Genetics of frost hardiness in <Emphasis Type="Italic">Juglans regia</Emphasis> L. and relationship with growth and phenology

The growing interest in broadleaf timber plantations in the Mediterranean area has promoted several studies focusing on the identification and characterization of variability sources in main timber-producing species. J. regia is one of these species, well-adapted to this area, but with freezing, damages registrations. Breeding focused on productive traits should include knowledge of adaptation, required to obtain a good selection capable of producing a suitable turnover in timber plantations. In this study, the features evaluated were autumn and winter frost hardiness and some vegetative traits on 22 half-sib J. regia progenies. Budsticks were exposed to sub-zero temperatures in a controlled chamber and using measurements of relative electrolyte content, the LT50 values (°C) were calculated by each individual. The study was carried out on seven-year-old progenies. The familiar heritability of autumn frost hardiness was 0.68, and on winter, it was 0.77. The autumn frost behaviour correlated genetically with the length of the growing season (0.574 ± 0.351), and both autumn and winter frost hardiness correlated inversely with secondary annual growth measured at breast height (?0.654 ± 0.259 and ?0.740 ± 0.227, respectively). These results pointed that growth could therefore be improved without increasing the frost vulnerability. This should be important for growers, particularly under climate change conditions.     

Guidelines: From artificial evolution to computational evolution: a research agenda

Computational scientists have developed algorithms inspired by natural evolution for at least 50 years. These algorithms solve optimization and design problems by building solutions that are 'more fit' relative to desired properties. However, the basic assumptions of this approach are outdated. We propose a research programme to develop a new field: computational evolution. This approach will produce algorithms that are based on current understanding of molecular and evolutionary biology and could solve previously unimaginable or intractable computational and biological problems.     

The timing of leaf fall affects cold acclimation by interactions with air temperature through water and carbohydrate contents

Three parameters (i.e. the water content, soluble sugar content and minimal air temperature) can be used to predict the cold acclimation process of walnut trees. In order to test this assumption, two-year-old walnuts were defoliated at two different dates, i.e. mechanical defoliation in early October (early leaf fall, EF) or natural defoliation in early November (natural leaf fall, NF) and conditioned in either outdoor freeze-deprived or cold-deprived (T_min > 13 °C) greenhouses over winter. Even if early defoliation date could have affected short day signal perception (SDSP), water balance and carbohydrate metabolism were more altered. EF treatment, by stopping transpiration, significantly increased tree's water content and at warm temperature high root activity stopped normal winter dehydration. Starch content decreased in all treatments, but there was only a significant increase in soluble sugar content when water content had sufficiently decreased. Thus, depending on date of defoliation, cold-deprived trees were or were not able to acclimate to frost (minimal frost hardiness = −21.8 °C vs. −22.1 °C in controls (freeze-deprived) for NF and −13.7 °C vs. −25.3 °C in controls for EF). Different treatments showed the relationship between minimal water content observed during winter and maximal soluble sugars synthesized. Thus, the cold acclimation process appeared dependent on these physiological parameters (water and soluble sugar contents) through the interaction between air temperature and timing of leaf fall.     

Consistent probabilistic outputs for protein function prediction

In predicting hierarchical protein function annotations, such as terms in the Gene Ontology (GO), the simplest approach makes predictions for each term independently. However, this approach has the unfortunate consequence that the predictor may assign to a single protein a set of terms that are inconsistent with one another; for example, the predictor may assign a specific GO term to a given protein ('purine nucleotide binding') but not assign the parent term ('nucleotide binding'). Such predictions are difficult to interpret. In this work, we focus on methods for calibrating and combining independent predictions to obtain a set of probabilistic predictions that are consistent with the topology of the ontology. We call this procedure 'reconciliation'. We begin with a baseline method for predicting GO terms from a collection of data types using an ensemble of discriminative classifiers. We apply the method to a previously described benchmark data set, and we demonstrate that the resulting predictions are frequently inconsistent with the topology of the GO. We then consider 11 distinct reconciliation methods: three heuristic methods; four variants of a Bayesian network; an extension of logistic regression to the structured case; and three novel projection methods - isotonic regression and two variants of a Kullback-Leibler projection method. We evaluate each method in three different modes - per term, per protein and joint - corresponding to three types of prediction tasks. Although the principal goal of reconciliation is interpretability, it is important to assess whether interpretability comes at a cost in terms of precision and recall. Indeed, we find that many apparently reasonable reconciliation methods yield reconciled probabilities with significantly lower precision than the original, unreconciled estimates. On the other hand, we find that isotonic regression usually performs better than the underlying, unreconciled method, and almost never performs worse; isotonic regression appears to be able to use the constraints from the GO network to its advantage. An exception to this rule is the high precision regime for joint evaluation, where Kullback-Leibler projection yields the best performance.     

