Detection of Tear Components Using Matrix-Assisted Laser Desorption Ionization/Time-of-Flight Mass Spectrometry for Rapid Dry Eye Diagnosis

Analysis and Characterization of the Extracellular Vesicles Released in Non-Cancer Diseases Using Matrix-Assisted Laser Desorption Ionization/Mass Spectrometry

The extracellular vesicles (EVs) released by cells play a crucial role in intercellular communications and interactions. The direct shedding of EVs from the plasma membrane represents a fundamental pathway for the transfer of properties and information between cells. These vesicles are classified based on their origin, biogenesis, size, content, surface markers, and functional features, encompassing a variety of bioactive molecules that reflect the physiological state and cell type of origin. Such molecules include lipids, nucleic acids, and proteins. Research efforts aimed at comprehending EVs, including the development of strategies for their isolation, purification, and characterization, have led to the discovery of new biomarkers. These biomarkers are proving invaluable for diagnosing diseases, monitoring disease progression, understanding treatment responses, especially in oncology, and addressing metabolic, neurological, infectious disorders, as well as advancing vaccine development. Matrix-Assisted Laser Desorption Ionization (MALDI)/Mass Spectrometry (MS) stands out as a leading tool for the analysis and characterization of EVs and their cargo. This technique offers inherent advantages such as a high throughput, minimal sample consumption, rapid and cost-effective analysis, and user-friendly operation. This review is mainly focused on the primary applications of MALDI-time-of-flight (TOF)/MS in the analysis and characterization of extracellular vesicles associated with non-cancerous diseases and pathogens that infect humans, animals, and plants.

Extracellular vesicle biomarkers in ocular fluids associated with ophthalmic diseases

Extracellular vesicles (EVs) are released as highly stable lipid bilayer particles carrying proteins, lipids, glycans and miRNAs. The contents of EVs vary based on the cellular origin, biogenesis route and the functional state of the cell suggesting certain diseased conditions. A growing body of evidence show that EVs carry important molecules implicated in the development and progression of ophthalmic diseases. EVs associated with ophthalmic diseases are mainly carried by one of the three ocular biofluids which include tears, aqueous humor and vitreous humor. This review summarizes the list of EV derived biomarkers identified thus far in ocular fluids for ophthalmic disease diagnosis. Further, the methods used for sample collection, sample volume and the sample numbers used in these studies have been highlighted. Emphasis has been given to describe the EV isolation and the characterization methods used, EV size profiled and the EV concentrations analyzed by these studies, thus providing a roadmap for future EV biomarker studies in ocular fluids.

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.

RNA Profiles of Tear Fluid Extracellular Vesicles in Patients with Dry Eye-Related Symptoms

Currently, diagnosing and stratifying dry eye disease (DED) require multiple tests, motivating interest in a single definitive test. The purpose of this study was to investigate the potential for using tear fluid extracellular vesicle (EV)-RNA in DED diagnostics. With a role in intercellular communication, nanosized EVs facilitate the protected transport of diverse bioactive molecules in biofluids, including tears. Schirmer strips were used to collect tears from 10 patients presenting with dry eye-related symptoms at the Norwegian Dry Eye Clinic. The samples comprised two groups, five from patients with a tear film break-up time (TBUT) of 2 s and five from patients with a TBUT of 10 s. Tear fluid EV-RNA was isolated using a Qiagen exoRNeasy Midi Kit, and the RNA was characterized using Affymetrix ClariomTM D microarrays. The mean signal values of the two groups were compared using a one-way ANOVA. A total of 26,639 different RNA transcripts were identified, comprising both mRNA and ncRNA subtypes. Approximately 6% of transcripts showed statistically significant differential abundance between the two groups. The mRNA sodium channel modifier 1 (SCNM1) was detected at a level 3.8 times lower, and the immature microRNA-130b was detected at a level 1.5 times higher in the group with TBUT 2 s compared to the group with TBUT 10 s. This study demonstrates the potential for using tear fluid EV-RNA in DED diagnostics.

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.

