crossmark COMMENTARY
The Future of Whole-Genome Sequencing for Public Health and the Clinic Marc W. Allard Food and Drug Administration, College Park, Maryland, USA
An American Society for Microbiology (ASM) conference titled the Conference on Rapid Next-Generation Sequencing and Bioinformatic Pipelines for Enhanced Molecular Epidemiological Investigation of Pathogens provided a venue for discussing how technologies surrounding whole-genome sequencing (WGS) are advancing microbiology. Several applications in microbial taxonomy, microbial forensics, and genomics for public health pathogen surveillance were presented at the meeting and are reviewed. All of these studies document that WGS is revolutionizing applications in microbiology and that the impact of these technologies will be profound. ASM is providing support mechanisms to promote discussions of WGS techniques to foster applications and interpretations.
T
he four minireviews that follow are based on talks presented in fall 2015 at the meeting of the 1st American Society for Microbiology (ASM) Conference on Rapid Next-Generation Sequencing and Bioinformatic Pipelines for Enhanced Molecular Epidemiological Investigation of Pathogens. One goal of ASM is to expand its offerings in whole-genome sequencing (WGS), including this meeting series, to provide an outlet for discussions of using WGS to enhance microbiology. Sessions at the meeting included Genomics for Food and Veterinary Pathogen Surveillance; One Health, Regulation and Assuring the Quality of NGS for Pathogen Surveillance; Genomics for Public Health Pathogen Surveillance; Bioinformatic Pipelines and Tools for Genomic Pathogen Surveillance; Omni-Omics for Pathogen Surveillance; Genomics for Microbial Taxonomy; Pathogen Surveillance Software Demonstration; Genomics for Microbial Forensics; Genomics for Clinical Microbiology Pathogen Surveillance; and Genomics for Virus Surveillance. The first two papers, by Maiden and Harrison (1) and Garrity (2), from the Microbial Taxonomy session, provided examples of how WGS is transforming bacterial taxonomy. Maiden and Harrison (1) show, using Neisseria, how WGS “is revolutionizing microbiology; however, complementary advances in accessible, reproducible, and rapid analysis techniques are required to realize the potential of these data.” The authors go on to document how multilocus sequence typing (MLST) approaches can discover the taxonomy of a bacterium and assist in the epidemiology of these diseases by cataloging the known diversity into a public database. By utilizing a sequence type (ST), the authors group isolates into clonal complexes (CCs), which often have associated clinical manifestations. The authors document that “a limited number of hyper-invasive lineages cause most meningococcal invasive disease cases.” Utilizing a global taxonomy, extracted from the WGS data, allows clinicians around the world to type cases and have a system to predict clinical outcomes. While complete genomes are available, often the ST taxonomy is sufficient and already is being used in the clinic. These authors also describe early use and characterization of antimicrobial resistance (AMR) with specific genes associated with resistance in many of these pathogens. For many human pathogens, it is becoming increasingly important to screen for AMR and for emerging resistance (3). Often, when the responsible gene is present, the resistance is present, thus allowing for high rates of AMR
1946
jcm.asm.org
prediction based on the WGS screening for the presence/absence of genes known to cause AMR. The authors describe methods and tools that could be used for any human pathogen, and there is ample opportunity to expand WGS into other clinical applications and other species of pathogen. The authors state that “the combination of WGS data with hierarchical data analysis approaches, such as those outlined here, will result in high-resolution, universal bacterial characterization methods that will have profound implications in all areas of microbiology.” The Garrity minireview (2) documents how much taxonomy has improved with 16S rRNA sequences and how much farther it can go with full genomes of reference taxonomy isolates. Garrity states, “Ideally, when supplemented with additional phenotypic and genotypic data (polyphasic data) it provides a rich description of each strain that places it into a biologically meaningful context.” Essentially, knowing which genes are present allows taxonomists to understand what makes each species special, and improves our understanding of the evolution of bacteria. Another minireview, from the Microbial Forensics session, outlines how WGS creates an expansion of tools for molecular forensics investigations (4). The authors describe how WGS “now allow[s] characterization of microorganisms for a variety of human forensics applications, such as human identification, body fluid characterization, postmortem interval estimation, and biocrimes involving tracking of infectious agents.” The authors describe how both epidemiology and microbial forensics are employed together to determine whether an outbreak is natural, accidental, or intentional. Like many who attended the ASM meeting, these authors anticipate that WGS (they
Accepted manuscript posted online 15 June 2016 Citation Allard MW. 2016. The future of whole-genome sequencing for public health and the clinic. J Clin Microbiol 54:1946 –1948. doi:10.1128/JCM.01082-16. Editor: C. S. Kraft, Emory University Address correspondence to [email protected]. For the articles discussed, see doi:10.1128/JCM.00301-16, doi:10.1128/JCM.00200-16, doi:10.1128/JCM.00046-16, and doi:10.1128/JCM.00081-16. Copyright © 2016, American Society for Microbiology. All Rights Reserved. The views expressed in this Commentary do not necessarily reflect the views of the journal or of ASM.
