Microreact: visualizing and sharing data for genomic epidemiology and phylogeography

Epidemic of carbapenem-resistant Klebsiella pneumoniae in Europe is driven by nosocomial spread

Public health interventions to control the current epidemic of carbapenem-resistant Klebsiella pneumoniae rely on a comprehensive understanding of its emergence and spread over a wide range of geographical scales. We analysed the genome sequences and epidemiological data of >1,700 K. pneumoniae samples isolated from patients in 244 hospitals in 32 countries during the European Survey of Carbapenemase-Producing Enterobacteriaceae. We demonstrate that carbapenemase acquisition is the main cause of carbapenem resistance and that it occurred across diverse phylogenetic backgrounds. However, 477 of 682 (69.9%) carbapenemase-positive isolates are concentrated in four clonal lineages, sequence types 11, 15, 101, 258/512 and their derivatives. Combined analysis of the genetic and geographic distances between isolates with different β-lactam resistance determinants suggests that the propensity of K. pneumoniae to spread in hospital environments correlates with the degree of resistance and that carbapenemase-positive isolates have the highest transmissibility. Indeed, we found that over half of the hospitals that contributed carbapenemase-positive isolates probably experienced within-hospital transmission, and interhospital spread is far more frequent within, rather than between, countries. Finally, we propose a value of 21 for the number of single nucleotide polymorphisms that optimizes the discrimination of hospital clusters and detail the international spread of the successful epidemic lineage, ST258/512.

Pilot Evaluation of a Fully Automated Bioinformatics System for Analysis of Methicillin-Resistant Staphylococcus aureus Genomes and Detection of Outbreaks

Genomic surveillance that combines bacterial sequencing and epidemiological information will become the gold standard for outbreak detection, but its clinical translation is hampered by the lack of automated interpretation tools. We performed a prospective pilot study to evaluate the analysis of methicillin-resistant Staphylococcus aureus (MRSA) genomes using the Next Gen Diagnostics (NGD) automated bioinformatics system.

Genomic surveillance that combines bacterial sequencing and epidemiological information will become the gold standard for outbreak detection, but its clinical translation is hampered by the lack of automated interpretation tools. We performed a prospective pilot study to evaluate the analysis of methicillin-resistant Staphylococcus aureus (MRSA) genomes using the Next Gen Diagnostics (NGD) automated bioinformatics system. Seventeen unselected MRSA-positive patients were identified in a clinical microbiology laboratory in England over a period of 2 weeks in 2018, and 1 MRSA isolate per case was sequenced on the Illumina MiniSeq instrument. The NGD system automatically activated after sequencing and processed fastq folders to determine species, multilocus sequence type, the presence of a mec gene, antibiotic susceptibility predictions, and genetic relatedness based on mapping to a reference MRSA genome and detection of pairwise core genome single-nucleotide polymorphisms. The NGD system required 90 s per sample to automatically analyze data from each run, the results of which were automatically displayed. The same data were independently analyzed using a research-based approach. There was full concordance between the two analysis methods regarding species (S. aureus), detection of mecA, sequence type assignment, and detection of genetic determinants of resistance. Both analysis methods identified two MRSA clusters based on relatedness, one of which contained 3 cases that were involved in an outbreak linked to a clinic and ward associated with diabetic patient care. We conclude that, in this pilot study, the NGD system provided rapid and accurate data that could support infection control practices.

Azithromycin non-susceptible Shigella circulating in Israel, 2014-2016

Shigella species remains a major diarrhoeagenic agent, affecting mostly children, with global high incidence and high mortality rate specially in developing areas. Although azithromycin is recommended for treatment of shigellosis, there are currently no CLSI susceptibility breakpoints, accordingly no routine antimicrobial susceptibility test is performed in the clinical laboratory. The purpose of this study was to estimate the prevalence, resistance profile and molecular epidemiology of azithromycin non-susceptible Shigella strains in Israel during a three year period. Shigella isolates (n = 1,170) referred to the National Reference Center during 2014-2016, were included in this study. Serotyping was performed by slide agglutination. Resistance genes, mph(A) and erm(B), were identified by PCR and the phenotype profile was determined by broth microdilution (BMD). Genetic relatedness was assessed by wgMLST. Decreased susceptibility to azithromycin (DSA) phenotype and genotype were detected in various Shigella species and serotypes related to diverse genetic backgrounds and antimicrobial profiles: 6% (26/423) of Shigella flexneri and 2% (16/747) of Shigella sonnei displayed DSA (MIC16 mg/L). Correlation of this phenotype with the presence of mph(A) and erm(B) genes was confirmed. All DSA-strains displayed resistance to ≥3 different antimicrobial classes. Among DSA-strains, 14% were resistant to quinolones and 5% displayed resistance to ceftriaxone. Most of these strains (32/42) were isolated from children in the southern and central regions of Israel. Clonality and significant relatedness was confirmed by PFGE and wgMLST. The presence of macrolide resistance genes among the different species and lineages reflects the transmissible nature of these genes. The emergence of DSA-Shigella reinforces the necessity to establish clinical breakpoints that would warrant routine testing, reporting and surveillance for this drug of choice.

PIRATE: A fast and scalable pangenomics toolbox for clustering diverged orthologues in bacteria

BACKGROUND

Cataloguing the distribution of genes within natural bacterial populations is essential for understanding evolutionary processes and the genetic basis of adaptation. Advances in whole genome sequencing technologies have led to a vast expansion in the amount of bacterial genomes deposited in public databases. There is a pressing need for software solutions which are able to cluster, catalogue and characterise genes, or other features, in increasingly large genomic datasets.

RESULTS

Here we present a pangenomics toolbox, PIRATE (Pangenome Iterative Refinement and Threshold Evaluation), which identifies and classifies orthologous gene families in bacterial pangenomes over a wide range of sequence similarity thresholds. PIRATE builds upon recent scalable software developments to allow for the rapid interrogation of thousands of isolates. PIRATE clusters genes (or other annotated features) over a wide range of amino acid or nucleotide identity thresholds and uses the clustering information to rapidly identify paralogous gene families and putative fission/fusion events. Furthermore, PIRATE orders the pangenome using a directed graph, provides a measure of allelic variation, and estimates sequence divergence for each gene family.

CONCLUSIONS

We demonstrate that PIRATE scales linearly with both number of samples and computation resources, allowing for analysis of large genomic datasets, and compares favorably to other popular tools. PIRATE provides a robust framework for analysing bacterial pangenomes, from largely clonal to panmictic species.

An African Salmonella Typhimurium ST313 sublineage with extensive drug-resistance and signatures of host adaptation

Bloodstream infections by Salmonella enterica serovar Typhimurium constitute a major health burden in sub-Saharan Africa (SSA). These invasive non-typhoidal (iNTS) infections are dominated by isolates of the antibiotic resistance-associated sequence type (ST) 313. Here, we report emergence of ST313 sublineage II.1 in the Democratic Republic of the Congo. Sublineage II.1 exhibits extensive drug resistance, involving a combination of multidrug resistance, extended spectrum β-lactamase production and azithromycin resistance. ST313 lineage II.1 isolates harbour an IncHI2 plasmid we name pSTm-ST313-II.1, with one isolate also exhibiting decreased ciprofloxacin susceptibility. Whole genome sequencing reveals that ST313 II.1 isolates have accumulated genetic signatures potentially associated with altered pathogenicity and host adaptation, related to changes observed in biofilm formation and metabolic capacity. Sublineage II.1 emerged at the beginning of the 21st century and is involved in on-going outbreaks. Our data provide evidence of further evolution within the ST313 clade associated with iNTS in SSA.