Revealing the presence of tear extracellular vesicles in Keratoconus

Extracellular vesicles (EVs) are lipid-bound vesicles that originate from the endosomal system or budded off from the plasma membrane. EVs are involved in cell-cell communication via transporting DNA, RNA, and proteins from one cell to another. Tear EVs (tEVs) have been reported in dry eye, Sjӧgren's Syndrome, and primary open-angle glaucoma. In this study, we sought to investigate the presence of tEVs in relation to keratoconus (KC). Tears were passively collected from the lateral meniscus from 10 healthy (5 males and 5 females) and 9 KC (4 males and 5 females) subjects. Tear samples were processed and analyzed using the ExoView™ R100. Statistical analysis was performed using a Mann-Whitney U non-parametric Student's t-test. All tEVs, in both Healthy and KC subjects, showed a CD9+ dominant tEV cohort independent of sex. A significant decrease in CD63+/CD9+ and CD63+/CD81+/CD9+ was found in the male KC tEVs (p < 0.05), but not in females compared to their healthy counterparts. Neither Healthy nor KC tEVs showed differences in the total number of tEVs, however significant differences were identified between the sexes (p < 0.05), with males having a higher number of tEVs. tEVs diameters ranged from 50 to 200 nm, in both Healthy and KC cohorts, with the majority in the 50-80 nm range suggesting exosome-dominant cohorts. To our knowledge, this is the first time, to date, that tEVs have been isolated and characterized in KCs. While further studies are warranted, the tEVs differences between KC and Healthy subjects suggest a potential role for tEVs in KC pathogenesis.

Tear Film miRNAs and Their Association With Human Dry Eye Disease

PURPOSE

miRNAs can regulate inflammatory pathways. The purpose of this work was to determine if inflammatory-related tear film miRNAs are associated with extracellular vesicles (EVs) in human non-Sjögren's Syndrome dry eye disease (DED) participants.

METHODS

Five DED and 5 non-DED human participants were recruited. Tears samples were collected by washing the ocular surface of both eyes with phosphate buffered saline, pooling samples from the right and left eyes, and purifying EVs from the samples with a polyethylene glycol (PEG) 8000 precipitation procedure. Samples were directly analyzed via ELISA or transmission electron microscopy (TEM), or RNA was isolated first from the EVs and evaluated with RNA-Seq.

RESULTS

EVs were identified in the tear film of both groups using TEM and ELISA. Following EV purification and RNA isolation, RNA-Seq determined that there were 126 EV miRNAs differentially expressed between the two groups when comparing their RNA cargoes. Ingenuity Pathways Analysis found 9 upregulated miRNAs that were associated with inflammation (miR-127-5p, miR-1273h-3p, miR-1288-5p, miR-130b-5p, miR-139-3p, miR-1910-5p, miR-203b-5p, miR-22-5p, and miR-4632-3p; all p < 0.049; fold regulation range = 1.43-1.67).

CONCLUSION

This study determined that EVs are present in the tear film and that tear EVs contain miRNAs that may be associated with DED inflammatory pathways.

Discovering the Secret of Diseases by Incorporated Tear Exosomes Analysis via Rapid-Isolation System: iTEARS

Nanoscale small extracellular vesicles (sEVs, exosomes) in tears allow us to investigate the multisignatures of diseases. However, the translations of tear sEVs for biomarker discovery and clinical diagnostics are practically limited by low recovery, long processing time, and small sample volume. Here, we report an incorporated tear-exosomes analysis via rapid-isolation system (iTEARS) via nanotechnology to discover the secrets of ocular disorders and systemic diseases. We isolate exosomes rapidly with high yield and purity from a few teardrops (∼10 μL) within 5 min via nanoporous membrane-based resonators for the quantitative detection and biomarker discovery through proteomic and transcriptomic analysis. We have identified 904 proteins, among which 228 proteins are discovered, 426 proteins are detected from exosomes of dry eye disease, and demonstrate CALML5, KRT6A, and S100P for the classification of dry eye disease. We have also investigated 484 miRNAs in tear exosomes and show miR-145-5p, miR-214-3p, miR-218-5p, and miR-9-5p are dysregulated during diabetic retinopathy development. We believe iTEARS can be used for improving molecular diagnostics via tears to identify ocular disorders, systemic diseases, and numerous other neurodegenerative diseases and cancer.

