Molecular mechanisms of β-lactam resistance in Streptococcus pneumoniae

Alterations in the target enzymes for β-lactam antibiotics, the penicillin-binding proteins (PBPs), have been recognized as a major resistance mechanism in Streptococcus pneumoniae. Mutations in PBPs that confer a reduced affinity to β-lactams have been identified in laboratory mutants and clinical isolates, and document an astounding variability of sites involved in this phenotype. Whereas point mutations are selected in the laboratory, clinical isolates display a mosaic structure of the affected PBP genes, the result of interspecies gene transfer and recombination events. Depending on the selective β-lactam, different combinations of PBP genes and mutations within are involved in conferring resistance, and astoundingly in non-PBP genes as well.     

The hedgehog receptor patched is involved in cholesterol transport

Background

Sonic hedgehog (Shh) signaling plays a crucial role in growth and patterning during embryonic development, and also in stem cell maintenance and tissue regeneration in adults. Aberrant Shh pathway activation is involved in the development of many tumors, and one of the most affected Shh signaling steps found in these tumors is the regulation of the signaling receptor Smoothened by the Shh receptor Patched. In the present work, we investigated Patched activity and the mechanism by which Patched inhibits Smoothened.

Methodology/Principal Findings

Using the well-known Shh-responding cell line of mouse fibroblasts NIH 3T3, we first observed that enhancement of the intracellular cholesterol concentration induces Smoothened enrichment in the plasma membrane, which is a crucial step for the signaling activation. We found that binding of Shh protein to its receptor Patched, which involves Patched internalization, increases the intracellular concentration of cholesterol and decreases the efflux of a fluorescent cholesterol derivative (BODIPY-cholesterol) from these cells. Treatment of fibroblasts with cyclopamine, an antagonist of Shh signaling, inhibits Patched expression and reduces BODIPY-cholesterol efflux, while treatment with the Shh pathway agonist SAG enhances Patched protein expression and BODIPY-cholesterol efflux. We also show that over-expression of human Patched in the yeast S. cerevisiae results in a significant boost of BODIPY-cholesterol efflux. Furthermore, we demonstrate that purified Patched binds to cholesterol, and that the interaction of Shh with Patched inhibits the binding of Patched to cholesterol.

Conclusion/Significance

Our results suggest that Patched may contribute to cholesterol efflux from cells, and to modulation of the intracellular cholesterol concentration. This activity is likely responsible for the inhibition of the enrichment of Smoothened in the plasma membrane, which is an important step in Shh pathway activation.     

Accessing the soil metagenome for studies of microbial diversity

Soil microbial communities contain the highest level of prokaryotic diversity of any environment, and metagenomic approaches involving the extraction of DNA from soil can improve our access to these communities. Most analyses of soil biodiversity and function assume that the DNA extracted represents the microbial community in the soil, but subsequent interpretations are limited by the DNA recovered from the soil. Unfortunately, extraction methods do not provide a uniform and unbiased subsample of metagenomic DNA, and as a consequence, accurate species distributions cannot be determined. Moreover, any bias will propagate errors in estimations of overall microbial diversity and may exclude some microbial classes from study and exploitation. To improve metagenomic approaches, investigate DNA extraction biases, and provide tools for assessing the relative abundances of different groups, we explored the biodiversity of the accessible community DNA by fractioning the metagenomic DNA as a function of (i) vertical soil sampling, (ii) density gradients (cell separation), (iii) cell lysis stringency, and (iv) DNA fragment size distribution. Each fraction had a unique genetic diversity, with different predominant and rare species (based on ribosomal intergenic spacer analysis [RISA] fingerprinting and phylochips). All fractions contributed to the number of bacterial groups uncovered in the metagenome, thus increasing the DNA pool for further applications. Indeed, we were able to access a more genetically diverse proportion of the metagenome (a gain of more than 80% compared to the best single extraction method), limit the predominance of a few genomes, and increase the species richness per sequencing effort. This work stresses the difference between extracted DNA pools and the currently inaccessible complete soil metagenome.     

Stand dynamics modulate water cycling and mortality risk in droughted tropical forest

Transpiration from the Amazon rainforest generates an essential water source at a global and local scale. However, changes in rainforest function with climate change can disrupt this process, causing significant reductions in precipitation across Amazonia, and potentially at a global scale. We report the only study of forest transpiration following a long‐term (>10 year) experimental drought treatment in Amazonian forest. After 15 years of receiving half the normal rainfall, drought‐related tree mortality caused total forest transpiration to decrease by 30%. However, the surviving droughted trees maintained or increased transpiration because of reduced competition for water and increased light availability, which is consistent with increased growth rates. Consequently, the amount of water supplied as rainfall reaching the soil and directly recycled as transpiration increased to 100%. This value was 25% greater than for adjacent nondroughted forest. If these drought conditions were accompanied by a modest increase in temperature (e.g., 1.5°C), water demand would exceed supply, making the forest more prone to increased tree mortality.     

