Christine Girousse

Source-to-sink transport of sugar and regulation by environmental factors

Source-to-sink transport of sugar is one of the major determinants of plant growth and relies on the efficient and controlled distribution of sucrose (and some other sugars such as raffinose and polyols) across plant organs through the phloem. However, sugar transport through the phloem can be affected by many environmental factors that alter source/sink relationships. In this paper, we summarize current knowledge about the phloem transport mechanisms and review the effects of several abiotic (water and salt stress, mineral deficiency, CO2, light, temperature, air, and soil pollutants) and biotic (mutualistic and pathogenic microbes, viruses, aphids, and parasitic plants) factors. Concerning abiotic constraints, alteration of the distribution of sugar among sinks is often reported, with some sinks as roots favored in case of mineral deficiency. Many of these constraints impair the transport function of the phloem but the exact mechanisms are far from being completely known. Phloem integrity can be disrupted (e.g., by callose deposition) and under certain conditions, phloem transport is affected, earlier than photosynthesis. Photosynthesis inhibition could result from the increase in sugar concentration due to phloem transport decrease. Biotic interactions (aphids, fungi, viruses…) also affect crop plant productivity. Recent breakthroughs have identified some of the sugar transporters involved in these interactions on the host and pathogen sides. The different data are discussed in relation to the phloem transport pathways. When possible, the link with current knowledge on the pathways at the molecular level will be highlighted.

Water Deficit-Induced Changes in Concentrations in Proline and Some Other Amino Acids in the Phloem Sap of Alfalfa

Changes in amino acid composition of alfalfa (Medicago sativa L.) phloem sap were studies in response to a water deficit. Sap was collected by stylectomy. As the leaf water potential ([psi]) decreased from -0.4 to -2.0 MPa, there was significant increase of the total amino acid concentration, due to that of some amino acids: proline, valine, isoleucine, leucine, glutamic acid, aspartic acid, and threonine. Asparagine concentration, which is the main amino acid assayed in the phloem sap of alfalfa (it accounts for 70% of the total content), did not vary with the plant water status. The other amino acid concentrations remained stable as [psi] varied; in particular, [gamma]-amino butyric acid concentration remained unchanged, whereas it varied in response to wounding. The more striking change in the sieve tubes was the accumulation of proline, which was observed below a [psi] threshold value of about -0.9 MPa (concentration x60 for a decrease of [psi] from -0.9 to -2.0 MPa). The role of such changes in phloem sap amino acid concentration in osmotic adjustment of growing tissues is discussed.

Compatible plant-aphid interactions: How aphids manipulate plant responses

To access phloem sap, aphids have developed a furtive strategy, their stylets progressing towards sieve tubes mainly through the apoplasmic compartment. Aphid feeding requires that they overcome a number of plant responses, ranging from sieve tube occlusion and activation of phytohormone-signalling pathways to expression of anti-insect molecules. In addition to bypassing plant defences, aphids have been shown to affect plant primary metabolism, which could be a strategy to improve phloem sap composition in nutrients required for their growth. During compatible interactions, leading to successful feeding and reproduction, aphids cause alterations in their host plant, including morphological changes, modified resource allocation and various local as well as systemic symptoms. Repeated salivary secretions injected from the first probe in the epidermal tissue up to ingestion of sieve-tube sap may play a crucial role in the compatibility between the aphid and the plant.

Phloem sap intricacy and interplay with aphid feeding

Aphididae feed upon the plant sieve elements (SE), where they ingest sugars, nitrogen compounds and other nutrients. For ingestion, aphid stylets penetrate SE, and because of the high hydrostatic pressure in SE, phloem sap exudes out into the stylets. Severing stylets to sample phloem exudates (i.e. stylectomy) has been used extensively for the study of phloem contents. Alternative sampling techniques are spontaneous exudation upon wounding that only works in a few plant species, and the popular EDTA-facilitated exudation technique. These approaches have allowed fundamental advances on the understanding of phloem sap composition and sieve tube physiology, which are surveyed in this review. A more complete picture of metabolites, ions, proteins and RNAs present in phloem sap is now available, which has provided large evidence for the phloem role as a signalling network in addition to its primary role in partitioning of photo-assimilates. Thus, phloem sap sampling methods can have remarkable applications to analyse plant nutrition, physiology and defence responses. Since aphid behaviour is suspected to be affected by phloem sap quality, attempts to manipulate phloem sap content were recently undertaken based on deregulation in mutant plants of genes controlling amino acid or sugar content of phloem sap. This opens up new strategies to control aphid settlement on a plant host.

