Borrelia burgdorferi BBK32 Inhibits the Classical Pathway by Blocking Activation of the C1 Complement Complex

Citation: Garcia, B. L., Zhi, H., Wager, B., Hook, M., & Skare, J. T. (2016). Borrelia burgdorferi BBK32 Inhibits the Classical Pathway by Blocking Activation of the C1 Complement Complex. Plos Pathogens, 12(1), 28. doi:10.1371/journal.ppat.1005404Pathogens that traffic in blood, lymphatics, or interstitial fluids must adopt strategies to evade innate immune defenses, notably the complement system. Through recruitment of host regulators of complement to their surface, many pathogens are able to escape complement-mediated attack. The Lyme disease spirochete, Borrelia burgdorferi, produces a number of surface proteins that bind to factor H related molecules, which function as the dominant negative regulator of the alternative pathway of complement. Relatively less is known about how B. burgdorferi evades the classical pathway of complement despite the observation that some sensu lato strains are sensitive to classical pathway activation. Here we report that the borrelial lipoprotein BBK32 potently and specifically inhibits the classical pathway by binding with high affinity to the initiating C1 complex of complement. In addition, B. burgdorferi cells that produce BBK32 on their surface bind to both C1 and C1r and a serum sensitive derivative of B. burgdorferi is protected from killing via the classical pathway in a BBK32-dependent manner. Subsequent biochemical and biophysical approaches localized the anti-complement activity of BBK32 to its globular C-terminal domain. Mechanistic studies reveal that BBK32 acts by entrapping C1 in its zymogen form by binding and inhibiting the C1 subcomponent, C1r, which serves as the initiating serine protease of the classical pathway. To our knowledge this is the first report of a spirochetal protein acting as a direct inhibitor of the classical pathway and is the only example of a biomolecule capable of specifically and noncovalently inhibiting C1/C1r. By identifying a unique mode of complement evasion this study greatly enhances our understanding of how pathogens subvert and potentially manipulate host innate immune systems

An evaluation of 9-1-1 calls to assess the effectiveness of dispatch-assisted cardiopulmonary resuscitation (CPR) instructions: design and methodology

<p>Abstract</p> <p>Background</p> <p>Cardiac arrest is the leading cause of mortality in Canada, and the overall survival rate for out-of-hospital cardiac arrest rarely exceeds 5%. Bystander cardiopulmonary resuscitation (CPR) has been shown to increase survival for cardiac arrest victims. However, bystander CPR rates remain low in Canada, rarely exceeding 15%, despite various attempts to improve them. Dispatch-assisted CPR instructions have the potential to improve rates of bystander CPR and many Canadian urban communities now offer instructions to callers reporting a victim in cardiac arrest. Dispatch-assisted CPR instructions are recommended by the International Guidelines on Emergency Cardiovascular Care, but their ability to improve cardiac arrest survival remains unclear.</p> <p>Methods/Design</p> <p>The overall goal of this study is to better understand the factors leading to successful dispatch-assisted CPR instructions and to ultimately save the lives of more cardiac arrest patients. The study will utilize a before-after, prospective cohort design to specifically: 1) Determine the ability of 9-1-1 dispatchers to correctly diagnose cardiac arrest; 2) Quantify the frequency and impact of perceived agonal breathing on cardiac arrest diagnosis; 3) Measure the frequency with which dispatch-assisted CPR instructions can be successfully completed; and 4) Measure the impact of dispatch-assisted CPR instructions on bystander CPR and survival rates.</p> <p>The study will be conducted in 19 urban communities in Ontario, Canada. All 9-1-1 calls occurring in the study communities reporting out-of-hospital cardiac arrest in victims 16 years of age or older for which resuscitation was attempted will be eligible. Information will be obtained from 9-1-1 call recordings, paramedic patient care reports, base hospital records, fire medical records and hospital medical records. Victim, caller and system characteristics will be measured in the study communities before the introduction of dispatch-assisted CPR instructions (before group), during the introduction (run-in phase), and following the introduction (after group).</p> <p>Discussion</p> <p>The study will obtain information essential to the development of clinical trials that will test a variety of educational approaches and delivery methods for telephone cardiopulmonary resuscitation instructions. This will be the first study in the world to clearly quantify the impact of dispatch-assisted CPR instructions on survival to hospital discharge for out-of-hospital cardiac arrest victims.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov NCT00664443</p

