David Lyon

Phytochemical composition of Potentilla anserina L. analyzed by an integrative GC-MS and LC-MS metabolomics platform

Potentilla anserina L. (Rosaceae) is known for its beneficial effects of prevention of pre-menstrual syndrome (PMS). For this reason P. anserina is processed into many food supplements and pharmaceutical preparations. Here we analyzed hydroalcoholic reference extracts and compared them with various extracts of different pharmacies using an integrative metabolomics platform comprising GC-MS and LC-MS analysis and software toolboxes for data alignment (MetMAX Beta 1.0) and multivariate statistical analysis (COVAIN 1.0). Multivariate statistics of the integrated GC-MS and LC-MS data showed strong differences between the different plant extract formulations. Different groups of compounds such as chlorogenic acid, kaempferol 3-O-rutinoside, acacetin 7-O-rutinoside, and genistein were reported for the first time in this species. The typical fragmentation pathway of the isoflavone genistein confirmed the identification of this active compound that was present with different abundances in all the extracts analyzed. As a result we have revealed that different extraction procedures from different vendors produce different chemical compositions, e.g. different genistein concentrations. Consequently, the treatment may have different effects. The integrative metabolomics platform provides the highest resolution of the phytochemical composition and a mean to define subtle differences in plant extract formulations.

Comprehensive Cell-specific Protein Analysis in Early and Late Pollen Development from Diploid Microsporocytes to Pollen Tube Growth

Pollen development in angiosperms is one of the most important processes controlling plant reproduction and thus productivity. At the same time, pollen development is highly sensitive to environmental fluctuations, including temperature, drought, and nutrition. Therefore, pollen biology is a major focus in applied studies and breeding approaches for improving plant productivity in a globally changing climate. The most accessible developmental stages of pollen are the mature pollen and the pollen tubes, and these are thus most frequently analyzed. To reveal a complete quantitative proteome map, we additionally addressed the very early stages, analyzing eight stages of tobacco pollen development: diploid microsporocytes, meiosis, tetrads, microspores, polarized microspores, bipolar pollen, desiccated pollen, and pollen tubes. A protocol for the isolation of the early stages was established. Proteins were extracted and analyzed by means of a new gel LC-MS fractionation protocol. In total, 3817 protein groups were identified. Quantitative analysis was performed based on peptide count. Exceedingly stage-specific differential protein regulation was observed during the conversion from the sporophytic to the gametophytic proteome. A map of highly specialized functionality for the different stages could be revealed from the metabolic activity and pronounced differentiation of proteasomal and ribosomal protein complex composition up to protective mechanisms such as high levels of heat shock proteins in the very early stages of development.

Possible Role of Nutritional Priming for Early Salt and Drought Stress Responses in Medicago truncatula

Most legume species establish a symbiotic association with soil bacteria. The plant accommodates the differentiated rhizobia in specialized organs, the root nodules. In this environment, the microsymbiont reduces atmospheric nitrogen (N) making it available for plant metabolism. Symbiotic N-fixation is driven by the respiration of the host photosynthates and thus constitutes an additional carbon sink for the plant. Molecular phenotypes of symbiotic and non-symbiotic Medicago truncatula are identified. The implication of nodule symbiosis on plant abiotic stress response mechanisms is not well understood. In this study, we exposed nodulated and non-symbiotic N-fertilized plants to salt and drought conditions. We assessed the stress effects with proteomic and metabolomic methods and found a nutritionally regulated phenotypic plasticity pivotal for a differential stress adjustment strategy.

mzGroupAnalyzer-Predicting Pathways and Novel Chemical Structures from Untargeted High-Throughput Metabolomics Data

The metabolome is a highly dynamic entity and the final readout of the genotype x environment x phenotype (GxExP) relationship of an organism. Monitoring metabolite dynamics over time thus theoretically encrypts the whole range of possible chemical and biochemical transformations of small molecules involved in metabolism. The bottleneck is, however, the sheer number of unidentified structures in these samples. This represents the next challenge for metabolomics technology and is comparable with genome sequencing 30 years ago. At the same time it is impossible to handle the amount of data involved in a metabolomics analysis manually. Algorithms are therefore imperative to allow for automated m/z feature extraction and subsequent structure or pathway assignment. Here we provide an automated pathway inference strategy comprising measurements of metabolome time series using LC- MS with high resolution and high mass accuracy. An algorithm was developed, called mzGroupAnalyzer, to automatically explore the metabolome for the detection of metabolite transformations caused by biochemical or chemical modifications. Pathways are extracted directly from the data and putative novel structures can be identified. The detected m/z features can be mapped on a van Krevelen diagram according to their H/C and O/C ratios for pattern recognition and to visualize oxidative processes and biochemical transformations. This method was applied to Arabidopsis thaliana treated simultaneously with cold and high light. Due to a protective antioxidant response the plants turn from green to purple color via the accumulation of flavonoid structures. The detection of potential biochemical pathways resulted in 15 putatively new compounds involved in the flavonoid-pathway. These compounds were further validated by product ion spectra from the same data. The mzGroupAnalyzer is implemented in the graphical user interface (GUI) of the metabolomics toolbox COVAIN (Sun & Weckwerth, 2012, Metabolomics 8: 81–93). The strategy can be extended to any biological system.