Aphid Infestation Causes Different Changes in Carbon and Nitrogen Allocation in Alfalfa Stems as Well as Different Inhibitions of Longitudinal and Radial Expansion

Alfalfa (Medicago sativa) stem elongation is strongly reduced by a pea aphid (Acyrthosiphon pisum Harris) infestation. As pea aphid is a phloem feeder that does not transmit virus or toxins, assimilate withdrawal is generally considered as the main mechanism responsible for growth reduction. Using a kinematic analysis, we investigated the spatial distributions of relative elemental growth rates of control and infested alfalfa stems. The water, carbon, and nitrogen contents per unit stem length were measured along the growth zone. Deposition rates and growth-sustaining fluxes were estimated from these patterns. Severe short-term aphid infestation (200 young adults over a 24-h period) induced a strong and synchronized reduction in rates of elongation and of water and carbon deposition. Reduced nitrogen content and associated negative nitrogen deposition rates were observed in some parts of the infested stems, especially in the apex. This suggested a mobilization of nitrogen from the apical part of the growth zone, converted from a sink tissue into a source tissue by aphids. Calculation of radial growth rates suggested that aphid infestation led to a smaller reduction in radial expansion than in elongation. Together with earlier observations of long-lasting effects of a short-term infestation, this supports the hypothesis that in addition to nutrient withdrawal, a thigmomorphogenesis-like mechanism is involved in the effect of aphid infestation on stem growth.

Proteomic and morphological analysis of early stages of wheat grain development

The identification of 249 proteins in the first 2 wks of wheat grain development enabled the chronological description of the early processes of grain formation. Cell division involved expression of the enzymes and proteins of the cytoskeleton and structure, DNA repair and replication enzymes and cellular metabolism enzymes (synthesis of amino acids, cell wall initiation, carbon fixation and energy production, cofactors and vitamins) with a peak expression at 125°Cday (degrees day after anthesis). After the first synthesis of amino acids, protein transport mechanisms, translation signals, sugar metabolism (polymerization of protein) and stress/defence proteins were activated with stable expression between 150 and 280°Cday. Proteins responsible for folding and degradation, including different subunits of proteasome, were highly expressed at 195°Cday. Proteins associated with starch granules (GBSS type 1) were present at the beginning of grain formation and increased regularly up to 280°Cday. Heat shock proteins (HSP70, 80, 90) were expressed throughout the early grain development stages.

Proteomic analysis of peripheral layers during wheat (Triticum aestivum L.) grain development

Grains of hexaploid wheat, Triticum aestivum (cv. Récital), were collected at 15 stages of development, from anthesis to physiological maturity, 0–700°C days (degree days after anthesis). Two hundred and seven proteins of grain peripheral layers (inner pericarp, hyaline, testa and aleurone layer) were identified by 2‐DE, MALDI‐TOF MS and data mining, then were classified in 16 different functional categories. Study of the protein expression over time allowed identification of five main profiles and four distinct phases of development. Composite expression curves indicated that there was a shift from metabolic processes, translation, transcription and ATP interconversion towards storage and defence processes. Protein synthesis, protein turnover, signal transduction, membrane transport and biosynthesis of secondary metabolites were the mediating functions of this shift. A picture of the dynamic processes taking place in peripheral layers during grain development was obtained in this study. It should further help in the construction of proteome reference maps for the developing peripheral layers.

