Comparing Mycobacterium tuberculosis transmission reconstruction models from whole genome sequence data.

Genomic epidemiology is routinely used worldwide to interrogate infectious disease dynamics. Multiple computational tools exist that reconstruct transmission networks by coupling genomic data with epidemiological models. Resulting inferences can improve our understanding of pathogen transmission dynamics, and yet the performance of these tools has not been evaluated for tuberculosis (TB), a disease process with complex epidemiology including variable latency and within-host heterogeneity. Here, we performed a systematic comparison of six publicly available transmission reconstruction models, evaluating their accuracy when predicting transmission events in simulated and real-world Mycobacterium tuberculosis outbreaks. We observed variability in the number of transmission links that were predicted with high probability (P ≥ 0.5) and low accuracy of these predictions against known transmission in simulated outbreaks. We also found a low proportion of epidemiologically supported case-contact pairs were identified in our real-world TB clusters. The specificity of all models was high, and a relatively high proportion of the total transmission events predicted by some models were true links, notably with TransPhylo, Outbreaker2, and Phybreak. Our findings may inform the choice of tools in TB transmission analyses and underscore the need for caution when interpreting transmission networks produced using probabilistic approaches.

GEViTRec: Data Reconnaissance Through Recommendation Using a Domain-Specific Visualization Prevalence Design Space.

Genomic Epidemiology (genEpi) is a branch of public health that uses many different data types including tabular, network, genomic, and geographic, to identify and contain outbreaks of deadly diseases. Due to the volume and variety of data, it is challenging for genEpi domain experts to conduct data reconnaissance; that is, have an overview of the data they have and make assessments toward its quality, completeness, and suitability. We present an algorithm for data reconnaissance through automatic visualization recommendation, GEViTRec. Our approach handles a broad variety of dataset types and automatically generates visually coherent combinations of charts, in contrast to existing systems that primarily focus on singleton visual encodings of tabular datasets. We automatically detect linkages across multiple input datasets by analyzing non-numeric attribute fields, creating a data source graph within which we analyze and rank paths. For each high-ranking path, we specify chart combinations with positional and color alignments between shared fields, using a gradual binding approach to transform initial partial specifications of singleton charts to complete specifications that are aligned and oriented consistently. A novel aspect of our approach is its combination of domain-agnostic elements with domain-specific information that is captured through a domain-specific visualization prevalence design space. Our implementation is applied to both synthetic data and real Ebola outbreak data. We compare GEViTRec's output to what previous visualization recommendation systems would generate, and to manually crafted visualizations used by practitioners. We conducted formative evaluations with ten genEpi experts to assess the relevance and interpretability of our results. Code, Data, and Study Materials Availability: https://github.com/amcrisan/GEVitRec.

Using Whole-genome Sequencing to Determine the Timing of Secondary Tuberculosis in British Columbia, Canada.

Combined with epidemiological data, whole-genome sequencing (WGS) can help better resolve individual tuberculosis (TB) transmission events to a degree not possible with traditional genotyping. We combine WGS data with patient-level data to calculate the timing of secondary TB among contacts of people diagnosed with active TB in British Columbia, Canada.

Trust and the ethical challenges in the use of whole genome sequencing for tuberculosis surveillance: a qualitative study of stakeholder perspectives.

