An atlas of protein turnover rates in mouse tissues

Systematic analysis of proteome turnover in an organoid model of pancreatic cancer by dSILO

The role of protein turnover in pancreatic ductal adenocarcinoma (PDA) metastasis has not been previously investigated. We introduce dynamic stable-isotope labeling of organoids (dSILO): a dynamic SILAC derivative that combines a pulse of isotopically labeled amino acids with isobaric tandem mass-tag (TMT) labeling to measure proteome-wide protein turnover rates in organoids. We applied it to a PDA model and discovered that metastatic organoids exhibit an accelerated global proteome turnover compared to primary tumor organoids. Globally, most turnover changes are not reflected at the level of protein abundance. Interestingly, the group of proteins that show the highest turnover increase in metastatic PDA compared to tumor is involved in mitochondrial respiration. This indicates that metastatic PDA may adopt alternative respiratory chain functionality that is controlled by the rate at which proteins are turned over. Collectively, our analysis of proteome turnover in PDA organoids offers insights into the mechanisms underlying PDA metastasis.

Postnatal changes in thyroid cartilage shape and cartilage matrix composition are not synchronized in Mus musculus

The study was conducted to quantify laryngeal cartilage matrix composition and to investigate its relationship with cartilage shape in a mouse model. A sample of 30 mice (CD-1 mouse, Mus musculus) from five age groups (postnatal Days 2, 21, 90, 365, and 720) were used. Three-dimensional mouse laryngeal thyroid cartilage reconstructions were generated from contrast-enhanced micro-computed tomography (CT) image stacks. Cartilage matrix composition was estimated as Hounsfield units (HU). HU were determined by overlaying 3D reconstructions as masks on micro-CT image stacks and then measuring the attenuation. Cartilage shape was quantified with landmarks placed on the surface of the thyroid cartilage. Shape differences between the five age groups were analyzed using geometric morphometrics and multiparametric analysis of landmarks. The relationship between HU and shape was investigated with correlational analyses. Among five age groups, HU became higher in older animals. The shape of the thyroid cartilage changes with age throughout the entire life of a mouse. The changes in shape were not synchronized with changes in cartilage matrix composition. The thyroid cartilage of young and old M. musculus larynx showed a homogenous mineralization pattern. High-resolution contrast-enhanced micro-CT imaging makes the mouse larynx accessible for analysis of genetic and environmental factors affecting shape and matrix composition.

Long-lived proteins and DNA as candidate predictive biomarkers for tissue associated diseases

Protein turnover is an important mechanism to maintain proteostasis. Long-lived proteins (LLPs) are vulnerable to lose their function due to time-accumulated damages. In this study we employed in vivo stable isotope labeling in mice from birth to postnatal day 89. Quantitative proteomics analysis of ten tissues and plasma identified 2113 LLPs, including widespread and tissue-specific ones. Interestingly, a significant percentage of LLPs was detected in plasma, implying a potential link to age-related cardiovascular diseases. LLPs identified in brains were related to neurodegenerative diseases. In addition, the relative quantification of DNA-derived deoxynucleosides from the same tissues provided information about cellular DNA renewal and showed good correlation with LLPs in the brain. The combined data reveal tissue-specific maps of mouse LLPs that may be involved in pathology due to a low renewal rate and an increased risk of damage. Tissue-derived peripheral LLPs hold promise as biomarkers for aging and age-related diseases.

