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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Self-rated health and reasons for non-vaccination against seasonal influenza in Canadian adults with asthma

Introduction

While seasonal influenza vaccination is recommended for individuals with asthma, uptake in this population is low. We examined how self-rated health impacts reasons for not being immunized against influenza in Canadian adults with asthma, focusing on those who have never been immunized.

Methods

We pooled four cycles of the Canadian Community Health Survey (cycles 3.1(2005), 2007/08, 2009/10 and 2011/12), grouping individuals by whether their reasons for not having been vaccinated were perceptual or technical. We used a multivariable logistic regression model, adjusted for confounders, to quantify the relationship between self-rated health and their reported reasons for not vaccinating.

Results

Among the 9,836 respondents, 84.4% cited perceptual barriers as a reason for not being vaccinated. After adjusting for socio-demographic characteristics and province of residence, we determined that reporting perceptual barriers was associated with self-rated health status, with the adjusted odds ratios ranging from 1.42 (95%CI: 0.97, 2.09) to 2.64 (95%CI: 1.74, 3.99) for fair and excellent health versus poor health, respectively. Each increase in self-rated health category was associated with greater odds of citing a perceptual rather than technical barrier as a reason for non-vaccination.

Discussion

Self-reported health influences people’s perception of the need for influenza vaccination. Viewing the results through the lens of the precaution adoption process model suggests that personalizing communication around both the risk of influenza and the effectiveness of the vaccine may improve uptake amongst adults with asthma.

RNA-Seq Analysis of Gene Expression, Viral Pathogen, and B-Cell/T-Cell Receptor Signatures in Complex Chronic Disease

Background

Chronic fatigue syndrome (CFS) remains poorly understood. Although infections are speculated to trigger the syndrome, a specific infectious agent and underlying pathophysiological mechanism remain elusive. In a previous study, we described similar clinical phenotypes in CFS patients and alternatively diagnosed chronic Lyme syndrome (ADCLS) patients—individuals diagnosed with Lyme disease by testing from private Lyme specialty laboratories but who test negative by reference 2-tiered serologic analysis.

Methods

Here, we performed blinded RNA-seq analysis of whole blood collected from 25 adults diagnosed with CFS and 13 ADCLS patients, comparing these cases to 25 matched controls and 11 patients with well-controlled systemic lupus erythematosus (SLE). Samples were collected at patient enrollment and not during acute symptom flares. RNA-seq data were used to study host gene expression, B-cell/T-cell receptor profiles (BCR/TCR), and potential viral infections.

Results

No differentially expressed genes (DEGs) were found to be significant when CFS or ADCLS cases were compared to controls. Forty-two DEGs were found when SLE cases were compared to controls, consistent with activation of interferon signaling pathways associated with SLE disease. BCR/TCR repertoire analysis did not show significant differences between CFS and controls or ADCLS and controls. Finally, viral sequences corresponding to anelloviruses, human pegivirus 1, herpesviruses, and papillomaviruses were detected in RNA-seq data, but proportions were similar (P = .73) across all genus-level taxonomic categories.

Conclusions

Our observations do not support a theory of transcriptionally mediated immune cell dysregulation in CFS and ADCLS, at least outside of periods of acute symptom flares.

A brief primer on genomic epidemiology: lessons learned from Mycobacterium tuberculosis

Genomics is now firmly established as a technique for the investigation and reconstruction of communicable disease outbreaks, with many genomic epidemiology studies focusing on revealing transmission routes of Mycobacterium tuberculosis. In this primer, we introduce the basic techniques underlying transmission inference from genomic data, using illustrative examples from M. tuberculosis and other pathogens routinely sequenced by public health agencies. We describe the laboratory and epidemiological scenarios under which genomics may or may not be used, provide an introduction to sequencing technologies and bioinformatics approaches to identifying transmission-informative variation and resistance-associated mutations, and discuss how variation must be considered in the light of available clinical and epidemiological information to infer transmission.

