The ROS wheel: refining ROS transcriptional footprints

In the last decade, microarray studies have delivered extensive inventories of transcriptome-wide changes in messenger RNA levels provoked by various types of oxidative stress in Arabidopsis (Arabidopsis thaliana). Previous cross-study comparisons indicated how different types of reactive oxygen species (ROS) and their subcellular accumulation sites are able to reshape the transcriptome in specific manners. However, these analyses often employed simplistic statistical frameworks that are not compatible with large-scale analyses. Here, we reanalyzed a total of 79 Affymetrix ATH1 microarray studies of redox homeostasis perturbation experiments. To create hierarchy in such a high number of transcriptomic data sets, all transcriptional profiles were clustered on the overlap extent of their differentially expressed transcripts. Subsequently, meta-analysis determined a single magnitude of differential expression across studies and identified common transcriptional footprints per cluster. The resulting transcriptional footprints revealed the regulation of various metabolic pathways and gene families. The RESPIRATORY BURST OXIDASE HOMOLOG F-mediated respiratory burst had a major impact and was a converging point among several studies. Conversely, the timing of the oxidative stress response was a determining factor in shaping different transcriptome footprints. Our study emphasizes the need to interpret transcriptomic data sets in a systematic context, where initial, specific stress triggers can converge to common, aspecific transcriptional changes. We believe that these refined transcriptional footprints provide a valuable resource for assessing the involvement of ROS in biological processes in plants

N-terminal proteomics assisted profiling of the unexplored translation initiation landscape in Arabidopsis thaliana

Proteogenomics is an emerging research field yet lacking a uniform method of analysis. Proteogenomic studies in which N-terminal proteomics and ribosome profiling are combined, suggest that a high number of protein start sites are currently missing in genome annotations. We constructed a proteogenomic pipeline specific for the analysis of N-terminal proteomics data, with the aim of discovering novel translational start sites outside annotated protein coding regions. In summary, unidentified MS/MS spectra were matched to a specific N-terminal peptide library encompassing protein N termini encoded in the Arabidopsis thaliana genome. After a stringent false discovery rate filtering, 117 protein N termini compliant with N-terminal methionine excision specificity and indicative of translation initiation were found. These include N-terminal protein extensions and translation from transposable elements and pseudogenes. Gene prediction provided supporting protein-coding models for approximately half of the protein N termini. Besides the prediction of functional domains (partially) contained within the newly predicted ORFs, further supporting evidence of translation was found in the recently released Araport11 genome re-annotation of Arabidopsis and computational translations of sequences stored in public repositories. Most interestingly, complementary evidence by ribosome profiling was found for 23 protein N termini. Finally, by analyzing protein N-terminal peptides, an in silico analysis demonstrates the applicability of our N-terminal proteogenomics strategy in revealing protein-coding potential in species with well-and poorly-annotated genomes

Does virulence assessment of Vibrio anguillarum using sea bass (Dicentrarchus labrax) larvae correspond with genotypic and phenotypic characterization?

Background: Vibriosis is one of the most ubiquitous fish diseases caused by bacteria belonging to the genus Vibrio such as Vibrio (Listonella) anguillarum. Despite a lot of research efforts, the virulence factors and mechanism of V. anguillarum are still insufficiently known, in part because of the lack of standardized virulence assays. Methodology/Principal Findings: We investigated and compared the virulence of 15 V. anguillarum strains obtained from different hosts or non-host niches using a standardized gnotobiotic bioassay with European sea bass (Dicentrarchus labrax L.) larvae as model hosts. In addition, to assess potential relationships between virulence and genotypic and phenotypic characteristics, the strains were characterized by random amplified polymorphic DNA (RAPD) and repetitive extragenic palindromic PCR (rep-PCR) analyses, as well as by phenotypic analyses using Biolog's Phenotype MicroArray (TM) technology and some virulence factor assays. Conclusions/Significance: Virulence testing revealed ten virulent and five avirulent strains. While some relation could be established between serotype, genotype and phenotype, no relation was found between virulence and genotypic or phenotypic characteristics, illustrating the complexity of V. anguillarum virulence. Moreover, the standardized gnotobiotic system used in this study has proven its strength as a model to assess and compare the virulence of different V. anguillarum strains in vivo. In this way, the bioassay contributes to the study of mechanisms underlying virulence in V. anguillarum

