scnRCA: A Novel Method to Detect Consistent Patterns of Translational Selection in Mutationally-Biased Genomes

Codon usage bias (CUB) results from the complex interplay between translational selection and mutational biases. Current methods for CUB analysis apply heuristics to integrate both components, limiting the depth and scope of CUB analysis as a technique to probe into the evolution and optimization of protein-coding genes. Here we introduce a self-consistent CUB index (scnRCA) that incorporates implicit correction for mutational biases, facilitating exploration of the translational selection component of CUB. We validate this technique using gene expression data and we apply it to a detailed analysis of CUB in the Pseudomonadales. Our results illustrate how the selective enrichment of specific codons among highly expressed genes is preserved in the context of genome-wide shifts in codon frequencies, and how the balance between mutational and translational biases leads to varying definitions of codon optimality. We extend this analysis to other moderate and fast growing bacteria and we provide unified support for the hypothesis that C- and A-ending codons of two-box amino acids, and the U-ending codons of four-box amino acids, are systematically enriched among highly expressed genes across bacteria. The use of an unbiased estimator of CUB allows us to report for the first time that the signature of translational selection is strongly conserved in the Pseudomonadales in spite of drastic changes in genome composition, and extends well beyond the core set of highly optimized genes in each genome. We generalize these results to other moderate and fast growing bacteria, hinting at selection for a universal pattern of gene expression that is conserved and detectable in conserved patterns of codon usage bias.     

The Impact of Alpha-Syntrophin Deletion on the Changes in Tissue Structure and Extracellular Diffusion Associated with Cell Swelling under Physiological and Pathological Conditions

Aquaporin-4 (AQP4) is the primary cellular water channel in the brain and is abundantly expressed by astrocytes along the blood-brain barrier and brain-cerebrospinal fluid interfaces. Water transport via AQP4 contributes to the activity-dependent volume changes of the extracellular space (ECS), which affect extracellular solute concentrations and neuronal excitability. AQP4 is anchored by α-syntrophin (α-syn), the deletion of which leads to reduced AQP4 levels in perivascular and subpial membranes. We used the real-time iontophoretic method and/or diffusion-weighted magnetic resonance imaging to clarify the impact of α-syn deletion on astrocyte morphology and changes in extracellular diffusion associated with cell swelling in vitro and in vivo. In mice lacking α-syn, we found higher resting values of the apparent diffusion coefficient of water (ADC_W) and the extracellular volume fraction (α). No significant differences in tortuosity (λ) or non-specific uptake (k′), were found between α-syn-negative (α-syn −/−) and α-syn-positive (α-syn +/+) mice. The deletion of α-syn resulted in a significantly smaller relative decrease in α observed during elevated K⁺ (10 mM) and severe hypotonic stress (−100 mOsmol/l), but not during mild hypotonic stress (−50 mOsmol/l). After the induction of terminal ischemia/anoxia, the final values of ADC_W as well as of the ECS volume fraction α indicate milder cell swelling in α-syn −/− in comparison with α-syn +/+ mice. Shortly after terminal ischemia/anoxia induction, the onset of a steep rise in the extracellular potassium concentration and an increase in λ was faster in α-syn −/− mice, but the final values did not differ between α-syn −/− and α-syn +/+ mice. This study reveals that water transport through AQP4 channels enhances and accelerates astrocyte swelling. The substantially altered ECS diffusion parameters will likely affect the movement of neuroactive substances and/or trophic factors, which in turn may modulate the extent of tissue damage and/or drug distribution.     

Chemical Diversity of the Natural Populations of Dalmatian Pyrethrum (Tanacetum cinerariifolium (Trevir.) Sch.Bip.) in Croatia

Dalmatian pyrethrum (Tanacetum cinerariifolium (Trevir. ) Sch.Bip. ) is a plant species endemic to the east Adriatic coast. The bioactive substance of Dalmatian pyrethrum is a natural insecticide, pyrethrin, a mixture of six active components (pyrethrins I and II, cinerins I and II, and jasmolins I and II). The insecticidal potential of pyrethrin was recognized decades ago, and dried and ground flowers have traditionally been used in Croatian agriculture and households. A total of 25 Dalmatian pyrethrum populations from Croatia were studied to determine the pyrethrin content and composition, and to identify distinct chemotypes. The total pyrethrin content ranged from 0.36 to 1.30% (dry flower weight; DW) and the pyrethrin I/pyrethrin II ratio ranged from 0.64 to 3.33%. The statistical analyses revealed that the correlations between the percentage of pyrethrin I and of all the other components were significant and negative. The total pyrethrin content was positively correlated with the percentage of pyrethrin I and negatively correlated with cinerin II. The multivariate analysis of the chemical variability enabled the identification of five chemotypes among 25 Dalmatian pyrethrum populations. The chemical characterization of indigenous Dalmatian pyrethrum populations may serve as a good background for future breeding and agricultural exploitation.     

