Explore the vast range of titles available.

Key Points Genome-wide association studies (GWAS) have been highly successful in the analyses of human genomic data. The increased availability of microorganism whole genomes provides the opportunity for microbial GWAS. Initial microbial GWAS have had success identifying variants for traits under strong selection, such as drug resistance, in a range of bacteria, viruses and protozoa. Several challenges to microbial GWAS exist that could hinder identifying variants under moderate selection. The primary challenge is the increased population stratification in microorganisms owing to selection and complex recombination patterns. Novel software that is tailored to the needs of microbial GWAS would greatly expedite progress in the field. In particular, the application of polygenic methods has yet to be evaluated in microorganisms. An exciting future area of research is the generation of host and microbial genomics data within the same samples. This will allow for genome-to-genome analyses to test for host–microorganism interactions. With the increasing availability of microbial whole genomes, researchers are beginning to carry out genome-wide association studies (GWAS) in bacteria, viruses and protozoa. In this Review, the authors discuss the specific challenges and considerations associated with the application of GWAS methods to microorganisms and consider the future of microbial GWAS in the light of lessons learned from human studies. The reduced costs of sequencing have led to whole-genome sequences for a large number of microorganisms, enabling the application of microbial genome-wide association studies (GWAS). Given the successes of human GWAS in understanding disease aetiology and identifying potential drug targets, microbial GWAS are likely to further advance our understanding of infectious diseases. These advances include insights into pressing global health problems, such as antibiotic resistance and disease transmission. In this Review, we outline the methodologies of GWAS, the current state of the field of microbial GWAS, and how lessons from human GWAS can direct the future of the field.

It has been 10 years since the introduction of modern transposon-insertion sequencing (TIS) methods, which combine genome-wide transposon mutagenesis with high-throughput sequencing to estimate the fitness contribution or essentiality of each genetic component in a bacterial genome. Four TIS variations were published in 2009: transposon sequencing (Tn-Seq), transposon-directed insertion site sequencing (TraDIS), insertion sequencing (INSeq) and high-throughput insertion tracking by deep sequencing (HITS). TIS has since become an important tool for molecular microbiologists, being one of the few genome-wide techniques that directly links phenotype to genotype and ultimately can assign gene function. In this Review, we discuss the recent applications of TIS to answer overarching biological questions. We explore emerging and multidisciplinary methods that build on TIS, with an eye towards future applications.In this Review, several experts discuss progress in the decade since the development of transposon-based approaches for bacterial genetic screens. They describe how advances in both experimental technologies and analytical strategies are resulting in insights into diverse biological processes.

The seventh cholera pandemic has heavily affected Africa, although the origin and continental spread of the disease remain undefined. We used genomic data from 1070 Vibrio cholerae O1 isolates, across 45 African countries and over a 49-year period, to show that past epidemics were attributable to a single expanded lineage. This lineage was introduced at least 11 times since 1970, into two main regions, West Africa and East/Southern Africa, causing epidemics that lasted up to 28 years. The last five introductions into Africa, all from Asia, involved multidrug-resistant sublineages that replaced antibiotic-susceptible sublineages after 2000. This phylogenetic framework describes the periodicity of lineage introduction and the stable routes of cholera spread, which should inform the rational design of control measures for cholera in Africa.

Population-level comparisons of prokaryotic genomes must take into account the substantial differences in gene content resulting from horizontal gene transfer, gene duplication and gene loss. However, the automated annotation of prokaryotic genomes is imperfect, and errors due to fragmented assemblies, contamination, diverse gene families and mis-assemblies accumulate over the population, leading to profound consequences when analysing the set of all genes found in a species. Here, we introduce Panaroo, a graph-based pangenome clustering tool that is able to account for many of the sources of error introduced during the annotation of prokaryotic genome assemblies. Panaroo is available at https://github.com/gtonkinhill/panaroo .

The assembly of DNA sequence data is undergoing a renaissance thanks to emerging technologies capable of producing reads tens of kilobases long. Assembling complete bacterial and small eukaryotic genomes is now possible, but the final step of circularizing sequences remains unsolved. Here we present Circlator, the first tool to automate assembly circularization and produce accurate linear representations of circular sequences. Using Pacific Biosciences and Oxford Nanopore data, Circlator correctly circularized 26 of 27 circularizable sequences, comprising 11 chromosomes and 12 plasmids from bacteria, the apicoplast and mitochondrion of Plasmodium falciparum and a human mitochondrion. Circlator is available at http://sanger-pathogens.github.io/circlator/ .

