Edward Lau | PubMed Health

PubMed2026

Body mass index-specific nanoparticle protein corona signatures in late pregnancy.

The protein corona (PC) formed on the surface of nanoparticles (NPs) upon exposure to human biofluids is a dynamic interface that reflects the physiological and pathological status of the host. In this study, we investigated how the maternal body mass index (BMI) influences the composition of the NPs' PC during late pregnancy. Polystyrene NPs were incubated with plasma samples collected from third-trimester pregnant individuals across normal weight, overweight, and obese BMI categories. Comprehensive characterization using dynamic light scattering (DLS), zeta potential measurements, and transmission electron microscopy (TEM) confirmed BMI-dependent differences in PC thickness and colloidal stability. SDS-PAGE and label-free quantitative proteomics revealed distinct molecular compositions: PCs from obese individuals were enriched in inflammatory and lipid metabolism-associated proteins (e.g., APOE and CRP), while normal weight-derived PCs showed higher levels of complementary regulators and extracellular matrix proteins. Principal component analysis (PCA) demonstrated clear clustering of proteomic profiles by the BMI group, suggesting BMI-specific PC fingerprints. These findings indicate that the maternal metabolic phenotype shapes nano-bio interactions at the proteomic level and highlight the potential of PC profiling as a non-invasive approach for assessing maternal health and metabolic status. This work lays the foundation for integrating NP-based proteomics into precision nanomedicine for maternal-fetal health monitoring.

Female↗

PubMed2025

Longevity of cardiac and skeletal muscle proteins is dependent on tissue and subcellular compartmentation patterns.

Myocytes are exceptionally long-lived cells that must maintain proteome integrity over decades while adjusting for changes in functional output and metabolic demand. We used in vivo stable isotope labeling combined with mass spectrometry proteomics and correlated multi-isotope imaging mass spectrometry to quantify and visualize protein turnover across cardiac, fast-twitch, and slow-twitch skeletal muscles, creating a resource of hundreds of individual protein turnover rates from each tissue. We found that cardiac muscle has the highest rate of protein turnover, followed by slow-twitch skeletal muscle and then fast-twitch skeletal muscle, and that these different rates of protein turnover are driven by different levels of muscle use, rather than myosin isoform composition. We also identified protein age heterogeneity at the myofiber and sarcomere levels. These findings uncover fundamental principles of muscle protein maintenance and have broad implications for understanding cellular aging, muscle disease, and the design of therapeutic strategies targeting muscle protein turnover.

Animals↗