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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/ .

Background Next generation sequencing (NGS) technology has revolutionized genomic and genetic research. The pace of change in this area is rapid with three major new sequencing platforms having been released in 2011: Ion Torrent’s PGM, Pacific Biosciences’ RS and the Illumina MiSeq. Here we compare the results obtained with those platforms to the performance of the Illumina HiSeq, the current market leader. In order to compare these platforms, and get sufficient coverage depth to allow meaningful analysis, we have sequenced a set of 4 microbial genomes with mean GC content ranging from 19.3 to 67.7%. Together, these represent a comprehensive range of genome content. Here we report our analysis of that sequence data in terms of coverage distribution, bias, GC distribution, variant detection and accuracy. Results Sequence generated by Ion Torrent, MiSeq and Pacific Biosciences technologies displays near perfect coverage behaviour on GC-rich, neutral and moderately AT-rich genomes, but a profound bias was observed upon sequencing the extremely AT-rich genome of Plasmodium falciparum on the PGM, resulting in no coverage for approximately 30% of the genome. We analysed the ability to call variants from each platform and found that we could call slightly more variants from Ion Torrent data compared to MiSeq data, but at the expense of a higher false positive rate. Variant calling from Pacific Biosciences data was possible but higher coverage depth was required. Context specific errors were observed in both PGM and MiSeq data, but not in that from the Pacific Biosciences platform. Conclusions All three fast turnaround sequencers evaluated here were able to generate usable sequence. However there are key differences between the quality of that data and the applications it will support.

Francis Drobniewski and colleagues report the whole-genome sequencing of 1,000 Mycobacterium tuberculosis strains obtained prospectively from patients over a 2-year period in Samara, Russia, a region with a high incidence of multidrug-resistant (MDR) tuberculosis. They compare these strains to a diverse panel of strains isolated from across the UK and characterize the patterns of the emergence and evolution of drug resistance. The molecular mechanisms determining the transmissibility and prevalence of drug-resistant tuberculosis in a population were investigated through whole-genome sequencing of 1,000 prospectively obtained patient isolates from Russia. Two-thirds belonged to the Beijing lineage, which was dominated by two homogeneous clades. Multidrug-resistant (MDR) genotypes were found in 48% of isolates overall and in 87% of the major clades. The most common rpoB mutation was associated with fitness-compensatory mutations in rpoA or rpoC , and a new intragenic compensatory substitution was identified. The proportion of MDR cases with extensively drug-resistant (XDR) tuberculosis was 16% overall, with 65% of MDR isolates harboring eis mutations, selected by kanamycin therapy, which may drive the expansion of strains with enhanced virulence. The combination of drug resistance and compensatory mutations displayed by the major clades confers clinical resistance without compromising fitness and transmissibility, showing that, in addition to weaknesses in the tuberculosis control program, biological factors drive the persistence and spread of MDR and XDR tuberculosis in Russia and beyond.

Background. Treatment of Neisseria gonorrhoeae infection is empirical and based on population-wide susceptibilities. Increasing antimicrobial resistance underscores the potential importance of rapid diagnostic tests, including sequence-based tests, to guide therapy. However, the usefulness of sequence-based diagnostic tests depends on the prevalence and dynamics of the resistance mechanisms. Methods. We define the prevalence and dynamics of resistance markers to extended-spectrum cephalosporins, macrolides, and fluoroquinolones in 1102 resistant and susceptible clinical N. gonorrhoeae isolates collected from 2000 to 2013 via the Centers for Disease Control and Prevention's Gonococcal Isolate Surveillance Project. Results. Reduced extended-spectrum cephalosporin susceptibility is predominantly clonal and associated with the mosaic penA XXXIV allele and derivatives (sensitivity 98% for cefixime and 91% for ceftriaxone), but alternative resistance mechanisms have sporadically emerged. Reduced azithromycin susceptibility has arisen through multiple mechanisms and shows limited clonal spread; the basis for resistance in 36% of isolates with reduced azithromycin susceptibility is unclear. Quinolone-resistant N. gonorrhoeae has arisen multiple times, with extensive clonal spread. Conclusions. Quinolone-resistant N. gonorrhoeae and reduced cefixime susceptibility appear amenable to development of sequence-based diagnostic tests, whereas the undefined mechanisms of resistance to ceftriaxone and azithromycin underscore the importance of phenotypic surveillance. The identification of multidrug-resistant isolates highlights the need for additional measures to respond to the threat of untreatable gonorrhea.