A targeted proteomics method for quantifying plasma apolipoprotein kinetics in individual mice using stable isotope labeling

Altered apolipoprotein kinetics play a critical role in promoting dyslipidemia and atherogenesis. Human apolipoprotein kinetics have been extensively evaluated, but similar studies in mice are hampered by the lack of robust methods suitable for the small amounts of blood that can be collected at sequential time points from individual mice. We describe a targeted liquid chromatography tandem mass spectrometry method for simultaneously quantifying the stable isotope enrichment of several apolipoproteins represented by multiple peptides in serial blood samples (15 μl each) obtained after retro-orbital injection of 13C6,15N2-lysine (Lys8) in mice. We determined apolipoprotein fractional clearance rates (FCRs) and production rates (PRs) in WT mice and in two genetic models widely used for atherosclerosis research, LDL receptor-deficient (Ldlr-/-) and apolipoprotein E-deficient (Apoe-/-) mice. Injection of Lys8 produced a unique and readily detectable mass shift of labeled compared with unlabeled peptides with sensitivity allowing robust kinetics analyses. Ldlr-/- mice showed slower FCRs of APOA1, APOA4, total APOB, APOB100, APOCs, APOE and APOM, while FCRs of APOA1, APOB100, APOC2, APOC3, and APOM were not lower in Apoe-/- mice versus WT mice. APOE PR was increased in Ldlr-/- mice, and APOB100 and APOA4 PRs were reduced in Apoe-/- mice. Thus, our method reproducibly quantifies plasma apolipoprotein kinetics in different mouse models. The method can easily be expanded to include a wide range of proteins in the same biospecimen and should be useful for determining the kinetics of apolipoproteins in animal models of human disease.

Remodeling of the human skeletal muscle proteome found after long-term endurance training but not after strength training

Exercise training has tremendous systemic tissue-specific health benefits, but the molecular adaptations to long-term exercise training are not completely understood. We investigated the skeletal muscle proteome of highly endurance-trained, strength-trained, and untrained individuals and performed exercise- and sex-specific analyses. Of the 6,000+ proteins identified, >650 were differentially expressed in endurance-trained individuals compared with controls. Strikingly, 92% of the shared proteins with higher expression in both the male and female endurance groups were known mitochondrial. In contrast to the findings in endurance-trained individuals, minimal differences were found in strength-trained individuals and between females and males. Lastly, a co-expression network and comparative literature analysis revealed key proteins and pathways related to the health benefits of exercise, which were primarily related to differences in mitochondrial proteins. This network is available as an interactive database resource where investigators can correlate clinical data with global gene and protein expression data for hypothesis generation.

Flexible Quality Control for Protein Turnover Rates Using d2ome

Bioinformatics tools are used to estimate in vivo protein turnover rates from the LC-MS data of heavy water labeled samples in high throughput. The quantification includes peak detection and integration in the LC-MS domain of complex input data of the mammalian proteome, which requires the integration of results from different experiments. The existing software tools for the estimation of turnover rate use predefined, built-in, stringent filtering criteria to select well-fitted peptides and determine turnover rates for proteins. The flexible control of filtering and quality measures will help to reduce the effects of fluctuations and interferences to the signals from target peptides while retaining an adequate number of peptides. This work describes an approach for flexible error control and filtering measures implemented in the computational tool d2ome for automating protein turnover rates. The error control measures (based on spectral properties and signal features) reduced the standard deviation and tightened the confidence intervals of the estimated turnover rates.

A high-fat diet increases hepatic mitochondrial turnover through restricted acetylation in a NAFLD mouse model

