Preface

Reviews in Environmental Science and Bio/Technology -     

Effect of sulfur compounds on biological reduction of nitric oxide in aqueous Fe(II)EDTA2- solutions.

Biological reduction of nitric oxide (NO) in aqueous solutions of EDTA chelated Fe(II) is one of the main steps in the BioDeNOx process, a novel bioprocess for the removal of nitrogen oxides (NOx) from polluted gas streams. Since NOx contaminated gases usually also contain sulfurous pollutants, the possible interferences of these sulfur compounds with the BioDeNOx process need to be identified. Therefore, the effect of the sulfur compounds Na2SO4, Na2SO3, and H2S on the biological NO reduction in aqueous solutions of Fe(II)EDTA2- (25 mM, pH 7.2, 55 degrees C) was studied in batch experiments. Sulfate and sulfite were found to not affect the reduction rate of Fe(II)EDTA2- complexed NO under the conditions tested. Sulfide, either dosed externally or formed during the batch incubation out of endogenous sulfur sources or the supplied sulfate or sulfite, influences the production and consumption of the intermediate nitrous oxide (N2O) during Fe(II)EDTA2- bound NO reduction. At low concentrations (0.2 g VSS/l) of denitrifying sludge, 0.2 mM free sulfide completely inhibited the nitrosyl-complex reduction. At higher biomass concentrations (1.3-2.3 g VSS/l), sulfide (from 15 microM to 0.8 mM) induced an incomplete NO denitrification with N2O accumulation. The reduction rates of NO to N2O were enhanced by anaerobic sludge, presumably because it kept FeEDTA in the reduced state.     

Biotic interactions enhance survival and fitness in the caddisfly <Emphasis Type="Italic">Micropterna sequax</Emphasis> (Trichoptera: Limnephilidae)

Fish-based index of biotic integrity (F-IBI) is widely used to assess river ecosystems. With survey data from the Yellow River fishery resources in the 1980s and 2008, fish composition and abundance, vertical distribution, trophic structure, reproductive guilds and tolerance in the river’s upstream, midstream, downstream, and estuary were examined, and F-IBI systems were established for each reach to assess river ecosystem health. Results showed that compared to the 1980s, the number of fish species in 2008 sharply declined in the midstream and downstream reaches, percentage of benthic fish species decreased in upstream and estuary, the number and percentage of omnivorous species decreased in all reaches, and percentage of tolerant fish species increased 15 times in upstream but decreased in midstream and downstream. The F-IBI scores in the four reaches in the 1980s were all higher than those in 2008 and decreased from upstream to estuary; the healthy conditions indicated by F-IBI scores in the 1980s were “good,” “fair,” “poor,” and “fair” from upstream to estuary and “degraded” to “poor” in all the reaches in 2008. This indicated that the river ecosystem has degraded from the 1980s to 2008. This was also shown by variations in water chemistry.     

How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use?

RNA-seq is now the technology of choice for genome-wide differential gene expression experiments, but it is not clear how many biological replicates are needed to ensure valid biological interpretation of the results or which statistical tools are best for analyzing the data. An RNA-seq experiment with 48 biological replicates in each of two conditions was performed to answer these questions and provide guidelines for experimental design. With three biological replicates, nine of the 11 tools evaluated found only 20%–40% of the significantly differentially expressed (SDE) genes identified with the full set of 42 clean replicates. This rises to >85% for the subset of SDE genes changing in expression by more than fourfold. To achieve >85% for all SDE genes regardless of fold change requires more than 20 biological replicates. The same nine tools successfully control their false discovery rate at ≲5% for all numbers of replicates, while the remaining two tools fail to control their FDR adequately, particularly for low numbers of replicates. For future RNA-seq experiments, these results suggest that at least six biological replicates should be used, rising to at least 12 when it is important to identify SDE genes for all fold changes. If fewer than 12 replicates are used, a superior combination of true positive and false positive performances makes edgeR and DESeq2 the leading tools. For higher replicate numbers, minimizing false positives is more important and DESeq marginally outperforms the other tools.     

Recruitment of ZipA to the Septal Ring of Escherichia coli Is Dependent on FtsZ and Independent of FtsA

Cell division in prokaryotes is mediated by the septal ring. In Escherichia coli, this organelle consists of several essential division proteins, including FtsZ, FtsA, and ZipA. To gain more insight into how the structure is assembled, we studied the interdependence of FtsZ, FtsA, and ZipA localization using both immunofluorescence and Gfp tagging techniques. To this end, we constructed a set of strains allowing us to determine the cellular location of each of these three proteins in cells from which one of the other two had been specifically depleted. Our results show that ZipA fails to accumulate in a ring shape in the absence of FtsZ. Conversely, depletion of ZipA does not abolish formation of FtsZ rings but leads to a significant reduction in the number of rings per unit of cell mass. In addition, ZipA does not appear to require FtsA for assembly into the septal ring and vice versa. It is suggested that septal ring formation starts by assembly of the FtsZ ring, after which ZipA and FtsA join this structure in a mutually independent fashion through direct interactions with the FtsZ protein.     

Stressor richness intensifies productivity loss but mitigates biodiversity loss

Ecosystems are subject to a multitude of anthropogenic environmental changes. Experimental research in the field of multiple stressors has typically involved varying the number of stressors, here termed stressor richness, but without controlling for total stressor intensity. Mistaking stressor intensity effects for stressor richness effects can misinform management decisions when there is a trade‐off between mitigating these two factors. We incorporate multiple stressors into three community models and show that, at a fixed total stressor intensity, increasing stressor richness aggravates joint stressor effects on ecosystem functioning, but reduces effects on species persistence and composition. In addition, stressor richness weakens the positive selection and negative complementarity effects on ecosystem function. We identify the among‐species variation of stressor effects on traits as a key determinant of the resulting community‐level stressor effects. Taken together, our results unravel the mechanisms linking multiple environmental changes to biodiversity and ecosystem function.     

Methods of Model Reduction for Large-Scale Biological Systems: A Survey of Current Methods and Trends

Complex models of biochemical reaction systems have become increasingly common in the systems biology literature. The complexity of such models can present a number of obstacles for their practical use, often making problems difficult to intuit or computationally intractable. Methods of model reduction can be employed to alleviate the issue of complexity by seeking to eliminate those portions of a reaction network that have little or no effect upon the outcomes of interest, hence yielding simplified systems that retain an accurate predictive capacity. This review paper seeks to provide a brief overview of a range of such methods and their application in the context of biochemical reaction network models. To achieve this, we provide a brief mathematical account of the main methods including timescale exploitation approaches, reduction via sensitivity analysis, optimisation methods, lumping, and singular value decomposition-based approaches. Methods are reviewed in the context of large-scale systems biology type models, and future areas of research are briefly discussed.     

Movement,connectivity and population structure of the intertidal fish Lipophrys pholis as revealed by otolith oxygen and carbon stable isotopes

The shanny Lipophrys pholis is an intertidal fish commonly found in Portuguese coastal waters. Spawning takes place from early autumn to mid spring, after which demersal eggs hatch and larvae disperse along the coast. Two to three months later, young juveniles return to the tide pools to settle. However, information on fish movement, habitat connectivity and population structure is scarce for this species. One hundred and twenty early juveniles (16–35?mm) were collected in April 2014 from six rocky beaches along the western and south Portuguese coasts (Agudela, Cabo do Mundo, Boa Nova, Peniche, Sines and Olhos de Água). δ¹⁸O and δ¹³C were determined by isotope-ratio mass spectrometry. Data were analysed to determine whether isotopic signatures could be used to assess the degree of separation between individuals collected from different locations. Mean δ¹³C and δ¹⁸O values ranged from ?0.02‰ to 1.14‰ and ?7.77‰ to ?6.62‰, respectively. Both seawater temperature and salinity caused differences in otolith δ¹⁸O among the four main sampling areas. The variation among areas in δ¹³C was most likely related to slight differences in the diet, growth and metabolism of fish. The distinct isotopic signatures, at least for the northern and central areas, suggested low levels of connectivity across large spatial scales during the juvenile stage. Furthermore, similar isotopic signatures within the same area indicated some degree of larval oceanic retention at short spatial scales. This study suggests that stable isotope records in otoliths could provide information about the home residency, movements and habitat connectivity of intertidal fishes.