Genomic evolution and local epidemiology of Klebsiella pneumoniae from a major hospital in Beijing, China, over a 15 year period: dissemination of known and novel high-risk clones

Klebsiella pneumoniae is a frequent cause of nosocomial and severe community-acquired infections. Multidrug-resistant (MDR) and hypervirulent (hv) strains represent major threats, and tracking their emergence, evolution and the emerging convergence of MDR and hv traits is of major importance. We employed whole-genome sequencing (WGS) to study the evolution and epidemiology of a large longitudinal collection of clinical K. pneumoniae isolates from the H301 hospital in Beijing, China. Overall, the population was highly diverse, although some clones were predominant. Strains belonging to clonal group (CG) 258 were dominant, and represented the majority of carbapenemase-producers. While CG258 strains showed high diversity, one clone, ST11-KL47, represented the majority of isolates, and was highly associated with the KPC-2 carbapenemase and several virulence factors, including a virulence plasmid. The second dominant clone was CG23, which is the major hv clone globally. While it is usually susceptible to multiple antibiotics, we found some isolates harbouring MDR plasmids encoding for ESBLs and carbapenemases. We also reported the local emergence of a recently described high-risk clone, ST383. Conversely to strains belonging to CG258, which are usually associated to KPC-2, ST383 strains seem to readily acquire carbapenemases of different types. Moreover, we found several ST383 strains carrying the hypervirulence plasmid. Overall, we detected about 5 % of simultaneous carriage of AMR genes (ESBLs or carbapenemases) and hypervirulence genes. Tracking the emergence and evolution of such strains, causing severe infections with limited treatment options, is fundamental in order to understand their origin and evolution and to limit their spread. This article contains data hosted by Microreact.

Molecular typing of Cryptosporidium in Israel

Cryptosporidium is a protozoan parasite associated with gastrointestinal illness. In immune-compromised individuals, the infection may become life-threatening. Cryptosporidiosis is a mandatory-reported disease but little was known about its prevalence and associated morbidity in Israel. Currently, laboratory diagnosis is based on microscopy or copro-antigen tests and the disease is underreported. Molecular assays, which are more sensitive and specific, are now increasingly used for identification and screening. Here, the molecular epidemiology of cryptosporidiosis is explored for the first time. Samples from 33 patients infected during an outbreak of 146 laboratory confirmed cases that occurred in Haifa and Western Galilee in 2015 were genotyped, as well as samples from 36 patients sporadically infected during 2014–2018 in different regions. The results suggest that Cryptosporidium subtypes found in Israel are more similar to those reported in the neighboring countries Jordan and Egypt than in European countries. C. hominis was the predominant species in the center and the north of Israel, implicating human-to-human transmission. C. hominis IeA11G3T3 was the most prevalent subtype contributing to morbidity.

Advances in Visualization Tools for Phylogenomic and Phylodynamic Studies of Viral Diseases

Genomic and epidemiological monitoring have become an integral part of our response to emerging and ongoing epidemics of viral infectious diseases. Advances in high-throughput sequencing, including portable genomic sequencing at reduced costs and turnaround time, are paralleled by continuing developments in methodology to infer evolutionary histories (dynamics/patterns) and to identify factors driving viral spread in space and time. The traditionally static nature of visualizing phylogenetic trees that represent these evolutionary relationships/processes has also evolved, albeit perhaps at a slower rate. Advanced visualization tools with increased resolution assist in drawing conclusions from phylogenetic estimates and may even have potential to better inform public health and treatment decisions, but the design (and choice of what analyses are shown) is hindered by the complexity of information embedded within current phylogenetic models and the integration of available meta-data. In this review, we discuss visualization challenges for the interpretation and exploration of reconstructed histories of viral epidemics that arose from increasing volumes of sequence data and the wealth of additional data layers that can be integrated. We focus on solutions that address joint temporal and spatial visualization but also consider what the future may bring in terms of visualization and how this may become of value for the coming era of real-time digital pathogen surveillance, where actionable results and adequate intervention strategies need to be obtained within days.

Cytomegalovirus distribution and evolution in hominines

Herpesviruses are thought to have evolved in very close association with their hosts. This is notably the case for cytomegaloviruses (CMVs; genus Cytomegalovirus) infecting primates, which exhibit a strong signal of co-divergence with their hosts. Some herpesviruses are however known to have crossed species barriers. Based on a limited sampling of CMV diversity in the hominine (African great ape and human) lineage, we hypothesized that chimpanzees and gorillas might have mutually exchanged CMVs in the past. Here, we performed a comprehensive molecular screening of all 9 African great ape species/subspecies, using 675 fecal samples collected from wild animals. We identified CMVs in eight species/subspecies, notably generating the first CMV sequences from bonobos. We used this extended dataset to test competing hypotheses with various degrees of co-divergence/number of host switches while simultaneously estimating the dates of these events in a Bayesian framework. The model best supported by the data involved the transmission of a gorilla CMV to the panine (chimpanzee and bonobo) lineage and the transmission of a panine CMV to the gorilla lineage prior to the divergence of chimpanzees and bonobos, more than 800,000 years ago. Panine CMVs then co-diverged with their hosts. These results add to a growing body of evidence suggesting that viruses with a double-stranded DNA genome (including other herpesviruses, adenoviruses, and papillomaviruses) often jumped between hominine lineages over the last few million years.

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'.

The use of next generation sequencing for improving food safety: Translation into practice

Next Generation Sequencing (NGS) combined with powerful bioinformatic approaches are revolutionising food microbiology. Whole genome sequencing (WGS) of single isolates allows the most detailed comparison possible hitherto of individual strains. The two principle approaches for strain discrimination, single nucleotide polymorphism (SNP) analysis and genomic multi-locus sequence typing (MLST) are showing concordant results for phylogenetic clustering and are complementary to each other. Metabarcoding and metagenomics, applied to total DNA isolated from either food materials or the production environment, allows the identification of complete microbial populations. Metagenomics identifies the entire gene content and when coupled to transcriptomics or proteomics, allows the identification of functional capacity and biochemical activity of microbial populations. The focus of this review is on the recent use and future potential of NGS in food microbiology and on current challenges. Guidance is provided for new users, such as public health departments and the food industry, on the implementation of NGS and how to critically interpret results and place them in a broader context. The review aims to promote the broader application of NGS technologies within the food industry as well as highlight knowledge gaps and novel applications of NGS with the aim of driving future research and increasing food safety outputs from its wider use.

Atlas of group A streptococcal vaccine candidates compiled using large-scale comparative genomics

Group A Streptococcus (GAS; Streptococcus pyogenes) is a bacterial pathogen for which a commercial vaccine for humans is not available. Employing the advantages of high-throughput DNA sequencing technology to vaccine design, we have analyzed 2,083 globally sampled GAS genomes. The global GAS population structure reveals extensive genomic heterogeneity driven by homologous recombination and overlaid with high levels of accessory gene plasticity. We identified the existence of more than 290 clinically associated genomic phylogroups across 22 countries, highlighting challenges in designing vaccines of global utility. To determine vaccine candidate coverage, we investigated all of the previously described GAS candidate antigens for gene carriage and gene sequence heterogeneity. Only 15 of 28 vaccine antigen candidates were found to have both low naturally occurring sequence variation and high (>99%) coverage across this diverse GAS population. This technological platform for vaccine coverage determination is equally applicable to prospective GAS vaccine antigens identified in future studies.

