Absolute quantification of Medicago truncatula sucrose synthase isoforms and N-metabolism enzymes in symbiotic root nodules and the detection of novel nodule phosphoproteins by mass spectrometry

Mass spectrometry (MS) has become increasingly important for tissue specific protein quantification at the isoform level, as well as for the analysis of protein post-translational regulation mechanisms and turnover rates. Thanks to the development of high accuracy mass spectrometers, peptide sequencing without prior knowledge of the amino acid sequence—de novo sequencing—can be performed. In this work, absolute quantification of a set of key enzymes involved in carbon and nitrogen metabolism in Medicago truncatula ‘Jemalong A17’ root nodules is presented. Among them, sucrose synthase (SuSy; EC 2.4.1.13), one of the central enzymes in sucrose cleavage in root nodules, has been further characterized and the relative phosphorylation state of the three most abundant isoforms has been quantified. De novo sequencing provided sequence information of a so far unidentified peptide, most probably belonging to SuSy2, the second most abundant isoform in M. truncatula root nodules. TiO2-phosphopeptide enrichment led to the identification of not only a phosphorylation site at Ser11 in SuSy1, but also of several novel phosphorylation sites present in other root nodule proteins such as alkaline invertase (AI; EC 3.2.1.26) and an RNA-binding protein

Unpredictability of metabolism—the key role of metabolomics science in combination with next-generation genome sequencing

Next-generation sequencing provides technologies which sequence whole prokaryotic and eukaryotic genomes in days, perform genome-wide association studies, chromatin immunoprecipitation followed by sequencing and RNA sequencing for transcriptome studies. An exponentially growing volume of sequence data can be anticipated, yet functional interpretation does not keep pace with the amount of data produced. In principle, these data contain all the secrets of living systems, the genotype–phenotype relationship. Firstly, it is possible to derive the structure and connectivity of the metabolic network from the genotype of an organism in the form of the stoichiometric matrix N. This is, however, static information. Strategies for genome-scale measurement, modelling and predicting of dynamic metabolic networks need to be applied. Consequently, metabolomics science—the quantitative measurement of metabolism in conjunction with metabolic modelling—is a key discipline for the functional interpretation of whole genomes and especially for testing the numerical predictions of metabolism based on genome-scale metabolic network models. In this context, a systematic equation is derived based on metabolomics covariance data and the genome-scale stoichiometric matrix which describes the genotype–phenotype relationship

Lesson from the Stoichiometry Determination of the Cohesin Complex: A Short Protease Mediated Elution Increases the Recovery from Cross-Linked Antibody-Conjugated Beads

Affinity purification of proteins using antibodies coupled to beads and subsequent mass spectrometric analysis has become a standard technique for the identification of protein complexes. With the recent transfer of the isotope dilution mass spectrometry principle (IDMS) to the field of proteomics, quantitative analysesssuch as the stoichiometry determination of protein complexesshave become achievable. Traditionally proteins were eluted from antibody-conjugated beads using glycine at low pH or using diluted acids such as HCl, TFA, or FA, but elution was often found to be incomplete. Using the cohesin complex and the anaphase promoting complex/cyclosome (APC/C) as examples, we show that a short 15-60 min predigestion with a protease such as LysC (modified on-bead digest termed protease elution) increases the elution efficiency 2- to 3-fold compared to standard acid elution protocols. While longer incubation periodssas performed in standard on-bead digestionsled to partial proteolysis of the cross-linked antibodies, no or only insignificant cleavage was observed after 15-60 min protease mediated elution. Using the protease elution method, we successfully determined the stoichiometry of the cohesin complex by absolute quantification of the four core subunits using LC-SRM analysis and 19 reference peptides generated with the EtEP strategy. Protease elution was 3-fold more efficient compared to HCl elution, but measurements using both elution techniques are in agreement with

Systems Integration of Biodefense Omics Data for Analysis of Pathogen-Host Interactions and Identification of Potential Targets

The NIAID (National Institute for Allergy and Infectious Diseases) Biodefense Proteomics program aims to identify targets for potential vaccines, therapeutics, and diagnostics for agents of concern in bioterrorism, including bacterial, parasitic, and viral pathogens. The program includes seven Proteomics Research Centers, generating diverse types of pathogen-host data, including mass spectrometry, microarray transcriptional profiles, protein interactions, protein structures and biological reagents. The Biodefense Resource Center (www.proteomicsresource.org) has developed a bioinformatics framework, employing a protein-centric approach to integrate and support mining and analysis of the large and heterogeneous data. Underlying this approach is a data warehouse with comprehensive protein + gene identifier and name mappings and annotations extracted from over 100 molecular databases. Value-added annotations are provided for key proteins from experimental findings using controlled vocabulary. The availability of pathogen and host omics data in an integrated framework allows global analysis of the data and comparisons across different experiments and organisms, as illustrated in several case studies presented here. (1) The identification of a hypothetical protein with differential gene and protein expressions in two host systems (mouse macrophage and human HeLa cells) infected by different bacterial (Bacillus anthracis and Salmonella typhimurium) and viral (orthopox) pathogens suggesting that this protein can be prioritized for additional analysis and functional characterization. (2) The analysis of a vaccinia-human protein interaction network supplemented with protein accumulation levels led to the identification of human Keratin, type II cytoskeletal 4 protein as a potential therapeutic target. (3) Comparison of complete genomes from pathogenic variants coupled with experimental information on complete proteomes allowed the identification and prioritization of ten potential diagnostic targets from Bacillus anthracis. The integrative analysis across data sets from multiple centers can reveal potential functional significance and hidden relationships between pathogen and host proteins, thereby providing a systems approach to basic understanding of pathogenicity and target identification

Current status of the multinational Arabidopsis community

The multinational Arabidopsis research community is highly collaborative and over the past thirty years these activities have been documented by the Multinational Arabidopsis Steering Committee (MASC). Here, we (a) highlight recent research advances made with the reference plant Arabidopsis thaliana; (b) provide summaries from recent reports submitted by MASC subcommittees, projects and resources associated with MASC and from MASC country representatives; and (c) initiate a call for ideas and foci for the “fourth decadal roadmap,” which will advise and coordinate the global activities of the Arabidopsis research community

The eukaryotic CO2-concentrating organelle is liquid-like and exhibits dynamic reorganization

Approximately 30%–40% of global CO 2 fixation occurs inside a non-membrane-bound organelle called the pyrenoid, which is found within the chloroplasts of most eukaryotic algae. The pyrenoid matrix is densely packed with the CO 2-fixing enzyme Rubisco and is thought to be a crystalline or amorphous solid. Here, we show that the pyrenoid matrix of the unicellular alga Chlamydomonas reinhardtii is not crystalline but behaves as a liquid that dissolves and condenses during cell division. Furthermore, we show that new pyrenoids are formed both by fission and de novo assembly. Our modeling predicts the existence of a “magic number” effect associated with special, highly stable heterocomplexes that influences phase separation in liquid-like organelles. This view of the pyrenoid matrix as a phase-separated compartment provides a paradigm for understanding its structure, biogenesis, and regulation. More broadly, our findings expand our understanding of the principles that govern the architecture and inheritance of liquid-like organelles