Tear and ocular surface disease biomarkers: A diagnostic and clinical perspective for ocular allergies and dry eye disease

Validated biomarkers to be used as biological tools for managing ocular surface diseases (OSDs) are still an unmet need in daily clinical practice. Many studies have contributed to the already extensive list of candidate biomarkers for these disorders. Dry eye (DE) and ocular allergy (OA) are complex and multifactorial diseases, often coexisting and with overlapping symptoms. The purpose of this review is to present a comprehensive updated revision of the most relevant biomarkers of DE and OA, with an emphasis on quantitative analyses and correlations with clinical parameter data. Analysis of biomarkers common for these pathologies has highlighted an important physiological process. Namely, the interleukin proteins (IL-1α, IL-1β and IL-17), tumour necrotic factor (TNFα) and interferon gamma (IFNγ; Th1-Th7 pathway) and IL-4, IL-5 and IL-13 (Th2 pathway) seem to represent similar inflammatory mechanisms. Moreover, changes in the levels of mucins (MUC1, MUC2, MUC4, MUC5 and MUC16) are common alterations in the tear film mucous layer. We also examine the current state of medical devices and the main limitations to their use in clinical practice. Translational research in biomarkers for clinical practice depends on a feasible transition from the laboratory to the point-of-care. This requires large-scale, coordinated clinical validation campaigns to select the biomarkers with the highest specificity and sensitivity and significant correlation with clinical parameters. Moreover, technical limitations of multiplexed quantitation systems must be overcome to detect and measure the levels of several biomarkers in very small samples. To ensure the future of biomarker research, significant progress is necessary in a number of fields. There is an urgent need for global unification of clinical classification and diagnostics criteria. Widespread integration of proteomic and transcriptomic data is paramount for performing meaningful analyses using appropriate bioinformatics tools and artificial intelligence systems.

Glaucoma Characterization by Machine Learning of Tear Metabolic Fingerprinting

Glaucoma is a common optic neuropathy disease affecting over 76 million people. Both timely diagnosis and progression monitoring are critical but challenging. Conventional characterization of glaucoma needs a combination of methods, calling for tedious procedures and experienced doctors. Herein, a platform through machine learning of tear metabolic fingerprinting (TMF) using nanoparticle enhanced laser desorption-ionization mass spectrometry is built. Direct TMF is obtained noninvasively, with fast speed and high reproducibility, using trace tear samples (down to 10 nL). Consequently, glaucoma patients are screened against healthy controls with the area under the curve (AUC) of 0.866, through machine learning of TMF. Further, primary open-angle glaucoma (POAG) is differentiated from primary angle-closure glaucoma (PACG) and an early-stage POAG is identified. Finally, a biomarker panel of six metabolites for glaucoma characterization (including screening, subtyping, and early diagnosis) with AUC of 0.827-0.891 is constructed, showing related metabolic pathways. The work will provide insights into eye diseases not limited to glaucoma.

Dry eye disease and proteomics

Dry eye disease (DED) is a highly prevalent disease worldwide mostly associated with age, though other factors such as screen use and contact lens wear explain why it is increasingly diagnosed in younger people. DED also disproportionately affects women. Symptoms include eye dryness, burning, pain and sensitivity to light that can significantly affect quality of life. This condition may progress to cause lasting damage to the ocular surface if left untreated. Currently, diagnosis is through assessment of signs and symptoms determined by clinical tests and questionnaires. However, there is considerable overlap between normal and DED result distributions of currently available metrics as signs and symptoms fluctuate over time and with disease severity. Importantly, the non-targeted approach of proteomics means that significant changes in novel proteins may be discovered. Proteomics is a powerful tool that has been applied to the field of DED to understand changes at a biochemical level, uncover new disease biomarkers and determine the success of clinical interventions. While individual proteins may not be sensitive enough when used as single biomarkers, proteomics opens the possibility to uncover several relevant proteins that may be combined in a panel to provide more accurate diagnostic value i.e. parallel testing. In this review we discuss the use of proteomics in DED research and the potential for application of proteomic results in the clinic. We also identify shortcomings and future avenues for research.