BACKGROUND: Emerging genomic technologies promise more efficient infectious disease control. Whole genome sequencing (WGS) is increasingly being used in tuberculosis (TB) diagnosis, surveillance, and epidemiology. However, while the use of WGS by public health agencies may raise ethical, legal, and socio-political concerns, these challenges are poorly understood. METHOD: Between November 2017 and April 2018, we conducted semi-structured interviews with 22 key stakeholders across the fields of governance and policy, public health, and laboratory sciences representing the major jurisdictions currently using WGS in national TB programs. Thematic analysis of the interviews was conducted using NVivo 11. RESULTS: Respondents identified several ethical and practical challenges associated with WGS in TB care and surveillance, all related to issues of trust, including: 1) the power of public health; 2) data sharing and profits derived from surveillance efforts; and 3) concerns regarding who has access to, and can benefit from, the technology. Additional challenges included: the potential utility that WGS adds to a public health program, the risks associated with linking necessary epidemiological metadata to the genomic data, and challenges associated with jurisdictional capacity to implement the technology. CONCLUSIONS: Successful implementation of WGS is dependent on fostering relationships of trust between those working with genomics technology and those directly impacted by it, including clinicians. Building trust (a) between the public and the public health agencies and (b) within public health agencies themselves is critical due to the inherent complexity of WGS and its implementation for communicable disease control purposes.

The problem with defining foreign birth as a risk factor in tuberculosis epidemiology studies.

OBJECTIVE: To examine how stratifying persons born outside Canada according to tuberculosis (TB) incidence in their birth country and other demographic factors refines our understanding of TB epidemiology and local TB transmission. BACKGROUND: Population-level TB surveillance programs and research studies in low incidence settings often report all persons born outside the country in which the study is conducted as "foreign-born"-a single label for a highly diverse population with variable TB risks. This may mask important TB epidemiologic trends and not accurately reflect local transmission patterns. METHODS: We used population-level data from two large cohorts in British Columbia (BC), Canada: an immigration cohort (n = 337,492 permanent residents to BC) and a genotyping cohort (n = 2290 culture-confirmed active TB cases). We stratified active TB case counts, incidence rates, and genotypic clustering (an indicator of TB transmission) in BC by birth country TB incidence, age at immigration, and years since arrival. RESULTS: Persons from high-incidence countries had a 12-fold higher TB incidence than those emigrating from low-incidence settings. Estimates of local transmission, as captured by genotyping, versus reactivation of latent TB infection acquired outside Canada varied when data were stratified by birthplace TB incidence, as did patient-level characteristics of individuals in each group, such as age and years between immigration and diagnosis. CONCLUSION: Categorizing persons beyond simply "foreign-born", particularly in the context of TB epidemiologic and molecular data, is needed for a more accurate understanding of TB rates and patterns of transmission.

Universal genotyping reveals province-level differences in the molecular epidemiology of tuberculosis.

OBJECTIVES: Compare the molecular epidemiology of tuberculosis (TB) between two large Canadian provinces-Ontario and British Columbia (BC)-to identify genotypic clusters within and across both provinces, allowing for an improved understanding of genotype data and providing context to more accurately identify clusters representing local transmission. DESIGN: We compared 24-locus Mycobacterial Interspersed Repetitive Units-Variable Number of Tandem Repeats (MIRU-VNTR) genotyping for 3,314 Ontario and 1,602 BC clinical Mycobacterium tuberculosis isolates collected from 2008 through 2014. Laboratory data for each isolate was linked to case-level records to obtain clinical and demographic data. RESULTS: The demographic characteristics of persons with TB varied between provinces, most notably in the proportion of persons born outside Canada, which was reflected in the large number of unique genotypes (n = 3,461). The proportion of clustered isolates was significantly higher in BC. Substantial clustering amongst non-Lineage 4 TB strains was observed within and across the provinces. Only two large clusters (≥10 cases/cluster) representing within province transmission had interprovincial genotype matches. CONCLUSION: We recommend expanding analysis of shared genotypes to include neighbouring jurisdictions, and implementing whole genome sequencing to improve identification of TB transmission, recognize outbreaks, and monitor changing trends in TB epidemiology.

Building the Framework for Standardized Clinical Laboratory Reporting of Next-generation Sequencing Data for Resistance-associated Mutations in Mycobacterium tuberculosis Complex.

