- Volume 5, Issue 1, 2019
Volume 5, Issue 1, 2019
- Outbreak Report
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- Genomic Methodologies
- Data Clustering Methods
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Genomic approaches used to investigate an atypical outbreak of Salmonella Adjame
In 2017, an outbreak of gastroenteritis in England attributed to Salmonella Adjame was detected and investigated. With the introduction of whole genome sequencing (WGS) for microbial typing, methods for comparing international outbreak data require evaluation. A case was defined as a person resident in England with a clinical sample from 1 June 2017 to 27 July 2017 from whom S. Adjame was isolated. Cases were interviewed and exposures analysed. Backward tracing of food provenance was undertaken. WGS was performed on isolates from cases and historical isolates and compared using Public Health England’s SnapperDB high-quality SNP pipeline and Enterobase’s Salmonella core genome multi-locus sequence typing (cgMLST) scheme. In total, 14 cases were identified. The majority were vegetarian, probably of South Asian descent, with a median age of 66.5 years with no recent international travel reported. Cases consumed a range of fresh food products including herbs and spices bought from South Asian grocers. Backward tracing did not identify a common source. WGS typing showed sub-clustering and considerable genetic variation across human samples. cgMLST allele-based analysis was comparable to SNP-derived phylogenetic analysis and clusters were defined using each method. Imported herbs or spices were suspected vehicles. The cases were linked in time and place but WGS showed marked heterogeneity, atypical of a point source Salmonella outbreak. The application of incorporating SNP or allelic differences into the case definition may not always be appropriate. With further validation, cgMLST could be used for international outbreak alerts when WGS analysis is being undertaken to facilitate comparison.
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- Research Article
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- Microbial Evolution and Epidemiology
- Communicable Disease Genomics
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Multi-step genomic dissection of a suspected intra-hospital Helicobacter cinaedi outbreak
Helicobacter cinaedi is an emerging pathogen causing bacteraemia and cellulitis. Nosocomial transmission of this microbe has been described, but detailed molecular-epidemiological analyses have not been performed. Here, we describe the results of a multi-step genome-wide phylogenetic analysis of a suspected intra-hospital outbreak of H. cinaedi that occurred in a hospital in Japan. The outbreak was recognized by the infectious control team (ICT) of the hospital as a sudden increase in H. cinaedi bacteraemia. ICT defined this outbreak case based on 16S rRNA sequence data and epidemiological information, but were unable to determine the source and route of the infections. We therefore re-investigated this case using whole-genome sequencing (WGS). We first performed a species-wide analysis using publicly available genome sequences to understand the level of genomic diversity of this under-studied species. The clusters identified were then separately analysed using the genome sequence of a representative strain in each cluster as a reference. These analyses provided a high-level phylogenetic resolution of each cluster, identified a confident set of outbreak isolates, and discriminated them from other closely related but distinct clones, which were locally circulating and invaded the hospital during the same period. By considering the epidemiological data, possible strain transmission chains were inferred, which highlighted the role of asymptomatic carriers or environmental contamination. The emergence of a subclone with increased resistance to fluoroquinolones in the outbreak was also recognized. Our results demonstrate the impact of the use of a closely related genome as a reference to maximize the power of WGS.
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Shared genome analyses of notable listeriosis outbreaks, highlighting the critical importance of epidemiological evidence, input datasets and interpretation criteria
Aleisha Reimer, Kelly Weedmark, Aaron Petkau, Christy-Lynn Peterson, Matthew Walker, Natalie Knox, Heather Kent, Philip Mabon, Chrystal Berry, Shaun Tyler, Lorelee Tschetter, Morganne Jerome, Vanessa Allen, Linda Hoang, Sadjia Bekal, Clifford Clark, Celine Nadon, Gary Van Domselaar, Franco Pagotto, Morag Graham, Jeff Farber and Matthew GilmourThe 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.
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- Mechanisms of Evolution
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Evolution of a clade of Acinetobacter baumannii global clone 1, lineage 1 via acquisition of carbapenem- and aminoglycoside-resistance genes and dispersion of ISAba1
More LessResistance to carbapenem and aminoglycoside antibiotics is a critical problem in Acinetobacter baumannii , particularly when genes conferring resistance are acquired by multiply or extensively resistant members of successful globally distributed clonal complexes, such as global clone 1 (GC1) . Here, we investigate the evolution of an expanding clade of lineage 1 of the GC1 complex via repeated acquisition of carbapenem- and aminoglycoside-resistance genes. Lineage 1 arose in the late 1970s and the Tn6168/OCL3 clade arose in the late 1990s from an ancestor that had already acquired resistance to third-generation cephalosporins and fluoroquinolones. Between 2000 and 2002, two distinct subclades have emerged, and they are distinguishable via the presence of an integrated phage genome in subclade 1 and AbaR4 (carrying the oxa23 carbapenem-resistance gene in Tn2006) at a specific chromosomal location in subclade 2. Part or all of the original resistance gene cluster in the chromosomally located AbaR3 has been lost from some isolates, but plasmids carrying alternate resistance genes have been gained. In one group in subclade 2, the chromosomally located AbGRI3, carrying the armA aminoglycoside-resistance gene, has been acquired from a GC2 isolate and incorporated via homologous recombination. ISAba1 entered the common ancestor of this clade as part of the cephalosporin-resistance transposon Tn6168 and has dispersed differently in each subclade. Members of subclade 1 share an ISAba1 in one specific position in the chromosome and in subclade 2 two different ISAba1 locations are shared. Further shared ISAba1 locations distinguish further divisions, potentially providing simple markers for epidemiological studies.
