Mass spectral libraries are collections of reference spectra, usually associated with specific analytes from which the spectra were generated, that are used for further downstream analysis of new spectra. There are many different formats used for encoding spectral libraries, but none have undergone a standardization process to ensure broad applicability to many applications. As part of the Human Proteome Organization Proteomics Standards Initiative (PSI), we have developed a standardized format for encoding spectral libraries, called mzSpecLib (https://psidev.info/mzSpecLib). It is primarily a data model that flexibly encodes metadata about the library entries using the extensible PSI-MS controlled vocabulary and can be encoded in and converted between different serialization formats. We have also developed a standardized data model and serialization for fragment ion peak annotations, called mzPAF (https://psidev.info/mzPAF). It is defined as a separate standard, since it may be used for other applications besides spectral libraries. The mzSpecLib and mzPAF standards are compatible with existing PSI standards such as ProForma 2.0 and the Universal Spectrum Identifier. The mzSpecLib and mzPAF standards have been primarily defined for peptides in proteomics applications with basic small molecule support. They could be extended in the future to other fields that need to encode spectral libraries for nonpeptidic analytes.

This is a detailed and user-friendly protocol for the cultivation and successful crossing of Lotus japonicus (L. japonicus) e.g. for the generation of higher order mutants, based on methods previously reported (Grant et al., 1962; Handberg and Stougaards, 1992; Jiang and Gresshoff, 1997; Pajuelo and Stougaard, 2005).

Metabolic fingerprinting is a powerful analytical technique, giving access to high-throughput identification and relative quantification of multiple metabolites. Because of short analysis times, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) is the preferred instrumental platform for fingerprinting, although its power in analysis of free fatty acids (FFAs) is limited. However, these metabolites are the biomarkers of human pathologies and indicators of food quality. Hence, a high-throughput method for their fingerprinting is required. Therefore, here we propose a MALDI-TOF-MS method for identification and relative quantification of FFAs in biological samples of different origins. Our approach relies on formation of monomolecular Langmuir films (LFs) at the interphase of aqueous barium acetate solution, supplemented with low amounts of 2,5-dihydroxybenzoic acid, and hexane extracts of biological samples. This resulted in detection limits of 10–13–10–14 mol and overall method linear dynamic range of at least 4 orders of magnitude with accuracy and precision within 2 and 17%, respectively. The method precision was verified with eight sample series of different taxonomies, which indicates a universal applicability of our approach. Thereby, 31 and 22 FFA signals were annotated by exact mass and identified by tandem MS, respectively. Among 20 FFAs identified in Fucus algae, 14 could be confirmed by gas chromatography-mass spectrometry.

Mass spectrometry (MS) is one of the primary techniques used for large-scale analysis of small molecules in metabolomics studies. To date, there has been little data format standardization in this field, as different software packages export results in different formats represented in XML or plain text, making data sharing, database deposition, and reanalysis highly challenging. Working within the consortia of the Metabolomics Standards Initiative, Proteomics Standards Initiative, and the Metabolomics Society, we have created mzTab-M to act as a common output format from analytical approaches using MS on small molecules. The format has been developed over several years, with input from a wide range of stakeholders. mzTab-M is a simple tab-separated text format, but importantly, the structure is highly standardized through the design of a detailed specification document, tightly coupled to validation software, and a mandatory controlled vocabulary of terms to populate it. The format is able to represent final quantification values from analyses, as well as the evidence trail in terms of features measured directly from MS (e.g., LC-MS, GC-MS, DIMS, etc.) and different types of approaches used to identify molecules. mzTab-M allows for ambiguity in the identification of molecules to be communicated clearly to readers of the files (both people and software). There are several implementations of the format available, and we anticipate widespread adoption in the field.

The smut fungus Ustilago maydis is an established model organism for elucidating how biotrophic pathogens colonize plants and how gene families contribute to virulence. Here we describe a step by step protocol for the generation of CRISPR plasmids for single and multiplexed gene editing in U. maydis. Furthermore, we describe the necessary steps required for generating edited clonal populations, losing the Cas9 containing plasmid, and for selecting the desired clones.

