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Background: New approaches are urgently required to address increasing rates of gonorrhoea and the emergence and global spread of antibiotic-resistant Neisseria gonorrhoeae. We used whole-genome sequencing to study transmission and track resistance in N gonorrhoeae isolates., Methods: We did whole-genome sequencing of isolates obtained from samples collected from patients attending sexual health services in Brighton, UK, between Jan 1, 2011, and March 9, 2015. We also included isolates from other UK locations, historical isolates from Brighton, and previous data from a US study. Samples from symptomatic patients and asymptomatic sexual health screening underwent nucleic acid amplification testing; positive samples and all samples from symptomatic patients were cultured for N gonorrhoeae, and resulting isolates were whole-genome sequenced. Cefixime susceptibility testing was done in selected isolates by agar incorporation, and we used sequence data to determine multi-antigen sequence types and penA genotypes. We derived a transmission nomogram to determine the plausibility of direct or indirect transmission between any two cases depending on the time between samples: estimated mutation rates, plus diversity noted within patients across anatomical sites and probable transmission pairs, were used to fit a coalescent model to determine the number of single nucleotide polymorphisms expected., Findings: 1407 (98%) of 1437 Brighton isolates between Jan 1, 2011, and March 9, 2015 were successfully sequenced. We identified 1061 infections from 907 patients. 281 (26%) of these infections were indistinguishable (ie, differed by zero single nucleotide polymorphisms) from one or more previous cases, and 786 (74%) had evidence of a sampled direct or indirect Brighton source. We observed multiple related samples across geographical locations. Of 1273 infections in Brighton (including historical data), 225 (18%) were linked to another case elsewhere in the UK, and 115 (9%) to a case in the USA. Four lineages initially identified in Brighton could be linked to 70 USA sequences, including 61 from a lineage carrying the mosaic penA XXXIV allele, which is associated with reduced cefixime susceptibility., Interpretation: We present a whole-genome-sequencing-based tool for genomic contact tracing of N gonorrhoeae and demonstrate local, national, and international transmission. Whole-genome sequencing can be applied across geographical boundaries to investigate gonorrhoea transmission and to track antimicrobial resistance., Funding: Oxford National Institute for Health Research Health Protection Research Unit and Biomedical Research Centre., Competing Interests: Declaration of interests The authors have no conflict of interest., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The rise in gonococcal antibiotic resistance and the threat of untreatable infection are focusing attention on strategies to limit the spread of drug-resistant gonorrhea. Mathematical models provide a framework to link the natural history of infection and patient behavior to epidemiological outcomes and can be used to guide research and enhance the public health impact of interventions. While limited knowledge of key disease parameters and networks of spread has impeded development of operational models of gonococcal transmission, new tools in gonococcal surveillance may provide useful data to aid tracking and modeling. Here, we highlight critical questions in the management of gonorrhea that can be addressed by mathematical models and identify key data needs. Our overarching aim is to articulate a shared agenda across gonococcus-related fields from microbiology to epidemiology that will catalyze a comprehensive evidence-based clinical and public health strategy for management of gonococcal infections and antimicrobial resistance., (© The Author 2015. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.)

Summary: Many studies report the high prevalence of multiply drug-resistant (MDR) strains. Because MDR infections are often significantly harder and more expensive to treat, they represent a growing public health threat. However, for different pathogens, different underlying mechanisms are traditionally used to explain these observations, and it is unclear whether each bacterial taxon has its own mechanism(s) for multidrug resistance or whether there are common mechanisms between distantly related pathogens. In this review, we provide a systematic overview of the causes of the excess of MDR infections and define testable predictions made by each hypothetical mechanism, including experimental, epidemiological, population genomic, and other tests of these hypotheses. Better understanding the cause(s) of the excess of MDR is the first step to rational design of more effective interventions to prevent the origin and/or proliferation of MDR., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

Epidemiologists aim to inform the design of public health interventions with evidence on the evolution, emergence and spread of infectious diseases. Sequencing of pathogen genomes, together with date, location, clinical manifestation and other relevant data about sample origins, can contribute to describing nearly every aspect of transmission dynamics, including local transmission and global spread. The analyses of these data have implications for all levels of clinical and public health practice, from institutional infection control to policies for surveillance, prevention and treatment. This review highlights the range of epidemiological questions that can be addressed from the combination of genome sequence and traditional 'line lists' (tables of epidemiological data where each line includes demographic and clinical features of infected individuals). We identify opportunities for these data to inform interventions that reduce disease incidence and prevalence. By considering current limitations of, and challenges to, interpreting these data, we aim to outline a research agenda to accelerate the genomics-driven transformation in public health microbiology.

