Proteome analysis of chloroplasts from the moss Physcomitrella patens (Hedw.) B.S.G

High levels of glucose alter Physcomitrella patens metabolism and trigger a differential proteomic response

Sugars act not only as substrates for plant metabolism, but also have a pivotal role in signaling pathways. Glucose signaling has been widely studied in the vascular plant Arabidopsis thaliana, but it has remained unexplored in non-vascular species such as Physcomitrella patens. To investigate P. patens response to high glucose treatment, we explored the dynamic changes in metabolism and protein population by applying a metabolomic fingerprint analysis (DIESI-MS), carbohydrate and chlorophyll quantification, Fv/Fm determination and label-free untargeted proteomics. Glucose feeding causes specific changes in P. patens metabolomic fingerprint, carbohydrate contents and protein accumulation, which is clearly different from those of osmotically induced responses. The maximal rate of PSII was not affected although chlorophyll decreased in both treatments. The biological process, cellular component, and molecular function gene ontology (GO) classifications of the differentially expressed proteins indicate the translation process is the most represented category in response to glucose, followed by photosynthesis, cellular response to oxidative stress and protein refolding. Importantly, although several proteins have high fold changes, these proteins have no predicted identity. The most significant discovery of our study at the proteome level is that high glucose increase abundance of proteins related to the translation process, which was not previously evidenced in non-vascular plants, indicating that regulation by glucose at the translational level is a partially conserved response in both plant lineages. To our knowledge, this is the first time that metabolome fingerprint and proteomic analyses are performed after a high sugar treatment in non-vascular plants. These findings unravel evolutionarily shared and differential responses between vascular and non-vascular plants.

The Physcomitrella patens Chloroplast Proteome Changes in Response to Protoplastation

Plant protoplasts are widely used for genetic manipulation and functional studies in transient expression systems. However, little is known about the molecular pathways involved in a cell response to the combined stress factors resulted from protoplast generation. Plants often face more than one type of stress at a time, and how plants respond to combined stress factors is therefore of great interest. Here, we used protoplasts of the moss Physcomitrella patens as a model to study the effects of short-term stress on the chloroplast proteome. Using label-free comparative quantitative proteomic analysis (SWATH-MS), we quantified 479 chloroplast proteins, 219 of which showed a more than 1.4-fold change in abundance in protoplasts. We additionally quantified 1451 chloroplast proteins using emPAI. We observed degradation of a significant portion of the chloroplast proteome following the first hour of stress imposed by the protoplast isolation process. Electron-transport chain (ETC) components underwent the heaviest degradation, resulting in the decline of photosynthetic activity. We also compared the proteome changes to those in the transcriptional level of nuclear-encoded chloroplast genes. Globally, the levels of the quantified proteins and their corresponding mRNAs showed limited correlation. Genes involved in the biosynthesis of chlorophyll and components of the outer chloroplast membrane showed decreases in both transcript and protein abundance. However, proteins like dehydroascorbate reductase 1 and 2-cys peroxiredoxin B responsible for ROS detoxification increased in abundance. Further, genes such as thylakoid ascorbate peroxidase were induced at the transcriptional level but down-regulated at the proteomic level. Together, our results demonstrate that the initial chloroplast reaction to stress is due changes at the proteomic level.

The mitochondrial proteome of the moss Physcomitrella patens

Extant basal land plants are routinely used to trace plant evolution and to track strategies for high abiotic stress resistance. Whereas the structure of mitochondrial genomes and RNA editing are already well studied, mitochondrial proteome research is restricted to a few data sets. While the mitochondrial proteome of the model moss Physcomitrella patens is covered to an estimated 15-25% by proteomic evidence to date, the available data have already provided insights into the evolution of metabolic compartmentation, dual targeting and mitochondrial heterogeneity. This review summarizes the current knowledge about the mitochondrial proteome of P. patens, and gives a perspective on its use as a mitochondrial model system. Its amenability to gene editing, metabolic labelling as well as fluorescence microscopy provides a unique platform to study open questions in mitochondrial biology, such as regulation of protein stability, responses to stress and connectivity to other organelles. Future challenges will include improving the proteomic resources for P. patens, and to link protein inventories and modifications as well as evolutionary differences to the functional level.

A proteomic approach to Physcomitrella patens rhizoid exudates

The interaction between plants and the surrounding environment has been widely studied, specially the defence reactions and the plant-plant interactions. One of the most remarkable metabolic features of plant roots is the ability to secrete a vast array of compounds into the rhizosphere, not only of low molecular weight but also polysaccharides and proteins. Here, we took advantage of proteomics to study the rhizoid exudates of Physcomitrella patens at early and late development stages (7 and 28 days of culture in liquid medium). Samples were extracted, separated and detected with nanoLC-MALDI-TOF/TOF MS/MS, identifying 47 proteins at the development stage of 7 days, and 66 proteins at 28 days. Moreover, 21 proteins were common to the two analyzed periods. All the identified proteins were classified into 8 functional categories: response to stress, response to stimulus, oxido-reduction, cell wall modification, photosynthesis and carbohydrate metabolism, transport, DNA metabolic process and regulation/signalling. Our results show important differences in the protein expression profile along the development of P. patens, mainly at the level of regulation- and senescence-related proteins. Defence-related proteins, such as chitinases, thaumatins and peroxidases have a major role in the interaction of P. patens with the environment.

Green targeting predictor and ambiguous targeting predictor 2: the pitfalls of plant protein targeting prediction and of transient protein expression in heterologous systems

The challenges of plant protein targeting prediction are the existence of dual subcellular targets and the bias of experimentally confirmed data towards few and mostly nonplant model species. To assess whether training with proteins from evolutionarily distant species has a negative impact on prediction accuracy, we developed the Green Targeting Predictor tool, which was trained with a species-specific data set for Physcomitrella patens. Its performance was compared with that of the same tool trained with a mixed data set. In addition, we updated the Ambiguous Targeting Predictor. We found that predictions deviated from in vivo observations predominantly for proteins diverging within the green lineage, as well as for dual targeted proteins. To evaluate the usefulness of heterologous expression systems, selected proteins were subjected to localization studies in P. patens, Arabidopsis thaliana and Nicotiana tabacum. Four out of six proteins that show dual targeting in the original plant system were located only in a single compartment in one or both heterologous systems. We conclude that targeting signals of divergent plant species exhibit differences, calling for custom in silico and in vivo approaches when aiming to unravel the actual distribution patterns of proteins within a plant cell.