Auxin: regulation, action, and interaction.

Auxin conjugates are thought to play important roles as storage forms for the active plant hormone indole-3-acetic acid (IAA). In its free form, IAA comprises only up to 25% of the total amount of IAA, depending on the tissue and the plant species studied. The major forms of IAA conjugate are low molecular weight ester or amide forms, but there is increasing evidence of the occurrence of peptides and proteins modified by IAA. Since the discovery of genes and enzymes involved in synthesis and hydrolysis of auxin conjugates, much knowledge has been gained on the biochemistry and function of these compounds, but there is still much to discover. For example, recent work has shown that some auxin conjugate hydrolases prefer conjugates with longer-chain auxins such as indole-3-propionic acid and indole-3-butyric acid as substrate. Also, the compartmentation of these reactions in the cell or in tissues has not been resolved in great detail. The function of auxin conjugates has been mainly elucidated by mutant analysis in genes for synthesis or hydrolysis and a possible function for conjugates inferred from these results. In the evolution of land plants auxin conjugates seem to be connected with the development of certain traits such as embryo, shoot, and vasculature. Most likely, the synthesis of auxin conjugates was developed first, since it has been already detected in moss, whereas sequences typical of auxin conjugate hydrolases were found according to database entries first in moss ferns. The implications for the regulation of auxin levels in different species will be discussed.

Auxin conjugates: their role for plant development and in the evolution of land plants

In plants, reactive oxygen species and, more particularly, hydrogen peroxide (H2O2) play a dual role as toxic by-products of normal cell metabolism and as regulatory molecules in stress perception and signal transduction. Peroxisomal catalases are an important sink for photorespiratory H2O2. Using ATH1 Affymetrix microarrays, expression profiles were compared between control and catalase-deficient Arabidopsis (Arabidopsis thaliana) plants. Reduced catalase levels already provoked differences in nuclear gene expression under ambient growth conditions, and these effects were amplified by high light exposure in a sun simulator for 3 and 8 h. This genome-wide expression analysis allowed us to reveal the expression characteristics of complete pathways and functional categories during H2O2 stress. In total, 349 transcripts were significantly up-regulated by high light in catalase-deficient plants and 88 were down-regulated. From this data set, H2O2 was inferred to play a key role in the transcriptional up-regulation of small heat shock proteins during high light stress. In addition, several transcription factors and candidate regulatory genes involved in H2O2 transcriptional gene networks were identified. Comparisons with other publicly available transcriptome data sets of abiotically stressed Arabidopsis revealed an important intersection with H2O2-deregulated genes, positioning elevated H2O2 levels as an important signal within abiotic stress-induced gene expression. Finally, analysis of transcriptional changes in a combination of a genetic (catalase deficiency) and an environmental (high light) perturbation identified a transcriptional cluster that was strongly and rapidly induced by high light in control plants, but impaired in catalase-deficient plants. This cluster comprises the complete known anthocyanin regulatory and biosynthetic pathway, together with genes encoding unknown proteins.

/pdf/genome-wide-analysis-of-hydrogen-peroxide-regulated-gene-2gtwxj8spg.pdf

Genome-Wide Analysis of Hydrogen Peroxide-Regulated Gene Expression in Arabidopsis Reveals a High Light-Induced Transcriptional Cluster Involved in Anthocyanin Biosynthesis

Uridine diphosphate (UDP) glycosyltransferases (UGTs) mediate the transfer of glycosyl residues from activated nucleotide sugars to acceptor molecules (aglycones), thus regulating properties of the acceptors such as their bioactivity, solubility and transport within the cell and throughout the organism. A superfamily of over 100 genes encoding UGTs, each containing a 42 amino acid consensus sequence, has been identified in the model plant Arabidopsis thaliana. A phylogenetic analysis of the conserved amino acids encoded by these Arabidopsis genes reveals the presence of 14 distinct groups of UGTs in this organism. Genes encoding UGTs have also been identified in several other higher plant species. Very little is yet known about the regulation of plant UGT genes or the localization of the enzymes they encode at the cellular and subcellular levels. The substrate specificities of these UGTs are now beginning to be established and will provide a foundation for further analysis of this large enzyme superfamily as well as a platform for future biotechnological applications.

/pdf/higher-plant-glycosyltransferases-13b28i9o2g.pdf

Higher plant glycosyltransferases

https://www.cell.com/trends/plant-science/pdf/S1360-1385(05)00228-1.pdf

Plant secondary metabolism glycosyltransferases: the emerging functional analysis.

http://www.jbc.org/content/276/6/4350.full.pdf

Identification and Biochemical Characterization of anArabidopsis Indole-3-acetic Acid Glucosyltransferase

Biochemistry is an experimental science characterized by an analytical and quantitative approach. Methods for the analysis of quantitative data are essential tools for handling the results of many biochemical studies. Some approaches are relatively straightforward and familiar to the biochemical community; others are more specialized, and their use is consequently less common. This chapter provides an account of two principal approaches to quantitative data analysis: least-squares fitting and regularization methods. A short summary of the theoretical background of these two approaches is followed by extensive coverage of applications taken from diverse areas including: enzyme kinetics, ligand binding, analytical ultracentrifugation, circular dichroism (CD), and the pH dependence of biochemical reactions. The discussion covers the nature of mathematical modeling of systems, and emphasizes the importance of selection of an appropriate physical model to describe the data.


Keywords:

Algorithm;
Gaussian (or Normal) Distribution;
Global Fitting;
Least-squares Fit;
Model;
Numerical Integration;
Occam's Razor;
Parameters

Jim Hoggett

Papers

Identification and Biochemical Characterization of anArabidopsis Indole-3-acetic Acid Glucosyltransferase

Quantitative Analysis of Biochemical Data