Assessing heat-related health risk in Europe via the Universal Thermal Climate Index (UTCI)

In this work the potential of the Universal Thermal Climate Index (UTCI) as a heat-related health risk indicator in Europe is demonstrated. The UTCI is a bioclimate index that uses a multi-node human heat balance model to represent the heat stress induced by meteorological conditions to the human body. Using 38 years of meteorological reanalysis data, UTCI maps were computed to assess the thermal bioclimate of Europe for the summer season. Patterns of heat stress conditions and non-thermal stress regions are identified across Europe. An increase in heat stress up to 1°C is observed during recent decades. Correlation with mortality data from 17 European countries revealed that the relationship between the UTCI and death counts depends on the bioclimate of the country, and death counts increase in conditions of moderate and strong stress, i.e. when UTCI is above 26°C and 32°C. The UTCI’s ability to represent mortality patterns is demonstrated for the 2003 European heatwave. These findings confirm the importance of UTCI as a bioclimatic index that is able to both capture the thermal bioclimatic variability of Europe, and relate such variability with the effects it has on human health

Laboratory evolution of Pyrococcus furiosus alcohol dehydrogenase to improve the production of (2S,5S)-hexanediol at moderate temperatures

There is considerable interest in the use of enantioselective alcohol dehydrogenases for the production of enantio- and diastereomerically pure diols, which are important building blocks for pharmaceuticals, agrochemicals and fine chemicals. Due to the need for a stable alcohol dehydrogenase with activity at low-temperature process conditions (30°C) for the production of (2S,5S)-hexanediol, we have improved an alcohol dehydrogenase from the hyperthermophilic archaeon Pyrococcus furiosus (AdhA). A stable S-selective alcohol dehydrogenase with increased activity at 30°C on the substrate 2,5-hexanedione was generated by laboratory evolution on the thermostable alcohol dehydrogenase AdhA. One round of error-prone PCR and screening of ∼1,500 mutants was performed. The maximum specific activity of the best performing mutant with 2,5-hexanedione at 30°C was tenfold higher compared to the activity of the wild-type enzyme. A 3D-model of AdhA revealed that this mutant has one mutation in the well-conserved NADP(H)-binding site (R11L), and a second mutation (A180V) near the catalytic and highly conserved threonine at position 183

The Pseudomonas Quinolone Signal (PQS) Balances Life and Death in Pseudomonas aeruginosa Populations

When environmental conditions deteriorate and become inhospitable, generic survival strategies for populations of bacteria may be to enter a dormant state that slows down metabolism, to develop a general tolerance to hostile parameters that characterize the habitat, and to impose a regime to eliminate damaged members. Here, we provide evidence that the pseudomonas quinolone signal (PQS) mediates induction of all of these phenotypes. For individual cells, PQS, an interbacterial signaling molecule of Pseudomonas aeruginosa, has both deleterious and beneficial activities: on the one hand, it acts as a pro-oxidant and sensitizes the bacteria towards oxidative and other stresses and, on the other, it efficiently induces a protective anti-oxidative stress response. We propose that this dual function fragments populations into less and more stress tolerant members which respond differentially to developing stresses in deteriorating habitats. This suggests that a little poison may be generically beneficial to populations, in promoting survival of the fittest, and in contributing to bacterial multi-cellular behavior. It further identifies PQS as an essential mediator of the shaping of the population structure of Pseudomonas and of its response to and survival in hostile environmental conditions

Python as a Federation Tool for GENESIS 3.0

The GENESIS simulation platform was one of the first broad-scale modeling systems in computational biology to encourage modelers to develop and share model features and components. Supported by a large developer community, it participated in innovative simulator technologies such as benchmarking, parallelization, and declarative model specification and was the first neural simulator to define bindings for the Python scripting language. An important feature of the latest version of GENESIS is that it decomposes into self-contained software components complying with the Computational Biology Initiative federated software architecture. This architecture allows separate scripting bindings to be defined for different necessary components of the simulator, e.g., the mathematical solvers and graphical user interface. Python is a scripting language that provides rich sets of freely available open source libraries. With clean dynamic object-oriented designs, they produce highly readable code and are widely employed in specialized areas of software component integration. We employ a simplified wrapper and interface generator to examine an application programming interface and make it available to a given scripting language. This allows independent software components to be ‘glued’ together and connected to external libraries and applications from user-defined Python or Perl scripts. We illustrate our approach with three examples of Python scripting. (1) Generate and run a simple single-compartment model neuron connected to a stand-alone mathematical solver. (2) Interface a mathematical solver with GENESIS 3.0 to explore a neuron morphology from either an interactive command-line or graphical user interface. (3) Apply scripting bindings to connect the GENESIS 3.0 simulator to external graphical libraries and an open source three dimensional content creation suite that supports visualization of models based on electron microscopy and their conversion to computational models. Employed in this way, the stand-alone software components of the GENESIS 3.0 simulator provide a framework for progressive federated software development in computational neuroscience

Genome sequencing reveals metabolic and cellular interdependence in an amoeba-kinetoplastid symbiosis

