MLST revisited: the gene-by-gene approach to bacterial genomics

Defining the Core Genome of Salmonella enterica Serovar Typhimurium for Genomic Surveillance and Epidemiological Typing

Salmonella enterica serovar Typhimurium is the most common Salmonella serovar causing foodborne infections in Australia and many other countries. Twenty-one S. Typhimurium strains from Salmonella reference collection A (SARA) were analyzed using Illumina high-throughput genome sequencing. Single nucleotide polymorphisms (SNPs) in 21 SARA strains ranged from 46 to 11,916 SNPs, with an average of 1,577 SNPs per strain. Together with 47 strains selected from publicly available S. Typhimurium genomes, the S. Typhimurium core genes (STCG) were determined. The STCG consist of 3,846 genes, a set that is much larger than that of the 2,882 Salmonella core genes (SCG) found previously. The STCG together with 1,576 core intergenic regions (IGRs) were defined as the S. Typhimurium core genome. Using 93 S. Typhimurium genomes from 13 epidemiologically confirmed community outbreaks, we demonstrated that typing based on the S. Typhimurium core genome (STCG plus core IGRs) provides superior resolution and higher discriminatory power than that based on SCG for outbreak investigation and molecular epidemiology of S. Typhimurium. STCG and STCG plus core IGR typing achieved 100% separation of all outbreaks compared to that of SCG typing, which failed to separate isolates from two outbreaks from background isolates. Defining the S. Typhimurium core genome allows standardization of genes/regions to be used for high-resolution epidemiological typing and genomic surveillance of S. Typhimurium.

Using multilocus sequence typing to study bacterial variation: prospects in the genomic era

Multilocus sequence typing (MLST) indexes the sequence variation present in a small number (usually seven) of housekeeping gene fragments located around the bacterial genome. Unique alleles at these loci are assigned arbitrary integer identifiers, which effectively summarizes the variation present in several thousand base pairs of genome sequence information as a series of numbers. Comparing bacterial isolates using allele-based methods efficiently corrects for the effects of lateral gene transfer present in many bacterial populations and is computationally efficient. This 'gene-by-gene' approach can be applied to larger collections of loci, such as the ribosomal protein genes used in ribosomal MLST (rMLST), up to and including the complete set of coding sequences present in a genome, whole-genome MLST (wgMLST), providing scalable, efficient and readily interpreted genome analysis.

Ecological Overlap and Horizontal Gene Transfer in Staphylococcus aureus and Staphylococcus epidermidis

The opportunistic pathogens Staphylococcus aureus and Staphylococcus epidermidis represent major causes of severe nosocomial infection, and are associated with high levels of mortality and morbidity worldwide. These species are both common commensals on the human skin and in the nasal pharynx, but are genetically distinct, differing at 24% average nucleotide divergence in 1,478 core genes. To better understand the genome dynamics of these ecologically similar staphylococcal species, we carried out a comparative analysis of 324 S. aureus and S. epidermidis genomes, including 83 novel S. epidermidis sequences. A reference pan-genome approach and whole genome multilocus-sequence typing revealed that around half of the genome was shared between the species. Based on a BratNextGen analysis, homologous recombination was found to have impacted on 40% of the core genes in S. epidermidis, but on only 24% of the core genes in S. aureus. Homologous recombination between the species is rare, with a maximum of nine gene alleles shared between any two S. epidermidis and S. aureus isolates. In contrast, there was considerable interspecies admixture of mobile elements, in particular genes associated with the SaPIn1 pathogenicity island, metal detoxification, and the methicillin-resistance island SCCmec. Our data and analysis provide a context for considering the nature of recombinational boundaries between S. aureus and S. epidermidis and, the selective forces that influence realized recombination between these species.

Measurably evolving pathogens in the genomic era

Current sequencing technologies have created unprecedented opportunities for studying microbial populations. For pathogens with comparatively low per-site mutation rates, such as DNA viruses and bacteria, whole-genome sequencing can reveal the accumulation of novel genetic variation between population samples taken at different times. The concept of 'measurably evolving populations' and related analytical approaches have provided powerful insights for fast-evolving RNA viruses, but their application to other pathogens is still in its infancy. We argue that previous distinctions between slow- and fast-evolving pathogens become blurred once evolution is assessed at a genome-wide scale, and we highlight important analytical challenges to be overcome to infer pathogen population dynamics from genomic data.

Multilocus sequence analysis (MLSA) in prokaryotic taxonomy

To obtain a higher resolution of the phylogenetic relationships of species within a genus or genera within a family, multilocus sequence analysis (MLSA) is currently a widely used method. In MLSA studies, partial sequences of genes coding for proteins with conserved functions ('housekeeping genes') are used to generate phylogenetic trees and subsequently deduce phylogenies. However, MLSA is not only suggested as a phylogenetic tool to support and clarify the resolution of bacterial species with a higher resolution, as in 16S rRNA gene-based studies, but has also been discussed as a replacement for DNA-DNA hybridization (DDH) in species delineation. Nevertheless, despite the fact that MLSA has become an accepted and widely used method in prokaryotic taxonomy, no common generally accepted recommendations have been devised to date for either the whole area of microbial taxonomy or for taxa-specific applications of individual MLSA schemes. The different ways MLSA is performed can vary greatly for the selection of genes, their number, and the calculation method used when comparing the sequences obtained. Here, we provide an overview of the historical development of MLSA and critically review its current application in prokaryotic taxonomy by highlighting the advantages and disadvantages of the method's numerous variations. This provides a perspective for its future use in forthcoming genome-based genotypic taxonomic analyses.