Pathogen evolution is influenced strongly by the host immune response. Previous studies of the effects of herd immunity on the population structure of directly transmitted, short-lived pathogens have primarily focused on the impact of competition for hosts. In contrast, for long-lived infections like HIV, theoretical work has focused on the mechanisms promoting antigenic variation within the host. In reality, successful transmission requires that pathogens balance both within- and between-host immune selection. The Opa adhesins in the bacterial Neisseria genus provide a unique system to study the evolution of the same antigens across two major pathogens: while N. meningitidis is an airborne, respiratory pathogen colonising the nasopharynx relatively transiently, N. gonorrhoeae can cause sexually transmitted, long-lived infections. We use a simple mathematical model and genomic data to show that trade-offs between immune selection pressures within- and between-hosts can explain the contrasting Opa repertoires observed in meningococci and gonococci.

Unlabelled: Human respiratory syncytial virus (RSV) is the leading cause of lower respiratory tract disease in infants and young children and an important respiratory pathogen in the elderly and immunocompromised. While population-wide molecular epidemiology studies have shown multiple cocirculating RSV genotypes and revealed antigenic and genetic change over successive seasons, little is known about the extent of viral diversity over the course of an individual infection, the origins of novel variants, or the effect of immune pressure on viral diversity and potential immune-escape mutations. To investigate viral population diversity in the presence and absence of selective immune pressures, we studied whole-genome deep sequencing of RSV in upper airway samples from an infant with severe combined immune deficiency syndrome and persistent RSV infection. The infection continued over several months before and after bone marrow transplant (BMT) from his RSV-immune father. RSV diversity was characterized in 26 samples obtained over 78 days. Diversity increased after engraftment, as defined by T-cell presence, and populations reflected variation mostly within the G protein, the major surface antigen. Minority populations with known palivizumab resistance mutations emerged after its administration. The viral population appeared to diversify in response to selective pressures, showing a statistically significant growth in diversity in the presence of pressure from immunity. Defining escape mutations and their dynamics will be useful in the design and application of novel therapeutics and vaccines. These data can contribute to future studies of the relationship between within-host and population-wide RSV phylodynamics., Importance: Human RSV is an important cause of respiratory disease in infants, the elderly, and the immunocompromised. RSV circulating in a community appears to change season by season, but the amount of diversity generated during an individual infection and the impact of immunity on this viral diversity has been unclear. To address this question, we described within-host RSV diversity by whole-genome deep sequencing in a unique clinical case of an RSV-infected infant with severe combined immunodeficiency and effectively no adaptive immunity who then gained adaptive immunity after undergoing bone marrow transplantation. We found that viral diversity increased in the presence of adaptive immunity and was primarily within the G protein, the major surface antigen. These data will be useful in designing RSV treatments and vaccines and to help understand the relationship between the dynamics of viral diversification within individual hosts and the viral populations circulating in a community., (Copyright © 2014, American Society for Microbiology. All Rights Reserved.)

Background: The emergence of Neisseria gonorrhoeae with decreased susceptibility to extended spectrum cephalosporins raises the prospect of untreatable gonorrhoea. In the absence of new treatments, efforts to slow the increasing incidence of resistant gonococcus require insight into the factors that contribute to its emergence and spread. We assessed the relatedness between isolates in the USA and reconstructed likely spread of lineages through different sexual networks., Methods: We sequenced the genomes of 236 isolates of N gonorrhoeae collected by the Centers for Disease Control and Prevention's Gonococcal Isolate Surveillance Project (GISP) from sentinel public sexually transmitted disease clinics in the USA, including 118 (97%) of the isolates from 2009-10 in GISP with reduced susceptibility to cefixime (cef(RS)) and 118 cefixime-susceptible isolates from GISP matched as closely as possible by location, collection date, and sexual orientation. We assessed the association between antimicrobial resistance genotype and phenotype and correlated phylogenetic clustering with location and sexual orientation., Findings: Mosaic penA XXXIV had a high positive predictive value for cef(RS). We found that two of the 118 cef(RS) isolates lacked a mosaic penA allele, and rechecking showed that these two were susceptible to cefixime. Of the 116 remaining cef(RS) isolates, 114 (98%) fell into two distinct lineages that have independently acquired mosaic penA allele XXXIV. A major lineage of cef(RS) strains spread eastward, predominantly through a sexual network of men who have sex with men. Eight of nine inferred transitions between sexual networks were introductions from men who have sex with men into the heterosexual population., Interpretation: Genomic methods might aid efforts to slow the spread of antibiotic-resistant N gonorrhoeae through augmentation of gonococcal outbreak surveillance and identification of populations that could benefit from increased screening for asymptomatic infections., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