Journal of Clinical Microbiology
August 2016 Volume 54 Number 8
Commentary
called this MPS, for massively parallel sequencing) eventually will become the routine method for sequencing and then go on to discuss the predicted impacts on the field of microbial forensics. They also provide a historical account of the use of microbial forensics, including early HIV infection cases that went to the courts. In these cases, sequencing was used to address numerous questions, including the following: “(1) Was the suspect the source responsible for the outbreak? (2) Could it be ascertained whether the patients who had been infected shared a source and thus could be included in the outbreak? (3) Alternatively, which patients could have been infected from other sources? (4) Could these alternative sources or the existence of different but simultaneous outbreaks be determined? (5) Could the duration of the outbreak be determined? and (6) Could the time of infection for each patient in the outbreak be estimated?” It is important to see that earlier sequencing methods attempted to answer the same questions that are still important to ongoing investigations and that the methods have only become better resolved and easier with WGS. These authors also touch on the role of metagenomics methods in various ways of characterizing all of the species present in a forensic sample. The future of microbial forensics will include expansion into new applications that can characterize and compare mixed environmental samples that often have thousands of species present. Last, the authors discuss the importance of validation for WGS methods that will be used in the courts and that will impact the health, life, and freedom of individuals if convicted. The last minireview, from the Genomics for Public Health Pathogen Surveillance session, outlines how the authors used WGS methods to create the GenomeTrakr network and databases for state, federal, and international laboratories to collaborate and share data during investigations of foodborne contaminants, to enhance food safety (5). The authors describe the development and growth of the FDA’s efforts in using WGS methods from earlier case studies (6, 7) to the regular use of WGS to support foodborne pathogen investigations. The current database and network are uploading over 2,300 WGS draft genomes per month with a current total of over 57,000 isolates sequenced and made publicly available at https://youtu.be/jLO1Ki5l8mM and http://www.fda.gov/Food/FoodScienceResearch/WholeGenome SequencingProgramWGS/. These authors also discuss the need to expand WGS-based databases for a One Health approach, both at the clinical level and in applying these methods within the food industry and on the farm. By making the data publicly available, the FDA fosters innovation in new methods of data analysis and new applications for rapid isolate characterization. These authors also predict that we will see massive growth in the use of WGS and global adoption of these methods. They argue that by placing the raw sequence data into publicly available shared access sites, they can facilitate the growth and adoption of these methods. The most recent growth in the GenomeTrakr database is coming from global partners whose countries decided to add their foodborne pathogens into the central repository at the National Center for Biotechnology Information (NCBI). The GenomeTrakr database is part of NCBI’s Pathogen Detections website, which has been developed for the deposit of WGS draft genomes for any human pathogen into the Sequence Read Archive (SRA) for development and sharing of human pathogen genomes. From these databases, numerous new taxonomy tools can be tested and launched for the rapid characterization of pathogens. All four minireviews are interconnected in that they share a
August 2016 Volume 54 Number 8
