pdx-1 function is specifically required in embryonic beta cells to generate appropriate numbers of endocrine cell types and maintain glucose homeostasis

The pdx1 gene is essential for pancreatic organogenesis in humans and mice; pdx1 mutations have been identified in human diabetic patients. Specific inactivation of pdx1 in adult beta cells revealed that this gene is required for maintenance of mature beta cell function. In the following study, a Cre-lox strategy was used to remove pdx1 function specifically from embryonic beta cells beginning at late-gestation, prior to islet formation. Animals in which pdx1 is lost in insulin-producing cells during embryogenesis had elevated blood glucose levels at birth and were overtly diabetic by weaning. Neonatal and adult mutant islets showed a dramatic reduction in the number of insulin(+) cells and an increase in both glucagon(+) and somatostatin(+) cells. Lineage tracing revealed that excess glucagon(+) and somatostatin(+) cells did not arise by interconversion of endocrine cell types. Examination of mutant islets revealed a decrease in proliferation of insulin-producing cells just before birth and a concomitant increase in proliferation of glucagon-producing cells. We propose that pdx1 is required for proliferation and function of the beta cells generated at late gestation, and that one function of normal beta cells is to inhibit the proliferation of other islet cell types, resulting in the appropriate numbers of the different endocrine cell types.     

Elemental Fingerprinting of Mussel Shells to Predict Population Sources and Redistribution Potential in the Gulf of Maine

As the climate warms, species that cannot tolerate changing conditions will only persist if they undergo range shifts. Redistribution ability may be particularly variable for benthic marine species that disperse as pelagic larvae in ocean currents. The blue mussel, Mytilus edulis, has recently experienced a warming-related range contraction in the southeastern USA and may face limitations to northward range shifts within the Gulf of Maine where dominant coastal currents flow southward. Thus, blue mussels might be especially vulnerable to warming, and understanding dispersal patterns is crucial given the species'' relatively long planktonic larval period (>1 month). To determine whether trace elemental “fingerprints” incorporated in mussel shells could be used to identify population sources (i.e. collection locations), we assessed the geographic variation in shell chemistry of blue mussels collected from seven populations between Cape Cod, Massachusetts and northern Maine. Across this ∼500 km of coastline, we were able to successfully predict population sources for over two-thirds of juvenile individuals, with almost 80% of juveniles classified within one site of their collection location and 97% correctly classified to region. These results indicate that significant differences in elemental signatures of mussel shells exist between open-coast sites separated by ∼50 km throughout the Gulf of Maine. Our findings suggest that elemental “fingerprinting” is a promising approach for predicting redistribution potential of the blue mussel, an ecologically and economically important species in the region.     

Comparative genetic mapping reveals synteny and collinearity between the American cranberry and diploid blueberry genomes

Cranberry and blueberry are closely related and recently domesticated fruit crops in the genus Vaccinium. Both have a presumed American origin and likely evolved from a common ancestor; however, details of their adaptive radiation and the extent of their genomic divergence remains little understood. To better understand their evolutionary and genomic relationships, a set of 323 cross-transferable simple sequence repeat (SSR) markers were identified, added to existing marker datasets, and used to construct linkage maps for cranberry (582 SSRs) and an interspecific diploid blueberry population (V. darrowii x V. corymbosum) x V. corymbosum (409 markers, densest blueberry SSR map currently available). The maps allowed for the first comparative genetic mapping study in Vaccinium, and revealed a surprisingly high degree of macro-synteny and collinearity between the cranberry and blueberry genomes. Approximately 93% of the blueberry linkage map was collinear with cranberry, while the remaining 7% (66.3 cM) was spread across 15 non-collinear regions detected in eight of the 12 linkage groups. These observations suggest that large-scale genome differentiation between the cranberry and blueberry genomes has not occurred during their evolution, and that sequence information will be highly transferable between the species in future genetic research and breeding. Finally, the set of 323 cross-transferable SSRs and linkage maps they were used to construct can serve as a shared resource for the Vaccinium research community, enabling additional comparative mapping studies, the identification and transfer of quantitative trait loci and candidate genes between species, and future exploration of evolutionary relationships in Vaccinium.     

Leveraging two-way probe-level block design for identifying differential gene expression with high-density oligonucleotide arrays

Background  

To identify differentially expressed genes across experimental conditions in oligonucleotide microarray experiments, existing statistical methods commonly use a summary of probe-level expression data for each probe set and compare replicates of these values across conditions using a form of the t-test or rank sum test. Here we propose the use of a statistical method that takes advantage of the built-in redundancy architecture of high-density oligonucleotide arrays.     

Validated predictive modelling of the environmental resistome

Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome.     

Soil Microbial Community Structure and Metabolic Activity of Pinus elliottii Plantations across Different Stand Ages in a Subtropical Area

Soil microbes play an essential role in the forest ecosystem as an active component. This study examined the hypothesis that soil microbial community structure and metabolic activity would vary with the increasing stand ages in long-term pure plantations of Pinus elliottii. The phospholipid fatty acids (PLFA) combined with community level physiological profiles (CLPP) method was used to assess these characteristics in the rhizospheric soils of P. elliottii. We found that the soil microbial communities were significantly different among different stand ages of P. elliottii plantations. The PLFA analysis indicated that the bacterial biomass was higher than the actinomycic and fungal biomass in all stand ages. However, the bacterial biomass decreased with the increasing stand ages, while the fungal biomass increased. The four maximum biomarker concentrations in rhizospheric soils of P. elliottii for all stand ages were 18:1ω9c, 16:1ω7c, 18:3ω6c (6,9,12) and cy19:0, representing measures of fungal and gram negative bacterial biomass. In addition, CLPP analysis revealed that the utilization rate of amino acids, polymers, phenolic acids, and carbohydrates of soil microbial community gradually decreased with increasing stand ages, though this pattern was not observed for carboxylic acids and amines. Microbial community diversity, as determined by the Simpson index, Shannon-Wiener index, Richness index and McIntosh index, significantly decreased as stand age increased. Overall, both the PLFA and CLPP illustrated that the long-term pure plantation pattern exacerbated the microecological imbalance previously described in the rhizospheric soils of P. elliottii, and markedly decreased the soil microbial community diversity and metabolic activity. Based on the correlation analysis, we concluded that the soil nutrient and C/N ratio most significantly contributed to the variation of soil microbial community structure and metabolic activity in different stand ages of P. elliottii plantations.