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- Microbe-Niche Interactions
- Pathogenesis
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Genomic analysis of bacteria in the Acute Oak Decline pathobiome
More LessThe UK’s native oak is under serious threat from Acute Oak Decline (AOD). Stem tissue necrosis is a primary symptom of AOD and several bacteria are associated with necrotic lesions. Two members of the lesion pathobiome, Brenneria goodwinii and Gibbsiella quercinecans , have been identified as causative agents of tissue necrosis. However, additional bacteria including Lonsdalea britannica and Rahnella species have been detected in the lesion microbiome, but their role in tissue degradation is unclear. Consequently, information on potential genome-encoded mechanisms for tissue necrosis is critical to understand the role and mechanisms used by bacterial members of the lesion pathobiome in the aetiology of AOD. Here, the whole genomes of bacteria isolated from AOD-affected trees were sequenced, annotated and compared against canonical bacterial phytopathogens and non-pathogenic symbionts. Using orthologous gene inference methods, shared virulence genes that retain the same function were identified. Furthermore, functional annotation of phytopathogenic virulence genes demonstrated that all studied members of the AOD lesion microbiota possessed genes associated with phytopathogens. However, the genome of B. goodwinii was the most characteristic of a necrogenic phytopathogen, corroborating previous pathological and metatranscriptomic studies that implicate it as the key causal agent of AOD lesions. Furthermore, we investigated the genome sequences of other AOD lesion microbiota to understand the potential ability of microbes to cause disease or contribute to pathogenic potential of organisms isolated from this complex pathobiome. The role of these members remains uncertain but some such as G. quercinecans may contribute to tissue necrosis through the release of necrotizing enzymes and may help more dangerous pathogens activate and realize their pathogenic potential or they may contribute as secondary/opportunistic pathogens with the potential to act as accessory species for B. goodwinii . We demonstrate that in combination with ecological data, whole genome sequencing provides key insights into the pathogenic potential of bacterial species whether they be phytopathogens, part-contributors or stimulators of the pathobiome.
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- Systems Microbiology
- Pangenome Analysis, Big-Data Approaches
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Where the plasmids roam: large-scale sequence analysis reveals plasmids with large host ranges
More LessDescribing the role of plasmids and their contribution to the exchange of genetic material among bacteria is essential for understanding the fields of plasmid epidemiology, microbial ecology, and commercial and synthetic microbiology. Broad-host-range (BHR) plasmids are those that are found not only in a single bacterial species, but in members of different taxonomic groups and are of significant interest to researchers in many fields. We applied a novel approach to computationally identify new BHR plasmids, in which we searched for highly similar cognate plasmids within a comprehensive plasmid database. After identifying 125 plasmid groups with highly similar cognates found in multiple taxa, we closely examined BHR plasmids found in multiple families. The majority of our identified BHR plasmids are found in members of the Enterobacteriaceae and closely related taxa, while three BHR plasmids of potential commercial significance were found in two species of Cyanobacteria . One plasmid with an exceptionally broad host range was found in both Gram-positive and Gram-negative bacterial species. This analysis demonstrates the utility of this method in identifying new BHR plasmids while highlighting unknown ranges of previously documented plasmids.
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- Methods
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- Genomic Methodologies
- Novel Phylogenetic Methods
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HomoplasyFinder: a simple tool to identify homoplasies on a phylogeny
More LessA homoplasy is a nucleotide identity resulting from a process other than inheritance from a common ancestor. Importantly, by distorting the ancestral relationships between nucleotide sequences, homoplasies can change the structure of the phylogeny. Homoplasies can emerge naturally, especially under high selection pressures and/or high mutation rates, or be created during the generation and processing of sequencing data. Identification of homoplasies is critical, both to understand their influence on the analyses of phylogenetic data and to allow an investigation into how they arose. Here we present HomoplasyFinder, a java application that can be used as a stand-a-lone tool or within the statistical programming environment R. Within R and Java, HomoplasyFinder is shown to be able to automatically, and quickly, identify any homoplasies present in simulated and real phylogenetic data. HomoplasyFinder can easily be incorporated into existing analysis pipelines, either within or outside of R, allowing the user to quickly identify homoplasies to inform downstream analyses and interpretation.
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