The function of glutaredoxin GRXS15 is required for lipoyl-dependent dehydrogenases in mitochondria.

Iron-sulfur (Fe-S) clusters are ubiquitous cofactors in all life and are used in a wide array of diverse biological processes, including electron transfer chains and several metabolic pathways. Biosynthesis machineries for Fe-S clusters exist in plastids, the cytosol, and mitochondria. A single monothiol glutaredoxin (GRX) is involved in Fe-S cluster assembly in mitochondria of yeast and mammals. In plants, the role of the mitochondrial homolog GRXS15 has only partially been characterized. Arabidopsis (Arabidopsis thaliana) grxs15 null mutants are not viable, but mutants complemented with the variant GRXS15 K83A develop with a dwarf phenotype similar to the knockdown line GRXS15amiR. In an in-depth metabolic analysis of the variant and knockdown GRXS15 lines, we show that most Fe-S cluster-dependent processes are not affected, including biotin biosynthesis, molybdenum cofactor biosynthesis, the electron transport chain, and aconitase in the tricarboxylic acid (TCA) cycle. Instead, we observed an increase in most TCA cycle intermediates and amino acids, especially pyruvate, glycine, and branched-chain amino acids (BCAAs). Additionally, we found an accumulation of branched-chain α-keto acids (BCKAs), the first degradation products resulting from transamination of BCAAs. In wild-type plants, pyruvate, glycine, and BCKAs are all metabolized through decarboxylation by mitochondrial lipoyl cofactor (LC)-dependent dehydrogenase complexes. These enzyme complexes are very abundant, comprising a major sink for LC. Because biosynthesis of LC depends on continuous Fe-S cluster supply to lipoyl synthase, this could explain why LC-dependent processes are most sensitive to restricted Fe-S supply in grxs15 mutants.

Environmental and physiological effects on grouping of drought-tolerant and susceptible rice varieties related to rice (Oryza sativa) root hydraulics under drought.

Background and Aims Root hydraulic limitations (i.e. intra-plant restrictions to water movement) may be related to crop performance under drought, and groupings in the hydraulic function of drought-tolerant and drought-susceptible rice (Oryza sativa) varieties have been previously reported. This study aimed to better understand the environmental and physiological relationships with rice root hydraulics under drought. Methods Xylem sap bleeding rates in the field (gsap g-1shoot) were measured on seasonal and diurnal time frames, during which time environmental conditions were monitored and physiological measurements were conducted. Complementary experiments on the effects of vapour pressure deficit (VPD) on root hydraulic conductivity and on transpiration rates of de-rooted tillers were conducted in growth chambers. Key Results The diurnal effects on bleeding rate were more closely related to irradiance than VPD, and VPD effects on root hydraulic conductivity measured on 21-day-old plants were due to effects on plant growth including root surface area, maximum root depth and root:shoot ratio. Leaf osmotic potential was related to the grouping of drought-tolerant and drought-susceptible varieties in rice root hydraulics, and these groupings were independent of differences in phenology. Low single-tiller bleeding rates were observed under high evapo-transpirational demand, higher bleeding rates were observed at more negative leaf osmotic potentials in drought-susceptible varieties, and drought-tolerant and susceptible varieties differed in the VPD-induced increase in transpiration rates of de-rooted tillers. Low root suberin amounts in some of the drought-susceptible varieties may have resulted in higher ion transport, as evidenced by higher sap K+ concentration and higher bleeding rates in those varieties. Conclusions These results provide evidence of the environmental effects on shoots that can influence root hydraulics. The consistent groupings of drought-tolerant and susceptible varieties suggest that traits affecting plant osmotic status may regulate root hydraulic response to drought in rice.

Parcellation-Free prediction of task fMRI activations from dMRI tractography.

The relationship between brain structure and function plays a crucial role in cognitive and clinical neuroscience. We present a supervised machine learning based approach that captures this relationship by predicting the spatial extent of activations that are observed with task based functional Magnetic Resonance Imaging (fMRI) from the local white matter connectivity, as reflected in diffusion MRI (dMRI) tractography. In particular, we explore three different feature representations of local connectivity patterns that do not require a pre-defined parcellation of cortical and subcortical structures. Instead, they employ cluster-based Bag of Features, Gaussian Mixture Models, and Fisher vectors. We demonstrate that our framework can be used to test the statistical significance of structure-function relationships, compare it to parcellation-based and group-average benchmarks, and propose an algorithm for visualizing our chosen feature representations that permits a neuroanatomical interpretation of our results.