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Biomedical subjects

L Legendre

Publications and source records attributed to L Legendre.

3 recordsLinked to original sources

Evidence for participation of GTP-binding proteins in elicitation of the rapid oxidative burst in cultured soybean cells.

GTP-binding proteins have been shown to serve as second messengers in the transduction of hormone signals across animal cell plasma membranes. We present here three lines of evidence to demonstrate that GTP-binding proteins are also involved in the elicitation of the defense response of cultured soybean cells. First, the antigen-binding fragment (Fab) of an antibody that specifically recognizes GTP-binding proteins in plants and animals was delivered into soybean cells using a non-destructive biotin-mediated delivery technique developed previously. Internalization of this Fab enhanced up to 10-fold the rapid oxidative burst induced by elicitor molecules, whereas internalization of its heat-denatured counterpart or unrelated proteins had no effect. Because the antibody recognizes a protein of molecular mass approximately 45 kDa in soybean cell membranes that is protected from ADP-ribosylation by GTP gamma S (guanosine 5'-O-(thiotriphosphate), we propose the 45-kDa GTP-binding protein is responsible for these effects. Second, mastoparan, a specific activator of GTP-binding proteins, was shown to induce the defense-related oxidative burst in the absence of elicitor stimulation, thus mimicking an activated receptor as it is thought to do in mammalian systems. Finally, but admittedly less convincing, the A subunit of cholera toxin, an activator of certain stimulatory GTP-binding proteins (Gs), was found to weakly enhance the conventional elicitor-induced oxidative burst. Taken together, these data argue for the involvement of GTP-binding proteins in elicitor signal transduction in soybean cells.

Adenosine Diphosphate Ribose

Analyzing multivariate flow cytometric data in aquatic sciences.

Flow cytometry has recently been introduced in aquatic ecology. Its unique feature is to measure several optical characteristics simultaneously on a large number of cells. Until now, these data have generally been analyzed in simple ways, e.g., frequency histograms and bivariate scatter diagrams, so that the multivariate potential of the data has not been fully exploited. This paper presents a way of answering ecologically meaningful questions, using the multivariate characteristics of the data. In order to do so, the multivariate data are reduced to a small number of classes by clustering, which reduces the data to a categorical variable. Multivariate pairwise comparisons can then be performed among samples using these new data vectors. The test case presented in the paper forms a time series of observations from which the new method enables us to study on the temporal evolution of cell types.

Data Interpretation, Statistical