Genomics and outbreak investigation: from sequence to consequence

PHA4GE quality control contextual data tags: standardized annotations for sharing public health sequence datasets with known quality issues to facilitate testing and training

As public health laboratories expand their genomic sequencing and bioinformatics capacity for the surveillance of different pathogens, labs must carry out robust validation, training, and optimization of wet- and dry-lab procedures. Achieving these goals for algorithms, pipelines and instruments often requires that lower quality datasets be made available for analysis and comparison alongside those of higher quality. This range of data quality in reference sets can complicate the sharing of sub-optimal datasets that are vital for the community and for the reproducibility of assays. Sharing of useful, but sub-optimal datasets requires careful annotation and documentation of known issues to enable appropriate interpretation, avoid being mistaken for better quality information, and for these data (and their derivatives) to be easily identifiable in repositories. Unfortunately, there are currently no standardized attributes or mechanisms for tagging poor-quality datasets, or datasets generated for a specific purpose, to maximize their utility, searchability, accessibility and reuse. The Public Health Alliance for Genomic Epidemiology (PHA4GE) is an international community of scientists from public health, industry and academia focused on improving the reproducibility, interoperability, portability, and openness of public health bioinformatic software, skills, tools and data. To address the challenges of sharing lower quality datasets, PHA4GE has developed a set of standardized contextual data tags, namely fields and terms, that can be included in public repository submissions as a means of flagging pathogen sequence data with known quality issues, increasing their discoverability. The contextual data tags were developed through consultations with the community including input from the International Nucleotide Sequence Data Collaboration (INSDC), and have been standardized using ontologies - community-based resources for defining the tag properties and the relationships between them. The standardized tags are agnostic to the organism and the sequencing technique used and thus can be applied to data generated from any pathogen using an array of sequencing techniques. The tags can also be applied to synthetic (lab created) data. The list of standardized tags is maintained by PHA4GE and can be found at https://github.com/pha4ge/contextual_data_QC_tags. Definitions, ontology IDs, examples of use, as well as a JSON representation, are provided. The PHA4GE QC tags were tested, and are now implemented, by the FDA's GenomeTrakr laboratory network as part of its routine submission process for SARS-CoV-2 wastewater surveillance. We hope that these simple, standardized tags will help improve communication regarding quality control in public repositories, in addition to making datasets of variable quality more easily identifiable. Suggestions for additional tags can be submitted to PHA4GE via the New Term Request Form in the GitHub repository. By providing a mechanism for feedback and suggestions, we also expect that the tags will evolve with the needs of the community.

Pulsed-Field Gel Electrophoresis Analysis of Bovine Associated Staphylococcus aureus: A Review

For decades now, DNA fingerprinting by means of pulsed-field gel electrophoresis (PFGE) continues to be the most widely used to separate large DNA molecules and distinguish between different strains in alternating pulses. This is done by isolating intact chromosomal DNA and using restriction enzymes with specific restriction sites to generate less than 30 restriction fragments from 50 Kb to 10 Mbp. These results make clone-specific band profiles easy to compare. Specialized equipment is required for the optimization of DNA separation and resolution, among which a contour-clamped homogeneous electric field (CHEF) apparatus is the most commonly used. As a result, the PFGE analysis of a bacterial genome provides useful information in terms of epidemiological investigations of different bacterial pathogens. For Staphylococcus aureus subtyping, despite its limitations and the emergence of alternative methods, PFGE analysis has proven to be an adequate choice and the gold standard for determining genetic relatedness, especially in outbreak detection and short-term surveillance in the veterinary field.

Whole-Genome Sequencing of Shiga Toxin-Producing Escherichia coli for Characterization and Outbreak Investigation

Shiga toxin-producing Escherichia coli (STEC) causes high frequencies of foodborne infections worldwide and has been linked to numerous outbreaks each year. Pulsed-field gel electrophoresis (PFGE) has been the gold standard for surveillance until the recent transition to whole-genome sequencing (WGS). To further understand the genetic diversity and relatedness of outbreak isolates, a retrospective analysis of 510 clinical STEC isolates was conducted. Among the 34 STEC serogroups represented, most (59.6%) belonged to the predominant six non-O157 serogroups. Core genome single nucleotide polymorphism (SNP) analysis differentiated clusters of isolates with similar PFGE patterns and multilocus sequence types (STs). One serogroup O26 outbreak strain and another non-typeable (NT) strain, for instance, were identical by PFGE and clustered together by MLST; however, both were distantly related in the SNP analysis. In contrast, six outbreak-associated serogroup O5 strains clustered with five ST-175 serogroup O5 isolates, which were not part of the same outbreak as determined by PFGE. The use of high-quality SNP analyses enhanced the discrimination of these O5 outbreak strains into a single cluster. In all, this study demonstrates how public health laboratories can more rapidly use WGS and phylogenetics to identify related strains during outbreak investigations while simultaneously uncovering important genetic attributes that can inform treatment practices.

Histopathologic and Immunohistochemical Assessment of Acute Respiratory Distress Syndrome (ARDS): Challenges and Complexities of Postmortem Diagnosis

Acute respiratory distress syndrome (ARDS) is a life-threatening condition due to acute lung injury (ALI), characterized by rapid-onset respiratory failure, leading to the clinical manifestations of poor lung compliance, severe hypoxemia, and dyspnea. ARDS/ALI has many causes, most commonly related to infections (sepsis, pneumonia), traumas, and multiple transfusions. The objective of this study is to assess the performance of postmortem anatomopathological examination in identifying etiological agents associated with ARDS or ALI in deceased patients from the State of São Paulo from 2017 to 2018. A retrospective cross-sectional study was performed based on the final outcome obtained by histopathology, histochemical, and immunohistochemical examination for ARDS/ALI differential diagnosis at the Pathology Center of the Adolfo Lutz Institute in São Paulo, Brazil. Of the 154 patients clinically diagnosed with ARDS or ALI, 57% tested positive for infectious agents, and the most frequent outcome was influenza A/H1N1 virus infection. In 43% of cases, no etiologic agent was identified. The opportunity to establish a diagnosis, identify particular infections, confirm a microbiological diagnosis, and uncover unanticipated etiologies is provided by postmortem pathologic analysis of ARDS. A molecular assessment could improve the diagnosis accuracy and lead to research into host responses and public health measures.

Targeted Whole Genome Sequencing (TWG-Seq) of Cucumber Green Mottle Mosaic Virus Using Tiled Amplicon Multiplex PCR and Nanopore Sequencing

Rapid and reliable detection tools are essential for disease surveillance and outbreak management, and genomic data is essential to determining pathogen origin and monitoring of transmission pathways. Low virus copy number and poor RNA quality can present challenges for genomic sequencing of plant viruses, but this can be overcome by enrichment of target nucleic acid. A targeted whole genome sequencing (TWG-Seq) approach for the detection of cucumber green mottle mosaic virus (CGMMV) has been developed where overlapping amplicons generated using two multiplex RT-PCR assays are then sequenced using the Oxford Nanopore MinION. Near complete coding region sequences were assembled with ≥100× coverage for infected leaf tissue dilution samples with RT-qPCR cycle quantification (Cq) values from 11.8 to 38 and in seed dilution samples with Cq values 13.8 to 27. Consensus sequences assembled using this approach showed greater than 99% nucleotide similarity when compared to genomes produced using metagenomic sequencing. CGMMV could be confidently detected in historical seed isolates with degraded RNA. Whilst limited access to, and costs associated with second-generation sequencing platforms can influence diagnostic outputs, the portable Nanopore technology offers an affordable high throughput sequencing alternative when combined with TWG-Seq for low copy or degraded samples.