NMR is a widely used analytical technique with a growing number of repositories available. As a result, demands for a vendor-agnostic, open data format for long-term archiving of NMR data have emerged with the aim to ease and encourage sharing, comparison, and reuse of NMR data. Here we present nmrML, an open XML-based exchange and storage format for NMR spectral data. The nmrML format is intended to be fully compatible with existing NMR data for chemical, biochemical, and metabolomics experiments. nmrML can capture raw NMR data, spectral data acquisition parameters, and where available spectral metadata, such as chemical structures associated with spectral assignments. The nmrML format is compatible with pure-compound NMR data for reference spectral libraries as well as NMR data from complex biomixtures, i.e., metabolomics experiments. To facilitate format conversions, we provide nmrML converters for Bruker, JEOL and Agilent/Varian vendor formats. In addition, easy-to-use Web-based spectral viewing, processing, and spectral assignment tools that read and write nmrML have been developed. Software libraries and Web services for data validation are available for tool developers and end-users. The nmrML format has already been adopted for capturing and disseminating NMR data for small molecules by several open source data processing tools and metabolomics reference spectral libraries, e.g., serving as storage format for the MetaboLights data repository. The nmrML open access data standard has been endorsed by the Metabolomics Standards Initiative (MSI), and we here encourage user participation and feedback to increase usability and make it a successful standard.

In addition to synthesizing and secreting copious amounts of pectic polymers (Young et al., 2008), Arabidopsis thaliana seed coat epidermal cells produce small amounts of cellulose and hemicelluloses typical of secondary cell walls (Voiniciuc et al., 2015c). These components are intricately linked and are released as a large mucilage capsule upon hydration of mature seeds. Alterations in the structure of minor mucilage components can have dramatic effects on the architecture of this gelatinous cell wall. The immunolabeling protocol described here makes it possible to visualize the distribution of specific polysaccharides in the seed mucilage capsule.

The Arabidopsis thaliana seed coat epidermis produces copious amounts of mucilage polysaccharides (Haughn and Western, 2012). Characterization of mucilage mutants has identified novel genes required for cell wall biosynthesis and modification (North et al., 2014). The biochemical analysis of seed mucilage is essential to evaluate how different mutations affect cell wall structure (Voiniciuc et al., 2015c). Here we describe a robust method to screen the monosaccharide composition of Arabidopsis seed mucilage using ion chromatography (IC). Mucilage from up to 48 samples can be extracted and prepared for IC analysis within 24 h (only 4 h hands-on). Furthermore, this protocol enables fast separation (31 min per sample), automatic detection and quantification of both neutral and acidic sugars.

The identification of metabolites by mass spectrometry constitutes a major bottleneck which considerably limits the throughput of metabolomics studies in biomedical or plant research. Here, we present a novel approach to analyze metabolomics data from untargeted, data-independent LC-MS/MS measurements. By integrated analysis of MS1 abundances and MS/MS spectra, the identification of regulated metabolite families is achieved. This approach offers a global view on metabolic regulation in comparative metabolomics. We implemented our approach in the web application “MetFamily”, which is freely available at http://msbi.ipb-halle.de/MetFamily/. MetFamily provides a dynamic link between the patterns based on MS1-signal intensity and the corresponding structural similarity at the MS/MS level. Structurally related metabolites are annotated as metabolite families based on a hierarchical cluster analysis of measured MS/MS spectra. Joint examination with principal component analysis of MS1 patterns, where this annotation is preserved in the loadings, facilitates the interpretation of comparative metabolomics data at the level of metabolite families. As a proof of concept, we identified two trichome-specific metabolite families from wild-type tomato Solanum habrochaites LA1777 in a fully unsupervised manner and validated our findings based on earlier publications and with NMR.

The Arabidopsis thaliana seed coat produces large amounts of cell wall polysaccharides, which swell out of the epidermal cells upon hydration of the mature dry seeds. While most mucilage polymers immediately diffuse in the surrounding solution, the remaining fraction tightly adheres to the seed, forming a dense gel-like capsule (Macquet et al., 2007). Recent evidence suggests that the adherence of mucilage is mediated by complex interactions between several cell wall components (Griffiths et al., 2014; Voiniciuc et al., 2015a). Therefore, it is important to evaluate how different cell wall mutants impact this mucilage property. This protocol facilitates the analysis of monosaccharides in sequentially extracted mucilage fractions, and quantifies the detachment of each component from seeds.