Assessment of antioxidant activity of carotenoid-enriched extracts from peach fruits using the new LOX/RNO method

Peach (Prunus persica L.) fruits contain several health-promoting phytochemicals. Among these, carotenoids, in addition to being involved in determining flesh color, play a relevant role in cell protection against oxidative stress. Nevertheless, antioxidant activity (AA) of peach carotenoids so far has not been investigated in as much detail as phenols. In the present study, for the first time, AA of peach carotenoid extracts was evaluated using the innovative lipoxygenase/4-nitroso-N,N-dimethylaniline (LOX/RNO) method, able to simultaneously detect different antioxidant mechanisms and synergistic antioxidant interactions, as well as using the well-known ORAC and TEAC assays. In particular, extracts were obtained from fruits collected in S4 development stage from two yellow-fleshed (Armking and Redhaven) and three white-fleshed (Silverking, Caldesi 2000, IFF331) varieties. The LOX/RNO method gave high AA values (10-150 μmol eq. Trolox/g f.w.), about 85-1900-fold higher than ORAC and TEAC methods. Moreover, the ratio between AA values, measured by the LOX/RNO method, of yellow- and white-fleshed peaches resulted equal to 14, but only 2.6 and 3.6 for ORAC and TEAC, respectively. Results of this study indicate that the LOX/RNO method, measuring high AA values and easily discriminating among samples, is an advisable tool to assess the AA of the carotenoid component in peach

The evolution of metabolism: How to test evolutionary hypotheses at the genomic level

The origin of primordial metabolism and its expansion to form the metabolic networks extant today represent excellent systems to study the impact of natural selection and the potential adaptive role of novel compounds. Here we present the current hypotheses made on the origin of life and ancestral metabolism and present the theories and mechanisms by which the large chemical diversity of plants might have emerged along evolution. In particular, we provide a survey of statistical methods that can be used to detect signatures of selection at the gene and population level, and discuss potential and limits of these methods for investigating patterns of molecular adaptation in plant metabolism

When a Crop Goes Back to the Wild: Feralization

Feral plants have been known since the inception of modern agriculture, but the genetic changes during what seemed to be a simple reversion of a domesticated form are poorly understood. Recent studies, revealing the changes occurring in weedy rice, show an unexpected degree of differentiation in these feral escapes

Ancestral sequence reconstruction - An underused approach to understand the evolution of gene function in plants?

Whilst substantial research effort has been placed on understanding the interactions of plant proteins with their molecular partners, relatively few studies in plant

How fruit ripening is ENCODEd

Integration of transcriptome profiles, epigenomic marks and chromatin-accessible regions highlights the conserved regulatory circuits governing ripening of fleshy fruits and unveils similarities with the development of dry fruits

Mobile Transposable Elements Shape Plant Genome Diversity

The presence of various types of structural variants, including transposons, make up the major part of the genomic differences among plant species. Two recent papers, Domínguez et al. and Alonge et al. explore specifically the impact that retrotransposons and other structural variants had on several tomato phenotypes of agricultural importance

Integrative Approaches to Enhance Understanding of Plant Metabolic Pathway Structure and Regulation.

Huge insight into molecular mechanisms and biological network coordination have been achieved following the application of various profiling technologies. Our knowledge of how the different molecular entities of the cell interact with one another suggests that, nevertheless, integration of data from different techniques could drive a more comprehensive understanding of the data emanating from different techniques. Here, we provide an overview of how such data integration is being used to aid the understanding of metabolic pathway structure and regulation. We choose to focus on the pairwise integration of large-scale metabolite data with that of the transcriptomic, proteomics, whole-genome sequence, growth- and yield-associated phenotypes, and archival functional genomic data sets. In doing so, we attempt to provide an update on approaches that integrate data obtained at different levels to reach a better understanding of either single gene function or metabolic pathway structure and regulation within the context of a broader biological process