Synthesis/degradation ratio mass spectrometry for measuring relative dynamic protein turnover

Turnover of the extracellular polymeric matrix of granules performing biological phosphate removal

Polyphosphate accumulating organisms (PAOs) are responsible for enhanced biological phosphate removal (EBPR) from wastewater, where they grow embedded in a matrix of extracellular polymeric substances (EPS). EPSs comprise a mixture of biopolymers like polysaccharides or (glyco)proteins. Despite previous studies, little is known about the dynamics of EPS in mixed cultures, and their production by PAOs and potential consumption by flanking microbes. EPSs are biodegradable and have been suggested to be a substrate for other organisms in the community. Studying EPS turnover can help elucidate their biosynthesis and biodegradation cycles. We analyzed the turnover of proteins and polysaccharides in the EPS of an enrichment culture of PAOs relative to the turnover of internal proteins. An anaerobic-aerobic sequencing batch reactor (SBR) simulating EBPR conditions was operated to enrich for PAOs. After achieving a stable culture, carbon source was switched to uniformly ¹³C-labeled acetate. Samples were collected at the end of each aerobic phase. EPSs were extracted by alkaline treatment. ¹³C enrichment in proteins and sugars (after hydrolysis of polysaccharides) in the extracted EPS were measured by mass spectrometry. The average turnover rate of sugars and proteins (0.167 and 0.192 d^-1 respectively) was higher than the expected value based on the solid removal rate (0.132 d^-1), and no significant difference was observed between intracellular and extracellular proteins. This indicates that EPS from the PAO enriched community is not selectively degraded by flanking populations under stable EBPR process conditions. Instead, we observed general decay of biomass, which corresponds to a value of 0.048 d^-1. KEY POINTS: • Proteins showed a higher turnover rate than carbohydrates. • Turnover of EPS was similar to the turnover of intracellular proteins. • EPS is not preferentially consumed by flanking populations.

Shotgun proteomics of extracellular matrix in late senescent human dermal fibroblasts reveals a down-regulated fibronectin-centered network

Extracellular matrix (ECM) proteins play a pivotal role in cell growth and differentiation. To characterize aged ECM proteins, we compared the proteomes by shotgun method of young (passage #15) and late senescent (passage #40) human dermal fibroblasts (HDFs) using SDS-PAGE coupled with LC–MS/MS. The relative abundance of identified proteins was determined using mol% of individual proteins as a semi-quantitative index. Fifteen ECM proteins including apolipoprotein B (APOB) and high-temperature requirement factor 1 (HTRA1) were up-regulated, whereas 50 proteins including fibronectin 1 (FN1) and vitronectin (VTN) were down-regulated in late senescent HDFs. The identified ECM proteins combined with plasma membrane were queried to construct the protein–protein interaction network using Ingenuity Pathways Analysis, resulting in a distinct FN1-centered network. Of differentially abundant ECM proteins in shotgun proteomics, the protein levels of FN1, VTN, APOB, and HTRA1 were verified by immunoblot analysis. The results suggest that the aging process in HDFs might be finally involved in the impaired FN1 regulatory ECM network combined with altered interaction of neighboring proteins. Shotgun proteomics of highly aged HDFs provides insight for further studies of late senescence-related alterations in ECM proteins.

Proteome Turnover Analysis in Haloferax volcanii by a Heavy Isotope Multilabeling Approach

The cellular protein repertoire is highly dynamic and responsive to internal or external stimuli. Its changes are largely the consequence of the combination of protein synthesis and degradation, referred collectively as protein turnover. Different proteomics techniques have been developed to determine the whole proteome turnover of a cell, but very few have been applied to archaea. In this chapter we describe a heavy isotope multilabeling method that allowed the successful analysis of relative protein synthesis and degradation rates on the proteome scale of the halophilic archaeon Haloferax volcanii. This method combines ¹⁵N and ¹³C isotope metabolic labeling with high-resolution mass spectrometry and data analysis tools (QuPE web-based platform) and could be applied to different archaea.

Impact of Target Turnover on the Translation of Drug-Target Residence Time to Time-Dependent Antibacterial Activity

The translation of time-dependent drug-target occupancy to extended pharmacological activity at low drug concentration depends on factors such as target vulnerability and the rate of target turnover. Previously, we demonstrated that the postantibiotic effect (PAE) caused by inhibitors of bacterial drug targets could be used to assess target vulnerability, and that high levels of target vulnerability coupled with relatively low rates of target resynthesis resulted in a strong correlation between drug-target residence time and the PAE following compound washout. Although the residence time of inhibitors on UDP-3-O-acyl-N-acetylglucosamine deacetylase (LpxC) in Pseudomonas aeruginosa (paLpxC) results in significant PAE, inhibitors of the equivalent enzyme in Escherichia coli (ecLpxC) do not cause a PAE. Hyperactivity of the fatty acid biosynthesis enzyme FabZ or the inclusion of sub-MIC levels of azithromycin lead to the observation of a PAE for three inhibitors of ecLpxC. FabZ hyperactivity has been shown to stabilize ecLpxC, and using mass spectrometry, we demonstrate that the appearance of a PAE can be directly linked to a 3-fold increase in the stability of ecLpxC. These studies substantiate the importance of target turnover in time-dependent drug activity.

