Polymerase chain reaction for the in vitro detection of the pESI plasmid associated with the globally circulating Salmonella Infantis outbreak strain.

A globally circulating strain of Salmonella enterica serotype Infantis containing the pESI plasmid has increased in prevalence in poultry meat samples and cases of human infections. In this study, a polymerase chain reaction (PCR) protocol was designed to detect the pESI plasmid and confirm the Infantis serotype of Salmonella isolates. Primers were tested bioinformatically to predict specificity, sensitivity, and precision. A total of 54 isolates of Salmonella serotypes Infantis, Senftenberg, and Alachua were tested, with and without the pESI plasmid carriage. Isolates of 31 additional serotypes were also screened to confirm specificity to Infantis. Specificity, sensitivity, and precision of each primer were >0.95. All isolates tested produced the expected band sizes. This PCR protocol provides a rapid and clear result for the detection of the pESI plasmid and serotype Infantis and will allow for the in vitro detection for epidemiological studies where whole-genome sequencing is not available.

Chewie Nomenclature Server (chewie-NS): a deployable nomenclature server for easy sharing of core and whole genome MLST schemas.

Chewie Nomenclature Server (chewie-NS, https://chewbbaca.online/) allows users to share genome-based gene-by-gene typing schemas and to maintain a common nomenclature, simplifying the comparison of results. The combination between local analyses and a public repository of allelic data strikes a balance between potential confidentiality issues and the need to compare results. The possibility of deploying private instances of chewie-NS facilitates the creation of nomenclature servers with a restricted user base to allow compliance with the strictest data policies. Chewie-NS allows users to easily share their own schemas and to explore publicly available schemas, including informative statistics on schemas and loci presented in interactive charts and tables. Users can retrieve all the information necessary to run a schema locally or all the alleles identified at a particular locus. The integration with the chewBBACA suite enables users to directly upload new schemas to chewie-NS, download existing schemas and synchronize local and remote schemas from chewBBACA command line version, allowing an easier integration into high-throughput analysis pipelines. The same REST API linking chewie-NS and the chewBBACA suite supports the interaction of other interfaces or pipelines with the databases available at chewie-NS, facilitating the reusability of the stored data.

Distance-based phylogenetic inference from typing data: a unifying view.

Typing methods are widely used in the surveillance of infectious diseases, outbreaks investigation and studies of the natural history of an infection. Moreover, their use is becoming standard, in particular with the introduction of high-throughput sequencing. On the other hand, the data being generated are massive and many algorithms have been proposed for a phylogenetic analysis of typing data, addressing both correctness and scalability issues. Most of the distance-based algorithms for inferring phylogenetic trees follow the closest pair joining scheme. This is one of the approaches used in hierarchical clustering. Moreover, although phylogenetic inference algorithms may seem rather different, the main difference among them resides on how one defines cluster proximity and on which optimization criterion is used. Both cluster proximity and optimization criteria rely often on a model of evolution. In this work, we review, and we provide a unified view of these algorithms. This is an important step not only to better understand such algorithms but also to identify possible computational bottlenecks and improvements, important to deal with large data sets.

Two multi-fragment recombination events resulted in the ß-lactam-resistant serotype 11A-ST6521 related to Spain9V-ST156 pneumococcal clone spreading in south-western Europe, 2008 to 2016.

