Clinical metagenomics.

Clinical metagenomic next-generation sequencing (mNGS), the comprehensive analysis of microbial and host genetic material (DNA and RNA) in samples from patients, is rapidly moving from research to clinical laboratories. This emerging approach is changing how physicians diagnose and treat infectious disease, with applications spanning a wide range of areas, including antimicrobial resistance, the microbiome, human host gene expression (transcriptomics) and oncology. Here, we focus on the challenges of implementing mNGS in the clinical laboratory and address potential solutions for maximizing its impact on patient care and public health

International Society for Disease Surveillance Conference 2011: Building the Future of Public Health Surveillance: Building the Future of Public Health Surveillance

Daniel Reidpath - ORCID: 0000-0002-8796-0420 https://orcid.org/0000-0002-8796-04204pubpub1117

Important Canine Zoonoses from a Public Health Perspective and the Introduction of Companion Animal Surveillance in the Prairie Provinces of Canada

ABSTRACT Prioritizing zoonotic and/or sapronotic pathogens of domestic animal populations and initiating ongoing surveillance of such pathogens is needed in Canada. From a One Health perspective, gathering and recording more comprehensive disease data on the population of animals most closely associated with humans is extremely valuable and necessary. Therefore, the purpose of this thesis was to identify a subset of domestic canine pathogens of public health significance specific to the Prairie Provinces of Canada and to establish a framework for a companion animal surveillance initiative to the region. This research was conducted within a two- year period from September 2019 to April 2021. The first component of this research involved the creation of a comprehensive list of any pathogen historically reported in the domestic dog by reviewing several companion animal infectious disease textbooks, which resulted in 594 pathogens total. This list was then pared down to identify only those pathogens that were significant from a public health perspective in Canada and the prairies. This was accomplished using a formulated stepwise approach that pathogens only moved on to the final list if: (1) the pathogen was zoonotic/sapronotic/anthroponotic, (2) the domestic dog was involved in transmission, maintenance or detection of the pathogen, and (3) there was a level of risk for occurrence of the pathogen in Canada. Following this stepwise approach, of the initial 594 canine pathogens 84 pathogens were deemed important in Canada and the prairies from a public health perspective. A follow-up study to this research involved a prioritization exercise using experts in the field of veterinary medicine, public health, and epidemiology to identify the top 5 highest priority pathogens from the final list of 84 canine pathogens upon which to focus a companion animal surveillance program specific to the Prairie Provinces. The exercise was accomplished through a voluntary survey using a semi-quantitative ranking strategy. The resulting top 5 pathogens to come out of the exercise were: (1) Echinococcus spp. (granulosus, multilocularis), (2) MRSA, (3) Salmonella enterica, (4) MRSP, and (5) Borrelia burgdorferi. The final component of this research examined the utility of clinical veterinarians and veterinary clinics in a companion animal surveillance program. In addition, responses from clinical veterinarians were used to formulate case definitions for the top 5 highest priority pathogens intended for surveillance. Assessing dogs as sentinels for pathogens of public health concern using Lyme disease as an example was also conducted in this research chapter. Data was gathered through a voluntary survey disseminated to clinical veterinarians in the provinces of Alberta, Saskatchewan, and Manitoba. The results of this survey identified that clinical veterinarians are willing to participate in a surveillance program, that there is important in-clinic veterinary data not currently being captured from a population or disease monitoring standpoint, and that domestic dogs can serve as good sentinels for Lyme disease risk in humans, specific to the prairies. This thesis provided the foundational steps for a companion animal surveillance initiative specific to the Prairie Provinces of Canada. It identified which pathogens involving the domestic dog pose a significant public health risk in Canada and the prairies, prioritized these pathogens from highest to lowest concern using expert opinion, and established the importance of cooperation with practicing veterinarians and veterinary clinics for a companion animal surveillance program to be successful