Use of whole genome sequencing in surveillance for antimicrobial-resistant Shigella sonnei infections acquired from domestic and international sources

Shigella species are a major cause of gastroenteritis worldwide, and Shigella sonnei is the most common species isolated within the United States. Previous surveillance work in Pennsylvania documented increased antimicrobial resistance (AMR) in S. sonnei associated with reported illnesses. The present study examined a subset of these isolates by whole genome sequencing (WGS) to determine the relationship between domestic and international isolates, to identify genes that may be useful for identifying specific Global Lineages of S. sonnei and to test the accuracy of WGS for predicting AMR phenotype. A collection of 22 antimicrobial-resistant isolates from patients infected within the United States or while travelling internationally between 2009 and 2014 was chosen for WGS. Phylogenetic analysis revealed both international and domestic isolates were one of two previously defined Global Lineages of S. sonnei, designated Lineage II and Lineage III. Twelve of 17 alleles tested distinguish these two lineages. Lastly, genome analysis was used to identify AMR determinants. Genotypic analysis was concordant with phenotypic resistance for six of eight antibiotic classes. For aminoglycosides and trimethoprim, resistance genes were identified in two and three phenotypically sensitive isolates, respectively. This article contains data hosted by Microreact.

Whole genome sequence of Vibrio cholerae directly from dried spotted filter paper

BACKGROUND

Global estimates for cholera annually approximate 4 million cases worldwide with 95,000 deaths. Recent outbreaks, including Haiti and Yemen, are reminders that cholera is still a global health concern. Cholera outbreaks can rapidly induce high death tolls by overwhelming the capacity of health facilities, especially in remote areas or areas of civil unrest. Recent studies demonstrated that stool specimens preserved on filter paper facilitate molecular analysis of Vibrio cholerae in resource limited settings. Specimens preserved in a rapid, low-cost, safe and sustainable manner for sequencing provides previously unavailable data about circulating cholera strains. This may ultimately contribute new information to shape public policy response on cholera control and elimination.

METHODOLOGY/PRINCIPAL FINDINGS

Whole genome sequencing (WGS) recovered close to a complete sequence of the V. cholerae O1 genome with satisfactory genome coverage from stool specimens enriched in alkaline peptone water (APW) and V. cholerae culture isolates, both spotted on filter paper. The minimum concentration of V. cholerae DNA sufficient to produce quality genomic information was 0.02 ng/μL. The genomic data confirmed the presence or absence of genes of epidemiological interest, including cholera toxin and pilus loci. WGS identified a variety of diarrheal pathogens from APW-enriched specimen spotted filter paper, highlighting the potential for this technique to explore the gut microbiome, potentially identifying co-infections, which may impact the severity of disease. WGS demonstrated that these specimens fit within the current global cholera phylogenetic tree, identifying the strains as the 7th pandemic El Tor.

CONCLUSIONS

WGS results allowed for mapping of short reads from APW-enriched specimen and culture isolate spotted filter papers. This provided valuable molecular epidemiological sequence information on V. cholerae strains from remote, low-resource settings. These results identified the presence of co-infecting pathogens while providing rare insight into the specific V. cholerae strains causing outbreaks in cholera-endemic areas.

EvoMining reveals the origin and fate of natural product biosynthetic enzymes

Natural products (NPs), or specialized metabolites, are important for medicine and agriculture alike, and for the fitness of the organisms that produce them. NP genome-mining aims at extracting biosynthetic information from the genomes of microbes presumed to produce these compounds. Typically, canonical enzyme sequences from known biosynthetic systems are identified after sequence similarity searches. Despite this being an efficient process, the likelihood of identifying truly novel systems by this approach is low. To overcome this limitation, we previously introduced EvoMining, a genome-mining approach that incorporates evolutionary principles. Here, we release and use our latest EvoMining version, which includes novel visualization features and customizable databases, to analyse 42 central metabolic enzyme families (EFs) conserved throughout Actinobacteria, Cyanobacteria, Pseudomonas and Archaea. We found that expansion-and-recruitment profiles of these 42 families are lineage specific, opening the metabolic space related to ‘shell’ enzymes. These enzymes, which have been overlooked, are EFs with orthologues present in most of the genomes of a taxonomic group, but not in all. As a case study of canonical shell enzymes, we characterized the expansion and recruitment of glutamate dehydrogenase and acetolactate synthase into scytonemin biosynthesis, and into other central metabolic pathways driving Archaea and Bacteria adaptive evolution. By defining the origin and fate of enzymes, EvoMining complements traditional genome-mining approaches as an unbiased strategy and opens the door to gaining insights into the evolution of NP biosynthesis. We anticipate that EvoMining will be broadly used for evolutionary studies, and for generating predictions of unprecedented chemical scaffolds and new antibiotics. This article contains data hosted by Microreact.

rPinecone: Define sub-lineages of a clonal expansion via a phylogenetic tree

The ability to distinguish different circulating pathogen clones from each other is a fundamental requirement to understand the epidemiology of infectious diseases. Phylogenetic analysis of genomic data can provide a powerful platform to identify lineages within bacterial populations, and thus inform outbreak investigation and transmission dynamics. However, resolving differences between pathogens associated with low-variant (LV) populations carrying low median pairwise single nucleotide variant (SNV) distances remains a major challenge. Here we present rPinecone, an R package designed to define sub-lineages within closely related LV populations. rPinecone uses a root-to-tip directional approach to define sub-lineages within a phylogenetic tree according to SNV distance from the ancestral node. The utility of this software was demonstrated using both simulated outbreaks and real genomic data of two LV populations: a hospital outbreak of methicillin-resistant Staphylococcus aureus and endemic Salmonella Typhi from rural Cambodia. rPinecone identified the transmission branches of the hospital outbreak and geographically confined lineages in Cambodia. Sub-lineages identified by rPinecone in both analyses were phylogenetically robust. It is anticipated that rPinecone can be used to discriminate between lineages of bacteria from LV populations where other methods fail, enabling a deeper understanding of infectious disease epidemiology for public health purposes.

GenomeGraphR: A user-friendly open-source web application for foodborne pathogen whole genome sequencing data integration, analysis, and visualization

Food safety risk assessments and large-scale epidemiological investigations have the potential to provide better and new types of information when whole genome sequence (WGS) data are effectively integrated. Today, the NCBI Pathogen Detection database WGS collections have grown significantly through improvements in technology, coordination, and collaboration, such as the GenomeTrakr and PulseNet networks. However, high-quality genomic data is not often coupled with high-quality epidemiological or food chain metadata. We have created a set of tools for cleaning, curation, integration, analysis and visualization of microbial genome sequencing data. It has been tested using Salmonella enterica and Listeria monocytogenes data sets provided by NCBI Pathogen Detection (160,000 sequenced isolates in 2018). GenomeGraphR presents foodborne pathogen WGS data and associated curated metadata in a user-friendly interface that allows a user to query a variety of research questions such as, transmission sources and dynamics, global reach, and persistence of genotypes associated with contamination in the food supply and foodborne illness across time or space. The application is freely available (https://fda-riskmodels.foodrisk.org/genomegraphr/).