Down-regulation of the TaGW2 gene by RNA interference results in decreased grain size and weight in wheat

For important food crops such as wheat and rice, grain yield depends on grain number and size. In rice (Oryza sativa), GW2 was isolated from a major quantitative trait locus for yield and encodes an E3 RING ligase that negatively regulates grain size. Wheat (Triticum aestivum) has TaGW2 homologues in the A, B, and D genomes, and polymorphisms in TaGW2-A were associated with grain width. Here, to investigate TaGW2 function, RNA interference (RNAi) was used to down-regulate TaGW2 transcript levels. Transgenic wheat lines showed significantly decreased grain size-related dimensions compared with controls. Furthermore, TaGW2 knockdown also caused a significant reduction in endosperm cell number. These results indicate that TaGW2 regulates grain size in wheat, possibly by controlling endosperm cell number. Wheat and rice GW2 genes thus seem to have divergent functions, with rice GW2 negatively regulating grain size and TaGW2 positively regulating grain size. Analysis of transcription of TaGW2 homoeologues in developing grains suggested that TaGW2-A and -D act in both the division and late grain-filling phases. Furthermore, biochemical and molecular analyses revealed that TaGW2-A is a functional E3 RING ubiquitin ligase with nucleocytoplasmic subcellular partitioning. A functional nuclear export sequence responsible for TaGW2-A export from the nucleus to the cytosol and retention in the nucleolus was identified. Therefore, these results show that TaGW2 acts in the regulation of grain size and may provide an important tool for enhancement of grain yield.

Transcriptional profile analysis of E3 ligase and hormone-related genes expressed during wheat grain development

BackgroundWheat grains are an important source of food, stock feed and raw materials for industry, but current production levels cannot meet world needs. Elucidation of the molecular mechanisms underlying wheat grain development will contribute valuable information to improving wheat cultivation. One of the most important mechanisms implicated in plant developmental processes is the ubiquitin-proteasome system (UPS). Among the different roles of the UPS, it is clear that it is essential to hormone signaling. In particular, E3 ubiquitin ligases of the UPS have been shown to play critical roles in hormone perception and signal transduction.ResultsA NimbleGen microarray containing 39,179 UniGenes was used to study the kinetics of gene expression during wheat grain development from the early stages of cell division to the mid-grain filling stage. By comparing 11 consecutive time-points, 9284 differentially expressed genes were identified and annotated during this study. A comparison of the temporal profiles of these genes revealed dynamic transcript accumulation profiles with major reprogramming events that occurred during the time intervals of 80-120 and 220-240°Cdays. The list of the genes expressed differentially during these transitions were identified and annotated. Emphasis was placed on E3 ligase and hormone-related genes. In total, 173 E3 ligase coding genes and 126 hormone-related genes were differentially expressed during the cell division and grain filling stages, with each family displaying a different expression profile.ConclusionsThe differential expression of genes involved in the UPS and plant hormone pathways suggests that phytohormones and UPS crosstalk might play a critical role in the wheat grain developmental process. Some E3 ligase and hormone-related genes seem to be up- or down-regulated during the early and late stages of the grain development.

Multimodel ensembles improve predictions of crop–environment–management interactions

A recent innovation in assessment of climate change impact on agricultural production has been to use crop multimodel ensembles (MMEs). These studies usually find large variability between individual models but that the ensemble mean (e-mean) and median (e-median) often seem to predict quite well. However, few studies have specifically been concerned with the predictive quality of those ensemble predictors. We ask what is the predictive quality of e-mean and e-median, and how does that depend on the ensemble characteristics. Our empirical results are based on five MME studies applied to wheat, using different data sets but the same 25 crop models. We show that the ensemble predictors have quite high skill and are better than most and sometimes all individual models for most groups of environments and most response variables. Mean squared error of e-mean decreases monotonically with the size of the ensemble if models are added at random, but has a minimum at usually 2-6 models if best-fit models are added first. Our theoretical results describe the ensemble using four parameters: average bias, model effect variance, environment effect variance, and interaction variance. We show analytically that mean squared error of prediction (MSEP) of e-mean will always be smaller than MSEP averaged over models and will be less than MSEP of the best model if squared bias is less than the interaction variance. If models are added to the ensemble at random, MSEP of e-mean will decrease as the inverse of ensemble size, with a minimum equal to squared bias plus interaction variance. This minimum value is not necessarily small, and so it is important to evaluate the predictive quality of e-mean for each target population of environments. These results provide new information on the advantages of ensemble predictors, but also show their limitations.