Identification and functional characterization of the Arabidopsis Snf1‐related protein kinase SnRK2.4 phosphatidic acid‐binding domain

Phosphatidic acid (PA) is an important signalling lipid involved in various stress‐induced signalling cascades. Two SnRK2 protein kinases (SnRK2.4 and SnRK2.10), previously identified as PA‐binding proteins, are shown here to prefer binding to PA over other anionic phospholipids and to associate with cellular membranes in response to salt stress in Arabidopsis roots. A 42 amino acid sequence was identified as the primary PA‐binding domain (PABD) of SnRK2.4. Unlike the full‐length SnRK2.4, neither the PABD‐YFP fusion protein nor the SnRK2.10 re‐localized into punctate structures upon salt stress treatment, showing that additional domains of the SnRK2.4 protein are required for its re‐localization during salt stress. Within the PABD, five basic amino acids, conserved in class 1 SnRK2s, were found to be necessary for PA binding. Remarkably, plants overexpressing the PABD, but not a non‐PA‐binding mutant version, showed a severe reduction in root growth. Together, this study biochemically characterizes the PA–SnRK2.4 interaction and shows that functionality of the SnRK2.4 PABD affects root development.     

Influencing the direct formation of ‘Janus’ particles in molecular dynamics simulations

The binary nucleation of phase-separated Lennard-Jones clusters was analysed under various system conditions using molecular dynamics simulations. The modified potential model provides a simple gateway to observe non-wetting behaviour and imitates the more complex interactions of non-miscible substances. Thus, not only the transition from ideally mixed clusters to so-called ‘Janus’ particles, but also the structural aspects and dynamic formation processes of nanoscopic droplets are directly observable from the gas phase. Various shapes and sizes of these inhomogeneous clusters have been found via simple tuning of system parameters. From this analysis, we gained further insight into the direct formation of ‘Janus’ particles from the gas phase.     

Odourant dominance in olfactory mixture processing: what makes a strong odourant?

The question of how animals process stimulus mixtures remains controversial as opposing views propose that mixtures are processed analytically, as the sum of their elements, or holistically, as unique entities different from their elements. Overshadowing is a widespread phenomenon that can help decide between these alternatives. In overshadowing, an individual trained with a binary mixture learns one element better at the expense of the other. Although element salience (learning success) has been suggested as a main explanation for overshadowing, the mechanisms underlying this phenomenon remain unclear. We studied olfactory overshadowing in honeybees to uncover the mechanisms underlying olfactory-mixture processing. We provide, to our knowledge, the most comprehensive dataset on overshadowing to date based on 90 experimental groups involving more than 2700 bees trained either with six odourants or with their resulting 15 binary mixtures. We found that bees process olfactory mixtures analytically and that salience alone cannot predict overshadowing. After normalizing learning success, we found that an unexpected feature, the generalization profile of an odourant, was determinant for overshadowing. Odourants that induced less generalization enhanced their distinctiveness and became dominant in the mixture. Our study thus uncovers features that determine odourant dominance within olfactory mixtures and allows the referring of this phenomenon to differences in neural activity both at the receptor and the central level in the insect nervous system.     

Divergent evolution of a bifunctional de novo protein

Primordial proteins, the evolutionary ancestors of modern sequences, are presumed to have been minimally active and nonspecific. Following eons of selective pressure, these early progenitors evolved into highly active and specific proteins. While evolutionary trajectories from poorly active and multifunctional generalists toward highly active specialists likely occurred many times in evolutionary history, such pathways are difficult to reconstruct in natural systems, where primordial sequences are lost to time. To test the hypothesis that selection for enhanced activity leads to a loss of promiscuity, we evolved a de novo designed bifunctional protein. The parental protein, denoted Syn‐IF, was chosen from a library of binary patterned 4‐helix bundles. Syn‐IF was shown previously to rescue two different auxotrophic strains of E. coli: ΔilvA and Δfes. These two strains contain deletions for proteins with very different biochemical functions; IlvA is involved in isoleucine biosynthesis, while Fes is involved in iron assimilation. In two separate experiments, Syn‐IF, was evolved for faster rescue of either ΔilvA or Δfes. Following multiple rounds of mutagenesis, two new proteins were selected, each capable of rescuing the selected function significantly faster than the parental protein. In each case, the evolved protein also lost the ability to rescue the unselected function. In both evolutionary trajectories, the original bifunctional generalist was evolved into a monofunctional specialist with enhanced activity.     