Tuberculosis is the primary infectious disease killer worldwide, with a growing threat from multidrug-resistant cases. Unfortunately, classic growth-based phenotypic drug susceptibility testing (DST) remains difficult, costly, and time consuming, while current rapid molecular testing options are limited by the diversity of antimicrobial-resistant genotypes that can be detected at once. Next-generation sequencing (NGS) offers the opportunity for rapid, comprehensive DST without the time or cost burden of phenotypic tests and can provide useful information for global surveillance. As access to NGS expands, it will be important to ensure that results are communicated clearly, consistent, comparable between laboratories, and associated with clear guidance on clinical interpretation of results. In this viewpoint article, we summarize 2 expert workshops regarding a standardized report format, focusing on relevant variables, terminology, and required minimal elements for clinical and laboratory reports with a proposed standardized template for clinical reporting NGS results for Mycobacterium tuberculosis.

Adjutant: an R-based tool to support topic discovery for systematic and literature reviews.

SUMMARY: Adjutant is an open-source, interactive and R-based application to support mining PubMed for literature reviews. Given a PubMed-compatible search query, Adjutant downloads the relevant articles and allows the user to perform an unsupervised clustering analysis to identify data-driven topic clusters. Following clustering, users can also sample documents using different strategies to obtain a more manageable dataset for further analysis. Adjutant makes explicit trade-offs between speed and accuracy, which are modifiable by the user, such that a complete analysis of several thousand documents can take a few minutes. All analytic datasets generated by Adjutant are saved, allowing users to easily conduct other downstream analyses that Adjutant does not explicitly support. AVAILABILITY AND IMPLEMENTATION: Adjutant is implemented in R, using Shiny, and is available at https://github.com/amcrisan/Adjutant. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Whole blood human transcriptome and virome analysis of ME/CFS patients experiencing post-exertional malaise following cardiopulmonary exercise testing.

Myalgic encephalomyelitis / chronic fatigue syndrome (ME/CFS) is a syndrome of unknown etiology characterized by profound fatigue exacerbated by physical activity, also known as post-exertional malaise (PEM). Previously, we did not detect evidence of immune dysregulation or virus reactivation outside of PEM periods. Here we sought to determine whether cardiopulmonary exercise stress testing of ME/CFS patients could trigger such changes. ME/CFS patients (n = 14) and matched sedentary controls (n = 11) were subjected to cardiopulmonary exercise on 2 consecutive days and followed up to 7 days post-exercise, and longitudinal whole blood samples analyzed by RNA-seq. Although ME/CFS patients showed significant worsening of symptoms following exercise versus controls, with 8 of 14 ME/CFS patients showing reduced oxygen consumption ([Formula: see text]) on day 2, transcriptome analysis yielded only 6 differentially expressed gene (DEG) candidates when comparing ME/CFS patients to controls across all time points. None of the DEGs were related to immune signaling, and no DEGs were found in ME/CFS patients before and after exercise. Virome composition (P = 0.746 by chi-square test) and number of viral reads (P = 0.098 by paired t-test) were not significantly associated with PEM. These observations do not support transcriptionally-mediated immune cell dysregulation or viral reactivation in ME/CFS patients during symptomatic PEM episodes.

Immunosignature Analysis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS).

A random-sequence peptide microarray can interrogate serum antibodies in a broad, unbiased fashion to generate disease-specific immunosignatures. This approach has been applied to cancer detection, diagnosis of infections, and interrogation of vaccine response. We hypothesized that there is an immunosignature specific to ME/CFS and that this could aid in the diagnosis. We studied two subject groups meeting the Canadian Consensus Definition of ME/CFS. ME/CFS (n = 25) and matched control (n = 25) sera were obtained from a Canadian study. ME/CFS (n = 25) sera were obtained from phase 1/2 Norwegian trials (NCT01156909). Sera from six healthy controls from the USA were included in the analysis. Canadian cases and controls were tested for a disease immunosignature. By combining results from unsupervised and supervised analyses, a candidate immunosignature with 654 peptides was able to differentiate ME/CFS from controls. The immunosignature was tested and further refined using the Norwegian and USA samples. This resulted in a 256-peptide immunosignature with the ability to separate ME/CFS cases from controls in the international data sets. We were able to identify a 256-peptide signature that separates ME/CFS samples from healthy controls, suggesting that the hit-and-run hypothesis of immune dysfunction merits further investigation. By extending testing of both our signature and one previously reported in the literature to larger cohorts, and further interrogating the specific peptides we and others have identified, we may deepen our understanding of the origins of ME/CFS and work towards a clinically meaningful diagnostic biomarker.