Lysine acetylation of proteins has emerged as a key posttranslational modification (PTM) that regulates mitochondrial metabolism. Acetylation may regulate energy metabolism by inhibiting and affecting the stability of metabolic enzymes and oxidative phosphorylation (OxPhos) subunits. Although protein turnover can be easily measured, due to the low abundance of modified proteins, it has been difficult to evaluate the effect of acetylation on the stability of proteins in vivo. We applied 2H2O-metabolic labeling coupled with immunoaffinity and high-resolution mass spectrometry method to measure the stability of acetylated proteins in mouse liver based on their turnover rates. As a proof-of-concept, we assessed the consequence of high-fat diet (HFD)-induced altered acetylation in protein turnover in LDL receptor-deficient (LDLR-/-) mice susceptible to diet-induced nonalcoholic fatty liver disease (NAFLD). HFD feeding for 12 wk led to steatosis, the early stage of NAFLD. A significant reduction in acetylation of hepatic proteins was observed in NAFLD mice, based on immunoblot analysis and label-free quantification with mass spectrometry. Compared with control mice on a normal diet, NAFLD mice had overall increased turnover rates of hepatic proteins, including mitochondrial metabolic enzymes (0.159 ± 0.079 vs. 0.132 ± 0.068 day-1), suggesting their reduced stability. Also, acetylated proteins had slower turnover rates (increased stability) than native proteins in both groups (0.096 ± 0.056 vs. 0.170 ± 0.059 day-1 in control, and 0.111 ± 0.050 vs. 0.208 ± 0.074 day-1 in NAFLD). Furthermore, association analysis revealed a relationship between the HFD-induced decrease in acetylation and increased turnover rates for hepatic proteins in NAFLD mice. These changes were associated with increased expressions of the hepatic mitochondrial transcriptional factor (TFAM) and complex II subunit without any changes to other OxPhos proteins, suggesting that enhanced mitochondrial biogenesis prevented restricted acetylation-mediated depletion of mitochondrial proteins. We conclude that decreased acetylation of mitochondrial proteins may contribute to adaptive improved hepatic mitochondrial function in the early stages of NAFLD.NEW & NOTEWORTHY This is the first method to quantify acetylome dynamics in vivo. This method revealed acetylation-mediated altered hepatic mitochondrial protein turnover in response to a high-fat diet in a mouse model of NAFLD.

Post-pubertal developmental trajectories of laryngeal shape and size in humans

Laryngeal morphotypes have been hypothesized related to both phonation and to laryngeal pathologies. Morphotypes have not been validated or demonstrated quantitatively and sources of shape and size variation are incompletely understood but are critical for the explanation of behavioral changes (e.g., changes of physical properties of a voice) and for therapeutic approaches to the larynx. This is the first study to take this crucial step and results are likely to have implications for surgeons and speech language pathologists. A stratified human sample was interrogated for phenotypic variation of the vocal organ. First, computed tomography image stacks were used to generate three-dimensional reconstructions of the thyroid cartilage. Then cartilage shapes were quantified using multivariate statistical analysis of high dimensional shape data from margins and surfaces of the thyroid cartilage. The effects of sex, age, body mass index (BMI) and body height on size and shape differences were analyzed. We found that sex, age, BMI and the age-sex interaction showed significant effects on the mixed sex sample. Among males, only age showed a strong effect. The thyroid cartilage increased in overall size, and the angulation between left and right lamina decreased in older males. Age, BMI and the age-height interaction were statistically significant factors within females. The angulation between left and right lamina increased in older females and was smaller in females with greater BMI. A cluster analysis confirmed the strong age effect on larynx shape in males and a complex interaction between the age, BMI and height variables in the female sample. The investigation demonstrated that age and BMI, two risk factors in a range of clinical conditions, are associated with shape and size variation of the human larynx. The effects influence shape differently in female and male larynges. The male-female shape dichotomy is partly size-dependent but predominantly size-independent.

Analysis and prediction of protein stability based on interaction network, gene ontology, and KEGG pathway enrichment scores

Metabolic stability of proteins plays a vital role in various dedicated cellular processes. Traditional methods of measuring the metabolic stability are time-consuming and expensive. Therefore, we developed a more efficient computational approach to understand the protein dynamic action mechanisms in biological process networks. In this study, we collected 341 short-lived proteins and 824 non-short-lived proteins from U2OS; 342 short-lived proteins and 821 non-short-lived proteins from HEK293T; 424 short-lived proteins and 1153 non-short-lived proteins from HCT116; and 384 short-lived proteins and 992 non-short-lived proteins from RPE1. The proteins were encoded by GO and KEGG enrichment scores based on the genes and their neighbors in STRING, resulting in 20,681 GO term features and 297 KEGG pathway features. We also incorporated the protein interaction information from STRING into the features and obtained 19,247 node features. Boruta and mRMR methods were used for feature filtering, and IFS method was used to obtain the best feature subsets and create the models with the highest performance. The present study identified 42 features that did not appear in previous studies and classified them into eight groups according to their functional annotation. By reviewing the literature, we found that the following three functional groups were critical in determining the stability of proteins: synaptic transmission, post-translational modifications, and cell fate determination. These findings may serve as a valuable reference for developing drugs that target protein stability.

