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This study investigated the evolution and epidemiology of the community-associated and multidrug-resistant Staphylococcus aureus clone European CC1-MRSA-IV. Whole-genome sequences were obtained for 194 European CC1-MRSA-IV isolates (189 of human and 5 of animal origin) from 12 countries, and 10 meticillin-susceptible precursors (from North-Eastern Romania; all of human origin) of the clone. Phylogenetic analysis was performed using a maximum-likelihood approach, a time-measured phylogeny was reconstructed using Bayesian analysis, and in silico microarray genotyping was performed to identify resistance, virulence-associated and SCCmec (staphylococcal cassette chromosome mec) genes. Isolates were typically sequence type 1 (190/204) and spa type t127 (183/204). Bayesian analysis indicated that European CC1-MRSA-IV emerged in approximately 1995 before undergoing rapid expansion in the late 1990s and 2000s, while spreading throughout Europe and into the Middle East. Phylogenetic analysis revealed an unstructured meticillin-resistant S. aureus (MRSA) population, lacking significant geographical or temporal clusters. The MRSA were genotypically multidrug-resistant, consistently encoded seh, and intermittently (34/194) encoded an undisrupted hlb gene with concomitant absence of the lysogenic phage-encoded genes sak and scn. All MRSA also harboured a characteristic ~5350 nt insertion in SCCmec adjacent to orfX. Detailed demographic data from Denmark showed that there, the clone is typically (25/35) found in the community, and often (10/35) among individuals with links to South-Eastern Europe. This study elucidated the evolution and epidemiology of European CC1-MRSA-IV, which emerged from a meticillin-susceptible lineage prevalent in North-Eastern Romania before disseminating rapidly throughout Europe.

This study investigated the evolution and epidemiology of the community-associated and multidrug-resistant Staphylococcus aureus clone European CC1-MRSA-IV. Whole-genome sequences were obtained for 194 European CC1-MRSA-IV isolates (189 of human and 5 of animal origin) from 12 countries, and 10 meticillin-susceptible precursors (from North-Eastern Romania; all of human origin) of the clone. Phylogenetic analysis was performed using a maximum-likelihood approach, a time-measured phylogeny was reconstructed using Bayesian analysis, and in silico microarray genotyping was performed to identify resistance, virulence-associated and SCCmec (staphylococcal cassette chromosome mec) genes. Isolates were typically sequence type 1 (190/204) and spa type t127 (183/204). Bayesian analysis indicated that European CC1-MRSA-IV emerged in approximately 1995 before undergoing rapid expansion in the late 1990s and 2000s, while spreading throughout Europe and into the Middle East. Phylogenetic analysis revealed an unstructured meticillin-resistant S. aureus (MRSA) population, lacking significant geographical or temporal clusters. The MRSA were genotypically multidrug-resistant, consistently encoded seh, and intermittently (34/194) encoded an undisrupted hlb gene with concomitant absence of the lysogenic phage-encoded genes sak and scn. All MRSA also harboured a characteristic ~5350 nt insertion in SCCmec adjacent to orfX. Detailed demographic data from Denmark showed that there, the clone is typically (25/35) found in the community, and often (10/35) among individuals with links to South-Eastern Europe. This study elucidated the evolution and epidemiology of European CC1-MRSA-IV, which emerged from a meticillin-susceptible lineage prevalent in North-Eastern Romania before disseminating rapidly throughout Europe.

Nanopore sequencing and phylodynamic modelling have been used to reconstruct the transmission dynamics of viral epidemics, but their application to bacterial pathogens has remained challenging. Here, we implement Random Forest models for single nucleotide polymorphism (SNP) polishing to estimate divergence and effective reproduction numbers (Re) of two community-associated, methicillin-resistant Staphylococcus aureus (MRSA) outbreaks in remote Far North Queensland and Papua New Guinea (n = 159). Successive bar-coded panels of S. aureus isolates (2 × 12 per MinION) sequenced at low-coverage (> 5x - 10x) provided sufficient data to accurately infer assembly genotypes with high recall when compared with Illumina references. De novo SNP calling with Clair was followed by SNP polishing using intra- and inter-species models trained on Snippy reference calls. Models achieved sufficient resolution on ST93 outbreak sequence types (> 70 - 90% accuracy and precision) for phylodynamic modelling from lineage-wide hybrid alignments and birth-death skyline models in BEAST2. Our method reproduced phylogenetic topology, geographical source of the outbreaks, and indications of sustained transmission (Re > 1). We provide Nextflow pipelines that implement SNP polisher training, evaluation, and outbreak alignments, enabling reconstruction of within-lineage transmission dynamics for infection control of bacterial disease outbreaks using nanopore sequencing.

