Proteome Scale-Protein Turnover Analysis Using High Resolution Mass Spectrometric Data from Stable-Isotope Labeled Plants

Elevated Temperature Effects on Protein Turnover Dynamics in Arabidopsis thaliana Seedlings Revealed by 15N-Stable Isotope Labeling and ProteinTurnover Algorithm

Global warming poses a threat to plant survival, impacting growth and agricultural yield. Protein turnover, a critical regulatory mechanism balancing protein synthesis and degradation, is crucial for the cellular response to environmental changes. We investigated the effects of elevated temperature on proteome dynamics in Arabidopsis thaliana seedlings using 15N-stable isotope labeling and ultra-performance liquid chromatography-high resolution mass spectrometry, coupled with the ProteinTurnover algorithm. Analyzing different cellular fractions from plants grown under 22 °C and 30 °C growth conditions, we found significant changes in the turnover rates of 571 proteins, with a median 1.4-fold increase, indicating accelerated protein dynamics under thermal stress. Notably, soluble root fraction proteins exhibited smaller turnover changes, suggesting tissue-specific adaptations. Significant turnover alterations occurred with redox signaling, stress response, protein folding, secondary metabolism, and photorespiration, indicating complex responses enhancing plant thermal resilience. Conversely, proteins involved in carbohydrate metabolism and mitochondrial ATP synthesis showed minimal changes, highlighting their stability. This analysis highlights the intricate balance between proteome stability and adaptability, advancing our understanding of plant responses to heat stress and supporting the development of improved thermotolerant crops.

Analytical methods for stable isotope labeling to elucidate rapid auxin kinetics in Arabidopsis thaliana

The phytohormone auxin plays a critical role in plant growth and development. Despite significant progress in elucidating metabolic pathways of the primary bioactive auxin, indole-3-acetic acid (IAA), over the past few decades, key components such as intermediates and enzymes have not been fully characterized, and the dynamic regulation of IAA metabolism in response to environmental signals has not been completely revealed. In this study, we established a protocol employing a highly sensitive liquid chromatography-mass spectrometry (LC-MS) instrumentation and a rapid stable isotope labeling approach. We treated Arabidopsis seedlings with two stable isotope labeled precursors ([13C6]anthranilate and [13C8, 15N1]indole) and monitored the label incorporation into proposed indolic compounds involved in IAA biosynthetic pathways. This Stable Isotope Labeled Kinetics (SILK) method allowed us to trace the turnover rates of IAA pathway precursors and product concurrently with a time scale of seconds to minutes. By measuring the entire pathways over time and using different isotopic tracer techniques, we demonstrated that these methods offer more detailed information about this complex interacting network of IAA biosynthesis, and should prove to be useful for studying auxin metabolic network in vivo in a variety of plant tissues and under different environmental conditions.

Tracking nitrogen allocation to proteome biosynthesis in a marine microbial community

Microbial growth in many environments is limited by nitrogen availability, yet there is limited understanding of how complex communities compete for and allocate this resource. Here we develop a broadly applicable approach to track biosynthetic incorporation of ¹⁵N-labelled nitrogen substrates into microbial community proteomes, enabling quantification of protein turnover and N allocation to specific cellular functions in individual taxa. Application to oligotrophic ocean surface water identifies taxa-specific substrate preferences and a distinct subset of protein functions undergoing active biosynthesis. The cyanobacterium Prochlorococcus is the most effective competitor for acquisition of ammonium and urea and shifts its proteomic allocation of N over the day/night cycle. Our approach reveals that infrastructure and protein-turnover functions comprise substantial biosynthetic demand for N in Prochlorococcus and a range of other microbial taxa. The direct interrogation of the proteomic underpinnings of N limitation with ¹⁵N-tracking proteomics illuminates how nutrient stress differentially influences metabolism in co-existing microbes.

