Quantitative Phosphoproteomic and System-Level Analysis of TOR Inhibition Unravel Distinct Organellar Acclimation in Chlamydomonas reinhardtii

Rapamycin is an inhibitor of the evolutionary conserved Target of Rapamycin (TOR) kinase which promotes and coordinates translation with cell growth and division. In heterotrophic organisms, TOR regulation is based on intra- and extracellular stimuli such as amino acids level and insulin perception. However, how plant TOR pathways have evolved to integrate plastid endosymbiosis is a remaining question. Despite the close association of the TOR signaling with the coordination between protein turn-over and growth, proteome and phosphoproteome acclimation to a rapamycin treatment have not yet been thoroughly investigated in Chlamydomonas reinhardtii. In this study, we have used in vivo label-free phospho-proteomic analysis to profile both protein and phosphorylation changes at 0, 24, and 48 h in Chlamydomonas cells treated with rapamycin. Using multivariate statistics we highlight the impact of TOR inhibition on both the proteome and the phosphoproteome. Two-way ANOVA distinguished differential levels of proteins and phosphoproteins in response either to culture duration and rapamycin treatment or combined effects. Finally, protein–protein interaction networks and functional enrichment analysis underlined the relation between plastid and mitochondrial metabolism. Prominent changes of proteins involved in sulfur, cysteine, and methionine as well as nucleotide metabolism on the one hand, and changes in the TCA cycle on the other highlight the interplay of chloroplast and mitochondria metabolism. Furthermore, TOR inhibition revealed changes in the endomembrane trafficking system. Phosphoproteomics data, on the other hand, highlighted specific differentially regulated phosphorylation sites for calcium-regulated protein kinases as well as ATG7, S6K, and PP2C. To conclude we provide a first combined Chlamydomonas proteomics and phosphoproteomics dataset in response to TOR inhibition, which will support further investigations

Combining metal oxide affinity chromatography (MOAC) and selective mass spectrometry for robust identification of in vivo protein phosphorylation sites

BACKGROUND: Protein phosphorylation is accepted as a major regulatory pathway in plants. More than 1000 protein kinases are predicted in the Arabidopsis proteome, however, only a few studies look systematically for in vivo protein phosphorylation sites. Owing to the low stoichiometry and low abundance of phosphorylated proteins, phosphorylation site identification using mass spectrometry imposes difficulties. Moreover, the often observed poor quality of mass spectra derived from phosphopeptides results frequently in uncertain database hits. Thus, several lines of evidence have to be combined for a precise phosphorylation site identification strategy. RESULTS: Here, a strategy is presented that combines enrichment of phosphoproteins using a technique termed metaloxide affinity chromatography (MOAC) and selective ion trap mass spectrometry. The complete approach involves (i) enrichment of proteins with low phosphorylation stoichiometry out of complex mixtures using MOAC, (ii) gel separation and detection of phosphorylation using specific fluorescence staining (confirmation of enrichment), (iii) identification of phosphoprotein candidates out of the SDS-PAGE using liquid chromatography coupled to mass spectrometry, and (iv) identification of phosphorylation sites of these enriched proteins using automatic detection of H(3)PO(4 )neutral loss peaks and data-dependent MS(3)-fragmentation of the corresponding MS(2)-fragment. The utility of this approach is demonstrated by the identification of phosphorylation sites in Arabidopsis thaliana seed proteins. Regulatory importance of the identified sites is indicated by conservation of the detected sites in gene families such as ribosomal proteins and sterol dehydrogenases. To demonstrate further the wide applicability of MOAC, phosphoproteins were enriched from Chlamydomonas reinhardtii cell cultures. CONCLUSION: A novel phosphoprotein enrichment procedure MOAC was applied to seed proteins of A. thaliana and to proteins extracted from C. reinhardtii. Thus, the method can easily be adapted to suit the sample of interest since it is inexpensive and the components needed are widely available. Reproducibility of the approach was tested by monitoring phosphorylation sites on specific proteins from seeds and C. reinhardtii in duplicate experiments. The whole process is proposed as a strategy adaptable to other plant tissues providing high confidence in the identification of phosphoproteins and their corresponding phosphorylation sites

Cereal Crop Proteomics: Systemic Analysis of Crop Drought Stress Responses Towards Marker-Assisted Selection Breeding

Sustainable crop production is the major challenge in the current global climate change scenario. Drought stress is one of the most critical abiotic factors which negatively impact crop productivity. In recent years, knowledge about molecular regulation has been generated to understand drought stress responses. For example, information obtained by transcriptome analysis has enhanced our knowledge and facilitated the identification of candidate genes which can be utilized for plant breeding. On the other hand, it becomes more and more evident that the translational and post-translational machinery plays a major role in stress adaptation, especially for immediate molecular processes during stress adaptation. Therefore, it is essential to measure protein levels and post-translational protein modifications to reveal information about stress inducible signal perception and transduction, translational activity and induced protein levels. This information cannot be revealed by genomic or transcriptomic analysis. Eventually, these processes will provide more direct insight into stress perception then genetic markers and might build a complementary basis for future marker-assisted selection of drought resistance. In this review, we survey the role of proteomic studies to illustrate their applications in crop stress adaptation analysis with respect to productivity. Cereal crops such as wheat, rice, maize, barley, sorghum and pearl millet are discussed in detail. We provide a comprehensive and comparative overview of all detected protein changes involved in drought stress in these crops and have summarized existing knowledge into a proposed scheme of drought response. Based on a recent proteome study of pearl millet under drought stress we compare our findings with wheat proteomes and another recent study which defined genetic marker in pearl millet