Exploiting genomics to mitigate the public health impact of antimicrobial resistance

Antimicrobial resistance (AMR) is a major global public health threat, which has been largely driven by the excessive use of antimicrobials. Control measures are urgently needed to slow the trajectory of AMR but are hampered by an incomplete understanding of the interplay between pathogens, AMR encoding genes, and mobile genetic elements at a microbial level. These factors, combined with the human, animal, and environmental interactions that underlie AMR dissemination at a population level, make for a highly complex landscape. Whole-genome sequencing (WGS) and, more recently, metagenomic analyses have greatly enhanced our understanding of these processes, and these approaches are informing mitigation strategies for how we better understand and control AMR. This review explores how WGS techniques have advanced global, national, and local AMR surveillance, and how this improved understanding is being applied to inform solutions, such as novel diagnostic methods that allow antimicrobial use to be optimised and vaccination strategies for better controlling AMR. We highlight some future opportunities for AMR control informed by genomic sequencing, along with the remaining challenges that must be overcome to fully realise the potential of WGS approaches for international AMR control.

A high-throughput multiplexing and selection strategy to complete bacterial genomes

BACKGROUND

Bacterial whole-genome sequencing based on short-read technologies often results in a draft assembly formed by contiguous sequences. The introduction of long-read sequencing technologies permits those contiguous sequences to be unambiguously bridged into complete genomes. However, the elevated costs associated with long-read sequencing frequently limit the number of bacterial isolates that can be long-read sequenced. Here we evaluated the recently released 96 barcoding kit from Oxford Nanopore Technologies (ONT) to generate complete genomes on a high-throughput basis. In addition, we propose an isolate selection strategy that optimizes a representative selection of isolates for long-read sequencing considering as input large-scale bacterial collections.

RESULTS

Despite an uneven distribution of long reads per barcode, near-complete chromosomal sequences (assembly contiguity = 0.89) were generated for 96 Escherichia coli isolates with associated short-read sequencing data. The assembly contiguity of the plasmid replicons was even higher (0.98), which indicated the suitability of the multiplexing strategy for studies focused on resolving plasmid sequences. We benchmarked hybrid and ONT-only assemblies and showed that the combination of ONT sequencing data with short-read sequencing data is still highly desirable (i) to perform an unbiased selection of isolates for long-read sequencing, (ii) to achieve an optimal genome accuracy and completeness, and (iii) to include small plasmids underrepresented in the ONT library.

CONCLUSIONS

The proposed long-read isolate selection ensures the completion of bacterial genomes that span the genome diversity inherent in large collections of bacterial isolates. We show the potential of using this multiplexing approach to close bacterial genomes on a high-throughput basis.

Resistance mechanisms and genetic relatedness among carbapenem-resistant Pseudomonas aeruginosa isolates from three major hospitals in Hanoi, Vietnam (2011-15)

Background

MDR bacteria including carbapenem-resistant Pseudomonas aeruginosa are recognized as an important cause of hospital-acquired infections worldwide. This investigation seeks to determine the molecular characterization and antibiotic resistance genes associated with carbapenem-resistant P. aeruginosa.

Methods

We conducted WGS and phylogenetic analysis of 72 carbapenem-resistant P. aeruginosa isolated from hospital-acquired infection patients from August 2011 to March 2015 in three major hospitals in Hanoi, Vietnam.

Results

We identified three variants of IMP gene, among which bla_IMP-15 was the most frequent (n = 34) in comparison to bla_IMP-26 (n = 2) and bla_IMP-51 (n = 12). We observed two isolates with imipenem MIC >128 mg/L that co-harboured bla_IMP-15 and bla_DIM-1 genes and seven isolates (imipenem MIC > 128 mg/L) with a bla_KPC-1 gene from the same hospital. MLST data shows that these 72 isolates belong to 18 STs and phylogenetic tree analysis has divided these isolates into nine groups.

Conclusions

Our results provide evidence that not only bla_IMP-26 but other IMP variants such as bla_IMP-15 and bla_IMP-51 genes and several STs (ST235, ST244, ST277, ST310, ST773 and ST3151) have been disseminating in healthcare settings in Vietnam. In addition, we report the emergence of two isolates belonging to ST1240 and ST3340 that harboured two important carbapenemase genes (bla_IMP-15 and bla_DIM-1) and seven isolates belonging to ST3151 of P. aeruginosa that carried the bla_KPC-1 gene in Vietnam, which could potentially cause serious restricted availability of treatment options in healthcare settings.

Surveillance of hemorrhagic fever and/or neuroinvasive disease: challenges of diagnosis

OBJECTIVE

To evaluate the performance of post mortem laboratory analysis in identifying the causes of hemorrhagic fever and/or neuroinvasive disease in deaths by arbovirus infection.

METHODS

Retrospective cross-sectional study based on the differential analysis and final outcome obtained in patients whose samples underwent laboratory testing for arboviruses at the Pathology Center of the Adolfo Lutz Institute, in São Paulo, Brazil.

RESULTS

Of the 1355 adults clinically diagnosed with hemorrhagic fever and/or neuroinvasive disease, the most commonly attributed cause of death and the most common final outcome was dengue fever. Almost half of the samples tested negative on all laboratory tests conducted.

CONCLUSION

The failure to identify the causative agent in a great number of cases highlights a gap in the diagnosis of deaths of unknown etiology. Additional immunohistochemical and molecular assessments need to be added to the post-mortem protocol if all laboratory evaluations performed fail to identify a causative agent. While part of our findings may be due to technical issues related to sample fixation, better information availability when making the initial diagnosis is crucial. Including molecular approaches might lead to a significant advancement in diagnostic accuracy.

Development and Application of a Fast Method to Acquire the Accurate Whole-Genome Sequences of Human Adenoviruses

The whole-genome sequencing (WGS) of human adenoviruses (HAdVs) plays an important role in identifying, typing, and mutation analysis of HAdVs. Nowadays, three generations of sequencing have been developed. The accuracy of first-generation sequencing is up to 99.99%, whereas this technology relies on PCR and is time consuming; the next-generation sequencing (NGS) is expensive and not cost effective for determining a few special samples; and the third-generation sequencing technology has a higher error rate. In this study, first, we developed an efficient HAdV genomic DNA extraction method. Using the complete genomic DNA instead of the PCR amplicons as the direct sequencing template and a set of walking primers, we developed the HAdV WGS method based on first-generation sequencing. The HAdV whole genomes were effectively sequenced by a set of one-way sequencing primers designed, which reduced the sequencing time and cost. More importantly, high sequence accuracy is guaranteed. Four HAdV strains (GZ01, GZ02, HK35, and HK91) were isolated from children with acute respiratory diseases (ARDs), and the complete genomes were sequenced using this method. The accurate sequences of the whole inverted terminal repeats (ITRs) at both ends of the HAdV genomes were also acquired. The genome sequence of human adenovirus type 14 (HAdV-B14) strain GZ01 acquired by this method is identical to the sequence released in GenBank, which indicates that this novel sequencing method has high accuracy. The comparative genomic analysis identified that strain GZ02 isolated in September 2010 had the identical genomic sequence with the HAdV-B14 strain GZ01 (October 2010). Therefore, strain GZ02 is the first HAdV-B14 isolate emergent in China (September 2010; GenBank acc no. MW692349). The WGS of HAdV-C2 strain HK91 and HAdV-E4 strain HK35 isolated from children with acute respiratory disease in Hong Kong were also determined by this sequencing method. In conclusion, this WGS method is fast, accurate, and universal for common human adenovirus species B, C, and E. The sequencing strategy may also be applied to the WGS of the other DNA viruses.

Extensive Hospital In-Ward Clustering Revealed By Molecular Characterization of Influenza A Virus Infection

BACKGROUND

Nosocomial transmission of influenza A virus (InfA) infection is not fully recognized. The aim of this study was to describe the characteristics of hospitalized patients with InfA infections during an entire season and to investigate in-ward transmission at a large, acute-care hospital.

