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Summary Chronic caloric restriction (CR) and rapamycin inhibit the mechanistic target of rapamycin (mTOR) signaling, thereby regulating metabolism and suppressing protein synthesis. Caloric restriction or rapamycin extends murine lifespan and ameliorates many aging‐associated disorders; however, the beneficial effects of shorter treatment on cardiac aging are not as well understood. Using a recently developed deuterated‐leucine labeling method, we investigated the effect of short‐term (10 weeks) CR or rapamycin on the proteomics turnover and remodeling of the aging mouse heart. Functionally, we observed that short‐term CR and rapamycin both reversed the pre‐existing age‐dependent cardiac hypertrophy and diastolic dysfunction. There was no significant change in the cardiac global proteome (823 proteins) turnover with age, with a median half‐life 9.1 days in the 5‐month‐old hearts and 8.8 days in the 27‐month‐old hearts. However, proteome half‐lives of old hearts significantly increased after short‐term CR (30%) or rapamycin (12%). This was accompanied by attenuation of age‐dependent protein oxidative damage and ubiquitination. Quantitative proteomics and pathway analysis revealed an age‐dependent decreased abundance of proteins involved in mitochondrial function, electron transport chain, citric acid cycle, and fatty acid metabolism as well as increased abundance of proteins involved in glycolysis and oxidative stress response. This age‐dependent cardiac proteome remodeling was significantly reversed by short‐term CR or rapamycin, demonstrating a concordance with the beneficial effect on cardiac physiology. The metabolic shift induced by rapamycin was confirmed by metabolomic analysis.

Homocysteinylation of lysine residues by homocysteine thiolactone (HCTL), a reactive homocysteine metabolite, results in protein aggregation and malfunction, and is a well-known risk factor for cardiovascular, autoimmune and neurological diseases. Human plasma paraoxonase-1 (PON1) and bleomycin hydrolase (Blmh) have been reported as the physiological HCTL detoxifying enzymes. However, the catalytic efficiency of HCTL hydrolysis by Blmh is low and not saturated at 20 mM HCTL. The catalytic efficiency of PON1 for HCTL hydrolysis is 100-fold lower than that of Blmh. A homocysteine thiolactonase (HCTLase) was purified from human liver and identified by mass spectrometry (MS) as the previously described human biphenyl hydrolase-like protein (BPHL). To further characterize this newly described HCTLase activity, BPHL was expressed in Escherichia coli and purified. The sequence of the recombinant BPHL (rBPHL) and hydrolytic products of the substrates HCTL and valacyclovir were verified by MS. We found that the catalytic efficiency (kcat/Km) of rBPHL for HCTL hydrolysis was 7.7 × 10(4) M(-1)s(-1), orders of magnitude higher than that of PON1 or Blmh, indicating a more significant physiological role for BPHL in detoxifying HCTL.

Reversed-phase liquid chromatography is the most commonly used separation method for shotgun proteomics. Nanoflow chromatography has emerged as the preferred chromatography method for its increased sensitivity and separation. Despite its common use, there are a wide range of parameters and conditions used across research groups. These parameters have an effect on the quality of the chromatographic separation, which is critical to maximizing the number of peptide identifications and minimizing ion suppression. Here we examined the relationship between column lengths, gradient lengths, peptide identifications, and peptide peak capacity. We found that while longer column and gradient lengths generally increase peptide identifications, the degree of improvement is dependent on both parameters and is diminished at longer column and gradients. Peak capacity, in comparison, showed a more linear increase with column and gradient lengths. We discuss the discrepancy between these two results and some of the considerations that should be taken into account when deciding on the chromatographic conditions for a proteomics experiment. Figure The effects of column and gradient lengths on the performance of nanoflow LC-MS/MS is examined in complex proteomic samples.

Summary Calorie restriction (CR) and rapamycin (RP) extend lifespan and improve health across model organisms. Both treatments inhibit mammalian target of rapamycin (mTOR) signaling, a conserved longevity pathway and a key regulator of protein homeostasis, yet their effects on proteome homeostasis are relatively unknown. To comprehensively study the effects of aging, CR, and RP on protein homeostasis, we performed the first simultaneous measurement of mRNA translation, protein turnover, and abundance in livers of young (3 month) and old (25 month) mice subjected to 10-week RP or 40% CR. Protein abundance and turnover were measured in vivo using 2H3-leucine heavy isotope labeling followed by LC-MS/MS, and translation was assessed by polysome profiling. We observed 35-60% increased protein half-lives after CR and 15% increased half-lives after RP compared to age-matched controls. Surprisingly, the effects of RP and CR on protein turnover and abundance differed greatly between canonical pathways, with opposite effects in mitochondrial (mt) dysfunction and eIF2 signaling pathways. CR most closely recapitulated the young phenotype in the top pathways. Polysome profiles indicated that CR reduced polysome loading while RP increased polysome loading in young and old mice, suggesting distinct mechanisms of reduced protein synthesis. CR and RP both attenuated protein oxidative damage. Our findings collectively suggest that CR and RP extend lifespan in part through the reduction of protein synthetic burden and damage and a concomitant increase in protein quality. However, these results challenge the notion that RP is a faithful CR mimetic and highlight mechanistic differences between the two interventions.