Proteome Turnover in the Spotlight: Approaches, Applications, and Perspectives

In all cells, proteins are continuously synthesized and degraded to maintain protein homeostasis and modify gene expression levels in response to stimuli. Collectively, the processes of protein synthesis and degradation are referred to as protein turnover. At a steady state, protein turnover is constant to maintain protein homeostasis, but in dynamic responses, proteins change their rates of synthesis and degradation to adjust their proteomes to internal or external stimuli. Thus, probing the kinetics and dynamics of protein turnover lends insight into how cells regulate essential processes such as growth, differentiation, and stress response. Here, we outline historical and current approaches to measuring the kinetics of protein turnover on a proteome-wide scale in both steady-state and dynamic systems, with an emphasis on metabolic tracing using stable isotope-labeled amino acids. We highlight important considerations for designing proteome turnover experiments, key biological findings regarding the conserved principles of proteome turnover regulation, and future perspectives for both technological and biological investigation.

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.

Hypothesis: protein and RNA attributes are continuously optimized over time

Background

Little is known why proteins and RNAs exhibit half-lives varying over several magnitudes. Despite many efforts, a conclusive link between half-lives and gene function could not be established suggesting that other determinants may influence these molecular attributes.

Results

Here, I find that with increasing gene age there is a gradual and significant increase of protein and RNA half-lives, protein structure, and other molecular attributes that tend to affect protein abundance. These observations are accommodated in a hypothesis which posits that new genes at ‘birth’ are not optimized and thus their products exhibit low half-lives and less structure but continuous mutagenesis eventually improves these attributes. Thus, the protein and RNA products of the oldest genes obtained their high degrees of stability and structure only after billions of years while the products of younger genes had less time to be optimized and are therefore less stable and structured. Because more stable proteins with lower turnover require less transcription to maintain the same level of abundance, reduced transcription-associated mutagenesis (TAM) would fixate the changes by increasing gene conservation.

Conclusions

Consequently, the currently observed diversity of molecular attributes is a snapshot of gene products being at different stages along their temporal path of optimization.

Guidelines for evaluating myocardial cell death

Cell death is a fundamental process in cardiac pathologies. Recent studies have revealed multiple forms of cell death, and several of them have been demonstrated to underlie adverse cardiac remodeling and heart failure. With the expansion in the area of myocardial cell death and increasing concerns over rigor and reproducibility, it is important and timely to set a guideline for the best practices of evaluating myocardial cell death. There are six major forms of regulated cell death observed in cardiac pathologies, namely apoptosis, necroptosis, mitochondrial-mediated necrosis, pyroptosis, ferroptosis, and autophagic cell death. In this article, we describe the best methods to identify, measure, and evaluate these modes of myocardial cell death. In addition, we discuss the limitations of currently practiced myocardial cell death mechanisms.

Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) for Quantitative Proteomics

Stable isotope labeling by amino acids in cell culture (SILAC) is a powerful approach for high-throughput quantitative proteomics. SILAC allows highly accurate protein quantitation through metabolic encoding of whole cell proteomes using stable isotope labeled amino acids. Since its introduction in 2002, SILAC has become increasingly popular. In this chapter we review the methodology and application of SILAC, with an emphasis on three research areas: dynamics of posttranslational modifications, protein-protein interactions, and protein turnover.

Perspectives on potentiating immunocapture-LC-MS for the bioanalysis of biotherapeutics and biomarkers

The integration of ligand-binding assay and LC-MS/MS (immunocapture-LC-MS) has unleashed the combined advantages of both powerful techniques for addressing the ever increasing bioanalytical challenges for biotherapeutics and biomarker assays. The highly specific, selective and sensitive characteristics of the immunocapture-LC-MS-based assays have enabled the determination of biotherapeutics and biomarkers in biomatrices with ease of method development, less requirements on key reagents as well as structural specificity for endogenous and engineered biomolecules. In addition, the versatile immunocapture-LC-MS technology has expanded into many challenging areas to enhance mechanistic studies of drug interactions with their targets. This paper intends to summarize our perspectives on enhancing the use of immunocapture-LC-MS in drug discovery and development for emerging new modalities.

EpiProfile 2.0: A Computational Platform for Processing Epi-Proteomics Mass Spectrometry Data

Epigenetics has become a fundamental scientific discipline with various implications for biology and medicine. Epigenetic marks, mostly DNA methylation and histone post-translational modifications (PTMs), play important roles in chromatin structure and function. Accurate quantification of these marks is an ongoing challenge due to the variety of modifications and their wide dynamic range of abundance. Here we present EpiProfile 2.0, an extended version of our 2015 software (v1.0), for accurate quantification of histone peptides based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. EpiProfile 2.0 is now optimized for data-independent acquisition through the use of precursor and fragment extracted ion chromatography to accurately determine the chromatographic profile and to discriminate isobaric forms of peptides. The software uses an intelligent retention time prediction trained on the analyzed samples to enable accurate peak detection. EpiProfile 2.0 supports label-free and isotopic labeling, different organisms, known sequence mutations in diseases, different derivatization strategies, and unusual PTMs (such as acyl-derived modifications). In summary, EpiProfile 2.0 is a universal and accurate platform for the quantification of histone marks via LC-MS/MS. Being the first software of its kind, we anticipate that EpiProfile 2.0 will play a fundamental role in epigenetic studies relevant to biology and translational medicine. EpiProfile is freely available at https://github.com/zfyuan/EpiProfile2.0_Family .

