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Perez de Souza, L.

Publications and source records attributed to Perez de Souza, L..

3 recordsLinked to original sources

Exploring the diversity of the CO2-concentrating mechanism (CCM) in different C4 subtypes

C4 plants have traditionally been classified into NADP-malic enzyme (NADP-ME), NAD-malic enzyme (NAD-ME) and PEP carboxykinase (PEPCK) subtypes based on the predominant C4-acid decarboxylating enzyme. To investigate the relative contributions of malate and aspartate to C4-pathway fluxes in each subtype, we performed 13CO2 pulse and pulse-chase labelling experiments on four C4 grass species: Zea mays and Setaria viridis (NADP-ME), Panicum miliaceum (NAD-ME) and Megathyrsus maximus (PEPCK). Only a proportion (8-50%) of the total malate pool in the leaves is photosynthetically active whereas essentially all of the aspartate pool is photosynthetically active. Estimates of metabolic fluxes indicate that approximately two thirds of the C4 pathway flux is via malate in Z. mays and the remaining third via aspartate, while in S. viridis 50% of the flux is via malate and 50% via aspartate. In P. miliaceum and M. maximus, 91% and 85% of the flux is via aspartate and the remaining 5% and 15% via malate, respectively. The results reveal greater complexity of C4 pathway fluxes than is usually represented in textbook diagrams, and demonstrate the feasibility of using non-radioactive 13CO2 in pulse-chase labelling experiments to study C4 photosynthesis and to detect C4 pathway fluxes in C3 plants engineered to perform C4 photosynthesis. Highlight StatementPhotosynthetic fluxes in C4 species are more complex than most textbook models show, with malate and aspartate both carrying C4 cycle fluxes in all three subtypes (NADP-ME, NAD-ME and PEPCK).

plant biology↗

MetPlast: an R package to evaluate Metabolic Plasticity using Information Theory statistical framework

MetPlast, is an R package that provides the functionalities necessary to analyze biological samples metabolic plasticity. This package takes advantage of the statistical framework provided by the Information Theory to quantify and defined metabolic plasticity parameters. Using previous implemented formula based on Shannon entropy we automatize the calculation and visualization of a set of metabolic plasticity indexes including metabolic diversity, metabolome specialization, and metabolite specialization. We use a publicly available metabolic data set on tomato domestication to demonstrate the power of the present tool to evaluate changes in metabolic plasticity parameters. Thus, MetPlast represents a new and invaluable member of the computational metabolomics toolbox, that will certainly help scientists to unveil hidden information in cell metabolomic landscape. Availability and implementationFreely available at https://github.com/danlucio86/MetPlast

bioinformatics↗

Genome-wide association studies of seed metabolites identify loci controlling specialized metabolites in Arabidopsis thaliana

Plants synthesize specialized metabolites to facilitate environmental and ecological interactions. During evolution, plants diversified in their potential to synthesize these metabolites. Quantitative differences in metabolite levels of natural Arabidopsis thaliana accessions can be employed to unravel the genetic basis for metabolic traits using genome-wide association studies (GWAS). Here, we performed metabolic GWAS (mGWAS) on seeds of a panel of 315 A. thaliana natural accessions, including the reference genotypes C24 and Col-0, for polar and semi-polar seed metabolites using untargeted ultra-performance liquid chromatography-mass spectrometry. As a complementary approach, we performed quantitative trait locus (QTL) mapping of near-isogenic introgression lines between C24 and Col-0 for specific seed specialized metabolites. Besides common QTL between seeds and leaves, GWAS revealed seed-specific QTL for specialized metabolites indicating differences in the genetic architecture of seeds and leaves. In seeds, aliphatic methylsulfinylalkyl and methylthioalkyl glucosinolates associated with the GS-ALK and GS-OHP locus on chromosome 4 containing alkenyl hydroxyalkyl producing 2 (AOP2) and 3 (AOP3) and/or with the GS-ELONG locus on chromosome 5 containing methylthioalkyl malate synthase (MAM1) and MAM3. We detected two unknown sulfur-containing compounds that were also mapped to these loci. In GWAS, some of the annotated flavonoids (kaempferol 3-O-rhamnoside-7-O-rhamnoside, quercetin 3-O-rhamnoside-7-O-rhamnoside) were mapped to transparent testa 7 (AT5G07990), encoding a cytochrome P450 75B1 monooxygenase. Three additional mass signals corresponding to quercetin-containing flavonols were mapped to UGT78D2 (AT5G17050). The association of the loci and associating metabolic features were functionally verified in knockdown mutant lines. By performing GWAS and QTL mapping, we were able to leverage variation of natural populations and parental lines to study seed specialized metabolism. The GWAS data set generated here is a high-quality resource that can be interrogated in further studies.

plant biology↗