iSanXoT: A standalone application for the integrative analysis of mass spectrometry-based quantitative proteomics data.

Many bioinformatics tools are available for the quantitative analysis of proteomics experiments. Most of these tools use a dedicated statistical model to derive absolute quantitative protein values from mass spectrometry (MS) data. Here, we present iSanXoT, a standalone application that processes relative abundances between MS signals and then integrates them sequentially to upper levels using the previously published Generic Integration Algorithm (GIA). iSanXoT offers unique capabilities that complement conventional quantitative software applications, including statistical weighting and independent modeling of error distributions in each integration, aggregation of technical or biological replicates, quantification of posttranslational modifications, and analysis of coordinated protein behavior. iSanXoT is a standalone, user-friendly application that accepts output from popular proteomics pipelines and enables unrestricted creation of quantification workflows and fully customizable reports that can be reused across projects or shared among users. Numerous publications attest the successful application of diverse integrative workflows constructed using the GIA for the analysis of high-throughput quantitative proteomics experiments. iSanXoT has been tested with the main operating systems. Download links for the corresponding distributions are available at https://github.com/CNIC-Proteomics/iSanXoT/releases.

In-gel protein digestion using acidic methanol produces a highly selective methylation of glutamic acid residues.

Mass-tolerant open search methods allow the high-throughput analysis of modified peptides by mass spectrometry. These techniques have paved the way to unbiased analysis of post-translational modifications in biological contexts, as well as of chemical modifications produced during the manipulation of protein samples. In this work, we have analyzed in-depth a wide variety of samples of different biological origin, including cells, extracellular vesicles, secretomes, centrosomes and tissue preparations, using Comet-ReCom, a recently improved version of the open search engine Comet-PTM. Our results demonstrate that glutamic acid residues undergo intensive methyl esterification when protein digestion is performed using in-gel techniques, but not using gel-free approaches. This effect was highly specific to Glu and was not found for other methylable residues such as Asp.

TurboPutative: A web server for data handling and metabolite classification in untargeted metabolomics.

Untargeted metabolomics aims at measuring the entire set of metabolites in a wide range of biological samples. However, due to the high chemical diversity of metabolites that range from small to large and more complex molecules (i.e., amino acids/carbohydrates vs. phospholipids/gangliosides), the identification and characterization of the metabolome remain a major bottleneck. The first step of this process consists of searching the experimental monoisotopic mass against databases, thus resulting in a highly redundant/complex list of candidates. Despite the progress in this area, researchers are still forced to manually explore the resulting table in order to prioritize the most likely identifications for further biological interpretation or confirmation with standards. Here, we present TurboPutative (https://proteomics.cnic.es/TurboPutative/), a flexible and user-friendly web-based platform composed of four modules (Tagger, REname, RowMerger, and TPMetrics) that streamlines data handling, classification, and interpretability of untargeted LC-MS-based metabolomics data. Tagger classifies the different compounds and provides preliminary insights into the biological system studied. REname improves putative annotation handling and visualization, allowing the recognition of isomers and equivalent compounds and redundant data removal. RowMerger reduces the dataset size, facilitating the manual comparison among annotations. Finally, TPMetrics combines different datasets with feature intensity and relevant information for the researcher and calculates a score based on adduct probability and feature correlations, facilitating further identification, assessment, and interpretation of the results. The TurboPutative web application allows researchers in the metabolomics field that are dealing with massive datasets containing multiple putative annotations to reduce the number of these entries by 80%-90%, thus facilitating the extrapolation of biological knowledge and improving metabolite prioritization for subsequent pathway analysis. TurboPutative comprises a rapid, automated, and customizable workflow that can also be included in programmed bioinformatics pipelines through its RESTful API services. Users can explore the performance of each module through demo datasets supplied on the website. The platform will help the metabolomics community to speed up the arduous task of manual data curation that is required in the first steps of metabolite identification, improving the generation of biological knowledge.

Crosstalk of Cytokinin with Ethylene and Auxin for Cell Elongation Inhibition and Boron Transport in Arabidopsis Primary Root under Boron Deficiency.

Several studies have shown the role of phytohormones in the regulation of root growth of Arabidopsis plants under boron (B) deficiency. Ethylene and auxin play an important role in the control of Arabidopsis primary root cell elongation under short-term B deprivation, whereas cytokinins regulate root growth inhibition under B deficiency by controlling meristem cell proliferation. In this work, we study the possible interaction among cytokinin, ethylene, and auxin in the primary root response to B-deprivation treatment, as well as their possible role in B uptake and transport. Wild type (WT) and two mutants related to auxin and ethylene (aux1 and acs11) Arabidopsis plants were grown in control (10 µM B) or B starvation (0 µM B) treatment, in the absence or presence of trans-zeatin, and their primary root growth was analyzed. The possible interaction between these hormones was also studied by analyzing AUX1 gene expression in the acs11 mutant and ACS11 gene expression in the aux1 mutant. The GUS reporter lines ARR5::GUS, IAA2::GUS, and EBS::GUS were used to observe changes in cytokinin, auxin, and ethylene levels in the root, respectively. The results of this work suggest that cytokinin inhibits root cell elongation under B deficiency through two different mechanisms: (i) an ethylene-dependent mechanism through increased expression of the ACS11 gene, which would lead to increased ethylene in the root, and (ii) an ethylene-independent mechanism through decreased expression of the AUX1 gene, which alters auxin signaling in the meristematic and elongation zones and stele. We also report that changes in the expression of several B transporters occur in response to auxin, ethylene, and cytokinin that may affect the plant B content.