Deuterium- and Tritium-Labelled Compounds: Applications in the Life Sciences

Hydrogen isotopes are unique tools for identifying and understanding biological and chemical processes. Hydrogen isotope labelling allows for the traceless and direct incorporation of an additional mass or radioactive tag into an organic molecule with almost no changes in its chemical structure, physical properties, or biological activity. Using deuterium-labelled isotopologues to study the unique mass-spectrometric patterns generated from mixtures of biologically relevant molecules drastically simplifies analysis. Such methods are now providing unprecedented levels of insight in a wide and continuously growing range of applications in the life sciences and beyond. Tritium (³ H), in particular, has seen an increase in utilization, especially in pharmaceutical drug discovery. The efforts and costs associated with the synthesis of labelled compounds are more than compensated for by the enhanced molecular sensitivity during analysis and the high reliability of the data obtained. In this Review, advances in the application of hydrogen isotopes in the life sciences are described.

A Simple Light Isotope Metabolic Labeling (SLIM-labeling) Strategy: A Powerful Tool to Address the Dynamics of Proteome Variations In Vivo

Many quantitative proteomics strategies rely on in vivo metabolic incorporation of amino acids with modified stable isotope profiles into proteins. These methods give rise to multiple ions for each peptide, with possible distortion of the isotopolog distribution, making the overall analytical process complex. We validated an alternative strategy, simple light isotope metabolic labeling (SLIM-labeling), which alleviates many of these problems. SLIM-labeling is based on the in vivo reduction of the isotopic composition of proteins using metabolic precursors with a unique light isotope composition to label all amino acids. This brings a new dimension to in-depth, high resolution MS-based quantitative proteomics. Here, we describe a ¹²C-based SLIM-labeling strategy using U-[¹²C]-glucose as the metabolic precursor of all amino acids in the pathogenic yeast Candida albicans Monoisotopic ion intensity increased exponentially following ¹²C enrichment, substantially improving peptide identification scores and protein sequence coverage in bottom-up analyses. Multiplexing samples of ¹²C composition varying from natural abundance (98.93%) to 100% makes it possible to address relative quantification issues, keeping all the critical information for each peptide within a single isotopolog cluster. We applied this method to measure, for the first time, protein turnover at the proteome scale in Candida albicans and its modulation by inhibitors of the proteasome and vacuolar protein degradation systems.

Comparative protein profiles of the Ambrosia plants

Ragweed pollen is primarily responsible for the hay fever allergies of sufferers throughout the world. A proteome study of three ragweed plants (Ambrosia artemisiifolia, Ambrosia trifida, and Ambrosia psilostachya) was undertaken to document and compare their protein profiles. Proteins extracted from the pollen of the three plants were subjected to one dimensional electrophoresis followed by tandem liquid chromatography-mass spectroscopy. Peptide sequence mapping permitted discovery of proteins not previously reported for all three plants and 45% of the identified proteins were shared by all three of them. Application of stringent criteria revealed not only a majority of known allergens for short ragweed but also allergens not previously reported for the other two plants. Additionally, potentially allergy inducing enolases are reported for the three plants. These results suggest that all three ragweed plants could contribute to the allergy malady.

Heavy Sugar and Heavy Water Create Tunable Intact Protein Mass Increases for Quantitative Mass Spectrometry in Any Feed and Organism

Stable isotope labeling techniques for quantitative top-down proteomics face unique challenges. These include unpredictable mass shifts following isotope labeling, which impedes analysis of unknown proteins and complex mixtures and exponentially greater susceptibility to incomplete isotope incorporation, manifesting as broadening of labeled intact protein peaks. Like popular bottom-up isotope labeling techniques, most top-down labeling methods are restricted to defined media/feed as well as amino acid auxotrophic organisms. We present a labeling method optimized for top-down proteomics that overcomes these challenges. We demonstrated this method through the spiking of ¹³C-sugar or ²H-water into standard laboratory feedstocks, resulting in tunable intact protein mass increases (TIPMI). After mixing of labeled and unlabeled samples, direct comparison of light and heavy peaks allowed for the relative quantitation of intact proteins in three popular model organisms, including prokaryotic and eukaryotic microorganisms and an animal. This internal standard method proved to be more accurate than label-free quantitation in our hands. Advantages over top-down SILAC include working equally well in nutrient-rich media, conceivably expanding applicability to any organism and all classes of biomolecules, not requiring high-resolving power MS for quantitation and being relatively inexpensive.

A simplified calculation procedure for mass isotopomer distribution analysis (MIDA) based on multiple linear regression

We have developed a novel, rapid and easy calculation procedure for Mass Isotopomer Distribution Analysis based on multiple linear regression which allows the simultaneous calculation of the precursor pool enrichment and the fraction of newly synthesized labelled proteins (fractional synthesis) using linear algebra. To test this approach, we used the peptide RGGGLK as a model tryptic peptide containing three subunits of glycine. We selected glycine labelled in two ¹³ C atoms (¹³ C₂ -glycine) as labelled amino acid to demonstrate that spectral overlap is not a problem in the proposed methodology. The developed methodology was tested first in vitro by changing the precursor pool enrichment from 10 to 40% of ¹³ C₂ -glycine. Secondly, a simulated in vivo synthesis of proteins was designed by combining the natural abundance RGGGLK peptide and 10 or 20% ¹³ C₂ -glycine at 1 : 1, 1 : 3 and 3 : 1 ratios. Precursor pool enrichments and fractional synthesis values were calculated with satisfactory precision and accuracy using a simple spreadsheet. This novel approach can provide a relatively rapid and easy means to measure protein turnover based on stable isotope tracers. Copyright © 2016 John Wiley & Sons, Ltd.