Testing for heterogeneity among the components of a binary composite outcome in a clinical trial

<p>Abstract</p> <p>Background</p> <p>Investigators designing clinical trials often use composite outcomes to overcome many statistical issues. Trialists want to maximize power to show a statistically significant treatment effect and avoid inflation of Type I error rate due to evaluation of multiple individual clinical outcomes. However, if the treatment effect is not similar among the components of this composite outcome, we are left not knowing how to interpret the treatment effect on the composite itself. Given significant heterogeneity among these components, a composite outcome may be judged as being invalid or un-interpretable for estimation of the treatment effect. This paper compares the power of different tests to detect heterogeneity of treatment effect across components of a composite binary outcome.</p> <p>Methods</p> <p>Simulations were done comparing four different models commonly used to analyze correlated binary data. These models included: logistic regression for ignoring correlation, logistic regression weighted by the intra cluster correlation coefficient, population average logistic regression using generalized estimating equations (GEE), and random effects logistic regression.</p> <p>Results</p> <p>We found that the population average model based on generalized estimating equations (GEE) had the greatest power across most scenarios. Adequate power to detect possible composite heterogeneity or variation between treatment effects of individual components of a composite outcome was seen when the power for detecting the main study treatment effect for the composite outcome was also reasonably high.</p> <p>Conclusions</p> <p>It is recommended that authors report tests of composite heterogeneity for composite outcomes and that this accompany the publication of the statistically significant results of the main effect on the composite along with individual components of composite outcomes.</p

Application of Two-Part Statistics for Comparison of Sequence Variant Counts

Investigation of microbial communities, particularly human associated communities, is significantly enhanced by the vast amounts of sequence data produced by high throughput sequencing technologies. However, these data create high-dimensional complex data sets that consist of a large proportion of zeros, non-negative skewed counts, and frequently, limited number of samples. These features distinguish sequence data from other forms of high-dimensional data, and are not adequately addressed by statistical approaches in common use. Ultimately, medical studies may identify targeted interventions or treatments, but lack of analytic tools for feature selection and identification of taxa responsible for differences between groups, is hindering advancement. The objective of this paper is to examine the application of a two-part statistic to identify taxa that differ between two groups. The advantages of the two-part statistic over common statistical tests applied to sequence count datasets are discussed. Results from the t-test, the Wilcoxon test, and the two-part test are compared using sequence counts from microbial ecology studies in cystic fibrosis and from cenote samples. We show superior performance of the two-part statistic for analysis of sequence data. The improved performance in microbial ecology studies was independent of study type and sequence technology used

Copy Number Variation and Transposable Elements Feature in Recent, Ongoing Adaptation at the Cyp6g1 Locus

The increased transcription of the Cyp6g1 gene of Drosophila melanogaster, and consequent resistance to insecticides such as DDT, is a widely cited example of adaptation mediated by cis-regulatory change. A fragment of an Accord transposable element inserted upstream of the Cyp6g1 gene is causally associated with resistance and has spread to high frequencies in populations around the world since the 1940s. Here we report the existence of a natural allelic series at this locus of D. melanogaster, involving copy number variation of Cyp6g1, and two additional transposable element insertions (a P and an HMS-Beagle). We provide evidence that this genetic variation underpins phenotypic variation, as the more derived the allele, the greater the level of DDT resistance. Tracking the spatial and temporal patterns of allele frequency changes indicates that the multiple steps of the allelic series are adaptive. Further, a DDT association study shows that the most resistant allele, Cyp6g1-[BP], is greatly enriched in the top 5% of the phenotypic distribution and accounts for ∼16% of the underlying phenotypic variation in resistance to DDT. In contrast, copy number variation for another candidate resistance gene, Cyp12d1, is not associated with resistance. Thus the Cyp6g1 locus is a major contributor to DDT resistance in field populations, and evolution at this locus features multiple adaptive steps occurring in rapid succession

Characteristics of heart beat intervals and prediction of death.