TurnoveR: A Skyline External Tool for Analysis of Protein Turnover in Metabolic Labeling Studies

In spite of its central role in biology and disease, protein turnover is a largely understudied aspect of most proteomic studies due to the complexity of computational workflows that analyze in vivo turnover rates. To address this need, we developed a new computational tool, TurnoveR, to accurately calculate protein turnover rates from mass spectrometric analysis of metabolic labeling experiments in Skyline, a free and open-source proteomics software platform. TurnoveR is a straightforward graphical interface that enables seamless integration of protein turnover analysis into a traditional proteomics workflow in Skyline, allowing users to take advantage of the advanced and flexible data visualization and curation features built into the software. The computational pipeline of TurnoveR performs critical steps to determine protein turnover rates, including isotopologue demultiplexing, precursor-pool correction, statistical analysis, and generation of data reports and visualizations. This workflow is compatible with many mass spectrometric platforms and recapitulates turnover rates and differential changes in turnover rates between treatment groups calculated in previous studies. We expect that the addition of TurnoveR to the widely used Skyline proteomics software will facilitate wider utilization of protein turnover analysis in highly relevant biological models, including aging, neurodegeneration, and skeletal muscle atrophy.

Plant Proteome Dynamics

Proteins are intimately involved in executing and controlling virtually all cellular processes. To understand the molecular mechanisms that underlie plant phenotypes, it is essential to investigate protein expression, interactions, and modifications, to name a few. The proteome is highly dynamic in time and space, and a plethora of protein modifications, protein interactions, and network constellations are at play under specific conditions and developmental stages. Analysis of proteomes aims to characterize the entire protein complement of a particular cell type, tissue, or organism-a challenging task, given the dynamic nature of the proteome. Modern mass spectrometry-based proteomics technology can be used to address this complexity at a system-wide scale by the global identification and quantification of thousands of proteins. In this review, we present current methods and technologies employed in mass spectrometry-based proteomics and provide examples of dynamic changes in the plant proteome elucidated by proteomic approaches.

Understanding the Phytoremediation Mechanisms of Potentially Toxic Elements: A Proteomic Overview of Recent Advances

Potentially toxic elements (PTEs) such as cadmium (Cd), lead (Pb), chromium (Cr), and arsenic (As), polluting the environment, pose a significant risk and cause a wide array of adverse changes in plant physiology. Above threshold accumulation of PTEs is alarming which makes them prone to ascend along the food chain, making their environmental prevention a critical intervention. On a global scale, current initiatives to remove the PTEs are costly and might lead to more pollution. An emerging technology that may help in the removal of PTEs is phytoremediation. Compared to traditional methods, phytoremediation is eco-friendly and less expensive. While many studies have reported several plants with high PTEs tolerance, uptake, and then storage capacity in their roots, stem, and leaves. However, the wide application of such a promising strategy still needs to be achieved, partly due to a poor understanding of the molecular mechanism at the proteome level controlling the phytoremediation process to optimize the plant's performance. The present study aims to discuss the detailed mechanism and proteomic response, which play pivotal roles in the uptake of PTEs from the environment into the plant's body, then scavenge/detoxify, and finally bioaccumulate the PTEs in different plant organs. In this review, the following aspects are highlighted as: (i) PTE's stress and phytoremediation strategies adopted by plants and (ii) PTEs induced expressional changes in the plant proteome more specifically with arsenic, cadmium, copper, chromium, mercury, and lead with models describing the metal uptake and plant proteome response. Recently, interest in the comparative proteomics study of plants exposed to PTEs toxicity results in appreciable progress in this area. This article overviews the proteomics approach to elucidate the mechanisms underlying plant's PTEs tolerance and bioaccumulation for optimized phytoremediation of polluted environments.

Protein turnover in the developing Triticum aestivum grain

Protein abundance in cereal grains is determined by the relative rates of protein synthesis and protein degradation during grain development but quantitation of these rates is lacking. Through combining in vivo stable isotope labelling and in-depth quantitative proteomics, we have measured the turnover of 1400 different types of proteins during wheat grain development. We demonstrate that there is a spatiotemporal pattern to protein turnover rates which explain part of the variation in protein abundances that is not attributable to differences in wheat gene expression. We show that c. 20% of total grain adenosine triphosphate (ATP) production is used for grain proteome biogenesis and maintenance, and nearly half of this budget is invested exclusively in storage protein synthesis. We calculate that 25% of newly synthesized storage proteins are turned over during grain development rather than stored. This approach to measure protein turnover rates at proteome scale reveals how different functional categories of grain proteins accumulate, calculates the costs of protein turnover during wheat grain development and identifies the most and the least stable proteins in the developing wheat grain.