Mitochondrial Function, Biology, and Role in Disease: A Scientific Statement From the American Heart Association

Cardiovascular disease is a major leading cause of morbidity and mortality in the United States and elsewhere. Alterations in mitochondrial function are increasingly being recognized as a contributing factor in myocardial infarction and in patients presenting with cardiomyopathy. Recent understanding of the complex interaction of the mitochondria in regulating metabolism and cell death can provide novel insight and therapeutic targets. The purpose of this statement is to better define the potential role of mitochondria in the genesis of cardiovascular disease such as ischemia and heart failure. To accomplish this, we will define the key mitochondrial processes that play a role in cardiovascular disease that are potential targets for novel therapeutic interventions. This is an exciting time in mitochondrial research. The past decade has provided novel insight into the role of mitochondria function and their importance in complex diseases. This statement will define the key roles that mitochondria play in cardiovascular physiology and disease and provide insight into how mitochondrial defects can contribute to cardiovascular disease; it will also discuss potential biomarkers of mitochondrial disease and suggest potential novel therapeutic approaches.

Assessing Cardiac Metabolism: A Scientific Statement From the American Heart Association

In a complex system of interrelated reactions, the heart converts chemical energy to mechanical energy. Energy transfer is achieved through coordinated activation of enzymes, ion channels, and contractile elements, as well as structural and membrane proteins. The heart's needs for energy are difficult to overestimate. At a time when the cardiovascular research community is discovering a plethora of new molecular methods to assess cardiac metabolism, the methods remain scattered in the literature. The present statement on "Assessing Cardiac Metabolism" seeks to provide a collective and curated resource on methods and models used to investigate established and emerging aspects of cardiac metabolism. Some of those methods are refinements of classic biochemical tools, whereas most others are recent additions from the powerful tools of molecular biology. The aim of this statement is to be useful to many and to do justice to a dynamic field of great complexity.

Proteome Dynamics: Tissue Variation in the Kinetics of Proteostasis in Intact Animals

Understanding the role of protein turnover in the maintenance of proteostasis requires accurate measurements of the rates of replacement of proteins in complex systems, such as intact animals. Moreover, any investigation of allometric scaling of protein turnover is likely to include species for which fully annotated proteomes are not available. We have used dietary administration of stable isotope labeled lysine to assess protein turnover rates for proteins from four tissues in the bank vole, Myodes glareolus. The annotated genome for this species is not available, so protein identification was attained through cross-species matching to the mouse. For proteins for which confident identifications were derived, the pattern of lysine incorporation over 40 days was used to define the rate of synthesis of individual proteins in the four tissues. The data were heavily filtered to retain a very high quality dataset of turnover rates for 1088 proteins. Comparative analysis of the four tissues revealed different median rates of degradation (kidney: 0.099 days⁻¹; liver 0.136 days⁻¹; heart, 0.054 days⁻¹, and skeletal muscle, 0.035 days⁻¹). These data were compared with protein degradation rates from other studies on intact animals or from cells in culture and indicate that both cell type and analytical methodology may contribute to variance in turnover data between different studies. These differences were not only due to tissue-specific proteins but were reflected in gene products common to all tissues. All data are available via ProteomeXchange with identifier PXD002054.

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

Protein turnover is an important aspect of the regulation of cellular processes for organisms when responding to developmental or environmental cues. The measurement of protein turnover in plants, in contrast to that of rapidly growing unicellular organismal cultures, is made more complicated by the high degree of amino acid recycling, resulting in significant transient isotope incorporation distributions that must be dealt with computationally for high throughput analysis to be practical. An algorithm in R, ProteinTurnover, was developed to calculate protein turnover with transient stable isotope incorporation distributions in a high throughput automated manner using high resolution MS and MS/MS proteomic analysis of stable isotopically labeled plant material. ProteinTurnover extracts isotopic distribution information from raw MS data for peptides identified by MS/MS from data sets of either isotopic label dilution or incorporation experiments. Variable isotopic incorporation distributions were modeled using binomial and beta-binomial distributions to deconvolute the natural abundance, newly synthesized/partial-labeled, and fully labeled peptide distributions. Maximum likelihood estimation was performed to calculate the distribution abundance proportion of old and newly synthesized peptides. The half-life or turnover rate of each peptide was calculated from changes in the distribution abundance proportions using nonlinear regression. We applied ProteinTurnover to obtain half-lives of proteins from enriched soluble and membrane fractions from Arabidopsis roots.

Spectral reproducibility and quantification of peptides in MALDI of samples prepared by micro-spotting

Previously, we reported that MALDI spectra of peptides became reproducible when temperature was kept constant. Linear calibration curves derived from such spectral data could be used for quantification. Homogeneity of samples was one of the requirements. Among the three popular matrices used in peptide MALDI [i.e., α-cyano-4-hydroxycinnamic acid (CHCA), 2,5-dihydroxybenzoic acid (DHB), and sinapinic acid (SA)], homogeneous samples could be prepared by conventional means only for CHCA. In this work, we showed that sample preparation by micro-spotting improved the homogeneity for all three cases.

