Copenhagen, Artillerivej 5 Denmark
| | - Mia Torpdahl
- Department of Bacteria, Parasites and Fungi, Statens Serum Institut, Copenhagen, Artillerivej 5 Denmark
| | - Mark T. Østerlund
- Department of Bacteria, Parasites and Fungi, Statens Serum Institut, Copenhagen, Artillerivej 5 Denmark
| | - Gitte Sørensen
- Department of Bacteria, Parasites and Fungi, Statens Serum Institut, Copenhagen, Artillerivej 5 Denmark
| | - John E. Olsen
- Department of Veterinary and Animal Sciences, University of Copenhagen, Stigbøjlen 4, Frederiksberg C, Denmark
| | - Eva M. Nielsen
- Department of Bacteria, Parasites and Fungi, Statens Serum Institut, Copenhagen, Artillerivej 5 Denmark
| | - Eva Litrup
- Department of Bacteria, Parasites and Fungi, Statens Serum Institut, Copenhagen, Artillerivej 5 Denmark
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Abstract
For many decades, Salmonella enterica has been subdivided by serological properties into serovars or further subdivided for epidemiological tracing by a variety of diagnostic tests with higher resolution. Recently, it has been proposed that so-called eBurst groups (eBGs) based on the alleles of seven housekeeping genes (legacy multilocus sequence typing [MLST]) corresponded to natural populations and could replace serotyping. However, this approach lacks the resolution needed for epidemiological tracing and the existence of natural populations had not been independently validated by independent criteria. Here, we describe EnteroBase, a web-based platform that assembles draft genomes from Illumina short reads in the public domain or that are uploaded by users. EnteroBase implements legacy MLST as well as ribosomal gene MLST (rMLST), core genome MLST (cgMLST), and whole genome MLST (wgMLST) and currently contains over 100,000 assembled genomes from Salmonella. It also provides graphical tools for visual interrogation of these genotypes and those based on core single nucleotide polymorphisms (SNPs). eBGs based on legacy MLST are largely consistent with eBGs based on rMLST, thus demonstrating that these correspond to natural populations. rMLST also facilitated the selection of representative genotypes for SNP analyses of the entire breadth of diversity within Salmonella. In contrast, cgMLST provides the resolution needed for epidemiological investigations. These observations show that genomic genotyping, with the assistance of EnteroBase, can be applied at all levels of diversity within the Salmonella genus.
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Fuche FJ, Sen S, Jones JA, Nkeze J, Permala-Booth J, Tapia MD, Sow SO, Tamboura B, Touré A, Onwuchekwa U, Sylla M, Kotloff KL, Tennant SM. Characterization of Invasive Salmonella Serogroup C1 Infections in Mali. Am J Trop Med Hyg 2017; 98:589-594. [PMID: 29280425 PMCID: PMC5929196 DOI: 10.4269/ajtmh.17-0508] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Nontyphoidal Salmonella (NTS) are the leading cause of foodborne infections worldwide and a major cause of bloodstream infections in infants and HIV-infected adults in sub-Saharan Africa (SSA). Salmonella Typhimurium (serogroup B) and Salmonella Enteritidis (serogroup D) are the most common serovars in this region. However, data describing rarer invasive NTS serovars, particularly those belonging to serogroups C1 and C2, circulating in SSA are lacking. We previously conducted systematic blood culture surveillance on pediatric patients in Bamako, Mali, from 2002 to 2014, and the results showed that serovars Typhimurium and Enteritidis accounted for 32% and 36% of isolates, respectively. Here, we present data on 27 Salmonella serogroup C1 strains that were isolated during this previous study. The strains were typed by serum agglutination and multilocus sequence typing (MLST). Sixteen strains were Salmonella Paratyphi C, four were Salmonella Colindale, and two were Salmonella Virchow. Interestingly, five strains were identified as the very rare Salmonella Brazzaville using a combination of serum agglutination and flagellin gene typing. Phenotypic characterization showed that Salmonella Brazzaville produced biofilm and exhibited catalase activity, which were not statistically different from the gastroenteritis-associated Salmonella Typhimurium sequence type (ST) 19. All tested Salmonella Paratyphi C strains were poor biofilm producers and showed significantly less catalase activity than Salmonella Typhimurium ST19. Overall, our study provides insight into the Salmonella serogroup C1 serovars that cause invasive disease in infants in Mali. In addition, we show that MLST and flagellin gene sequencing, in association with traditional serum agglutination, are invaluable tools to help identify rare Salmonella serovars.