Regional grassland productivity responses to precipitation during multiyear above‐ and below‐average rainfall periods

There is considerable uncertainty in the magnitude and direction of changes in precipitation associated with climate change, and ecosystem responses are also uncertain. Multiyear periods of above‐ and below‐average rainfall may foretell consequences of changes in rainfall regime. We compiled long‐term aboveground net primary productivity (ANPP) and precipitation (PPT) data for eight North American grasslands, and quantified relationships between ANPP and PPT at each site, and in 1–3 year periods of above‐ and below‐average rainfall for mesic, semiarid cool, and semiarid warm grassland types. Our objective was to improve understanding of ANPP dynamics associated with changing climatic conditions by contrasting PPT–ANPP relationships in above‐ and below‐average PPT years to those that occurred during sequences of multiple above‐ and below‐average years. We found differences in PPT–ANPP relationships in above‐ and below‐average years compared to long‐term site averages, and variation in ANPP not explained by PPT totals that likely are attributed to legacy effects. The correlation between ANPP and current‐ and prior‐year conditions changed from year to year throughout multiyear periods, with some legacy effects declining, and new responses emerging. Thus, ANPP in a given year was influenced by sequences of conditions that varied across grassland types and climates. Most importantly, the influence of prior‐year ANPP often increased with the length of multiyear periods, whereas the influence of the amount of current‐year PPT declined. Although the mechanisms by which a directional change in the frequency of above‐ and below‐average years imposes a persistent change in grassland ANPP require further investigation, our results emphasize the importance of legacy effects on productivity for sequences of above‐ vs. below‐average years, and illustrate the utility of long‐term data to examine these patterns.     

integRATE: a desirability-based data integration framework for the prioritization of candidate genes across heterogeneous omics and its application to preterm birth

Background

The integration of high-quality, genome-wide analyses offers a robust approach to elucidating genetic factors involved in complex human diseases. Even though several methods exist to integrate heterogeneous omics data, most biologists still manually select candidate genes by examining the intersection of lists of candidates stemming from analyses of different types of omics data that have been generated by imposing hard (strict) thresholds on quantitative variables, such as P-values and fold changes, increasing the chance of missing potentially important candidates.

Methods

To better facilitate the unbiased integration of heterogeneous omics data collected from diverse platforms and samples, we propose a desirability function framework for identifying candidate genes with strong evidence across data types as targets for follow-up functional analysis. Our approach is targeted towards disease systems with sparse, heterogeneous omics data, so we tested it on one such pathology: spontaneous preterm birth (sPTB).

Results

We developed the software integRATE, which uses desirability functions to rank genes both within and across studies, identifying well-supported candidate genes according to the cumulative weight of biological evidence rather than based on imposition of hard thresholds of key variables. Integrating 10 sPTB omics studies identified both genes in pathways previously suspected to be involved in sPTB as well as novel genes never before linked to this syndrome. integRATE is available as an R package on GitHub (https://github.com/haleyeidem/integRATE).

Conclusions

Desirability-based data integration is a solution most applicable in biological research areas where omics data is especially heterogeneous and sparse, allowing for the prioritization of candidate genes that can be used to inform more targeted downstream functional analyses.

     

Genetic polymorphisms of Echinococcus tapeworms in China as determined by mitochondrial and nuclear DNA sequences

The genetic polymorphisms of Echinococcus spp. in the eastern Tibetan Plateau and the Xinjiang Uyghur Autonomous Region were evaluated by DNA sequencing analyses of genes for mitochondrial cytochrome c oxidase subunit 1 (cox1) and nuclear elongation factor-1 alpha (ef1a). We collected 68 isolates of Echinococcus granulosus sensu stricto (s.s.) from Xinjiang and 113 isolates of E. granulosus s. s., 49 isolates of Echinococcus multilocularis and 34 isolates of Echinococcus shiquicus from the Tibetan Plateau. The results of molecular identification by mitochondrial and nuclear markers were identical, suggesting the infrequency of introgressive hybridization. A considerable intraspecific variation was detected in mitochondrial cox1 sequences. The parsimonious network of cox1 haplotypes showed star-like features in E. granulosus s. s. and E. multilocularis, but a divergent feature in E. shiquicus. The cox1 neutrality indexes computed by Tajima’s D and Fu’s Fs tests showed high negative values in E. granulosus s. s. and E. multilocularis, indicating significant deviations from neutrality. In contrast, the low positive values of both tests were obtained in E. shiquicus. These results suggest the following hypotheses: (i) recent founder effects arose in E. granulosus and E. multilocularis after introducing particular individuals into the endemic areas by anthropogenic movement or natural migration of host mammals, and (ii) the ancestor of E. shiquicus was segregated into the Tibetan Plateau by colonising alpine mammals and its mitochondrial locus has evolved without bottleneck effects.     

Complex phylogenetic distribution of a non-canonical genetic code in green algae

Background  

A non-canonical nuclear genetic code, in which TAG and TAA have been reassigned from stop codons to glutamine, has evolved independently in several eukaryotic lineages, including the ulvophycean green algal orders Dasycladales and Cladophorales. To study the phylogenetic distribution of the standard and non-canonical genetic codes, we generated sequence data of a representative set of ulvophycean green algae and used a robust green algal phylogeny to evaluate different evolutionary scenarios that may account for the origin of the non-canonical code.