Increasing numbers of individuals with cystic fibrosis are becoming infected with the multidrug-resistant non-tuberculous mycobacterium (NTM) Mycobacterium abscessus, which causes progressive lung damage and is extremely challenging to treat. How this organism is acquired is not currently known, but there is growing concern that person-to-person transmission could occur. We aimed to define the mechanisms of acquisition of M abscessus in individuals with cystic fibrosis. Whole genome sequencing and antimicrobial susceptibility testing were done on 168 consecutive isolates of M abscessus from 31 patients attending an adult cystic fibrosis centre in the UK between 2007 and 2011. In parallel, we undertook detailed environmental testing for NTM and defined potential opportunities for transmission between patients both in and out of hospital using epidemiological data and social network analysis. Phylogenetic analysis revealed two clustered outbreaks of near-identical isolates of the M abscessus subspecies massiliense (from 11 patients), differing by less than ten base pairs. This variation represents less diversity than that seen within isolates from a single individual, strongly indicating between-patient transmission. All patients within these clusters had numerous opportunities for within-hospital transmission from other individuals, while comprehensive environmental sampling, initiated during the outbreak, failed to detect any potential point source of NTM infection. The clusters of M abscessus subspecies massiliense showed evidence of transmission of mutations acquired during infection of an individual to other patients. Thus, isolates with constitutive resistance to amikacin and clarithromycin were isolated from several individuals never previously exposed to long-term macrolides or aminoglycosides, further indicating cross-infection. Whole genome sequencing has revealed frequent transmission of multidrug resistant NTM between patients with cystic fibrosis despite conventional cross-infection measures. Although the exact transmission route is yet to be established, our epidemiological analysis suggests that it could be indirect. The Wellcome Trust, Papworth Hospital, NIHR Cambridge Biomedical Research Centre, UK Health Protection Agency, Medical Research Council, and the UKCRC Translational Infection Research Initiative.

Group A Streptococcus (GAS; Streptococcus pyogenes ) is a bacterial pathogen for which a commercial vaccine for humans is not available. Employing the advantages of high-throughput DNA sequencing technology to vaccine design, we have analyzed 2,083 globally sampled GAS genomes. The global GAS population structure reveals extensive genomic heterogeneity driven by homologous recombination and overlaid with high levels of accessory gene plasticity. We identified the existence of more than 290 clinically associated genomic phylogroups across 22 countries, highlighting challenges in designing vaccines of global utility. To determine vaccine candidate coverage, we investigated all of the previously described GAS candidate antigens for gene carriage and gene sequence heterogeneity. Only 15 of 28 vaccine antigen candidates were found to have both low naturally occurring sequence variation and high (>99%) coverage across this diverse GAS population. This technological platform for vaccine coverage determination is equally applicable to prospective GAS vaccine antigens identified in future studies. Analyses of 2,083 globally distributed group A Streptococcus (GAS) genomes enable the development of a compendium of all GAS vaccine antigen sequences, providing a platform for population-genomics-informed vaccine design.

Prediction of antibiotic resistance phenotypes from whole genome sequencing data by machine learning methods has been proposed as a promising platform for the development of sequence-based diagnostics. However, there has been no systematic evaluation of factors that may influence performance of such models, how they might apply to and vary across clinical populations, and what the implications might be in the clinical setting. Here, we performed a meta-analysis of seven large Neisseria gonorrhoeae datasets, as well as Klebsiella pneumoniae and Acinetobacter baumannii datasets, with whole genome sequence data and antibiotic susceptibility phenotypes using set covering machine classification, random forest classification, and random forest regression models to predict resistance phenotypes from genotype. We demonstrate how model performance varies by drug, dataset, resistance metric, and species, reflecting the complexities of generating clinically relevant conclusions from machine learning-derived models. Our findings underscore the importance of incorporating relevant biological and epidemiological knowledge into model design and assessment and suggest that doing so can inform tailored modeling for individual drugs, pathogens, and clinical populations. We further suggest that continued comprehensive sampling and incorporation of up-to-date whole genome sequence data, resistance phenotypes, and treatment outcome data into model training will be crucial to the clinical utility and sustainability of machine learning-based molecular diagnostics.

