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Whole-genome sequencing (WGS) of Staphylococcus aureus is increasingly used as part of infection prevention practices, but most applications are focused on conserved core genomic regions due to limitations of short-read technologies. In this study we established a long-read technology-based WGS screening program of all first-episode MRSA blood infections at a major urban hospital. A survey of 132 MRSA genomes assembled from long reads revealed widespread gain/loss of accessory mobile genetic elements among established hospital- and community-associated lineages impacting >10% of each genome, and frequent megabase-scale inversions between endogenous prophages. We also characterized an outbreak of a CC5/ST105/USA100 clone among 3 adults and 18 infants in a neonatal intensive care unit (NICU) lasting 7 months. The pattern of changes among complete outbreak genomes provided full spatiotemporal resolution of its origins and progression, which was characterized by multiple sub-transmissions and likely precipitated by equipment sharing. Compared to other hospital strains, the outbreak strain carried distinct mutations and accessory genetic elements that impacted genes with roles in metabolism, resistance and persistence. This included a DNA-recognition domain recombination in the hsdS gene of a Type-I restriction-modification system that altered DNA methylation. RNA-Seq profiling showed that the (epi)genetic changes in the outbreak clone attenuated agr gene expression and upregulated genes involved in stress response and biofilm formation. Overall our findings demonstrate that long-read sequencing substantially improves our ability to characterize accessory genomic elements that impact MRSA virulence and persistence, and provides valuable information for infection control efforts.

Clostridioides difficileis a leading cause of health care-associated infections. Although significant progress has been made in the understanding of its genome, the epigenome ofC. difficileand its functional impact has not been systematically explored. Here, we performed the first comprehensive DNA methylome analysis ofC. difficileusing 36 human isolates and observed great epigenomic diversity. We discovered an orphan DNA methyltransferase with a well-defined specificity whose corresponding gene is highly conserved across our dataset and in all ~300 globalC. difficilegenomes examined. Inactivation of the methyltransferase gene negatively impacted sporulation, a key step inC. difficiledisease transmission, consistently supported by multi-omics data, genetic experiments, and a mouse colonization model. Further experimental and transcriptomic analysis also suggested that epigenetic regulation is associated with cell length, biofilm formation, and host colonization. These findings open up a new epigenetic dimension to characterize medically relevant biological processes in this critical pathogen. This work also provides a set of methods for comparative epigenomics and integrative analysis, which we expect to be broadly applicable to bacterial epigenomics studies.

Clostridioides (formerly Clostridium) difficile is a leading cause of healthcare-associated infections. Although considerable progress has been made in the understanding of its genome, the epigenome of C. difficile and its functional impact has not been systematically explored. Here, we perform a comprehensive DNA methylome analysis of C. difficile using 36 human isolates and observe a high level of epigenomic diversity. We discovered an orphan DNA methyltransferase with a well-defined specificity, the corresponding gene of which is highly conserved across our dataset and in all of the approximately 300 global C. difficile genomes examined. Inactivation of the methyltransferase gene negatively impacts sporulation, a key step in C. difficile disease transmission, and these results are consistently supported by multiomics data, genetic experiments and a mouse colonization model. Further experimental and transcriptomic analyses suggest that epigenetic regulation is associated with cell length, biofilm formation and host colonization. These findings provide a unique epigenetic dimension to characterize medically relevant biological processes in this important pathogen. This study also provides a set of methods for comparative epigenomics and integrative analysis, which we expect to be broadly applicable to bacterial epigenomic studies. In this work, Fang et al. analyse the epigenetic landscape of Clostridioides difficile and identify a DNA methyltransferase present across C. difficile strains that is required for optimal sporulation and in vivo colonization and disease.

Whole-genome sequences for Stenotrophomonas maltophilia serial isolates from a bacteremic patient before and after development of levofloxacin resistance were assembled de novo and differed by one single-nucleotide variant in smeT , a repressor for multidrug efflux operon smeDEF . Along with sequenced isolates from five contemporaneous cases, they displayed considerable diversity compared against all published complete genomes. Whole-genome sequencing and complete assembly can conclusively identify resistance mechanisms emerging in S. maltophilia strains during clinical therapy.

In a liver transplant recipient with vancomycin-resistant Enterococcus (VRE) surgical site and bloodstream infection, a combination of pulsed-field gel electrophoresis, multilocus sequence typing, and whole genome sequencing identified that donor and recipient VRE isolates were highly similar when compared to time-matched hospital isolates. Comparison of de novo assembled isolate genomes was highly suggestive of transplant transmission rather than hospital-acquired transmission and also identified subtle internal rearrangements between donor and recipient missed by other genomic approaches. Given the improved resolution, whole-genome assembly of pathogen genomes is likely to become an essential tool for investigation of potential organ transplant transmissions.

Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or 'passenger', cancer mutations from causal, or 'driver', mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer.

Variable tandem repeats are frequently used for genetic mapping, genotyping, and forensics studies. Moreover, variation in some repeats underlies rapidly evolving traits or certain diseases. However, mutation rates vary greatly from repeat to repeat, and as a consequence, not all tandem repeats are suitable genetic markers or interesting unstable genetic modules. We developed a model, “SERV,” that predicts the variability of a broad range of tandem repeats in a wide range of organisms. The nonlinear model uses three basic characteristics of the repeat (number of repeated units, unit length, and purity) to produce a numeric “VARscore” that correlates with repeat variability. SERV was experimentally validated using a large set of different artificial repeats located in the Saccharomyces cerevisiae URA3 gene. Further in silico analysis shows that SERV outperforms existing models and accurately predicts repeat variability in bacteria and eukaryotes, including plants and humans. Using SERV, we demonstrate significant enrichment of variable repeats within human genes involved in transcriptional regulation, chromatin remodeling, morphogenesis, and neurogenesis. Moreover, SERV allows identification of known and candidate genes involved in repeat-based diseases. In addition, we demonstrate the use of SERV for the selection and comparison of suitable variable repeats for genotyping and forensic purposes. Our analysis indicates that tandem repeats used for genotyping should have a VARscore between 1 and 3. SERV is publicly available from http://hulsweb1.cgr.harvard.edu/SERV/.