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Affiliation(s)
- Fabien J Fuche
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland.,Center for Vaccine Development and Institute for Global Health, University of Maryland School of Medicine, Baltimore, Maryland
| | - Sunil Sen
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland.,Center for Vaccine Development and Institute for Global Health, University of Maryland School of Medicine, Baltimore, Maryland
| | - Jennifer A Jones
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland.,Center for Vaccine Development and Institute for Global Health, University of Maryland School of Medicine, Baltimore, Maryland
| | - Joseph Nkeze
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland.,Center for Vaccine Development and Institute for Global Health, University of Maryland School of Medicine, Baltimore, Maryland
| | - Jasnehta Permala-Booth
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland.,Center for Vaccine Development and Institute for Global Health, University of Maryland School of Medicine, Baltimore, Maryland
| | - Milagritos D Tapia
- Department of Pediatrics, University of Maryland School of Medicine, Baltimore, Maryland.,Center for Vaccine Development and Institute for Global Health, University of Maryland School of Medicine, Baltimore, Maryland
| | - Samba O Sow
- Centre pour le Développement des Vaccins, Mali, Bamako, Mali
| | - Boubou Tamboura
- Centre pour le Développement des Vaccins, Mali, Bamako, Mali
| | - Aliou Touré
- Centre pour le Développement des Vaccins, Mali, Bamako, Mali
| | - Uma Onwuchekwa
- Centre pour le Développement des Vaccins, Mali, Bamako, Mali
| | - Mamadou Sylla
- Centre pour le Développement des Vaccins, Mali, Bamako, Mali
| | - Karen L Kotloff
- Department of Pediatrics, University of Maryland School of Medicine, Baltimore, Maryland.,Center for Vaccine Development and Institute for Global Health, University of Maryland School of Medicine, Baltimore, Maryland
| | - Sharon M Tennant
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland.,Center for Vaccine Development and Institute for Global Health, University of Maryland School of Medicine, Baltimore, Maryland
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10
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Park JH, Kim HS, Yim JH, Kim YJ, Kim DH, Chon JW, Kim H, Om AS, Seo KH. Comparison of the isolation rates and characteristics of Salmonella isolated from antibiotic-free and conventional chicken meat samples. Poult Sci 2017; 96:2831-2838. [DOI: 10.3382/ps/pex055] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Accepted: 02/22/2017] [Indexed: 01/02/2023] Open
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11
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Choi D, Chon JW, Kim HS, Kim DH, Lim JS, Yim JH, Seo KH. Incidence, Antimicrobial Resistance, and Molecular Characteristics of Nontyphoidal Salmonella Including Extended-Spectrum β-Lactamase Producers in Retail Chicken Meat. J Food Prot 2015; 78:1932-7. [PMID: 26555514 DOI: 10.4315/0362-028x.jfp-15-145] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
The present study was undertaken to determine the prevalence of Salmonella in 100 chicken carcass samples from five integrated broiler operation brands in Korea. Serotypes, antibiotic resistance patterns, extended-spectrum β-lactamase (ESBL) genotype, and clonal divergence using multilocus sequence typing of the isolated strains were analyzed. A total of 42 chicken samples were contaminated with nontyphoidal Salmonella (NTS) isolates: 16 isolates (38%) were Salmonella Virchow, 9 (21%) were Salmonella Bareilly, and 8 (19%) were Salmonella Infantis. A multidrug resistance (MDR; resistant to more than three classes of antibiotics) phenotype was observed in 29% of the isolates, which were resistant to five or more classes of antibiotics. The dominant MDR type was resistance to classes of penicillin, cephalosporins, aminoglycosides, quinolones, and tetracyclines. All the MDR isolates were positive for ESBL producers, and all but one (with the CTX-M-1 genotype) had the CTX-M-15 genotype. Multilocus sequence typing of the isolates revealed ST16 as the dominant sequence type; Salmonella Virchow, Salmonella Infantis, and Salmonella Richmond were all ST16, indicating a close genetic relationship between these serovars. This is the first study in Korea showing the CTX-M-1 type of NTS and the prevalence of ESBL-producing strains among NTS isolated from retail chicken meat. Our findings suggest that MDR Salmonella contamination is widely prevalent in retail chicken meat, and consumption of inadequately cooked products could lead to dissemination of NTS, which is hazardous to human health.
