Determining and interpreting protein lifetimes in mammalian tissues

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.

Derailed protein turnover in the aging mammalian brain

Efficient protein turnover is essential for cellular homeostasis and organ function. Loss of proteostasis is a hallmark of aging culminating in severe dysfunction of protein turnover. To investigate protein turnover dynamics as a function of age, we performed continuous in vivo metabolic stable isotope labeling in mice along the aging continuum. First, we discovered that the brain proteome uniquely undergoes dynamic turnover fluctuations during aging compared to heart and liver tissue. Second, trends in protein turnover in the brain proteome during aging showed sex-specific differences that were tightly tied to cellular compartments. Next, parallel analyses of the insoluble proteome revealed that several cellular compartments experience hampered turnover, in part due to misfolding. Finally, we found that age-associated fluctuations in proteasome activity were associated with the turnover of core proteolytic subunits, which was recapitulated by pharmacological suppression of proteasome activity. Taken together, our study provides a proteome-wide atlas of protein turnover across the aging continuum and reveals a link between the turnover of individual proteasome subunits and the age-associated decline in proteasome activity.

Analysis of proteome-wide degradation dynamics in ALS SOD1 iPSC-derived patient neurons reveals disrupted VCP homeostasis

Mutations in SOD1 cause amyotrophic lateral sclerosis (ALS) through gain-of-function effects, yet the mechanisms by which misfolded mutant SOD1 (mutSOD1) protein impairs human motor neurons (MNs) remain unclear. Here, we use induced-pluripotent-stem-cell-derived MNs coupled to metabolic stable isotope labeling and mass spectrometry to investigate proteome-wide degradation dynamics. We find several proteins, including the ALS-causal valosin-containing protein (VCP), which predominantly acts in proteasome degradation and autophagy, that degrade slower in mutSOD1 relative to isogenic control MNs. The interactome of VCP is altered in mutSOD1 MNs in vitro, while VCP selectively accumulates in the affected motor cortex of ALS-SOD1 patients. Overexpression of VCP rescues mutSOD1 toxicity in MNs in vitro and in a C. elegans model in vivo, in part due to its ability to modulate the degradation of insoluble mutSOD1. Our results demonstrate that VCP contributes to mutSOD1-dependent degeneration, link two distinct ALS-causal genes, and highlight selective protein degradation impairment in ALS pathophysiology.

Exceptional longevity of mammalian ovarian and oocyte macromolecules throughout the reproductive lifespan

The mechanisms contributing to age-related deterioration of the female reproductive system are complex, however aberrant protein homeostasis is a major contributor. We elucidated exceptionally stable proteins, structures, and macromolecules that persist in mammalian ovaries and gametes across the reproductive lifespan. Ovaries exhibit localized structural and cell-type specific enrichment of stable macromolecules in both the follicular and extrafollicular environments. Moreover, ovaries and oocytes both harbor a panel of exceptionally long-lived proteins, including cytoskeletal, mitochondrial, and oocyte-derived proteins. The exceptional persistence of these long-lived molecules suggest a critical role in lifelong maintenance and age-dependent deterioration of reproductive tissues.

The cochlea is built to last a lifetime

Orchestration of protein production and degradation and the regulation of protein lifetimes play a central role in many basic biological processes. Nearly all mammalian proteins are replenished by protein turnover in waves of synthesis and degradation. Protein lifetimes in vivo are typically measured in days, but a small number of extremely long-lived proteins (ELLPs) persist for months or even years. ELLPs are rare in all tissues but are enriched in tissues containing terminally differentiated post-mitotic cells and extracellular matrix. Consistently, emerging evidence suggests that the cochlea may be particularly enriched in ELLPs. Damage to ELLPs in specialized cell types, such as crystallin in the lens cells of the eye, causes organ failure such as cataracts. Similarly, damage to cochlear ELLPs is likely to occur with many insults, including acoustic overstimulation, drugs, anoxia, and antibiotics, and may play an underappreciated role in hearing loss. Furthermore, hampered protein degradation may contribute to acquired hearing loss. In this review, I highlight our knowledge of the lifetimes of cochlear proteins with an emphasis on ELLPs and the potential contribution that impaired cochlear protein degradation has on acquired hearing loss and the emerging relevance of ELLPs.

Mass-Spectrometric Evaluation of the African Swine Fever Virus-Induced Host Shutoff Using Dynamic Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC)

African swine fever is a viral disease of swine caused by the African swine fever virus (ASFV). Currently, ASFV is spreading over the Eurasian continent and threatening global pig husbandry. One viral strategy to undermine an efficient host cell response is to establish a global shutoff of host protein synthesis. This shutoff has been observed in ASFV-infected cultured cells using two-dimensional electrophoresis combined with metabolic radioactive labeling. However, it remained unclear if this shutoff was selective for certain host proteins. Here, we characterized ASFV-induced shutoff in porcine macrophages by measurement of relative protein synthesis rates using a mass spectrometric approach based on stable isotope labeling with amino acids in cell culture (SILAC). The impact of ASFV infection on the synthesis of >2000 individual host proteins showed a high degree of variability, ranging from complete shutoff to a strong induction of proteins that are absent from naïve cells. GO-term enrichment analysis revealed that the most effective shutoff was observed for proteins related to RNA metabolism, while typical representatives of the innate immune system were strongly induced after infection. This experimental setup is suitable to quantify a virion-induced host shutoff (vhs) after infection with different viruses.

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.

Toward a hypothesis-free understanding of how phosphorylation dynamically impacts protein turnover

The turnover measurement of proteins and proteoforms has been largely facilitated by workflows coupling metabolic labeling with mass spectrometry (MS), including dynamic stable isotope labeling by amino acids in cell culture (dynamic SILAC) or pulsed SILAC (pSILAC). Very recent studies including ours have integrated themeasurement of post-translational modifications (PTMs) at the proteome level (i.e., phosphoproteomics) with pSILAC experiments in steady state systems, exploring the link between PTMs and turnover at the proteome-scale. An open question in the field is how to exactly interpret these complex datasets in a biological perspective. Here, we present a novel pSILAC phosphoproteomic dataset which was obtained during a dynamic process of cell starvation using data-independent acquisition MS (DIA-MS). To provide an unbiased "hypothesis-free" analysis framework, we developed a strategy to interrogate how phosphorylation dynamically impacts protein turnover across the time series data. With this strategy, we discovered a complex relationship between phosphorylation and protein turnover that was previously underexplored. Our results further revealed a link between phosphorylation stoichiometry with the turnover of phosphorylated peptidoforms. Moreover, our results suggested that phosphoproteomic turnover diversity cannot directly explain the abundance regulation of phosphorylation during cell starvation, underscoring the importance of future studies addressing PTM site-resolved protein turnover.

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.