WGS methodology, and so, each is directly enhanced by the applications described by the others. One of the strengths of WGS is that the sequence formats have long been standardized, and most new sequencers produce data that can be formatted into these standards, so that new data can be directly compared to the last 30 years of sequence information archived and stored at NCBI. Having a stable format has allowed for the continual development and growth of data analysis tools. Collecting complete genomes of data requires some modifications to software, but it is often doing more of the same analyses or developing shortcuts for existing methods. For all of these minireviews, the large amounts of data being collected using WGS have allowed investigators to expand existing applications to higher resolution and more detailed characterization of isolates and/or mixed samples. As investigators develop smarter databases where phenotype and genotype are collected on the same samples and deposited into publicly available databases, more phenotypic predictions will be possible from improved rapid genetic characterization. The future of microbiology will see enriched metadata collected and deposited with the genome and or metagenome. Many future scientific advances will be a result of more open access to large amounts of data. The FDA has followed the NCBI in open access to data and in early access to publicly funded research. Public funding requires full and timely release of all of the data so that the public can examine the data and leverage it for more useful applications. Not only will the future of microbiology and the impact of WGS benefit from new developments in data analysis of big data, but the current technology also shows no sign of slowing down in regular equipment and chemistry improvements. In the past 5 years, we have seen refrigerator-sized sequencers shrink in size, first to desktop instruments and recently to palm-sized instruments, with the promise of smaller mobile devices. It will not be long before we see sequencers that fit in your pocket and run on your smartphone. In the Internet of Things, a sequencer will be just one more thing, collecting massive amounts of genomic data with fully integrated data analysis, with rapid interpretation and great visualizations. These improvements with the ongoing decline in the costs per base will fully democratize WGS technologies so that we will see more everyday use of the technology. For some companies, this vision goes beyond daily use by academics and government regulators to include full adoption by the food and health industries and the forensic community and, last, directly by the consumer. Based on current trends in growth of the GenomeTrakr database and network, it is relatively easy to predict that we will see WGS in every department of public health and agriculture laboratory in the United States in the next 5 years. The CDC has already been effectively funded to manage the clinical characterization of foodborne pathogens through the National Strategy for Combating Antibiotic-Resistant Bacteria (CARB) program. Microbial forensics also will likely adopt these methods in the crime labs as well, based on the improved microbial characterizations that are gained by adopting WGS technology. Global expansion in these fields is also happening rapidly. The speed of this growth is more difficult to predict and will depend on the direct costs of testing and the ancillary cost to support the technology. Much of the ancillary costs come from data analysis and interpretation. The first two minireviews predict long-term use of MLST and 16S rRNA approaches, respectively, due to the high costs of going directly to full WGS, though I am more hopeful that technology will continue to improve rapidly (but reading the tea leaves is always a tricky proposition).
Journal of Clinical Microbiology
jcm.asm.org
1947
Commentary
In light of all of these advances, it is no wonder that ASM is supporting a multipronged effort to meet and discuss the impacts of WGS. Whole-genome sequencing is truly transforming many aspects of microbiology, and these impacts are just being applied to numerous projects. At the 1st ASM Conference on Rapid NextGeneration Sequencing and Bioinformatic Pipelines for Enhanced Molecular Epidemiological Investigation of Pathogens, numerous other applications were presented in both seminar and poster formats. ASM hopes to see more if these presentations come out as minireviews. It is clear that the future is bright for advancement of WGS methods and interpretation. It is an exciting time to be a microbiologist, as the field currently has a new tool that will provide insights into microbiology for many years to come. FUNDING INFORMATION The research received support from internal U.S. FDA funding.
REFERENCES 1. Maiden MCJ, Harrison OB. 2016. Population and functional genomics of Neisseria revealed with gene-by-gene approaches. J Clin Microbiol 54: 1949 –1955. http://dx.doi.org/10.1128/JCM.00301-16.