Using genomics to understand antimicrobial resistance and transmission in Neisseria gonorrhoeae

Gonorrhoea infections are on the increase and strains that are resistant to all antimicrobials used to treat the disease have been found worldwide. These observations encouraged the World Health Organization to include Neisseria gonorrhoeae on their list of high-priority organisms in need of new treatments. Fortunately, concurrent resistance to both antimicrobials used in dual therapy is still rare. The fight against antimicrobial resistance (AMR) must begin from an understanding of how it evolves and spreads in sexual networks. Genome-based analyses have allowed the study of the gonococcal population dynamics and transmission, giving a novel perspective on AMR gonorrhoea. Here, we will review past, present and future treatment options for gonorrhoea and explain how genomics is helping to increase our understanding of the changing AMR and transmission landscape. This article contains data hosted by Microreact.

Fast and flexible bacterial genomic epidemiology with PopPUNK

The routine use of genomics for disease surveillance provides the opportunity for high-resolution bacterial epidemiology. Current whole-genome clustering and multilocus typing approaches do not fully exploit core and accessory genomic variation, and they cannot both automatically identify, and subsequently expand, clusters of significantly similar isolates in large data sets spanning entire species. Here, we describe PopPUNK (Population Partitioning Using Nucleotide K-mers), a software implementing scalable and expandable annotation- and alignment-free methods for population analysis and clustering. Variable-length k-mer comparisons are used to distinguish isolates’ divergence in shared sequence and gene content, which we demonstrate to be accurate over multiple orders of magnitude using data from both simulations and genomic collections representing 10 taxonomically widespread species. Connections between closely related isolates of the same strain are robustly identified, despite interspecies variation in the pairwise distance distributions that reflects species’ diverse evolutionary patterns. PopPUNK can process 10³–10⁴ genomes in a single batch, with minimal memory use and runtimes up to 200-fold faster than existing model-based methods. Clusters of strains remain consistent as new batches of genomes are added, which is achieved without needing to reanalyze all genomes de novo. This facilitates real-time surveillance with consistent cluster naming between studies and allows for outbreak detection using hundreds of genomes in minutes. Interactive visualization and online publication is streamlined through the automatic output of results to multiple platforms. PopPUNK has been designed as a flexible platform that addresses important issues with currently used whole-genome clustering and typing methods, and has potential uses across bacterial genetics and public health research.

Emergence of new genotypes and lineages of dengue viruses during the 2012-15 epidemics in southern India

OBJECTIVES

To genotypically characterize dengue virus (DENV) isolates among dengue-infected children from 2012-13/2014-15 outbreaks in southern India.

METHODS

Children hospitalized with suspected dengue were tested for dengue RT-PCR targeting Capsid-preMembrane (C-prM) and Envelope (Env) regions. Following virologic confirmation (n=612), a representative selection of DENV isolates (n=99) were sequenced for C-prM, aligned using ClustalW and subjected to phylogenetic analysis by maximum-likelihood method in MEGA6.

RESULTS

In 2012-13 (n=113), DENV-3 (44, 38.9%) and DENV-2 (43, 38.1%) predominated; DENV-1 (22, 19.5%) and DENV-4 (1, 0.9%) were less common. The pattern changed in 2014-15 (n=499), when DENV-1 (329, 65.7%) predominated, followed by DENV-2 (97, 21.2%), DENV-3 (36, 6.7%) and DENV-4 (10, 2.0%). Multiple-serotype co-infections occurred in 2.7% and 5.4% in 2012-13 and 2014-15, respectively. Genotype III (GIII) of DENV-1 predominated (85.7%) in 2012-13, ceding to GI predominance (80.8%) in 2014-15. Among DENV-2, 71.9% (23/32) showed distinct clustering suggesting a new lineage, 'GIVc'. All tested DENV-4 were GIC, whose clustering pattern showed the emergence of two distinct clades.

CONCLUSIONS

New genotypic/lineage variations in DENV-1 and DENV-2 may have influenced the magnitude and severity of dengue epidemics in southern India during this period. These findings emphasize the role of active surveillance of DENV serotypes/genotypes in aiding outbreak control and vaccine studies.

A public database for the new MLST scheme for Treponema pallidum subsp. pallidum: surveillance and epidemiology of the causative agent of syphilis

Treponema pallidum subsp. pallidum is the causative agent of syphilis, a sexually transmitted disease with worldwide prevalence. Several different molecular typing schemes are currently available for this pathogen. To enable population biology studies of the syphilis agent and for epidemiological surveillance at the global scale, a harmonized typing tool needs to be introduced. Recently, we published a new multi-locus sequence typing (MLST) with the potential to significantly enhance the epidemiological data in several aspects (e.g., distinguishing genetically different clades of syphilis, subtyping inside these clades, and finally, distinguishing different subspecies of non-cultivable pathogenic treponemes). In this short report, we introduce the PubMLST database for treponemal DNA data storage and for assignments of allelic profiles and sequencing types. Moreover, we have summarized epidemiological data of all treponemal strains (n = 358) with available DNA sequences in typing loci and found several association between genetic groups and characteristics of patients. This study proposes the establishment of a single MLST of T. p. pallidum and encourages researchers and public health communities to use this PubMLST database as a universal tool for molecular typing studies of the syphilis pathogen.

Prevalence of faecal carriage of extended-spectrum β-lactamase (ESBL)-producing Escherichia coli in veterinary hospital staff and students

Extended-spectrum β-lactamase (ESBL)-producing bacteria causing clinical infections are often also multidrug-resistant (MDR; resistance to ≥3 antimicrobial drug classes), therefore treatment options may be limited. High carriage rates of these potentially zoonotic bacteria have been found in livestock and companion animals. Therefore, people working in veterinary hospitals may be a high-risk population for carriage. This is the first study to determine the prevalence and longitudinal carriage of antimicrobial-resistant (AMR) and ESBL-producing faecal Escherichia coli in veterinary hospital staff and students. Prevalence of faecal AMR and ESBL-producing E coli was determined in 84 staff members and students in three UK veterinary hospitals. Twenty-seven participants were followed for six weeks to investigate longitudinal carriage. Antimicrobial susceptibility and phenotypic ESBL production were determined and selected isolates were whole genome sequenced. ESBL-producing E coli were isolated from five participants (5.95 per cent; 95 per cent CI 0.89 to 11.0 per cent); two participants carried ESBL-producing E coli resistant to all antimicrobials tested. Carriage of MDR E coli was common (32.1 per cent; 95per cent CI 22.2 to 42.1 per cent) and there was a high prevalence of ciprofloxacin resistance (11.9 per cent; 95 per cent CI 4.98 to 18.8 per cent). ESBL-producing E coli were isolated from seven longitudinal participants (25.9 per cent; 95 per cent CI 9.40 to 42.5 per cent); two participants carried ESBL-producing E coli for the entire study period. Twenty-six participants (96.3 per cent; 95 per cent CI 89.2 to 100) carried ≥1 MDR E coli isolate during the six-week period, with seven participants (25.9 per cent) carrying ≥1 MDR isolate for at least five out of six weeks. The prevalence of faecal ESBL-producing E coli in cross-sectional participants is similar to asymptomatic general populations. However, much higher levels of carriage were observed longitudinally in participants. It is vital that veterinary hospitals implement gold-standard biosecurity to prevent transmission of MDR and ESBL-producing bacteria between patients and staff. Healthcare providers should be made aware that people working in veterinary hospitals are a high-risk population for carriage of MDR and ESBL-producing bacteria, and that this poses a risk to the carrier and for transmission of resistance throughout the wider community.