BackgroundThe successful pneumococcal clone Spain9V-ST156 (PMEN3) is usually associated with vaccine serotypes 9V and 14.AimOur objective was to analyse the increase of a serotype 11A variant of PMEN3 as cause of invasive pneumococcal disease (IPD) in Spain and its spread in south-western Europe.MethodsWe conducted a prospective multicentre study of adult IPD in Spain (2008-16). Furthermore, a subset of 61 penicillin-resistant serotype 11A isolates from France, Italy, Portugal and Spain were subjected to whole genome sequencing (WGS) and compared with 238 genomes from the European Nucleotide Archive (ENA).ResultsAlthough the incidence of serotype 11A in IPD was stable, a clonal shift was detected from CC62 (penicillin-susceptible) to CC156 (penicillin-resistant). By WGS, three major 11A-CC156 lineages were identified, linked to ST156 (n = 5 isolates; France, Italy and Portugal), ST166 (n = 4 isolates; France and Portugal) and ST838/6521 (n = 52 isolates; France, Portugal and Spain). Acquisition of the 11A capsule allowed to escape vaccine effect. AP200 (11A-ST62) was the donor for ST156 and ST838/6521 but not for ST166. In-depth analysis of ST838/6521 lineage showed two multi-fragment recombination events including four and seven fragments from an 11A-ST62 and an NT-ST344 representative, respectively.ConclusionThe increase in penicillin-resistant serotype 11A IPD in Spain was linked to the spread of a vaccine escape PMEN3 recombinant clone. Several recombination events were observed in PMEN3 acquiring an 11A capsule. The most successful 11A-PMEN3 lineage spreading in south-western Europe appeared after two multi-fragment recombination events with representatives of two major pneumococcal clones (11A-ST62 and NT-ST344).

DEN-IM: dengue virus genotyping from amplicon and shotgun metagenomic sequencing.

Dengue virus (DENV) represents a public health threat and economic burden in affected countries. The availability of genomic data is key to understanding viral evolution and dynamics, supporting improved control strategies. Currently, the use of high-throughput sequencing (HTS) technologies, which can be applied both directly to patient samples (shotgun metagenomics) and to PCR-amplified viral sequences (amplicon sequencing), is potentially the most informative approach to monitor viral dissemination and genetic diversity by providing, in a single methodological step, identification and characterization of the whole viral genome at the nucleotide level. Despite many advantages, these technologies require bioinformatics expertise and appropriate infrastructure for the analysis and interpretation of the resulting data. In addition, the many software solutions available can hamper the reproducibility and comparison of results. Here we present DEN-IM, a one-stop, user-friendly, containerized and reproducible workflow for the analysis of DENV short-read sequencing data from both amplicon and shotgun metagenomics approaches. It is able to infer the DENV coding sequence (CDS), identify the serotype and genotype, and generate a phylogenetic tree. It can easily be run on any UNIX-like system, from local machines to high-performance computing clusters, performing a comprehensive analysis without the requirement for extensive bioinformatics expertise. Using DEN-IM, we successfully analysed two types of DENV datasets. The first comprised 25 shotgun metagenomic sequencing samples from patients with variable serotypes and genotypes, including an in vitro spiked sample containing the four known serotypes. The second consisted of 106 paired-end and 76 single-end amplicon sequences of DENV 3 genotype III and DENV 1 genotype I, respectively, where DEN-IM allowed detection of the intra-genotype diversity. The DEN-IM workflow, parameters and execution configuration files, and documentation are freely available at https://github.com/B-UMMI/DEN-IM).

BacPipe: A Rapid, User-Friendly Whole-Genome Sequencing Pipeline for Clinical Diagnostic Bacteriology.

Despite rapid advances in whole genome sequencing (WGS) technologies, their integration into routine microbiological diagnostics has been hampered by the lack of standardized downstream bioinformatics analysis. We developed a comprehensive and computationally low-resource bioinformatics pipeline (BacPipe) enabling direct analyses of bacterial whole-genome sequences (raw reads or contigs) obtained from second- or third-generation sequencing technologies. A graphical user interface was developed to visualize real-time progression of the analysis. The scalability and speed of BacPipe in handling large datasets was demonstrated using 4,139 Illumina paired-end sequence files of publicly available bacterial genomes (2.9-5.4 Mb) from the European Nucleotide Archive. BacPipe is integrated in EBI-SELECTA, a project-specific portal (H2020-COMPARE), and is available as an independent docker image that can be used across Windows- and Unix-based systems. BacPipe offers a fully automated "one-stop" bacterial WGS analysis pipeline to overcome the major hurdle of WGS data analysis in hospitals and public-health and for infection control monitoring.

Distinct Phenotypic and Genomic Signatures Underlie Contrasting Pathogenic Potential of Staphylococcus epidermidis Clonal Lineages.