From bench to bountiful harvests : a road map for the next decade of Arabidopsis research

In the face of an increasing world population and climate instability, the demands for food and fuel will continue to rise. Plant science will be crucial to help meet these exponentially increasing requirements for food and fuel supplies. Fundamental plant research will play a major role in providing key advances in our understanding of basic plant processes that can then flow into practical advances through knowledge sharing and collaborations. The model plant Arabidopsis thaliana has played a major role in our understanding of plant biology, and the Arabidopsis community has developed many tools and resources to continue building on this knowledge. Drawing from previous experience of internationally coordinated projects, The international Arabidopsis community, represented by the Multinational Arabidopsis Steering Committee (MASC), has drawn up a road map for the next decade of Arabidopsis research to inform scientists and decision makers on the future foci of Arabidopsis research within the wider plant science landscape. This article provides a summary of the MASC road map

COVRECON: Combining Genome-scale Metabolic Network Reconstruction and Data-driven Inverse Modeling to Reveal Changes in Metabolic Interaction Networks

One central goal of systems biology is to infer biochemical regulations from large-scale OMICS data. Many aspects of cellular physiology and organism phenotypes could be understood as a result of the metabolic interaction network dynamics. Previously, we have derived a mathematical method addressing this problem using metabolomics data for the inverse calculation of a biochemical Jacobian network. However, these algorithms for this inference are limited by two issues: they rely on structural network information that needs to be assembled manually, and they are numerically unstable due to ill-conditioned regression problems, which makes them inadequate for dealing with large-scale metabolic networks. In this work, we present a novel regression-loss based inverse Jacobian algorithm and related workflow COVRECON. It consists of two parts: a, Sim-Network and b, Inverse differential Jacobian evaluation. Sim-Network automatically generates an organism-specific enzyme and reaction dataset from Bigg and KEGG databases, which is then used to reconstruct the Jacobian's structure for a specific metabolomics dataset. Instead of directly solving a regression problem, the new inverse differential Jacobian part is based on a more robust approach and rates the biochemical interactions according to their relevance from large-scale metabolomics data. This approach is illustrated by in silico stochastic analysis with different-sized metabolic networks from the BioModels database. The advantages of COVRECON are that 1) it automatically reconstructs a data-driven superpathway metabolic interaction model; 2) more general network structures can be considered; 3) the new inverse algorithms improve stability, decrease computation time, and extend to large-scale modelsComment: non

Integrative molecular profiling indicates a central role of transitory starch breakdown in establishing a stable C/N homeostasis during cold acclimation in two natural accessions of Arabidopsis thaliana

Figure S1. Comparison of metabolite levels between non-acclimated and acclimated plants. Ratios were built by dividing the absolute mean values of metabolite levels of Rsch by levels of Cvi, or by dividing absolute mean values of metabolites of acc by na plants. Asterisks indicate significant differences as described in the figure. Grey-coloured metabolites were not experimentally analysed. (TIF 1649 kb

Species-specific analysis of protein sequence motifs using mutual information

BACKGROUND: Protein sequence motifs are by definition short fragments of conserved amino acids, often associated with a specific function. Accordingly protein sequence profiles derived from multiple sequence alignments provide an alternative description of functional motifs characterizing families of related sequences. Such profiles conveniently reflect functional necessities by pointing out proximity at conserved sequence positions as well as depicting distances at variable positions. Discovering significant conservation characteristics within the variable positions of profiles mirrors group-specific and, in particular, evolutionary features of the underlying sequences. RESULTS: We describe the tool PROfile analysis based on Mutual Information (PROMI) that enables comparative analysis of user-classified protein sequences. PROMI is implemented as a web service using Perl and R as well as other publicly available packages and tools on the server-side. On the client-side platform-independence is achieved by generally applied internet delivery standards. As one possible application analysis of the zinc finger C(2)H(2)-type protein domain is introduced to illustrate the functionality of the tool. CONCLUSION: The web service PROMI should assist researchers to detect evolutionary correlations in protein profiles of defined biological sequences. It is available at where additional documentation can be found

Metabolite profiling in plant biology: platforms and destinations

Optimal use of genome sequences and gene-expression resources requires powerful phenotyping platforms, including those for systematic analysis of metabolite composition. The most used technologies for metabolite profiling, including mass spectral, nuclear magnetic resonance and enzyme-based approaches, have various advantages and disadvantages, and problems can arise with reliability and the interpretation of the huge datasets produced. These techniques will be useful for answering important biological questions in the future

ProMEX – a mass spectral reference database for plant proteomics

The ProMEX database is one of the main collection of annotated tryptic peptides in plant proteomics. The main objective of the ProMEX database is to provide experimental MS/MS-based information for cell type-specific or sub-cellular proteomes in Arabidopsis thaliana, Medicago truncatula, Chlamydomonas reinhardtii, Lotus japonicus, Lotus corniculatus, Phaseolus vulgaris, Lycopersicon esculentum, Solanum tuberosum, Nicotiana tabacum, Glycine max, Zea mays, Bradyrhizobium japonicum, and Sinorhizobium meliloti. Direct links at the protein level to the most relevant databases are present in ProMEX. Furthermore, the spectral sequence information are linked to their respective pathways and can be viewed in pathway maps