Synechocystis PCC6803 and PCC6906 dnaK2 expression confers salt and oxidative stress tolerance in Arabidopsis via reduction of hydrogen peroxide accumulation.

Abiotic stress slows plant growth and development. Because salt stress, particularly from NaCl, acts as an important limiting factor in agricultural productivity, the identification and manipulation of genes related to salt tolerance could improve crop productivity. Prokaryotic, heat shock protein (Hsp), DnaK from the ubiquitous Hsp70 family is upregulated in cells that are under abiotic stress. Synechocystis spp. cyanobacteria encode at least three potential DnaK proteins in their genome. Here, expressions of dnaK1s and dnaK2s from two Synechocystis spp. PCC6803 (Sy6803) and PCC6906 (Sy6906), enhanced salt tolerance in a dnaK-defective Escherichia coli strain. In contrast, dnaK3s in both strains were ineffective, indicating that dnaK3 is functionally different from dnaK1 and dnaK2 in Synechocystis spp. under salt stress. Ectopic expression of dnaK2s from Sy6803 and Sy6906 conferred salt tolerance in transgenic Arabidopsis plants, which exhibited greater root length, chlorophyll content, fresh weight, and survival rate than wild type plants, all in the presence of NaCl. In transgenic plants, hydrogen peroxide (H2O2) accumulation was reduced under NaCl stress and loss of chlorophyll content was reduced under H2O2 stress. Overall results suggest that dnaK2s from Sy6803 and Sy6906 confer salt and oxidative tolerance in transgenic plants by reduction of H2O2 accumulation.

A rapid, simple method for the genetic discrimination of intact Arabidopsis thaliana mutant seeds using metabolic profiling by direct analysis in real-time mass spectrometry.

BACKGROUND: Efficient high throughput screening systems of useful mutants are prerequisite for study of plant functional genomics and lots of application fields. Advance in such screening tools, thanks to the development of analytic instruments. Direct analysis in real-time (DART)-mass spectrometry (MS) by ionization of complex materials at atmospheric pressure is a rapid, simple, high-resolution analytical technique. Here we describe a rapid, simple method for the genetic discrimination of intact Arabidopsis thaliana mutant seeds using metabolic profiling by DART-MS. RESULTS: To determine whether this DART-MS combined by multivariate analysis can perform genetic discrimination based on global metabolic profiling, intact Arabidopsis thaliana mutant seeds were subjected to DART-MS without any sample preparation. Partial least squares-discriminant analysis (PLS-DA) of DART-MS spectral data from intact seeds classified 14 different lines of seeds into two distinct groups: Columbia (Col-0) and Landsberg erecta (Ler) ecotype backgrounds. A hierarchical dendrogram based on partial least squares-discriminant analysis (PLS-DA) subdivided the Col-0 ecotype into two groups: mutant lines harboring defects in the phenylpropanoid biosynthetic pathway and mutants without these defects. These results indicated that metabolic profiling with DART-MS could discriminate intact Arabidopsis seeds at least ecotype level and metabolic pathway level within same ecotype. CONCLUSION: The described DART-MS combined by multivariate analysis allows for rapid screening and metabolic characterization of lots of Arabidopsis mutant seeds without complex metabolic preparation steps. Moreover, potential novel metabolic markers can be detected and used to clarify the genetic relationship between Arabidopsis cultivars. Furthermore this technique can be applied to predict the novel gene function of metabolic mutants regardless of morphological phenotypes.

Fast determination of the ripeness stage of strawberries using infrared spectroscopy combined with principal component analysis.

The utility of infrared (IR) spectroscopy for the determination of strawberry ripeness has been successfully demonstrated. Transmission IR spectra were collected using dried liquid extracts from strawberry flesh. The overall IR feature provided fairly noticeable differences, and the ripeness stage was clearly identified using principal component analysis (PCA). Although all of the extracted components contributed to the resulting spectral features for discrimination, the variation of carbohydrate and amide residues played a major role for providing the selective spectral feature. Additionally, NMR spectra were also collected to quantify the concentrations of three small sugars (alpha-glucose, beta-glucose and sucrose) as well as to evaluate the NMR spectral features at each ripeness step. The concentrations of three sugars increased from early to late growth stages. Both IR and NMR spectroscopies were valuable to elucidate the metabolic signatures for the determining of ripeness stage; however, IR spectroscopy could be more advantageous when fast and high throughput analysis is essential.

A proposed framework for the description of plant metabolomics experiments and their results.

The study of the metabolite complement of biological samples, known as metabolomics, is creating large amounts of data, and support for handling these data sets is required to facilitate meaningful analyses that will answer biological questions. We present a data model for plant metabolomics known as ArMet (architecture for metabolomics). It encompasses the entire experimental time line from experiment definition and description of biological source material, through sample growth and preparation to the results of chemical analysis. Such formal data descriptions, which specify the full experimental context, enable principled comparison of data sets, allow proper interpretation of experimental results, permit the repetition of experiments and provide a basis for the design of systems for data storage and transmission. The current design and example implementations are freely available (http://www.armet.org/). We seek to advance discussion and community adoption of a standard for metabolomics, which would promote principled collection, storage and transmission of experiment data.