The power of evolution: accessing the synthetic potential of P450s

AbstractCytochromes P450 can catalyse hydroxylation reactions that are of considerable potential synthetic value, but a number of practical difficulties have hitherto prevented their use for this purpose. Recent advances, including intelligently designed laboratory evolution experiments, promise to overcome these obstacles, and to add P450s to the enzymatic armoury of the chemist

Ultra-endurance athletic performance suggests that energetics drive human morphological thermal adaptation

Both extinct and extant hominin populations display morphological features consistent with Bergmann's and Allen's Rules. However, the functional implications of the morphologies described by these ecological laws are poorly understood. We examined this through the lens of endurance running. Previous research concerning endurance running has focused on locomotor energetic economy. We considered a less-studied dimension of functionality, thermoregulation. The performance of male ultra-marathon runners (n = 88) competing in hot and cold environments was analysed with reference to expected thermoregulatory energy costs and the optimal morphologies predicted by Bergmann's and Allen's Rules. Ecogeographical patterning supporting both principles was observed in thermally challenging environments. Finishers of hot-condition events had significantly longer legs than finishers of cold-condition events. Furthermore, hot-condition finishers had significantly longer legs than those failing to complete hot-condition events. A degree of niche-picking was evident; athletes may have tailored their event entry choices in accordance with their previous race experiences. We propose that the interaction between prolonged physical exertion and hot or cold climates may induce powerful selective pressures driving morphological adaptation. The resulting phenotypes reduce thermoregulatory energetic expenditure, allowing diversion of energy to other functional outcomes such as faster running

Recombination operators and selection strategies for evolutionary Markov Chain Monte Carlo algorithms

Markov Chain Monte Carlo (MCMC) methods are often used to sample from intractable target distributions. Some MCMC variants aim to improve the performance by running a population of MCMC chains. In this paper, we investigate the use of techniques from Evolutionary Computation (EC) to design population-based MCMC algorithms that exchange useful information between the individual chains. We investigate how one can ensure that the resulting class of algorithms, called Evolutionary MCMC (EMCMC), samples from the target distribution as expected from any MCMC algorithm. We analytically and experimentally show—using examples from discrete search spaces—that the proposed EMCMCs can outperform standard MCMCs by exploiting common partial structures between the more likely individual states. The MCMC chains in the population interact through recombination and selection. We analyze the required properties of recombination operators and acceptance (or selection) rules in EMCMCs. An important issue is how to preserve the detailed balance property which is a sufficient condition for an irreducible and aperiodic EMCMC to converge to a given target distribution. Transferring EC techniques to population-based MCMCs should be done with care. For instance, we prove that EMCMC algorithms with an elitist acceptance rule do not sample the target distribution correctly

Glubodies: randomized libraries of glutathione transferase enzymes

AbstractBackground: The immunoglobulin framework has been mutagenized to engineer recombinant libraries of proteins as potential diagnostics and novel catalysts, although the often shallow binding cleft may limit the utility of this framework for binding diverse small organic molecules. By contrast, the glutathione S-transferase (GST) family of enzymes contains a deep binding cleft, which has evolved to accommodate a broad range of hydrophobic xenobiotics. We set out to determine whether GST molecules with novel ligand-binding characteristics could be produced by random mutagenesis of segments of the binding cleft.Results: We have identified two ligand-recognition segments (LRSs) in human GST P1, which are near the active site in the folded protein, but have characteristics indicating that the integrity of their sequence is not essential for the overall structure or activity of the protein. Libraries of GST P1-derived proteins were produced by substituting randomized sequences for an LRS or inserting random sequences into an LRS. The recombinant proteins in the libraries, collectively designated as ‘glubodies,’ generally retain enzymatic activity but differ markedly both from each other and from the parent enzyme in sensitivity to inhibition by diverse small organic compounds. In some instances, a glubody is inhibited by completely novel structures.Conclusions: We have shown that a non-antibody framework can be used to create large libraries of proteins with a wide range of binding specificities for small organic molecules. The glubodies provide a rich source of data for correlating the structural and functional features of proteins relevant to ligand binding. The criteria applied for identifying an LRS in GST P1 are generally applicable to other protein frameworks

The science of clinical practice: disease diagnosis or patient prognosis? Evidence about "what is likely to happen" should shape clinical practice.

BACKGROUND: Diagnosis is the traditional basis for decision-making in clinical practice. Evidence is often lacking about future benefits and harms of these decisions for patients diagnosed with and without disease. We propose that a model of clinical practice focused on patient prognosis and predicting the likelihood of future outcomes may be more useful. DISCUSSION: Disease diagnosis can provide crucial information for clinical decisions that influence outcome in serious acute illness. However, the central role of diagnosis in clinical practice is challenged by evidence that it does not always benefit patients and that factors other than disease are important in determining patient outcome. The concept of disease as a dichotomous 'yes' or 'no' is challenged by the frequent use of diagnostic indicators with continuous distributions, such as blood sugar, which are better understood as contributing information about the probability of a patient's future outcome. Moreover, many illnesses, such as chronic fatigue, cannot usefully be labelled from a disease-diagnosis perspective. In such cases, a prognostic model provides an alternative framework for clinical practice that extends beyond disease and diagnosis and incorporates a wide range of information to predict future patient outcomes and to guide decisions to improve them. Such information embraces non-disease factors and genetic and other biomarkers which influence outcome. SUMMARY: Patient prognosis can provide the framework for modern clinical practice to integrate information from the expanding biological, social, and clinical database for more effective and efficient care