Community-associated, methicillin-resistantStaphylococcus aureus(MRSA) lineages have emerged in many geographically distinct regions around the world during the past 30 years. Here, we apply consistent phylodynamic methods across multiple community-associated MRSA lineages to describe and contrast their patterns of emergence and dissemination. We generated whole genome sequencing data for the Australian sequence type (ST) 93-MRSA-IV from remote communities in Far North Queensland and Papua New Guinea, and the Bengal Bay ST772-MRSA-V clone from metropolitan communities in Pakistan. Increases in the effective reproduction number (Re) and sustained transmission (Re> 1) coincided with spread of progenitor methicillin-susceptibleS. aureus(MSSA) in remote northern Australia, dissemination of the ST93-MRSA-IV geno-type into population centers on the Australian East Coast, and sub-sequent importation into the highlands of Papua New Guinea and Far North Queensland. Analysis of a ST772-MRSA-V cluster in Pakistan suggests that sustained transmission in the community following importation of resistant genotypes may be more common than previously thought. Applying the same phylodynamic methods to existing lineage datasets, we identified common signatures of epidemic growth in the emergence and epidemiological trajectory of community-associatedS. aureuslineages from America, Asia, Australasia and Europe. Surges in Rewere observed at the divergence of antibiotic resistant strains, coinciding with their establishment in regional population centers. Epidemic growth was also observed amongst drug-resistant MSSA clades in Africa and northern Australia. Our data suggest that the emergence of community-associated MRSA and MSSA lineages in the late 20th century was driven by a combination of antibiotic resistant genotypes and host epidemiology, leading to abrupt changes in lineage-wide transmission dynamics and sustained transmission in regional population centers.

Background Antimicrobial resistance (AMR) poses a major threat to human health. Whole-genome sequencing holds great potential for AMR identification; however, there remain major gaps in accurately and comprehensively detecting AMR across the spectrum of AMR-conferring determinants and pathogens. Methods Using 16 wild-type Burkholderia pseudomallei and 25 with acquired AMR, we first assessed the performance of existing AMR software (ARIBA, CARD, ResFinder, and AMRFinderPlus) for detecting clinically relevant AMR in this pathogen. B. pseudomallei was chosen due to limited treatment options, high fatality rate, and AMR caused exclusively by chromosomal mutation (i.e. single-nucleotide polymorphisms [SNPs], insertions-deletions [indels], copy-number variations [CNVs], inversions, and functional gene loss). Due to poor performance with existing tools, we developed ARDaP ( A ntimicrobial R esistance D etection a nd P rediction) to identify the spectrum of AMR-conferring determinants in B. pseudomallei. Findings CARD, ResFinder, and AMRFinderPlus failed to identify any clinically-relevant AMR in B. pseudomallei; ARIBA identified AMR encoded by SNPs and indels that were manually added to its database. However, none of these tools identified CNV, inversion, or gene loss determinants, and ARIBA could not differentiate AMR determinants from natural genetic variation. In contrast, ARDaP accurately detected all SNP, indel, CNV, inversion, and gene loss AMR determinants described in B. pseudomallei (n≈50). Additionally, ARDaP accurately predicted three previously undescribed determinants. In mixed strain data, ARDaP identified AMR to as low as ~5% allelic frequency. Interpretation Existing AMR software packages are inadequate for chromosomal AMR detection due to an inability to detect resistance conferred by CNVs, inversions, and functional gene loss. ARDaP overcomes these major shortcomings. Further, ARDaP enables AMR prediction from mixed sequence data down to 5% allelic frequency, and can differentiate natural genetic variation from AMR determinants. ARDaP databases can be constructed for any microbial species of interest for comprehensive AMR detection. Funding National Health and Medical Research Council (BJC, EPP, DSS); Australian Government (DEM, ES); Advance Queensland (EPP, DSS).