Metagenomic Investigation of Plasma in Individuals with ME/CFS Highlights the Importance of Technical Controls to Elucidate Contamination and Batch Effects

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating disease causing indefinite fatigue. ME/CFS has long been hypothesised to have an infectious cause; however, no specific infectious agent has been identified. We used metagenomics to analyse the RNA from plasma samples from 25 individuals with ME/CFS and compare their microbial content to technical controls as well as three control groups: individuals with alternatively diagnosed chronic Lyme syndrome (N = 13), systemic lupus erythematosus (N = 11), and healthy controls (N = 25). We found that the majority of sequencing reads were removed during host subtraction, thus there was very low microbial RNA content in the plasma. The effects of sample batching and contamination during sample processing proved to outweigh the effects of study group on microbial RNA content, as the few differences in bacterial or viral RNA abundance we did observe between study groups were most likely caused by contamination and batch effects. Our results highlight the importance of including negative controls in all metagenomic analyses, since there was considerable overlap between bacterial content identified in study samples and control samples. For example, Proteobacteria, Firmicutes, Actinobacteria, and Bacteriodes were found in both study samples and plasma-free negative controls. Many of the taxonomic groups we saw in our plasma-free negative control samples have previously been associated with diseases, including ME/CFS, demonstrating how incorrect conclusions may arise if controls are not used and batch effects not accounted for.

Virus genomics and evolution: the transformative effect of new technologies and multidisciplinary collaboration on virus research and outbreak management

The first Virus Genomics and Evolution Conference was held at the Wellcome Genome Campus in Hinxton, UK, 8–10 June 2016.

Declaring a tuberculosis outbreak over with genomic epidemiology

We report an updated method for inferring the time at which an infectious disease was transmitted between persons from a time-labelled pathogen genome phylogeny. We applied the method to 48 Mycobacterium tuberculosis genomes as part of a real-time public health outbreak investigation, demonstrating that although active tuberculosis (TB) cases were diagnosed through 2013, no transmission events took place beyond mid-2012. Subsequent cases were the result of progression from latent TB infection to active disease, and not recent transmission. This evolutionary genomic approach was used to declare the outbreak over in January 2015.

Stopping outbreaks with real-time genomic epidemiology

One of the most successful public health applications of next-generation sequencing is whole-genome sequencing of pathogens to not only detect and characterize outbreaks, but also to inform outbreak management. Using genomics, infection control teams can now track, with extraordinarily high resolution, the transmission events within outbreaks, opening up possibilities for targeted interventions. These successes are positioning the emerging field of genomic epidemiology to replace traditional molecular epidemiology, and increasing our ability to limit the spread of multidrug-resistant organisms.

Metagenomics for pathogen detection in public health

Traditional pathogen detection methods in public health infectious disease surveillance rely upon the identification of agents that are already known to be associated with a particular clinical syndrome. The emerging field of metagenomics has the potential to revolutionize pathogen detection in public health laboratories by allowing the simultaneous detection of all microorganisms in a clinical sample, without a priori knowledge of their identities, through the use of next-generation DNA sequencing. A single metagenomics analysis has the potential to detect rare and novel pathogens, and to uncover the role of dysbiotic microbiomes in infectious and chronic human disease. Making use of advances in sequencing platforms and bioinformatics tools, recent studies have shown that metagenomics can even determine the whole-genome sequences of pathogens, allowing inferences about antibiotic resistance, virulence, evolution and transmission to be made. We are entering an era in which more novel infectious diseases will be identified through metagenomics-based methods than through traditional laboratory methods. The impetus is now on public health laboratories to integrate metagenomics techniques into their diagnostic arsenals.

Genomic analysis identifies targets of convergent positive selection in drug-resistant Mycobacterium tuberculosis

M. tuberculosis is evolving antibiotic resistance, threatening attempts at tuberculosis epidemic control. Mechanisms of resistance, including genetic changes favored by selection in resistant isolates, are incompletely understood. Using 116 newly sequenced and 7 previously sequenced M. tuberculosis whole genomes, we identified genome-wide signatures of positive selection specific to the 47 drug-resistant strains. By searching for convergent evolution--the independent fixation of mutations in the same nucleotide position or gene--we recovered 100% of a set of known resistance markers. We also found evidence of positive selection in an additional 39 genomic regions in resistant isolates. These regions encode components in cell wall biosynthesis, transcriptional regulation and DNA repair pathways. Mutations in these regions could directly confer resistance or compensate for fitness costs associated with resistance. Functional genetic analysis of mutations in one gene, ponA1, demonstrated an in vitro growth advantage in the presence of the drug rifampicin.