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Affiliation(s)
- Dasom Choi
- Center for Food Safety, College of Veterinary Medicine, Konkuk University, Hwayang-dong, Gwangjin-gu, Seoul 143-701, Republic of Korea
| | - Jung-Whan Chon
- U.S. Food and Drug Administration, National Center for Toxicological Research, Division of Microbiology, Jefferson, Arkansas 72079, USA
| | - Hong-Seok Kim
- Center for Food Safety, College of Veterinary Medicine, Konkuk University, Hwayang-dong, Gwangjin-gu, Seoul 143-701, Republic of Korea
| | - Dong-Hyeon Kim
- Center for Food Safety, College of Veterinary Medicine, Konkuk University, Hwayang-dong, Gwangjin-gu, Seoul 143-701, Republic of Korea
| | - Jong-Soo Lim
- Center for Food Safety, College of Veterinary Medicine, Konkuk University, Hwayang-dong, Gwangjin-gu, Seoul 143-701, Republic of Korea
| | - Jin-Hyeok Yim
- Center for Food Safety, College of Veterinary Medicine, Konkuk University, Hwayang-dong, Gwangjin-gu, Seoul 143-701, Republic of Korea
| | - Kun-Ho Seo
- Center for Food Safety, College of Veterinary Medicine, Konkuk University, Hwayang-dong, Gwangjin-gu, Seoul 143-701, Republic of Korea.
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12
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Cain-Hom C, Pabalate R, Pham A, Patel HN, Wiler R, Cox JC. Mammalian Genotyping Using Acoustic Droplet Ejection for Enhanced Data Reproducibility, Superior Throughput, and Minimized Cross-Contamination. ACTA ACUST UNITED AC 2015; 21:37-48. [PMID: 26311060 DOI: 10.1177/2211068215601637] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2015] [Indexed: 12/20/2022]
Abstract
Genetically engineered animal models are major tools of a drug discovery pipeline because they facilitate understanding of the molecular and biochemical basis of disease. These highly complex models of human disease often require increasingly convoluted genetic analysis. With growing needs for throughput and consistency, we find that traditional aspiration-and-dispense liquid-handling robots no longer have the required speed, quality, or reproducibility.We present an adaptation and installation of an acoustic droplet ejection (ADE) liquid-handling system for ultra-high-throughput screening of genetically engineered models. An ADE system is fully integrated with existing laboratory processes and platforms to facilitate execution of PCR and quantitative PCR (qPCR) reactions. Such a configuration permits interrogation of highly complex genetic models in a variety of backgrounds. Our findings demonstrate that a single ADE system replaces 8-10 traditional liquid-handling robots while increasing quality and reproducibility.We demonstrate significant improvements achieved by transitioning to an ADE device: extremely low detectable cross-contamination in PCR and qPCR despite extensive use, greatly increased data reproducibility (large increases in data quality and Cq consistency), lowered reaction volumes for large cost savings, and nearly a magnitude increase in speed per instrument. We show several comparisons between traditional- and ADE-based pipetting for a qPCR-based workflow.