云纹石斑鱼幼鱼血清生化指标对低温胁迫的响应

设置9、13、17℃3个温度梯度(17℃对照组),对云纹石斑鱼(Epinephelus moara)幼鱼进行7 d的胁迫实验,检测了血清中生化指标和代谢酶活力。结果表明:血清总蛋白(TP)和葡萄糖(GLU)含量在温度骤降后虽有变化,但无显著性差异(P0.05);血清中甘油三酯(TG)和肌酐(CREA)含量在水温骤降至9℃和13℃,7 d后与胁迫前比较均差异显著(P0.05);代谢酶指标中碱性磷酸酶(AKP)、谷草转氨酶(GOT)、谷丙转氨酶(GPT)和乳酸脱氢酶(LDH)的活力,随低温胁迫的强度和胁迫时间的延长活力都呈上升趋势,且实验结束时均与胁迫前差异显著(P0.05);乳酸脱氢酶活力在实验结束时各低温胁迫实验组之间也有显著性差异(P0.05);研究认为,在耐受温度范围的下限云纹石斑鱼幼鱼遭受低温骤降胁迫时,短期内血清生化指标不发生显著变化;幼鱼通过血清代谢酶活力的升高来响应低温胁迫,以提高抗应激能力;但停食会导致免疫力和抗氧化能力下降,因此实际生产中仍应降低胁迫强度和缩短胁迫时间。     

Trace Metal Mixture Toxicity in Aquatic Organism Reviewed from a Biotoxicity Perspective

Biotoxicity of individual metals is well investigated but that of metal mixture, an environmental reality, in the developing metal mixture, is relatively obscure. Experimental evidences had shown that this mixture could give rise to combined effects that were different from the effect of metals one by one. This review provides an overview of recent research on metal mixture toxicity and the methods employed to predict their toxic combined effects. The two established reference models, the concentration-addition model and the independent-addition model, were used for evaluating the combined effect from the biological activities of the metal mixtures. While the reference models had provided reasonable tools for analyzing the combined effects, the actual predictions for binary metal mixtures showed often somewhat less than additive combined effects compared to what has been observed. As the metal bioavailability is oriented by several environmental factors as well as the toxicodynamics of metals is highly compound-specific, the non-interactive combined effects may be confused with different processes of the interactions. Thus, for improving the predictability of combined effects in metal mixture toxicity, numerous qualitative and quantitative analysis are required for the processes governing the toxicokinetics and dynamics of metals in aquatic organisms.     

Combined arginine and ascorbic acid treatment induces apoptosis in the hepatoma cell line HA22T/VGH and changes in redox status involving the pentose phosphate pathway and reactive oxygen and nitrogen species

Arginine is a physiological substrate for nitric oxide synthase to generate nitric oxide (NO), which can influence tumor cell survival, while ascorbic acid is selectively toxic for cancer cells. This study explored the effect of an arginine/ascorbic acid combination on human cancer cell lines. The hepatoma cell line HA22T/VGH was the most sensitive of the tested cells to combination treatment. A combination of 5.74 mM of arginine and 0.57 mM of ascorbic acid induced HA22T/VGH cell death through apoptosis and an increase in levels of reactive oxygen species and NO, as well as its stable products NO₂⁻ and NO₃⁻. The combination also reduced the activity of glucose-6-phosphate dehydrogenase, 6-phosphogluconate dehydrogenase, and transaldolase in the pentose phosphate pathway, a major mechanism for producing NADPH, resulting in a marked decrease in intracellular NADPH levels. A dramatic decrease in intracellular glutathione (GSH) levels, a decrease in the mitochondrial membrane potential, ATP depletion and release of cytochrome c were also seen. Caspase-9 and caspase-3 were activated, apoptotic protein Bax expression increased and the expression of the anti-apoptotic proteins Bcl-2 and Bcl-xL decreased. These results suggest that this combination induced HA22T/VGH cell death by interfering with redox state regulation by a reduction in pentose phosphate pathway activity and increasing oxidative and nitrosative stress.     

