Region-Specific Proteostasis Remodeling Shapes Motility Decline in the Aging Gut

1. Overview

Slowed intestinal movement and constipation are common features of aging and significantly affect quality of life in older adults. Although age-related gut dysfunction is well recognized clinically, the molecular mechanisms underlying this decline remain poorly understood. Effective motility depends on coordinated communication between enteric neurons, smooth muscle cells, and resident immune cells within the gut muscular layer.

Recent studies in the aging brain reveal convergence of two processes: immune cells adopt lipid droplet–accumulating metabolic states¹, and neural tissue accumulates slow-degrading, poorly soluble proteins, a phenomenon increasingly recognized as age-associated proteostasis remodeling (“proteose”)². Our prior work demonstrated that muscularis macrophages (MMs), which genetically mirror microglia, undergo lipid droplet accumulation and metabolic reprogramming with age in the small intestine, while the colon exhibits a distinct aging-associated immune profile³. These findings raise a new question: does immune metabolic remodeling in the aging gut coincide with proteose-like shifts in protein solubility within the enteric neuromuscular niche?

This project will test whether aging induces redistribution of proteins toward less soluble fractions within the gut muscular layer and whether such remodeling differs between small intestine and colon. Using detergent-based protein fractionation and quantitative mass spectrometry, we will generate proof-of-concept data to determine whether immune metabolic divergence aligns with region-specific proteostasis instability in aged mice.

Funding and facilities:

Aged mouse cohorts are available through ongoing NIH-supported studies. Proteomic analyses will be conducted using established institutional mass spectrometry infrastructure. No new animal approvals are required.

Timeline:

Months 1–2: tissue collection and fractionation.

Months 2–4: mass spectrometry acquisition.

Months 4–6: data analysis and dissemination.

Data sharing:

All raw and processed data will be deposited in an open-access repository. The protocol will be preregistered on ResearchHub, and results will be shared as a preprint regardless of outcome.

2. Introduction

Aging alters cellular homeostasis across multiple organs, often through subtle destabilization of protein maintenance rather than overt tissue loss⁴. Protein turnover, degradation, and solubility are tightly regulated processes that preserve signaling fidelity, structural integrity, and metabolic balance. With age, this regulation can break, leading to accumulation of slow-degrading or poorly soluble proteins, a process increasingly recognized as age-associated proteostasis remodeling, or “proteose”. In neural tissues, redistribution of proteins toward less soluble pools has been associated with impaired synaptic signaling and increased functional vulnerability³. Importantly, proteostasis disruption in the aging brain does not occur in isolation. It coincides with metabolic remodeling of microglia, including the emergence of lipid droplet–accumulating microglial states (LDAM)¹. These immune cells exhibit altered metabolism and reduced debris clearance capacity. The coexistence of lipid-accumulating immune cells and slow-degrading neuronal proteins suggests that immune metabolic remodeling and proteostasis instability may represent coordinated features of aging neural niches.

Preliminary Findings: Muscularis macrophages (MMs), the resident immune cells of the enteric neuromuscular layer, share transcriptional and functional characteristics with microglia, including expression of P2ry12, Hexb, and Cx3cr1 ⁵. These MMs closely associate with enteric neurons and contribute to maintenance of neuromuscular homeostasis ^6-7. In our prior work, we observed age-associated lipid droplet accumulation and metabolic reprogramming (i.e., loss of phagocytotic activity, loss of healthy mitochondria) in small intestinal MMs (Fig. 1), while colonic MMs displayed a distinct aging-associated profile with comparatively limited lipid accumulation (Fig. 2). These findings establish region-specific immune metabolic aging programs within the gut. Whether proteose-like remodeling also occurs in the aging enteric neuromuscular niche, and whether such changes align with immune metabolic divergence, remain unknown. Because neuronal signaling and smooth muscle contraction depend on tightly regulated protein turnover and localization, redistribution of proteins toward less soluble pools could destabilize coordinated neuromuscular function and contribute to age-associated dysmotility.

Fig. 1 Lipid droplet–accumulating MMs expand with age in the small intestine.
(Left) Representative confocal images of small intestine muscularis tissue stained with BODIPY (green), anti-MHC II (MMs, red), and anti-Hu (neurons, blue) from young and aged mice (n = 8 each). MMs containing lipid droplets (LD) are shown (arrow). A Magnified image (square) shown with 3D rendering on right. (Right) The percent of LD⁺ macrophages was significantly higher in aged than young mice. Male, black solid circles (●); female, open circles (○).