METHODS

During the 2016-17 season, all hospitalized patients ≥18 years old with laboratory-verified (real-time polymerase chain reaction) InfA were identified. Cases were characterized according to age; sex; comorbidity; antiviral therapy; viral load, expressed as cycle threshold values; length of hospital stay; 30-day mortality; and whether the InfA infection met criteria for a health care-associated influenza A infection (HCAI). Respiratory samples positive for InfA that were collected at the same wards within 7 days were chosen for whole-genome sequencing (WGS) and a phylogenetic analysis was performed to detect clustering. For reference, concurrent InfA strains from patients with community-acquired infection were included.

RESULTS

We identified a total of 435 InfA cases, of which 114 (26%) met the HCAI criteria. The overall 30-day mortality rate was higher among patients with HCAI (9.6% vs 4.6% among non-HCAI patients), although the difference was not statistically significant in a multivariable analysis, where age was the only independent risk factor for death (P < .05). We identified 8 closely related clusters (involving ≥3 cases) and another 10 pairs of strains, supporting in-ward transmission.

CONCLUSIONS

We found that the in-ward transmission of InfA occurs frequently and that HCAI may have severe outcomes. WGS may be used for outbreak investigations, as well as for evaluations of the effects of preventive measures.

Evaluation of a Combined Multilocus Sequence Typing and Whole-Genome Sequencing Two-Step Algorithm for Routine Typing of Clostridioides difficile

Multilocus sequence typing (MLST) is a low-resolution but rapid genotyping method for Clostridioides difficile Whole-genome sequencing (WGS) has emerged as the new gold standard for C. difficile typing, but cost and lack of standardization still limit broad utilization. In this study, we evaluated the potential to combine the portability of MLST with the increased resolution of WGS for a cost-saving approach to routine C. difficile typing. C. difficile strains from two New York City hospitals (hospital A and hospital B) were selected. WGS single-nucleotide polymorphism (wgSNP) was performed using established methods. Sequence types (ST) were determined using PubMLST, while wgSNP analysis was performed using the Bionumerics software. An additional analysis of a subset of data (hospital A) was made comparing the Bionumerics software to the CosmosID pipeline. Cost and turnaround time to results were compared for the algorithmic approach of MLST followed by wgSNP versus direct wgSNP. Among the 202 C. difficile isolates typed, 91% (n = 185/203) clustered within the representative ST, showing a high agreement between MLST and wgSNP. While clustering was similar between the Bionumerics and CosmosID pipelines, large differences in the overall number of SNPs were noted. A two-step algorithm for routine typing results in significantly lower cost than routine use of WGS. Our results suggest that using MLST as a first step in routine typing of C. difficile followed by WGS for MLST concordant strains is a less technically demanding, cost-saving approach for performing C. difficile typing than WGS alone without loss of discriminatory power.

Potential role of viral metagenomics as a surveillance tool for the early detection of emerging novel pathogens

Since the early times, human beings have always been faced with deadly microbial infections, both bacterial and viral. Pathogens such as viruses are always evolving owing to the processes of antigenic shift and drift. Such viral evolution results in the emergence of new types and serovars that prove deadly for humans-like influenza pandemics, severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). The pandemic of novel coronavirus SARS-CoV-2 is the recent example. It has resulted in a great loss of human lives and a serious burden on economy across the globe. To counter such situations, a system should exist for the early detection of emerging viral pathogens. This will help prevent possible outbreaks and save human lives. Most of such deadly novel viruses and viral outbreaks are known to be originated from animal hosts. Regular monitoring of potential hot spots of such emerging microbes, such as zoos and animal markets, through metagenomics could help assess the presence of new viruses and pathogens. In this review, we focus on the potential of viral metagenomics and propose a surveillance system based on it for the early detection and hence prevention of such emerging viral infections.

Genetic grouping of SARS-CoV-2 coronavirus sequences using informative subtype markers for pandemic spread visualization

We propose an efficient framework for genetic subtyping of SARS-CoV-2, the novel coronavirus that causes the COVID-19 pandemic. Efficient viral subtyping enables visualization and modeling of the geographic distribution and temporal dynamics of disease spread. Subtyping thereby advances the development of effective containment strategies and, potentially, therapeutic and vaccine strategies. However, identifying viral subtypes in real-time is challenging: SARS-CoV-2 is a novel virus, and the pandemic is rapidly expanding. Viral subtypes may be difficult to detect due to rapid evolution; founder effects are more significant than selection pressure; and the clustering threshold for subtyping is not standardized. We propose to identify mutational signatures of available SARS-CoV-2 sequences using a population-based approach: an entropy measure followed by frequency analysis. These signatures, Informative Subtype Markers (ISMs), define a compact set of nucleotide sites that characterize the most variable (and thus most informative) positions in the viral genomes sequenced from different individuals. Through ISM compression, we find that certain distant nucleotide variants covary, including non-coding and ORF1ab sites covarying with the D614G spike protein mutation which has become increasingly prevalent as the pandemic has spread. ISMs are also useful for downstream analyses, such as spatiotemporal visualization of viral dynamics. By analyzing sequence data available in the GISAID database, we validate the utility of ISM-based subtyping by comparing spatiotemporal analyses using ISMs to epidemiological studies of viral transmission in Asia, Europe, and the United States. In addition, we show the relationship of ISMs to phylogenetic reconstructions of SARS-CoV-2 evolution, and therefore, ISMs can play an important complementary role to phylogenetic tree-based analysis, such as is done in the Nextstrain project. The developed pipeline dynamically generates ISMs for newly added SARS-CoV-2 sequences and updates the visualization of pandemic spatiotemporal dynamics, and is available on Github at https://github.com/EESI/ISM (Jupyter notebook), https://github.com/EESI/ncov_ism (command line tool) and via an interactive website at https://covid19-ism.coe.drexel.edu/.

Outbreak analytics: a developing data science for informing the response to emerging pathogens

Despite continued efforts to improve health systems worldwide, emerging pathogen epidemics remain a major public health concern. Effective response to such outbreaks relies on timely intervention, ideally informed by all available sources of data. The collection, visualization and analysis of outbreak data are becoming increasingly complex, owing to the diversity in types of data, questions and available methods to address them. Recent advances have led to the rise of outbreak analytics, an emerging data science focused on the technological and methodological aspects of the outbreak data pipeline, from collection to analysis, modelling and reporting to inform outbreak response. In this article, we assess the current state of the field. After laying out the context of outbreak response, we critically review the most common analytics components, their inter-dependencies, data requirements and the type of information they can provide to inform operations in real time. We discuss some challenges and opportunities and conclude on the potential role of outbreak analytics for improving our understanding of, and response to outbreaks of emerging pathogens. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

Operational models and criteria for incorporating microbial whole genome sequencing in hospital microbiology - A systematic literature review

BACKGROUND

Microbial whole genome sequencing (WGS) has many advantages over standard microbiological methods. However, it is not yet widely implemented in routine hospital diagnostics due to notable challenges.

OBJECTIVES

The aim was to extract managerial, financial and clinical criteria supporting the decision to implement WGS in routine diagnostic microbiology, across different operational models of implementation in the hospital setting.

METHODS

This was a systematic review of literature identified through PubMed and Web of Science. English literature studies discussing the applications of microbial WGS without limitation on publication date were eligible. A narrative approach for categorization and synthesis of the sources identified was adopted.