Summary Reactive oxygen species (ROS) are highly reactive oxygen-containing molecules associated with aging and a broad spectrum of pathologies. We have previously shown that transgenic expression of the antioxidant enzyme catalase targeted to the mitochondria (mCAT) in mice reduces ROS, attenuates age-related disease, and increases lifespan. However, it has been increasingly recognized that ROS also has beneficial roles in signaling, hormesis, stress response, and immunity. We therefore hypothesized that mCAT might be beneficial only when ROS approaches pathological levels in older age and might not be advantageous at a younger age when basal ROS is low. We analyzed abundance and turnover of the global proteome in hearts and livers of young (4 month) and old (20 month) mCAT and wild-type (WT) mice. In old hearts and livers of WT mice, protein half-lives were reduced compared to young, while in mCAT mice the reverse was observed; the longest half-lives were seen in old mCAT mice and the shortest in young mCAT. Protein abundance of old mCAT hearts recapitulated a more youthful proteomic expression profile (P-value < 0.01). However, young mCAT mice partially phenocopied the older wild-type proteome (P-value < 0.01). Age strongly interacts with mCAT, consistent with antagonistic pleiotropy in the reverse of the typical direction. These findings underscore the contrasting roles of ROS in young vs. old mice and indicate the need for better understanding of the interaction between dose and age in assessing the efficacy of therapeutic interventions in aging, including mitochondrial antioxidants.

We report an algorithm designed for the calibration of low resolution peptide mass spectra. Our algorithm is implemented in a program called FineTune, which corrects systematic mass measurement error in 1 min, with no input required besides the mass spectra themselves. The mass measurement accuracy for a set of spectra collected on an LTQ-Velos improved 20-fold from –0.1776 ± 0.0010  m/z to 0.0078 ± 0.0006  m/z after calibration (avg ± 95 % confidence interval). The precision in mass measurement was improved due to the correction of non-linear variation in mass measurement accuracy across the m/z range.

The shift towards the subcutaneous administration route for biologics therapeutics has gained momentum due to its patient-friendly nature, convenience, reduced healthcare burden, and improved compliance compared to traditional intravenous infusions. However, one of the potentially significant challenges with this transition is managing the viscosity of the administered solutions. High viscosity can pose substantial development and manufacturability challenges, directly impacting the patient by increasing injection time and pain at the injection site. Moreover, high viscosity formulations can prolong residence time at the injection site, affecting absorption kinetics and potentially altering the intended pharmacological profile and therapeutic efficacy of the biologic candidate. This publication explores the application of a multimodal feature learning workflow for predicting the viscosity of antibodies in therapeutics discovery, integrating multiple data sources such as sequence, structural, physicochemical properties, and embeddings from a language model. This approach enables the model to learn from various underlying rules, including physicochemical rules from molecular simulations and molecular protein evolutionary rules by large, pre-trained deep learning foundation models. By comparing the effectiveness of this approach against other selected published viscosity prediction methods, this study offers insights on their intrinsic viscosity predictive potential and usability in therapeutics antibody early development pipelines.

The gut microbiome and its metabolites are increasingly implicated in several cardiovascular diseases, but their role in human myocardial infarction (MI) injury responses have yet to be established. To address this, we examined stool samples from 77 ST-elevation MI (STEMI) patients using 16 S V3-V4 next-generation sequencing, metagenomics and machine learning. Our analysis identified an enriched population of butyrate-producing bacteria. These findings were then validated using a controlled ischemia/reperfusion model using eight nonhuman primates. To elucidate mechanisms, we inoculated gnotobiotic mice with these bacteria and found that they can produce beta-hydroxybutyrate, supporting cardiac function post-MI. This was further confirmed using HMGCS2-deficient mice which lack endogenous ketogenesis and have poor outcomes after MI. Inoculation increased plasma ketone levels and provided significant improvements in cardiac function post-MI. Together, this demonstrates a previously unknown role of gut butyrate-producers in the post-MI response. Here, Chen et. al . characterize the relationship between the gut microbiota and plasma metabolite changes in the context of ST-elevation myocardial infarction (STEMI), unveiling a role of butyrate-producing bacteria and their ketogenesis in post-STEMI cardiac repair, a finding validated in nonhuman primate and mouse models. They show that butyrate supplementation reduces myocardial infarction severity in mice, underscoring the significance of butyrate-producing bacteria and beta-hydroxybutyrate in improving post-MI outcomes.