A newly developed tetraplex real-time RT-PCR for simultaneous screening of influenza virus types A, B, C and D

BACKGROUND

Human- or avian-to-swine transmissions have founded several autonomously circulating influenza A virus (IAV) lineages in swine populations that cause economically important respiratory disease. Little is known on other human influenza virus types, like B (IBV) and C (ICV) in European swine, and of the recently detected novel animal influenza virus type D (IDV).

OBJECTIVES

Development of a cost-effective diagnostic tool for large-scale surveillance programmes targeting all four influenza virus types.

METHODS

An influenza ABCD tetraplex real-time RT-PCR (RT-qPCR) was developed in the frame of this study. A selection of reference virus strains and more than 4000 porcine samples from a passive IAV surveillance programme in European swine with acute respiratory disease were examined.

RESULTS

Two IBV, a single IDV but no ICV infections were identified by tetraplex RT-qPCR. IBV and IDV results were confirmed by conventional RT-PCR and partial sequence analysis.

CONCLUSIONS

The tetraplex RT-qPCR proved fit for purpose as a sensitive, specific and high-throughput tool to study influenza virus transmission at the human-animal interface. Complementing close-meshed active virological and serological surveillance is required to better understand the true incidence and prevalence of influenza virus type B, C and D infections in swine.

From Theory to Practice: Translating Whole-Genome Sequencing (WGS) into the Clinic

Hospitals worldwide are facing an increasing incidence of hard-to-treat infections. Limiting infections and providing patients with optimal drug regimens require timely strain identification as well as virulence and drug-resistance profiling. Additionally, prophylactic interventions based on the identification of environmental sources of recurrent infections (e.g., contaminated sinks) and reconstruction of transmission chains (i.e., who infected whom) could help to reduce the incidence of nosocomial infections. WGS could hold the key to solving these issues. However, uptake in the clinic has been slow. Some major scientific and logistical challenges need to be solved before WGS fulfils its potential in clinical microbial diagnostics. In this review we identify major bottlenecks that need to be resolved for WGS to routinely inform clinical intervention and discuss possible solutions.

The phylogeography and incidence of multi-drug resistant typhoid fever in sub-Saharan Africa

There is paucity of data regarding the geographical distribution, incidence, and phylogenetics of multi-drug resistant (MDR) Salmonella Typhi in sub-Saharan Africa. Here we present a phylogenetic reconstruction of whole genome sequenced 249 contemporaneous S. Typhi isolated between 2008-2015 in 11 sub-Saharan African countries, in context of the 2,057 global S. Typhi genomic framework. Despite the broad genetic diversity, the majority of organisms (225/249; 90%) belong to only three genotypes, 4.3.1 (H58) (99/249; 40%), 3.1.1 (97/249; 39%), and 2.3.2 (29/249; 12%). Genotypes 4.3.1 and 3.1.1 are confined within East and West Africa, respectively. MDR phenotype is found in over 50% of organisms restricted within these dominant genotypes. High incidences of MDR S. Typhi are calculated in locations with a high burden of typhoid, specifically in children aged <15 years. Antimicrobial stewardship, MDR surveillance, and the introduction of typhoid conjugate vaccines will be critical for the control of MDR typhoid in Africa.

Typhoid fever is caused by the bacterium Salmonella Typhi. Here, Park et al. analyse the genomes of 249 S. Typhi isolates from 11 sub-Saharan African countries, identifying genes and plasmids associated with antibiotic resistance and showing that multi-drug resistance is highly pervasive in sub-Saharan Africa.

Hypermucoviscous capsular 1 (K1) serotype Klebsiella pneumoniae necrotising fasciitis and metastatic endophthalmitis

A 48-year-old man presented with a non-healing wound on his left foot after stepping on a nail. He self-medicated with amoxicillin, but the wound progressed prompting consult. On examination, his left foot was diffusely swollen with surrounding erythema, areas of gangrene, foul-smelling purulent discharge and subcutaneous emphysema. He was managed as a case of necrotising fasciitis and underwent emergent amputation. Three days after amputation, he developed a sudden and progressive blurring of vision, swelling and conjunctival erythema, with purulent discharge and the presence of hypopyon on the left eye. He was then managed as a case of endophthalmitis of the left eye and underwent pars plana vitrectomy. All cultures (blood, tissue and vitreous fluid) grew pan-susceptible hypermucoviscous Klebsiella pneumoniae, with positive string tests and confirmed by multilocus gene sequencing and sequence type analysis. He gradually improved with intravenous antibiotics, but only regained light perception in the left eye.

PANINI: Pangenome Neighbour Identification for Bacterial Populations

The standard workhorse for genomic analysis of the evolution of bacterial populations is phylogenetic modelling of mutations in the core genome. However, a notable amount of information about evolutionary and transmission processes in diverse populations can be lost unless the accessory genome is also taken into consideration. Here, we introduce panini (Pangenome Neighbour Identification for Bacterial Populations), a computationally scalable method for identifying the neighbours for each isolate in a data set using unsupervised machine learning with stochastic neighbour embedding based on the t-SNE (t-distributed stochastic neighbour embedding) algorithm. panini is browser-based and integrates with the Microreact platform for rapid online visualization and exploration of both core and accessory genome evolutionary signals, together with relevant epidemiological, geographical, temporal and other metadata. Several case studies with single- and multi-clone pneumococcal populations are presented to demonstrate the ability to identify biologically important signals from gene content data. panini is available at http://panini.pathogen.watch and code at http://gitlab.com/cgps/panini.

Genome-wide analysis of Streptococcus pneumoniae serogroup 19 in the decade after the introduction of pneumococcal conjugate vaccines in Australia

The decline in invasive pneumococcal disease (IPD), following the introduction of the 7-valent pneumococcal conjugate vaccination (PCV-7), was tempered by emergence of non-vaccine serotypes, particularly 19A. In Australia, three years after PCV-7 was replaced by PCV-13, containing 19A and 19F antigens, serogroup 19 was still a prominent cause of IPD in children under five. In this study we examined the evolution of serogroup 19 before and after introduction of paediatric vaccines in New South Wales (NSW), Australia. Genomes of 124 serogroup 19 IPD isolates collected before (2004) and after introduction of PCV-7 (2008) and PCV-13 (2014), from children under five in NSW, were analysed. Eleven core genome sequence clusters (cgSC) and 35 multilocus sequence types (ST) were identified. The majority (78/124) of the isolates belonged to four cgSCs: cgSC7 (ST199), cgSC11 (ST320), cgSC8 (ST63) and cgSC9 (ST2345). ST63 and ST2345 were exclusively serotype 19A and accounted for its predominantly intermediate penicillin resistance; these two clusters first appeared in 2008 and largely disappeared after introduction of PCV-13. Serogroup 19 was responsible for the highest proportion of vaccine failures in NSW. Relatively low immunogenicity of serogroup 19 antigens and Australia's three-dose vaccine schedule could affect the population dynamics of this serogroup.

Real-Time Analysis and Visualization of Pathogen Sequence Data

The rapid development of sequencing technologies has to led to an explosion of pathogen sequence data, which are increasingly collected as part of routine surveillance or clinical diagnostics. In public health, sequence data are used to reconstruct the evolution of pathogens, to anticipate future spread, and to target interventions. In clinical settings, whole-genome sequencing can identify pathogens at the strain level, can be used to predict phenotypes such as drug resistance and virulence, and can inform treatment by linking closely related cases. While sequencing has become cheaper, the analysis of sequence data has become an important bottleneck. Deriving interpretable and actionable results for a large variety of pathogens, each with its own complexity, from continuously updated data is a daunting task that requires flexible bioinformatic workflows and dissemination platforms. Here, we review recent developments in real-time analyses of pathogen sequence data, with a particular focus on the visualization and integration of sequence and phenotype data.