Fig. 2 Lipid droplet–accumulating MMs expand with age in the colon.
(Left) Representative confocal images of colon muscularis tissue stained with BODIPY (green), anti-MHC II (MMs, red), and anti-Hu (neurons, blue) from young and aged mice (n = 8 each). MMs containing lipid droplets (LD) are shown (arrow). A Magnified image (square) shown with 3D rendering on right. (Right) The percent of LD⁺ macrophages remained the same in aged than young mice. Male, black solid circles (●); female, open circles (○).

We therefore propose to determine whether aging drives redistribution of proteins toward insoluble fractions within the enteric muscular layer and whether such remodeling differs between small intestine and colon.

We propose the following hypotheses:

H1: Aging promotes redistribution of proteins toward insoluble fractions within the enteric muscularis layer.

H2: Small intestine and colon exhibit distinct proteostasis remodeling patterns aligned with divergent immune metabolic programs.

H3: Age-associated solubility shifts preferentially involve neuron- and smooth muscle–enriched proteins, consistent with impaired neuromuscular coordination.

Study Impact

Regardless of outcome, this study will clarify whether proteose remodeling represents a conserved feature of enteric aging and whether it converges with immune metabolic remodeling within the neuromuscular niche. By defining region-specific proteostasis signatures in aged tissue, we will generate mechanistic targets linking immune metabolism, protein stability, and functional gut decline. As a clinically integrated translational laboratory with direct access to human gastrointestinal specimens, we are uniquely positioned to rapidly validate these findings in patient tissue and extend them toward human-relevant aging interventions.

3. Methods

Participants/Sample

This study will use male C57BL/6J mice at three defined age groups representing distinct stages of adult aging: young (3–4 months), mid-aged (15–18 months), and aged (20–24 months). These timepoints capture mature adulthood, early aging transition, and advanced aging, enabling assessment of progressive changes along chronological order. Animals will be housed under standard conditions with ad libitum access to food and water and will not undergo prior experimental manipulation. Mice showing signs of infection, tumor burden, severe weight loss, or other systemic illness will be excluded.

Five biological replicates per age group (n = 5; total n = 15) will be included. This sample size is consistent with prior tissue-level metabolomic and proteomic aging studies, including our recently submitted metabolomics analysis of the muscularis layer, in which robust age-associated metabolic differences were detected using n = 5 biological replicates per group. These findings indicate moderate-to-large effect sizes in age-associated tissue remodeling. Because the current study is designed to detect global shifts in protein solubility distribution rather than subtle single-protein expression changes, moderate-to-large effect sizes are anticipated. Label-free data-independent acquisition (DIA) proteomics typically achieves reproducible quantification of high- and mid-abundance proteins using 5 biological replicates per group. Statistical power is further strengthened by modeling age as an ordered variable (young , mid-aged , aged), increasing sensitivity to monotonic trends across aging. False discovery rate (FDR) will be controlled at 5% to account for multiple testing.

Materials and Procedures

Muscularis externa tissue will be isolated from young (3–4 months), mid-aged (15–18 months), and aged (20–24 months) C57BL/6J mice under approved institutional animal protocols. Following euthanasia, small intestine and colon will be rapidly excised and placed in ice-cold buffer. The neuromuscular layer will be carefully dissected under stereomicroscopy. Tissue samples will be flash-frozen in liquid nitrogen and stored at −80°C until processing. Five to six biological replicates per age group will be included.

To assess age-associated redistribution of proteins between water soluble and aggregation-enriched pools, sequential biochemical fractionation will be performed. Frozen muscularis tissue will be homogenized in ice-cold 0.32M sucrose buffer (10mM Tris-HCl, pH 7.5) containing protease inhibitors and subjected to ultracentrifugation at 100,000 × g for 30 minutes at 4°C. The supernatant will be collected as the water-soluble fraction. The remaining pellet will then be resuspended in 1% sarkosyl in 50 mM Tris-HCl (pH 7.5) and incubated with gentle agitation for 30 minutes at room temperature to solubilize detergent-extractable proteins. Following a second ultracentrifugation step, the supernatant will be discarded and the final pellet, representing the water-insoluble fraction enriched for aggregation-prone proteins, will be retained.