Protein turnover forms one of the highest maintenance costs in Lactococcus lactis

Protein turnover plays an important role in cell metabolism by regulating metabolic fluxes. Furthermore, the energy costs for protein turnover have been estimated to account for up to a third of the total energy production during cell replication and hence may represent a major limiting factor in achieving either higher biomass or production yields. This work aimed to measure the specific growth rate (μ)-dependent abundance and turnover rate of individual proteins, estimate the ATP cost for protein production and turnover, and compare this with the total energy balance and other maintenance costs. The lactic acid bacteria model organism Lactococcus lactis was used to measure protein turnover rates at μ = 0.1 and 0.5 h(-1) in chemostat experiments. Individual turnover rates were measured for ~75% of the total proteome. On average, protein turnover increased by sevenfold with a fivefold increase in growth rate, whilst biomass yield increased by 35%. The median turnover rates found were higher than the specific growth rate of the bacterium, which suggests relatively high energy consumption for protein turnover. We found that protein turnover costs alone account for 38 and 47% of the total energy produced at μ = 0.1 and 0.5 h(-1), respectively, and gene ontology groups Energy metabolism and Translation dominated synthesis costs at both growth rates studied. These results reflect the complexity of metabolic changes that occur in response to changes in environmental conditions, and signify the trade-off between biomass yield and the need to produce ATP for maintenance processes.

Protein turnover on the scale of the proteome

Protein turnover is a neglected dimension in postgenomic studies, defining the dynamics of changes in protein expression and forging a link between transcriptome, proteome and metabolome. Recent advances in postgenomic technologies have led to the development of new proteomic techniques to measure protein turnover on a proteome-wide scale. These methods are driven by stable isotope metabolic labeling of cells in culture or in intact animals. This review considers the merits and difficulties of different methods that allow access to proteome dynamics.

Stable isotope labeling by amino acids in cell culture (SILAC) for quantitative proteomics

Stable isotope labeling by amino acids in cell culture (SILAC) is a powerful approach for high-throughput quantitative proteomics. SILAC allows highly accurate protein quantitation through metabolic encoding of whole cell proteomes using stable isotope labeled amino acids. Since its introduction in 2002, SILAC has become increasingly popular. In this chapter we review the methodology and application of SILAC, with an emphasis on three research areas: dynamics of posttranslational modifications, protein-protein interactions, and protein turnover.

Proteome turnover in bacteria: current status for Corynebacterium glutamicum and related bacteria

With the advent of high-resolution mass spectrometry together with sophisticated data analysis and interpretation algorithms, determination of protein synthesis and degradation rates (i.e. protein turnover) on a proteome-wide scale by employing stable isotope-labelled amino acids has become feasible. These dynamic data provide a deeper understanding of protein homeostasis and stress response mechanisms in microorganisms than well-established ‘steady state’ proteomics approaches. In this article, we summarize the technological challenges and solutions both on the biochemistry/mass spectrometry and bioinformatics level for turnover proteomics with a focus on chromatographic techniques. Although the number of available case studies for Corynebacterium glutamicum and related actinobacteria is still very limited, our review illustrates the potential of protein turnover studies for an improved understanding of questions in the area of biotechnology and biomedicine. Here, new insights from investigations of growth phase transition and different stress dynamics including iron, acid and heat stress for pathogenic but also for industrial actinobacteria are presented. Finally, we will comment on the advantages of integrated software solutions for biologists and briefly discuss the remaining technical challenges and upcoming possibilities for protein turnover analysis.

An Internal Standard-Assisted Synthesis and Degradation Proteomic Approach Reveals the Potential Linkage between VPS4B Depletion and Activation of Fatty Acid β-Oxidation in Breast Cancer Cells

The endosomal/lysosomal system, in particular the endosomal sorting complexes required for transport (ESCRTs), plays an essential role in regulating the trafficking and destination of endocytosed receptors and their associated signaling molecules. Recently, we have shown that dysfunction and down-regulation of vacuolar protein sorting 4B (VPS4B), an ESCRT-III associated protein, under hypoxic conditions can lead to the abnormal accumulation of epidermal growth factor receptor (EGFR) and aberrant EGFR signaling in breast cancer. However, the pathophysiological consequences of VPS4B dysfunction remain largely elusive. In this study, we used an internal standard-assisted synthesis and degradation mass spectrometry (iSDMS) method, which permits the direct measurement of protein synthesis, degradation and protein dynamic expression, to address the effects of VPS4B dysfunction in altering EGF-mediated protein expression. Our initial results indicate that VPS4B down-regulation decreases the expression of many proteins involved in glycolytic pathways, while increased the expression of proteins with roles in mitochondrial fatty acid β-oxidation were up-regulated in VPS4B-depleted cells. This observation is also consistent with our previous finding that hypoxia can induce VPS4B down-regulated, suggesting that the adoption of fatty acid β-oxidation could potentially serve as an alternative energy source and survival mechanism for breast cancer cells in response to hypoxia-mediated VPS4B dysfunction.

