An ant colony optimisation algorithm for the 2D and 3D hydrophobic polar protein folding problem

Background  

The protein folding problem is a fundamental problems in computational molecular biology and biochemical physics. Various optimisation methods have been applied to formulations of the ab-initio folding problem that are based on reduced models of protein structure, including Monte Carlo methods, Evolutionary Algorithms, Tabu Search and hybrid approaches. In our work, we have introduced an ant colony optimisation (ACO) algorithm to address the non-deterministic polynomial-time hard (NP-hard) combinatorial problem of predicting a protein's conformation from its amino acid sequence under a widely studied, conceptually simple model – the 2-dimensional (2D) and 3-dimensional (3D) hydrophobic-polar (HP) model.     

Characterization and acceleration of genome shuffling and ploidy reduction in synthetic allopolyploids by genome sequencing and editing

Polyploidy and the subsequent ploidy reduction and genome shuffling are the major driving forces of genome evolution. Here, we revealed short-term allopolyploid genome evolution by sequencing a synthetic intergeneric hybrid (Raphanobrassica, RRCC). In this allotetraploid, the genome deletion was quick, while rearrangement was slow. The core and high-frequency genes tended to be retained while the specific and low-frequency genes tended to be deleted in the hybrid. The large-fragment deletions were enriched in the heterochromatin region and probably derived from chromosome breaks. The intergeneric translocations were primarily of short fragments dependent on homoeology, indicating a gene conversion origin. To accelerate genome shuffling, we developed an efficient genome editing platform for Raphanobrassica. By editing Fanconi Anemia Complementation Group M (FANCM) genes, homoeologous recombination, chromosome deletion and secondary meiosis with additional ploidy reduction were accelerated. FANCM was shown to be a checkpoint of meiosis and controller of ploidy stability. By simultaneously editing FLIP genes, gene conversion was precisely introduced, and mosaic genes were produced around the target site. This intergeneric hybrid and genome editing platform not only provides models that facilitate experimental evolution research by speeding up genome shuffling and conversion but also accelerates plant breeding by enhancing intergeneric genetic exchange and creating new genes.     

Influence of different data cleaning solutions of point‐occurrence records on downstream macroecological diversity models

Digital point‐occurrence records from the Global Biodiversity Information Facility (GBIF) and other data providers enable a wide range of research in macroecology and biogeography. However, data errors may hamper immediate use. Manual data cleaning is time‐consuming and often unfeasible, given that the databases may contain thousands or millions of records. Automated data cleaning pipelines are therefore of high importance. Taking North American Ephedra as a model, we examined how different data cleaning pipelines (using, e.g., the GBIF web application, and four different R packages) affect downstream species distribution models (SDMs). We also assessed how data differed from expert data. From 13,889 North American Ephedra observations in GBIF, the pipelines removed 31.7% to 62.7% false positives, invalid coordinates, and duplicates, leading to datasets between 9484 (GBIF application) and 5196 records (manual‐guided filtering). The expert data consisted of 704 records, comparable to data from field studies. Although differences in the absolute numbers of records were relatively large, species richness models based on stacked SDMs (S‐SDM) from pipeline and expert data were strongly correlated (mean Pearson''s r across the pipelines: .9986, vs. the expert data: .9173). Our results suggest that all R package‐based pipelines reliably identified invalid coordinates. In contrast, the GBIF‐filtered data still contained both spatial and taxonomic errors. Major drawbacks emerge from the fact that no pipeline fully discovered misidentified specimens without the assistance of taxonomic expert knowledge. We conclude that application‐filtered GBIF data will still need additional review to achieve higher spatial data quality. Achieving high‐quality taxonomic data will require extra effort, probably by thoroughly analyzing the data for misidentified taxa, supported by experts.     

Zur Ökologie der zymogenen planktischen Bakterienflora natürlicher Gewässer

Ohne ZusammenfassungAuszug aus der gleichnamigen Dissertation der mathematisch-naturwissenschaftlichen Fakultät der Universität Göttingen 1955.     

Beverage specific alcohol intake in a population-based study: Evidence for a positive association between pulmonary function and wine intake

Background  

Lung function is a strong predictor of cardiovascular and all-cause mortality. Previous studies suggest that alcohol exposure may be linked to impaired pulmonary function through oxidant-antioxidant mechanisms. Alcohol may be an important source of oxidants; however, wine contains several antioxidants. In this study we analyzed the relation of beverage specific alcohol intake with forced expiratory volume in one second (FEV₁) and forced vital capacity (FVC) in a random sample of 1555 residents of Western New York, USA.     

Contribution of crop model structure,parameters and climate projections to uncertainty in climate change impact assessments

Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple‐ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple‐ensemble probabilistic assessment, the median of simulated yield change was ?4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981–2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple‐ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources.