Temporal and spatial trends in heavy metal concentrations in the marine mussel Mytilus edulis from the Western Scheldt estuary (The Netherlands)

Since the first North Sea Conference (1984, Bremen), all countries bordering the North Sea made commitments to reduce discharge of hazardous substances into the North Sea. From Belgium and The Netherlands, large reductions (upto 90) in heavy metal emissions from land-based sources have been reported between 1985 and 2000. Recently, some studies in the Western Scheldt estuary (WS) have shown that total metal concentration in the water, sediments and suspended particles have decreased compared to levels in the 70s. However, data on aquatic organisms is still very limited and it is therefore difficult to confirm whether the reductions in pollution input and generally improving water quality in the WS have a corresponding impact on the levels of heavy metals in aquatic organisms. The current study measured metal concentrations in the soft tissues of mussels, Mytilus edulis (known to be good indicators of environmental metal pollution) during the period 1996–2002. Spatial (salinity and pollution gradients), temporal and seasonal variations were also studied. Results showed a down-stream decreasing trend for the metals studied (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn) during all sampling campaigns. There was also a significant seasonal effect on tissue metal concentrations, with a peak observed around spring in both WS and the nearby less polluted Eastern Scheldt (ES). On temporal trends, a clear drop of metals in mussels was observed in the early 80s coinciding with the start of the efforts to reduce chemical pollution input into the North Sea. Since those early reductions, metal concentrations in mussels generally remained unchanged upto mid 90s. However, in recent times metal concentration in mussels have increased significantly, for example Cd in 2002 was almost 10 times the values in 1983 and similar to levels seen during the peak in the 70s. Other metals also increased in the 90s also reaching levels seen in the 70s. As there is no indication of recent increase in metal input into the estuary, we suggest that increased metal concentrations observed in mussels in recent years especially in the upper estuary are most likely a result of changes in physical and chemical speciation and metal bioavailability. Such changes may be caused by changes in some water quality parameters in the estuary (i.e. increased dissolved oxygen, concentration of organic matter), resulting in conditions that favour releases of sediment-bound metals into the water column. The relationship between metal content and season showed very similar annual profiles in the polluted WS and less polluted ES. Thus, seasonal variations in metal concentrations appear to be largely controlled by biological processes, while total body burdens are dependent on environmental levels and bioavailability.     

Combining next‐generation sequencing and progeny testing for rapid identification of induced recessive and dominant mutations in maize M2 individuals

Molecular identification of mutant alleles responsible for certain phenotypic alterations is a central goal of genetic analyses. In this study we describe a rapid procedure suitable for the identification of induced recessive and dominant mutations applied to two Zea mays mutants expressing a dwarf and a pale green phenotype, respectively, which were obtained through pollen ethyl methanesulfonate (EMS) mutagenesis. First, without prior backcrossing, induced mutations (single nucleotide polymorphisms, SNPs) segregating in a (M₂) family derived from a heterozygous (M₁) parent were identified using whole‐genome shotgun (WGS) sequencing of a small number of (M₂) individuals with mutant and wild‐type phenotypes. Second, the state of zygosity of the mutation causing the phenotype was determined for each sequenced individual by phenotypic segregation analysis of the self‐pollinated (M₃) offspring. Finally, we filtered for segregating EMS‐induced SNPs whose state of zygosity matched the determined state of zygosity of the mutant locus in each sequenced (M₂) individuals. Through this procedure, combining sequencing of individuals and Mendelian inheritance, three and four SNPs in linkage passed our zygosity filter for the homozygous dwarf and heterozygous pale green mutation, respectively. The dwarf mutation was found to be allelic to the an1 locus and caused by an insertion in the largest exon of the AN1 gene. The pale green mutation affected the nuclear W2 gene and was caused by a non‐synonymous amino acid exchange in encoded chloroplast DNA polymerase with a predicted deleterious effect. This coincided with lower cpDNA levels in pale green plants.     

Aquatic carbon fluxes dampen the overall variation of net ecosystem productivity in the Amazon basin: An analysis of the interannual variability in the boundless carbon cycle

The river–floodplain network plays an important role in the carbon (C) cycle of the Amazon basin, as it transports and processes a significant fraction of the C fixed by terrestrial vegetation, most of which evades as CO₂ from rivers and floodplains back to the atmosphere. There is empirical evidence that exceptionally dry or wet years have an impact on the net C balance in the Amazon. While seasonal and interannual variations in hydrology have a direct impact on the amounts of C transferred through the river–floodplain system, it is not known how far the variation of these fluxes affects the overall Amazon C balance. Here, we introduce a new wetland forcing file for the ORCHILEAK model, which improves the representation of floodplain dynamics and allows us to closely reproduce data‐driven estimates of net C exports through the river–floodplain network. Based on this new wetland forcing and two climate forcing datasets, we show that across the Amazon, the percentage of net primary productivity lost to the river–floodplain system is highly variable at the interannual timescale, and wet years fuel aquatic CO₂ evasion. However, at the same time overall net ecosystem productivity (NEP) and C sequestration are highest during wet years, partly due to reduced decomposition rates in water‐logged floodplain soils. It is years with the lowest discharge and floodplain inundation, often associated with El Nino events, that have the lowest NEP and the highest total (terrestrial plus aquatic) CO₂ emissions back to atmosphere. Furthermore, we find that aquatic C fluxes display greater variation than terrestrial C fluxes, and that this variation significantly dampens the interannual variability in NEP of the Amazon basin. These results call for a more integrative view of the C fluxes through the vegetation‐soil‐river‐floodplain continuum, which directly places aquatic C fluxes into the overall C budget of the Amazon basin.     

The impact of low-magnitude high-frequency vibration on fracture healing is profoundly influenced by the oestrogen status in mice

Fracture healing is impaired in aged and osteoporotic individuals. Because adequate mechanical stimuli are able to increase bone formation, one therapeutical approach to treat poorly healing fractures could be the application of whole-body vibration, including low-magnitude high-frequency vibration (LMHFV). We investigated the effects of LMHFV on fracture healing in aged osteoporotic mice. Female C57BL/6NCrl mice (n=96) were either ovariectomised (OVX) or sham operated (non-OVX) at age 41 weeks. When aged to 49 weeks, all mice received a femur osteotomy that was stabilised using an external fixator. The mice received whole-body vibrations (20 minutes/day) with 0.3 g peak-to-peak acceleration and a frequency of 45 Hz. After 10 and 21 days, the osteotomised femurs and intact bones (contra-lateral femurs, lumbar spine) were evaluated using bending-testing, micro-computed tomography (μCT), histology and gene expression analyses. LMHFV disturbed fracture healing in aged non-OVX mice, with significantly reduced flexural rigidity (−81%) and bone formation (−80%) in the callus. Gene expression analyses demonstrated increased oestrogen receptor β (ERβ, encoded by Esr2) and Sost expression in the callus of the vibrated animals, but decreased β-catenin, suggesting that ERβ might mediate these negative effects through inhibition of osteoanabolic Wnt/β-catenin signalling. In contrast, in OVX mice, LMHFV significantly improved callus properties, with increased flexural rigidity (+1398%) and bone formation (+637%), which could be abolished by subcutaneous oestrogen application (0.025 mg oestrogen administered in a 90-day-release pellet). On a molecular level, we found an upregulation of ERα in the callus of the vibrated OVX mice, whereas ERβ was unaffected, indicating that ERα might mediate the osteoanabolic response. Our results indicate a major role for oestrogen in the mechanostimulation of fracture healing and imply that LMHFV might only be safe and effective in confined target populations.KEY WORDS: Whole-body vibration, LMHFV, Fracture healing, Oestrogen receptor signalling, Wnt signalling     

Neutrophil activation by Candida glabrata but not Candida albicans promotes fungal uptake by monocytes

Candida albicans and Candida glabrata account for the majority of candidiasis cases worldwide. Although both species are in the same genus, they differ in key virulence attributes. Within this work, live cell imaging was used to examine the dynamics of neutrophil activation after confrontation with either C. albicans or C. glabrata. Analyses revealed higher phagocytosis rates of C. albicans than C. glabrata that resulted in stronger PMN (polymorphonuclear cells) activation by C. albicans. Furthermore, we observed differences in the secretion of chemokines, indicating chemotactic differences in PMN signalling towards recruitment of further immune cells upon confrontation with Candida spp. Supernatants from co‐incubations of neutrophils with C. glabrata primarily attracted monocytes and increased the phagocytosis of C. glabrata by monocytes. In contrast, PMN activation by C. albicans resulted in recruitment of more neutrophils. Two complex infection models confirmed distinct targeting of immune cell populations by the two Candida spp.: In a human whole blood infection model, C. glabrata was more effectively taken up by monocytes than C. albicans and histopathological analyses of murine model infections confirmed primarily monocytic infiltrates in C. glabrata kidney infection in contrast to PMN‐dominated infiltrates in C. albicans infection. Taken together, our data demonstrate that the human opportunistic fungi C. albicans and C. glabrata are differentially recognized by neutrophils and one outcome of this differential recognition is the preferential uptake of C. glabrata by monocytes.     