Patients with Chronic Obstructive Pulmonary Disease harbour a variation of Haemophilus species

H. haemolyticus is often misidentified as NTHi due to their close phylogenetic relationship. Differentiating between the two is important for correct identification and appropriate treatment of infective organism and to ensure any role of H. haemolyticus in disease is not being overlooked. Speciation however is not completely reliable by culture and PCR methods due to the loss of haemolysis by H. haemolyticus and the heterogeneity of NTHi. Haemophilus isolates from COPD as part of the AERIS study (ClinicalTrials - NCT01360398) were speciated by analysing sequence data for the presence of molecular markers. Further investigation into the genomic relationship was carried out using average nucleotide identity and phylogeny of allelic and genome alignments. Only 6.3% were identified as H. haemolyticus. Multiple in silico methods were able to distinguish H. haemolyticus from NTHi. However, no single gene target was found to be 100% accurate. A group of omp2 negative NTHi were observed to be phylogenetically divergent from H. haemolyticus and remaining NTHi. The presence of an atypical group from a geographically and disease limited set of isolates supports the theory that the heterogeneity of NTHi may provide a genetic continuum between NTHi and H. haemolyticus.

Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications

The PubMLST.org website hosts a collection of open-access, curated databases that integrate population sequence data with provenance and phenotype information for over 100 different microbial species and genera.  Although the PubMLST website was conceived as part of the development of the first multi-locus sequence typing (MLST) scheme in 1998 the software it uses, the Bacterial Isolate Genome Sequence database (BIGSdb, published in 2010), enables PubMLST to include all levels of sequence data, from single gene sequences up to and including complete, finished genomes.  Here we describe developments in the BIGSdb software made from publication to June 2018 and show how the platform realises microbial population genomics for a wide range of applications.  The system is based on the gene-by-gene analysis of microbial genomes, with each deposited sequence annotated and curated to identify the genes present and systematically catalogue their variation.  Originally intended as a means of characterising isolates with typing schemes, the synthesis of sequences and records of genetic variation with provenance and phenotype data permits highly scalable (whole genome sequence data for tens of thousands of isolates) means of addressing a wide range of functional questions, including: the prediction of antimicrobial resistance; likely cross-reactivity with vaccine antigens; and the functional activities of different variants that lead to key phenotypes.  There are no limitations to the number of sequences, genetic loci, allelic variants or schemes (combinations of loci) that can be included, enabling each database to represent an expanding catalogue of the genetic variation of the population in question.  In addition to providing web-accessible analyses and links to third-party analysis and visualisation tools, the BIGSdb software includes a RESTful application programming interface (API) that enables access to all the underlying data for third-party applications and data analysis pipelines.

Diagnosing Emerging Fungal Threats: A One Health Perspective

Emerging fungal pathogens are a growing threat to global health, ecosystems, food security, and the world economy. Over the last century, environmental change and globalized transport, twinned with the increasing application of antifungal chemical drugs have led to increases in outbreaks of fungal diseases with sometimes catastrophic effects. In order to tackle contemporary epidemics and predemic threats, there is a pressing need for a unified approach in identification and monitoring of fungal pathogens. In this paper, we discuss current high throughput technologies, as well as new platforms capable of combining diverse data types to inform practical epidemiological strategies with a focus on emerging fungal pathogens of wildlife.

Gene exchange drives the ecological success of a multi-host bacterial pathogen

The capacity for some pathogens to jump into different host-species populations is a major threat to public health and food security. Staphylococcus aureus is a multi-host bacterial pathogen responsible for important human and livestock diseases. Here, using a population-genomic approach, we identify humans as a major hub for ancient and recent S. aureus host-switching events linked to the emergence of endemic livestock strains, and cows as the main animal reservoir for the emergence of human epidemic clones. Such host-species transitions are associated with horizontal acquisition of genetic elements from host-specific gene pools conferring traits required for survival in the new host-niche. Importantly, genes associated with antimicrobial resistance are unevenly distributed among human and animal hosts, reflecting distinct antibiotic usage practices in medicine and agriculture. In addition to gene acquisition, genetic diversification has occurred in pathways associated with nutrient acquisition, implying metabolic remodelling after a host switch in response to distinct nutrient availability. For example, S. aureus from dairy cattle exhibit enhanced utilization of lactose-a major source of carbohydrate in bovine milk. Overall, our findings highlight the influence of human activities on the multi-host ecology of a major bacterial pathogen, underpinned by horizontal gene transfer and core genome diversification.

Pneumococcal vaccine impacts on the population genomics of non-typeable Haemophilus influenzae

The implementation of pneumococcal conjugate vaccines (PCVs) has led to a decline in vaccine-type disease. However, there is evidence that the epidemiology of non-typeable Haemophilus influenzae (NTHi) carriage and disease can be altered as a consequence of PCV introduction. We explored the epidemiological shifts in NTHi carriage using whole genome sequencing over a 5-year period that included PCV13 replacement of PCV7 in the UK’s National Immunization Programme in 2010. Between 2008/09 and 2012/13 (October to March), nasopharyngeal swabs were taken from children <5 years of age. Significantly increased carriage post-PCV13 was observed and lineage-specific associations with Streptococcus pneumoniae were seen before but not after PCV13 introduction. NTHi were characterized into 11 discrete, temporally stable lineages, congruent with current knowledge regarding the clonality of NTHi. The increased carriage could not be linked to the expansion of a particular clone and different co-carriage dynamics were seen before PCV13 implementation when NTHi co-carried with vaccine serotype pneumococci. In summary, PCV13 introduction has been shown to have an indirect effect on NTHi epidemiology and there exists both negative and positive, distinct associations between pneumococci and NTHi. This should be considered when evaluating the impacts of pneumococcal vaccine design and policy.

GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens

Current methods struggle to reconstruct and visualize the genomic relationships of large numbers of bacterial genomes. GrapeTree facilitates the analyses of large numbers of allelic profiles by a static “GrapeTree Layout” algorithm that supports interactive visualizations of large trees within a web browser window. GrapeTree also implements a novel minimum spanning tree algorithm (MSTree V2) to reconstruct genetic relationships despite high levels of missing data. GrapeTree is a stand-alone package for investigating phylogenetic trees plus associated metadata and is also integrated into EnteroBase to facilitate cutting edge navigation of genomic relationships among bacterial pathogens.

Genomic epidemiology of the commercially important pathogen Renibacterium salmoninarum within the Chilean salmon industry

Renibacterium salmoninarum is the causative agent of bacterial kidney disease (BKD), which is a commercially important disease of farmed salmonids. Typing by conventional methods provides limited information on the evolution and spread of this pathogen, as there is a low level of standing variation within the R. salmoninarum population. Here, we apply whole-genome sequencing to 42 R. salmoninarum isolates from Chile, primarily from salmon farms, in order to understand the epidemiology of BKD in this country. The patterns of genomic variation are consistent with multiple introductions to Chile, followed by rapid dissemination over a 30 year period. The estimated dates of introduction broadly coincide with major events in the development of the Chilean aquaculture industry. We find evidence for significant barriers to transmission of BKD in the Chilean salmon production chain that may also be explained by previously undescribed signals of host tropism in R. salmoninarum. Understanding the genomic epidemiology of BKD can inform disease intervention and improve sustainability of the economically important salmon industry. This article contains data hosted by Microreact.

