Identification of B6T173 (ZmPrx35) as the prevailing peroxidase in highly insect-resistant maize (Zea mays, p84C3) kernels by activity-directed purification

White-rot fungus Phlebia floridensis ITM 12: Laccase production, oxidoreductase profile, and hydrogen-peroxide independent activity

Phlebia genus is a relevant group of fungi with a crucial role in numerous ecosystems. In tropical and subtropical areas this genus allows the efficient degradation of lignin and carbon recovery; however, the majority of these fungal species remain undiscovered. The main purpose of this work was to determine the enzymatic activity of extracellular proteins of a novel Phlebia floridensis strain isolated in Yucatan Peninsula, Mexico. The results that are reported here demonstrate that the soluble protein extract of P. floridensis can degrade a broad spectrum of recalcitrant compounds. This induced protein extract is able to modify not only phenolic and nonphenolic compounds, but also anthroquinone dyes, even without the addition of exogenous hydrogen peroxide. Using liquid chromatography-mass spectrometry (LC-MS), we were able to identify a novel chloroperoxidase in enzymatic extract. As far as we know, this is the first report about the presence of this type of enzyme in the Phlebia genus.

Modulation of Aleurone Peroxidases in Kernels of Insect-Resistant Maize (Zea mays L.; Pob84-C3R) After Mechanical and Insect Damage

Peroxidases (PODs) have many biological functions during the plant life cycle. In maize kernels, endosperm PODs have been identified as biochemical contributors to resistance against Sitophilus zeamais, but their identities have not been determined. In this study, we identified these PODs and determined whether their contributions are basal or inducible. Semi-purification and LC-MS/MS analyses showed that the protein ZmPrx35 is the predominant soluble endosperm POD from kernels of Pob84-C3R. Subsequent time-course analyses after mechanical damage showed that POD activity was regulated in a fluctuating kinetics pattern and that zmprx35 mRNA expression levels reflected this pattern. After 48 h of infestation with S. zeamais or Prostephanus truncatus, soluble endosperm POD activities were 1.38- or 0.85-fold, respectively. Under the same conditions, zmprx35 expression was induced 1.61-fold (S. zeamais infestation) and 1.17-fold (P. truncatus infestation). These findings suggest that ZmPrx35 contributes to the protective responses of aleurone cells against wounding and pest attacks, which could be enhanced/repressed by insect factors. Our data also provide evidence that the mechanisms of resistance of maize Pob84-C3R kernels toward the insect pests S. zeamais and P. truncatus are independent.

Developing Pericarp of Maize: A Model to Study Arabinoxylan Synthesis and Feruloylation

Cell walls are comprised of networks of entangled polymers that differ considerably between species, tissues and developmental stages. The cell walls of grasses, a family that encompasses major crops, contain specific polysaccharide structures such as xylans substituted with feruloylated arabinose residues. Ferulic acid is involved in the grass cell wall assembly by mediating linkages between xylan chains and between xylans and lignins. Ferulic acid contributes to the physical properties of cell walls, it is a hindrance to cell wall degradability (thus biomass conversion and silage digestibility) and may contribute to pest resistance. Many steps leading to the formation of grass xylans and their cross-linkages remain elusive. One explanation might originate from the fact that many studies were performed on lignified stem tissues. Pathways leading to lignins and feruloylated xylans share several steps, and lignin may impede the release and thus the quantification of ferulic acid. To overcome these difficulties, we used the pericarp of the maize B73 line as a model to study feruloylated xylan synthesis and crosslinking. Using Fourier-transform infra-red spectroscopy and biochemical analyses, we show that this tissue has a low lignin content and is composed of approximately 50% heteroxylans and approximately 5% ferulic acid. Our study shows that, to date, maize pericarp contains the highest level of ferulic acid reported in plant tissue. The detection of feruloylated xylans with a polyclonal antibody shows that the occurrence of these polysaccharides is developmentally regulated in maize grain. We used the genomic tools publicly available for the B73 line to study the expression of genes within families involved or suggested to be involved in the phenylpropanoid pathway, xylan formation, feruloylation and their oxidative crosslinking. Our analysis supports the hypothesis that the feruloylated moiety of xylans originated from feruloylCoA and is transferred by a member of the BAHD acyltransferase family. We propose candidate genes for functional characterization that could subsequently be targeted for grass crop breeding.

An evolving computational platform for biological mass spectrometry: workflows, statistics and data mining with MASSyPup64

In biological mass spectrometry, crude instrumental data need to be converted into meaningful theoretical models. Several data processing and data evaluation steps are required to come to the final results. These operations are often difficult to reproduce, because of too specific computing platforms. This effect, known as 'workflow decay', can be diminished by using a standardized informatic infrastructure. Thus, we compiled an integrated platform, which contains ready-to-use tools and workflows for mass spectrometry data analysis. Apart from general unit operations, such as peak picking and identification of proteins and metabolites, we put a strong emphasis on the statistical validation of results and Data Mining. MASSyPup64 includes e.g., the OpenMS/TOPPAS framework, the Trans-Proteomic-Pipeline programs, the ProteoWizard tools, X!Tandem, Comet and SpiderMass. The statistical computing language R is installed with packages for MS data analyses, such as XCMS/metaXCMS and MetabR. The R package Rattle provides a user-friendly access to multiple Data Mining methods. Further, we added the non-conventional spreadsheet program teapot for editing large data sets and a command line tool for transposing large matrices. Individual programs, console commands and modules can be integrated using the Workflow Management System (WMS) taverna. We explain the useful combination of the tools by practical examples: (1) A workflow for protein identification and validation, with subsequent Association Analysis of peptides, (2) Cluster analysis and Data Mining in targeted Metabolomics, and (3) Raw data processing, Data Mining and identification of metabolites in untargeted Metabolomics. Association Analyses reveal relationships between variables across different sample sets. We present its application for finding co-occurring peptides, which can be used for target proteomics, the discovery of alternative biomarkers and protein-protein interactions. Data Mining derived models displayed a higher robustness and accuracy for classifying sample groups in targeted Metabolomics than cluster analyses. Random Forest models do not only provide predictive models, which can be deployed for new data sets, but also the variable importance. We demonstrate that the later is especially useful for tracking down significant signals and affected pathways in untargeted Metabolomics. Thus, Random Forest modeling supports the unbiased search for relevant biological features in Metabolomics. Our results clearly manifest the importance of Data Mining methods to disclose non-obvious information in biological mass spectrometry . The application of a Workflow Management System and the integration of all required programs and data in a consistent platform makes the presented data analyses strategies reproducible for non-expert users. The simple remastering process and the Open Source licenses of MASSyPup64 (http://www.bioprocess.org/massypup/) enable the continuous improvement of the system.