BackgroundAntimicrobial resistance (AMR) poses a major threat to human health. Whole-genome sequencing holds great potential for AMR identification; however, there remain major gaps in comprehensively detecting AMR across the spectrum of AMR-conferring determinants and pathogens.MethodsUsing 16 wild-type Burkholderia pseudomallei and 25 with acquired AMR, we first assessed the performance of existing AMR software (ARIBA and CARD) for detecting clinically relevant AMR in this pathogen. B. pseudomallei was chosen due to limited treatment options, high fatality rate, and AMR caused exclusively by chromosomal mutation (i.e. single-nucleotide polymorphisms [SNPs], insertions-deletions [indels], copy-number variations [CNVs], and functional gene loss). Due to poor performance with existing tools, we developed ARDaP (Antimicrobial Resistance Detection and Prediction) to identify the spectrum of AMR-conferring determinants in B. pseudomallei.ResultsCARD failed to identify any clinically-relevant AMR in B. pseudomallei, ARIBA cannot differentiate AMR determinants from natural genetic variation, and neither CARD or ARIBA can identify CNV or gene loss determinants. In contrast, ARDaP accurately detected all SNP, indel, CNV, and gene loss AMR determinants described in B. pseudomallei (n≈50). Additionally, ARDaP accurately predicted three previously undescribed determinants. In mixed strain data, ARDaP identified AMR to as low as ~5% allelic frequency.ConclusionsWe demonstrate that existing AMR software are inadequate for comprehensive AMR detection; ARDaP overcomes the shortcomings of existing tools. Further, ARDaP enables AMR prediction from mixed sequence data down to 5% allelic frequency. ARDaP databases can be constructed for any microbial species of interest for comprehensive AMR detection.

Background Staphylococcus aureus has a high prevalence in chronic rhinosinusitis (CRS) patients and is suggested to play a more etiopathogenic role in CRS patients with nasal polyps (CRSwNP), a severe form of the CRS spectrum with poorer surgical outcomes. We performed a microbial genome-wide association study (mGWAS) to investigate whether S. aureus isolates from CRS patients have particular genetic markers associated with CRS with nasal polyps (CRSwNP) or CRS without nasal polyps (CRSsNP). Methods Whole genome sequencing was performed on S. aureus isolates collected from 28 CRSsNP and 30 CRSwNP patients. A mGWAS approach was employed using large-scale comparative genomics to identify genetic variation within our dataset. Results Considerable genetic variation was observed, with > 90,000 single nucleotide polymorphisms (SNPs) sites identified. There was little correlation with CRS subtype based on SNPs and Insertion/Delection (Indels). One indel was found to significantly correlate with CRSwNP and occurred in the promoter region of a bacitracin transport system ATP-binding protein. Additionally, two variants of the highly variable superantigen-like (SSL) proteins were found to significantly correlate with each CRS phenotype. No significant association with other virulence or antibiotic resistance genes were observed, consistent with previous studies. Conclusion To our knowledge this study is the first to use mGWAS to investigate the contribution of microbial genetic variation to CRS presentations. Utilising the most comprehensive genome-wide analysis methods available, our results suggest that CRS phenotype may be influenced by genetic factors other than specific virulence mechanisms within the S. aureus genome. Electronic supplementary material The online version of this article (10.1186/s12901-018-0064-1) contains supplementary material, which is available to authorized users.

Network-based approaches are emerging as valuable tools for the analysis of complex genetic structure in wild and captive populations. netview p combines data quality control with the construction of population networks through mutual k-nearest neighbours thresholds applied to genome-wide SNPs. The program is cross-platform compatible, open-source and efficiently operates on data ranging from hundreds to hundreds of thousands of SNPs. The pipeline was used for the analysis of pedigree data from simulated (n = 750, SNPs = 1279) and captive silver-lipped pearl oysters (n = 415, SNPs = 1107), wild populations of the European hake from the Atlantic and Mediterranean (n = 834, SNPs = 380) and grey wolves from North America (n = 239, SNPs = 78 255). The population networks effectively visualize large- and fine-scale genetic structure within and between populations, including family-level structure and relationships. netview p comprises a network-based addition to other population analysis tools and provides user-friendly access to a complex network analysis pipeline through implementation in python.