The devastating Haitian cholera outbreak that began in October 2010 is the first known cholera epidemic in this island nation. Epidemiological and genomic data have provided strong evidence that United Nations security forces from Nepal introduced toxigenic Vibrio cholerae O1, the cause of epidemic cholera, to Haiti shortly before the outbreak arose. However, some have contended that indigenous V. cholerae contributed to the outbreak. In a recent paper (mBio 4:e00398-13, 2013), L. S. Katz et al. explored the nature and rate of changes in this ancient pathogen's genome during an outbreak, based on whole-genome sequencing of 23 Haitian V. cholerae clinical isolates obtained over a 20-month period. Notably, they detected point mutations, deletions, and inversions but found no insertion of horizontally transmitted DNA, arguing strongly against the idea that autochthonous V. cholerae donated DNA to the outbreak strain. Furthermore, they found that Haitian epidemic V. cholerae isolates were virtually untransformable. Comparative genomic analyses revealed that the Haitian isolates were nearly identical to isolates from Nepal and that the Nepalese-Haitian isolates were distinguishable from isolates circulating elsewhere in the world. Reconstruction of the phylogeny of the Haitian isolates was consistent with a single introduction of V. cholerae to Haiti sometime between late July and late October 2010, dates remarkably concordant with epidemiological observations. In aggregate, this paper provides additional compelling evidence that the V. cholerae strain responsible for the Haitian cholera epidemic came from Nepal and illustrates the power of whole-genome-based analyses for epidemiology, pathogen evolution, and forensics.

Sequence data are well established in the reconstruction of the phylogenetic and demographic scenarios that have given rise to outbreaks of viral pathogens. The application of similar methods to bacteria has been hindered in the main by the lack of high-resolution nucleotide sequence data from quality samples. Developing and already available genomic methods have greatly increased the amount of data that can be used to characterize an isolate and its relationship to others. However, differences in sequencing platforms and data analysis mean that these enhanced data come with a cost in terms of portability: results from one laboratory may not be directly comparable with those from another. Moreover, genomic data for many bacteria bear the mark of a history including extensive recombination, which has the potential to greatly confound phylogenetic and coalescent analyses. Here, we discuss the exacting requirements of genomic epidemiology, and means by which the distorting signal of recombination can be minimized to permit the leverage of growing datasets of genomic data from bacterial pathogens.

Unlabelled: The large outbreak of diarrhea and hemolytic uremic syndrome (HUS) caused by Shiga toxin-producing Escherichia coli O104:H4 in Europe from May to July 2011 highlighted the potential of a rarely identified E. coli serogroup to cause severe disease. Prior to the outbreak, there were very few reports of disease caused by this pathogen and thus little known of its diversity and evolution. The identification of cases of HUS caused by E. coli O104:H4 in France and Turkey after the outbreak and with no clear epidemiological links raises questions about whether these sporadic cases are derived from the outbreak. Here, we report genome sequences of five independent isolates from these cases and results of a comparative analysis with historical and 2011 outbreak isolates. These analyses revealed that the five isolates are not derived from the outbreak strain; however, they are more closely related to the outbreak strain and each other than to isolates identified prior to the 2011 outbreak. Over the short time scale represented by these closely related organisms, the majority of genome variation is found within their mobile genetic elements: none of the nine O104:H4 isolates compared here contain the same set of plasmids, and their prophages and genomic islands also differ. Moreover, the presence of closely related HUS-associated E. coli O104:H4 isolates supports the contention that fully virulent O104:H4 isolates are widespread and emphasizes the possibility of future food-borne E. coli O104:H4 outbreaks., Importance: In the summer of 2011, a large outbreak of bloody diarrhea with a high rate of severe complications took place in Europe, caused by a previously rarely seen Escherichia coli strain of serogroup O104:H4. Identification of subsequent infections caused by E. coli O104:H4 raised questions about whether these new cases represented ongoing transmission of the outbreak strain. In this study, we sequenced the genomes of isolates from five recent cases and compared them with historical isolates. The analyses reveal that, in the very short term, evolution of the bacterial genome takes place in parts of the genome that are exchanged among bacteria, and these regions contain genes involved in adaptation to local environments. We show that these recent isolates are not derived from the outbreak strain but are very closely related and share many of the same disease-causing genes, emphasizing the concern that these bacteria may cause future severe outbreaks.

