89 resultados para Functional-structural Plant Modelling


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Plant resistance proteins (R proteins) recognize corresponding pathogen avirulence (Avr) proteins either indirectly through detection of changes in their host protein targets or through direct R-Avr protein interaction. Although indirect recognition imposes selection against Avr effector function, pathogen effector molecules recognized through direct interaction may overcome resistance through sequence diversification rather than loss of function. Here we show that the flax rust fungus AvrLS67 genes, whose products are recognized by the L5, L6, and L7 R proteins of flax, are highly diverse, with 12 sequence variants identified from six rust strains. Seven AvrL567 variants derived from Avr alleles induce necrotic responses when expressed in flax plants containing corresponding resistance genes (R genes), whereas five variants from avr alleles do not. Differences in recognition specificity between AvA567 variants and evidence for diversifying selection acting on these genes suggest they have been involved in a gene-specific arms race with the corresponding flax R genes. Yeast two-hybrid assays indicate that recognition is based on direct R-Avr protein interaction and recapitulate the interaction specificity observed in planta. Biochemical analysis of Escherichia coli-produced AvrL567 proteins shows that variants that escape recognition nevertheless maintain a conserved structure and stability, suggesting that the amino acid sequence differences directly affect the R-Avr protein interaction. We suggest that direct recognition associated with high genetic diversity at corresponding R and Avr gene loci represents an alternative outcome of plant-pathogen coevolution to indirect recognition associated with simple balanced polymorphisms for functional and nonfunctional R and Avr genes.

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Self-incompatibility RNases (S-RNases) are an allelic series of style glycoproteins associated with rejection of self-pollen in solanaceous plants. The nucleotide sequences of S-RNase alleles from several genera have been determined, but the structure of the gene products has only been described for those from Nicotiana alata. We report on the N-glycan structures and the disulfide bonding of the S-3-RNase from wild tomato (Lycopersicon peruvianum) and use this and other information to construct a model of this molecule. The S-3-RNase has a single N-glycosylation site (Asn-28) to which one of three N-glycans is attached. S-3-RNase has seven Cys residues; six are involved in disulfide linkages (Cys-16-Cys-21, Cys-46-Cys-91, and Cys-166-Cys-177), and one has a free thiol group (Cys-150). The disulfide-bonding pattern is consistent with that observed in RNase Rh, a related RNase for which radiographic-crystallographic information is available. A molecular model of the S-3-RNase shows that four of the most variable regions of the S-RNases are clustered on one surface of the molecule. This is discussed in the context of recent experiments that set out to determine the regions of the S-RNase important for recognition during the self-incompatibility response.

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Human N-acetyltransferase type 1 (NAT1) catalyses the N- or O-acetylation of various arylamine and heterocyclic amine substrates and is able to bioactivate several known carcinogens. Despite wide inter-individual variability in activity, historically, NAT1 was considered to be monomorphic in nature. However, recent reports of allelic variation at the NAT1 locus suggest that it may be a polymorphically expressed enzyme. In the present study, peripheral blood mononuclear cell NAT1 activity in 85 individuals was found to be bimodally distributed with approximately 8% of the population being slow acetylators. Subsequent sequencing of the individuals having slow acetylator status showed all to have either a (CT)-T-190 or G(560)A base substitution located in the protein encoding region of the NAT1 gene. The (CT)-T-190 base substitution changed a highly conserved Arg(64), which others have shown to be essential for fully functional NAT1 protein. The (CT)-T-190 mutation has not been reported previously and we have named it NAT1*17. The G(560)A mutation is associated with the base substitutions previously observed in the NAT1*10 allele and this variant (NAT1*14) encodes for a protein with reduced acetylation capacity. A novel method using linear PCR and dideoxy terminators was developed for the detection of NAT1*14 and NAT1*17. Neither of these variants was found in the rapid acetylator population. We conclude that both the (CT)-T-190 (NAT1*17) and G(560)A (NAT1*14) NAT1 structural variants are involved in a distinct NAT1 polymorphism. Because NAT1 can bioactivate several carcinogens, this polymorphism may have implications for cancer risk in individual subjects. (C) 1998 Chapman & Hall Ltd.

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Traditional field sampling approaches for ecological studies of restored habitat can only cover small areas in detail, con be time consuming, and are often invasive and destructive. Spatially extensive and non-invasive remotely sensed data can make field sampling more focused and efficient. The objective of this work was to investigate the feasibility and accuracy of hand-held and airborne remotely sensed data to estimate vegetation structural parameters for an indicator plant species in a restored wetland. High spatial resolution, digital, multispectral camera images were captured from an aircraft over Sweetwater Marsh (San Diego County, California) during each growing season between 1992-1996. Field data were collected concurrently, which included plant heights, proportional ground cover and canopy architecture type, and spectral radiometer measurements. Spartina foliosa (Pacific cordgrass) is the indicator species for the restoration monitoring. A conceptual model summarizing the controls on the spectral reflectance properties of Pacific cordgrass was established. Empirical models were developed relating the stem length, density, and canopy architecture of cordgrass to normalized-difference-vegetation-index values. The most promising results were obtained from empirical estimates of total ground cover using image data that had been stratified into high, middle, and low marsh zones. As part of on-going restoration monitoring activities, this model is being used to provide maps of estimated vegetation cover.