Metabolic signatures of tear extracellular vesicles caused by herpes simplex keratitis.

PURPOSE: Herpes simplex keratitis (HSK), caused by type 1 herpes simplex virus (HSV) reactivation, is a severe infectious disease that leads to vision loss. HSV can trigger metabolic reprogramming in the host cell and change the extracellular vesicles (EV) cargos; however, little is known about the EV metabolic signatures during ocular HSV infection. Here, we aimed to depict the EV-associated metabolic landscape in HSK patients' tears. METHODS: We collected 82 samples from 41 participants with unilateral HSK (contralateral unaffected tears were set as negative control), including subtype cohorts of 13 epithelial, 20 stromal, and 8 endothelial HSK. We isolated tear EVs via our previously established platform and conducted metabolic analysis using LC-MS/MS. The metabolic signatures for recognizing HSK and subtypes were assessed through differential analysis and machine learning algorithms. RESULTS: Hypopsia and increased extracellular CD63 levels were observed in affected eyes. We identified 339 metabolites based on sEVs isolated from tears. Differential analysis revealed alterations in energy and amino acid metabolism, as well as the infectious microenvironment. Furthermore, we observed dysregulated metabolite such as methyldopa, which is associated with inappropriate neovascularization and corneal sensation loss, contributing to the HSK severity particularly in the stromal subtype. Moreover, machine learning classification also suggested a set of EV metabolic signatures that have potential for pan-keratitis detection. CONCLUSIONS: Our findings demonstrate that tear EV metabolites can serve as valuable indicators for comprehending the underlying pathological mechanisms. This knowledge is expected to facilitate the development of liquid biopsy means and therapeutic target discovery.

Interaction network of extracellular vesicles building universal analysis via eye tears: iNEBULA.

Discovering the secrets of diseases from tear extracellular vesicles (EVs) is well-recognized and appreciated. However, a precise understanding of the interaction network between EV populations and their biogenesis from our body requires more in-depth and systematic analysis. Here, we report the biological profiles of different-size tear EV subsets from healthy individuals and the origins of EV proteins. We have identified about 1800 proteins and revealed the preferential differences in the biogenesis among distinct subsets. We observe that eye-related proteins that maintain retinal homeostasis and regulate inflammation are preferentially enriched in medium-size EVs (100 to 200 nm) fractions. Using universal analysis in combination with the Human Protein Atlas consensus dataset, we found the genesis of tear EV proteins with 37 tissues and 79 cell types. The proteins related to retinal neuronal cells, glial cells, and blood and immune cells are selectively enriched among EV subsets. Our studies in heterogeneous tear EVs provide building blocks for future transformative precision molecular diagnostics and therapeutics.

Extracellular vesicles metabolic changes reveals plasma signature in stage-dependent diabetic kidney disease.

OBJECTIVE: Early diagnosis of diabetic kidney disease (DKD) has long been a complex problem. This study aimed to analyze the metabolomic characteristics of plasma extracellular vesicles (EVs) at different stages of DKD in order to evaluate the metabolites of plasma EVs and select new biomarkers for the early diagnosis of DKD. PATIENTS AND METHODS: A total of 78 plasma samples were collected, including samples from 20 healthy controls, 20 patients with type 2 diabetes mellitus (T2DM), 18 patients with DKD stage III, and 20 patients with DKD stage IV. In addition, EVs were isolated for metabolomics analysis. RESULTS: The results identified differences in EV metabolomic characteristics in DKD patients at different stages, as well as significant differences in EV metabolomics between T2DM patients without DKD and patients with DKD. Ten Significantly differential metabolites were associated with the occurrence and progression of DKD. Uracil, LPC(O-18:1/0:0), sphingosine 1-phosphate, and 4-acetamidobutyric acid were identified as potential early biomarkers for DKD, showing excellent predictive performance. CONCLUSION: Uracil, LPC(O-18:1/0:0), sphingosine 1-phosphate, and 4-acetamidobutyric acid exhibited potential as suitable biomarkers for early DKD diagnosis. Unexpectedly, combining these four candidate metabolites resulted in enhanced predictive ability for DKD.

Highly Selective Purification of Plasma Extracellular Vesicles Using Titanium Dioxide Microparticles for Depicting the Metabolic Signatures of Diabetic Retinopathy.

Extracellular vesicle (EV) cargos with regular fluctuations hold the potential for providing chemical predictors toward clinical diagnosis and prognosis. A plasma sample is one of the most important sources of circulating EVs, yet the technical barrier and cost consumption in plasma-EV isolation still limit its application in disease diagnosis and biomarker discovery. Here, we introduced an easy-to-use strategy that allows selectively purifying small EVs (sEVs) from human plasma and detecting their metabolic alternations. Fe3O4@TiO2 microbeads with a rough island-shaped surface have proven the capability of performing efficient and reversible sEV capture owing to the phospholipid affinity, enhanced binding sites, and size-exclusion-like effect of the rough TiO2 shell. The proposed system can also shorten the separation procedure from hours to 20 min when compared with the ultracentrifugation method and yield approximately 108 sEV particles from 100 µL of plasma. Metabolome variations of sEVs among progressive diabetic retinopathy subjects were finally studied, observing a cluster of metabolites with elevated levels and suggesting potential roles of these sEV chemicals in diabetic retinopathy onset and progression. Such a scalable and flexible EV capture system can be seen as an effective analytical tool for facilitating plasma-based liquid biopsies.