1948
jcm.asm.org
2. Garritty GM. 2016. A new genomics-driven taxonomy of Bacteria and Archaea: are we there yet? J Clin Microbiol 54:1956 –1963. http://dx.doi.org /10.1128/JCM.00200-16. 3. Pecora ND, Li N, Allard M, Li C, Albano E, Delaney M, Dubois A, Onderdonk AB, Bry L. 2015. Genomically informed surveillance for carbapenem-resistant Enterobacteriaceae in a health care system. mBio 6(4): e01030-15. http://dx.doi.org/10.1128/mBio.01030-15. 4. Schmedes SE, Sajantila A, Budowle B. 2016. Expansion of microbial forensics. J Clin Microbiol 54:1964 –1974. http://dx.doi.org/10.1128/JCM .00046-16. 5. Allard MW, Strain E, Melka D, Bunning K, Musser SM, Brown EW, Timme R. 2016. Practical value of food pathogen traceability through building a whole-genome sequencing network and database. J Clin Microbiol 54:1975–1983. http://dx.doi.org/10.1128/JCM.00081-16. 6. Hoffmann M, Zhao S, Pettengill J, Luo Y, Monday SR, Abbott J, Ayers SL, Cinar HN, Muruvanda T, Li C, Allard MW, Whichard J, Meng J, Brown EW, McDermott PF. 2014. Comparative genomic analysis and virulence differences in closely related Salmonella enterica serotype Heidelberg isolates from humans, retail meats, and animals. Genome Biol Evol 6:1046 –1068. http://dx.doi.org/10.1093/gbe/evu079. 7. Lienau EK, Strain E, Wang C, Cao G, Zheng J, Meng J, Ottesen A, Keys C, Stones R, Hammack T, Musser S, Brown EW, Allard MW. 2011. Next-generation sequencing provides high resolution clustering of food and clinical sources during a foodborne outbreak of salmonellosis. N Engl J Med http://dx.doi.org/10.1056/NEJMc1100443.
Journal of Clinical Microbiology
August 2016 Volume 54 Number 8
The Future of Whole-Genome Sequencing for Public Health and the Clinic Marc W. Allard Food and Drug Administration, College Park, Maryland, USA
An American Society for Microbiology (ASM) conference titled the Conference on Rapid Next-Generation Sequencing and Bioinformatic Pipelines for Enhanced Molecular Epidemiological Investigation of Pathogens provided a venue for discussing how technologies surrounding whole-genome sequencing (WGS) are advancing microbiology. Several applications in microbial taxonomy, microbial forensics, and genomics for public health pathogen surveillance were presented at the meeting and are reviewed. All of these studies document that WGS is revolutionizing applications in microbiology and that the impact of these technologies will be profound. ASM is providing support mechanisms to promote discussions of WGS techniques to foster applications and interpretations.
T
he four minireviews that follow are based on talks presented in fall 2015 at the meeting of the 1st American Society for Microbiology (ASM) Conference on Rapid Next-Generation Sequencing and Bioinformatic Pipelines for Enhanced Molecular Epidemiological Investigation of Pathogens. One goal of ASM is to expand its offerings in whole-genome sequencing (WGS), including this meeting series, to provide an outlet for discussions of using WGS to enhance microbiology. Sessions at the meeting included Genomics for Food and Veterinary Pathogen Surveillance; One Health, Regulation and Assuring the Quality of NGS for Pathogen Surveillance; Genomics for Public Health Pathogen Surveillance; Bioinformatic Pipelines and Tools for Genomic Pathogen Surveillance; Omni-Omics for Pathogen Surveillance; Genomics for Microbial Taxonomy; Pathogen Surveillance Software Demonstration; Genomics for Microbial Forensics; Genomics for Clinical Microbiology Pathogen Surveillance; and Genomics for Virus Surveillance. The first two papers, by Maiden and Harrison (1) and Garrity (2), from the Microbial Taxonomy session, provided examples of how WGS is transforming bacterial taxonomy. Maiden and Harrison (1) show, using