Several mathematical models of epidemic cholera have recently been proposed in response to outbreaks in Zimbabwe and Haiti. These models aim to estimate the dynamics of cholera transmission and the impact of possible interventions, with a goal of providing guidance to policy makers in deciding among alternative courses of action, including vaccination, provision of clean water, and antibiotics. Here, we discuss concerns about model misspecification, parameter uncertainty, and spatial heterogeneity intrinsic to models for cholera. We argue for caution in interpreting quantitative predictions, particularly predictions of the effectiveness of interventions. We specify sensitivity analyses that would be necessary to improve confidence in model-based quantitative prediction, and suggest types of monitoring in future epidemic settings that would improve analysis and prediction.

The degree to which molecular epidemiology reveals information about the sources and transmission patterns of an outbreak depends on the resolution of the technology used and the samples studied. Isolates of Escherichia coli O104:H4 from the outbreak centered in Germany in May-July 2011, and the much smaller outbreak in southwest France in June 2011, were indistinguishable by standard tests. We report a molecular epidemiological analysis using multiplatform whole-genome sequencing and analysis of multiple isolates from the German and French outbreaks. Isolates from the German outbreak showed remarkably little diversity, with only two single nucleotide polymorphisms (SNPs) found in isolates from four individuals. Surprisingly, we found much greater diversity (19 SNPs) in isolates from seven individuals infected in the French outbreak. The German isolates form a clade within the more diverse French outbreak strains. Moreover, five isolates derived from a single infected individual from the French outbreak had extremely limited diversity. The striking difference in diversity between the German and French outbreak samples is consistent with several hypotheses, including a bottleneck that purged diversity in the German isolates, variation in mutation rates in the two E. coli outbreak populations, or uneven distribution of diversity in the seed populations that led to each outbreak.

Helicobacter pylori seroprevalence levels in US adults participating in the continuous National Health and Nutrition Examination Survey (1999-2000) increased with age in all racial/ethnic groups, with significantly higher age-standardized levels in Mexican Americans (64.0%, 95% confidence interval (CI): 58.8, 69.2) and non-Hispanic blacks (52.0%, 95% CI: 48.3, 55.7) compared with non-Hispanic whites (21.2%, 95% CI: 19.1, 23.2). Although seroprevalence levels remained similar to those found in National Health and Nutrition Examination Surveys from 1988 to 1991 among non-Hispanic blacks and Mexican Americans, they were significantly lower in non-Hispanic whites, especially at older ages. The factors driving the decline in H. pylori seroprevalence appear to be acting preferentially on the non-Hispanic white population.

Motivation: To date, computational searches for cis-regulatory modules (CRMs) have relied on two methods. The first, phylogenetic footprinting, has been used to find CRMs in non-coding sequence, but does not directly link DNA sequence with spatio-temporal patterns of expression. The second, based on searches for combinations of transcription factor (TF) binding motifs, has been employed in genome-wide discovery of similarly acting enhancers, but requires prior knowledge of the set of TFs acting at the CRM and the TFs' binding motifs., Results: We propose a method for CRM discovery that combines aspects of both approaches in an effort to overcome their individual limitations. By treating phylogenetically footprinted non-coding regions (PFRs) as proxies for CRMs, we endeavor to find PFRs near co-regulated genes that are comprised of similar short, conserved sequences. Using Markov chains as a convenient formulation to assess similarity, we develop a sampling algorithm to search a large group of PFRs for the most similar subset. When starting with a set of genes involved in Drosophila early blastoderm development and using phylogenetic comparisons of Drosophila melanogaster and D.pseudoobscura genomes, we show here that our algorithm successfully detects known CRMs. Further, we use our similarity metric, based on Markov chain discrimination, in a genome-wide search, and uncover additional known and many candidate early blastoderm CRMs., Availability: Software is available via http://arep.med.harvard.edu/enhancer