Proteotyping: Proteomic characterization, classification and identification of microorganisms--A prospectus

Modern microbial systematics requires a range of methodologies for the comprehensive characterization, classification and identification of microorganisms. While whole-genome sequences provide the ultimate reference for defining microbial phylogeny and taxonomy, selected biomarker-based strategies continue to provide the means for the bulk of microbial systematic studies. Proteomics, the study of the expression of genes, as well as the structure and function of the resulting proteins, offers indirect measures of genome sequence data. Recent developments in applications of proteomics for analyzing microorganisms have paralleled the growing microbial genome sequence database, as well as the evolution of mass spectrometry (MS) instrumentation and bioinformatics. MALDI-TOF MS, which generates proteomic mass patterns for 'fingerprint'-based characterizations, has provided a marked breakthrough for microbial identification. However, MALDI-TOF MS is limited in the number of targets that can be detected for strain characterization. Advanced methods of tandem mass spectrometry, in which proteins and peptides generated from proteins, are characterized and identified, using LC-MS/MS, provide the ability to detect hundreds or thousands of expressed microbial strain markers for high-resolution characterizations and identifications. Model studies demonstrate the application of proteomics-based analyses for bacterial species- and strain-level detection and identification and for characterization of environmentally relevant, metabolically diverse bacteria. Proteomics-based approaches represent an emerging complement to traditional methods of characterizing microorganisms, enabling the elucidation of the expressed biomarkers of genome sequence information, which can be applied to 'proteotyping' applications of microorganisms at all taxonomic levels.

First step in using molecular data for microbial food safety risk assessment; hazard identification of Escherichia coli O157:H7 by coupling genomic data with in vitro adherence to human epithelial cells

The potential for using whole genome sequencing (WGS) data in microbiological risk assessment (MRA) has been discussed on several occasions since the beginning of this century. Still, the proposed heuristic approaches have never been applied in a practical framework. This is due to the non-trivial problem of mapping microbial information consisting of thousands of loci onto a probabilistic scale for risks. The paradigm change for MRA involves translation of multidimensional microbial genotypic information to much reduced (integrated) phenotypic information and onwards to a single measure of human risk (i.e. probability of illness).

In this paper a first approach in methodology development is described for the application of WGS data in MRA; this is supported by a practical example. That is, combining genetic data (single nucleotide polymorphisms; SNPs) for Shiga toxin-producing Escherichia coli (STEC) O157 with phenotypic data (in vitro adherence to epithelial cells as a proxy for virulence) leads to hazard identification in a Genome Wide Association Study (GWAS).

This application revealed practical implications when using SNP data for MRA. These can be summarized by considering the following main issues: optimum sample size for valid inference on population level, correction for population structure, quantification and calibration of results, reproducibility of the analysis, links with epidemiological data, anchoring and integration of results into a systems biology approach for the translation of molecular studies to human health risk.

Future developments in genetic data analysis for MRA should aim at resolving the mapping problem of processing genetic sequences to come to a quantitative description of risk. The development of a clustering scheme focusing on biologically relevant information of the microbe involved would be a useful approach in molecular data reduction for risk assessment.

Rapid high resolution genotyping of Francisella tularensis by whole genome sequence comparison of annotated genes ("MLST+")

The zoonotic disease tularemia is caused by the bacterium Francisella tularensis. This pathogen is considered as a category A select agent with potential to be misused in bioterrorism. Molecular typing based on DNA-sequence like canSNP-typing or MLVA has become the accepted standard for this organism. Due to the organism's highly clonal nature, the current typing methods have reached their limit of discrimination for classifying closely related subpopulations within the subspecies F. tularensis ssp. holarctica. We introduce a new gene-by-gene approach, MLST+, based on whole genome data of 15 sequenced F. tularensis ssp. holarctica strains and apply this approach to investigate an epidemic of lethal tularemia among non-human primates in two animal facilities in Germany. Due to the high resolution of MLST+ we are able to demonstrate that three independent clones of this highly infectious pathogen were responsible for these spatially and temporally restricted outbreaks.

Proficiency testing for bacterial whole genome sequencing: an end-user survey of current capabilities, requirements and priorities

The advent of next-generation sequencing (NGS) has revolutionised public health microbiology. Given the potential impact of NGS, it is paramount to ensure standardisation of 'wet' laboratory and bioinformatic protocols and promote comparability of methods employed by different laboratories and their outputs. Therefore, one of the ambitious goals of the Global Microbial Identifier (GMI) initiative (http://www.globalmicrobialidentifier.org/) has been to establish a mechanism for inter-laboratory NGS proficiency testing (PT). This report presents findings from the survey recently conducted by Working Group 4 among GMI members in order to ascertain NGS end-use requirements and attitudes towards NGS PT. The survey identified the high professional diversity of laboratories engaged in NGS-based public health projects and the wide range of capabilities within institutions, at a notable range of costs. The priority pathogens reported by respondents reflected the key drivers for NGS use (high burden disease and 'high profile' pathogens). The performance of and participation in PT was perceived as important by most respondents. The wide range of sequencing and bioinformatics practices reported by end-users highlights the importance of standardisation and harmonisation of NGS in public health and underpins the use of PT as a means to assuring quality. The findings of this survey will guide the design of the GMI PT program in relation to the spectrum of pathogens included, testing frequency and volume as well as technical requirements. The PT program for external quality assurance will evolve and inform the introduction of NGS into clinical and public health microbiology practice in the post-genomic era.

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.

Ribosomal protein biomarkers provide root nodule bacterial identification by MALDI-TOF MS

Accurate identification of soil bacteria that form nitrogen-fixing associations with legume crops is challenging given the phylogenetic diversity of root nodule bacteria (RNB). The labor-intensive and time-consuming 16S ribosomal RNA (rRNA) sequencing and/or multilocus sequence analysis (MLSA) of conserved genes so far remain the favored molecular tools to characterize symbiotic bacteria. With the development of mass spectrometry (MS) as an alternative method to rapidly identify bacterial isolates, we recently showed that matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) can accurately characterize RNB found inside plant nodules or grown in cultures. Here, we report on the development of a MALDI-TOF RNB-specific spectral database built on whole cell MS fingerprints of 116 strains representing the major rhizobial genera. In addition to this RNB-specific module, which was successfully tested on unknown field isolates, a subset of 13 ribosomal proteins extracted from genome data was found to be sufficient for the reliable identification of nodule isolates to rhizobial species as shown in the putatively ascribed ribosomal protein masses (PARPM) database. These results reveal that data gathered from genome sequences can be used to expand spectral libraries to aid the accurate identification of bacterial species by MALDI-TOF MS.