RESULTS

A total of 98 sources were included. Four main alternative operational models for incorporating WGS in clinical microbiology laboratories were identified: full in-house sequencing and analysis, full outsourcing of sequencing and analysis and two hybrid models combining in-house/outsourcing of the sequencing and analysis components. Six main criteria (and multiple related sub-criteria) for WGS implementation emerged from our review and included cost (e.g. the availability of resources for capital and operational investment); manpower (e.g. the ability to provide training programmes or recruit trained personnel), laboratory infrastructure (e.g. the availability of supplies and consumables or sequencing platforms), bioinformatics requirements (e.g. the availability of valid analysis tools); computational infrastructure (e.g. the availability of storage space or data safety arrangements); and quality control (e.g. the existence of standardized procedures).

CONCLUSIONS

The decision to incorporate WGS in routine diagnostics involves multiple, sometimes competing, criteria and sub-criteria. Mapping these criteria systematically is an essential stage in developing policies for adoption of this technology, e.g. using a multicriteria decision tool. Future research that will prioritize criteria and sub-criteria that were identified in our review in the context of operational models will inform decision-making at clinical and managerial levels with respect to effective implementation of WGS for routine use. Beyond WGS, similar decision-making challenges are expected with respect to future integration of clinical metagenomics.

Shared genome analyses of notable listeriosis outbreaks, highlighting the critical importance of epidemiological evidence, input datasets and interpretation criteria

The persuasiveness of genomic evidence has pressured scientific agencies to supplement or replace well-established methodologies to inform public health and food safety decision-making. This study of 52 epidemiologically defined Listeria monocytogenes isolates, collected between 1981 and 2011, including nine outbreaks, was undertaken (1) to characterize their phylogenetic relationship at finished genome-level resolution, (2) to elucidate the underlying genetic diversity within an endemic subtype, CC8, and (3) to re-evaluate the genetic relationship and epidemiology of a CC8-delimited outbreak in Canada in 2008. Genomes representing Canadian Listeria outbreaks between 1981 and 2010 were closed and manually annotated. Single nucleotide variants (SNVs) and horizontally acquired traits were used to generate phylogenomic models. Phylogenomic relationships were congruent with classical subtyping and epidemiology, except for CC8 outbreaks, wherein the distribution of SNV and prophages revealed multiple co-evolving lineages. Chronophyletic reconstruction of CC8 evolution indicates that prophage-related genetic changes among CC8 strains manifest as PFGE subtype reversions, obscuring the relationship between CC8 isolates, and complicating the public health interpretation of subtyping data, even at maximum genome resolution. The size of the shared genome interrogated did not change the genetic relationship measured between highly related isolates near the tips of the phylogenetic tree, illustrating the robustness of these approaches for routine public health applications where the focus is recent ancestry. The possibility exists for temporally and epidemiologically distinct events to appear related even at maximum genome resolution, highlighting the continued importance of epidemiological evidence.

Investigation of a Carbapenemase-producing Acinetobacter baumannii outbreak using whole genome sequencing versus a standard epidemiologic investigation

Background

The standard epidemiologic investigation of outbreaks typically relies on spatiotemporal data and pulsed-field gel electrophoresis (PFGE), but whole genome sequencing (WGS) is becoming increasingly used. This investigation aimed to characterize a carbapenemase-producing Acinetobacter baumannii (CPAb) nosocomial outbreak using WGS compared to a standard outbreak investigation.

Methods

The CPAb outbreak occurred in a single center between 2012 and 2014. The standard investigation used spatiotemporal data and PFGE to generate a chain of transmission. A separate WGS investigation generated a chain of transmission based solely on WGS and date of sampling and was blinded to all other spatiotemporal data and PFGE. Core single nucleotide variant (SNV) phylogenetic analysis was performed on WGS data generated using the Illumina MiSeq platform. The chains of transmission were compared quantitatively and qualitatively to assess the concordance between both methods.

Results

28 colonized and infected cases were included. Of the 27 transmission events identified using the standard investigation, 12 (44%) were identical to the transmission events using WGS. WGS identified several transmission events that had not been detected by traditional method, and numerous transmission events that had occurred on different hospital wards than suspected by standard methods. The average number (standard deviation [SD]) of SNVs per transmission events was 1.63 (SD, 1.31) by traditional method and 0.63 (SD, 0.79) by WGS (p = 0.001) All isolates harbored the rare carbapenemase bla_OXA-237.

Conclusions

The traditional and WGS investigations had moderate concordance. When used alongside epidemiologic data and clinical information, WGS could help improve the mapping of transmission events.

Current progress and future opportunities in applications of bioinformatics for biodefense and pathogen detection: report from the Winter Mid-Atlantic Microbiome Meet-up, College Park, MD, January 10, 2018

The Mid-Atlantic Microbiome Meet-up (M3) organization brings together academic, government, and industry groups to share ideas and develop best practices for microbiome research. In January of 2018, M3 held its fourth meeting, which focused on recent advances in biodefense, specifically those relating to infectious disease, and the use of metagenomic methods for pathogen detection. Presentations highlighted the utility of next-generation sequencing technologies for identifying and tracking microbial community members across space and time. However, they also stressed the current limitations of genomic approaches for biodefense, including insufficient sensitivity to detect low-abundance pathogens and the inability to quantify viable organisms. Participants discussed ways in which the community can improve software usability and shared new computational tools for metagenomic processing, assembly, annotation, and visualization. Looking to the future, they identified the need for better bioinformatics toolkits for longitudinal analyses, improved sample processing approaches for characterizing viruses and fungi, and more consistent maintenance of database resources. Finally, they addressed the necessity of improving data standards to incentivize data sharing. Here, we summarize the presentations and discussions from the meeting, identifying the areas where microbiome analyses have improved our ability to detect and manage biological threats and infectious disease, as well as gaps of knowledge in the field that require future funding and focus.

Molecular epidemiology of cattle tuberculosis in Mexico through whole-genome sequencing and spoligotyping

Mycobacterium bovis infection in cattle persists in Mexico, posing a threat to human health. Control of bovine tuberculosis, through the National Program Against Bovine Tuberculosis, has led to the decrease of disease prevalence in most of the country, except for high dairy production regions. Genotyping of M. bovis has been performed mainly by spoligotyping and variable number tandem repeats (VNTR), but higher resolution power can be useful for a finer definition of the spread of the disease. Whole genome sequencing and spoligotyping was performed for a set of 322 M. bovis isolates from different sources in Mexico: Baja California, Coahuila, Estado de Mexico, Guanajuato, Hidalgo, Jalisco, Queretaro and Veracruz, from dairy and beef cattle, as well as humans. Twelve main genetic clades were obtained through WGS and genetic diversity analysis. A clear differentiation of the Baja California isolates was seen as they clustered together exclusively. However, isolates from the central states showed no specific clustering whatsoever. Although WGS proves to have higher resolving power than spoligotyping, and since there was concordance between WGS and spoligotyping results, we consider that the latter is still an efficient and practical method for monitoring bovine tuberculosis in developing countries, where resources for higher technology are scarce.

Combination random isothermal amplification and nanopore sequencing for rapid identification of the causative agent of an outbreak

BACKGROUND

Outbreaks of fever of unknown origin start with nonspecific symptoms and case definition is only slowly developed and adapted, therefore, identifying the causative agent is crucial to ensure suitable treatment and control measures. As an alternative method for Polymerase Chain Reaction in molecular diagnostics diagnostic, metagenomics can be applied to identify the pathogen responsible for the outbreak through sequencing all nucleic acids present in a sample extract. Sequencing data obtained can identify new or variants of known agents.

OBJECTIVES

To develop a rapid and field applicable protocol to allow the identification of the causative agent of an outbreak.

STUDY DESIGN

We explored a sequencing protocol relying on multiple displacement isothermal amplification and nanopore sequencing in order to allow the identification of the causative agent in a sample. To develop the procedure, a mock sample consisting of supernatant from Zika virus tissue culture was used.