Endosymbiotic relationships between eukaryotic and prokaryotic cells are common in nature. Endosymbioses between two eukaryotes are also known; cyanobacterium-derived plastids have spread horizontally when one eukaryote assimilated another. A unique instance of a non-photosynthetic, eukaryotic endosymbiont involves members of the genus Paramoeba, amoebozoans that infect marine animals such as farmed fish and sea urchins. Paramoeba species harbor endosymbionts belonging to the Kinetoplastea, a diverse group of flagellate protists including some that cause devastating diseases. To elucidate the nature of this eukaryote-eukaryote association, we sequenced the genomes and transcriptomes of Paramoeba pemaquidensis and its endosymbiont Perkinsela sp. The endosymbiont nuclear genome is ~9.5 Mbp in size, the smallest of a kinetoplastid thus far discovered. Genomic analyses show that Perkinsela sp. has lost the ability to make a flagellum but retains hallmark features of kinetoplastid biology, including polycistronic transcription, trans-splicing, and a glycosome-like organelle. Mosaic biochemical pathways suggest extensive ‘cross-talk’ between the two organisms, and electron microscopy shows that the endosymbiont ingests amoeba cytoplasm, a novel form of endosymbiont-host communication. Our data reveal the cell biological and biochemical basis of the obligate relationship between Perkinsela sp. and its amoeba host, and provide a foundation for understanding pathogenicity determinants in economically important Paramoeba

What does the structure-function relationship of the HIV-1 Tat protein teach us about developing an AIDS vaccine?

The human immunodeficiency virus type 1 (HIV-1) trans-activator of transcription protein Tat is an important factor in viral pathogenesis. In addition to its function as the key trans-activator of viral transcription, Tat is also secreted by the infected cell and taken up by neighboring cells where it has an effect both on infected and uninfected cells. In this review we will focus on the relationship between the structure of the Tat protein and its function as a secreted factor. To this end we will summarize some of the exogenous functions of Tat that have been implicated in HIV-1 pathogenesis and the impact of structural variations and viral subtype variants of Tat on those functions. Finally, since in some patients the presence of Tat-specific antibodies or CTL frequencies are associated with slow or non-progression to AIDS, we will also discuss the role of Tat as a potential vaccine candidate, the advances made in this field, and the importance of using a Tat protein capable of eliciting a protective or therapeutic immune response to viral challenge

Thermodynamic Basis for the Emergence of Genomes during Prebiotic Evolution

The RNA world hypothesis views modern organisms as descendants of RNA molecules. The earliest RNA molecules must have been random sequences, from which the first genomes that coded for polymerase ribozymes emerged. The quasispecies theory by Eigen predicts the existence of an error threshold limiting genomic stability during such transitions, but does not address the spontaneity of changes. Following a recent theoretical approach, we applied the quasispecies theory combined with kinetic/thermodynamic descriptions of RNA replication to analyze the collective behavior of RNA replicators based on known experimental kinetics data. We find that, with increasing fidelity (relative rate of base-extension for Watson-Crick versus mismatched base pairs), replications without enzymes, with ribozymes, and with protein-based polymerases are above, near, and below a critical point, respectively. The prebiotic evolution therefore must have crossed this critical region. Over large regions of the phase diagram, fitness increases with increasing fidelity, biasing random drifts in sequence space toward ‘crystallization.’ This region encloses the experimental nonenzymatic fidelity value, favoring evolutions toward polymerase sequences with ever higher fidelity, despite error rates above the error catastrophe threshold. Our work shows that experimentally characterized kinetics and thermodynamics of RNA replication allow us to determine the physicochemical conditions required for the spontaneous crystallization of biological information. Our findings also suggest that among many potential oligomers capable of templated replication, RNAs may have evolved to form prebiotic genomes due to the value of their nonenzymatic fidelity

Multivariate Protein Signatures of Pre-Clinical Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative (ADNI) Plasma Proteome Dataset

Background: Recent Alzheimer's disease (AD) research has focused on finding biomarkers to identify disease at the pre-clinical stage of mild cognitive impairment (MCI), allowing treatment to be initiated before irreversible damage occurs. Many studies have examined brain imaging or cerebrospinal fluid but there is also growing interest in blood biomarkers. The Alzheimer's Disease Neuroimaging Initiative (ADNI) has generated data on 190 plasma analytes in 566 individuals with MCI, AD or normal cognition. We conducted independent analyses of this dataset to identify plasma protein signatures predicting pre-clinical AD. Methods and Findings: We focused on identifying signatures that discriminate cognitively normal controls (n = 54) from individuals with MCI who subsequently progress to AD (n = 163). Based on p value, apolipoprotein E (APOE) showed the strongest difference between these groups (p = 2.3×10−13). We applied a multivariate approach based on combinatorial optimization ((α,β)-k Feature Set Selection), which retains information about individual participants and maintains the context of interrelationships between different analytes, to identify the optimal set of analytes (signature) to discriminate these two groups. We identified 11-analyte signatures achieving values of sensitivity and specificity between 65% and 86% for both MCI and AD groups, depending on whether APOE was included and other factors. Classification accuracy was improved by considering “meta-features,” representing the difference in relative abundance of two analytes, with an 8-meta-feature signature consistently achieving sensitivity and specificity both over 85%. Generating signatures based on longitudinal rather than cross-sectional data further improved classification accuracy, returning sensitivities and specificities of approximately 90%. Conclusions: Applying these novel analysis approaches to the powerful and well-characterized ADNI dataset has identified sets of plasma biomarkers for pre-clinical AD. While studies of independent test sets are required to validate the signatures, these analyses provide a starting point for developing a cost-effective and minimally invasive test capable of diagnosing AD in its pre-clinical stages