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Affiliation(s)
- Carol Cain-Hom
- Department of Transgenic Technology, Genentech Inc., San Francisco, CA, USA
| | - Ryan Pabalate
- Department of Transgenic Technology, Genentech Inc., San Francisco, CA, USA
| | - Anna Pham
- Department of Transgenic Technology, Genentech Inc., San Francisco, CA, USA
| | - Hetal N Patel
- Department of Transgenic Technology, Genentech Inc., San Francisco, CA, USA
| | - Rhonda Wiler
- Department of Transgenic Technology, Genentech Inc., San Francisco, CA, USA
| | - J Colin Cox
- Department of Transgenic Technology, Genentech Inc., San Francisco, CA, USA
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13
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Yun YS, Chae SJ, Na HY, Chung GT, Yoo CK, Lee DY. Modified Method of Multilocus Sequence Typing (MLST) for Serotyping inSalmonellaSpecies. ACTA ACUST UNITED AC 2015. [DOI: 10.4167/jbv.2015.45.4.314] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Affiliation(s)
- Young-Sun Yun
- Division of Enteric Diseases, Center for Infectious Diseases, Korea National Institute of Health, Osong, Korea
| | - Su-Jin Chae
- Division of Enteric Diseases, Center for Infectious Diseases, Korea National Institute of Health, Osong, Korea
| | - Hye-Young Na
- Division of Enteric Diseases, Center for Infectious Diseases, Korea National Institute of Health, Osong, Korea
| | - Gyung Tae Chung
- Division of Enteric Diseases, Center for Infectious Diseases, Korea National Institute of Health, Osong, Korea
| | - Cheon-Kwon Yoo
- Division of Enteric Diseases, Center for Infectious Diseases, Korea National Institute of Health, Osong, Korea
| | - Deog-Yong Lee
- Division of Enteric Diseases, Center for Infectious Diseases, Korea National Institute of Health, Osong, Korea
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14
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Rhoads DD, Sintchenko V, Rauch CA, Pantanowitz L. Clinical microbiology informatics. Clin Microbiol Rev 2014; 27:1025-47. [PMID: 25278581 PMCID: PMC4187636 DOI: 10.1128/cmr.00049-14] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The clinical microbiology laboratory has responsibilities ranging from characterizing the causative agent in a patient's infection to helping detect global disease outbreaks. All of these processes are increasingly becoming partnered more intimately with informatics. Effective application of informatics tools can increase the accuracy, timeliness, and completeness of microbiology testing while decreasing the laboratory workload, which can lead to optimized laboratory workflow and decreased costs. Informatics is poised to be increasingly relevant in clinical microbiology, with the advent of total laboratory automation, complex instrument interfaces, electronic health records, clinical decision support tools, and the clinical implementation of microbial genome sequencing. This review discusses the diverse informatics aspects that are relevant to the clinical microbiology laboratory, including the following: the microbiology laboratory information system, decision support tools, expert systems, instrument interfaces, total laboratory automation, telemicrobiology, automated image analysis, nucleic acid sequence databases, electronic reporting of infectious agents to public health agencies, and disease outbreak surveillance. The breadth and utility of informatics tools used in clinical microbiology have made them indispensable to contemporary clinical and laboratory practice. Continued advances in technology and development of these informatics tools will further improve patient and public health care in the future.
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Affiliation(s)
- Daniel D Rhoads
- Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Vitali Sintchenko
- Marie Bashir Institute for Infectious Diseases and Biosecurity and Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia Centre for Infectious Diseases and Microbiology-Public Health, Institute of Clinical Pathology and Medical Research, Westmead Hospital, Sydney, New South Wales, Australia
| | - Carol A Rauch
- Department of Pathology, Microbiology and Immunology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Liron Pantanowitz
- Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
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15
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Lärkeryd A, Myrtennäs K, Karlsson E, Dwibedi CK, Forsman M, Larsson P, Johansson A, Sjödin A. CanSNPer: a hierarchical genotype classifier of clonal pathogens. Bioinformatics 2014; 30:1762-4. [PMID: 24574113 DOI: 10.1093/bioinformatics/btu113] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
SUMMARY Advances in typing methodologies have recently reformed the field of molecular epidemiology of pathogens. The falling cost of sequencing technologies is creating a deluge of whole genome sequencing data that burdens bioinformatics resources and tool development. In particular, single nucleotide polymorphisms in core genomes of pathogens are recognized as the most important markers for inferring genetic relationships because they are evolutionarily stable and amenable to high-throughput detection methods. Sequence data will provide an excellent opportunity to extend our understanding of infectious disease when the challenge of extracting knowledge from available sequence resources is met. Here, we present an efficient and user-friendly genotype classification pipeline, CanSNPer, based on an easily expandable database of predefined canonical single nucleotide polymorphisms. AVAILABILITY AND IMPLEMENTATION All documentation and Python-based source code for the CanSNPer are freely available at http://github.com/adrlar/CanSNPer.