Proteome dynamics: revisiting turnover with a global perspective

Although bulk protein turnover has been measured with the use of stable isotope labeled tracers for over half a century, it is only recently that the same approach has become applicable to the level of the proteome, permitting analysis of the turnover of many proteins instead of single proteins or an aggregated protein pool. The optimal experimental design for turnover studies is dependent on the nature of the biological system under study, which dictates the choice of precursor label, protein pool sampling strategy, and treatment of data. In this review we discuss different approaches and, in particular, explore how complexity in experimental design and data processing increases as we shift from unicellular to multicellular systems, in particular animals.

Protein turnover: measurement of proteome dynamics by whole animal metabolic labelling with stable isotope labelled amino acids

The measurement of protein turnover in tissues of intact animals is obtained by whole animal dynamic labelling studies, requiring dietary administration of precursor label. It is difficult to obtain full labelling of precursor amino acids in the diet and if partial labelling is used, calculation of the rate of turnover of each protein requires knowledge of the precursor relative isotope abundance (RIA). We describe an approach to dynamic labelling of proteins in the mouse with a commercial diet supplemented with a pure, deuterated essential amino acid. The pattern of isotopomer labelling can be used to recover the precursor RIA, and sampling of urinary secreted proteins can monitor the development of liver precursor RIA non-invasively. Time-series analysis of the labelling trajectories for individual proteins allows accurate determination of the first order rate constant for degradation. The acquisition of this parameter over multiple proteins permits turnover profiling of cellular proteins and comparisons of different tissues. The median rate of degradation of muscle protein is considerably lower than liver or kidney, with heart occupying an intermediate position.

Protein turnover quantification in a multilabeling approach: from data calculation to evaluation

Liquid chromatography coupled to tandem mass spectrometry in combination with stable-isotope labeling is an established and widely spread method to measure gene expression on the protein level. However, it is often not considered that two opposing processes are responsible for the amount of a protein in a cell--the synthesis as well as the degradation. With this work, we provide an integrative, high-throughput method--from the experimental setup to the bioinformatics analysis--to measure synthesis and degradation rates of an organism's proteome. Applicability of the approach is demonstrated with an investigation of heat shock response, a well-understood regulatory mechanism in bacteria, on the biotechnologically relevant Corynebacterium glutamicum. Utilizing a multilabeling approach using both heavy stable nitrogen as well as carbon isotopes cells are metabolically labeled in a pulse-chase experiment to trace the labels' incorporation in newly synthesized proteins and its loss during protein degradation. Our work aims not only at the calculation of protein turnover rates but also at their statistical evaluation, including variance and hierarchical cluster analysis using the rich internet application QuPE.

Automated MALDI matrix coating system for multiple tissue samples for imaging mass spectrometry

Uniform matrix deposition on tissue samples for matrix-assisted laser desorption/ionization (MALDI) is key for reproducible analyte ion signals. Current methods often result in nonhomogenous matrix deposition, and take time and effort to produce acceptable ion signals. Here we describe a fully-automated method for matrix deposition using an enclosed spray chamber and spray nozzle for matrix solution delivery. A commercial air-atomizing spray nozzle was modified and combined with solenoid controlled valves and a Programmable Logic Controller (PLC) to control and deliver the matrix solution. A spray chamber was employed to contain the nozzle, sample, and atomized matrix solution stream, and to prevent any interference from outside conditions as well as allow complete control of the sample environment. A gravity cup was filled with MALDI matrix solutions, including DHB in chloroform/methanol (50:50) at concentrations up to 60 mg/mL. Various samples (including rat brain tissue sections) were prepared using two deposition methods (spray chamber, inkjet). A linear ion trap equipped with an intermediate-pressure MALDI source was used for analyses. Optical microscopic examination showed a uniform coating of matrix crystals across the sample. Overall, the mass spectral images gathered from tissues coated using the spray chamber system were of better quality and more reproducible than from tissue specimens prepared by the inkjet deposition method.

MALDI mass spectrometric imaging of cardiac tissue following myocardial infarction in a rat coronary artery ligation model

Although acute myocardial infarction (MI) is consistently among the top causes of death in the United States, the spatial distribution of lipids and metabolites following MI remains to be elucidated. This work presents the investigation of an in vivo rat model of MI using mass spectrometric imaging (MSI) and multivariate data analysis. MSI was conducted on cardiac tissue following a 24-h left anterior descending coronary artery ligation to analyze multiple compound classes. First, the spatial distribution of a small metabolite, creatine, was used to identify areas of infarcted myocardium. Second, multivariate data analysis and tandem mass spectrometry were used to identify phospholipid (PL) markers of MI. A number of lysophospholipids demonstrated increased ion signal in areas of infarction. In contrast, select intact PLs demonstrated decreased ion signal in the area of infarction. The complementary nature of these two lipid classes suggests increased activity of phospholipase A(2), an enzyme that has been implicated in coronary heart disease and inflammation.

