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Biology subjects

Mur, L. A.

Publications and source records attributed to Mur, L. A..

2 recordsLinked to original sources

Metabolomic approaches highlight two mechanisms of accelerated grain filling in Mediterranean oat (Avena sativa L.) cultivars during drought.

Grain filling in cereals is complex process that determines the final grain yield and quality. Abiotic stresses can have major impact on grain filling. Oats (Avena sativa L.) is sensitive to drought which adversely affect yield and productivity. In this study, we characterised the grain filling responses of two Mediterranean oat cultivars Flega and Patones under severe drought. Grains from the top (older) and bottom (younger) spikelets of primary panicle were larger in size in response to drought, particularly in Patones, suggesting accelerated grain development. The metabolomes of source (sheath, flag leaf) and sink (developing grains) tissues were profiled to describe source-sink partitioning. In Patones, the developing grains showed increased sugars and amino acids which indicate accelerated grain filling. These were associated with elevated -linolenic acid levels in source tissues but decreased in developing grains under drought. There was also a significant decrease in C18 fatty acids (FA) and jasmonates (JA) derivatives in the developing grains which suggested a role for JA signalling in Patones with drought. Flega showed a different response, with accelerated flowering and enhanced energy metabolism in both source and sink organs. The accumulation of ophthalmic acid in grains of Flega and lower levels of reduced glutathione in source tissues suggested greater oxidative stress than Patones under drought may be driving the grain filling phenotype. This study suggests that oats cultivars can use -linolenic acid-linked signalling or oxidative events influences accelerated grain filling with drought. These could be important traits in developing oat cultivars that maintain yield in drought-prone environments. HighlightThe impact on drought in one tolerant and one susceptible oat cultivar was assessed at the grain filling stage. The drought tolerant cultivar, Patones, showed accelerated grain development which could be a strategy to escape drought. Metabolite mapping of flag leaves, sheath and grains of Flega suggested that alpha linolenic acid could be regulating the altered sink-source relationships. The drought susceptible cultivar, Metabolomics shifts in Flega suggested that oxidative stress accelerated flowering.

plant biology↗

DIMEdb: an integrated database and web service for metabolite identification in direct infusion mass spectrometery

MotivationMetabolomics involves the characterisation, identification, and quantification of small molecules (metabolites) that act as the reaction intermediates of biological processes. Over the past few years, we have seen wide scale improvements in data processing, database, and statistical analysis tools. Direct infusion mass spectrometery (DIMS) is a widely used platform that is able to produce a global fingerprint of the metabolome, without the requirement of a prior chromatographic step - making it ideal for wide scale high-throughput metabolomics analysis. In spite of these developments, metabolite identification still remains a key bottleneck in untargeted mass spectrometry-based metabolomics studies. The first step of the metabolite identification task is to query masses against a metaboite database to get putative metabolite annotations. Each existing metabolite database differs in a number of aspects including coverage, format, and accessibility - often limiting the user to a rudimentary web interface. Manually combining multiple search results for a single experiment where there may be potentially hundreds of masses to investigate becomes an incredibly arduous task.\n\nResultsTo facilitate unified access to metabolite information we have created the Direct Infusion MEtabolite database (DIMEdb), a comprehensive web-based metabolite database that contains over 80,000 metabolites sourced from a number of renowned metabolite databases of which can be utilised in the analysis and annotation of DIMS data. To demostrate the efficacy of DIMEdb, a simple use case for metabolic identification is presented. DIMEdb aims to provide a single point of access to metabolite information, and hopefully facilitate the development of much needed bioinformatic tools.\n\nAvailabilityDIMEdb is freely available at https://dimedb.ibers.aber.ac.uk.\n\nContactkeo7@aber.ac.uk\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