OBJECTIVE: To assess the value for improving risk stratification of measures, unadjusted and adjusted for heart rate, of heart rate variability (HRV) and heart rate turbulence (HRT) based on 2- to 24-h ambulatory electrocardiographic recordings; and to relate this to the decision to use an implantable cardiac defibrillator (ICD) and the attendant consequences on effectiveness and cost-effectiveness. BACKGROUND: Risk stratification for high risk or low risk of lethal ventricular arrhythmic events, and hence for a decision about defibrillator implant, most commonly utilizes the left ventricular ejection fraction (LVEF). Electrocardiographic (ECG) approaches include 24-h ambulatory ECG recordings, with counts of ventricular premature contractions (VPCs), measures of heart rate variability (HRV), and heart rate turbulence (HRT). HRT has two components: turbulence onset (TO) and turbulence slope (TS). METHODS AND RESULTS: We evaluated the qualifying ambulatory ECG recordings from 744 patients in the active treatment arms of the Cardiac Arrhythmia Suppression Trial (CAST). Beat characteristics, VPC counts, normal-to-normal beat intervals, and time-domain measures of HRV and HRT were calculated. Tachograms were rescaled to a heart rate of 75 and the resulting "normalized" measures evaluated as risk predictors for death, compared to unnormalized measures. Measures based on 2-h ECGs were also evaluated as risk predictors. The most powerful univariate predictor of survival was the normalized turbulence slope. The best multivariate prediction model had six components: history of angina, hypertension, diabetes, and absence of post-myocardial infarction revascularization, the log of LVEF, normalized TS, HR, and an interaction term of HR and normalized TS. Gains in effectiveness from use of this model cost between $0 and$4000 per year of life saved. CONCLUSIONS: Turbulence slope substantially exceeded other ECG-based measures in improving prediction of subsequent death in models which included LVEF, and other clinical parameters. Use of this model would improve the effectiveness and cost-effectiveness of the ICD

Structural relationships between measures based on heart beat intervals: Potential for improved risk assessment

Decreased left ventricular ejection fraction is the most commonly used risk factor for identification of patients at high-risk for lethal ventricular arrhythmic events. Twenty-four-hour electrocardiographic (ECG) approaches to risk stratification include: counts of ventricular premature contractions (VPCs), measures of heart rate variability (HRV), and heart rate turbulence (HRT) which has two components, turbulence onset and turbulence slope ITS). Refinement of these ECG risk stratifiers could enhance their clinical utility. We explored the structural relationships between heart rate (HR) and HRV and HRT measures. Our goal was to separate out the component of these measures due to the underlying average heart rate (HR), thus potentially reducing the variability of the measures and increasing their power to stratify risk. We proposed re-scaling tachograms of heart-beat intervals so that the re-scaled tachogram has a HR of 75 (or equivalently an average interval of 800 ms) and calculating HRV and HRT from the rescaled time series. We also explored the relationship between the number of VPCs and HRT. We showed that TS is structurally related to the number of VPCs (and hence to the length of the ECG recording). We proposed an adjusted TS that is independent of the number of VPCs. We also addressed the ability of shorter ECG recording to estimate HRV and HRT measures. We evaluated standard and rescaled HRV and HRT measures using qualifying ambulatory ECG recordings from 744 patients in the Cardiac Arrhythmia Suppression Trial. We found that measures based on the rescaled tachogram had reduced variance (20% to 40%). Correlations between measures were also substantially reduced. We also found substantial circadian effects on some, but not all HRV indices, not explained by the circadian pattern in HR and possibly pointing to additional measures for risk prediction. In conclusion, we found that adjusting for HR and the number of VPCs in heart-beat related ambulatory ECG measures has the potential to significantly improve the power of these measures to risk stratify cardiac patients