A large isoniazid-resistant tuberculosis outbreak centred on London, United Kingdom, has been ongoing since 1995. The aim of this study was to investigate the power and value of whole genome sequencing (WGS) to resolve the transmission network compared to current molecular strain typing approaches, including analysis of intra-host diversity within a specimen, across body sites, and over time, with identification of genetic factors underlying the epidemiological success of this cluster. We sequenced 344 outbreak isolates from individual patients collected over 14 y (2 February 1998-22 June 2012). This demonstrated that 96 (27.9%) were indistinguishable, and only one differed from this major clone by more than five single nucleotide polymorphisms (SNPs). The maximum number of SNPs between any pair of isolates was nine SNPs, and the modal distance between isolates was two SNPs. WGS was able to reveal the direction of transmission of tuberculosis in 16 cases within the outbreak (4.7%), including within a multidrug-resistant cluster that carried a rare rpoB mutation associated with rifampicin resistance. Eleven longitudinal pairs of patient pulmonary isolates collected up to 48 mo apart differed from each other by between zero and four SNPs. Extrapulmonary dissemination resulted in acquisition of a SNP in two of five cases. WGS analysis of 27 individual colonies cultured from a single patient specimen revealed ten loci differed amongst them, with a maximum distance between any pair of six SNPs. A limitation of this study, as in previous studies, is that indels and SNPs in repetitive regions were not assessed due to the difficulty in reliably determining this variation. Our study suggests that (1) certain paradigms need to be revised, such as the 12 SNP distance as the gold standard upper threshold to identify plausible transmissions; (2) WGS technology is helpful to rule out the possibility of direct transmission when isolates are separated by a substantial number of SNPs; (3) the concept of a transmission chain or network may not be useful in institutional or household settings; (4) the practice of isolating single colonies prior to sequencing is likely to lead to an overestimation of the number of SNPs between cases resulting from direct transmission; and (5) despite appreciable genomic diversity within a host, transmission of tuberculosis rarely results in minority variants becoming dominant. Thus, whilst WGS provided some increased resolution over variable number tandem repeat (VNTR)-based clustering, it was insufficient for inferring transmission in the majority of cases.

Three 1,000-year-old mycobacterial genomes from Peruvian human skeletons reveal that a member of the Mycobacterium tuberculosis complex derived from seals caused human disease before contact in the Americas. Tuberculosis in the Americas Mycobacterium tuberculosis has a long history as a human pathogen, but how and when this unfortunate relationship began is not clear. Although the strains found in the Americas today are closely related to those in Europe, archaeological evidence suggests that the disease was present in the New World before contact with Europeans. Johannes Krause and colleagues sequenced three approximately 1,000-year-old M. tuberculosis genomes from human remains in Peru, proving that the pathogen caused human disease in the pre-contact New World. The ancient DNA is most closely related to that found in strains adapted to seals and sea lions. The authors hypothesize that these sea mammals may have contracted the disease from an African host species and carried it across the oceans where exploitation of marine resources by coastal peoples of South America allowed zoonotic transfer. This strain of tuberculosis may have then adapted to humans before being replaced by European strains introduced post-contact. Modern strains of Mycobacterium tuberculosis from the Americas are closely related to those from Europe, supporting the assumption that human tuberculosis was introduced post-contact 1 . This notion, however, is incompatible with archaeological evidence of pre-contact tuberculosis in the New World 2 . Comparative genomics of modern isolates suggests that M. tuberculosis attained its worldwide distribution following human dispersals out of Africa during the Pleistocene epoch 3 , although this has yet to be confirmed with ancient calibration points. Here we present three 1,000-year-old mycobacterial genomes from Peruvian human skeletons, revealing that a member of the M. tuberculosis complex caused human disease before contact. The ancient strains are distinct from known human-adapted forms and are most closely related to those adapted to seals and sea lions. Two independent dating approaches suggest a most recent common ancestor for the M. tuberculosis complex less than 6,000 years ago, which supports a Holocene dispersal of the disease. Our results implicate sea mammals as having played a role in transmitting the disease to humans across the ocean.

Bacterial genomes vary extensively in terms of both gene content and gene sequence. This plasticity hampers the use of traditional SNP-based methods for identifying all genetic associations with phenotypic variation. Here we introduce a computationally scalable and widely applicable statistical method (SEER) for the identification of sequence elements that are significantly enriched in a phenotype of interest. SEER is applicable to tens of thousands of genomes by counting variable-length k-mers using a distributed string-mining algorithm. Robust options are provided for association analysis that also correct for the clonal population structure of bacteria. Using large collections of genomes of the major human pathogens Streptococcus pneumoniae and Streptococcus pyogenes , SEER identifies relevant previously characterized resistance determinants for several antibiotics and discovers potential novel factors related to the invasiveness of S. pyogenes . We thus demonstrate that our method can answer important biologically and medically relevant questions. Plasticity and clonal population structure in bacterial genomes can hinder traditional SNP-based genetic association studies. Here, Corander and colleagues present a method to identify variable-length sequence elements enriched in a phenotype of interest, and demonstrate its use in human pathogens.