Validation of an arterial tortuosity measure with application to hypertension collection of clinical hypertensive patients

<p>Abstract</p> <p>Background</p> <p>Hypertension may increase tortuosity or twistedness of arteries. We applied a centerline extraction algorithm and tortuosity metric to magnetic resonance angiography (MRA) brain images to quantitatively measure the tortuosity of arterial vessel centerlines. The most commonly used arterial tortuosity measure is the distance factor metric (DFM). This study tested a DFM based measurement’s ability to detect increases in arterial tortuosity of hypertensives using existing images. Existing images presented challenges such as different resolutions which may affect the tortuosity measurement, different depths of the area imaged, and different artifacts of imaging that require filtering.</p> <p>Methods</p> <p>The stability and accuracy of alternative centerline algorithms was validated in numerically generated models and test brain MRA data. Existing images were gathered from previous studies and clinical medical systems by manually reading electronic medical records to identify hypertensives and negatives. Images of different resolutions were interpolated to similar resolutions. Arterial tortuosity in MRA images was measured from a DFM curve and tested on numerically generated models as well as MRA images from two hypertensive and three negative control populations. Comparisons were made between different resolutions, different filters, hypertensives versus negatives, and different negative controls.</p> <p>Results</p> <p>In tests using numerical models of a simple helix, the measured tortuosity increased as expected with more tightly coiled helices. Interpolation reduced resolution-dependent differences in measured tortuosity. The Korean hypertensive population had significantly higher arterial tortuosity than its corresponding negative control population across multiple arteries. In addition one negative control population of different ethnicity had significantly less arterial tortuosity than the other two.</p> <p>Conclusions</p> <p>Tortuosity can be compared between images of different resolutions by interpolating from lower to higher resolutions. Use of a universal negative control was not possible in this study. The method described here detected elevated arterial tortuosity in a hypertensive population compared to the negative control population and can be used to study this relation in other populations.</p

Ethanol reversal of tolerance to the respiratory depressant effects of morphine

Opioids are the most common drugs associated with unintentional drug overdose. Death results from respiratory depression. Prolonged use of opioids results in the development of tolerance but the degree of tolerance is thought to vary between different effects of the drugs. Many opioid addicts regularly consume alcohol (ethanol), and post-mortem analyses of opioid overdose deaths have revealed an inverse correlation between blood morphine and ethanol levels. In the present study, we determined whether ethanol reduced tolerance to the respiratory depressant effects of opioids. Mice were treated with opioids (morphine, methadone, or buprenorphine) for up to 6 days. Respiration was measured in freely moving animals breathing 5% CO(2) in air in plethysmograph chambers. Antinociception (analgesia) was measured as the latency to remove the tail from a thermal stimulus. Opioid tolerance was assessed by measuring the response to a challenge dose of morphine (10 mg/kg i.p.). Tolerance developed to the respiratory depressant effect of morphine but at a slower rate than tolerance to its antinociceptive effect. A low dose of ethanol (0.3 mg/kg) alone did not depress respiration but in prolonged morphine-treated animals respiratory depression was observed when ethanol was co-administered with the morphine challenge. Ethanol did not alter the brain levels of morphine. In contrast, in methadone- or buprenorphine-treated animals no respiratory depression was observed when ethanol was co-administered along with the morphine challenge. As heroin is converted to morphine in man, selective reversal of morphine tolerance by ethanol may be a contributory factor in heroin overdose deaths

Incidence of Diabetes in the Working Population in Spain: Results from the ICARIA Cohort

INTRODUCTION: Our objective was to evaluate the incidence of type 2 diabetes mellitus (T2DM) in a working population in Spain and to assess associations between its development and several risk factors. METHODS: The ICARIA (Ibermutuamur CArdiovascular RIsk Assessment) cohort (n = 627,523) includes ~3% of Spanish workers. This analysis was undertaken in individuals whose glycaemic status during the index period (May 2004-December 2007) was determined to be normal or indicative of prediabetes [fasting plasma glucose (FPG) 100-125 mg/dl] and who had at least one FPG measurement taken 9 months after a first measurement during follow-up (May 2004-June 2014) (n = 380,366). T2DM patients were defined as those with an FPG ? 126 mg/day and those who had already been diagnosed with T2DM or were taking antihyperglycaemic medications. RESULTS: The incidence rate of T2DM was 5.0 [95% confidence interval (CI) 4.9-5.1] cases per 1000 person-years. Under multivariate logistic regression analysis, the factor showing the strongest association with the occurrence of T2DM was the baseline FPG level, with the likelihood of T2DM almost doubling for every 5 mg/dl increase in baseline FPG between 100 and < 126 mg/dl. The presence of other cardiometabolic risk factors and being a blue-collar worker were also significantly associated with the occurrence of T2DM. CONCLUSIONS: The incidence of T2DM in the working population was within the range encountered in the general population and prediabetes was found to be the strongest risk factor for the development of diabetes. The workplace is an appropriate and feasible setting for the assessment of easily measurable risk factors, such as the presence of prediabetes and other cardiometabolic factors, to facilitate the early detection of individuals at higher risk of diabetes and the implementation of diabetes prevention programmes