Day and night isotope labelling reveal metabolic pathway specific regulation of protein synthesis rates in Arabidopsis

Plants have a diurnal separation of metabolic fluxes and a need for differential maintenance of protein machinery in the day and night. To directly assess the output of the translation process and to estimate the ATP investment involved, the individual rates of protein synthesis and degradation of hundreds of different proteins need to be measured simultaneously. We quantified protein synthesis and degradation through pulse labelling with heavy hydrogen in Arabidopsis thaliana rosettes to allow such an assessment of ATP investment in leaf proteome homeostasis on a gene-by-gene basis. Light-harvesting complex proteins were synthesised and degraded much faster in the day (approximately 10:1), while carbon metabolism and vesicle trafficking components were translated at similar rates day or night. Few leaf proteins changed in abundance between the day and the night despite reduced protein synthesis rates at night, indicating that protein degradation rates are tightly coordinated. The data reveal how the pausing of photosystem synthesis and degradation at night allows the redirection of a decreased energy budget to a selective night-time maintenance schedule.

In vivo homopropargylglycine incorporation enables sampling, isolation and characterization of nascent proteins from Arabidopsis thaliana

Determining which proteins are actively synthesized at a given point in time and extracting a representative sample for analysis is important to understand plant responses. Here we show that the methionine (Met) analogue homopropargylglycine (HPG) enables Bio-Orthogonal Non-Canonical Amino acid Tagging (BONCAT) of a small sample of the proteins being synthesized in Arabidopsis plants or cell cultures, facilitating their click-chemistry enrichment for analysis. The sites of HPG incorporation could be confirmed by peptide mass spectrometry at Met sites throughout protein amino acid sequences and correlation with independent studies of protein labelling with ¹⁵ N verified the data. We provide evidence that HPG-based BONCAT tags a better sample of nascent plant proteins than azidohomoalanine (AHA)-based BONCAT in Arabidopsis and show that the AHA induction of Met metabolism and greater inhibition of cell growth rate than HPG probably limits AHA incorporation at Met sites in Arabidopsis. We show HPG-based BONCAT provides a verifiable method for sampling, which plant proteins are being synthesized at a given time point and enriches a small portion of new protein molecules from the bulk protein pool for identification, quantitation and subsequent biochemical analysis. Enriched nascent polypeptides samples were found to contain significantly fewer common post-translationally modified residues than the same proteins from whole plant extracts, providing evidence for age-related accumulation of post-translational modifications in plants.

Protocol: analytical methods for visualizing the indolic precursor network leading to auxin biosynthesis

BACKGROUND

The plant hormone auxin plays a central role in regulation of plant growth and response to environmental stimuli. Multiple pathways have been proposed for biosynthesis of indole-3-acetic acid (IAA), the primary auxin in a number of plant species. However, utilization of these different pathways under various environmental conditions and developmental time points remains largely unknown.

RESULTS

Monitoring incorporation of stable isotopes from labeled precursors into proposed intermediates provides a method to trace pathway utilization and characterize new biosynthetic routes to auxin. These techniques can be aided by addition of chemical inhibitors to target specific steps or entire pathways of auxin synthesis.

CONCLUSIONS

Here we describe techniques for pathway analysis in Arabidopsis thaliana seedlings using multiple stable isotope-labeled precursors and chemical inhibitors coupled with highly sensitive liquid chromatography-mass spectrometry (LC-MS) methods. These methods should prove to be useful to researchers studying routes of IAA biosynthesis in vivo in a variety of plant tissues.