BMX: a tool for computing bacterial phyletic composition from orthologous maps

Background

New sequencing technologies have made it possible to explore genetic diversity at higher resolution in microbial populations. However, our understanding evolutionary relationships, and comparison of closely and distantly related bacterial genomes from these massive datasets remains a formidable challenge. Numerous clustering algorithms that group genomic data based on homology have been developed, but new tools are still required to analyse the resultant orthologous maps to understand functional genetic similarities and their phyletic patterns (patterns of presence of absence of genes).

Findings

Bacterial Makeup eXplorer (BMX) implements an algorithm that swiftly and efficiently facilitates the determination of the number of orthologs in prokaryotic genomes employing a reference free approach, which may be further exploited to transfer of gene annotations. BMX is able to integrate orthologous maps of highly diverse prokaryotic genomes therefore making it possible to perform robust and scalable, multi-platform, high quality annotation transfer and gene-by-gene composition assessment method. In addition results are presented in the form of publication quality figures.

Conclusions

BMX allows extensive data analysis of orthologous map databases to understand underlying biological relationships. Furthermore, BMX is portable across different platforms and can be installed easily. In summary, BMX allows higher resolution analysis of genomes from diverse bacterial populations

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-015-1017-z) contains supplementary material, which is available to authorized users.

Concordance and discordance of sequence survey methods for molecular epidemiology

The post-genomic era is characterized by the direct acquisition and analysis of genomic data with many applications, including the enhancement of the understanding of microbial epidemiology and pathology. However, there are a number of molecular approaches to survey pathogen diversity, and the impact of these different approaches on parameter estimation and inference are not entirely clear. We sequenced whole genomes of bacterial pathogens, Burkholderia pseudomallei, Yersinia pestis, and Brucella spp. (60 new genomes), and combined them with 55 genomes from GenBank to address how different molecular survey approaches (whole genomes, SNPs, and MLST) impact downstream inferences on molecular evolutionary parameters, evolutionary relationships, and trait character associations. We selected isolates for sequencing to represent temporal, geographic origin, and host range variability. We found that substitution rate estimates vary widely among approaches, and that SNP and genomic datasets yielded different but strongly supported phylogenies. MLST yielded poorly supported phylogenies, especially in our low diversity dataset, i.e., Y. pestis. Trait associations showed that B. pseudomallei and Y. pestis phylogenies are significantly associated with geography, irrespective of the molecular survey approach used, while Brucella spp. phylogeny appears to be strongly associated with geography and host origin. We contrast inferences made among monomorphic (clonal) and non-monomorphic bacteria, and between intra- and inter-specific datasets. We also discuss our results in light of underlying assumptions of different approaches.

ClonalFrameML: efficient inference of recombination in whole bacterial genomes

Recombination is an important evolutionary force in bacteria, but it remains challenging to reconstruct the imports that occurred in the ancestry of a genomic sample. Here we present ClonalFrameML, which uses maximum likelihood inference to simultaneously detect recombination in bacterial genomes and account for it in phylogenetic reconstruction. ClonalFrameML can analyse hundreds of genomes in a matter of hours, and we demonstrate its usefulness on simulated and real datasets. We find evidence for recombination hotspots associated with mobile elements in Clostridium difficile ST6 and a previously undescribed 310kb chromosomal replacement in Staphylococcus aureus ST582. ClonalFrameML is freely available at http://clonalframeml.googlecode.com/.

A genome-based identification approach for members of the genus Bifidobacterium

During recent years, the significant and increasing interest in novel bifidobacterial strains with health-promoting characteristics has catalyzed the development of methods for efficient and reliable identification of Bifidobacterium strains at (sub) species level. We developed an assay based on recently acquired bifidobacterial genomic data and involving 98 primer pairs, called the Bifidobacterium-ampliseq panel. This panel includes multiplex PCR primers that target both core and variable genes of the pangenome of this genus. Our results demonstrate that the employment of the Bifidobacterium-ampliseq panel allows rapid and specific identification of the so far recognized 48 (sub)species harboring the Bifidobacterium genus, and thus represents a cost- and time-effective bifidobacterial screening methodology.

Practical benefits of knowing the enemy: modern molecular tools for diagnosing the etiology of bacterial diseases and understanding the taxonomy and diversity of plant-pathogenic bacteria

Knowing the identity of bacterial plant pathogens is essential to strategic and sustainable disease management in agricultural systems. This knowledge is critical for growers, diagnosticians, extension agents, and others dealing with crops. However, such identifications are linked to bacterial taxonomy, a complicated and changing discipline that depends on methods and information that are often not used by those who are diagnosing field problems. Modern molecular tools for fingerprinting and sequencing allow for pathogen identification in the absence of distinguishing or conveniently tested phenotypic characteristics. These methods are also useful in studying the etiology and epidemiology of phytopathogenic bacteria from epidemics, as was done in numerous studies conducted in California's Salinas Valley. Multilocus and whole-genome sequence analyses are becoming the cornerstones of studies of microbial diversity and bacterial taxonomy. Whole-genome sequence analysis needs to become adequately accessible, automated, and affordable in order to be used routinely for identification and epidemiology. The power of molecular tools in accurately identifying bacterial pathogenesis is therefore of value to the farmer, diagnostician, phytobacteriologist, and taxonomist.