Cross-reactive and vaccine-induced antibody to an emerging swine-origin variant of influenza A virus subtype H3N2 (H3N2v)

BACKGROUND

Cases of infection due to a novel swine-origin variant of influenza A virus subtype H3N2 (H3N2v) have recently been identified in the United States, primarily among children. We estimate levels of cross-reactive antibody to H3N2v by age and assess whether seasonal trivalent inactivated influenza vaccine (TIV), with or without adjuvant, may increase seroprotection.

METHODS

Antibody to H3N2v was assessed by hemagglutination inhibition (HI) assay and, for a subset, also by microneutralization assay. Seroprevalence and seroprotection were defined as an HI titer of ≥40, and levels were compared with those for ancestral and contemporary human strains. The analysis included 1116 sera collected during fall 2010, corresponding to approximately 100 sera per decade of life. Vaccine-induced antibody levels were also assessed in sera from 136 children aged <10 years and 65 adults aged 20-59 years before and after receipt of 2010-2011 split TIV and in sera from 182 elderly individuals aged ≥65 years before and after receipt of 2011-2012 split TIV (for 31 individuals), MF59-adjuvanted TIV (for 72), or unadjuvanted subunit TIV (for 79).

RESULTS

The overall prevalence of HI titers of ≥40 against A(H3N2)v was 25%. No children aged <5 years and <20% of individuals aged ≤14 years or ≥40 years had an HI titer of ≥40. Conversely, among individuals aged 15-39 years, half of teens and adults showed H3N2v seroprotection. Following TIV receipt, <15% of individuals in any vaccine group developed a 4-fold increase in antibody level.

CONCLUSIONS

A substantial proportion of adolescents and young adults have cross-reactive antibody against emerging H3N2v, whereas children and older adults show broad susceptibility. Recent formulations of TIV do not substantially increase seroprotection. A specific vaccine would be needed if H3N2v establishes epidemic spread.

CLINICAL TRIALS REGISTRATION

NCT01140009 and NCT01368796.

Cross-lineage influenza B and heterologous influenza A antibody responses in vaccinated mice: immunologic interactions and B/Yamagata dominance

The annually reformulated trivalent inactivated influenza vaccine (TIV) includes both influenza A/subtypes (H3N2 and H1N1) but only one of two influenza B/lineages (Yamagata or Victoria). In a recent series of clinical trials to evaluate prime-boost response across influenza B/lineages, influenza-naïve infants and toddlers originally primed with two doses of 2008–09 B/Yamagata-containing TIV were assessed after two doses of B/Victoria-containing TIV administered in the subsequent 2009–10 and 2010–11 seasons. In these children, the Victoria-containing vaccines strongly recalled antibody to the initiating B/Yamagata antigen but induced only low B/Victoria antibody responses. To further evaluate this unexpected pattern of cross-lineage vaccine responses, we conducted additional immunogenicity assessment in mice. In the current study, mice were primed with two doses of 2008–09 Yamagata-containing TIV and subsequently boosted with two doses of 2010–11 Victoria-containing TIV (Group-Yam/Vic). With the same vaccines, we also assessed the reverse order of two-dose Victoria followed by two-dose Yamagata immunization (Group-Vic/Yam). The Group-Yam/Vic mice showed strong homologous responses to Yamagata antigen. However, as previously reported in children, subsequent doses of Victoria antigen substantially boosted Yamagata but induced only low antibody response to the immunizing Victoria component. The reverse order of Group-Vic/Yam mice also showed low homologous responses to Victoria but subsequent heterologous immunization with even a single dose of Yamagata antigen induced substantial boost response to both lineages. For influenza A/H3N2, homologous responses were comparably robust for the differing TIV variants and even a single follow-up dose of the heterologous strain, regardless of vaccine sequence, substantially boosted antibody to both strains. For H1N1, two doses of 2008–09 seasonal antigen significantly blunted response to two doses of the 2010–11 pandemic H1N1 antigen. Immunologic interactions between influenza viruses considered antigenically distant and in particular the cross-lineage influenza B and dominant Yamagata boost responses we have observed in both human and animal studies warrant further evaluation.

A sentinel platform to evaluate influenza vaccine effectiveness and new variant circulation, Canada 2010-2011 season

BACKGROUND

During the 2010-2011 winter, a large number of outbreaks due to influenza A/H3N2 at long-term care facilities, including higher-than-expected attack rates among vaccinated staff, were reported in some regions of Canada. Interim analysis from the community-based sentinel surveillance system showed circulating H3N2 variants and suboptimal vaccine effectiveness (VE), assessed here for the entire season's data set.