A novel method for visualizing in-vivo rates of protein degradation provides insight into how TRIM28 regulates muscle size

Skeletal muscle size is controlled by the balance between protein synthesis and protein degradation. Given the essential role of skeletal muscle in maintaining a high quality of life, understanding the mechanisms that modulate this balance are of critical importance. Previously, we demonstrated that muscle-specific knockout of TRIM28 reduces muscle size and function and in the current study, we discovered that this effect is associated with an increase in protein degradation and a dramatic reduction in the expression of Mettl21c. Importantly, we also determined that overexpression of Mettl21c is sufficient to induce hypertrophy in both control and TRIM28 knockout muscles. Moreover, we developed a simple pulse-chase biorthogonal non-canonical amino acid tagging technique that enabled us to visualize the in vivo rate of protein degradation, and with this technique were able to conclude that the hypertrophic effect of Mettl21c is due, at least in part, to an inhibition of protein degradation.

Quantifying label enrichment from two mass isotopomers increases proteome coverage for in vivo protein turnover using heavy water metabolic labeling

Heavy water metabolic labeling followed by liquid chromatography coupled with mass spectrometry is a powerful high throughput technique for measuring the turnover rates of individual proteins in vivo. The turnover rate is obtained from the exponential decay modeling of the depletion of the monoisotopic relative isotope abundance. We provide theoretical formulas for the time course dynamics of six mass isotopomers and use the formulas to introduce a method that utilizes partial isotope profiles, only two mass isotopomers, to compute protein turnover rate. The use of partial isotope profiles alleviates the interferences from co-eluting contaminants in complex proteome mixtures and improves the accuracy of the estimation of label enrichment. In five different datasets, the technique consistently doubles the number of peptides with high goodness-of-fit characteristics of the turnover rate model. We also introduce a software tool, d2ome+, which automates the protein turnover estimation from partial isotope profiles.

Turnover and replication analysis by isotope labeling (TRAIL) reveals the influence of tissue context on protein and organelle lifetimes

The lifespans of proteins range from minutes to years within mammalian tissues. Protein lifespan is relevant to organismal aging, as long-lived proteins accrue damage over time. It is unclear how protein lifetime is shaped by tissue context, where both cell turnover and proteolytic degradation contribute to protein turnover. We develop turnover and replication analysis by ¹⁵ N isotope labeling (TRAIL) to quantify protein and cell lifetimes with high precision and demonstrate that cell turnover, sequence-encoded features, and environmental factors modulate protein lifespan across tissues. Cell and protein turnover flux are comparable in proliferative tissues, while protein turnover outpaces cell turnover in slowly proliferative tissues. Physicochemical features such as hydrophobicity, charge, and disorder influence protein turnover in slowly proliferative tissues, but protein turnover is much less sequence-selective in highly proliferative tissues. Protein lifetimes vary nonrandomly across tissues after correcting for cell turnover. Multiprotein complexes such as the ribosome have consistent lifetimes across tissues, while mitochondria, peroxisomes, and lipid droplets have variable lifetimes. TRAIL can be used to explore how environment, aging, and disease affect tissue homeostasis.

