Assessing the reliability of eBURST using simulated populations with known ancestry

BACKGROUND: The program eBURST uses multilocus sequence typing data to divide bacterial populations into groups of closely related strains (clonal complexes), predicts the founding genotype of each group, and displays the patterns of recent evolutionary descent of all other strains in the group from the founder. The reliability of eBURST was evaluated using populations simulated with different levels of recombination in which the ancestry of all strains was known. RESULTS: For strictly clonal simulations, where all allelic change is due to point mutation, the groups of related strains identified by eBURST were very similar to those expected from the true ancestry and most of the true ancestor-descendant relationships (90–98%) were identified by eBURST. Populations simulated with low or moderate levels of recombination showed similarly high performance but the reliability of eBURST declined with increasing recombination to mutation ratio. Populations simulated under a high recombination to mutation ratio were dominated by a single large straggly eBURST group, which resulted from the incorrect linking of unrelated groups of strains into the same eBURST group. The reliability of the ancestor-descendant links in eBURST diagrams was related to the proportion of strains in the largest eBURST group, which provides a useful guide to when eBURST is likely to be unreliable. CONCLUSION: Examination of eBURST groups within populations of a range of bacterial species showed that most were within the range in which eBURST is reliable, and only a small number (e.g. Burkholderia pseudomallei and Enterococcus faecium) appeared to have such high rates of recombination that eBURST is likely to be unreliable. The study also demonstrates how three simple tests in eBURST v3 can be used to detect unreliable eBURST performance and recognise populations in which there appears to be a high rate of recombination relative to mutation

Effectiveness and cost-effectiveness of traditional and new partner notification technologies for curable sexually transmitted infections: observational study, systematic reviews and mathematical modelling.

BACKGROUND: Partner notification is essential to the comprehensive case management of sexually transmitted infections. Systematic reviews and mathematical modelling can be used to synthesise information about the effects of new interventions to enhance the outcomes of partner notification. OBJECTIVE: To study the effectiveness and cost-effectiveness of traditional and new partner notification technologies for curable sexually transmitted infections (STIs). DESIGN: Secondary data analysis of clinical audit data; systematic reviews of randomised controlled trials (MEDLINE, EMBASE and Cochrane Central Register of Controlled Trials) published from 1 January 1966 to 31 August 2012 and of studies of health-related quality of life (HRQL) [MEDLINE, EMBASE, ISI Web of Knowledge, NHS Economic Evaluation Database (NHS EED), Database of Abstracts of Reviews of Effects (DARE) and Health Technology Assessment (HTA)] published from 1 January 1980 to 31 December 2011; static models of clinical effectiveness and cost-effectiveness; and dynamic modelling studies to improve parameter estimation and examine effectiveness. SETTING: General population and genitourinary medicine clinic attenders. PARTICIPANTS: Heterosexual women and men. INTERVENTIONS: Traditional partner notification by patient or provider referral, and new partner notification by expedited partner therapy (EPT) or its UK equivalent, accelerated partner therapy (APT). MAIN OUTCOME MEASURES: Population prevalence; index case reinfection; and partners treated per index case. RESULTS: Enhanced partner therapy reduced reinfection in index cases with curable STIs more than simple patient referral [risk ratio (RR) 0.71; 95% confidence interval (CI) 0.56 to 0.89]. There are no randomised trials of APT. The median number of partners treated for chlamydia per index case in UK clinics was 0.60. The number of partners needed to treat to interrupt transmission of chlamydia was lower for casual than for regular partners. In dynamic model simulations, >10% of partners are chlamydia positive with look-back periods of up to 18 months. In the presence of a chlamydia screening programme that reduces population prevalence, treatment of current partners achieves most of the additional reduction in prevalence attributable to partner notification. Dynamic model simulations show that cotesting and treatment for chlamydia and gonorrhoea reduce the prevalence of both STIs. APT has a limited additional effect on prevalence but reduces the rate of index case reinfection. Published quality-adjusted life-year (QALY) weights were of insufficient quality to be used in a cost-effectiveness study of partner notification in this project. Using an intermediate outcome of cost per infection diagnosed, doubling the efficacy of partner notification from 0.4 to 0.8 partners treated per index case was more cost-effective than increasing chlamydia screening coverage. CONCLUSIONS: There is evidence to support the improved clinical effectiveness of EPT in reducing index case reinfection. In a general heterosexual population, partner notification identifies new infected cases but the impact on chlamydia prevalence is limited. Partner notification to notify casual partners might have a greater impact than for regular partners in genitourinary clinic populations. Recommendations for future research are (1) to conduct randomised controlled trials using biological outcomes of the effectiveness of APT and of methods to increase testing for human immunodeficiency virus (HIV) and STIs after APT; (2) collection of HRQL data should be a priority to determine QALYs associated with the sequelae of curable STIs; and (3) standardised parameter sets for curable STIs should be developed for mathematical models of STI transmission that are used for policy-making. FUNDING: The National Institute for Health Research Health Technology Assessment programme