A systematic method for surveying data visualizations and a resulting genomic epidemiology visualization typology: GEViT.

MOTIVATION: Data visualization is an important tool for exploring and communicating findings from genomic and healthcare datasets. Yet, without a systematic way of organizing and describing the design space of data visualizations, researchers may not be aware of the breadth of possible visualization design choices or how to distinguish between good and bad options. RESULTS: We have developed a method that systematically surveys data visualizations using the analysis of both text and images. Our method supports the construction of a visualization design space that is explorable along two axes: why the visualization was created and how it was constructed. We applied our method to a corpus of scientific research articles from infectious disease genomic epidemiology and derived a Genomic Epidemiology Visualization Typology (GEViT) that describes how visualizations were created from a series of chart types, combinations and enhancements. We have also implemented an online gallery that allows others to explore our resulting design space of visualizations. Our results have important implications for visualization design and for researchers intending to develop or use data visualization tools. Finally, the method that we introduce is extensible to constructing visualizations design spaces across other research areas. AVAILABILITY AND IMPLEMENTATION: Our browsable gallery is available at http://gevit.net and all project code can be found at https://github.com/amcrisan/gevitAnalysisRelease. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Within-host Mycobacterium tuberculosis diversity and its utility for inferences of transmission.

Whole genome sequencing in conjunction with traditional epidemiology has been used to reconstruct transmission networks of Mycobacterium tuberculosis during outbreaks. Given its low mutation rate, genetic diversity within M. tuberculosis outbreaks can be extremely limited - making it difficult to determine precisely who transmitted to whom. In addition to consensus SNPs (cSNPs), examining heterogeneous alleles (hSNPs) has been proposed to improve resolution. However, few studies have examined the potential biases in detecting these hSNPs. Here, we analysed genome sequence data from 25 specimens from British Columbia, Canada. Specimens were sequenced to a depth of 112-296×. We observed biases in read depth, base quality, strand distribution and read placement where possible hSNPs were initially identified, so we applied conservative filters to reduce false positives. Overall, there was phylogenetic concordance between the observed 2542 cSNP and 63 hSNP loci. Furthermore, we identified hSNPs shared exclusively by epidemiologically linked patients, supporting their use in transmission inferences. We conclude that hSNPs may add resolution to transmission networks, particularly where the overall genetic diversity is low.

Genotyping and Whole-Genome Sequencing to Identify Tuberculosis Transmission to Pediatric Patients in British Columbia, Canada, 2005-2014.

Background: Tuberculosis (TB) in children is often an indicator of recent transmission. Genotyping and whole-genome sequencing (WGS) can enhance pediatric TB investigations by confirming or refuting transmission events. Methods: Mycobacterium tuberculosis isolates from all pediatric patients <18 years with culture-confirmed TB in British Columbia (BC) from 2005 to 2014 (n = 49) were genotyped by Mycobacterial Interspersed Repetitive Units-Variable Number Tandem Repeat (MIRU-VNTR) and compared with adult isolates. Genotypically clustered cases underwent WGS. Clinical, demographic, and contact data were reviewed for each case. Results: Twenty-three children were Canadian-born, 7 to Canadian-born parents (CBP) and 16 to foreign-born parents (FBP). Of the 26 foreign-born children, all were born in Asia (81%) or Africa (19%). Using molecular and epidemiological data, we determined that 15 children had acquired their infection within BC, and household transmission explained all 7 Canadian-born (FBP) children that acquired TB locally. In contrast, 6 of 7 Canadian-born (CBP) children were exposed via a non-household community source. Eight Canadian-born (FBP) children acquired their infections through travel to their parents' place of birth. All but 1 of the foreign-born children acquired their infection outside of BC. Conclusions: Genotyping and genomic data reveal that drivers of pediatric transmission vary according to a child's age, birthplace, and their parents' place of birth.