METHODS

Nasal/nasopharyngeal swabs and epidemiologic details were collected from patients presenting to sentinel sites within 7 days of onset of influenza-like illness. Cases tested positive for influenza by real-time reverse-transcription polymerase chain reaction; controls tested negative. Odds ratios for medically attended, laboratory-confirmed influenza in vaccinated vs nonvaccinated participants were used to derive adjusted VE. Viruses were characterized by hemagglutination inhibition (HI), and the hemagglutinin genes of a subset were sequenced to explore vaccine relatedness.

RESULTS

Final 2010-2011 VE analysis included 1718 participants (half aged 20-49 years), 93 with A(H1N1)pdm09, 408 with A/H3N2, and 199 with influenza B. Among adults aged 20-49 years, adjusted VE was 65% (95% confidence interval [CI], 8%-87%) for A(H1N1)pdm09 and 66% (95% CI, 10%-87%) for influenza B. Vaccine effectiveness was substantially lower for A/H3N2, at 39% (95% CI, 0%-63%). Phylogenetic analysis identified 2 circulating H3N2 variant clades, A/HongKong/2121/2010 (87%) and A/Victoria/208/2009 (11%), bearing multiple amino acid substitutions at antigenic sites (12 and 8, respectively) compared with the H3N2 vaccine component used in Canada (A/Victoria/210/2009[NYMC X-187]). However, HI characterized all H3N2 isolates as well matched to the vaccine.

CONCLUSIONS

Public health observations of increased facility H3N2 outbreaks were consistent with the sentinel network's detection of genetic variants and suboptimal VE but not with conventional HI characterization. We highlight the utility of a multicomponent sentinel surveillance platform that incorporates genotypic, phenotypic, and epidemiologic indicators into the assessment of influenza virus, new variant circulation, vaccine relatedness, and VE.

Estimates of influenza vaccine effectiveness for 2007-2008 from Canada's sentinel surveillance system: cross-protection against major and minor variants

OBJECTIVES

To estimate influenza vaccine effectiveness (VE) for the 2007-2008 season and assess the sentinel surveillance system in Canada for monitoring virus evolution and impact on VE.

METHODS

Nasal/nasopharyngeal swabs and epidemiologic details were collected from patients presenting to a sentinel physician within 7 days of influenza-like illness onset. Cases tested positive for influenza A/B virus by real-time polymerase chain reaction; controls tested negative. Hemagglutination inhibition (HI) and gene sequencing explored virus relatedness to vaccine. VE was calculated as 1 minus the odds ratio for influenza in vaccinated versus nonvaccinated participants, with adjustment for confounders.

RESULTS

Of 1425 participants, 21% were vaccinated. Influenza virus was detected in 689 (48%), of which isolates from 663 were typed/subtyped: 189 (29%) were A/H1, 210 (32%) were A/H3, and 264 (40%) were B. Of A/H1N1 isolates, 6% showed minor HI antigenic mismatch to vaccine, with greater variation based on genetic identity. All A/H3N2 isolates showed moderate antigenic mismatch, and 98% of influenza B virus isolates showed major lineage-level mismatch to vaccine. Adjusted VE for A/H1N1, A/H3N2, and B components was 69% (95% confidence interval [CI], 44%-83%), 57% (95% CI, 32%-73%), and 55% (95% CI, 32%-70%), respectively, with an overall VE of 60% (95% CI, 45%-71%).

CONCLUSIONS

Detailed antigenic and genotypic analysis of influenza viruses was consistent with epidemiologic estimates of VE showing cross-protection. A routine sentinel surveillance system that combines detailed virus and VE monitoring annually, as modeled in Canada, may guide improved vaccine selection and protection.

Cross-reactive antibody to swine influenza A(H3N2) subtype virus in children and adults before and after immunisation with 2010/11 trivalent inactivated influenza vaccine in Canada, August to November 2010

In pre- and post-immunisation sera from children (17-120 months-old) and adults (20-59 years-old) immunised with 2010/11 trivalent inactivated influenza vaccine, we assessed age-related patterns of sero-susceptibility and vaccine-induced cross-reactive antibodies to a representative swine H3N2 (swH3N2) and a related ancestral human H3N2 (A/Sydney/5/1997) influenza virus. Few children but a greater proportion of adults showed pre-immunisation haemagglutination inhibition titres ≥40 to either virus. Titres increased with age among children but decreased in adults. Fewer than 20% showed a four-fold rise in antibody titres to either virus following immunisation. Further investigation is warranted to guide ongoing risk assessment and response to emerging swine H3N2 viruses.