Assessing Protein Synthesis and Degradation Rates in Arabidopsis thaliana Using Amino Acid Analysis

Plants continually synthesize and degrade proteins, for example, to adjust protein content during development or during adaptation to new environments. In order to estimate global protein synthesis and degradation rates in plants, we developed a relatively simple and inexpensive method using a combination of ¹³ CO₂ labeling and mass spectrometry-based analyses. Arabidopsis thaliana plants are subjected to a 24-hr ¹³ CO₂ pulse followed by a 4-day ¹² CO₂ chase. Soluble alanine and serine from total protein and glucose from cell wall material are analyzed by gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) and their ¹³ C enrichment (%) is estimated. The rate of protein synthesis during the ¹³ CO₂ pulse experiment is defined as the rate of incorporation of labeled amino acids into proteins normalized by a correction factor for incomplete enrichment in free amino acid pools. The rate of protein degradation is estimated as the difference between the rate of protein synthesis and the relative growth rate calculated using the ¹³ C enrichment of glucose from cell wall material. Degradation rates are also estimated from the ¹² CO₂ pulse experiment. The following method description includes setting up and performing labeling experiments, preparation and measurement of samples, and calculation steps. In addition, an R script is provided for the calculations. 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Setting up the ¹³ CO₂ labeling system and stable isotope labeling of Arabidopsis thaliana rosette leaves Basic Protocol 2: Extraction of soluble amino acids for GC-TOF-MS analysis Basic Protocol 3: Preparation of amino acids from total protein for GC-TOF-MS analysis Basic Protocol 4: Preparation of sugars from cell wall material for GC-TOF-MS analysis Basis Protocol 5: GC-TOF-MS analysis of ¹³ C-labeled samples and estimation of ¹³ C enrichment (%) Basis Protocol 6: Estimation of protein synthesis and degradation rates.

Diurnal dynamics of the Arabidopsis rosette proteome and phosphoproteome

Plant growth depends on the diurnal regulation of cellular processes, but it is not well understood if and how transcriptional regulation controls diurnal fluctuations at the protein level. Here, we report a high-resolution Arabidopsis thaliana (Arabidopsis) leaf rosette proteome acquired over a 12 hr light:12 hr dark diurnal cycle and the phosphoproteome immediately before and after the light-to-dark and dark-to-light transitions. We quantified nearly 5,000 proteins and 800 phosphoproteins, of which 288 fluctuated in their abundance and 226 fluctuated in their phosphorylation status. Of the phosphoproteins, 60% were quantified for changes in protein abundance. This revealed six proteins involved in nitrogen and hormone metabolism that had concurrent changes in both protein abundance and phosphorylation status. The diurnal proteome and phosphoproteome changes involve proteins in key cellular processes, including protein translation, light perception, photosynthesis, metabolism and transport. The phosphoproteome at the light-dark transitions revealed the dynamics at phosphorylation sites in either anticipation of or response to a change in light regime. Phosphorylation site motif analyses implicate casein kinase II and calcium/calmodulin-dependent kinases among the primary light-dark transition kinases. The comparative analysis of the diurnal proteome and diurnal and circadian transcriptome established how mRNA and protein accumulation intersect in leaves during the diurnal cycle of the plant.

Studying the Temporal Dynamics of the Gut Microbiota Using Metabolic Stable Isotope Labeling and Metaproteomics

The gut microbiome and its metabolic processes are dynamic systems. Surprisingly, our understanding of gut microbiome dynamics is limited. Here, we report a metaproteomic workflow that involves protein stable isotope probing (protein-SIP) and identification/quantification of partially labeled peptides. We also developed a package, which we call MetaProfiler, that corrects for false identifications and performs phylogenetic and time series analysis for the study of microbiome dynamics. From the stool sample of five mice that were fed with ¹⁵N hydrolysate from Ralstonia eutropha, we identified 12 326 nonredundant unlabeled peptides, of which 8256 of their heavy counterparts were quantified. These peptides revealed incorporation profiles over time that were different between and within taxa, as well as between and within clusters of orthologous groups (COGs). Our study helps unravel the complex dynamics of protein synthesis and bacterial dynamics in the mouse microbiome. MetaProfiler and the bioinformatic pipeline are available at https://github.com/northomics/MetaProfiler.git.