SNP typing for germplasm identification of Amomum villosum Lour. Based on DNA barcoding markers

Amomum villosum Lour., produced from Yangchun, Guangdong Province, China, is a Daodi medicinal material of Amomi Fructus in traditional Chinese medicine. This herb germplasm should be accurately identified and collected to ensure its quality and safety in medication. In the present study, single nucleotide polymorphism typing method was evaluated on the basis of DNA barcoding markers to identify the germplasm of Amomi Fructus. Genomic DNA was extracted from the leaves of 29 landraces representing three Amomum species (A. villosum Lour., A. xanthioides Wall. ex Baker and A. longiligulare T. L. Wu) by using the CTAB method. Six barcoding markers (ITS, ITS2, LSU D1–D3, matK, rbcL and trnH-psbA) were PCR amplified and sequenced; SNP typing and phylogenetic analysis were performed to differentiate the landraces. Results showed that high-quality bidirectional sequences were acquired for five candidate regions (ITS, ITS2, LSU D1–D3, matK, and rbcL) except trnH-psbA. Three ribosomal regions, namely, ITS, ITS2, and LSU D1–D3, contained more SNP genotypes (STs) than the plastid genes rbcL and matK. In the 29 specimens, 19 STs were detected from the combination of four regions (ITS, LSU D1–D3, rbcL, and matK). Phylogenetic analysis results further revealed two clades. Minimum-spanning tree demonstrated the existence of two main groups: group I was consisting of 9 STs (ST1–8 and ST11) of A. villosum Lour., and group II was composed of 3 STs (ST16–18) of A. longiligulare T.L. Wu. Our results suggested that ITS and LSU D1–D3 should be incorporated with the core barcodes rbcL and matK. The four combined regions could be used as a multiregional DNA barcode to precisely differentiate the Amomi Fructus landraces in different producing areas.

A gene-by-gene population genomics platform: de novo assembly, annotation and genealogical analysis of 108 representative Neisseria meningitidis genomes

BACKGROUND

Highly parallel, 'second generation' sequencing technologies have rapidly expanded the number of bacterial whole genome sequences available for study, permitting the emergence of the discipline of population genomics. Most of these data are publically available as unassembled short-read sequence files that require extensive processing before they can be used for analysis. The provision of data in a uniform format, which can be easily assessed for quality, linked to provenance and phenotype and used for analysis, is therefore necessary.

RESULTS

The performance of de novo short-read assembly followed by automatic annotation using the pubMLST.org Neisseria database was assessed and evaluated for 108 diverse, representative, and well-characterised Neisseria meningitidis isolates. High-quality sequences were obtained for >99% of known meningococcal genes among the de novo assembled genomes and four resequenced genomes and less than 1% of reassembled genes had sequence discrepancies or misassembled sequences. A core genome of 1600 loci, present in at least 95% of the population, was determined using the Genome Comparator tool. Genealogical relationships compatible with, but at a higher resolution than, those identified by multilocus sequence typing were obtained with core genome comparisons and ribosomal protein gene analysis which revealed a genomic structure for a number of previously described phenotypes. This unified system for cataloguing Neisseria genetic variation in the genome was implemented and used for multiple analyses and the data are publically available in the PubMLST Neisseria database.

CONCLUSIONS

The de novo assembly, combined with automated gene-by-gene annotation, generates high quality draft genomes in which the majority of protein-encoding genes are present with high accuracy. The approach catalogues diversity efficiently, permits analyses of a single genome or multiple genome comparisons, and is a practical approach to interpreting WGS data for large bacterial population samples. The method generates novel insights into the biology of the meningococcus and improves our understanding of the whole population structure, not just disease causing lineages.

Cronobacter, the emergent bacterial pathogen Enterobacter sakazakii comes of age; MLST and whole genome sequence analysis

BACKGROUND

Following the association of Cronobacter spp. to several publicized fatal outbreaks in neonatal intensive care units of meningitis and necrotising enterocolitis, the World Health Organization (WHO) in 2004 requested the establishment of a molecular typing scheme to enable the international control of the organism. This paper presents the application of Next Generation Sequencing (NGS) to Cronobacter which has led to the establishment of the Cronobacter PubMLST genome and sequence definition database (http://pubmlst.org/cronobacter/) containing over 1000 isolates with metadata along with the recognition of specific clonal lineages linked to neonatal meningitis and adult infections

RESULTS

Whole genome sequencing and multilocus sequence typing (MLST) has supports the formal recognition of the genus Cronobacter composed of seven species to replace the former single species Enterobacter sakazakii. Applying the 7-loci MLST scheme to 1007 strains revealed 298 definable sequence types, yet only C. sakazakii clonal complex 4 (CC4) was principally associated with neonatal meningitis. This clonal lineage has been confirmed using ribosomal-MLST (51-loci) and whole genome-MLST (1865 loci) to analyse 107 whole genomes via the Cronobacter PubMLST database. This database has enabled the retrospective analysis of historic cases and outbreaks following re-identification of those strains.

CONCLUSIONS

The Cronobacter PubMLST database offers a central, open access, reliable sequence-based repository for researchers. It has the capacity to create new analysis schemes 'on the fly', and to integrate metadata (source, geographic distribution, clinical presentation). It is also expandable and adaptable to changes in taxonomy, and able to support the development of reliable detection methods of use to industry and regulatory authorities. Therefore it meets the WHO (2004) request for the establishment of a typing scheme for this emergent bacterial pathogen. Whole genome sequencing has additionally shown a range of potential virulence and environmental fitness traits which may account for the association of C. sakazakii CC4 pathogenicity, and propensity for neonatal CNS.