Pheno2Geno - High-throughput generation of genetic markers and maps from molecular phenotypes for crosses between inbred strains

Background

Genetic markers and maps are instrumental in quantitative trait locus (QTL) mapping in segregating populations. The resolution of QTL localization depends on the number of informative recombinations in the population and how well they are tagged by markers. Larger populations and denser marker maps are better for detecting and locating QTLs. Marker maps that are initially too sparse can be saturated or derived de novo from high-throughput omics data, (e.g. gene expression, protein or metabolite abundance). If these molecular phenotypes are affected by genetic variation due to a major QTL they will show a clear multimodal distribution. Using this information, phenotypes can be converted into genetic markers.

Results

The Pheno2Geno tool uses mixture modeling to select phenotypes and transform them into genetic markers suitable for construction and/or saturation of a genetic map. Pheno2Geno excludes candidate genetic markers that show evidence for multiple possibly epistatically interacting QTL and/or interaction with the environment, in order to provide a set of robust markers for follow-up QTL mapping.We demonstrate the use of Pheno2Geno on gene expression data of 370,000 probes in 148 A. thaliana recombinant inbred lines. Pheno2Geno is able to saturate the existing genetic map, decreasing the average distance between markers from 7.1 cM to 0.89 cM, close to the theoretical limit of 0.68 cM (with 148 individuals we expect a recombination every 100/148=0.68 cM); this pinpointed almost all of the informative recombinations in the population.

Conclusion

The Pheno2Geno package makes use of genome-wide molecular profiling and provides a tool for high-throughput de novo map construction and saturation of existing genetic maps. Processing of the showcase dataset takes less than 30 minutes on an average desktop PC. Pheno2Geno improves QTL mapping results at no additional laboratory cost and with minimum computational effort. Its results are formatted for direct use in R/qtl, the leading R package for QTL studies. Pheno2Geno is freely available on CRAN under “GNU GPL v3”. The Pheno2Geno package as well as the tutorial can also be found at: http://pheno2geno.nl.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0475-6) contains supplementary material, which is available to authorized users.     

Rewriting the Central European Early Bronze Age Chronology: Evidence from Large-Scale Radiocarbon Dating

The transition from the Neolithic to the Early Bronze Age in Central Europe has often been considered as a supra-regional uniform process, which led to the growing mastery of the new bronze technology. Since the 1920s, archaeologists have divided the Early Bronze Age into two chronological phases (Bronze A1 and A2), which were also seen as stages of technical progress. On the basis of the early radiocarbon dates from the cemetery of Singen, southern Germany, the beginning of the Early Bronze Age in Central Europe was originally dated around 2300/2200 BC and the transition to more complex casting techniques (i.e., Bronze A2) around 2000 BC. On the basis of 140 newly radiocarbon dated human remains from Final Neolithic, Early and Middle Bronze Age cemeteries south of Augsburg (Bavaria) and a re-dating of ten graves from the cemetery of Singen, we propose a significantly different dating range, which forces us to re-think the traditional relative and absolute chronologies as well as the narrative of technical development. We are now able to date the beginning of the Early Bronze Age to around 2150 BC and its end to around 1700 BC. Moreover, there is no transition between Bronze (Bz) A1 and Bronze (Bz) A2, but a complete overlap between the type objects of the two phases from 1900–1700 BC. We thus present a revised chronology of the assumed diagnostic type objects of the Early Bronze Age and recommend a radiocarbon-based view on the development of the material culture. Finally, we propose that the traditional phases Bz A1 and Bz A2 do not represent a chronological sequence, but regionally different social phenomena connected to the willingness of local actors to appropriate the new bronze technology.     

Modeling Solute Transport by DLA in Soils of Northeastern Egypt

Arid soils in Egypt display large variability in solute transport properties, causing problems in soil management. To characterize this variability, dye infiltration experiments were conducted on four plots representing three main soil types in northeastern Egypt. The plots represented both cultivated and uncultivated land use. The observed dye patterns displayed a large variability and especially the clay soils indicated a high degree of preferential flow. The loamy sand and sandy soils displayed a more uniform dye distribution indicating more homogeneous soil properties. The observed dye patterns were modeled using a diffusion limited aggregation (DLA) model. The DLA is a random walk model where model parameters can be optimized using genetic algorithms (GA). The DLA model reproduced the observed dye patterns for all soils in an excellent way. The best fit was obtained with a specific combination of directional random walk probabilities P_u, P_d, P_r, and P_l for each plot (correlation 0.97–0.99). To account for soil layers with different hydraulic properties a two layer DLA model was developed. For all plots the P_u (upward random walk probability) was higher for the upper more homogeneous soil layer. The overall results showed that spatial variability resulting from solute transport for the investigated soils can be modeled using a DLA approach.