Whole-genome sequencing and social-network analysis of a tuberculosis outbreak

BACKGROUND

An outbreak of tuberculosis occurred over a 3-year period in a medium-size community in British Columbia, Canada. The results of mycobacterial interspersed repetitive unit-variable-number tandem-repeat (MIRU-VNTR) genotyping suggested the outbreak was clonal. Traditional contact tracing did not identify a source. We used whole-genome sequencing and social-network analysis in an effort to describe the outbreak dynamics at a higher resolution.

METHODS

We sequenced the complete genomes of 32 Mycobacterium tuberculosis outbreak isolates and 4 historical isolates (from the same region but sampled before the outbreak) with matching genotypes, using short-read sequencing. Epidemiologic and genomic data were overlaid on a social network constructed by means of interviews with patients to determine the origins and transmission dynamics of the outbreak.

RESULTS

Whole-genome data revealed two genetically distinct lineages of M. tuberculosis with identical MIRU-VNTR genotypes, suggesting two concomitant outbreaks. Integration of social-network and phylogenetic analyses revealed several transmission events, including those involving "superspreaders." Both lineages descended from a common ancestor and had been detected in the community before the outbreak, suggesting a social, rather than genetic, trigger. Further epidemiologic investigation revealed that the onset of the outbreak coincided with a recorded increase in crack cocaine use in the community.

CONCLUSIONS

Through integration of large-scale bacterial whole-genome sequencing and social-network analysis, we show that a socioenvironmental factor--most likely increased crack cocaine use--triggered the simultaneous expansion of two extant lineages of M. tuberculosis that was sustained by key members of a high-risk social network. Genotyping and contact tracing alone did not capture the true dynamics of the outbreak. (Funded by Genome British Columbia and others.).

Systems-level comparison of host responses induced by pandemic and seasonal influenza A H1N1 viruses in primary human type I-like alveolar epithelial cells in vitro

BACKGROUND

Pandemic influenza H1N1 (pdmH1N1) virus causes mild disease in humans but occasionally leads to severe complications and even death, especially in those who are pregnant or have underlying disease. Cytokine responses induced by pdmH1N1 viruses in vitro are comparable to other seasonal influenza viruses suggesting the cytokine dysregulation as seen in H5N1 infection is not a feature of the pdmH1N1 virus. However a comprehensive gene expression profile of pdmH1N1 in relevant primary human cells in vitro has not been reported. Type I alveolar epithelial cells are a key target cell in pdmH1N1 pneumonia.

METHODS

We carried out a comprehensive gene expression profiling using the Affymetrix microarray platform to compare the transcriptomes of primary human alveolar type I-like alveolar epithelial cells infected with pdmH1N1 or seasonal H1N1 virus.

RESULTS

Overall, we found that most of the genes that induced by the pdmH1N1 were similarly regulated in response to seasonal H1N1 infection with respect to both trend and extent of gene expression. These commonly responsive genes were largely related to the interferon (IFN) response. Expression of the type III IFN IL29 was more prominent than the type I IFN IFNβ and a similar pattern of expression of both IFN genes was seen in pdmH1N1 and seasonal H1N1 infection. Genes that were significantly down-regulated in response to seasonal H1N1 but not in response to pdmH1N1 included the zinc finger proteins and small nucleolar RNAs. Gene Ontology (GO) and pathway over-representation analysis suggested that these genes were associated with DNA binding and transcription/translation related functions.

CONCLUSIONS

Both seasonal H1N1 and pdmH1N1 trigger similar host responses including IFN-based antiviral responses and cytokine responses. Unlike the avian H5N1 virus, pdmH1N1 virus does not have an intrinsic capacity for cytokine dysregulation. The differences between pdmH1N1 and seasonal H1N1 viruses lay in the ability of seasonal H1N1 virus to down regulate zinc finger proteins and small nucleolar RNAs, which are possible viral transcriptional suppressors and eukaryotic translation initiation factors respectively. These differences may be biologically relevant and may represent better adaptation of seasonal H1N1 influenza virus to the host.