Diagnosing drug-resistance remains an obstacle to the elimination of tuberculosis. Phenotypic drug-susceptibility testing is slow and expensive, and commercial genotypic assays screen only common resistance-determining mutations. We used whole-genome sequencing to characterise common and rare mutations predicting drug resistance, or consistency with susceptibility, for all first-line and second-line drugs for tuberculosis. Between Sept 1, 2010, and Dec 1, 2013, we sequenced a training set of 2099 Mycobacterium tuberculosis genomes. For 23 candidate genes identified from the drug-resistance scientific literature, we algorithmically characterised genetic mutations as not conferring resistance (benign), resistance determinants, or uncharacterised. We then assessed the ability of these characterisations to predict phenotypic drug-susceptibility testing for an independent validation set of 1552 genomes. We sought mutations under similar selection pressure to those characterised as resistance determinants outside candidate genes to account for residual phenotypic resistance. We characterised 120 training-set mutations as resistance determining, and 772 as benign. With these mutations, we could predict 89·2% of the validation-set phenotypes with a mean 92·3% sensitivity (95% CI 90·7–93·7) and 98·4% specificity (98·1–98·7). 10·8% of validation-set phenotypes could not be predicted because uncharacterised mutations were present. With an in-silico comparison, characterised resistance determinants had higher sensitivity than the mutations from three line-probe assays (85·1% vs 81·6%). No additional resistance determinants were identified among mutations under selection pressure in non-candidate genes. A broad catalogue of genetic mutations enable data from whole-genome sequencing to be used clinically to predict drug resistance, drug susceptibility, or to identify drug phenotypes that cannot yet be genetically predicted. This approach could be integrated into routine diagnostic workflows, phasing out phenotypic drug-susceptibility testing while reporting drug resistance early. Wellcome Trust, National Institute of Health Research, Medical Research Council, and the European Union.

Enterococcus faecalis is a commensal and nosocomial pathogen, which is also ubiquitous in animals and insects, representing a classical generalist microorganism. Here, we study E. faecalis isolates ranging from the pre-antibiotic era in 1936 up to 2018, covering a large set of host species including wild birds, mammals, healthy humans, and hospitalised patients. We sequence the bacterial genomes using short- and long-read techniques, and identify multiple extant hospital-associated lineages, with last common ancestors dating back as far as the 19th century. We find a population cohesively connected through homologous recombination, a metabolic flexibility despite a small genome size, and a stable large core genome. Our findings indicate that the apparent hospital adaptations found in hospital-associated E. faecalis lineages likely predate the “modern hospital” era, suggesting selection in another niche, and underlining the generalist nature of this nosocomial pathogen. Enterococcus faecalis is a commensal microorganism of animals, insects and humans, but also a nosocomial pathogen. Here, the authors analyse genomic sequences from E. faecalis isolates from animals and humans, and find that the last common ancestors of multiple hospital-associated lineages date to the pre-antibiotic era.

Bacterial antimicrobial resistance (AMR) poses a significant public health threat. The increase of both global awareness and affordable whole genome sequencing has yielded an ever-growing collection of bacterial genome sequence datasets and corresponding antibiotic resistance metadata. This enables the use of computational techniques, including machine learning (ML), to predict phenotypes and discover novel AMR-associated variants. With the great variety of resistance mechanisms to interrogate and the number of datasets that can be mined, there is a need to identify where novel AMR marker discovery is most necessary. Multiple databases and annotation pipelines exist to annotate AMR variants known to be associated with resistance to specific antibiotics or antibiotic classes, however, the completeness of these databases varies, and for some antibiotics, even the most complete databases remain insufficient for accurate classification. Here, we build predictive ML models using only those known markers, which we call “minimal models” of resistance. We predict the binary resistance phenotypes of 20 major antimicrobials in the genomically diverse pathogen Klebsiella pneumoniae, allowing us to identify their shortcomings in phenotype prediction, thereby highlighting opportunities for novel marker discovery. We provide a critical review of the differences in annotation tools and databases commonly used in bacterial AMR studies, and outline guidance for the establishment of a standard dataset for the development and benchmarking of ML models of AMR.