Neisseria, how WGS “is revolutionizing microbiology; however, complementary advances in accessible, reproducible, and rapid analysis techniques are required to realize the potential of these data.” The authors go on to document how multilocus sequence typing (MLST) approaches can discover the taxonomy of a bacterium and assist in the epidemiology of these diseases by cataloging the known diversity into a public database. By utilizing a sequence type (ST), the authors group isolates into clonal complexes (CCs), which often have associated clinical manifestations. The authors document that “a limited number of hyper-invasive lineages cause most meningococcal invasive disease cases.” Utilizing a global taxonomy, extracted from the WGS data, allows clinicians around the world to type cases and have a system to predict clinical outcomes. While complete genomes are available, often the ST taxonomy is sufficient and already is being used in the clinic. These authors also describe early use and characterization of antimicrobial resistance (AMR) with specific genes associated with resistance in many of these pathogens. For many human pathogens, it is becoming increasingly important to screen for AMR and for emerging resistance (3). Often, when the responsible gene is present, the resistance is present, thus allowing for high rates of AMR
1946
jcm.asm.org
prediction based on the WGS screening for the presence/absence of genes known to cause AMR. The authors describe methods and tools that could be used for any human pathogen, and there is ample opportunity to expand WGS into other clinical applications and other species of pathogen. The authors state that “the combination of WGS data with hierarchical data analysis approaches, such as those outlined here, will result in high-resolution, universal bacterial characterization methods that will have profound implications in all areas of microbiology.” The Garrity minireview (2) documents how much taxonomy has improved with 16S rRNA sequences and how much farther it can go with full genomes of reference taxonomy isolates. Garrity states, “Ideally, when supplemented with additional phenotypic and genotypic data (polyphasic data) it provides a rich description of each strain that places it into a biologically meaningful context.” Essentially, knowing which genes are present allows taxonomists to understand what makes each species special, and improves our understanding of the evolution of bacteria. Another minireview, from the Microbial Forensics session, outlines how WGS creates an expansion of tools for molecular forensics investigations (4). The authors describe how WGS “now allow[s] characterization of microorganisms for a variety of human forensics applications, such as human identification, body fluid characterization, postmortem interval estimation, and biocrimes involving tracking of infectious agents.” The authors describe how both epidemiology and microbial forensics are employed together to determine whether an outbreak is natural, accidental, or intentional. Like many who attended the ASM meeting, these authors anticipate that WGS (they
Accepted manuscript posted online 15 June 2016 Citation Allard MW. 2016. The future of whole-genome sequencing for public health and the clinic. J Clin Microbiol 54:1946 –1948. doi:10.1128/JCM.01082-16. Editor: C. S. Kraft, Emory University Address correspondence to [email protected]. For the articles discussed, see doi:10.1128/JCM.00301-16, doi:10.1128/JCM.00200-16, doi:10.1128/JCM.00046-16, and doi:10.1128/JCM.00081-16. Copyright © 2016, American Society for Microbiology. All Rights Reserved. The views expressed in this Commentary do not necessarily reflect the views of the journal or of ASM.