Drought and Recovery: Independently Regulated Processes Highlighting the Importance of Protein Turnover Dynamics and Translational Regulation in Medicago truncatula

Climate change in conjunction with population growth necessitates a systems biology approach to characterize plant drought acclimation as well as a more thorough understanding of the molecular mechanisms of stress recovery. Plants are exposed to a continuously changing environment. Extremes such as several weeks of drought are followed by rain. This requires a molecular plasticity of the plant enabling drought acclimation and the necessity of deacclimation processes for recovery and continuous growth. During drought stress and subsequent recovery, the metabolome and proteome are regulated through a sequence of molecular processes including synthesis and degradation and molecular interaction networks are part of this regulatory process. In order to study this complex regulatory network, a comprehensive analysis is presented for the first time, investigating protein turnover and regulatory classes of proteins and metabolites during a stress recovery scenario in the model legume Medicago truncatula. The data give novel insights into the molecular capacity and differential processes required for acclimation and deacclimation of severe drought stressed plants. Functional cluster and network analyses unraveled independent regulatory mechanisms for stress and recovery with different dynamic phases that during the course of recovery define the plants deacclimation from stress. The combination of relative abundance levels and turnover analysis revealed an early transition phase that seems key for recovery initiation through water resupply and is independent from renutrition. Thus, a first indication for a metabolite and protein-based load capacity was observed necessary for the recovery from drought, an important but thus far ignored possible feature toward tolerance. The data indicate that apart from the plants molecular stress response mechanisms, plasticity may be related to the nutritional status of the plant prior to stress initiation. A new perspective and possible new targets as well as metabolic mechanisms for future plant-bioengineering toward enhanced drought stress tolerance are presented.

Targeted quantitative analysis of a diurnal RuBisCO subunit expression and translation profile in Chlamydomonas reinhardtii introducing a novel Mass Western approach

UNLABELLED RuBisCO catalyzes the rate-limiting step of CO2 fixation in photosynthesis. Hypothetical mechanisms for the regulation of rbcL and rbcS gene expression assume that both large (LSU) and small (SSU) RuBisCO subunit proteins (RSUs) are present in equimolar amounts to fit the 1:1 subunit stoichiometry of the holoenzyme. However, the actual quantities of the RSUs have never been determined in any photosynthetic organism. In this study the absolute amount of rbc transcripts and RSUs was quantified in Chlamydomonas reinhardtii grown during a diurnal light/dark cycle. A novel approach utilizing more reliable protein stoichiometry quantification is introduced. The rbcL:rbcS transcript and protein ratios were both 5:1 on average during the diurnal time course, indicating that SSU is the limiting factor for the assembly of the holoenzyme. The oscillation of the RSUs was 9h out of phase relative to the transcripts. The amount of rbc transcripts was at its maximum in the dark while that of RSUs was at its maximum in the light phase suggesting that translation of the rbc transcripts is activated by light as previously hypothesized. A possible post-translational regulation that might be involved in the accumulation of a 37-kDa N-terminal LSU fragment during the light phase is discussed. BIOLOGICAL SIGNIFICANCE A novel MS based approach enabling the exact stoichiometric analysis and absolute quantification of protein complexes is presented in this article. The application of this method revealed new insights in RuBisCO subunit dynamics.

Medicago truncatula and Glycine max: Different Drought Tolerance and Similar Local Response of the Root Nodule Proteome

Legume crops present important agronomical and environmental advantages mainly due to their capacity to reduce atmospheric N2 to ammonium via symbiotic nitrogen fixation (SNF). This process is very sensitive to abiotic stresses such as drought, but the mechanism underlying this response is not fully understood. The goal of the current work is to compare the drought response of two legumes with high economic impact and research importance, Medicago truncatula and Glycine max, by characterizing their root nodule proteomes. Our results show that, although M. truncatula exhibits lower water potential values under drought conditions compared to G. max, SNF declined analogously in the two legumes. Both of their nodule proteomes are very similar, and comparable down-regulation responses in the diverse protein functional groups were identified (mainly proteins related to the metabolism of carbon, nitrogen, and sulfur). We suggest lipoxygenases and protein turnover as newly recognized players in SNF regulation. Partial drought conditions applied to a split-root system resulted in the local down-regulation of the entire proteome of drought-stressed nodules in both legumes. The high degree of similarity between both legume proteomes suggests that the vast amount of research conducted on M. truncatula could be applied to economically important legume crops, such as soybean.