Tuberculosis incidence in the UK has risen in the past decade. Disease control depends on epidemiological data, which can be difficult to obtain. Whole-genome sequencing can detect microevolution within Mycobacterium tuberculosis strains. We aimed to estimate the genetic diversity of related M tuberculosis strains in the UK Midlands and to investigate how this measurement might be used to investigate community outbreaks. In a retrospective observational study, we used Illumina technology to sequence M tuberculosis genomes from an archive of frozen cultures. We characterised isolates into four groups: cross-sectional, longitudinal, household, and community. We measured pairwise nucleotide differences within hosts and between hosts in household outbreaks and estimated the rate of change in DNA sequences. We used the findings to interpret network diagrams constructed from 11 community clusters derived from mycobacterial interspersed repetitive-unit–variable-number tandem-repeat data. We sequenced 390 separate isolates from 254 patients, including representatives from all five major lineages of M tuberculosis. The estimated rate of change in DNA sequences was 0·5 single nucleotide polymorphisms (SNPs) per genome per year (95% CI 0·3–0·7) in longitudinal isolates from 30 individuals and 25 families. Divergence is rarely higher than five SNPs in 3 years. 109 (96%) of 114 paired isolates from individuals and households differed by five or fewer SNPs. More than five SNPs separated isolates from none of 69 epidemiologically linked patients, two (15%) of 13 possibly linked patients, and 13 (17%) of 75 epidemiologically unlinked patients (three-way comparison exact p<0·0001). Genetic trees and clinical and epidemiological data suggest that super-spreaders were present in two community clusters. Whole-genome sequencing can delineate outbreaks of tuberculosis and allows inference about direction of transmission between cases. The technique could identify super-spreaders and predict the existence of undiagnosed cases, potentially leading to early treatment of infectious patients and their contacts. Medical Research Council, Wellcome Trust, National Institute for Health Research, and the Health Protection Agency.

Since 2014, England has seen increased scarlet fever activity unprecedented in modern times. In 2016, England's scarlet fever seasonal rise coincided with an unexpected elevation in invasive Streptococcus pyogenes infections. We describe the molecular epidemiological investigation of these events. We analysed changes in S pyogenes emm genotypes, and notifications of scarlet fever and invasive disease in 2014–16 using regional (northwest London) and national (England and Wales) data. Genomes of 135 non-invasive and 552 invasive emm1 isolates from 2009–16 were analysed and compared with 2800 global emm1 sequences. Transcript and protein expression of streptococcal pyrogenic exotoxin A (SpeA; also known as scarlet fever or erythrogenic toxin A) in sequenced, non-invasive emm1 isolates was quantified by real-time PCR and western blot analyses. Coincident with national increases in scarlet fever and invasive disease notifications, emm1 S pyogenes upper respiratory tract isolates increased significantly in northwest London in the March to May period, from five (5%) of 96 isolates in 2014, to 28 (19%) of 147 isolates in 2015 (p=0·0021 vs 2014 values), to 47 (33%) of 144 in 2016 (p=0·0080 vs 2015 values). Similarly, invasive emm1 isolates collected nationally in the same period increased from 183 (31%) of 587 in 2015 to 267 (42%) of 637 in 2016 (p<0·0001). Sequences of emm1 isolates from 2009–16 showed emergence of a new emm1 lineage (designated M1UK)—with overlap of pharyngitis, scarlet fever, and invasive M1UK strains—which could be genotypically distinguished from pandemic emm1 isolates (M1global) by 27 single-nucleotide polymorphisms. Median SpeA protein concentration in supernatant was nine-times higher among M1UK isolates (190·2 ng/mL [IQR 168·9–200·4]; n=10) than M1global isolates (20·9 ng/mL [0·0–27·3]; n=10; p<0·0001). M1UK expanded nationally to represent 252 (84%) of all 299 emm1 genomes in 2016. Phylogenetic analysis of published datasets identified single M1UK isolates in Denmark and the USA. A dominant new emm1 S pyogenes lineage characterised by increased SpeA production has emerged during increased S pyogenes activity in England. The expanded reservoir of M1UK and recognised invasive potential of emm1 S pyogenes provide plausible explanation for the increased incidence of invasive disease, and rationale for global surveillance. UK Medical Research Council, UK National Institute for Health Research, Wellcome Trust, Rosetrees Trust, Stoneygate Trust.