Quantitative analysis of dynamic protein-protein interactions in planta by a floated-leaf luciferase complementation imaging (FLuCI) assay using binary Gateway vectors

Dynamic protein-protein interactions are essential in all cellular and developmental processes. Protein-fragment complementation assays allow such protein-protein interactions to be investigated in vivo. In contrast to other protein-fragment complementation assays, the split-luciferase (split-LUC) complementation approach facilitates dynamic and quantitative in vivo analysis of protein interactions, as the restoration of luciferase activity upon protein-protein interaction of investigated proteins is reversible. Here, we describe the development of a floated-leaf luciferase complementation imaging (FLuCI) assay that enables rapid and quantitative in vivo analyses of protein interactions in leaf discs floating on a luciferin infiltration solution after transient expression of split-LUC-labelled interacting proteins in Nicotiana benthamiana. We generated a set of eight Gateway-compatible split-LUC destination vectors, enabling fast, and almost fail-safe cloning of candidate proteins to the LUC termini in all possible constellations. We demonstrate their functionality by visualizing the well-established homodimerization of the 14-3-3 regulator proteins. Quantitative interaction analyses of the molybdenum co-factor biosynthesis proteins CNX6 and CNX7 show that the luciferase-based protein-fragment complementation assay allows direct real-time monitoring of absolute values of protein complex assembly. Furthermore, the split-LUC assay is established as valuable tool to investigate the dynamics of protein interactions by monitoring the disassembly of actin filaments in planta. The new Gateway-compatible split-LUC destination vector system, in combination with the FLuCI assay, provides a useful means to facilitate quantitative analyses of interactions between large numbers of proteins constituting interaction networks in plant cells.     

Photosynthetic carbon partitioning and lipid production in the oleaginous microalga Pseudochlorococcum sp. (Chlorophyceae) under nitrogen-limited conditions

Photosynthetic carbon partitioning into starch and neutral lipid was investigated in the oleaginous green microalga Pseudochlorococcum sp. When grown under low light and nitrogen-replete conditions, the algal cells possessed a basal level of starch. When grown under high light and nitrogen-limited conditions, starch synthesis was transiently up-regulated. After nitrogen depletion, starch content decreased while neutral lipid rapidly increased to 52.1% of cell dry weight, with a maximum neutral lipid productivity of 0.35 g L⁻¹ D⁻¹. These results suggest that Pseudochlorococcum used starch as a primary carbon and energy storage product. As nitrogen was depleted for an extended period of time, cells shift the carbon partitioning into neutral lipid as a secondary storage product. Partial inhibition of starch synthesis and degradation enzymes resulted in a decrease in neutral lipid content, indicating that conversion of starch to neutral lipid may contribute to overall neutral lipid accumulation. Biotechnological application of Pseudochlorococcum sp. as a production strain for biofuel was assessed.     

From phenotype to genotype: a Bayesian solution

The study of biological systems commonly depends on inferring the state of a 'hidden' variable, such as an underlying genotype, from that of an 'observed' variable, such as an expressed phenotype. However, this cannot be achieved using traditional quantitative methods when more than one genetic mechanism exists for a single observable phenotype. Using a novel latent class Bayesian model, it is possible to infer the prevalence of different genetic elements in a population given a sample of phenotypes. As an exemplar, data comprising phenotypic resistance to six antimicrobials obtained from passive surveillance of Salmonella Typhimurium DT104 are analysed to infer the prevalence of individual resistance genes, as well as the prevalence of a genomic island known as SGI1 and its variants. Three competing models are fitted to the data and distinguished between using posterior predictive p-values to assess their ability to predict the observed number of unique phenotypes. The results suggest that several SGI1 variants circulate in a few fixed forms through the population from which our data were derived. The methods presented could be applied to other types of phenotypic data, and represent a useful and generic mechanism of inferring the genetic population structure of organisms.