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Funder: Department of Health {UK), Genome-wide association studies (GWAS) are increasingly being applied to investigate the genetic basis of bacterial traits. However, approaches to perform power calculations for bacterial GWAS are limited. Here we implemented two alternative approaches to conduct power calculations using existing collections of bacterial genomes. First, a sub-sampling approach was undertaken to reduce the allele frequency and effect size of a known and detectable genotype-phenotype relationship by modifying phenotype labels. Second, a phenotype-simulation approach was conducted to simulate phenotypes from existing genetic variants. We implemented both approaches into a computational pipeline (PowerBacGWAS) that supports power calculations for burden testing, pan-genome and variant GWAS; and applied it to collections of Enterococcus faecium, Klebsiella pneumoniae and Mycobacterium tuberculosis. We used this pipeline to determine sample sizes required to detect causal variants of different minor allele frequencies (MAF), effect sizes and phenotype heritability, and studied the effect of homoplasy and population diversity on the power to detect causal variants. Our pipeline and user documentation are made available and can be applied to other bacterial populations. PowerBacGWAS can be used to determine sample sizes required to find statistically significant associations, or the associations detectable with a given sample size. We recommend to perform power calculations using existing genomes of the bacterial species and population of study.

Nosocomial acquisition and transmission of vancomycin-resistant Enterococcus faecium (VREfm) is the driver for E. faecium carriage in hospitalized patients, which, in turn, is a risk factor for invasive infection in immunocompromised patients. In the present study, we provide a comprehensive picture of E. faecium transmission in an entire sampled patient population using a sequence-driven approach. We prospectively identified and followed 149 haematology patients admitted to a hospital in England for 6 months. Patient stools (n = 376) and environmental swabs (n = 922) were taken at intervals and cultured for E. faecium. We sequenced 1,560 isolates (1,001 stool, 559 environment) and focused our genomic analyses on 1,477 isolates (95%) in the hospital-adapted clade A1. Of 101 patients who provided two or more stool samples, 40 (40%) developed E. faecium carriage after admission based on culture, compared with 64 patients (63%) based on genomic analysis (73% VREfm). Half of 922 environmental swabs (447, 48%) were positive for VREfm. Network analysis showed that, of 111 patients positive for the A1 clade, 67 had strong epidemiological and genomic links with at least one other patient and/or their direct environment, supporting nosocomial transmission. Six patients (3.4%) developed an invasive E. faecium infection from their own gut-colonizing strain, which was preceded by nosocomial acquisition of the infecting isolate in half of these. Two informatics approaches (subtype categorization to define phylogenetic clusters and the development of an SNP cut-off for transmission) were central to our analyses, both of which will inform the future translation of E. faecium sequencing into routine outbreak detection and investigation. In conclusion, we showed that carriage and environmental contamination by the hospital-adapted E. faecium lineage were hyperendemic in our study population and that improved infection control measures will be needed to reduce hospital acquisition rates.