Comprehensive tissue-specific proteome analysis of drought stress responses in Pennisetum glaucum (L.) R. Br. (Pearl millet)☆

UNLABELLED Pearl millet is the fifth most important cereal crop worldwide and cultivated especially by small holder farmers in arid and semi-arid regions because of its drought and salt tolerance. The molecular mechanisms of drought stress tolerance in Pennisetum remain elusive. We have used a shotgun proteomics approach to investigate protein signatures from different tissues under drought and control conditions. Drought stressed plants showed significant changes in stomatal conductance and increased root growth compared to the control plants. Root, leaf and seed tissues were harvested and 2281 proteins were identified and quantified in total. Leaf tissue showed the largest number of significant changes (120), followed by roots (25) and seeds (10). Increased levels of root proteins involved in cell wall-, lipid-, secondary- and signaling metabolism and the concomitantly observed increased root length point to an impaired shoot-root communication under drought stress. The harvest index (HI) showed a significant reduction under drought stress. Proteins with a high correlation to the HI were identified using sparse partial least square (sPLS) analysis. Considering the importance of Pearl millet as a stress tolerant food crop, this study provides a first reference data set for future investigations of the underlying molecular mechanisms. BIOLOGICAL SIGNIFICANCE Drought stress is the most limiting factor for plant growth and crop production worldwide. At the same time drought susceptible cereal crops are among the largest producers worldwide. In contrast, Pearl millet is a drought and salt tolerant cereal crop especially used in arid and semi-arid regions by small farmers. The multifactorial molecular mechanisms of this unique drought tolerance are not known. Here, we employ shotgun proteomics for a first characterization of the Pearl millet drought stress proteome. The experimental setup and the data set generated from this study reveal comprehensive physiological and proteomic responses of the drought stressed Pearl millet plants. Our study reveals statistically significant tissue-specific protein signatures during the adaptation to drought conditions. Thus, the work provides a first reference study of the drought stress proteome and related drought responsive proteins (DRPs) in Pearl millet.

A Proteomic Workflow Using High-Throughput De Novo Sequencing Towards Complementation of Genome Information for Improved Comparative Crop Science

The proteomic study of non-model organisms, such as many crop plants, is challenging due to the lack of comprehensive genome information. Changing environmental conditions require the study and selection of adapted cultivars. Mutations, inherent to cultivars, hamper protein identification and thus considerably complicate the qualitative and quantitative comparison in large-scale systems biology approaches. With this workflow, cultivar-specific mutations are detected from high-throughput comparative MS analyses, by extracting sequence polymorphisms with de novo sequencing. Stringent criteria are suggested to filter for confidential mutations. Subsequently, these polymorphisms complement the initially used database, which is ready to use with any preferred database search algorithm. In our example, we thereby identified 26 specific mutations in two cultivars of Pisum sativum and achieved an increased number (17 %) of peptide spectrum matches.

Automated Protein Turnover Calculations from 15N Partial Metabolic Labeling LC/MS Shotgun Proteomics Data

Protein turnover is a well-controlled process in which polypeptides are constantly being degraded and subsequently replaced with newly synthesized copies. Extraction of composite spectral envelopes from complex LC/MS shotgun proteomics data can be a challenging task, due to the inherent complexity of biological samples. With partial metabolic labeling experiments this complexity increases as a result of the emergence of additional isotopic peaks. Automated spectral extraction and subsequent protein turnover calculations enable the analysis of gigabytes of data within minutes, a prerequisite for systems biology high throughput studies. Here we present a fully automated method for protein turnover calculations from shotgun proteomics data. The approach enables the analysis of complex shotgun LC/MS 15N partial metabolic labeling experiments. Spectral envelopes of 1419 peptides can be extracted within an hour. The method quantifies turnover by calculating the Relative Isotope Abundance (RIA), which is defined as the ratio between the intensity sum of all heavy (15N) to the intensity sum of all light (14N) and heavy peaks. To facilitate this process, we have developed a computer program based on our method, which is freely available to download at http://promex.pph.univie.ac.at/protover.