The evolution and global transmission of antimicrobial resistance has been well documented in Gram-negative bacteria and healthcare-associated epidemic pathogens, often emerging from regions with heavy antimicrobial use. However, the degree to which similar processes occur with Gram-positive bacteria in the community setting is less well understood. Here, we trace the recent origins and global spread of a multidrug resistant, community-associatedStaphylococcus aureuslineage from the Indian subcontinent, the Bengal Bay clone (ST772). We generated whole genome sequence data of 340 isolates from 14 countries, including the first isolates from Bangladesh and India, to reconstruct the evolutionary history and genomic epidemiology of the lineage. Our data shows that the clone emerged on the Indian subcontinent in the early 1970s and disseminated rapidly in the 1990s. Short-term outbreaks in community and healthcare settings occurred following intercontinental transmission, typically associated with travel and family contacts on the subcontinent, but ongoing endemic transmission was uncommon. Acquisition of a multidrug resistance integrated plasmid was instrumental in the divergence of a single dominant and globally disseminated clade in the early 1990s. Phenotypic data on biofilm, growth and toxicity point to antimicrobial resistance as the driving force in the evolution of ST772. The Bengal Bay clone therefore combines the multidrug resistance of traditional healthcare-associated clones with the epidemiological transmission of community-associated MRSA. Our study demonstrates the importance of whole genome sequencing for tracking the evolution of emerging and resistant pathogens. It provides a critical framework for ongoing surveillance of the clone on the Indian subcontinent and elsewhere.ImportanceThe Bengal Bay clone (ST772) is a community-acquired and multidrug-resistantStaphylococcus aureuslineage first isolated from Bangladesh and India in 2004. In this study, we show that the Bengal Bay clone emerged from a virulent progenitor circulating on the Indian subcontinent. Its subsequent global transmission was associated with travel or family contact in the region. ST772 progressively acquired specific resistance elements at limited cost to its fitness and continues to be exported globally resulting in small-scale community and healthcare outbreaks. The Bengal Bay clone therefore combines the virulence potential and epidemiology of community-associated clones with the multidrug-resistance of healthcare-associatedS. aureuslineages. This study demonstrates the importance of whole genome sequencing for the surveillance of highly antibiotic resistant pathogens, which may emerge in the community setting of regions with poor antibiotic stewardship and rapidly spread into hospitals and communities across the world.

Very long-chain polyunsaturated fatty acids (VLC-PUFAs) are important dietary requirements for maintaining human health. Many marine microalgae are naturally high in ω-3 VLC-PUFAs, however, the molecular mechanisms underpinning fatty acid (FA) desaturation and elongation in algae are poorly understood. An advanced molecular understanding would facilitate improvements of this nascent industry. We aimed to investigate expression responses of four front-end fatty acid desaturase genes and downstream effects on FA profiles to nitrogen limitation and cultivation growth stage in Isochrysis aff. galbana (TISO). Cultures were grown in nitrogen-replete and -deplete medium; samples were harvested during logarithmic, late logarithmic and stationary growth phases to analyse FA content/composition and gene expression of ∆(6)-, ∆(8)-, ∆(5)- and ∆(4)-desaturases (d6FAD (putative), d8FAD, d5FAD and d4FAD, respectively). d6FAD (putative) exhibited no differential expression, while d8FAD, d5FAD and d4FAD were significantly upregulated during logarithmic growth of nutrient-replete cultures, coinciding with rapid cell division. In conclusion, it is demonstrated that expression of some FADs in I. aff. galbana varies with culture age and nitrogen status which has downstream consequences on FA desaturation levels. This has implications for the commercial production of VLC-PUFAs where a trade-off between total lipid yield and VLC-PUFAs has to be made.