Pattern mining of mass spectrometry quality control data

Pattern mining of mass spectrometry quality control data Mass spectrometry is widely used to identify proteins based on the mass distribution of their peptides. Unfortunately, because of its inherent complexity, the results of a mass spectrometry experiment can be subject to a large variability. As a means of quality control, recently several qualitative metrics have been defined. [1] Initially these quality control metrics were evaluated independently in order to separately assess particular stages of a mass spectrometry experiment. However, this method is insufficient because the different stages of an experiment do not function in isolation, instead they will influence each other. As a result, subsequent work employed a multivariate statistics approach to assess the correlation structure of the different quality control metrics. [2] However, by making use of some more advanced data mining techniques, additional useful information can be extracted from these quality control metrics. Various pattern mining techniques can be employed to discover hidden patterns in this quality control data. Subspace clustering tries to detect clusters of items based on a restricted set of dimensions. [3] This can be leveraged to for example detect aberrant experiments where only a few of the quality control metrics are outliers, but the experiment still behaved correctly in general. In addition, specialized frequent itemset mining and association rule learning techniques can be used to discover relationships between the various stages of a mass spectrometry experiment, as they are exhibited by the different quality control metrics. Finally, a major source of untapped information lies in the temporal aspect. Most often, problems in a mass spectrometry setup appear gradually, but are only observed after a critical juncture. As previous analyses have not used this temporal information directly, there remains a large potential to detect these problems as soon as they start to manifest by taking this additional dimension of information into account. Based on the previously discovered patterns, these can be evaluated over time by making use of sequential pattern mining techniques. The awareness has risen that suitable quality control information is mandatory to assess the validity of a mass spectrometry experiment. Current efforts aim to standardize this quality control information [4], which will facilitate the dissemination of the data. This results in a large amount of as of yet untapped information, which can be leveraged by making use of specific data mining techniques in order to harness the full power of this new information. [1] Rudnick, P. A. et al. Performance metrics for liquid chromatography-tandem mass spectrometry systems in proteomics analyses. Molecular & Cellular Proteomics 9, 225–241 (2010). [2] Wang, X. et al. QC metrics from CPTAC raw LC-MS/MS data interpreted through multivariate statistics. Analytical Chemistry 86, 2497–2509 (2014). [3] Aksehirli, E., Goethals, B., Müller, E. & Vreeken, J. Cartification: A neighborhood preserving transformation for mining high dimensional data. in Thirteenth IEEE International Conference on Data Mining - ICDM ’13 937–942 (IEEE, 2013). doi:10.1109/ICDM.2013.146 [4] Walzer, M. et al. qcML: An exchange format for quality control metrics from mass spectrometry experiments. Molecular & Cellular Proteomics (2014). doi:10.1074/mcp.M113.03590

The Plant PTM Viewer, a central resource for exploring plant protein modifications

Posttranslational modifications (PTMs) of proteins are central in any kind of cellular signaling. Modern mass spectrometry technologies enable comprehensive identification and quantification of various PTMs. Given the increased numbers and types of mapped protein modifications, a database is necessary that simultaneously integrates and compares site‐specific information for different PTMs, especially in plants for which the available PTM data are poorly catalogued. Here, we present the Plant PTM Viewer (http://www.psb.ugent.be/PlantPTMViewer), an integrative PTM resource that comprises approximately 370,000 PTM sites for 19 types of protein modifications in plant proteins from five different species. The Plant PTM Viewer provides the user with a protein sequence overview in which the experimentally evidenced PTMs are highlighted together with an estimate of the confidence by which the modified peptides and, if possible, the actual modification sites were identified and with functional protein domains or active site residues. The PTM sequence search tool can query PTM combinations in specific protein sequences, whereas the PTM BLAST tool searches for modified protein sequences to detect conserved PTMs in homologous sequences. Taken together, these tools help to assume the role and potential interplay of PTMs in specific proteins or within a broader systems biology context. The Plant PTM Viewer is an open repository that allows the submission of mass spectrometry‐based PTM data to remain at pace with future PTM plant studies

Protein methionine sulfoxide dynamics in Arabidopsis thaliana under oxidative stress

