Metabolism of dimethylsulfoniopropionate and glycine betaine by a marine bacterium

Abstract The metabolism of the methylated osmolytes glycine betaine (GB) and dimethylsulfoniopropionate (DMSP) was studied in a bacterium (strain MD 14–50) isolated from a colony of the cyanobacterium Trichodesmium . MD 14–50 when grown on DMSP cleaved dimethylsulfide (DMS) from DMSP and oxidized acrylate. In contrast to DMSP, GB was metabolized by sequential N-demethylations. Low concentrations (100 μM) of DMSP or GB allowed the growth of MD 14–50 on glucose at higher salinities than in their absence. At elevated salinities, DMSP was accumulated intracellularly with less catabolism and DMS production. Thus, DMSP and GB were catabolized by different mechanisms but functioned interchangeably as osmolytes.     

Gene action,genetic variation,and GWAS: A user-friendly web tool

Fisher’s partitioning of genotypic values and genetic variance is highly relevant in the current era of genome-wide association studies (GWASs). However, despite being more than a century old, a number of persistent misconceptions related to nonadditive genetic effects remain. We developed a user-friendly web tool, the Falconer ShinyApp, to show how the combination of gene action and allele frequencies at causal loci translate to genetic variance and genetic variance components for a complex trait. The app can be used to demonstrate the relationship between a SNP effect size estimated from GWAS and the variation the SNP generates in the population, i.e., how locus-specific effects lead to individual differences in traits. In addition, it can also be used to demonstrate how within and between locus interactions (dominance and epistasis, respectively) usually do not lead to a large amount of nonadditive variance relative to additive variance, and therefore, that these interactions usually do not explain individual differences in a population.     

Low-molecular-weight sulfonates, a major substrate for sulfate reducers in marine microbial mats.

Several low-molecular-weight sulfonates were added to microbial mat slurries to investigate their effects on sulfate reduction. Instantaneous production of sulfide occurred after taurine and cysteate were added to all of the microbial mats tested. The rates of production in the presence of taurine and cysteate were 35 and 24 microM HS(-) h(-1) in a stromatolite mat, 38 and 36 microM HS(-) h(-1) in a salt pond mat, and 27 and 18 microM HS(-) h(-1) in a salt marsh mat, respectively. The traditionally used substrates lactate and acetate stimulated the rate of sulfide production 3 to 10 times more than taurine and cysteate stimulated the rate of sulfide production in all mats, but when ethanol, glycolate, and glutamate were added to stromatolite mat slurries, the resulting increases were similar to the increases observed with taurine and cysteate. Isethionate, sulfosuccinate, and sulfobenzoate were tested only with the stromatolite mat slurry, and these compounds had much smaller effects on sulfide production. Addition of molybdate resulted in a greater inhibitory effect on acetate and lactate utilization than on sulfonate use, suggesting that different metabolic pathways were involved. In all of the mats tested taurine and cysteate were present in the pore water at nanomolar to micromolar concentrations. An enrichment culture from the stromatolite mat was obtained on cysteate in a medium lacking sulfate and incubated anaerobically. The rate of cysteate consumption by this enrichment culture was 1.6 pmol cell(-1) h(-1). Compared to the results of slurry studies, this rate suggests that organisms with properties similar to the properties of this enrichment culture are a major constituent of the sulfidogenic population. In addition, taurine was consumed at some of highest dilutions obtained from most-probable-number enrichment cultures obtained from stromatolite samples. Based on our comparison of the sulfide production rates found in various mats, low-molecular-weight sulfonates are important sources of C and S in these ecosystems.     

Quantifying the randomness of extinctions

Extinctions occur either randomly or in a more deterministic and predictable manner, with certain characteristics making some species more vulnerable to (local) extinction than others. Although the quantification of extinction randomness would better our understanding of the extinction causes and increase the predictability of future species losses, few quantification methods are currently available. To this purpose, we propose two indices based on a comparison of an a priori (expected) extinction series with an observed one. Whereas the first index requires data on the order of extinctions, the second index is only concerned with which species went extinct and which did not. Using a model for generating extinction data, we tested both indices successfully for accordance with the robustness prerequisites. Index outputs were furthermore unaffected by species richness, apart from decreased variation with rising species numbers. Because of its independence of non-extinct species and its focus on extinction sequences, the first randomness index seems especially useful for use in paleontological and paleo-ecological research. The second index is likely a good tool to study shorter term extinctions, for which the extinction order is often not known and for which the comparison with species that did persist is of greater interest. We use a real dataset to illustrate this. Finally, we discuss how it is possible to expand the use of this index toward identifying previously unknown extinction-promoting species characteristics, and toward a credible assessment of the extinction risk posed by global change.     

Solvated protein–DNA docking using HADDOCK

Interfacial water molecules play an important role in many aspects of protein–DNA specificity and recognition. Yet they have been mostly neglected in the computational modeling of these complexes. We present here a solvated docking protocol that allows explicit inclusion of water molecules in the docking of protein–DNA complexes and demonstrate its feasibility on a benchmark of 30 high-resolution protein–DNA complexes containing crystallographically-determined water molecules at their interfaces. Our protocol is capable of reproducing the solvation pattern at the interface and recovers hydrogen-bonded water-mediated contacts in many of the benchmark cases. Solvated docking leads to an overall improvement in the quality of the generated protein–DNA models for cases with limited conformational change of the partners upon complex formation. The applicability of this approach is demonstrated on real cases by docking a representative set of 6 complexes using unbound protein coordinates, model-built DNA and knowledge-based restraints. As HADDOCK supports the inclusion of a variety of NMR restraints, solvated docking is also applicable for NMR-based structure calculations of protein–DNA complexes.