Citrus phenylpropanoids and defence against pathogens. Part I: Metabolic profiling in elicited fruits

Penicillium spp. are among the major postharvest pathogens of citrus fruit. Induction of natural resistance in fruits constitutes one of the alternatives to chemical fungicides. Here, we investigated the involvement of the phenylpropanoid pathway in the induction of resistance in Navelate oranges by examining changes in the metabolic profile of upon eliciting citrus fruits. By using both HPLC-PDA-FD and HPLC-PDA-QTOF-MS allowed the identification of several compounds that seem to be relevant for induced resistance. In elicited fruits, a greater diversity of phenolic compounds was observed in the flavedo (outer coloured part of the peel) when compared to the albedo (inner white part). Moreover, only small changes were detected in the most abundant citrus flavonoids. The coumarin scoparone was among the compounds with the highest induction upon elicitation. Two other highly induced compounds were identified as citrusnin A and drupanin aldehyde. All three compounds are known to exert antimicrobial activity. Our results suggest that phenylpropanoids and their derivatives play an important role in the induction of resistance in citrus fruit.This work was supported by Research Grants AGL2008-04828-C03-02, AGL2009-11969 and CONSOLIDER FUNC-FOOD from the Spanish Ministry of Science and Technology, and PROMETEO/2010/010 from the Generalitat Valenciana.Peer Reviewe

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

G.: Codes, involutions and DNA encodings

If we knew what it was we were doing, it would not be called research, would it? (Albert Einstein)

Digital Information Encoding on DNA

Novel approaches to information encoding with DNA are explored using a new Watson-Crick structure for binary strings more appropriate to model DNA hybridization. First, a Gibbs energy analysis of codeword sets is obtained by using a template and extant error-correcting codes. Template-based codes have too low Gibbs energies that allow cross-hybridization. Second, a new technique is presented to construct arbitrarily large sets of noncrosshybridizing codewords of high quality by two major criteria. They have a large minimum number of mismatches between arbitrary pairs of words and alignments; moreover, their pairwise Gibbs energies of hybridization remain bounded within a safe region according to a modified nearest-neighbor model that has been verified in vitro. The technique is scalable to long strands of up to 150-mers, is in principle implementable in vitro, and may be useful in further combinatorial analysis of DNA structures. Finally, a novel method to encode abiotic information in DNA arrays is defined and some preliminary experimental results are discussed. These new methods can be regarded as a different implementation of Tom Head\u27s idea of writing on DNA molecules [22], although only through hybridization. © Springer-Verlag 2004