Syndromic surveillance: reports from a national conference, 2003

Overview of Syndromic Surveillance -- What is Syndromic Surveillance? -- Linking Better Surveillance to Better Outcomes -- Review of the 2003 National Syndromic Surveillance Conference - Lessons Learned and Questions To Be Answered -- -- System Descriptions -- New York City Syndromic Surveillance Systems -- Syndrome and Outbreak Detection Using Chief-Complaint Data - Experience of the Real-Time Outbreak and Disease Surveillance Project -- Removing a Barrier to Computer-Based Outbreak and Disease Surveillance - The RODS Open Source Project -- National Retail Data Monitor for Public Health Surveillance -- National Bioterrorism Syndromic Surveillance Demonstration Program -- Daily Emergency Department Surveillance System - Bergen County, New Jersey -- Hospital Admissions Syndromic Surveillance - Connecticut, September 2001-November 2003 -- BioSense - A National Initiative for Early Detection and Quantification of Public Health Emergencies -- Syndromic Surveillance at Hospital Emergency Departments - Southeastern Virginia -- -- Research Methods -- Bivariate Method for Spatio-Temporal Syndromic Surveillance -- Role of Data Aggregation in Biosurveillance Detection Strategies with Applications from ESSENCE -- Scan Statistics for Temporal Surveillance for Biologic Terrorism -- Approaches to Syndromic Surveillance When Data Consist of Small Regional Counts -- Algorithm for Statistical Detection of Peaks - Syndromic Surveillance System for the Athens 2004 Olympic Games -- Taming Variability in Free Text: Application to Health Surveillance -- Comparison of Two Major Emergency Department-Based Free-Text Chief-Complaint Coding Systems -- How Many Illnesses Does One Emergency Department Visit Represent? Using a Population-Based Telephone Survey To Estimate the Syndromic Multiplier -- Comparison of Office Visit and Nurse Advice Hotline Data for Syndromic Surveillance - Baltimore-Washington, D.C., Metropolitan Area, 2002 -- Progress in Understanding and Using Over-the-Counter Pharmaceuticals for Syndromic Surveillance -- -- Evaluation -- Evaluation Challenges for Syndromic Surveillance - Making Incremental Progress -- Measuring Outbreak-Detection Performance By Using Controlled Feature Set Simulations -- Evaluation of Syndromic Surveillance Systems - Design of an Epidemic Simulation Model -- Benchmark Data and Power Calculations for Evaluating Disease Outbreak Detection Methods -- Bio-ALIRT Biosurveillance Detection Algorithm Evaluation -- ESSENCE II and the Framework for Evaluating Syndromic Surveillance Systems -- Conducting Population Behavioral Health Surveillance by Using Automated Diagnostic and Pharmacy Data Systems -- Evaluation of an Electronic General-Practitioner-Based Syndromic Surveillance System -- National Symptom Surveillance Using Calls to a Telephone Health Advice Service - United Kingdom, December 2001-February 2003 -- Field Investigations of Emergency Department Syndromic Surveillance Signals - New York City -- Should We Be Worried? Investigation of Signals Generated by an Electronic Syndromic Surveillance System - Westchester County, New York -- -- Public Health Practice -- Public Health Information Network - Improving Early Detection by Using a Standards-Based Approach to Connecting Public Health and Clinical Medicine -- Information System Architectures for Syndromic Surveillance -- Perspective of an Emergency Physician Group as a Data Provider for Syndromic Surveillance -- SARS Surveillance Project - Internet-Enabled Multiregion Surveillance for Rapidly Emerging Disease -- Health Information Privacy and Syndromic Surveillance SystemsPapers from the second annual National Syndromic Surveillance Conference convened by the New York City Department of Health and Mental Hygiene, the New York Academy of Medicine, and the CDC in New York City during Oct. 23-24, 2003. Published as the September 24, 2004 supplement to vol. 53 of MMWR. Morbidity and mortality weekly report.1571461