RESULTS

The procedure took under seven hours including sample preparation and data analysis using an offline BLAST search. In total, 63,678 sequence files covering around 10,000 bases were extracted. BLAST search revealed the presence of Zika virus.

CONCLUSION

In conclusion, the protocol has potential for point of need sequencing to identify RNA viruses. The whole procedure was operated in a suitcase laboratory. However, the procedure is cooling chain dependent and the cost per sequencing run is still high.

Reverse line probe assay for cheap detection of Single Nucleotide Polymorphisms in Mycobacterium tuberculosis

More and more Single Nucleotide Polymosrphisms of interest among pathogenic organisms are described with the advent of Whole Genome Sequencing but WGS approach is still too expensive, time consuming, and relying on bioinformatical means that are not available in many developing countries. This study presents a low-cost reverse hybridization line probe technique for detecting SNPs in Mycobacterium tuberculosis. The proposed test is able to detect mutations in the RRDR of rpoB gene in M. tuberculosis with specificity and sensitivity of 98% and 100%, respectively and for an average cost of less than €3 per sample. The technique proved efficient not only on pure DNA samples extracted from culture isolates but also on crude extracts from clinical samples. The flexibility of the platform allows to get it transformed to any kind of test detection, hence, building a bridge between rich countries performing SNP discovery and countries with high burden that can target these SNPs on the collected samples.

Food-Borne Outbreak Investigation and Molecular Typing: High Diversity of Staphylococcus aureus Strains and Importance of Toxin Detection

Staphylococcus aureus is an important aetiological agent of food intoxications in the European Union as it can cause gastro-enteritis through the production of various staphylococcal enterotoxins (SEs) in foods. Reported enterotoxin dose levels causing food-borne illness are scarce and varying. Three food poisoning outbreaks due to enterotoxin-producing S. aureus strains which occurred in 2013 in Belgium are described. The outbreaks occurred in an elderly home, at a barbecue event and in a kindergarten and involved 28, 18, and six cases, respectively. Various food leftovers contained coagulase positive staphylococci (CPS). Low levels of staphylococcal enterotoxins ranging between 0.015 ng/g and 0.019 ng/g for enterotoxin A (SEA), and corresponding to 0.132 ng/g for SEC were quantified in the food leftovers for two of the reported outbreaks. Molecular typing of human and food isolates using pulsed-field gel electrophoresis (PFGE) and enterotoxin gene typing, confirmed the link between patients and the suspected foodstuffs. This also demonstrated the high diversity of CPS isolates both in the cases and in healthy persons carrying enterotoxin genes encoding emetic SEs for which no detection methods currently exist. For one outbreak, the investigation pointed out to the food handler who transmitted the outbreak strain to the food. Tools to improve staphylococcal food poisoning (SFP) investigations are presented.

MICRA: an automatic pipeline for fast characterization of microbial genomes from high-throughput sequencing data

The increase in available sequence data has advanced the field of microbiology; however, making sense of these data without bioinformatics skills is still problematic. We describe MICRA, an automatic pipeline, available as a web interface, for microbial identification and characterization through reads analysis. MICRA uses iterative mapping against reference genomes to identify genes and variations. Additional modules allow prediction of antibiotic susceptibility and resistance and comparing the results of several samples. MICRA is fast, producing few false-positive annotations and variant calls compared to current methods, making it a tool of great interest for fully exploiting sequencing data.

Pseudomonas aeruginosa intensive care unit outbreak: winnowing of transmissions with molecular and genomic typing

Background

Pseudomonas aeruginosa healthcare outbreaks can be time consuming and difficult to investigate. Guidance does not specify which typing technique is most practical for decision-making.

Aim

To explore the usefulness of whole-genome sequencing (WGS) in the investigation of a P. aeruginosa outbreak, describing how it compares with pulsed-field gel electrophoresis (PFGE) and variable number tandem repeat (VNTR) analysis.

Methods

Six patient isolates and six environmental samples from an intensive care unit (ICU) positive for P. aeruginosa over two years underwent VNTR, PFGE and WGS.

Findings

VNTR and PFGE were required to fully determine the potential source of infection and rule out others. WGS results unambiguously distinguished linked isolates, giving greater assurance of the transmission route between wash-hand basin water and two patients, supporting the control measures employed.

Conclusion

WGS provided detailed information without the need for further typing. When allied to epidemiological information, WGS can be used to understand outbreak situations rapidly and with certainty. Implementation of WGS in real-time would be a major advance in day-to-day practice. It could become a standard of care as it becomes more widespread due to its reproducibility and lower costs.

Next generation sequencing reveals the antibiotic resistant variants in the genome of Pseudomonas aeruginosa

Rapid progress in next generation sequencing and allied computational tools have aided in identification of single nucleotide variants in genomes of several organisms. In the present study, we have investigated single nucleotide polymorphism (SNP) in ten multi-antibiotic resistant Pseudomonas aeruginosa clinical isolates. All the draft genomes were submitted to Rapid Annotations using Subsystems Technology (RAST) web server and the predicted protein sequences were used for comparison. Non-synonymous single nucleotide polymorphism (nsSNP) found in the clinical isolates compared to the reference genome (PAO1), and the comparison of nsSNPs between antibiotic resistant and susceptible clinical isolates revealed insights into the genome variation. These nsSNPs identified in the multi-drug resistant clinical isolates were found to be altering a single amino acid in several antibiotic resistant genes. We found mutations in genes encoding efflux pump systems, cell wall, DNA replication and genes involved in repair mechanism. In addition, nucleotide deletions in the genome and mutations leading to generation of stop codons were also observed in the antibiotic resistant clinical isolates. Next generation sequencing is a powerful tool to compare the whole genomes and analyse the single base pair variations found within the antibiotic resistant genes. We identified specific mutations within antibiotic resistant genes compared to the susceptible strain of the same bacterial species and these findings may provide insights to understand the role of single nucleotide variants in antibiotic resistance.

Genomic insights from whole genome sequencing of four clonal outbreak Campylobacter jejuni assessed within the global C. jejuni population

BACKGROUND

Whole genome sequencing (WGS) is useful for determining clusters of human cases, investigating outbreaks, and defining the population genetics of bacteria. It also provides information about other aspects of bacterial biology, including classical typing results, virulence, and adaptive strategies of the organism. Cell culture invasion and protein expression patterns of four related multilocus sequence type 21 (ST21) C. jejuni isolates from a significant Canadian water-borne outbreak were previously associated with the presence of a CJIE1 prophage. Whole genome sequencing was used to examine the genetic diversity among these isolates and confirm that previous observations could be attributed to differential prophage carriage. Moreover, we sought to determine the presence of genome sequences that could be used as surrogate markers to delineate outbreak-associated isolates.

RESULTS

Differential carriage of the CJIE1 prophage was identified as the major genetic difference among the four outbreak isolates. High quality single-nucleotide variant (hqSNV) and core genome multilocus sequence typing (cgMLST) clustered these isolates within expanded datasets consisting of additional C. jejuni strains. The number and location of homopolymeric tract regions was identical in all four outbreak isolates but differed from all other C. jejuni examined. Comparative genomics and PCR amplification enabled the identification of large chromosomal inversions of approximately 93 kb and 388 kb within the outbreak isolates associated with transducer-like proteins containing long nucleotide repeat sequences. The 93-kb inversion was characteristic of the outbreak-associated isolates, and the gene content of this inverted region displayed high synteny with the reference strain.

CONCLUSIONS

The four outbreak isolates were clonally derived and differed mainly in the presence of the CJIE1 prophage, validating earlier findings linking the prophage to phenotypic differences in virulence assays and protein expression. The identification of large, genetically syntenous chromosomal inversions in the genomes of outbreak-associated isolates provided a unique method for discriminating outbreak isolates from the background population. Transducer-like proteins appear to be associated with the chromosomal inversions. CgMLST and hqSNV analysis also effectively delineated the outbreak isolates within the larger C. jejuni population structure.