Association between the 2008-09 seasonal influenza vaccine and pandemic H1N1 illness during Spring-Summer 2009: four observational studies from Canada

BACKGROUND

In late spring 2009, concern was raised in Canada that prior vaccination with the 2008-09 trivalent inactivated influenza vaccine (TIV) was associated with increased risk of pandemic influenza A (H1N1) (pH1N1) illness. Several epidemiologic investigations were conducted through the summer to assess this putative association.

STUDIES INCLUDED

(1) test-negative case-control design based on Canada's sentinel vaccine effectiveness monitoring system in British Columbia, Alberta, Ontario, and Quebec; (2) conventional case-control design using population controls in Quebec; (3) test-negative case-control design in Ontario; and (4) prospective household transmission (cohort) study in Quebec. Logistic regression was used to estimate odds ratios for TIV effect on community- or hospital-based laboratory-confirmed seasonal or pH1N1 influenza cases compared to controls with restriction, stratification, and adjustment for covariates including combinations of age, sex, comorbidity, timeliness of medical visit, prior physician visits, and/or health care worker (HCW) status. For the prospective study risk ratios were computed. Based on the sentinel study of 672 cases and 857 controls, 2008-09 TIV was associated with statistically significant protection against seasonal influenza (odds ratio 0.44, 95% CI 0.33-0.59). In contrast, estimates from the sentinel and three other observational studies, involving a total of 1,226 laboratory-confirmed pH1N1 cases and 1,505 controls, indicated that prior receipt of 2008-09 TIV was associated with increased risk of medically attended pH1N1 illness during the spring-summer 2009, with estimated risk or odds ratios ranging from 1.4 to 2.5. Risk of pH1N1 hospitalization was not further increased among vaccinated people when comparing hospitalized to community cases.

CONCLUSIONS

Prior receipt of 2008-09 TIV was associated with increased risk of medically attended pH1N1 illness during the spring-summer 2009 in Canada. The occurrence of bias (selection, information) or confounding cannot be ruled out. Further experimental and epidemiological assessment is warranted. Possible biological mechanisms and immunoepidemiologic implications are considered.

Robust TLR4-induced gene expression patterns are not an accurate indicator of human immunity

BACKGROUND

Activation of Toll-like receptors (TLRs) is widely accepted as an essential event for defence against infection. Many TLRs utilize a common signalling pathway that relies on activation of the kinase IRAK4 and the transcription factor NFkappaB for the rapid expression of immunity genes.

METHODS

21 K DNA microarray technology was used to evaluate LPS-induced (TLR4) gene responses in blood monocytes from a child with an IRAK4-deficiency. In vitro responsiveness to LPS was confirmed by real-time PCR and ELISA and compared to the clinical predisposition of the child and IRAK4-deficient mice to Gram negative infection.

RESULTS

We demonstrated that the vast majority of LPS-responsive genes in IRAK4-deficient monocytes were greatly suppressed, an observation that is consistent with the described role for IRAK4 as an essential component of TLR4 signalling. The severely impaired response to LPS, however, is inconsistent with a remarkably low incidence of Gram negative infections observed in this child and other children with IRAK4-deficiency. This unpredicted clinical phenotype was validated by demonstrating that IRAK4-deficient mice had a similar resistance to infection with Gram negative S. typhimurium as wildtype mice. A number of immunity genes, such as chemokines, were expressed at normal levels in human IRAK4-deficient monocytes, indicating that particular IRAK4-independent elements within the repertoire of TLR4-induced responses are expressed.

CONCLUSIONS

Sufficient defence to Gram negative immunity does not require IRAK4 or a robust, 'classic' inflammatory and immune response.