Background: Staphylococcus epidermidis is a common skin commensal that has emerged as a pathogen in hospitals, mainly related to medical devices-associated infections. Noteworthy, infection rates by S. epidermidis have the tendency to rise steeply in next decades together with medical devices use and immunocompromized population growth. Staphylococcus epidermidis population structure includes two major clonal lineages (A/C and B) that present contrasting pathogenic potentials. To address this distinction and explore the basis of increased pathogenicity of A/C lineage, we performed a detailed comparative analysis using phylogenetic and integrated pangenome-wide-association study (panGWAS) approaches and compared the lineages's phenotypes in in vitro conditions mimicking carriage and infection. Results: Each S. epidermidis lineage had distinct phenotypic signatures in skin and infection conditions and differed in genomic content. Combination of phenotypic and genotypic data revealed that both lineages were well adapted to skin environmental cues. However, they appear to occupy different skin niches, perform distinct biological functions in the skin and use different mechanisms to complete the same function: lineage B strains showed evidence of specialization to survival in microaerobic and lipid rich environment, characteristic of hair follicle and sebaceous glands; lineage A/C strains showed evidence for adaption to diverse osmotic and pH conditions, potentially allowing them to occupy a broader and more superficial skin niche. In infection conditions, A/C strains had an advantage, having the potential to bind blood-associated host matrix proteins, form biofilms at blood pH, resist antibiotics and macrophage acidity and to produce proteases. These features were observed to be rare in the lineage B strains. PanGWAS analysis produced a catalog of putative S. epidermidis virulence factors and identified an epidemiological molecular marker for the more pathogenic lineage. Conclusion: The prevalence of A/C lineage in infection is probably related to a higher metabolic and genomic versatility that allows rapid adaptation during transition from a commensal to a pathogenic lifestyle. The putative virulence and phenotypic factors associated to A/C lineage constitute a reliable framework for future studies on S. epidermidis pathogenesis and the finding of an epidemiological marker for the more pathogenic lineage is an asset for the management of S. epidermidis infections.

Author Correction: Critical steps in clinical shotgun metagenomics for the concomitant detection and typing of microbial pathogens.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Plasmid ATLAS: plasmid visual analytics and identification in high-throughput sequencing data.

Plasmid ATLAS (pATLAS, http://www.patlas.site) provides an easy-to-use web accessible database with visual analytics tools to explore the relationships of plasmids available in NCBI's RefSeq database. pATLAS has two main goals: (i) to provide an easy way to search for plasmids deposited in NCBI RefSeq and their associated metadata; (ii) to visualize the relationships of plasmids in a graph, allowing the exploration of plasmid evolution. pATLAS allows searching by plasmid name, bacterial host taxa, antibiotic resistance and virulence genes, plasmid families, and by sequence length and similarity. pATLAS is also able to represent in the plasmid network, plasmid sets identified by external pipelines using mapping, mash screen or assembly from high-throughput sequencing data. By representing the identified hits within the network of relationships between plasmids, allowing the possibility of removing redundant results, and by taking advantage of the browsing capabilities of pATLAS, users can more easily interpret the pipelines' results. All these analyses can be saved to a JSON file for sharing and future re-evaluation. Furthermore, by offering a REST-API, the pATLAS database and network display are easily accessible by other interfaces or pipelines.

Critical steps in clinical shotgun metagenomics for the concomitant detection and typing of microbial pathogens.