Bacterial Genomics Reveal the Complex Epidemiology of an Emerging Pathogen in Arctic and Boreal Ungulates

Northern ecosystems are currently experiencing unprecedented ecological change, largely driven by a rapidly changing climate. Pathogen range expansion, and emergence and altered patterns of infectious disease, are increasingly reported in wildlife at high latitudes. Understanding the causes and consequences of shifting pathogen diversity and host-pathogen interactions in these ecosystems is important for wildlife conservation, and for indigenous populations that depend on wildlife. Among the key questions are whether disease events are associated with endemic or recently introduced pathogens, and whether emerging strains are spreading throughout the region. In this study, we used a phylogenomic approach to address these questions of pathogen endemicity and spread for Erysipelothrix rhusiopathiae, an opportunistic multi-host bacterial pathogen associated with recent mortalities in arctic and boreal ungulate populations in North America. We isolated E. rhusiopathiae from carcasses associated with large-scale die-offs of muskoxen in the Canadian Arctic Archipelago, and from contemporaneous mortality events and/or population declines among muskoxen in northwestern Alaska and caribou and moose in western Canada. Bacterial genomic diversity differed markedly among these locations; minimal divergence was present among isolates from muskoxen in the Canadian Arctic, while in caribou and moose populations, strains from highly divergent clades were isolated from the same location, or even from within a single carcass. These results indicate that mortalities among northern ungulates are not associated with a single emerging strain of E. rhusiopathiae, and that alternate hypotheses need to be explored. Our study illustrates the value and limitations of bacterial genomic data for discriminating between ecological hypotheses of disease emergence, and highlights the importance of studying emerging pathogens within the broader context of environmental and host factors.

Exploiting Bacterial Whole-Genome Sequencing Data for Evaluation of Diagnostic Assays: Campylobacter Species Identification as a Case Study

The application of whole-genome sequencing (WGS) to problems in clinical microbiology has had a major impact on the field. Clinical laboratories are now using WGS for pathogen identification, antimicrobial susceptibility testing, and epidemiological typing. WGS data also represent a valuable resource for the development and evaluation of molecular diagnostic assays, which continue to play an important role in clinical microbiology. To demonstrate this application of WGS, this study used publicly available genomic data to evaluate a duplex real-time PCR (RT-PCR) assay that targets mapA and ceuE for the detection of Campylobacter jejuni and Campylobacter coli, leading global causes of bacterial gastroenteritis. In silico analyses of mapA and ceuE primer and probe sequences from 1,713 genetically diverse C. jejuni and C. coli genomes, supported by RT-PCR testing, indicated that the assay was robust, with 1,707 (99.7%) isolates correctly identified. The high specificity of the mapA-ceuE assay was the result of interspecies diversity and intraspecies conservation of the target genes in C. jejuni and C. coli Rare instances of a lack of specificity among C. coli isolates were due to introgression in mapA or sequence diversity in ceuE The results of this study illustrate how WGS can be exploited to evaluate molecular diagnostic assays by using publicly available data, online databases, and open-source software.

Third generation sequencing technologies applied to diagnostic microbiology: benefits and challenges in applications and data analysis

INTRODUCTION

The diagnosis of infectious diseases is among the most successful areas of application of new generation sequencing technologies. The field has seen the development of numerous experimental and analytical approaches for the detection and the fine description of pathogenic and non-pathogenic microorganisms.

AREAS COVERED

Without claiming to be exhaustive with respect to all applications and methods developed over the years, this review focuses on the advantages and the issues brought by the new technologies, with an eye in particular to third generation sequencing methods. Both experimental procedures and algorithmic strategies are presented, following the most relevant publications which have led to progress in our ability of detecting infectious agents. Expert commentary: The technical advance brought by third generation sequencing platforms has the potential to significantly expand the range of diagnostic tools that will be available to clinicians. Nonetheless, the implementation of these technologies in clinical practice is still far from being actionable and will temporally follow the path undertaken by second generation methods, which still require the setup of standardized pipelines in both wet and dry laboratory procedures.

Microbial bioinformatics 2020

Microbial bioinformatics in 2020 will remain a vibrant, creative discipline, adding value to the ever‐growing flood of new sequence data, while embracing novel technologies and fresh approaches. Databases and search strategies will struggle to cope and manual curation will not be sustainable during the scale‐up to the million‐microbial‐genome era. Microbial taxonomy will have to adapt to a situation in which most microorganisms are discovered and characterised through the analysis of sequences. Genome sequencing will become a routine approach in clinical and research laboratories, with fresh demands for interpretable user‐friendly outputs. The “internet of things” will penetrate healthcare systems, so that even a piece of hospital plumbing might have its own IP address that can be integrated with pathogen genome sequences. Microbiome mania will continue, but the tide will turn from molecular barcoding towards metagenomics. Crowd‐sourced analyses will collide with cloud computing, but eternal vigilance will be the price of preventing the misinterpretation and overselling of microbial sequence data. Output from hand‐held sequencers will be analysed on mobile devices. Open‐source training materials will address the need for the development of a skilled labour force. As we boldly go into the third decade of the twenty‐first century, microbial sequence space will remain the final frontier!

FDA Escherichia coli Identification (FDA-ECID) Microarray: a Pangenome Molecular Toolbox for Serotyping, Virulence Profiling, Molecular Epidemiology, and Phylogeny

Most Escherichia coli strains are nonpathogenic. However, for clinical diagnosis and food safety analysis, current identification methods for pathogenic E. coli either are time-consuming and/or provide limited information. Here, we utilized a custom DNA microarray with informative genetic features extracted from 368 sequence sets for rapid and high-throughput pathogen identification. The FDA Escherichia coli Identification (FDA-ECID) platform contains three sets of molecularly informative features that together stratify strain identification and relatedness. First, 53 known flagellin alleles, 103 alleles of wzx and wzy, and 5 alleles of wzm provide molecular serotyping utility. Second, 41,932 probe sets representing the pan-genome of E. coli provide strain-level gene content information. Third, approximately 125,000 single nucleotide polymorphisms (SNPs) of available whole-genome sequences (WGS) were distilled to 9,984 SNPs capable of recapitulating the E. coli phylogeny. We analyzed 103 diverse E. coli strains with available WGS data, including those associated with past foodborne illnesses, to determine robustness and accuracy. The array was able to accurately identify the molecular O and H serotypes, potentially correcting serological failures and providing better resolution for H-nontypeable/nonmotile phenotypes. In addition, molecular risk assessment was possible with key virulence marker identifications. Epidemiologically, each strain had a unique comparative genomic fingerprint that was extended to an additional 507 food and clinical isolates. Finally, a 99.7% phylogenetic concordance was established between microarray analysis and WGS using SNP-level data for advanced genome typing. Our study demonstrates FDA-ECID as a powerful tool for epidemiology and molecular risk assessment with the capacity to profile the global landscape and diversity of E. coli.

IMPORTANCE This study describes a robust, state-of-the-art platform developed from available whole-genome sequences of E. coli and Shigella spp. by distilling useful signatures for epidemiology and molecular risk assessment into one assay. The FDA-ECID microarray contains features that enable comprehensive molecular serotyping and virulence profiling along with genome-scale genotyping and SNP analysis. Hence, it is a molecular toolbox that stratifies strain identification and pathogenic potential in the contexts of epidemiology and phylogeny. We applied this tool to strains from food, environmental, and clinical sources, resulting in significantly greater phylogenetic and strain-specific resolution than previously reported for available typing methods.

