Mass spectrometry-based proteome profiling in disease models

Introduction

Mass spectrometry-based proteomics has revolutionized biomedical research by enabling comprehensive, unbiased characterization of protein expression across biological systems [1] . Contemporary instrumentation combining high-resolution accurate-mass analysis with multiplexed quantification strategies now permits quantification of thousands of proteins from limited biological material with exceptional precision [2] . These technological advances position proteomics as a powerful discovery tool for identifying disease mechanisms, biomarkers, and therapeutic targets across diverse pathological conditions. Tandem mass tag isobaric labeling represents the current standard for multiplexed quantitative proteomics, enabling simultaneous comparison of up to 16 samples with high precision and accuracy [3] . Reporter ions released during fragmentation provide relative quantification while peptide backbone fragments enable sequence identification. Combined with extensive fractionation and high-resolution Orbitrap mass analysis, TMT-based workflows routinely quantify over 8,000 proteins from complex biological samples [4] . This depth of coverage approaches comprehensive proteome characterization for many mammalian tissues. Non-alcoholic fatty liver disease represents the hepatic manifestation of metabolic syndrome, affecting approximately 25% of the global adult population [5] . The disease spectrum ranges from simple steatosis through nonalcoholic steatohepatitis with inflammation and fibrosis to cirrhosis and hepatocellular carcinoma [6] . Despite this substantial burden, no pharmacological therapies have received regulatory approval specifically for NAFLD, partly reflecting incomplete understanding of molecular mechanisms driving disease initiation and progression [7] . Mouse models of diet-induced fatty liver disease have proven invaluable for investigating NAFLD pathophysiology given their recapitulation of key disease features and amenability to experimental manipulation [8] . High-fat diet feeding in C57BL/6J mice induces hepatic steatosis, insulin resistance, and inflammatory changes resembling human disease progression [9] . While transcriptomic profiling has characterized gene expression changes in these models, protein-level characterization provides complementary information given substantial posttranscriptional regulation of metabolic enzymes [10] . Previous proteomic investigations of fatty liver disease have employed various quantification strategies with differing coverage and precision. Label-free quantification approaches offer simplicity but suffer from missing values and run-to-run variability [11] . SILAC metabolic labeling provides excellent precision but requires specialized cell culture conditions limiting applicability to tissue samples [12] . TMT-based quantification combines multiplexing efficiency with high precision, making it ideally suited for comparative tissue proteomics with limited sample numbers. This research aimed to comprehensively characterize hepatic proteome alterations in diet-induced NAFLD using state-of-the-art TMT-based quantitative proteomics. The specific objectives included profiling differentially expressed proteins between control and NAFLD mouse livers, identifying dysregulated metabolic pathways through enrichment analysis, validating key findings using orthogonal methods, and nominating candidate biomarkers with translational potential. We hypothesized that high-fat diet-induced steatosis would produce coordinated changes in lipid metabolic pathway proteins reflecting the metabolic reprogramming underlying hepatic fat accumulation.

Mass Spectrometry Technology Platform

The Orbitrap Fusion Tribrid mass spectrometer was selected for this research based on its exceptional performance characteristics for TMT-based quantitative proteomics [13] . The tribrid architecture combining quadrupole mass filtering, Orbitrap high-resolution analysis, and linear ion trap rapid scanning enables optimized acquisition strategies. Synchronous precursor selection with MS3 quantification eliminates ratio compression artifacts that compromise TMT accuracy in traditional MS2-based workflows. The nanoflow liquid chromatography system employed C18 reversed-phase separation with 500 mm analytical columns achieving greater than 300,000 theoretical plates. Extended gradients of 180 minutes maximized peptide separation and identification depth. High-pH reversed-phase fractionation prior to analysis reduced sample complexity while maintaining orthogonality, with 12 fractions providing optimal balance between depth and throughput. This platform configuration routinely achieves identification of greater than 10,000 proteins and quantification of greater than 8,000 with coefficients of variation below 10%.

Materials and Methods

Materials

This quantitative proteomics research was conducted at the Proteomics Core Facility, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, between March 2020 and September 2022. The animal experimental protocol received approval from the Stockholm Regional Ethics Committee for Animal Research (Protocol Dnr 2019-15847, approved February 12, 2020). All procedures adhered to European Union Directive 2010/63/EU and Swedish Animal Welfare Act provisions governing animal experimentation. Male C57BL/6J mice aged 8 weeks were obtained from Charles River Laboratories and housed under specific pathogen-free conditions with 12-hour light/dark cycles and ad libitum access to food and water. Following one-week acclimation, mice were randomly assigned to receive either high-fat diet (Research Diets D12492, 60% kcal from fat) or standard chow (Labfor R70, 10% kcal from fat) for 16 weeks. Body weight and food consumption were monitored weekly. Sample size calculations based on anticipated proteomic effect sizes indicated requirement for six animals per group with 80% power. At research termination, mice were fasted for 6 hours then euthanized by cervical dislocation under isoflurane anesthesia. Livers were rapidly excised, weighed, and divided for proteomics, histology, and biochemical analyses. Tissue portions for proteomics were snap-frozen in liquid nitrogen and stored at -80°C. Formalin-fixed paraffinembedded sections underwent hematoxylin-eosin staining for histological assessment by a pathologist blinded to group assignment. NAFLD activity scores were determined using standard criteria.