Emerg Infect Dis

PMC4550154611

K-meeridel põhinevad meetodid bakterite ja plasmiidide tuvastamiseks

Väitekirja elektrooniline versioon ei sisalda publikatsiooneMikroorganismid on Maad asustanud juba miljardeid aastaid ning neid leidub peaaegu kõikjal. Isegi meie oleme nendega lahutamatult seotud – baktereid elab nii meie nahal kui ka soolestikus. Osad bakteritest võivad aga olla patogeensed ja põhjustada haigusi. Näiteks oli keskajal suure hulga elanikkonnast tapnud Musta Surma põhjustajaks katkubakter Yersinia pestis. Tänapäeval aitavad meid bakterite vastu antibiootikumid, kuid järjest suurem probleem on antibiootikumiresistentsuse laialdane levik. Sellele aitavad kaasa plasmiidid – bakterites olevad DNA järjestused, mis on bakteri enda kromosoomist eraldiseisvad ning mida bakterid võivad kiirelt üksteisele edasi anda. Käesoleva doktoritöö eesmärgiks oli luua bakterite ja plasmiidide tuvastamiseks meetodid, mis võimaldaksid töötada sekveneerimiskeskuste poolt toodetud toorandmetega. Ülesande lahendamiseks otsustasime kasutada k-meeridel põhinevat analüüsi. K-meer tähistab lühikest DNA juppi pikkusega k nukleotiidi. Pikema DNA järjestuse, näiteks bakterigenoomi, saab jagada lühemateks k-meerideks ning vaadelda seda kui k-meeride kogumit. Sellise lähenemise eeliseks on sõltumatus lugemi pikkusest – kõik lugemid sisaldavad k-meere ning analüüsides k-meeride hulki, on võimalik määrata algse proovi koostis. StrainSeeker on meie töögrupis loodud programm bakteritüvede määramiseks. Me arendasime välja uudse algoritmi, mis näitab proovis esineva bakteri eeldatavat asukohta kasutaja poolt ette antaval fülogeneetilisel puul. Lõime ka visuaalse kasutajaliidesega veebiserveri. Plasmiidide tuvastamiseks eeldasime, et plasmiidide arv bakteri rakus on tavaliselt suurem bakteri kromosoomi omast, seega võiks ka plasmiidi k-meeride keskmine esinemissagedus olla suurem kui bakteri kromosoomi k-meeride puhul. Me testisime oma programmi, mis sai nimeks PlasmidSeeker, nii simuleeritud kui ka reaalsete bakteri täisgenoomi sekveneerimisandmestikega, millede puhul oli teada proovide tegelik koostis. PlasmidSeeker leidis üles kõik proovides olnud plasmiidid ning määras täpselt ka nende koopiaarvu. Kokkuvõttes oleme oma tööga andnud panuse arvutuslikku mikrobioloogiasse, luues uued võimalused bakteriaalsete proovide analüüsiks.Microbes have roamed Earth for billions of years and can be found almost anywhere. They are present even on our skin and in our gut. However, some bacteria can be pathogenic and cause diseases. For instance, the Black Death, which killed millions during the Middle Ages, was caused by the bacterium Yersinia pestis. Nowadays, antibiotics protect us against the bacterial threat, but a new problem is looming – widespread antibiotic resistance. This is partly facilitated by plasmids – DNA sequences which are separate from the bacterial chromosome and can be readily passed from one bacterium to the other. The general goal of this work was to develop methods for the identification of bacteria and plasmids from raw data produced by sequencing centers. We decided to use k-mer based analysis for this task. K-mer itself is simply a short stretch of DNA with a length of k nucleotides. A long DNA sequence, such as a bacterial genome, can be divided into shorter k-mers and analyzed as a whole. This has the advantage of not being limited by read length – any read contains k-mers and by analyzing these, we can identify the contents of the sample. StrainSeeker is a bacterial identification program developed by our group. We developed a novel algorithm that predicts the location of an isolated bacterium on the user-provided phylogenetic tree. Also, we created a web server with a visual interface for users with limited bioinformatics experience. For plasmid detection, we assumed that the plasmid copy number is usually higher compared to the bacterial chromosome. This means that the average frequency of plasmid k-mers should also be higher than the frequency of chromosomal k-mers. We named the program PlasmidSeeker and tested it with real and simulated bacterial whole genome sequencing samples, in which the real plasmid content was known. PlasmidSeeker detected all plasmids and accurately estimated their copy numbers. With our work, we have made a contribution to the field of computational microbiology and provided novel means for the analysis of bacterial samples

Metagenomic Applications in Virus Discovery, Ecology, and the Surveillance of Australian Wildlife

Metagenomic next-generation sequencing (mNGS), particularly total RNA sequencing (“meta-transcriptomics”), has led to a revolution in virus discovery, veterinary diagnostics and virus evolution. Wildlife naturally harbour a diverse assemblage of infectious microorganisms and these can be a source of novel, and often poorly studied, diseases of humans and other animals. Many mortality and morbidity events in wildlife are long-standing, neglected and unsolved. These include wobbly possum disease, black and white bird disease, clenched claw syndrome and bearded dragon respiratory disease. To provide a new understanding of these diseases and identify pathogens in diseased wildlife with unknown aetiology across different taxa, I developed and applied a meta-transcriptomic-based pipeline that was used in combination with retrospective clinical metadata, histopathology, phylogeny, and molecular assays. Accordingly, novel viruses were identified from a wide range of virus families, including the Circoviridae, Chaphamaparvoviridae, Flaviviridae, Astroviridae, Picornaviridae, Paramixoviridae, Adenoviridae, and Polyomaviridae, greatly extending our knowledge of virus diversity in wildlife, including marsupials, birds, and reptiles from both the wild and captive environments. Similarly, through exploiting meta-transcriptomic approaches and mining the Sequence Read Archive, I discovered four novel hepatitis delta-like viruses from fish, amphibians and termites, thereby rejecting the concept that hepatitis delta viruses are only associated with humans. In sum, my work highlights a successful combination of metagenomics with traditional tools to transform veterinary clinical diagnostics and disease surveillance. In doing so, it sheds light on the enormous diversity of viruses, elucidating their origins and evolutionary history, and allowing the discovery of pathogens from wildlife biodiversity diseases within a One Health perspective