Enzymes as Parts in Need of Replacement - and How to Extend Their Working Life

Enzymes catalyze reactions in vivo at different rates and each enzyme molecule has a lifetime limit before it is degraded and replaced to enable catalysis to continue. Considering these rates together as a unitless ratio of catalytic cycles until replacement (CCR) provides a new quantitative tool to assess the replacement schedule of and energy investment into enzymes as they relate to function. Here, we outline the challenges of determining CCRs and new approaches to overcome them and then assess the CCRs of selected enzymes in bacteria and plants to reveal a range of seven orders of magnitude for this ratio. Modifying CCRs in plants holds promise to lower cellular costs, to tailor enzymes for particular environments, and to breed enzyme improvements for crop productivity.

Silencing of OsCV (chloroplast vesiculation) maintained photorespiration and N assimilation in rice plants grown under elevated CO2

High CO₂ concentrations stimulate net photosynthesis by increasing CO₂ substrate availability for Rubisco, simultaneously suppressing photorespiration. Previously, we reported that silencing the chloroplast vesiculation (cv) gene in rice increased source fitness, through the maintenance of chloroplast stability and the expression of photorespiration-associated genes. Because high atmospheric CO₂ conditions diminished photorespiration, we tested whether CV silencing might be a viable strategy to improve the effects of high CO₂ on grain yield and N assimilation in rice. Under elevated CO₂ , OsCV expression was induced, and OsCV was targeted to peroxisomes where it facilitated the removal of OsPEX11-1 from the peroxisome and delivered it to the vacuole for degradation. This process correlated well with the reduction in the number of peroxisomes, the decreased catalase activity and the increased H₂ O₂ content in wild-type plants under elevated CO₂ . At elevated CO₂ , CV-silenced rice plants maintained peroxisome proliferation and photorespiration and displayed higher N assimilation than wild-type plants. This was supported by higher activity of enzymes involved in NO₃^- and NH₄⁺ assimilation and higher total and seed protein contents. Co-immunoprecipitation of OsCV-interacting proteins suggested that, similar to its role in chloroplast protein turnover, OsCV acted as a scaffold, binding peroxisomal proteins.

Tracing metabolic flux through time and space with isotope labeling experiments

Metabolism is dynamic and must function in context-specific ways to adjust to changes in the surrounding cellular and ecological environment. When isotopic tracers are used, metabolite flow (i.e. metabolic flux) can be quantified through biochemical networks to assess metabolic pathway operation. The cellular activities considered across multiple tissues and organs result in the observed phenotype and can be analyzed to discover emergent, whole-system properties of biology and elucidate misconceptions about network operation. However, temporal and spatial challenges remain significant hurdles and require novel approaches and creative solutions. We survey current investigations in higher plant and animal systems focused on dynamic isotope labeling experiments, spatially resolved measurement strategies, and observations from re-analysis of our own studies that suggest prospects for future work. Related discoveries will be necessary to push the frontier of our understanding of metabolism to suggest novel solutions to cure disease and feed a growing future world population.

Bayesian Confidence Intervals for Multiplexed Proteomics Integrate Ion-statistics with Peptide Quantification Concordance

Multiplexed proteomics has emerged as a powerful tool to measure relative protein expression levels across multiple conditions. The relative protein abundances are inferred by comparing the signals generated by isobaric tags, which encode the samples' origins. Intuitively, the trust associated with a protein measurement depends on the similarity of ratios from the protein's peptides and the signal-strength of these measurements. However, typically the average peptide ratio is reported as the estimate of relative protein abundance, which is only the most likely ratio with a very naive model. Moreover, there is no sense on the confidence in these measurements. Here, we present a mathematically rigorous approach that integrates peptide signal strengths and peptide-measurement agreement into an estimation of the true protein ratio and the associated confidence (BACIQ). The main advantages of BACIQ are: (1) It removes the need to threshold reported peptide signal based on an arbitrary cut-off, thereby reporting more measurements from a given experiment; (2) Confidence can be assigned without replicates; (3) For repeated experiments BACIQ provides confidence intervals for the union, not the intersection, of quantified proteins; (4) For repeated experiments, BACIQ confidence intervals are more predictive than confidence intervals based on protein measurement agreement. To demonstrate the power of BACIQ we reanalyzed previously published data on subcellular protein movement on treatment with an Exportin-1 inhibiting drug. We detect ∼2× more highly significant movers, down to subcellular localization changes of ∼1%. Thus, our method drastically increases the value obtainable from quantitative proteomics experiments, helping researchers to interpret their data and prioritize resources. To make our approach easily accessible we distribute it via a Python/Stan package.