Methods

Frozen liver tissue (approximately 30 mg) was homogenized in lysis buffer containing 8 M urea, 50 mM Tris-HCl pH 8.0, 75 mM NaCl, and protease/phosphatase inhibitor cocktails using probe sonication. Lysates were clarified by centrifugation at 20,000g for 20 minutes at 4°C. Protein concentration was determined by bicinchoninic acid assay with bovine serum albumin standards. Equal protein amounts (100 μg) from each sample underwent reduction with dithiothreitol, alkylation with iodoacetamide, and overnight tryptic digestion at 37°C following urea dilution to 1.5 M [14] . Peptides were desalted using C18 solid-phase extraction and labeled with TMT-11plex reagents according to manufacturer protocols. Labeling efficiency exceeding 99% was confirmed by preliminary LC-MS analysis. Labeled samples were combined and fractionated by high-pH reversed-phase chromatography into 12 fractions. Each fraction was analyzed by nanoLC-MS/MS on Orbitrap Fusion Tribrid using synchronous precursor selection MS3 acquisition with real-time search enabling intelligent data acquisition [15] . Raw mass spectrometry data were processed in MaxQuant version 2.0.3.1 against the UniProt mouse reference proteome with standard settings for TMT quantification including reporter ion mass tolerance 0.003 Da. False discovery rates were controlled at 1% at both peptide and protein levels using target-decoy approach. Statistical analysis utilized Perseus version 1.6.15.0 with log2 transformation, normalization, and moderated t-test for differential expression. Pathway enrichment employed Reactome and KEGG databases with Benjamini-Hochberg correction [16] . Western blot validation used standard protocols with antibodies against selected differentially expressed proteins.

Results

Discussion

This quantitative proteomics research establishes a comprehensive hepatic protein expression signature of dietinduced non-alcoholic fatty liver disease, revealing coordinated metabolic reprogramming favoring de novo lipogenesis over fatty acid oxidation. The identification of 342 differentially expressed proteins with enrichment in well-characterized lipid metabolic pathways validates the biological relevance of our findings and provides mechanistic insight into disease pathophysiology [17] . The coordinated up-regulation of lipogenic enzymes including fatty acid synthase, acetyl-CoA carboxylase, and stearoyl-CoA desaturase reflects enhanced de novo lipogenesis characteristic of NAFLD. These enzymes are transcriptionally regulated by sterol regulatory element-binding protein 1, which itself showed significant up-regulation in our dataset [18] . The magnitude of changes observed, with FAS demonstrating nearly 4-fold increase, exceeds previously reported transcriptomic alterations, suggesting additional posttranscriptional amplification of the lipogenic program. The corresponding down-regulation of fatty acid β-oxidation machinery represents the complementary arm of metabolic imbalance leading to triglyceride accumulation. Carnitine palmitoyltransferase 1A, the rate-limiting enzyme for mitochondrial fatty acid import, showed greater than 2.5-fold decrease. PPARα and its coactivator PGC1α, master regulators of oxidative metabolism, demonstrated parallel reductions [19] . This coordinated suppression of oxidative capacity alongside enhanced lipogenesis creates the metabolic environment permissive for hepatic steatosis development.

The TMT-based quantification approach provided exceptional precision with median coefficient of variation below 10%, enabling detection of moderate expression changes with statistical confidence. The synchronous precursor selection MS3 acquisition strategy eliminated ratio compression artifacts that have historically compromised TMT accuracy [20] . These technical advances contributed to the high concordance observed between mass spectrometry quantification and Western blot validation for selected proteins.

The identification of twelve candidate biomarker proteins with consistent differential expression, pathway relevance, and potential detectability in circulation provides translational opportunities. Current NAFLD diagnosis relies on invasive liver biopsy, creating urgent need for non-invasive biomarkers [21] . Several identified proteins including secreted forms of lipogenic enzymes warrant further investigation as circulating biomarkers for disease detection and monitoring.

Biomarker Translation Considerations

Acknowledgement

Acknowledgements

References

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