High throughput sequencing has been proposed as a one-stop solution for diagnostics and molecular typing directly from patient samples, allowing timely and appropriate implementation of measures for treatment, infection prevention and control. However, it is unclear how the variety of available methods impacts the end results. We applied shotgun metagenomics on diverse types of patient samples using three different methods to deplete human DNA prior to DNA extraction. Libraries were prepared and sequenced with Illumina chemistry. Data was analyzed using methods likely to be available in clinical microbiology laboratories using genomics. The results of microbial identification were compared to standard culture-based microbiological methods. On average, 75% of the reads corresponded to human DNA, being a major determinant in the analysis outcome. None of the kits was clearly superior suggesting that the initial ratio between host and microbial DNA or other sample characteristics were the major determinants of the proportion of microbial reads. Most pathogens identified by culture were also identified through metagenomics, but substantial differences were noted between the taxonomic classification tools. In two cases the high number of human reads resulted in insufficient sequencing depth of bacterial DNA for identification. In three samples, we could infer the probable multilocus sequence type of the most abundant species. The tools and databases used for taxonomic classification and antimicrobial resistance identification had a key impact on the results, recommending that efforts need to be aimed at standardization of the analysis methods if metagenomics is to be used routinely in clinical microbiology.

Large-Scale Simulations of Bacterial Populations Over Complex Networks.

The understanding of bacterial population genetics and evolution is crucial in epidemic outbreak studies and pathogen surveillance. However, all epidemiological studies are limited to their sampling capacities which, by being usually biased or limited due to economic constraints, can hamper the real knowledge of the bacterial population structure of a given species. To this end, mathematical models and large-scale simulations can provide a quantitative analytical framework that can be used to assess how or if limited sampling can infer the true population structure. In this article, we address the large-scale simulation of genetic evolution of bacterial populations, using Wright-Fisher model, in the presence of complex host contact networks. We present an efficient approach for large-scale simulations over complex host contact networks, using MapReduce on top of Apache Spark and GraphX API. We evaluate the relation between cluster computing power and simulations speedup and include insights on how bacterial population diversity can be affected by mutation and recombination rates, and network topology.

Fast phylogenetic inference from typing data.

BACKGROUND: Microbial typing methods are commonly used to study the relatedness of bacterial strains. Sequence-based typing methods are a gold standard for epidemiological surveillance due to the inherent portability of sequence and allelic profile data, fast analysis times and their capacity to create common nomenclatures for strains or clones. This led to development of several novel methods and several databases being made available for many microbial species. With the mainstream use of High Throughput Sequencing, the amount of data being accumulated in these databases is huge, storing thousands of different profiles. On the other hand, computing genetic evolutionary distances among a set of typing profiles or taxa dominates the running time of many phylogenetic inference methods. It is important also to note that most of genetic evolution distance definitions rely, even if indirectly, on computing the pairwise Hamming distance among sequences or profiles. RESULTS: We propose here an average-case linear-time algorithm to compute pairwise Hamming distances among a set of taxa under a given Hamming distance threshold. This article includes both a theoretical analysis and extensive experimental results concerning the proposed algorithm. We further show how this algorithm can be successfully integrated into a well known phylogenetic inference method, and how it can be used to speedup querying local phylogenetic patterns over large typing databases.

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.

Clinical and molecular epidemiology of Acinetobacter baumannii bloodstream infections in an endemic setting.

AIM: The transmission dynamics of Acinetobacter baumannii in endemic settings, and the relation between microbial properties and patients' clinical outcomes, are yet obscure and hampered by insufficient metadata. METHODS & RESULTS: Of 20 consecutive patients with A. baumannii bloodstream infection that were thoroughly analyzed at a single center, at least one transmission opportunity was evident for 85% of patients. This implies that patient-to-patient transmission is the major mode of A. baumannii acquisitions in health facilities. Moreover, all patients who died immediately (<24 h of admission) were infected with a single clone (ST457; relative risk = 1.6; p = 0.05). CONCLUSION: This preliminary analysis should prompt further investigation by mapping genomic virulence determinants among A. baumannii ST457 lineage compared with other strains.

PHYLOViZ 2.0: providing scalable data integration and visualization for multiple phylogenetic inference methods.