Multilocus sequence analysis of Anaplasma phagocytophilum reveals three distinct lineages with different host ranges in clinically ill French cattle

Molecular epidemiology represents a powerful approach to elucidate the complex epidemiological cycles of multi-host pathogens, such as Anaplasma phagocytophilum. A. phagocytophilum is a tick-borne bacterium that affects a wide range of wild and domesticated animals. Here, we characterized its genetic diversity in populations of French cattle; we then compared the observed genotypes with those found in horses, dogs, and roe deer to determine whether genotypes of A. phagocytophilum are shared among different hosts. We sampled 120 domesticated animals (104 cattle, 13 horses, and 3 dogs) and 40 wild animals (roe deer) and used multilocus sequence analysis on nine loci (ankA, msp4, groESL, typA, pled, gyrA, recG, polA, and an intergenic region) to characterize the genotypes of A. phagocytophilum present. Phylogenic analysis revealed three genetic clusters of bacterial variants in domesticated animals. The two principal clusters included 98% of the bacterial genotypes found in cattle, which were only distantly related to those in roe deer. One cluster comprised only cattle genotypes, while the second contained genotypes from cattle, horses, and dogs. The third contained all roe deer genotypes and three cattle genotypes. Geographical factors could not explain this clustering pattern. These results suggest that roe deer do not contribute to the spread of A. phagocytophilum in cattle in France. Further studies should explore if these different clusters are associated with differing disease severity in domesticated hosts. Additionally, it remains to be seen if the three clusters of A. phagocytophilum genotypes in cattle correspond to distinct epidemiological cycles, potentially involving different reservoir hosts.

Genome sequencing of an extended series of NDM-producing Klebsiella pneumoniae isolates from neonatal infections in a Nepali hospital characterizes the extent of community- versus hospital-associated transmission in an endemic setting

NDM-producing Klebsiella pneumoniae strains represent major clinical and infection control challenges, particularly in resource-limited settings with high rates of antimicrobial resistance. Determining whether transmission occurs at a gene, plasmid, or bacterial strain level and within hospital and/or the community has implications for monitoring and controlling spread. Whole-genome sequencing (WGS) is the highest-resolution typing method available for transmission epidemiology. We sequenced carbapenem-resistant K. pneumoniae isolates from 26 individuals involved in several infection case clusters in a Nepali neonatal unit and 68 other clinical Gram-negative isolates from a similar time frame, using Illumina and PacBio technologies. Within-outbreak chromosomal and closed-plasmid structures were generated and used as data set-specific references. Three temporally separated case clusters were caused by a single NDM K. pneumoniae strain with a conserved set of four plasmids, one being a 304,526-bp plasmid carrying bla(NDM-1). The plasmids contained a large number of antimicrobial/heavy metal resistance and plasmid maintenance genes, which may have explained their persistence. No obvious environmental/human reservoir was found. There was no evidence of transmission of outbreak plasmids to other Gram-negative clinical isolates, although bla(NDM) variants were present in other isolates in different genetic contexts. WGS can effectively define complex antimicrobial resistance epidemiology. Wider sampling frames are required to contextualize outbreaks. Infection control may be effective in terminating outbreaks caused by particular strains, even in areas with widespread resistance, although this study could not demonstrate evidence supporting specific interventions. Larger, detailed studies are needed to characterize resistance genes, vectors, and host strains involved in disease, to enable effective intervention.

Clinical detection and characterization of bacterial pathogens in the genomics era

The availability of genome sequences obtained using next-generation sequencing (NGS) has revolutionized the field of infectious diseases. Indeed, more than 38,000 bacterial and 5,000 viral genomes have been sequenced to date, including representatives of all significant human pathogens. These tremendous amounts of data have not only enabled advances in fundamental biology, helping to understand the pathogenesis of microorganisms and their genomic evolution, but have also had implications for clinical microbiology. Here, we first review the current achievements of genomics in the development of improved diagnostic tools, including those that are now available in the clinic, such as the design of PCR assays for the detection of microbial pathogens, virulence factors or antibiotic-resistance determinants, or the design of optimized culture media for 'unculturable' pathogens. We then review the applications of genomics to the investigation of outbreaks, either through the design of genotyping assays or the direct sequencing of the causative strains. Finally, we discuss how genomics might change clinical microbiology in the future.

The domestication of the probiotic bacterium Lactobacillus acidophilus

Lactobacillus acidophilus is a Gram-positive lactic acid bacterium that has had widespread historical use in the dairy industry and more recently as a probiotic. Although L. acidophilus has been designated as safe for human consumption, increasing commercial regulation and clinical demands for probiotic validation has resulted in a need to understand its genetic diversity. By drawing on large, well-characterised collections of lactic acid bacteria, we examined L. acidophilus isolates spanning 92 years and including multiple strains in current commercial use. Analysis of the whole genome sequence data set (34 isolate genomes) demonstrated L. acidophilus was a low diversity, monophyletic species with commercial isolates essentially identical at the sequence level. Our results indicate that commercial use has domesticated L. acidophilus with genetically stable, invariant strains being consumed globally by the human population.

Phylogenomic and MALDI-TOF MS analysis of Streptococcus sinensis HKU4T reveals a distinct phylogenetic clade in the genus Streptococcus

Streptococcus sinensis is a recently discovered human pathogen isolated from blood cultures of patients with infective endocarditis. Its phylogenetic position, as well as those of its closely related species, remains inconclusive when single genes were used for phylogenetic analysis. For example, S. sinensis branched out from members of the anginosus, mitis, and sanguinis groups in the 16S ribosomal RNA gene phylogenetic tree, but it was clustered with members of the anginosus and sanguinis groups when groEL gene sequences used for analysis. In this study, we sequenced the draft genome of S. sinensis and used a polyphasic approach, including concatenated genes, whole genomes, and matrix-assisted laser desorption ionization-time of flight mass spectrometry to analyze the phylogeny of S. sinensis. The size of the S. sinensis draft genome is 2.06 Mb, with GC content of 42.2%. Phylogenetic analysis using 50 concatenated genes or whole genomes revealed that S. sinensis formed a distinct cluster with Streptococcus oligofermentans and Streptococcus cristatus, and these three streptococci were clustered with the “sanguinis group.” As for phylogenetic analysis using hierarchical cluster analysis of the mass spectra of streptococci, S. sinensis also formed a distinct cluster with S. oligofermentans and S. cristatus, but these three streptococci were clustered with the “mitis group.” On the basis of the findings, we propose a novel group, named “sinensis group,” to include S. sinensis, S. oligofermentans, and S. cristatus, in the Streptococcus genus. Our study also illustrates the power of phylogenomic analyses for resolving ambiguities in bacterial taxonomy.