Interpreting whole genome sequencing for investigating tuberculosis transmission: a systematic review

BACKGROUND

Whole genome sequencing (WGS) is becoming an important part of epidemiological investigations of infectious diseases due to greater resolution and cost reductions compared to traditional typing approaches. Many public health and clinical teams will increasingly use WGS to investigate clusters of potential pathogen transmission, making it crucial to understand the benefits and assumptions of the analytical methods for investigating the data. We aimed to understand how different approaches affect inferences of transmission dynamics and outline limitations of the methods.

METHODS

We comprehensively searched electronic databases for studies that presented methods used to interpret WGS data for investigating tuberculosis (TB) transmission. Two authors independently selected studies for inclusion and extracted data. Due to considerable methodological heterogeneity between studies, we present summary data with accompanying narrative synthesis rather than pooled analyses.

RESULTS

Twenty-five studies met our inclusion criteria. Despite the range of interpretation tools, the usefulness of WGS data in understanding TB transmission often depends on the amount of genetic diversity in the setting. Where diversity is small, distinguishing re-infections from relapses may be impossible; interpretation may be aided by the use of epidemiological data, examining minor variants and deep sequencing. Conversely, when within-host diversity is large, due to genetic hitchhiking or co-infection of two dissimilar strains, it is critical to understand how it arose. Greater understanding of microevolution and mixed infection will enhance interpretation of WGS data.

CONCLUSIONS

As sequencing studies have sampled more intensely and integrated multiple sources of information, the understanding of TB transmission and diversity has grown, but there is still much to be learnt about the origins of diversity that will affect inferences from these data. Public health teams and researchers should combine epidemiological, clinical and WGS data to strengthen investigations of transmission.

Role of Clinicogenomics in Infectious Disease Diagnostics and Public Health Microbiology

Clinicogenomics is the exploitation of genome sequence data for diagnostic, therapeutic, and public health purposes. Central to this field is the high-throughput DNA sequencing of genomes and metagenomes. The role of clinicogenomics in infectious disease diagnostics and public health microbiology was the topic of discussion during a recent symposium (session 161) presented at the 115th general meeting of the American Society for Microbiology that was held in New Orleans, LA. What follows is a collection of the most salient and promising aspects from each presentation at the symposium.

Genomic Epidemiology: Whole-Genome-Sequencing-Powered Surveillance and Outbreak Investigation of Foodborne Bacterial Pathogens

As we are approaching the twentieth anniversary of PulseNet, a network of public health and regulatory laboratories that has changed the landscape of foodborne illness surveillance through molecular subtyping, public health microbiology is undergoing another transformation brought about by so-called next-generation sequencing (NGS) technologies that have made whole-genome sequencing (WGS) of foodborne bacterial pathogens a realistic and superior alternative to traditional subtyping methods. Routine, real-time, and widespread application of WGS in food safety and public health is on the horizon. Technological, operational, and policy challenges are still present and being addressed by an international and multidisciplinary community of researchers, public health practitioners, and other stakeholders.

Rapid identification of pathogens using molecular techniques

Real-time PCR is the traditional face of nucleic acid detection in the diagnostic microbiology laboratory and is now generally regarded as robust enough to be widely adopted. Methods based on nucleic acid detection of this type are bringing increased accuracy to diagnosis in areas where culture is difficult and/or expensive, and these methods are often effective partners to other rapid molecular diagnostic tools such as matrix-assisted laser desorption ionisation-time of flight mass spectrometry (MALDI-TOF MS). This change in practice has particularly affected the recognition of viruses and fastidious or antibiotic-exposed bacteria, but has been also shown to be effective in the recognition of troublesome or specialised phenotypes such as antiviral resistance and transmissible antibiotic resistance in the Enterobacteriaceae. Quantitation and high-intensity sequencing (of multiple whole genomes) has brought new opportunities as well as new challenges to the microbiology community. Diagnostic microbiologists currently training might be expected to deal less with the culture-based techniques of the last half-century than with the high-volume data and complex analyses of the next.

First report of an astrovirus type 5 gastroenteritis outbreak in a residential elderly care home identified by sequencing

BACKGROUND

This is the report of an outbreak of human astrovirus type 5 gastroenteritis that occurred in a residential care home for older people in June 2013 in Tayside, Scotland, and which involved seven staff members and thirteen residents. This type of astrovirus has not been found in Scotland before and is rarely described in the literature.

OBJECTIVES

Using molecular methods such as PCR and sequencing to detect the cause of this gastroenteritis outbreak and to contain the outbreak using Public Health measures.

STUDY DESIGN

Following an epidemiological investigation, stool samples were sent for routine virology and microbiology testing at the local microbiology and virology laboratory and were found to be negative. Further testing with real-time PCR and gene sequencing at the West of Scotland Specialist Virology Centre was performed. Data on the epidemiology and the response to the outbreak was collected.

RESULTS

All samples had a 99% match to human astrovirus type 5. The use of standard infection control precautions with the addition of transmission-based precautions most likely contained the spread of the virus in this situation.

CONCLUSIONS

This report illustrates the importance of using PCR and sequencing to identify pathogens such as astrovirus in outbreaks of vomiting and diarrhoea in older people particularly if routine virology and microbiology tests are negative.

Whole-genome sequencing targets drug-resistant bacterial infections

During the past two decades, the technological progress of whole-genome sequencing (WGS) had changed the fields of Environmental Microbiology and Biotechnology, and, currently, is changing the underlying principles, approaches, and fundamentals of Public Health, Epidemiology, Health Economics, and national productivity. Today’s WGS technologies are able to compete with conventional techniques in cost, speed, accuracy, and resolution for day-to-day control of infectious diseases and outbreaks in clinical laboratories and in long-term epidemiological investigations. WGS gives rise to an exciting future direction for personalized Genomic Epidemiology. One of the most vital and growing public health problems is the emerging and re-emerging of multidrug-resistant (MDR) bacterial infections in the communities and healthcare settings, reinforced by a decline in antimicrobial drug discovery. In recent years, retrospective analysis provided by WGS has had a great impact on the identification and tracking of MDR microorganisms in hospitals and communities. The obtained genomic data are also important for developing novel easy-to-use diagnostic assays for clinics, as well as for antibiotic and therapeutic development at both the personal and population levels. At present, this technology has been successfully applied as an addendum to the real-time diagnostic methods currently used in clinical laboratories. However, the significance of WGS for public health may increase if: (a) unified and user-friendly bioinformatics toolsets for easy data interpretation and management are established, and (b) standards for data validation and verification are developed. Herein, we review the current and future impact of this technology on diagnosis, prevention, treatment, and control of MDR infectious bacteria in clinics and on the global scale.

The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes

Whole-genome sequences are now available for many microbial species and clades, however existing whole-genome alignment methods are limited in their ability to perform sequence comparisons of multiple sequences simultaneously. Here we present the Harvest suite of core-genome alignment and visualization tools for the rapid and simultaneous analysis of thousands of intraspecific microbial strains. Harvest includes Parsnp, a fast core-genome multi-aligner, and Gingr, a dynamic visual platform. Together they provide interactive core-genome alignments, variant calls, recombination detection, and phylogenetic trees. Using simulated and real data we demonstrate that our approach exhibits unrivaled speed while maintaining the accuracy of existing methods. The Harvest suite is open-source and freely available from: http://github.com/marbl/harvest.

The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes

Whole-genome sequences are now available for many microbial species and clades, however existing whole-genome alignment methods are limited in their ability to perform sequence comparisons of multiple sequences simultaneously. Here we present the Harvest suite of core-genome alignment and visualization tools for the rapid and simultaneous analysis of thousands of intraspecific microbial strains. Harvest includes Parsnp, a fast core-genome multi-aligner, and Gingr, a dynamic visual platform. Together they provide interactive core-genome alignments, variant calls, recombination detection, and phylogenetic trees. Using simulated and real data we demonstrate that our approach exhibits unrivaled speed while maintaining the accuracy of existing methods. The Harvest suite is open-source and freely available from: http://github.com/marbl/harvest.