High Throughput Sequencing provides a cost effective means of generating high resolution data for hundreds or even thousands of strains, and is rapidly superseding methodologies based on a few genomic loci. The wealth of genomic data deposited on public databases such as Sequence Read Archive/European Nucleotide Archive provides a powerful resource for evolutionary analysis and epidemiological surveillance. However, many of the analysis tools currently available do not scale well to these large datasets, nor provide the means to fully integrate ancillary data. Here we present PHYLOViZ 2.0, an extension of PHYLOViZ tool, a platform independent Java tool that allows phylogenetic inference and data visualization for large datasets of sequence based typing methods, including Single Nucleotide Polymorphism (SNP) and whole genome/core genome Multilocus Sequence Typing (wg/cgMLST) analysis. PHYLOViZ 2.0 incorporates new data analysis algorithms and new visualization modules, as well as the capability of saving projects for subsequent work or for dissemination of results. AVAILABILITY AND IMPLEMENTATION: http://www.phyloviz.net/ (licensed under GPLv3). CONTACT: cvaz@inesc-id.ptSupplementary information: Supplementary data are available at Bioinformatics online.

Beta-hemolytic Streptococcus dysgalactiae strains isolated from horses are a genetically distinct population within the Streptococcus dysgalactiae taxon.

The pathogenic role of beta-hemolytic Streptococcus dysgalactiae in the equine host is increasingly recognized. A collection of 108 Lancefield group C (n = 96) or L (n = 12) horse isolates recovered in the United States and in three European countries presented multilocus sequence typing (MLST) alleles, sequence types and emm types (only 56% of the isolates could be emm typed) that were, with few exceptions, distinct from those previously found in human Streptococcus dysgalactiae subsp. equisimilis. Characterization of a subset of horse isolates by multilocus sequence analysis (MLSA) and 16S rRNA gene sequence showed that most equine isolates could also be differentiated from S. dysgalactiae strains from other animal species, supporting the existence of a horse specific genomovar. Draft genome information confirms the distinctiveness of the horse genomovar and indicates the presence of potentially horse-specific virulence factors. While this genomovar represents most of the isolates recovered from horses, a smaller MLST and MLSA defined sub-population seems to be able to cause infections in horses, other animals and humans, indicating that transmission between hosts of strains belonging to this group may occur.

Not seeing the forest for the trees: size of the minimum spanning trees (MSTs) forest and branch significance in MST-based phylogenetic analysis.

Trees, including minimum spanning trees (MSTs), are commonly used in phylogenetic studies. But, for the research community, it may be unclear that the presented tree is just a hypothesis, chosen from among many possible alternatives. In this scenario, it is important to quantify our confidence in both the trees and the branches/edges included in such trees. In this paper, we address this problem for MSTs by introducing a new edge betweenness metric for undirected and weighted graphs. This spanning edge betweenness metric is defined as the fraction of equivalent MSTs where a given edge is present. The metric provides a per edge statistic that is similar to that of the bootstrap approach frequently used in phylogenetics to support the grouping of taxa. We provide methods for the exact computation of this metric based on the well known Kirchhoff's matrix tree theorem. Moreover, we implement and make available a module for the PHYLOViZ software and evaluate the proposed metric concerning both effectiveness and computational performance. Analysis of trees generated using multilocus sequence typing data (MLST) and the goeBURST algorithm revealed that the space of possible MSTs in real data sets is extremely large. Selection of the edge to be represented using bootstrap could lead to unreliable results since alternative edges are present in the same fraction of equivalent MSTs. The choice of the MST to be presented, results from criteria implemented in the algorithm that must be based in biologically plausible models.

Phylogenetic and clonality analysis of Bacillus pumilus isolates uncovered a highly heterogeneous population of different closely related species and clones.

Bacillus pumilus is a Gram-positive bacterium with a wide range of attributed applications, namely as a plant growth promoting rhizobacteria (PGPR), animal, and human probiotic. However, a rare putative role in human diseases has been reported, namely in food poisoning or as anthrax-like cutaneous infectious agent. This species is difficult to distinguish from its closely related species on the basis of phenotypic or biochemical characteristics and 16S rRNA gene sequences. In this study, the phylogenetic analysis of gyrB and rpoB gene sequences of a collection of isolates previously identified as B. pumilus, assigned most of them (93%, 38 of 41 isolates) to B. safensis or to the new recently described B. invictae. Moreover, we extended the previously reported recognized habitats of these species and unveiled a human health or biotechnological relevance (e.g. as implicated in food poisoning or PGPR) for them. Additionally, we demonstrated that both B. safensis and B. invictae species encompass a clonally diverse population, which can justify their great adaptation ability to different niches, with evidence of clonal-host specificity.