Metabolic deuterium oxide (D2O) labeling in quantitative omics studies: A tutorial review

Mass spectrometry (MS) is an invaluable tool for sensitive detection and characterization of individual biomolecules in omics studies. MS combined with stable isotope labeling enables the accurate and precise determination of quantitative changes occurring in biological samples. Metabolic isotope labeling, wherein isotopes are introduced into biomolecules through biosynthetic metabolism, is one of the main labeling strategies. Among the precursors employed in metabolic isotope labeling, deuterium oxide (D₂O) is cost-effective and easy to implement in any biological systems. This tutorial review aims to explain the basic principle of D₂O labeling and its applications in omics research. D₂O labeling incorporates D into stable C-H bonds in various biomolecules, including nucleotides, proteins, lipids, and carbohydrates. Typically, D₂O labeling is performed at low enrichment of 1%-10% D₂O, which causes subtle changes in the isotopic distribution of a biomolecule, instead of the complete separation between labeled and unlabeled samples in a mass spectrum. D₂O labeling has been employed in various omics studies to determine the metabolic flux, turnover rate, and relative quantification. Moreover, the advantages and challenges of D₂O labeling and its future prospects in quantitative omics are discussed. The economy, versatility, and convenience of D₂O labeling will be beneficial for the long-term omics studies for higher organisms.

Retention Time Alignment for Protein Turnover Studies Using Heavy Water Metabolic Labeling

Retention time (RT) alignment has been important for robust protein identification and quantification in proteomics. In data-dependent acquisition mode, whereby the precursor ions are semistochastically chosen for fragmentation in MS/MS, the alignment is used in an approach termed matched between runs (MBR). MBR transfers peptides, which were fragmented and identified in one experiment, to a replicate experiment where they were not identified. Before the MBR transfer, the RTs of experiments are aligned to reduce the chance of erroneous transfers. Despite its widespread use in other areas of quantitative proteomics, RT alignment has not been applied in data analyses for protein turnover using an atom-based stable isotope-labeling agent such as metabolic labeling with deuterium oxide, D2O. Deuterium incorporation changes isotope profiles of intact peptides in full scans and their fragment ions in tandem mass spectra. It reduces the peptide identification rates in current database search engines. Therefore, the MBR becomes more important. Here, we report on an approach to incorporate RT alignment with peptide quantification in studies of proteome turnover using heavy water metabolic labeling and LC-MS. The RT alignment uses correlation-optimized time warping. The alignment, followed by the MBR, improves labeling time point coverage, especially for long labeling durations.

Determining and interpreting protein lifetimes in mammalian tissues

The orchestration of protein production and degradation, and the regulation of protein lifetimes, play a central role in the majority of biological processes. Recent advances in proteomics have enabled the estimation of protein half-lives for thousands of proteins in vivo. What is the utility of these measurements, and how can they be leveraged to interpret the proteome changes occurring during development, aging, and disease? This opinion article summarizes leading technical approaches and highlights their strengths and weaknesses. We also disambiguate frequently used terminology, illustrate recent mechanistic insights, and provide guidance for interpreting and validating protein turnover measurements. Overall, protein lifetimes, coupled to estimates of protein levels, are essential for obtaining a deep understanding of mammalian biology and the basic processes defining life itself.

Software Tool for Visualization and Validation of Protein Turnover Rates Using Heavy Water Metabolic Labeling and LC-MS

Metabolic stable isotope labeling followed by liquid chromatography coupled with mass spectrometry (LC-MS) is a powerful tool for in vivo protein turnover studies of individual proteins on a large scale and with high throughput. Turnover rates of thousands of proteins from dozens of time course experiments are determined by data processing tools, which are essential components of the workflows for automated extraction of turnover rates. The development of sophisticated algorithms for estimating protein turnover has been emphasized. However, the visualization and annotation of the time series data are no less important. The visualization tools help to validate the quality of the model fits, their goodness-of-fit characteristics, mass spectral features of peptides, and consistency of peptide identifications, among others. Here, we describe a graphical user interface (GUI) to visualize the results from the protein turnover analysis tool, d2ome, which determines protein turnover rates from metabolic D₂O labeling followed by LC-MS. We emphasize the specific features of the time series data and their visualization in the GUI. The time series data visualized by the GUI can be saved in JPEG format for storage and further dissemination.