Universal Genotyping for Tuberculosis Prevention Programs: a 5-Year Comparison with On-Request Genotyping.

Prospective universal genotyping of tuberculosis (TB) isolates is used by many laboratories to detect clusters of cases and inform contact investigations. Prior to universal genotyping, most TB prevention programs genotyped isolates on request only, relying on requests from public health professionals whose knowledge of a patient's clinical, demographic, and epidemiological characteristics suggested potential transmission. To justify the switch from on-request to universal genotyping-particularly in the public health domain, with its limited resources and competing priorities-it is important to demonstrate the additional benefit provided by a universal genotyping program. We compared the clustering patterns revealed by retrospective 24-locus mycobacterial interspersed repetitive unit-variable-number tandem repeat genotyping of all culture-positive isolates over a 5-year period to the patterns previously established by our genotyping-on-request program in the low-incidence setting of British Columbia, Canada. We found that 23.8% of isolates were requested during the study period, and while requested isolates had increased odds of belonging to a genotype cluster (adjusted odds ratio, 2.3; 95% confidence interval, 1.5 to 3.3), only 54.6% clustered with the requested comparator strain. Universal genotyping revealed 94 clusters ranging in size from 2 to 53 isolates (mean = 5) and involving 432 individuals. On-request genotyping missed 54 (57.4%) of these clusters and 130 (30.1%) clustered individuals. Our results underscore that TB patient networks are complex, with unrecognized linkages between patients, and a prospective province-wide universal genotyping program provides an informative, bias-free tool to explore transmission to a degree not possible with on-request genotyping.

Evidence-based design and evaluation of a whole genome sequencing clinical report for the reference microbiology laboratory.

BACKGROUND: Microbial genome sequencing is now being routinely used in many clinical and public health laboratories. Understanding how to report complex genomic test results to stakeholders who may have varying familiarity with genomics-including clinicians, laboratorians, epidemiologists, and researchers-is critical to the successful and sustainable implementation of this new technology; however, there are no evidence-based guidelines for designing such a report in the pathogen genomics domain. Here, we describe an iterative, human-centered approach to creating a report template for communicating tuberculosis (TB) genomic test results. METHODS: We used Design Study Methodology-a human centered approach drawn from the information visualization domain-to redesign an existing clinical report. We used expert consults and an online questionnaire to discover various stakeholders' needs around the types of data and tasks related to TB that they encounter in their daily workflow. We also evaluated their perceptions of and familiarity with genomic data, as well as its utility at various clinical decision points. These data shaped the design of multiple prototype reports that were compared against the existing report through a second online survey, with the resulting qualitative and quantitative data informing the final, redesigned, report. RESULTS: We recruited 78 participants, 65 of whom were clinicians, nurses, laboratorians, researchers, and epidemiologists involved in TB diagnosis, treatment, and/or surveillance. Our first survey indicated that participants were largely enthusiastic about genomic data, with the majority agreeing on its utility for certain TB diagnosis and treatment tasks and many reporting some confidence in their ability to interpret this type of data (between 58.8% and 94.1%, depending on the specific data type). When we compared our four prototype reports against the existing design, we found that for the majority (86.7%) of design comparisons, participants preferred the alternative prototype designs over the existing version, and that both clinicians and non-clinicians expressed similar design preferences. Participants showed clearer design preferences when asked to compare individual design elements versus entire reports. Both the quantitative and qualitative data informed the design of a revised report, available online as a LaTeX template. CONCLUSIONS: We show how a human-centered design approach integrating quantitative and qualitative feedback can be used to design an alternative report for representing complex microbial genomic data. We suggest experimental and design guidelines to inform future design studies in the bioinformatics and microbial genomics domains, and suggest that this type of mixed-methods study is important to facilitate the successful translation of pathogen genomics in the clinic, not only for clinical reports but also more complex bioinformatics data visualization software.