A molecular toolbox for studying protein degradation in mammalian cells

Protein degradation is a crucial regulatory process in maintaining cellular proteostasis. The selective degradation of intracellular proteins controls diverse cellular and biochemical processes in all kingdoms of life. Targeted protein degradation is implicated in controlling the levels of regulatory proteins as well as eliminating misfolded and any otherwise abnormal proteins. Deregulation of protein degradation is concomitant with the progression of various neurodegenerative disorders such as Parkinson's and Alzheimer's diseases. Thus, methods of measuring metabolic half-lives of proteins greatly influence our understanding of the diverse functions of proteins in mammalian cells including neuronal cells. Historically, protein degradation rates have been studied via exploiting methods that estimate overall protein degradation or focus on few individual proteins. Notably, with the recent technical advances and developments in proteomic and imaging techniques, it is now possible to measure degradation rates of a large repertoire of defined proteins and analyze the degradation profile in a detailed spatio-temporal manner, with the aim of determining proteome-wide protein stabilities upon different physiological conditions. Herein, we discuss some of the classical and novel methods for determining protein degradation rates highlighting the crucial role of some state of art approaches in deciphering the global impact of dynamic nature of targeted degradation of cellular proteins. This article is part of the Special Issue "Proteomics".

Metabolic Patterns in Spirodela polyrhiza Revealed by 15N Stable Isotope Labeling of Amino Acids in Photoautotrophic, Heterotrophic, and Mixotrophic Growth Conditions

In this study we describe a [¹⁵N] stable isotopic labeling study of amino acids in Spirodela polyrhiza (common duckweed) grown under three different light and carbon input conditions which represent unique potential metabolic modes. Plants were grown with a light cycle, either with supplemental sucrose (mixotrophic) or without supplemental sucrose (photoautotrophic) and in the dark with supplemental sucrose (heterotrophic). Labeling patterns, pool sizes (both metabolically active and inactive), and kinetics/turnover rates were estimated for 17 of the proteinogenic amino acids. Estimation of these parameters followed several overall trends. First, most amino acids showed plateaus in labeling patterns of <100% [¹⁵N]-labeling, indicating the possibility of a large proportion of amino acids residing in metabolically inactive metabolite pools. Second, total pool sizes appear largest in the dark (heterotrophic) condition, whereas active pool sizes appeared to be largest in the light with sucrose (mixotrophic) growth condition. In contrast turnover measurements based on pool size were highest overall in the light with sucrose experiment, with the exception of leucine/isoleucine, lysine, and arginine, which all showed higher turnover in the dark. K-means clustering analysis also revealed more rapid turnover in the light treatments with many amino acids clustering in lower-turnover groups. Emerging insights from other research were also supported, such as the prevalence of alternate pathways for serine metabolism in non-photosynthetic cells. These data provide extensive novel information on amino acid pool size and kinetics in S. polyrhiza and can serve as groundwork for future metabolic studies.

Protein Turnover in Aging and Longevity

Progressive loss of proteostasis is a hallmark of aging that is marked by declines in various components of proteostasis machinery, including: autophagy, ubiquitin-mediated degradation, protein synthesis, and others. While declines in proteostasis have historically been observed as changes in these processes, or as bulk changes in the proteome, recent advances in proteomic methodologies have enabled the comprehensive measurement of turnover directly at the level of individual proteins in vivo. These methods, which utilize a combination of stable-isotope labeling, mass spectrometry, and specialized software analysis, have now been applied to various studies of aging and longevity. Here we review the role of proteostasis in aging and longevity, with a focus on the proteomic methods available to conduct protein turnover in aging models and the insights these studies have provided thus far.