INSaFLU: an automated open web-based bioinformatics suite "from-reads" for influenza whole-genome-sequencing-based surveillance

BACKGROUND

A new era of flu surveillance has already started based on the genetic characterization and exploration of influenza virus evolution at whole-genome scale. Although this has been prioritized by national and international health authorities, the demanded technological transition to whole-genome sequencing (WGS)-based flu surveillance has been particularly delayed by the lack of bioinformatics infrastructures and/or expertise to deal with primary next-generation sequencing (NGS) data.

RESULTS

We developed and implemented INSaFLU ("INSide the FLU"), which is the first influenza-oriented bioinformatics free web-based suite that deals with primary NGS data (reads) towards the automatic generation of the output data that are actually the core first-line "genetic requests" for effective and timely influenza laboratory surveillance (e.g., type and sub-type, gene and whole-genome consensus sequences, variants' annotation, alignments and phylogenetic trees). By handling NGS data collected from any amplicon-based schema, the implemented pipeline enables any laboratory to perform multi-step software intensive analyses in a user-friendly manner without previous advanced training in bioinformatics. INSaFLU gives access to user-restricted sample databases and projects management, being a transparent and flexible tool specifically designed to automatically update project outputs as more samples are uploaded. Data integration is thus cumulative and scalable, fitting the need for a continuous epidemiological surveillance during the flu epidemics. Multiple outputs are provided in nomenclature-stable and standardized formats that can be explored in situ or through multiple compatible downstream applications for fine-tuned data analysis. This platform additionally flags samples as "putative mixed infections" if the population admixture enrolls influenza viruses with clearly distinct genetic backgrounds, and enriches the traditional "consensus-based" influenza genetic characterization with relevant data on influenza sub-population diversification through a depth analysis of intra-patient minor variants. This dual approach is expected to strengthen our ability not only to detect the emergence of antigenic and drug resistance variants but also to decode alternative pathways of influenza evolution and to unveil intricate routes of transmission.

CONCLUSIONS

In summary, INSaFLU supplies public health laboratories and influenza researchers with an open "one size fits all" framework, potentiating the operationalization of a harmonized multi-country WGS-based surveillance for influenza virus. INSaFLU can be accessed through https://insaflu.insa.pt .

Recent Asian origin of chytrid fungi causing global amphibian declines

Globalized infectious diseases are causing species declines worldwide, but their source often remains elusive. We used whole-genome sequencing to solve the spatiotemporal origins of the most devastating panzootic to date, caused by the fungus Batrachochytrium dendrobatidis, a proximate driver of global amphibian declines. We traced the source of B. dendrobatidis to the Korean peninsula, where one lineage, BdASIA-1, exhibits the genetic hallmarks of an ancestral population that seeded the panzootic. We date the emergence of this pathogen to the early 20th century, coinciding with the global expansion of commercial trade in amphibians, and we show that intercontinental transmission is ongoing. Our findings point to East Asia as a geographic hotspot for B. dendrobatidis biodiversity and the original source of these lineages that now parasitize amphibians worldwide.

Laboratory and molecular surveillance of paediatric typhoidal Salmonella in Nepal: Antimicrobial resistance and implications for vaccine policy

Background

Children are substantially affected by enteric fever in most settings with a high burden of the disease, including Nepal. However pathogen population structure and transmission dynamics are poorly delineated in young children, the proposed target group for immunization programs. Here we present whole genome sequencing and antimicrobial susceptibility data on 198 S. Typhi and 66 S. Paratyphi A isolated from children aged 2 months to 15 years of age during blood culture surveillance at Patan Hospital, Nepal, 2008–2016.

Principal findings

S. Typhi was the dominant agent and comprised several distinct genotypes, dominated by 4.3.1 (H58). The heterogeneity of genotypes in children under five was reduced compared to data from 2005–2006, attributable to ongoing clonal expansion of H58. Most isolates (86%) were non-susceptible to fluoroquinolones, associated mainly with S. Typhi H58 lineage II and S. Paratyphi A harbouring mutations in the quinolone resistance-determining region (QRDR); non-susceptible strains from these groups accounted for 50% and 25% of all isolates. Multi-drug resistance (MDR) was rare (3.5% of S. Typhi, 0 S. Paratyphi A) and restricted to chromosomal insertions of resistance genes in H58 lineage I strains. Temporal analyses revealed a shift in dominance from H58 Lineage I to H58 Lineage II, with the latter being significantly more common after 2010. Comparison to global data sets showed the local S. Typhi and S. Paratyphi A strains had close genetic relatives in other South Asian countries, indicating regional strain circulation. Multiple imports from India of ciprofloxacin-resistant H58 lineage II strains were identified, but these were rare and showed no evidence of clonal replacement of local S. Typhi.

Significance

These data indicate that enteric fever in Nepal continues to be a major public health issue with ongoing inter- and intra-country transmission, and highlights the need for regional coordination of intervention strategies. The absence of a S. Paratyphi A vaccine is cause for concern, given its prevalence as a fluoroquinolone resistant enteric fever agent in this setting.

Multilocus Sequence Typing Reveals a New Cluster of Closely Related Candida tropicalis Genotypes in Italian Patients With Neurological Disorders

Candida tropicalis is a pathogenic yeast that has emerged as an important cause of candidemia especially in elderly patients with hematological malignancies. Infections caused by this species are mainly reported from Latin America and Asian-Pacific countries although recent epidemiological data revealed that C. tropicalis accounts for 6-16.4% of the Candida bloodstream infections (BSIs) in Italy by representing a relevant issue especially for patients receiving long-term hospital care. The aim of this study was to describe the genetic diversity of C. tropicalis isolates contaminating the hands of healthcare workers (HCWs) and hospital environments and/or associated with BSIs occurring in patients with different neurological disorders and without hematological disease. A total of 28 C. tropicalis isolates were genotyped using multilocus sequence typing analysis of six housekeeping (ICL1, MDR1, SAPT2, SAPT4, XYR1, and ZWF1) genes and data revealed the presence of only eight diploid sequence types (DSTs) of which 6 (75%) were completely new. Four eBURST clonal complexes (CC2, CC10, CC11, and CC33) contained all DSTs found in this study and the CC33 resulted in an exclusive, well-defined, clonal cluster from Italy. In conclusion, C. tropicalis could represent an important cause of BSIs in long-term hospitalized patients with no underlying hematological disease. The findings of this study also suggest a potential horizontal transmission of a specific C. tropicalis clone through hands of HCWs and expand our understanding of the molecular epidemiology of this pathogen whose population structure is still far from being fully elucidated as its complexity increases as different categories of patients and geographic areas are examined.