Journal of Clinical Microbiology
August 2016 Volume 54 Number 8
Commentary
called this MPS, for massively parallel sequencing) eventually will become the routine method for sequencing and then go on to discuss the predicted impacts on the field of microbial forensics. They also provide a historical account of the use of microbial forensics, including early HIV infection cases that went to the courts. In these cases, sequencing was used to address numerous questions, including the following: “(1) Was the suspect the source responsible for the outbreak? (2) Could it be ascertained whether the patients who had been infected shared a source and thus could be included in the outbreak? (3) Alternatively, which patients could have been infected from other sources? (4) Could these alternative sources or the existence of different but simultaneous outbreaks be determined? (5) Could the duration of the outbreak be determined? and (6) Could the time of infection for each patient in the outbreak be estimated?” It is important to see that earlier sequencing methods attempted to answer the same questions that are still important to ongoing investigations and that the methods have only become better resolved and easier with WGS. These authors also touch on the role of metagenomics methods in various ways of characterizing all of the species present in a forensic sample. The future of microbial forensics will include expansion into new applications that can characterize and compare mixed environmental samples that often have thousands of species present. Last, the authors discuss the importance of validation for WGS methods that will be used in the courts and that will impact the health, life, and freedom of individuals if convicted. The last minireview, from the Genomics for Public Health Pathogen Surveillance session, outlines how the authors used WGS methods to create the GenomeTrakr network and databases for state, federal, and international laboratories to collaborate and share data during investigations of foodborne contaminants, to enhance food safety (5). The authors describe the development and growth of the FDA’s efforts in using WGS methods from earlier case studies (6, 7) to the regular use of WGS to support foodborne pathogen investigations. The current database and network are uploading over 2,300 WGS draft genomes per month with a current total of over 57,000 isolates sequenced and made publicly available at https://youtu.be/jLO1Ki5l8mM and http://www.fda.gov/Food/FoodScienceResearch/WholeGenome SequencingProgramWGS/. These authors also discuss the need to expand WGS-based databases for a One Health approach, both at the clinical level and in applying these methods within the food industry and on the farm. By making the data publicly available, the FDA fosters innovation in new methods of data analysis and new applications for rapid isolate characterization. These authors also predict that we will see massive growth in the use of WGS and global adoption of these methods. They argue that by placing the raw sequence data into publicly available shared access sites, they can facilitate the growth and adoption of these methods. The most recent growth in the GenomeTrakr database is coming from global partners whose countries decided to add their foodborne pathogens into the central repository at the National Center for Biotechnology Information (NCBI). The GenomeTrakr database is part of NCBI’s Pathogen Detections website, which has been developed for the deposit of WGS draft genomes for any human pathogen into the Sequence Read Archive (SRA) for development and sharing of human pathogen genomes. From these databases, numerous new taxonomy tools can be tested and launched for the rapid characterization of pathogens. All four minireviews are interconnected in that they share a
August 2016 Volume 54 Number 8
WGS methodology, and so, each is directly enhanced by the applications described by the others. One of the strengths of WGS is that the sequence formats have long been standardized, and most new sequencers produce data that can be formatted into these standards, so that new data can be directly compared to the last 30 years of sequence information archived and stored at NCBI. Having a stable format has allowed for the continual development and growth of data analysis tools. Collecting complete genomes of data requires some modifications to software, but it is often doing more of the same analyses or developing shortcuts for existing methods. For all of these minireviews, the large amounts of data being collected using WGS have allowed investigators to expand existing applications to higher resolution and more detailed characterization of isolates and/or mixed samples. As investigators develop smarter databases where phenotype and genotype are collected on the same samples and deposited into publicly available databases, more phenotypic predictions will be possible from improved rapid genetic characterization. The future of microbiology will see enriched metadata collected and deposited with the genome and or metagenome. Many future scientific advances will be a result of more open access to large amounts of data. The FDA has followed the NCBI in open access to data and in early access to publicly funded research. Public funding requires full and timely release of all of the data so that the public can examine the data and leverage it for more useful applications. Not only will the future of microbiology and the impact of WGS benefit from new developments in data analysis of big data, but the current technology also shows no sign of slowing down in regular equipment and chemistry improvements. In the past 5 years, we have seen refrigerator-sized sequencers shrink in size, first to desktop instruments and recently to palm-sized instruments, with the promise of smaller mobile devices. It will not be long before we see sequencers that fit in your pocket and run on your smartphone. In the Internet of Things, a sequencer will be just one more thing, collecting massive amounts of genomic data with fully integrated data analysis, with rapid interpretation and great visualizations. These improvements with the ongoing decline in the costs per base will fully democratize WGS technologies so that we will see more everyday use of the technology. For some companies, this vision goes beyond daily use by academics and government regulators to include full adoption by the food and health industries and the forensic community and, last, directly by the consumer. Based on current trends in growth of the GenomeTrakr database and network, it is relatively easy to predict that we will see WGS in every department of public health and agriculture laboratory in the United States in the next 5 years. The CDC has already been effectively funded to manage the clinical characterization of foodborne pathogens through the National Strategy for Combating Antibiotic-Resistant Bacteria (CARB) program. Microbial forensics also will likely adopt these methods in the crime labs as well, based on the improved microbial characterizations that are gained by adopting WGS technology. Global expansion in these fields is also happening rapidly. The speed of this growth is more difficult to predict and will depend on the direct costs of testing and the ancillary cost to support the technology. Much of the ancillary costs come from data analysis and interpretation. The first two minireviews predict long-term use of MLST and 16S rRNA approaches, respectively, due to the high costs of going directly to full WGS, though I am more hopeful that technology will continue to improve rapidly (but reading the tea leaves is always a tricky proposition).