To enable downstream proteomic analysis, both soluble and insoluble pellet will be fully denatured separately in buffer containing 2% SDS, 8 M urea, and 50 mM Tris-HCl (pH 8.0). Samples will be sonicated briefly to ensure complete solubilization, reduced with dithiothreitol, and alkylated with iodoacetamide. Detergents and chaotropic agents will be removed using an S-Trap based cleanup method prior to overnight trypsin digestion. Peptides will be desalted using C18 solid-phase extraction and subjected to liquid chromatography–tandem mass spectrometry. Mass spectrometry will be performed at the Carnegie Mass Spectrometry Facility using a Thermo Fisher Orbitrap Eclipse Tribrid mass spectrometer coupled to an EASY-nLC 1200 nanoLC system. Peptides will be separated on a reversed-phase C18 analytical column using a 90–120 minute acetonitrile gradient and analyzed in data-independent acquisition (DIA) mode to ensure reproducible and comprehensive protein quantification across biological replicates. Raw data will be processed using established DIA analysis pipelines (e.g., MSFragger or DIA-NN) against the UniProt mouse reference proteome, with peptide- and protein-level false discovery rate controlled at 5%.

Planned Analyses

Protein abundance values will be log2-transformed and median-normalized prior to analysis. Proteins identified with fewer than two unique peptides or detected in less than 70% of samples per group will be excluded. Principal component analysis will be performed to assess clustering by age group and to detect potential outliers. Differential abundance will be assessed using linear modeling frameworks, with age analyzed both categorically (young, mid-aged, aged) and as an ordered variable to detect progressive changes across aging. Multiple testing will be controlled using a 5% false discovery rate.

To specifically evaluate protein aggregation dynamics, a solubility index (log2 insoluble/soluble ratio) will be calculated for each protein and modeled as a function of age. We will test whether this index increases with advancing age, indicating progressive redistribution toward insolubility. To link proteomic changes to functional cell populations, detected proteins will be annotated using curated gene sets derived from published enteric single-cell datasets, enabling stratified analyses of neuron-enriched, smooth muscle–enriched, and macrophage-enriched proteins. Pathway enrichment analyses will be conducted using Gene Ontology and Reactome databases, with the full set of detected proteins serving as background, to determine whether aging preferentially affects proteostasis, mitochondrial function, cytoskeletal organization, or synaptic-related pathways.

Ethics and Data Management

All animal procedures will be conducted under approved institutional animal care and use committee (IACUC) protocols. No human subjects are involved. Raw and processed proteomic data will be deposited in a publicly accessible proteomics repository (e.g., PRIDE or MassIVE) upon publication. Data analysis scripts and annotation pipelines will be made available through an open-source platform to ensure transparency and reproducibility.

4. Budget

Proteomic mass spectrometry: $8,000
Protein fractionation and sample preparation reagents: $1,000
Bioinformatics and data analysis resources: $500
Contingency: $500

Total: $10,000

Animal housing and breeding costs are supported through existing NIH-funded studies. No personnel salary support is requested. Proteomic analyses will be performed in collaboration with the Carnegie Mass Spectrometry Facility using established institutional infrastructure, allowing cost-efficient execution of the proposed assays. The requested funds will be used exclusively for proteomic sample preparation, mass spectrometry acquisition, and associated data analysis costs.

5. References

Marschallinger, J. et al. Lipid-droplet-accumulating microglia represent a dysfunctional and proinflammatory state in the aging brain. Nature Neuroscience, 194–208 (2020).

Guldner, Ian H., et al. "Ageing promotes microglial accumulation of slow-degrading synaptic proteins." Nature (2026): 1-12.

Ye, Jiayu, et al. "AGING-SPECIFIC LIPID ACCUMULATION IN GUT MUSCULARIS MACROPHAGES CAUSES PRO-INFLAMMATORY PHENOTYPE AND LOSS OF HOMEOSTATIC FUNCTION." GASTROENTEROLOGY. Vol. 139. No. 1. 1600 JOHN F KENNEDY BOULEVARD, STE 1800, PHILADELPHIA, PA 19103-2899 USA: WB SAUNDERS CO-ELSEVIER INC, 2025.

López-Otín, Carlos, et al. "Hallmarks of aging: An expanding universe." Cell 186.2 (2023): 243-278.

Bishop, E. S. et al. Age-dependent Microglial Disease Phenotype Results in Functional Decline in Gut Macrophages. Gastro hep advances, 261–276 (2023).

Viola, M. F. et al. Dedicated macrophages organize and maintain the enteric nervous system. Nature, 818–826 (2023).

Luo, J. et al. TRPV4 Channel Signaling in Macrophages Promotes Gastrointestinal Motility via Direct Effects on Smooth Muscle Cells. Immunity, 107-119.e4 (2018).

Region-Specific Proteostasis Remodeling Shapes Motility Decline in the Aging Gut

Region-Specific Proteostasis Remodeling Shapes Motility Decline in the Aging Gut

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Request for Proposals - Aging and Longevity

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