Zoonotic Transfer of Clostridium difficile Harboring Antimicrobial Resistance between Farm Animals and Humans

The emergence of Clostridium difficile as a significant human diarrheal pathogen is associated with the production of highly transmissible spores and the acquisition of antimicrobial resistance genes (ARGs) and virulence factors. Unlike the hospital-associated C. difficile RT027 lineage, the community-associated C. difficile RT078 lineage is isolated from both humans and farm animals; however, the geographical population structure and transmission networks remain unknown. Here, we applied whole-genome phylogenetic analysis of 248 C. difficile RT078 strains from 22 countries. Our results demonstrate limited geographical clustering for C. difficile RT078 and extensive coclustering of human and animal strains, thereby revealing a highly linked intercontinental transmission network between humans and animals. Comparative whole-genome analysis reveals indistinguishable accessory genomes between human and animal strains and a variety of antimicrobial resistance genes in the pangenome of C. difficile RT078. Thus, bidirectional spread of C. difficile RT078 between farm animals and humans may represent an unappreciated route disseminating antimicrobial resistance genes between humans and animals. These results highlight the importance of the "One Health" concept to monitor infectious disease emergence and the dissemination of antimicrobial resistance genes.

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.

Distinct Campylobacter fetus lineages adapted as livestock pathogens and human pathobionts in the intestinal microbiota

Campylobacter fetus is a venereal pathogen of cattle and sheep, and an opportunistic human pathogen. It is often assumed that C. fetus infection occurs in humans as a zoonosis through food chain transmission. Here we show that mammalian C. fetus consists of distinct evolutionary lineages, primarily associated with either human or bovine hosts. We use whole-genome phylogenetics on 182 strains from 17 countries to provide evidence that C. fetus may have originated in humans around 10,500 years ago and may have "jumped" into cattle during the livestock domestication period. We detect C. fetus genomes in 8% of healthy human fecal metagenomes, where the human-associated lineages are the dominant type (78%). Thus, our work suggests that C. fetus is an unappreciated human intestinal pathobiont likely spread by human to human transmission. This genome-based evolutionary framework will facilitate C. fetus epidemiology research and the development of improved molecular diagnostics and prevention schemes for this neglected pathogen.

Phandango: an interactive viewer for bacterial population genomics

Summary

Fully exploiting the wealth of data in current bacterial population genomics datasets requires synthesizing and integrating different types of analysis across millions of base pairs in hundreds or thousands of isolates. Current approaches often use static representations of phylogenetic, epidemiological, statistical and evolutionary analysis results that are difficult to relate to one another. Phandango is an interactive application running in a web browser allowing fast exploration of large-scale population genomics datasets combining the output from multiple genomic analysis methods in an intuitive and interactive manner.

Availability and implementation

Phandango is a web application freely available for use at www.phandango.net and includes a diverse collection of datasets as examples. Source code together with a detailed wiki page is available on GitHub at https://github.com/jameshadfield/phandango.

Food Safety in the Age of Next Generation Sequencing, Bioinformatics, and Open Data Access

Public health labs and food regulatory agencies globally are embracing whole genome sequencing (WGS) as a revolutionary new method that is positioned to replace numerous existing diagnostic and microbial typing technologies with a single new target: the microbial draft genome. The ability to cheaply generate large amounts of microbial genome sequence data, combined with emerging policies of food regulatory and public health institutions making their microbial sequences increasingly available and public, has served to open up the field to the general scientific community. This open data access policy shift has resulted in a proliferation of data being deposited into sequence repositories and of novel bioinformatics software designed to analyze these vast datasets. There also has been a more recent drive for improved data sharing to achieve more effective global surveillance, public health and food safety. Such developments have heightened the need for enhanced analytical systems in order to process and interpret this new type of data in a timely fashion. In this review we outline the emergence of genomics, bioinformatics and open data in the context of food safety. We also survey major efforts to translate genomics and bioinformatics technologies out of the research lab and into routine use in modern food safety labs. We conclude by discussing the challenges and opportunities that remain, including those expected to play a major role in the future of food safety science.

Whole genome sequencing of Shigella sonnei through PulseNet Latin America and Caribbean: advancing global surveillance of foodborne illnesses

Objectives

Shigella sonnei is a globally important diarrhoeal pathogen tracked through the surveillance network PulseNet Latin America and Caribbean (PNLA&C), which participates in PulseNet International. PNLA&C laboratories use common molecular techniques to track pathogens causing foodborne illness. We aimed to demonstrate the possibility and advantages of transitioning to whole genome sequencing (WGS) for surveillance within existing networks across a continent where S. sonnei is endemic.

Methods

We applied WGS to representative archive isolates of S. sonnei (n = 323) from laboratories in nine PNLA&C countries to generate a regional phylogenomic reference for S. sonnei and put this in the global context. We used this reference to contextualise 16 S. sonnei from three Argentinian outbreaks, using locally generated sequence data. Assembled genome sequences were used to predict antimicrobial resistance (AMR) phenotypes and identify AMR determinants.

Results

S. sonnei isolates clustered in five Latin American sublineages in the global phylogeny, with many (46%, 149 of 323) belonging to previously undescribed sublineages. Predicted multidrug resistance was common (77%, 249 of 323), and clinically relevant differences in AMR were found among sublineages. The regional overview showed that Argentinian outbreak isolates belonged to distinct sublineages and had different epidemiologic origins.

Conclusions

Latin America contains novel genetic diversity of S. sonnei that is relevant on a global scale and commonly exhibits multidrug resistance. Retrospective passive surveillance with WGS has utility for informing treatment, identifying regionally epidemic sublineages and providing a framework for interpretation of prospective, locally sequenced outbreaks.

The Promise of Whole Genome Pathogen Sequencing for the Molecular Epidemiology of Emerging Aquaculture Pathogens

Aquaculture is the fastest growing food-producing sector, and the sustainability of this industry is critical both for global food security and economic welfare. The management of infectious disease represents a key challenge. Here, we discuss the opportunities afforded by whole genome sequencing of bacterial and viral pathogens of aquaculture to mitigate disease emergence and spread. We outline, by way of comparison, how sequencing technology is transforming the molecular epidemiology of pathogens of public health importance, emphasizing the importance of community-oriented databases and analysis tools.

Identification of IncA/C Plasmid Replication and Maintenance Genes and Development of a Plasmid Multilocus Sequence Typing Scheme

Plasmids of incompatibility group A/C (IncA/C) are becoming increasingly prevalent within pathogenic Enterobacteriaceae They are associated with the dissemination of multiple clinically relevant resistance genes, including bla_CMY and bla_NDM Current typing methods for IncA/C plasmids offer limited resolution. In this study, we present the complete sequence of a bla_NDM-1-positive IncA/C plasmid, pMS6198A, isolated from a multidrug-resistant uropathogenic Escherichia coli strain. Hypersaturated transposon mutagenesis, coupled with transposon-directed insertion site sequencing (TraDIS), was employed to identify conserved genetic elements required for replication and maintenance of pMS6198A. Our analysis of TraDIS data identified roles for the replicon, including repA, a toxin-antitoxin system; two putative partitioning genes, parAB; and a putative gene, 053 Construction of mini-IncA/C plasmids and examination of their stability within E. coli confirmed that the region encompassing 053 contributes to the stable maintenance of IncA/C plasmids. Subsequently, the four major maintenance genes (repA, parAB, and 053) were used to construct a new plasmid multilocus sequence typing (PMLST) scheme for IncA/C plasmids. Application of this scheme to a database of 82 IncA/C plasmids identified 11 unique sequence types (STs), with two dominant STs. The majority of bla_NDM-positive plasmids examined (15/17; 88%) fall into ST1, suggesting acquisition and subsequent expansion of this bla_NDM-containing plasmid lineage. The IncA/C PMLST scheme represents a standardized tool to identify, track, and analyze the dissemination of important IncA/C plasmid lineages, particularly in the context of epidemiological studies.