TypOn: the microbial typing ontology

Abstract

Bacterial identification and characterization at subspecies level is commonly known as Microbial Typing. Currently, these methodologies are fundamental tools in Clinical Microbiology and bacterial population genetics studies to track outbreaks and to study the dissemination and evolution of virulence or pathogenicity factors and antimicrobial resistance. Due to advances in DNA sequencing technology, these methods have evolved to become focused on sequence-based methodologies. The need to have a common understanding of the concepts described and the ability to share results within the community at a global level are increasingly important requisites for the continued development of portable and accurate sequence-based typing methods, especially with the recent introduction of Next Generation Sequencing (NGS) technologies. In this paper, we present an ontology designed for the sequence-based microbial typing field, capable of describing any of the sequence-based typing methodologies currently in use and being developed, including novel NGS based methods. This is a fundamental step to accurately describe, analyze, curate, and manage information for microbial typing based on sequence based typing methods.

Multi Locus Sequence Typing scheme for Acidithiobacillus caldus strain evaluation and differentiation

Phenotypic, metabolic and genetic properties of several Acidithiobacillus caldus strains indicate the existence of as yet undefined levels of variation within the species. Inspite of this, intraspecies genetic diversity has not yet been explored in detail. In this study, the design and implementation of a Multi Locus Sequence Typing (MLST) scheme for At. caldus is described. This represents the first MLST-based study applied to industrial isolates of the species. Seven informative and discriminant MLST markers were selected using a sequence-driven approach and a custom-designed bioinformatic pipeline. The allelic profiles of thirteen At. caldus strains from diverse geographical origins and industrial settings were derived using this scheme. MLST-based population structure analysis indicated only moderate amounts of genetic diversity within the set of strains, further supporting their current assignment to a single species. Also, no clear evidence for geographical isolation could be derived from this study. However, the prevalence of sequence type 1 in heap leaching industrial settings support the view that bioprocess conditions and dynamics may have a strong influence on At. caldus (microbial) microdiversity patterns. The MLST scheme presented herein is a valuable tool for the identification and classification of strains of At. caldus for either ecological or evolutionary studies and possibly also for industrial monitoring purposes.

Recombination blurs phylogenetic groups routine assignment in Escherichia coli: setting the record straight

The characterization of population structures plays a main role for understanding outbreaks and the dynamics of bacterial spreading. In Escherichia coli, the widely used combination of multiplex-PCR scheme together with goeBURST has some limitations. The purpose of this study is to show that the combination of different phylogenetic approaches based on concatenated sequences of MLST genes results in a more precise assignment of E. coli phylogenetic groups, complete understanding of population structure and reconstruction of ancestral clones. A collection of 80 Escherichia coli strains of different origins was analyzed following the Clermont and Doumith's multiplex-PCR schemes. Doumith's multiplex-PCR showed only 1.7% of misassignment, whereas Clermont's-2000 protocol reached 14.0%, although the discrepancies reached 30% and 38.7% respectively when recombinant C, F and E phylogroups were considered. Therefore, correct phylogroup attribution is highly variable and depends on the clonal composition of the sample. As far as population structure of these E. coli strains, including 48 E. coli genomes from GenBank, goeBURST provides a quite dispersed population structure; whereas NeighborNet approach reveals a complex population structure. MLST-based eBURST can infer different founder genotypes, for instance ST23/ST88 could be detected as the founder genotypes for STC23; however, phylogenetic reconstructions might suggest ST410 as the ancestor clone and several evolutionary trajectories with different founders. To improve our routine understanding of E. coli molecular epidemiology, we propose a strategy based on three successive steps; first, to discriminate three main groups A/B1/C, D/F/E and B2 following Doumith's protocol; second, visualization of population structure based on MLST genes according to goeBURST, using NeighborNet to establish more complex relationships among STs; and third, to perform, a cost-free characterization of evolutionary trajectories in variants emerging along the clonal expansion using parsimony methods of phylogenetic analysis.

Genomic insights into the evolutionary origin of Xanthomonas axonopodis pv. citri and its ecological relatives

Xanthomonas axonopodis pv. citri (Xac) is the causal agent of citrus bacterial canker (CBC) and is a serious problem worldwide. Like CBC, several important diseases in other fruits, such as mango, pomegranate, and grape, are also caused by Xanthomonas pathovars that display remarkable specificity toward their hosts. While citrus and mango diseases were documented more than 100 years ago, the pomegranate and grape diseases have been known only since the 1950s and 1970s, respectively. Interestingly, diseases caused by all these pathovars were noted first in India. Our genome-based phylogenetic studies suggest that these diverse pathogens belong to a single species and these pathovars may be just a group of rapidly evolving strains. Furthermore, the recently reported pathovars, such as those infecting grape and pomegranate, form independent clonal lineages, while the citrus and mango pathovars that have been known for a long time form one clonal lineage. Such an understanding of their phylogenomic relationship has further allowed us to understand major and unique variations in the lineages that give rise to these pathovars. Whole-genome sequencing studies including ecological relatives from their putative country of origin has allowed us to understand the evolutionary history of Xac and other pathovars that infect fruits.