Molecular Epidemiology of Tuberculosis in British Columbia, Canada: A 10-Year Retrospective Study.

Background: Understanding regional molecular epidemiology allows for the development of more efficient tuberculosis prevention strategies in low-incidence settings. Methods: We analyzed 24-locus mycobacterial interspersed repetitive-unit-variable-number tandem repeat (MIRU-VNTR) genotyping for 2290 Mycobacterium tuberculosis clinical isolates collected in the province of British Columbia (BC), Canada, in 2005-2014. Laboratory data for each isolate were linked to case-level clinical and demographic data. These data were used to describe the molecular epidemiology of tuberculosis across the province. Results: We detected >1500 distinct genotypes across the 4 major M. tuberculosis lineages, reflecting BC's diverse population. Disease site and clustering rates varied across lineages, and MIRU-VNTR was used to group the 2290 isolates into 189 clusters (2-70 isolates per cluster), with an overall clustering rate of 42.4% and an estimated local transmission rate of 34.1%. Risk factors for clustering varied between Canadian-born and foreign-born individuals; the former had increased odds (odds ratio, 7.8; 95% confidence interval [CI], 6.2-9.6) of belonging to a genotypic cluster, although nearly one-quarter of clusters included both Canadian- and foreign-born persons. Large clusters (≥10 cases) occurred more frequently within the M. tuberculosis Euro-American lineage, and individual-level risk factors associated with belonging to a large cluster included being Canadian born (adjusted odds ratio, 3.3; 95% CI, 2.3-4.8), residing in a rural area (2.3; 1.2-4.5), and illicit drug use (2.0; 1.2-3.4). Conclusions: Although tuberculosis in BC largely arises through reactivation of latent tuberculosis in foreign-born persons, locally transmitted infections occur in discrete populations with distinct disease and risk factor profiles, representing groups for targeted interventions.

Towards a genomics-informed, real-time, global pathogen surveillance system.

The recent Ebola and Zika epidemics demonstrate the need for the continuous surveillance, rapid diagnosis and real-time tracking of emerging infectious diseases. Fast, affordable sequencing of pathogen genomes - now a staple of the public health microbiology laboratory in well-resourced settings - can affect each of these areas. Coupling genomic diagnostics and epidemiology to innovative digital disease detection platforms raises the possibility of an open, global, digital pathogen surveillance system. When informed by a One Health approach, in which human, animal and environmental health are considered together, such a genomics-based system has profound potential to improve public health in settings lacking robust laboratory capacity.

Genome Sequences of the Mycobacterium tuberculosis H37Rv-ptkA Deletion Mutant and Its Parental Strain.

Mycobacterium tuberculosis, the etiological agent of tuberculosis, is one of the most devastating infectious agents in the world. Here, we report the draft genome sequences of the M. tuberculosis protein tyrosine kinase (ptkA) deletion mutant and its parental strain H37Rv, which are used in genetic studies and for drug discovery.

Complete Genome Sequence of Mycobacterium chimaera SJ42, a Nonoutbreak Strain from an Immunocompromised Patient with Pulmonary Disease.

Mycobacterium chimaera, a nontuberculous mycobacterium (NTM) belonging to the Mycobacterium avium complex (MAC), is an opportunistic pathogen that can cause respiratory and disseminated disease. We report the complete genome sequence of a strain, SJ42, isolated from an immunocompromised male presenting with MAC pneumonia, assembled from Illumina and Oxford Nanopore data.