Determining degradation and synthesis rates of arabidopsis proteins using the kinetics of progressive 15N labeling of two-dimensional gel-separated protein spots

The growth and development of plant tissues is associated with an ordered succession of cellular processes that are reflected in the appearance and disappearance of proteins. The control of the kinetics of protein turnover is central to how plants can rapidly and specifically alter protein abundance and thus molecular function in response to environmental or developmental cues. However, the processes of turnover are largely hidden during periods of apparent steady-state protein abundance, and even when proteins accumulate it is unclear whether enhanced synthesis or decreased degradation is responsible. We have used a (15)N labeling strategy with inorganic nitrogen sources coupled to a two-dimensional fluorescence difference gel electrophoresis and mass spectrometry analysis of two-dimensional IEF/SDS-PAGE gel spots to define the rate of protein synthesis (K(S)) and degradation (K(D)) of Arabidopsis cell culture proteins. Through analysis of MALDI-TOF/TOF mass spectra from 120 protein spots, we were able to quantify K(S) and K(D) for 84 proteins across six functional groups and observe over 65-fold variation in protein degradation rates. K(S) and K(D) correlate with functional roles of the proteins in the cell and the time in the cell culture cycle. This approach is based on progressive (15)N labeling that is innocuous for the plant cells and, because it can be used to target analysis of proteins through the use of specific gel spots, it has broad applicability.

Dynamic proteome analysis of Cyanothece sp. ATCC 51142 under constant light

Understanding the dynamic nature of protein abundances provides insights into protein turnover not readily apparent from conventional, static mass spectrometry measurements. This level of data is particularly informative when surveying protein abundances in biological systems subjected to large perturbations or alterations in environment such as cyanobacteria. Our current analysis expands upon conventional proteomic approaches in cyanobacteria by measuring dynamic changes of the proteome using a (13)C(15)N-l-leucine metabolic labeling in Cyanothece ATCC51142. Metabolically labeled Cyanothece ATCC51142 cells grown under nitrogen-sufficient conditions in continuous light were monitored longitudinally for isotope incorporation over a 48 h period, revealing 414 proteins with dynamic changes in abundances. In particular, proteins involved in carbon fixation, pentose phosphate pathway, cellular protection, redox regulation, protein folding, assembly, and degradation showed higher levels of isotope incorporation, suggesting that these biochemical pathways are important for growth under continuous light. Calculation of relative isotope abundances (RIA) values allowed the measurement of actual active protein synthesis over time for different biochemical pathways under high light exposure. Overall results demonstrated the utility of "non-steady state" pulsed metabolic labeling for systems-wide dynamic quantification of the proteome in Cyanothece ATCC51142 that can also be applied to other cyanobacteria.

Proteome turnover in the green alga Ostreococcus tauri by time course 15N metabolic labeling mass spectrometry

Protein synthesis and degradation determine the cellular levels of proteins, and their control hence enables organisms to respond to environmental change. Experimentally, these are little known proteome parameters; however, recently, SILAC-based mass spectrometry studies have begun to quantify turnover in the proteomes of cell lines, yeast, and animals. Here, we present a proteome-scale method to quantify turnover and calculate synthesis and degradation rate constants of individual proteins in autotrophic organisms such as algae and plants. The workflow is based on the automated analysis of partial stable isotope incorporation with (15)N. We applied it in a study of the unicellular pico-alga Ostreococcus tauri and observed high relative turnover in chloroplast-encoded ATPases (0.42-0.58% h(-1)), core photosystem II proteins (0.34-0.51% h(-1)), and RbcL (0.47% h(-1)), while nuclear-encoded RbcS2 is more stable (0.23% h(-1)). Mitochondrial targeted ATPases (0.14-0.16% h(-1)), photosystem antennae (0.09-0.14% h(-1)), and histones (0.07-0.1% h(-1)) were comparatively stable. The calculation of degradation and synthesis rate constants k(deg) and k(syn) confirms RbcL as the bulk contributor to overall protein turnover. This study performed over 144 h of incorporation reveals dynamics of protein complex subunits as well as isoforms targeted to different organelles.

Systems-wide proteomic analysis in mammalian cells reveals conserved, functional protein turnover

The turnover of each protein in the mammalian proteome is a functionally important characteristic. Here, we employed high-resolution mass spectrometry to quantify protein dynamics in nondividing mammalian cells. The ratio of externally supplied versus endogenous amino acids to de novo protein synthesis was about 17:1. Using subsaturating SILAC labeling, we obtained accurate turnover rates of 4106 proteins in HeLa and 3528 proteins in C2C12 cells. Comparison of these human and mouse cell lines revealed a highly significant turnover correlation of protein orthologs and thus high species conservation. Functionally, we observed statistically significant trends for the turnover of phosphoproteins and gene ontology categories that showed extensive covariation between mouse and human. Likewise, the members of some protein complexes, such as the proteasome, have highly similar turnover rates. The high species conservation and the low complex variances thus imply great regulatory fine-tuning of protein turnover.

Proteomics moves from expression to turnover: update and future perspective

Proteomics is a rapidly developing discipline that seeks to understand the role of proteins in the wider biological context. In order to take a holistic view of a biological system, it is vital that we can elucidate the dynamics of the proteome. In this article, we have outlined the recent advances in experimental strategies for measuring protein synthesis and degradation on a proteome-wide scale. The application of mass spectrometry and non-mass spectrometric-based approaches in this field of research has been discussed. The article also explores the challenges associated with these types of analyses and the development of appropriate bioinformatic resources for interrogating the complex datasets that are generated.