Genotypic and phenotypic characteristics of Cronobacter species, with particular attention to the newly reclassified species Cronobacter helveticus, Cronobacter pulveris, and Cronobacter zurichensis

In 2013, Enterobacter helveticus, Enterobacter pulveris and Enterobacter turicensis, were reclassified as Cronobacter helveticus, Cronobacter pulveris and Cronobacter zurichensis, respectively. Previously these species had been used as negative controls for some Cronobacter detection assays. This study examined cultural, biochemical and molecular Cronobacter detection and identification assays, with emphasis on the new species. Additionally, 32 Cronobacter genomes were examined for the presence of PCR target genes using the BLAST function of the online Cronobacter PubMLST facility. The results of the cultural methods varied and no single medium was able to correctly detect all Cronobacter spp. Since the supporting databases have not been updated to include the Cronobacter genus, Enterobacter sakazakii was returned for four strains of the newly reclassified species with ID32E and none with API 20E. PCR probes targeting rpoB and ompA could not correctly identify the new Cronobacter spp., due to primer specificity or absent target genes. As neonates have been identified as a high-risk group for infection, international standards require the absence of all Cronobacter species in powdered infant formula. However, many conventional detection methods cannot correctly identify the newly recognized species. Conversely, DNA sequence-based methods can adapt to taxonomic revisions and will likely become more common.

Molecular and pathological insights into Chlamydia pecorum-associated sporadic bovine encephalomyelitis (SBE) in Western Australia

Background

Despite its global recognition as a ruminant pathogen, cases of Chlamydia pecorum infection in Australian livestock are poorly documented. In this report, a C. pecorum specific Multi Locus Sequence Analysis scheme was used to characterise the C. pecorum strains implicated in two cases of sporadic bovine encephalomyelitis confirmed by necropsy, histopathology and immunohistochemistry. This report provides the first molecular evidence for the presence of mixed infections of C. pecorum strains in Australian cattle.

Case presentation

Affected animals were two markedly depressed, dehydrated and blind calves, 12 and 16 weeks old. The calves were euthanized and necropsied. In one calf, a severe fibrinous polyserositis was noted with excess joint fluid in all joints whereas in the other, no significant lesions were seen. No gross abnormalities were noted in the brain of either calf. Histopathological lesions seen in both calves included: multifocal, severe, subacute meningoencephalitis with vasculitis, fibrinocellular thrombosis and malacia; diffuse, mild, acute interstitial pneumonia; and diffuse, subacute epicarditis, severe in the calf with gross serositis. Immunohistochemical labelling of chlamydial antigen in brain, spleen and lung from the two affected calves and brain from two archived cases, localised the antigen to the cytoplasm of endothelium, mesothelium and macrophages. C. pecorum specific qPCR, showed dissemination of the pathogen to multiple organs. Phylogenetic comparisons with other C. pecorum bovine strains from Australia, Europe and the USA revealed the presence of two genetically distinct sequence types (ST). The predominant ST detected in the brain, heart, lung and liver of both calves was identical to the C. pecorum ST previously described in cases of SBE. A second ST detected in an ileal tissue sample from one of the calves, clustered with previously typed faecal bovine isolates.

Conclusion

This report provides the first data to suggest that identical C. pecorum STs may be associated with SBE in geographically separated countries and that these may be distinct from those found in the gastrointestinal tract. This report provides a platform for further investigations into SBE and for understanding the genetic relationships that exist between C. pecorum strains detected in association with other infectious diseases in livestock.

Identifying Neisseria species by use of the 50S ribosomal protein L6 (rplF) gene

The comparison of 16S rRNA gene sequences is widely used to differentiate bacteria; however, this gene can lack resolution among closely related but distinct members of the same genus. This is a problem in clinical situations in those genera, such as Neisseria, where some species are associated with disease while others are not. Here, we identified and validated an alternative genetic target common to all Neisseria species which can be readily sequenced to provide an assay that rapidly and accurately discriminates among members of the genus. Ribosomal multilocus sequence typing (rMLST) using ribosomal protein genes has been shown to unambiguously identify these bacteria. The PubMLST Neisseria database (http://pubmlst.org/neisseria/) was queried to extract the 53 ribosomal protein gene sequences from 44 genomes from diverse species. Phylogenies reconstructed from these genes were examined, and a single 413-bp fragment of the 50S ribosomal protein L6 (rplF) gene was identified which produced a phylogeny that was congruent with the phylogeny reconstructed from concatenated ribosomal protein genes. Primers that enabled the amplification and direct sequencing of the rplF gene fragment were designed to validate the assay in vitro and in silico. Allele sequences were defined for the gene fragment, associated with particular species names, and stored on the PubMLST Neisseria database, providing a curated electronic resource. This approach provides an alternative to 16S rRNA gene sequencing, which can be readily replicated for other organisms for which more resolution is required, and it has potential applications in high-resolution metagenomic studies.

Whole-genome-based Mycobacterium tuberculosis surveillance: a standardized, portable, and expandable approach

Whole-genome sequencing (WGS) allows for effective tracing of Mycobacterium tuberculosis complex (MTBC) (tuberculosis pathogens) transmission. However, it is difficult to standardize and, therefore, is not yet employed for interlaboratory prospective surveillance. To allow its widespread application, solutions for data standardization and storage in an easily expandable database are urgently needed. To address this question, we developed a core genome multilocus sequence typing (cgMLST) scheme for clinical MTBC isolates using the Ridom SeqSphere(+) software, which transfers the genome-wide single nucleotide polymorphism (SNP) diversity into an allele numbering system that is standardized, portable, and not computationally intensive. To test its performance, we performed WGS analysis of 26 isolates with identical IS6110 DNA fingerprints and spoligotyping patterns from a longitudinal outbreak in the federal state of Hamburg, Germany (notified between 2001 and 2010). The cgMLST approach (3,041 genes) discriminated the 26 strains with a resolution comparable to that of SNP-based WGS typing (one major cluster of 22 identical or closely related and four outlier isolates with at least 97 distinct SNPs or 63 allelic variants). Resulting tree topologies are highly congruent and grouped the isolates in both cases analogously. Our data show that SNP- and cgMLST-based WGS analyses facilitate high-resolution discrimination of longitudinal MTBC outbreaks. cgMLST allows for a meaningful epidemiological interpretation of the WGS genotyping data. It enables standardized WGS genotyping for epidemiological investigations, e.g., on the regional public health office level, and the creation of web-accessible databases for global TB surveillance with an integrated early warning system.