Genomic epidemiology of a protracted hospital outbreak caused by multidrug-resistant Acinetobacter baumannii in Birmingham, England

Background

Multidrug-resistant Acinetobacter baumannii commonly causes hospital outbreaks. However, within an outbreak, it can be difficult to identify the routes of cross-infection rapidly and accurately enough to inform infection control. Here, we describe a protracted hospital outbreak of multidrug-resistant A. baumannii, in which whole-genome sequencing (WGS) was used to obtain a high-resolution view of the relationships between isolates.

Methods

To delineate and investigate the outbreak, we attempted to genome-sequence 114 isolates that had been assigned to the A. baumannii complex by the Vitek2 system and obtained informative draft genome sequences from 102 of them. Genomes were mapped against an outbreak reference sequence to identify single nucleotide variants (SNVs).

Results

We found that the pulsotype 27 outbreak strain was distinct from all other genome-sequenced strains. Seventy-four isolates from 49 patients could be assigned to the pulsotype 27 outbreak on the basis of genomic similarity, while WGS allowed 18 isolates to be ruled out of the outbreak. Among the pulsotype 27 outbreak isolates, we identified 31 SNVs and seven major genotypic clusters. In two patients, we documented within-host diversity, including mixtures of unrelated strains and within-strain clouds of SNV diversity. By combining WGS and epidemiological data, we reconstructed potential transmission events that linked all but 10 of the patients and confirmed links between clinical and environmental isolates. Identification of a contaminated bed and a burns theatre as sources of transmission led to enhanced environmental decontamination procedures.

Conclusions

WGS is now poised to make an impact on hospital infection prevention and control, delivering cost-effective identification of routes of infection within a clinically relevant timeframe and allowing infection control teams to track, and even prevent, the spread of drug-resistant hospital pathogens.

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.

Epidemiologic data and pathogen genome sequences: a powerful synergy for public health

Epidemiologists aim to inform the design of public health interventions with evidence on the evolution, emergence and spread of infectious diseases. Sequencing of pathogen genomes, together with date, location, clinical manifestation and other relevant data about sample origins, can contribute to describing nearly every aspect of transmission dynamics, including local transmission and global spread. The analyses of these data have implications for all levels of clinical and public health practice, from institutional infection control to policies for surveillance, prevention and treatment. This review highlights the range of epidemiological questions that can be addressed from the combination of genome sequence and traditional ‘line lists’ (tables of epidemiological data where each line includes demographic and clinical features of infected individuals). We identify opportunities for these data to inform interventions that reduce disease incidence and prevalence. By considering current limitations of, and challenges to, interpreting these data, we aim to outline a research agenda to accelerate the genomics-driven transformation in public health microbiology.

KvarQ: targeted and direct variant calling from fastq reads of bacterial genomes

BACKGROUND

High-throughput DNA sequencing produces vast amounts of data, with millions of short reads that usually have to be mapped to a reference genome or newly assembled. Both reference-based mapping and de novo assembly are computationally intensive, generating large intermediary data files, and thus require bioinformatics skills that are often lacking in the laboratories producing the data. Moreover, many research and practical applications in microbiology require only a small fraction of the whole genome data.

RESULTS

We developed KvarQ, a new tool that directly scans fastq files of bacterial genome sequences for known variants, such as single nucleotide polymorphisms (SNP), bypassing the need of mapping all sequencing reads to a reference genome and de novo assembly. Instead, KvarQ loads "testsuites" that define specific SNPs or short regions of interest in a reference genome, and directly synthesizes the relevant results based on the occurrence of these markers in the fastq files. KvarQ has a versatile command line interface and a graphical user interface. KvarQ currently ships with two "testsuites" for Mycobacterium tuberculosis, but new "testsuites" for other organisms can easily be created and distributed. In this article, we demonstrate how KvarQ can be used to successfully detect all main drug resistance mutations and phylogenetic markers in 880 bacterial whole genome sequences. The average scanning time per genome sequence was two minutes. The variant calls of a subset of these genomes were validated with a standard bioinformatics pipeline and revealed >99% congruency.

CONCLUSION

KvarQ is a user-friendly tool that directly extracts relevant information from fastq files. This enables researchers and laboratory technicians with limited bioinformatics expertise to scan and analyze raw sequencing data in a matter of minutes. KvarQ is open-source, and pre-compiled packages with a graphical user interface are available at http://www.swisstph.ch/kvarq.

Whole-genome sequencing to control antimicrobial resistance

Following recent improvements in sequencing technologies, whole-genome sequencing (WGS) is positioned to become an essential tool in the control of antibiotic resistance, a major threat in modern healthcare. WGS has already found numerous applications in this area, ranging from the development of novel antibiotics and diagnostic tests through to antibiotic stewardship of currently available drugs via surveillance and the elucidation of the factors that allow the emergence and persistence of resistance. Numerous proof-of-principle studies have also highlighted the value of WGS as a tool for day-to-day infection control and, for some pathogens, as a primary diagnostic tool to detect antibiotic resistance. However, appropriate data analysis platforms will need to be developed before routine WGS can be introduced on a large scale.

Genomic variation between Campylobacter jejuni isolates associated with milk-borne-disease outbreaks

Bacterial genome sequencing has led to the development of new approaches for the analysis of food-borne epidemics and the exploration of the relatedness of outbreak-associated isolates and their separation from nonassociated isolates. Using Illumina technology, we sequenced a total of six isolates (two from patients, two from raw bulk milk, and two from dairy cattle) associated with a milk-borne Campylobacter jejuni outbreak in a farming family and compared their genomes. These isolates had identical pulsed-field gel electrophoresis (PFGE) types, and their multilocus sequence typing (MLST) type was ST-50. We used the Ma_1 isolate (milk) as the reference, and its genome was assembled and tentatively ordered using the C. jejuni NCTC 11168 genome as the scaffold. Using whole-genome MLST (wgMLST), we identified a total of three single-nucleotide polymorphisms (SNPs) and differences in poly(G or C) or poly(A or T) tracts in 12 loci among the isolates. Several new alleles not present in the database were detected. In contrast, the sequences of the unassociated C. jejuni strains P14 and 1-12S (both ST-50) differed by 420 to 454 alleles from the epidemic-associated isolates. We found that the fecal contamination of bulk tank milk occurred by highly related sequence variants of C. jejuni, which are reflected as SNPs and differences in the length of the poly(A or T) tracts. Poly(G or C) tracts are reversibly variable and are thus unstable markers for comparison. Further, unrelated strains of ST-50 were clearly separated from the outbreak-associated isolates, indicating that wgMLST is an excellent tool for analysis. In addition, other useful data related to the genes and genetic systems of the isolates were obtained.

Real-time investigation of a Legionella pneumophila outbreak using whole genome sequencing

Legionella pneumophila is the main pathogen responsible for outbreaks of Legionnaires' disease, which can be related to contaminated water supplies such as cooling towers or water pipes. We combined conventional molecular methods and whole genome sequence (WGS) analysis to investigate an outbreak of L. pneumophila in a large Australian hospital. Typing of these isolates using sequence-based typing and virulence gene profiling, was unable to discriminate between outbreak and non-outbreak isolates. WGS analysis was performed on isolates during the outbreak, as well as on unlinked isolates from the Public Health Microbiology reference collection. The more powerful resolution provided by analysis of whole genome sequences allowed outbreak isolates to be distinguished from isolates that were temporally and spatially unassociated with the outbreak, demonstrating that this technology can be used in real-time to investigate L. pneumophila outbreaks.