The dynamic state of protein turnover: It's about time

The continual destruction and renewal of proteins that maintain cellular homeostasis has been rigorously studied since the late 1930s. Experimental techniques for measuring protein turnover have evolved to measure the dynamic regulation of key proteins and now, entire proteomes. In the past decade, the proteomics field has aimed to discover how cells adjust their proteomes to execute numerous regulatory programs in response to specific cellular and environmental cues. By combining classical biochemical techniques with modern, high-throughput technologies, researchers have begun to reveal the synthesis and degradation mechanisms that shape protein turnover on a global scale. This review examines several recent developments in protein turnover research, emphasizing the combination of metabolic labeling and mass spectrometry.

Quantitative tracking of isotope flows in proteomes of microbial communities

Stable isotope probing (SIP) has been used to track nutrient flows in microbial communities, but existing protein-based SIP methods capable of quantifying the degree of label incorporation into peptides and proteins have been demonstrated only by targeting usually less than 100 proteins per sample. Our method automatically (i) identifies the sequence of and (ii) quantifies the degree of heavy atom enrichment for thousands of proteins from microbial community proteome samples. These features make our method suitable for comparing isotopic differences between closely related protein sequences, and for detecting labeling patterns in low-abundance proteins or proteins derived from rare community members. The proteomic SIP method was validated using proteome samples of known stable isotope incorporation levels at 0.4%, ∼50%, and ∼98%. The method was then used to monitor incorporation of (15)N into established and regrowing microbial biofilms. The results indicate organism-specific migration patterns from established communities into regrowing communities and provide insights into metabolism during biofilm formation. The proteomic SIP method can be extended to many systems to track fluxes of (13)C or (15)N in microbial communities.

Multivariate statistical identification of human bladder carcinomas using ambient ionization imaging mass spectrometry

Diagnosis of human bladder cancer in untreated tissue sections is achieved by using imaging data from desorption electrospray ionization mass spectrometry (DESI-MS) combined with multivariate statistical analysis. We use the distinctive DESI-MS glycerophospholipid (GP) mass spectral profiles to visually characterize and formally classify twenty pairs (40 tissue samples) of human cancerous and adjacent normal bladder tissue samples. The individual ion images derived from the acquired profiles correlate with standard histological hematoxylin and eosin (H&E)-stained serial sections. The profiles allow us to classify the disease status of the tissue samples with high accuracy as judged by reference histological data. To achieve this, the data from the twenty pairs were divided into a training set and a validation set. Spectra from the tumor and normal regions of each of the tissue sections in the training set were used for orthogonal projection to latent structures (O-PLS) treated partial least-square discriminate analysis (PLS-DA). This predictive model was then validated by using the validation set and showed a 5% error rate for classification and a misclassification rate of 12%. It was also used to create synthetic images of the tissue sections showing pixel-by-pixel disease classification of the tissue and these data agreed well with the independent classification that uses histological data by a certified pathologist. This represents the first application of multivariate statistical methods for classification by ambient ionization although these methods have been applied previously to other MS imaging methods. The results are encouraging in terms of the development of a method that could be utilized in a clinical setting through visualization and diagnosis of intact tissue.

Quantitation of newly synthesized proteins by pulse labeling with azidohomoalanine

Measuring protein synthesis and degradation rates on a proteomic scale is an important step toward modeling the kinetics in complicated cellular response networks. A gel-free method, able to quantify changes in the formation of new proteins on a 15 min timescale, compatible with mass spectrometry is described. The methionine analogue, azidohomoalanine (azhal), is used to label newly formed proteins during a short pulse-labeling period following an environmental switch in Escherichia coli. Following digestion a selective reaction against azhal-containing peptides is applied to enrich these peptides by diagonal chromatography. This technique enables quantitation of hundreds of newly synthesized proteins and provides insight into immediate changes in newly synthesized proteins on a proteomic scale after an environmental perturbation.

Protein turnover methods in single-celled organisms: dynamic SILAC

Early achievements in proteomics were qualitative, typified by the identification of very small quantities of proteins. However, as the subject has developed, there has been a pressure to develop approaches to define the amounts of each protein--whether in a relative or an absolute sense. A further dimension to quantitative proteomics embeds the behavior of each protein in terms of its turnover. Virtually every protein in the cell is in a dynamic state, subject to continuous synthesis and degradation, the relative rates of which control the expansion or the contraction of the protein pool, and the absolute values of which dictate the temporal responsiveness of the protein pool. Strategies must therefore be developed to assess the turnover of individual proteins in the proteome. Because a protein can be turning over rapidly even when the protein pool is in steady state, the only acceptable approach to measure turnover is to use metabolic labels that are incorporated or lost from the protein pool as it is replaced. Using metabolic labeling on a proteome-wide scale in turn requires metabolic labels that contain stable isotopes, the incorporation or loss of which can be assessed by mass spectrometry. A typical turnover experiment is complex. The choice of metabolic label is dictated by several factors, including abundance in the proteome, metabolic redistribution of the label in the precursor pool, and the downstream mass spectrometric analytical protocols. Key issues include the need to control and understand the relative isotope abundance of the precursor, the optimization of label flux into and out of the protein pool, and a sampling strategy that ensures the coverage of the greatest range of turnover rates. Finally, the informatics approaches to data analysis will not be as straightforward as in other areas of proteomics. In this chapter, we will discuss the principles and practice of workflow development for turnover analysis, exemplified by the development of methodologies for turnover analysis in the model eukaryote Saccharomyces cerevisiae.