Reactive oxygen species such as hydrogen peroxide can modify proteins via direct oxidation of their sulfur-containing amino acids, cysteine and methionine. Methionine oxidation, studied here, is a reversible posttranslational modification that is emerging as a mechanism by which proteins perceive oxidative stress and function in redox signaling. Identification of proteins with oxidized methionines is the first prerequisite toward understanding the functional effect of methionine oxidation on proteins and the biological processes in which they are involved. Here, we describe a proteome-wide study of in vivo protein-bound methionine oxidation in plants upon oxidative stress using Arabidopsis thaliana catalase 2 knock-out plants as a model system. We identified over 500 sites of oxidation in about 400 proteins and quantified the differences in oxidation between wild-type and catalase 2 knock-out plants. We show that the activity of two plant-specific glutathione S-transferases, GSTF9 and GSTT23, is significantly reduced upon oxidation. And, by sampling over time, we mapped the dynamics of methionine oxidation and gained new insights into this complex and dynamic landscape of a part of the plant proteome that is sculpted by oxidative stress

Chemical genetics approach identifies abnormal inflorescence meristem 1 as a putative target of a novel sulfonamide that protects catalase2-deficient Arabidopsis against photorespiratory stress

Alterations of hydrogen peroxide (H2O2) levels have a profound impact on numerous signaling cascades orchestrating plant growth, development, and stress signaling, including programmed cell death. To expand the repertoire of known molecular mechanisms implicated in H2O2 signaling, we performed a forward chemical screen to identify small molecules that could alleviate the photorespiratory-induced cell death phenotype of Arabidopsisthaliana mutants lacking H2O2-scavenging capacity by peroxisomal catalase2. Here, we report the characterization of pakerine, an m-sulfamoyl benzamide from the sulfonamide family. Pakerine alleviates the cell death phenotype of cat2 mutants exposed to photorespiration-promoting conditions and delays dark-induced senescence in wild-type Arabidopsis leaves. By using a combination of transcriptomics, metabolomics, and affinity purification, we identified abnormal inflorescence meristem 1 (AIM1) as a putative protein target of pakerine. AIM1 is a 3-hydroxyacyl-CoA dehydrogenase involved in fatty acid β-oxidation that contributes to jasmonic acid (JA) and salicylic acid (SA) biosynthesis. Whereas intact JA biosynthesis was not required for pakerine bioactivity, our results point toward a role for β-oxidation-dependent SA production in the execution of H2O2-mediated cell death

Extracellular peptide Kratos restricts cell death during vascular development and stress in Arabidopsis

During plant vascular development, xylem tracheary elements (TEs) form water-conducting, empty pipes by genetically regulated cell death. Cell death is prevented from spreading to non-TEs by unidentified intercellular mechanisms, downstream of METACASPASE9 (MC9)-mediated regulation of autophagy in TEs. Here, we identified differentially abundant extracellular peptides in vascular-differentiating wild-type and MC9-down-regulated Arabidopsis cell suspensions. A peptide named Kratos rescued the abnormally high ectopic non-TE death resulting from either MC9 knockout or TE-specific overexpression of the ATG5 autophagy protein during experimentally induced vascular differentiation in Arabidopsis cotyledons. Kratos also reduced cell death following mechanical damage and extracellular ROS production in Arabidopsis leaves. Stress-induced but not vascular non-TE cell death was enhanced by another identified peptide, named Bia. Bia is therefore reminiscent of several known plant cell death-inducing peptides acting as damage-associated molecular patterns. In contrast, Kratos plays a novel extracellular cell survival role in the context of development and during stress response.Peer reviewe

Assessing the potential of wild yeasts for bioethanol production

Bioethanol fermentations expose yeasts to a new, complex and challenging fermentation medium with specific inhibitors and sugar mixtures depending on the type of carbon source. It is, therefore, suggested that the natural diversity of yeasts should be further exploited in order to find yeasts with good ethanol yield in stressed fermentation media. In this study, we screened more than 50 yeast isolates of which we selected five isolates with promising features. The species Candida bombi, Wickerhamomyces anomalus and Torulaspora delbrueckii showed better osmo- and hydroxymethylfurfural tolerance than Saccharomyces cerevisiae. However, S. cerevisiae isolates had the highest ethanol yield in fermentation experiments mimicking high gravity fermentations (25\ua0% glucose) and artificial lignocellulose hydrolysates (with a myriad of inhibitors). Interestingly, among two tested S. cerevisiaestrains, a wild strain isolated from an oak tree performed better than Ethanol Red, a S. cerevisiae strain which is currently commonly used in industrial bioethanol fermentations. Additionally, a W. anomalus strain isolated from sugar beet thick juice was found to have a comparable ethanol yield, but needed longer fermentation time. Other non-Saccharomycesyeasts yielded lower ethanol amounts