Systems-level comparison of host-responses elicited by avian H5N1 and seasonal H1N1 influenza viruses in primary human macrophages

Human disease caused by highly pathogenic avian influenza (HPAI) H5N1 can lead to a rapidly progressive viral pneumonia leading to acute respiratory distress syndrome. There is increasing evidence from clinical, animal models and in vitro data, which suggests a role for virus-induced cytokine dysregulation in contributing to the pathogenesis of human H5N1 disease. The key target cells for the virus in the lung are the alveolar epithelium and alveolar macrophages, and we have shown that, compared to seasonal human influenza viruses, equivalent infecting doses of H5N1 viruses markedly up-regulate pro-inflammatory cytokines in both primary cell types in vitro. Whether this H5N1-induced dysregulation of host responses is driven by qualitative (i.e activation of unique host pathways in response to H5N1) or quantitative differences between seasonal influenza viruses is unclear. Here we used microarrays to analyze and compare the gene expression profiles in primary human macrophages at 1, 3, and 6 h after infection with H5N1 virus or low-pathogenic seasonal influenza A (H1N1) virus. We found that host responses to both viruses are qualitatively similar with the activation of nearly identical biological processes and pathways. However, in comparison to seasonal H1N1 virus, H5N1 infection elicits a quantitatively stronger host inflammatory response including type I interferon (IFN) and tumor necrosis factor (TNF)-α genes. A network-based analysis suggests that the synergy between IFN-β and TNF-α results in an enhanced and sustained IFN and pro-inflammatory cytokine response at the early stage of viral infection that may contribute to the viral pathogenesis and this is of relevance to the design of novel therapeutic strategies for H5N1 induced respiratory disease.

Enabling a systems biology approach to immunology: focus on innate immunity

Immunity is not simply the product of a series of discrete linear signalling pathways; rather it is comprised of a complex set of integrated responses arising from a dynamic network of thousands of molecules subject to multiple influences. Its behaviour often cannot be explained or predicted solely by examining its components. Here, we review recently developed resources for the systems-level investigation of immunity. Although innate immunity is emphasized here, its considerable overlap with adaptive immunity makes many of these resources relevant to both arms of the immune response. We discuss recent studies implementing these approaches and illustrate the potential of systems biology to generate novel insights into the complexities of innate immunity.

InnateDB: facilitating systems-level analyses of the mammalian innate immune response

Although considerable progress has been made in dissecting the signaling pathways involved in the innate immune response, it is now apparent that this response can no longer be productively thought of in terms of simple linear pathways. InnateDB (www.innatedb.ca) has been developed to facilitate systems-level analyses that will provide better insight into the complex networks of pathways and interactions that govern the innate immune response. InnateDB is a publicly available, manually curated, integrative biology database of the human and mouse molecules, experimentally verified interactions and pathways involved in innate immunity, along with centralized annotation on the broader human and mouse interactomes. To date, more than 3500 innate immunity-relevant interactions have been contextually annotated through the review of 1000 plus publications. Integrated into InnateDB are novel bioinformatics resources, including network visualization software, pathway analysis, orthologous interaction network construction and the ability to overlay user-supplied gene expression data in an intuitively displayed molecular interaction network and pathway context, which will enable biologists without a computational background to explore their data in a more systems-oriented manner.

Computer-aided biotechnology: from immuno-informatics to reverse vaccinology

Genome sequences from many organisms, including humans, have been completed, and high-throughput analyses have produced burgeoning volumes of 'omics' data. Bioinformatics is crucial for the management and analysis of such data and is increasingly used to accelerate progress in a wide variety of large-scale and object-specific functional analyses. Refined algorithms enable biotechnologists to follow 'computer-aided strategies' based on experiments driven by high-confidence predictions. In order to address compound problems, current efforts in immuno-informatics and reverse vaccinology are aimed at developing and tuning integrative approaches and user-friendly, automated bioinformatics environments. This will herald a move to 'computer-aided biotechnology': smart projects in which time-consuming and expensive large-scale experimental approaches are progressively replaced by prediction-driven investigations.

Complexities of targeting innate immunity to treat infection

Innate immunity is an ancient form of host defence that is activated rapidly to enable, through a multiplicity of effector mechanisms, defence against a broad spectrum of microbial threats. From this perspective, innate immunity has desirable characteristics of a therapy against infections, and, as a consequence, the innate immune system has become a major target for the development of therapeutics to control inflammation and immune defences. Although advances in the field have come at a furious pace, and several companies are advancing the first Toll-like receptor-based drugs, there remain many unanswered questions about innate immunity and maintaining balance in the immune response. Indeed, innate immunity represents an enormously complex network of molecules, pathways and interactions, controlled by multiple positive and negative regulatory proteins, which are starting to be evaluated in more depth using systems biology approaches. However, accompanying the protective mechanisms is the production of pro-inflammatory cytokines such that, if excessive amplification of innate immunity occurs, there is the potential for such syndromes as sepsis and chronic inflammation.