Identification of calcium-dependent phospholipid-binding proteins in higher plant cells

AbstractCalcium-dependent phospholipid-binding proteins of apparent Mr 33 000 and 35 000 were isolated from suspension cultures of tomato cells. Two-dimensional gel electrophoresis showed the proteins to have isoelectric points of approx. 5.7 and 5.6, respectively. In the presence of calcium, both proteins bound to liposomes formed from a mixture of phosphatidylserine and phosphatidylcholine, but not to liposomes of phosphatidylcholine alone. Both proteins showed immunological similarities to previously characterized calcium-dependent phospholipid-binding proteins (annexins) from Torpedo marmorata and mammalian species. The protein of Mr 33 000 cross-reacted with three separate antisera raised to the annexin Torpedo calelectrin, whereas that of Mr 35 000 cross-reacted with antisera to the bovine annexins p68 and p32/34. We suggest that the two proteins may represent the first identification in higher plants of the annexin family of calcium-dependent phospholipid-binding proteins

Functional and informatics analysis enables glycosyltransferase activity prediction

The elucidation and prediction of how changes in a protein result in altered activities and selectivities remain a major challenge in chemistry. Two hurdles have prevented accurate family-wide models: obtaining (i) diverse datasets and (ii) suitable parameter frameworks that encapsulate activities in large sets. Here, we show that a relatively small but broad activity dataset is sufficient to train algorithms for functional prediction over the entire glycosyltransferase superfamily 1 (GT1) of the plant Arabidopsis thaliana. Whereas sequence analysis alone failed for GT1 substrate utilization patterns, our chemical–bioinformatic model, GT-Predict, succeeded by coupling physicochemical features with isozyme-recognition patterns over the family. GT-Predict identified GT1 biocatalysts for novel substrates and enabled functional annotation of uncharacterized GT1s. Finally, analyses of GT-Predict decision pathways revealed structural modulators of substrate recognition, thus providing information on mechanisms. This multifaceted approach to enzyme prediction may guide the streamlined utilization (and design) of biocatalysts and the discovery of other family-wide protein functions

Coexpression of Neighboring Genes in the Genome of Arabidopsis thaliana

Large-scale analyses of expression data of eukaryotic organisms are now becoming increasingly routine. The data sets are revealing interesting and novel patterns of genomic organization, which provide insight both into molecular evolution and how structure and function of a genome interrelate. Our study investigates, for the first time, how genome organization affects expression of a gene in the Arabidopsis genome. The analyses show that neighboring genes are coexpressed. This pattern has been found for all eukaryotic genomes studied so far, but as yet, it remains unclear whether it is due to selective or nonselective influences. We have investigated reasons for coexpression of neighboring genes in Arabidopsis, and our evidence suggests that orientation of gene pairs plays a significant role, with potential sharing of regulatory elements in divergently transcribed genes. Using the data available in the KEGG database, we find evidence that genes in the same pathway are coexpressed, although this is not a major cause for the coexpression of neighboring genes