K-meeridel põhinevad meetodid bakterite ja plasmiidide tuvastamiseks

Väitekirja elektrooniline versioon ei sisalda publikatsiooneMikroorganismid on Maad asustanud juba miljardeid aastaid ning neid leidub peaaegu kõikjal. Isegi meie oleme nendega lahutamatult seotud – baktereid elab nii meie nahal kui ka soolestikus. Osad bakteritest võivad aga olla patogeensed ja põhjustada haigusi. Näiteks oli keskajal suure hulga elanikkonnast tapnud Musta Surma põhjustajaks katkubakter Yersinia pestis. Tänapäeval aitavad meid bakterite vastu antibiootikumid, kuid järjest suurem probleem on antibiootikumiresistentsuse laialdane levik. Sellele aitavad kaasa plasmiidid – bakterites olevad DNA järjestused, mis on bakteri enda kromosoomist eraldiseisvad ning mida bakterid võivad kiirelt üksteisele edasi anda. Käesoleva doktoritöö eesmärgiks oli luua bakterite ja plasmiidide tuvastamiseks meetodid, mis võimaldaksid töötada sekveneerimiskeskuste poolt toodetud toorandmetega. Ülesande lahendamiseks otsustasime kasutada k-meeridel põhinevat analüüsi. K-meer tähistab lühikest DNA juppi pikkusega k nukleotiidi. Pikema DNA järjestuse, näiteks bakterigenoomi, saab jagada lühemateks k-meerideks ning vaadelda seda kui k-meeride kogumit. Sellise lähenemise eeliseks on sõltumatus lugemi pikkusest – kõik lugemid sisaldavad k-meere ning analüüsides k-meeride hulki, on võimalik määrata algse proovi koostis. StrainSeeker on meie töögrupis loodud programm bakteritüvede määramiseks. Me arendasime välja uudse algoritmi, mis näitab proovis esineva bakteri eeldatavat asukohta kasutaja poolt ette antaval fülogeneetilisel puul. Lõime ka visuaalse kasutajaliidesega veebiserveri. Plasmiidide tuvastamiseks eeldasime, et plasmiidide arv bakteri rakus on tavaliselt suurem bakteri kromosoomi omast, seega võiks ka plasmiidi k-meeride keskmine esinemissagedus olla suurem kui bakteri kromosoomi k-meeride puhul. Me testisime oma programmi, mis sai nimeks PlasmidSeeker, nii simuleeritud kui ka reaalsete bakteri täisgenoomi sekveneerimisandmestikega, millede puhul oli teada proovide tegelik koostis. PlasmidSeeker leidis üles kõik proovides olnud plasmiidid ning määras täpselt ka nende koopiaarvu. Kokkuvõttes oleme oma tööga andnud panuse arvutuslikku mikrobioloogiasse, luues uued võimalused bakteriaalsete proovide analüüsiks.Microbes have roamed Earth for billions of years and can be found almost anywhere. They are present even on our skin and in our gut. However, some bacteria can be pathogenic and cause diseases. For instance, the Black Death, which killed millions during the Middle Ages, was caused by the bacterium Yersinia pestis. Nowadays, antibiotics protect us against the bacterial threat, but a new problem is looming – widespread antibiotic resistance. This is partly facilitated by plasmids – DNA sequences which are separate from the bacterial chromosome and can be readily passed from one bacterium to the other. The general goal of this work was to develop methods for the identification of bacteria and plasmids from raw data produced by sequencing centers. We decided to use k-mer based analysis for this task. K-mer itself is simply a short stretch of DNA with a length of k nucleotides. A long DNA sequence, such as a bacterial genome, can be divided into shorter k-mers and analyzed as a whole. This has the advantage of not being limited by read length – any read contains k-mers and by analyzing these, we can identify the contents of the sample. StrainSeeker is a bacterial identification program developed by our group. We developed a novel algorithm that predicts the location of an isolated bacterium on the user-provided phylogenetic tree. Also, we created a web server with a visual interface for users with limited bioinformatics experience. For plasmid detection, we assumed that the plasmid copy number is usually higher compared to the bacterial chromosome. This means that the average frequency of plasmid k-mers should also be higher than the frequency of chromosomal k-mers. We named the program PlasmidSeeker and tested it with real and simulated bacterial whole genome sequencing samples, in which the real plasmid content was known. PlasmidSeeker detected all plasmids and accurately estimated their copy numbers. With our work, we have made a contribution to the field of computational microbiology and provided novel means for the analysis of bacterial samples