Lipids from microalgae have become a valuable product with applications ranging from biofuels to human nutrition. While changes in fatty acid (FA) content and composition under nitrogen limitation are well documented, the involved molecular mechanisms are poorly understood. Acetyl-CoA carboxylase (ACCase) is a key enzyme in the FA synthesis and elongation pathway. Plastidial and cytosolic ACCases provide malonyl-CoA for de novo FA synthesis in the plastid and FA elongation in the endoplasmic reticulum, respectively. The present study aimed at investigating the expression of plastidial and cytosolic ACCase in Chromera velia and Isochrysis aff. galbana (TISO) and their impact on FA content and elongation level when grown under nitrogen-deplete conditions. In C. velia, plastidial ACCase was significantly upregulated during nitrogen starvation and with culture age, strongly correlating with increased FA content. Conversely, plastidial ACCase of I. aff. galbana was not differentially expressed in nitrogen-deplete cultures, but upregulated during the logarithmic phase of nitrogen-replete cultures. In contrast to plastidial ACCase, the cytosolic ACCase of C. velia was downregulated with culture age and nitrogen-starvation, strongly correlating with an increase in medium-chain FAs. In conclusion, the expression of plastidial and cytosolic ACCase changed with growth phase and nutrient status in a species-specific manner and nitrogen limitation did not always result in FA accumulation.

Evaluating the genetic contribution of individuals to population structure is essential to select informative individuals for genome sequencing, genotype imputation and to ascertain complex population structures. Existing methods for the selection of informative individuals for genomic imputation solely focus on the identification of key ancestors, which can lead to a loss of phasing accuracy of the reference population. Currently many methods are independently applied to investigate complex population structures. Based on the Eigenvalue Decomposition (EVD) of a genomic relationship matrix we describe a novel approach to evaluate the genetic contribution of individuals to population structure. We combined the identification of key contributors with model-based clustering and population network visualization into an integrated three-step approach, which allows identification of high-resolution population structures and substructures around such key contributors. The approach was applied and validated in four disparate datasets including a simulated population (5,100 individuals and 10,000 SNPs), a highly structured experimental sheep population (1,421 individuals and 44,693 SNPs) and two large complex pedigree populations namely horse (1,077 individuals and 38,124 SNPs) and cattle (2,457 individuals and 45,765 SNPs). In the simulated and experimental sheep dataset, our method, which is unsupervised, successfully identified all known key contributors. Applying our three-step approach to the horse and cattle populations, we observed high-resolution population substructures including the absence of obvious important key contributors. Furthermore, we show that compared to commonly applied strategies to select informative individuals for genotype imputation including the computation of marginal gene contributions (Pedig) and the optimization of genetic relatedness (Rel), the selection of key contributors provided the highest phasing accuracies within the selected reference populations. The presented approach opens new perspectives in the characterization and informed management of populations in general, and in areas such as conservation genetics and selective animal breeding in particular, where assessing the genetic contribution of influential and admixed individuals is crucial for research and management applications. As such, this method provides a valuable complement to common applied tools to visualize complex population structures and to select individuals for re-sequencing.

Background Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of hospital-associated infection, but there is growing awareness of the emergence of multidrug-resistant lineages in community settings around the world. One such lineage is ST772-MRSA-V, which has disseminated globally and is increasingly prevalent in India. Here, we present the complete genome sequence of DAR4145, a strain of the ST772-MRSA-V lineage from India, and investigate its genomic characteristics in regards to antibiotic resistance and virulence factors. Results Sequencing using single-molecule real-time technology resulted in the assembly of a single continuous chromosomal sequence, which was error-corrected, annotated and compared to nine draft genome assemblies of ST772-MRSA-V from Australia, Malaysia and India. We discovered numerous and redundant resistance genes associated with mobile genetic elements (MGEs) and known core genome mutations that explain the highly antibiotic resistant phenotype of DAR4145. Staphylococcal toxins and superantigens, including the leukotoxin Panton-Valentinin Leukocidin, were predominantly associated with genomic islands and the phage φ-IND772PVL. Some of these mobile resistance and virulence factors were variably present in other strains of the ST772-MRSA-V lineage. Conclusions The genomic characteristics presented here emphasize the contribution of MGEs to the emergence of multidrug-resistant and highly virulent strains of community-associated MRSA. Antibiotic resistance was further augmented by chromosomal mutations and redundancy of resistance genes. The complete genome of DAR4145 provides a valuable resource for future investigations into the global dissemination and phylogeography of ST772-MRSA-V. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1599-9) contains supplementary material, which is available to authorized users.