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Affiliation(s)
- Adrian Lärkeryd
- Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden
| | - Kerstin Myrtennäs
- Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden
| | - Edvin Karlsson
- Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden
| | - Chinmay Kumar Dwibedi
- Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, SwedenDepartment of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden
| | - Mats Forsman
- Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden
| | - Pär Larsson
- Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden
| | - Anders Johansson
- Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden
| | - Andreas Sjödin
- Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, SwedenDepartment of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden
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16
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Haase JK, Didelot X, Lecuit M, Korkeala H, Achtman M. The ubiquitous nature ofListeria monocytogenesclones: a large-scale Multilocus Sequence Typing study. Environ Microbiol 2013; 16:405-16. [DOI: 10.1111/1462-2920.12342] [Citation(s) in RCA: 105] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2013] [Accepted: 11/16/2013] [Indexed: 11/28/2022]
Affiliation(s)
- Jana K. Haase
- Environmental Research Institute; University College Cork; Cork Ireland
| | - Xavier Didelot
- Department of Infectious Disease Epidemiology; Imperial College London; London UK
| | - Marc Lecuit
- Institut Pasteur; Biology of Infection Unit; National Reference Centre and WHO collaborating centre for Listeria; Inserm Unit 1117 Paris France
- Division of Infectious Diseases and Tropical Medicine; Necker-Enfants Malades University Hospital; APHP; Paris France
| | | | - Mark Achtman
- Environmental Research Institute; University College Cork; Cork Ireland
- Warwick Medical School; University of Warwick; Coventry CV4 7AL UK
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17
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Population structures in the SARA and SARB reference collections of Salmonella enterica according to MLST, MLEE and microarray hybridization. INFECTION GENETICS AND EVOLUTION 2013; 16:314-25. [DOI: 10.1016/j.meegid.2013.03.003] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2013] [Revised: 02/27/2013] [Accepted: 03/05/2013] [Indexed: 11/18/2022]
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18
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Jolley KA, Maiden MC. Automated extraction of typing information for bacterial pathogens from whole genome sequence data: Neisseria meningitidis as an exemplar. ACTA ACUST UNITED AC 2013; 18:20379. [PMID: 23369391 DOI: 10.2807/ese.18.04.20379-en] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Whole genome sequence (WGS) data are increasingly used to characterise bacterial pathogens. These data provide detailed information on the genotypes and likely phenotypes of aetiological agents, enabling the relationships of samples from potential disease outbreaks to be established precisely. However, the generation of increasing quantities of sequence data does not, in itself, resolve the problems that many microbiological typing methods have addressed over the last 100 years or so; indeed, providing large volumes of unstructured data can confuse rather than resolve these issues. Here we review the nascent field of storage of WGS data for clinical application and show how curated sequence-based typing schemes on websites have generated an infrastructure that can exploit WGS for bacterial typing efficiently. We review the tools that have been implemented within the PubMLST website to extract clinically useful, strain-characterisation information that can be provided to physicians and public health professionals in a timely, concise and understandable way. These data can be used to inform medical decisions such as how to treat a patient, whether to instigate public health action, and what action might be appropriate. The information is compatible both with previous sequence-based typing data and also with data obtained in the absence of WGS, providing a flexible infrastructure for WGS-based clinical microbiology.
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Affiliation(s)
- K A Jolley
- Department of Zoology, University of Oxford, Oxford, United Kingdom
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