The Siva protein is a novel intracellular ligand of the CD4 receptor that promotes HIV-1 envelope-induced apoptosis in T-lymphoid cells

In addition to its positive signaling function in the antigen presentation process, CD4 acts as the primary receptor for HIV-1. Contact between CD4 and the viral envelope leads to virus entry, but can also trigger apoptosis of uninfected CD4⁺ T-cells through a mechanism that is poorly understood. We show that Siva-1, a death domain-containing proapoptotic protein, associates with the cytoplasmic domain of CD4. This interaction is mediated by the cysteine-rich region found in the C-terminal part of the Siva-1 protein. Expression of Siva-1 specifically increases the susceptibility of both T-cell lines and unstimulated human primary CD4⁺ T-lymphocytes to CD4-mediated apoptosis triggered by the HIV-1 envelope, and results in activation of a caspase-dependent mitochondrial pathway. The same susceptibility is observed in T-cells expressing a truncated form of CD4 that is able to recruit Siva-1 but fails to associate with p56^Lck, indicating that Siva-1 participates in a pathway independent of the p56^Lck kinase activity. Altogether, these results suggest that Siva-1 might participate in the CD4-initiated signaling apoptotic pathway induced by the HIV-1 envelope in T-lymphoid cells. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Chromatographic study of magnesium and calcium binding to immobilized human serum albumin

The use of immobilized human serum albumin (HSA) as a stationary phase in affinity chromatography has been shown to be useful in resolving optical antipodes or to investigate interactions between drugs and protein. However, to our knowledge, no inorganic ion binding has been studied on this immobilized protein type. To do this, the human serum albumin stationary phase was assimilated to a weak cation-exchanger by working with a mobile phase pH equal to 6.5. A study of the eluent ionic strength effect on ion retention was carried out by varying the buffer concentrations and the column temperatures. The thermodynamic parameters for magnesium and calcium transfer from the mobile to the stationary phase were determined from linear van’t Hoff plots. An enthalpy–entropy compensation study revealed that the type of interaction was independent of the mobile phase composition. A simple model based on the Gouy–Chapman theory was considered in order to describe the retention behavior of the test cations with the mobile phase ionic strength. From this theoretical approach, the relative charge densities of the human serum albumin surface implied in the binding process were estimated at different column temperatures.     

Anti-coagulant rodenticide binding properties of human serum albumin: a biochromatographic approach

In this paper, the anti-coagulant rodenticide-human serum albumin (HSA) binding was investigated using a perturbation method to calculate the solute distribution isotherms. It was shown that rodenticide can bound either on the benzodiazepine HSA site with low affinity (site I) or on the warfarin HSA site with high affinity (site II). The thermodynamic parameters of this association were calculated for the two HSA binding sites. For the site II, the rodenticide-HSA association was governed enthalpically whereas for the site I, this one was driven entropically. Moreover, the role of the magnesium (Mg(2+)) and calcium (Ca(2+)) on this association was carried out. It was clearly demonstrated that the rodenticide affinity for the site I was not affected by modifying the bulk solvent surface tension whereas for the site II the association constant increased strongly with the Mg(2+) or the Ca(2+) concentration in the bulk solvent. These results showed that the rodenticide-HSA affinity and thus the rodenticide toxicological effect depends on the Mg(2+) or Ca(2+) concentration.     

SECIS-binding protein 2, a key player in selenoprotein synthesis,is an intrinsically disordered protein

Selenocysteine (Sec) is co-translationally incorporated into selenoproteins at a reprogrammed UGA codon. In mammals, this requires a dedicated machinery comprising a stem-loop structure in the 3′ UTR RNA (the SECIS element) and the specific SECIS Binding Protein 2. In this report, disorder-prediction methods and several biophysical techniques showed that ca. 70% of the SBP2 sequence is disordered, whereas the RNA binding domain appears to be folded and functional. These results are consistent with a recent report on the role of the Hsp90 chaperone for the folding of SBP2 and other functionally unrelated proteins bearing an RNA binding domain homologous to SBP2.