Delaying chloroplast turnover increases water-deficit stress tolerance through the enhancement of nitrogen assimilation in rice

Abiotic stress-induced senescence in crops is a process particularly affecting the photosynthetic apparatus, decreasing photosynthetic activity and inducing chloroplast degradation. A pathway for stress-induced chloroplast degradation that involves the CHLOROPLAST VESICULATION (CV) gene was characterized in rice (Oryza sativa) plants. OsCV expression was up-regulated with the age of the plants and when plants were exposed to water-deficit conditions. The down-regulation of OsCV expression contributed to the maintenance of the chloroplast integrity under stress. OsCV-silenced plants displayed enhanced source fitness (i.e. carbon and nitrogen assimilation) and photorespiration, leading to water-deficit stress tolerance. Co-immunoprecipitation, intracellular co-localization, and bimolecular fluorescence demonstrated the in vivo interaction between OsCV and chloroplastic glutamine synthetase (OsGS2), affecting source-sink relationships of the plants under stress. Our results would indicate that the OsCV-mediated chloroplast degradation pathway is involved in the regulation of nitrogen assimilation during stress-induced plant senescence.

A reference-based protein degradation assay without global translation inhibitors

Although it is widely appreciated that the use of global translation inhibitors, such as cycloheximide, in protein degradation assays may result in artefacts, these inhibitors continue to be employed, owing to the absence of robust alternatives. We describe here the promoter reference technique (PRT), an assay for protein degradation with two advantageous features: a reference protein and a gene-specific inhibition of translation. In PRT assays, one measures, during a chase, the ratio of a test protein to a long-lived reference protein, a dihydrofolate reductase (DHFR). The test protein and DHFR are coexpressed, in the yeast Saccharomyces cerevisiae, on a low-copy plasmid from two identical P _TDH3 promoters containing additional, previously developed DNA elements. Once transcribed, these elements form 5'-RNA aptamers that bind to the added tetracycline, which represses translation of aptamer-containing mRNAs. The selectivity of repression avoids a global inhibition of translation. This selectivity is particularly important if a component of a relevant proteolytic pathway (e.g. a specific ubiquitin ligase) is itself short-lived. We applied PRT to the Pro/N-end rule pathway, whose substrates include the short-lived Mdh2 malate dehydrogenase. Mdh2 is targeted for degradation by the Gid4 subunit of the GID ubiquitin ligase. Gid4 is also a metabolically unstable protein. Through analyses of short-lived Mdh2 as a target of short-lived Gid4, we illustrate the advantages of PRT over degradation assays that lack a reference and/or involve cycloheximide. In sum, PRT avoids the use of global translation inhibitors during a chase and also provides a "built-in" reference protein.

Protein Degradation Rate in Arabidopsis thaliana Leaf Growth and Development

We applied ¹⁵N labeling approaches to leaves of the Arabidopsis thaliana rosette to characterize their protein degradation rate and understand its determinants. The progressive labeling of new peptides with ¹⁵N and measuring the decrease in the abundance of >60,000 existing peptides over time allowed us to define the degradation rate of 1228 proteins in vivo. We show that Arabidopsis protein half-lives vary from several hours to several months based on the exponential constant of the decay rate for each protein. This rate was calculated from the relative isotope abundance of each peptide and the fold change in protein abundance during growth. Protein complex membership and specific protein domains were found to be strong predictors of degradation rate, while N-end amino acid, hydrophobicity, or aggregation propensity of proteins were not. We discovered rapidly degrading subunits in a variety of protein complexes in plastids and identified the set of plant proteins whose degradation rate changed in different leaves of the rosette and correlated with leaf growth rate. From this information, we have calculated the protein turnover energy costs in different leaves and their key determinants within the proteome.

Recent advances in stable isotope-enabled mass spectrometry-based plant metabolomics

Methods employing isotope labeled compounds have been an important part of the bioanalytical canon for many decades. The past fifteen years have seen the development of many new approaches using stable (non-radioactive) isotopes as labels for high-throughput bioanalytical, 'omics-scale' measurements of metabolites (metabolomics) and proteins (proteomics). This review examines stable isotopic labeling approaches that have been developed for labeling whole intact plants, plant tissues, or crude extracts of plant materials with stable isotopes (mainly using ²H, ¹³C, ¹⁵N, ¹⁸O or ³⁴S). The application of metabolome-scale labeling for improving metabolite annotation, metabolic pathway elucidation, and relative quantification in mass spectrometry-based metabolomics of plants is also reviewed.