Bacillus invictae sp. nov., isolated from a health product.

A Gram-positive, rod-shaped, endospore-forming Bacillus isolate, Bi.(FFUP1) (T), recovered in Portugal from a health product was subjected to a polyphasic study and compared with the type strains of Bacillus pumilus, Bacillus safensis, Bacillus altitudinis and Bacillus xiamenensis, the phenotypically and genotypically most closely related species. Acid production from cellobiose, D-glucose and D-mannose and absence of acid production from D-arabinose, erythritol, inositol, maltose, mannitol, raffinose, rhamnose, sorbitol, starch and L-tryptophan discriminated this new isolate from the type strains of the most closely related species. Additionally, a significant different protein and carbohydrate signature was evidenced by spectroscopic techniques, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and Fourier transform IR spectroscopy with attenuated total reflectance. Using a chemometric approach, the score plot generated by principal component analysis clearly delineated the isolate as a separate cluster. The quinone system for strain Bi.(FFUP1) (T) comprised predominantly menaquinone MK-7 and major polar lipids were diphosphatidylglycerol, an unidentified phospholipid and an unidentified glycolipid. Strain Bi.(FFUP1) (T) showed ≥ 99% 16S rRNA gene sequence similarity to B. safensis FO-036b(T), B. pumilus (7061(T) and SAFR-032), B. altitudinis 41KF2b(T) and B. xiamenensis HYC-10(T). Differences in strain Bi.FFUP1 (T) gyrB and rpoB sequences in comparison with the most closely related species and DNA-DNA hybridization experiments with Bi.FFUP1 (T) and B. pumilus ATCC 7061(T), B. safensis FO-036b(T), B. altitudinis 41KF2b(T) and B. xiamenensis HYC-10(T) gave relatedness values of 39.6% (reciprocal 38.0%), 49.9% (reciprocal 42.9%), 61.9% (reciprocal 52.2%) and 61.7% (reciprocal 49.2%), respectively, supported the delineation of strain Bi.(FFUP1) (T) as a representative of a novel species of the genus Bacillus, for which the name Bacillus invictae sp. nov. is proposed, with strain Bi.(FFUP1) (T) ( =DSM 26896(T) =CCUG 64113(T)) as the type strain.

Scarlet fever is caused by a limited number of Streptococcus pyogenes lineages and is associated with the exotoxin genes ssa, speA and speC.

BACKGROUND: Several outbreaks of scarlet fever caused by Streptococcus pyogenes were recently reported. Scarlet fever is historically considered a toxin-mediated disease, dependent on the production of the exotoxins SpeA and SpeC, but a strict association between scarlet fever and these exotoxins is not always detected. The aims of this study were to characterize the scarlet fever bacterial isolates recovered from patients in a Lisbon hospital and to identify any distinctive characteristics of such isolates. METHODS: We characterized a collection of 303 pharyngeal S. pyogenes collected between 2002 and 2008. One-hundred and one were isolated from scarlet fever patients and 202 were associated to a diagnosis of tonsillo-pharyngitis. Isolates were characterized by T and emm typing, pulsed field gel electrophoresis profiling and superantigen gene profiling. RESULTS: The diversity of the scarlet fever isolates was lower than that of the pharyngitis isolates. Specific lineages of emm87, emm4 and emm3 were overrepresented in scarlet fever isolates but only 1 pulsed field gel electrophoresis major lineage was significantly associated with scarlet fever. Multivariate analysis indicated associations of ssa, speA and speC with scarlet fever. CONCLUSIONS: In nonoutbreak conditions, scarlet fever is caused by a number of distinct genetic lineages. The lower diversity of these isolates and the association with specific exotoxin genes indicates that some lineages are more prone to cause this presentation than others even in nonoutbreak conditions.