Bacterial whole-genome sequencing revisited: portable, scalable, and standardized analysis for typing and detection of virulence and antibiotic resistance genes

Multidrug-resistant nosocomial pathogens present a major burden for hospitals. Rapid cluster identification and pathogen profiling, i.e., of antibiotic resistance and virulence genes, are crucial for effective infection control. Methicillin-resistant Staphylococcus aureus (MRSA), in particular, is now one of the leading causes of nosocomial infections. In this study, whole-genome sequencing (WGS) was applied retrospectively to an unusual spike in MRSA cases in two intensive care units (ICUs) over the course of 4 weeks. While the epidemiological investigation concluded that there were two separate clusters, each associated with one ICU, S. aureus protein A gene (spa) typing data suggested that they belonged to single clonal cluster (all cases shared spa type t001). Standardized gene sets were used to extract an allele-based profile for typing and an antibiotic resistance and toxin gene profile. The WGS results produced high-resolution allelic profiles, which were used to discriminate the MRSA clusters, corroborating the epidemiological investigation and identifying previously unsuspected transmission events. The antibiotic resistance profile was in agreement with the original clinical laboratory susceptibility profile, and the toxin profile provided additional, previously unknown information. WGS coupled with allelic profiling provided a high-resolution method that can be implemented as regular screening for effective infection control.

Biobanking and translation of human genetics and genomics for infectious diseases

Biobanks are invaluable resources in genomic research of both the infectious diseases and their hosts. This article examines the role of biobanks in basic research of infectious disease genomics, as well as the relevance and applicability of biobanks in the translation of impending knowledge and the clinical uptake of knowledge of infectious diseases. Our research identifies potential fields of interaction between infectious disease genomics and biobanks, in line with global trends in the integration of genome-based knowledge into clinical practice. It also examines various networks and biobanks that specialize in infectious diseases (including HIV, HPV and Chlamydia trachomatis), and provides examples of successful research and clinical uptake stemming from these biobanks. Finally, it outlines key issues with respect to data privacy in infectious disease genomics, as well as the utility of adequately designed and maintained electronic health records. We maintain that the public should be able to easily access a clear and detailed outline of regulations and procedures for sample and data utilization by academic or commercial investigators, and also should be able to understand the precise roles of relevant governing bodies. This would ultimately facilitate uptake by researchers and clinics. As a result of the efforts and resources invested by several networks and consortia, there is an increasing awareness of the prospective uses of biobanks in advancing infectious disease genomic research, diagnostics and their clinical management.

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The role of biobanks in research of host genomic factors and infectious diseases.

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Examples of translation of HIV, HPV and Chlamydia research results into clinics.

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Lack of published overviews of infectious disease biobanks, result is low visibility.

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Regulations and sample utilization procedures should be more easily accessible.

A reference pan-genome approach to comparative bacterial genomics: identification of novel epidemiological markers in pathogenic Campylobacter

The increasing availability of hundreds of whole bacterial genomes provides opportunities for enhanced understanding of the genes and alleles responsible for clinically important phenotypes and how they evolved. However, it is a significant challenge to develop easy-to-use and scalable methods for characterizing these large and complex data and relating it to disease epidemiology. Existing approaches typically focus on either homologous sequence variation in genes that are shared by all isolates, or non-homologous sequence variation--focusing on genes that are differentially present in the population. Here we present a comparative genomics approach that simultaneously approximates core and accessory genome variation in pathogen populations and apply it to pathogenic species in the genus Campylobacter. A total of 7 published Campylobacter jejuni and Campylobacter coli genomes were selected to represent diversity across these species, and a list of all loci that were present at least once was compiled. After filtering duplicates a 7-isolate reference pan-genome, of 3,933 loci, was defined. A core genome of 1,035 genes was ubiquitous in the sample accounting for 59% of the genes in each isolate (average genome size of 1.68 Mb). The accessory genome contained 2,792 genes. A Campylobacter population sample of 192 genomes was screened for the presence of reference pan-genome loci with gene presence defined as a BLAST match of ≥ 70% identity over ≥ 50% of the locus length--aligned using MUSCLE on a gene-by-gene basis. A total of 21 genes were present only in C. coli and 27 only in C. jejuni, providing information about functional differences associated with species and novel epidemiological markers for population genomic analyses. Homologs of these genes were found in several of the genomes used to define the pan-genome and, therefore, would not have been identified using a single reference strain approach.

Multilocus Sequence Typing for Interpreting Blood Isolates of Staphylococcus epidermidis

Staphylococcus epidermidis is an important cause of nosocomial infection and bacteremia. It is also a common contaminant of blood cultures and, as a result, there is frequently uncertainty as to its diagnostic significance when recovered in the clinical laboratory. One molecular strategy that might be of value in clarifying the interpretation of S. epidermidis identified in blood culture is multilocus sequence typing. Here, we examined 100 isolates of this species (50 blood isolates representing true bacteremia, 25 likely contaminant isolates, and 25 skin isolates) and the ability of sequence typing to differentiate them. Three machine learning algorithms (classification regression tree, support vector machine, and nearest neighbor) were employed. Genetic variability was substantial between isolates, with 44 sequence types found in 100 isolates. Sequence types 2 and 5 were most commonly identified. However, among the classification algorithms we employed, none were effective, with CART and SVM both yielding only 73% diagnostic accuracy and nearest neighbor analysis yielding only 53% accuracy. Our data mirror previous studies examining the presence or absence of pathogenic genes in that the overlap between truly significant organisms and contaminants appears to prevent the use of MLST in the clarification of blood cultures recovering S. epidermidis.