Harmonizing Labeling and Analytical Strategies to Obtain Protein Turnover Rates in Intact Adult Animals

Changes in the abundance of individual proteins in the proteome can be elicited by modulation of protein synthesis (the rate of input of newly synthesized proteins into the protein pool) or degradation (the rate of removal of protein molecules from the pool). A full understanding of proteome changes therefore requires a definition of the roles of these two processes in proteostasis, collectively known as protein turnover. Because protein turnover occurs even in the absence of overt changes in pool abundance, turnover measurements necessitate monitoring the flux of stable isotope–labeled precursors through the protein pool such as labeled amino acids or metabolic precursors such as ammonium chloride or heavy water. In cells in culture, the ability to manipulate precursor pools by rapid medium changes is simple, but for more complex systems such as intact animals, the approach becomes more convoluted. Individual methods bring specific complications, and the suitability of different methods has not been comprehensively explored. In this study, we compare the turnover rates of proteins across four mouse tissues, obtained from the same inbred mouse strain maintained under identical husbandry conditions, measured using either [¹³C₆]lysine or [²H₂]O as the labeling precursor. We show that for long-lived proteins, the two approaches yield essentially identical measures of the first-order rate constant for degradation. For short-lived proteins, there is a need to compensate for the slower equilibration of lysine through the precursor pools. We evaluate different approaches to provide that compensation. We conclude that both labels are suitable, but careful determination of precursor enrichment kinetics in amino acid labeling is critical and has a considerable influence on the numerical values of the derived protein turnover rates.

•

Controlled comparison of heavy water or amino acid labeling for protein turnover.

•

Delays in amino acid precursor labeling mostly affect high turnover proteins

•

Both methods produced similar turnover rates after adjustment of precursor kinetics.

•

Recommendations for analytical workflows for protein turnover studies in animals.

Protein degradation on the global scale

Protein degradation occurs through proteasomal, endosomal, and lysosomal pathways. Technological advancements have allowed for the determination of protein copy numbers and turnover rates on a global scale, which has provided an overview of trends and rules governing protein degradation. Sharper chemical and gene-editing tools have enabled the specific perturbation of each degradation pathway, whose effects on protein dynamics can now be comprehensively analyzed. We review major studies and innovation in this field and discuss the interdependence between the major pathways of protein degradation.

A peptidoform based proteomic strategy for studying functions of post-translational modifications

Protein post-translational modifications (PTMs) generate an enormous, but as yet undetermined, expansion of the produced proteoforms. In this Viewpoint, we firstly reviewed the concepts of proteoform and peptidoform. We show that many of the current PTM biological investigation and annotation studies largely follow a PTM site-specific rather than proteoform-specific approach. We further illustrate a potentially useful matching strategy in which a particular "modified peptidoform" is matched to the corresponding "unmodified peptidoform" as a reference for the quantitative analysis between samples and conditions. We suggest this strategy has the potential to provide more directly relevant information to learn the PTM site-specific biological functions. Accordingly, we advocate for the wider use of the nomenclature "peptidoform" in future bottom-up proteomic studies.

Protein turnover models for LC-MS data of heavy water metabolic labeling

Protein turnover is vital for cellular functioning and is often associated with the pathophysiology of a variety of diseases. Metabolic labeling with heavy water followed by liquid chromatography coupled to mass spectrometry is a powerful tool to study in vivo protein turnover in high throughput and large scale. Heavy water is a cost-effective and easy to use labeling agent. It labels all nonessential amino acids. Due to its toxicity in high concentrations (20% or higher), small enrichments (8% or smaller) of heavy water are used with most organisms. The low concentration results in incomplete labeling of peptides/proteins. Therefore, the data processing is more challenging and requires accurate quantification of labeled and unlabeled forms of a peptide from overlapping mass isotopomer distributions. The work describes the bioinformatics aspects of the analysis of heavy water labeled mass spectral data, available software tools and current challenges and opportunities.