The Impact of the Human DNA Topoisomerase II C-Terminal Domain on Activity

Type II DNA topoisomerases (topos) are essential enzymes needed for the resolution of topological problems that occur during DNA metabolic processes. Topos carry out an ATP-dependent strand passage reaction whereby one double helix is passed through a transient break in another. Humans have two topoII isoforms, alpha and beta, which while enzymatically similar are differentially expressed and regulated, and are thought to have different cellular roles. The C-terminal domain (CTD) of the enzyme has the most diversity, and has been implicated in regulation. We sought to investigate the impact of the CTD domain on activity.We have investigated the role of the human topoII C-terminal domain by creating constructs encoding C-terminally truncated recombinant topoIIalpha and beta and topoIIalpha+beta-tail and topoIIbeta+alpha-tail chimeric proteins. We then investigated function in vivo in a yeast system, and in vitro in activity assays. We find that the C-terminal domain of human topoII isoforms is needed for in vivo function of the enzyme, but not needed for cleavage activity. C-terminally truncated enzymes had similar strand passage activity to full length enzymes, but the presence of the opposite C-terminal domain had a large effect, with the topoIIalpha-CTD increasing activity, and the topoIIbeta-CTD decreasing activity.In vivo complementation data show that the topoIIalpha C-terminal domain is needed for growth, but the topoIIbeta isoform is able to support low levels of growth without a C-terminal domain. This may indicate that topoIIbeta has an additional localisation signal. In vitro data suggest that, while the lack of any C-terminal domain has little effect on activity, the presence of either the topoIIalpha or beta C-terminal domain can affect strand passage activity. Data indicates that the topoIIbeta-CTD may be a negative regulator. This is the first report of in vitro data with chimeric human topoIIs

Extrinsically derived TNF is primarily responsible for limiting antiviral CD8+ T cell response magnitude.

TNF is a pro-inflammatory cytokine produced by both lymphoid and non-lymphoid cells. As a consequence of the widespread expression of its receptors (TNFR1 and 2), TNF plays a role in many important biological processes. In the context of influenza A virus (IAV) infection, TNF has variably been implicated in mediating immunopathology as well as suppression of the immune response. Although a number of cell types are able to produce TNF, the ability of CD8+ T cells to produce TNF following viral infection is a hallmark of their effector function. As such, the regulation and role of CD8+ T cell-derived TNF following viral infection is of great interest. Here, we show that the biphasic production of TNF by CD8+ T cells following in vitro stimulation corresponds to distinct patterns of epigenetic modifications. Further, we show that a global loss of TNF during IAV infection results in an augmentation of the peripheral virus-specific CD8+ T cell response. Subsequent adoptive transfer experiments demonstrated that this attenuation of the CD8+ T cell response was largely, but not exclusively, conferred by extrinsic TNF, with intrinsically-derived TNF making only modest contributions. In conclusion, TNF exerts an immunoregulatory role on CD8+ T cell responses following IAV infection, an effect that is largely mediated by extrinsically-derived TNF

A Novel Role for the NLRC4 Inflammasome in Mucosal Defenses against the Fungal Pathogen Candida albicans

Candida sp. are opportunistic fungal pathogens that colonize the skin and oral cavity and, when overgrown under permissive conditions, cause inflammation and disease. Previously, we identified a central role for the NLRP3 inflammasome in regulating IL-1β production and resistance to dissemination from oral infection with Candida albicans. Here we show that mucosal expression of NLRP3 and NLRC4 is induced by Candida infection, and up-regulation of these molecules is impaired in NLRP3 and NLRC4 deficient mice. Additionally, we reveal a role for the NLRC4 inflammasome in anti-fungal defenses. NLRC4 is important for control of mucosal Candida infection and impacts inflammatory cell recruitment to infected tissues, as well as protects against systemic dissemination of infection. Deficiency in either NLRC4 or NLRP3 results in severely attenuated pro-inflammatory and antimicrobial peptide responses in the oral cavity. Using bone marrow chimeric mouse models, we show that, in contrast to NLRP3 which limits the severity of infection when present in either the hematopoietic or stromal compartments, NLRC4 plays an important role in limiting mucosal candidiasis when functioning at the level of the mucosal stroma. Collectively, these studies reveal the tissue specific roles of the NLRP3 and NLRC4 inflammasome in innate immune responses against mucosal Candida infection

“Working the System”—British American Tobacco's Influence on the European Union Treaty and Its Implications for Policy: An Analysis of Internal Tobacco Industry Documents

Katherine Smith and colleagues investigate the ways in which British American Tobacco influenced the European Union Treaty so that new EU policies advance the interests of major corporations, including those that produce products damaging to health

Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands

Developing a realistic sexual network model of chlamydia transmission in Britain.

BACKGROUND: A national chlamydia screening programme is currently being rolled out in the UK and other countries. However, much of the epidemiology remains poorly understood. In this paper we present a stochastic, individual based, dynamic sexual network model of chlamydia transmission and its parameterisation. Mathematical models provide a theoretical framework for understanding the key epidemiological features of chlamydia: sexual behaviour, health care seeking and transmission dynamics. RESULTS: The model parameters were estimated either directly or by systematic fitting to a variety of appropriate data sources. The fitted model was representative of sexual behaviour, chlamydia epidemiology and health care use in England. We were able to recapture the observed age distribution of chlamydia prevalence. CONCLUSION: Estimating parameters for models of sexual behaviour and transmission of chlamydia is complex. Most of the parameter values are highly correlated, highly variable and there is little empirical evidence to inform estimates. We used a novel approach to estimate the rate of active treatment seeking, by combining data sources, which improved the credibility of the model results. The model structure is flexible and is broadly applicable to other developed world settings and provides a practical tool for public health decision makers