Journal of Clinical Microbiology
jcm.asm.org
1947
Commentary
In light of all of these advances, it is no wonder that ASM is supporting a multipronged effort to meet and discuss the impacts of WGS. Whole-genome sequencing is truly transforming many aspects of microbiology, and these impacts are just being applied to numerous projects. At the 1st ASM Conference on Rapid NextGeneration Sequencing and Bioinformatic Pipelines for Enhanced Molecular Epidemiological Investigation of Pathogens, numerous other applications were presented in both seminar and poster formats. ASM hopes to see more if these presentations come out as minireviews. It is clear that the future is bright for advancement of WGS methods and interpretation. It is an exciting time to be a microbiologist, as the field currently has a new tool that will provide insights into microbiology for many years to come. FUNDING INFORMATION The research received support from internal U.S. FDA funding.
REFERENCES 1. Maiden MCJ, Harrison OB. 2016. Population and functional genomics of Neisseria revealed with gene-by-gene approaches. J Clin Microbiol 54: 1949 –1955. http://dx.doi.org/10.1128/JCM.00301-16.
1948
jcm.asm.org
2. Garritty GM. 2016. A new genomics-driven taxonomy of Bacteria and Archaea: are we there yet? J Clin Microbiol 54:1956 –1963. http://dx.doi.org /10.1128/JCM.00200-16. 3. Pecora ND, Li N, Allard M, Li C, Albano E, Delaney M, Dubois A, Onderdonk AB, Bry L. 2015. Genomically informed surveillance for carbapenem-resistant Enterobacteriaceae in a health care system. mBio 6(4): e01030-15. http://dx.doi.org/10.1128/mBio.01030-15. 4. Schmedes SE, Sajantila A, Budowle B. 2016. Expansion of microbial forensics. J Clin Microbiol 54:1964 –1974. http://dx.doi.org/10.1128/JCM .00046-16. 5. Allard MW, Strain E, Melka D, Bunning K, Musser SM, Brown EW, Timme R. 2016. Practical value of food pathogen traceability through building a whole-genome sequencing network and database. J Clin Microbiol 54:1975–1983. http://dx.doi.org/10.1128/JCM.00081-16. 6. Hoffmann M, Zhao S, Pettengill J, Luo Y, Monday SR, Abbott J, Ayers SL, Cinar HN, Muruvanda T, Li C, Allard MW, Whichard J, Meng J, Brown EW, McDermott PF. 2014. Comparative genomic analysis and virulence differences in closely related Salmonella enterica serotype Heidelberg isolates from humans, retail meats, and animals. Genome Biol Evol 6:1046 –1068. http://dx.doi.org/10.1093/gbe/evu079. 7. Lienau EK, Strain E, Wang C, Cao G, Zheng J, Meng J, Ottesen A, Keys C, Stones R, Hammack T, Musser S, Brown EW, Allard MW. 2011. Next-generation sequencing provides high resolution clustering of food and clinical sources during a foodborne outbreak of salmonellosis. N Engl J Med http://dx.doi.org/10.1056/NEJMc1100443.
Journal of Clinical Microbiology
August 2016 Volume 54 Number 8