Metabolomics and lipidomics approaches in human tears: A systematic review

The human tear film is at the interface between the ocular surface and the external environment. Although investigation has been hindered by its small volume, improvements in preanalytical and analytical methods have allowed the omics approach to represent an innovative biomarker search strategy. There is still a significant lack of standardization, representing a barrier for performing between-studies comparisons and transferring experimental findings into clinical use and trials. We summarize the preanalytical and analytical procedures, describe the biomarkers that can be found using the metabo-lipidomics approach, and provide our expert opinion for omics investigations in human tears. For this systematic review of 38 studies, we searched PubMed by combining Boolean operators with the following keywords: tear, metabolomic, lipidomic, -omics. The human tear metabo-lipidome has been well-characterized in normal individuals using high-resolution liquid chromatography coupled with mass spectrometry. Lipid and metabolite profiles were influenced by ocular (e.g. dry eye disorders; Meibomian gland dysfunction; contact lens wear; glaucoma; keratoconus; pterygium) and systemic conditions (e.g. multiple sclerosis). Investigating the tear metabo-lipidome could improve our understanding of the pathogenesis of both ocular and systemic diseases, but also provide diagnostic as well as prognostic biomarkers.

Integrated Pipeline of Rapid Isolation and Analysis of Human Plasma Exosomes for Cancer Discrimination Based on Deep Learning of MALDI-TOF MS Fingerprints

Plasma exosomes have shown great potential for liquid biopsy in clinical cancer diagnosis. Herein, we present an integrated strategy for isolating and analyzing exosomes from human plasma rapidly and then discriminating different cancers excellently based on deep learning fingerprints of plasma exosomes. Sequential size-exclusion chromatography (SSEC) was developed efficiently for separating exosomes from human plasma. SSEC isolated plasma exosomes, taking as less as 2 h for a single sample with high purity such that the discard rates of high-density lipoproteins and low/very low-density lipoproteins were 93 and 85%, respectively. Benefitting from the rapid and high-purity isolation, the contents encapsulated in exosomes, covered by plasma proteins, were well profiled by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MS). We further analyzed 220 clinical samples, including 79 breast cancer patients, 57 pancreatic cancer patients, and 84 healthy controls. After MS data pre-processing and feature selection, the extracted MS feature peaks were utilized as inputs for constructing a multi-classifier artificial neural network (denoted as Exo-ANN) model. The optimized model avoided overfitting and performed well in both training cohorts and test cohorts. For the samples in the independent test cohort, it realized a diagnosed accuracy of 80.0% with an area under the curve of 0.91 for the whole group. These results suggest that our integrated pipeline may become a generic tool for liquid biopsy based on the analysis of plasma exosomes in clinics.

Single-particle analysis of tear fluid reveals abundant presence of tissue factor-exposing extracellular vesicles with strong coagulation activity

Extracellular vesicles (EVs) in easily accessible body fluids have emerged as a promising source for liquid biopsy. Although tear collection is fast, safe, and noninvasive, EVs of tear fluid are less studied and their involvement in physiological and pathological processes is largely unknown. The aim of present study was to analyze and characterize EVs in tear fluid at the single-particle level to reveal the population heterogeneity. A laboratory-built nano-flow cytometer (nFCM) was used to analyze the purity, size distribution, and particle concentration of EVs isolated from unstimulated tears (basal tears) upon double ultracentrifugation (17 min at 100,000×g, 4 °C) via side scattering detection. The expression of CD9, CD63, CD81, CD47, CD45, CD24, and EpCAM was assessed via immunofluorescent detection. The EV concentration in tear fluid was measured to be 1.1 ± 0.7 × 10¹¹ particles/mL, which is approximately 100-fold higher than that of plasma EVs. In particular, it was identified for the first time that tears have strong coagulant activity owing to the abundant presence of tissue factor (TF) on tear EVs. The concentration of TF-exposing EVs (4.4 ± 3.1 × 10¹⁰ particles/mL) was found to be approximately 100-fold higher than their counterparts in saliva (4.5 ± 2.1 × 10⁸ particles/mL). We postulate that TF-exposing vesicles in tears might play a role in host defense by promoting clot formation and thus reducing the risk of pathogen invasion. The coagulant activity of tears triggered by TF-exposing EVs could provide a new research perspective for ophthalmic research.