Glycan-binding profile of DC-like cells

Modification of vaccine carriers by decoration with glycans can enhance binding to and even targeting of dendritic cells (DCs), thus augmenting vaccine efficacy. To find a specific glycan-“vector” it is necessary to know glycan-binding profile of DCs. This task is not trivial; the small number of circulating blood DCs available for isolation hinders screening and therefore advancement of the profiling. It would be more convenient to employ long-term cell cultures or even primary DCs from murine blood. We therefore examined whether THP-1 (human monocyte cell line) and DC2.4 (immature murine DC-like cell line) could serve as a model for human DCs. These cells were probed with a set of glycans previously identified as binding to circulating human CD14low/-CD16+CD83+ DCs. In addition, we tested a subpopulation of murine CD14low/-CD80+СD11c+CD16+ cells reported as relating to the human CD14low/-CD16+CD83+ cells. Manα1–3(Manα1–6)Manβ1–4GlcNAcβ1–4GlcNAcβ bound to both the cell lines and the murine CD14low/-CD80+СD11c+CD16+ cells. Primary cells, but not the cell cultures, were capable of binding GalNAcα1–3Galβ (Adi), the most potent ligand for binding to human circulating DCs. In conclusion, not one of the studied cell lines proved an adequate model for DCs processes involving lectin binding. Although the glycan-binding profile of BYRB-Rb (8.17)1Iem mouse DCs could prove useful for assessing human DCs, important glycan interactions were missing, a situation which was aggravated when employing cells from the BALB/c strain. Accordingly, one must treat results from murine work with caution when seeking vaccine targeting of human DCs, and certainly should avoid cell lines such as THP-1 and DC2.4 cells.     

Investigating the heat shock protein response involved in coral bleaching across scleractinian species in the central Red Sea

Coral Reefs - Coral bleaching represents the most serious threat to contemporary coral reefs. In response, focus is being laid on understanding the cellular processes involved in the response of...     

Sequential adaptive variables and subject selection for GEE methods

Modeling correlated or highly stratified multiple-response data is a common data analysis task in many applications, such as those in large epidemiological studies or multisite cohort studies. The generalized estimating equations method is a popular statistical method used to analyze these kinds of data, because it can manage many types of unmeasured dependence among outcomes. Collecting large amounts of highly stratified or correlated response data is time-consuming; thus, the use of a more aggressive sampling strategy that can accelerate this process—such as the active-learning methods found in the machine-learning literature—will always be beneficial. In this study, we integrate adaptive sampling and variable selection features into a sequential procedure for modeling correlated response data. Besides reporting the statistical properties of the proposed procedure, we also use both synthesized and real data sets to demonstrate the usefulness of our method.     

Calcium and iron as key drivers of brown moss composition through differential effects on phosphorus availability

Brown moss-dominated rich fens are characterized by minerotrophic conditions, in which calcium (Ca) and iron (Fe) concentrations show large variations. We examined the relative importance of Ca and Fe in relation to the occurrence of three typical brown moss species: Scorpidium scorpioides, Scorpidium cossonii, and Hamatocaulis vernicosus. Peat chemistry was examined in 24 stands of brown moss-dominated rich fens: 12 in the Netherlands and 12 in central Sweden. Ca and Fe turned out to be important drivers of brown moss composition. Fens dominated by Scorpidium scorpioides or Scorpidium cossonii were characterized by high pore water Ca-concentrations and total soil Ca-contents, but low P-availability. In these Ca-rich, but Fe-poor fens, foliar N:P ratios of vascular vegetation exceeded 20?g?g^?1, indicating phosphorus (P)-limitation due to Ca-P precipitation or low P-sorption capacity due to low Fe-levels. In contrast, fens dominated by Hamatocaulis vernicosus were characterized by high pore water Fe-concentrations and total soil Fe-contents, but also relatively high P-availability. N:P ratios in these fens were below 13.5?g?g^?1, indicating potential nitrogen (N)-limitation. We conclude that the relative roles of Ca and Fe, as related to the geohydrological conditions present, strongly determine the brown moss composition in rich fens through their differential effects on plant P-availability.