The use of in-strip digestion for fast proteomic analysis on tear fluid from dry eye patients

Systems biology of dry eye: Unraveling molecular mechanisms through multi-omics integration

Dry eye disease (DED) is a multifactorial condition with complex and incompletely understood molecular mechanisms. Advances in multi-omics technologies, including genomics, transcriptomics, proteomics, metabolomics, and microbiomics, have provided new insights into the pathophysiology of DED. Genomic analyses have identified key genetic variants linked to immune regulation and lacrimal gland function. Transcriptomic studies reveal upregulated inflammatory pathways in ocular surface tissues, implicating these as core drivers of chronic inflammation. Proteomic research highlights significant alterations in tear protein composition, especially proteins involved in inflammation and tissue repair. Metabolomics studies focus on disrupted lipid metabolism and oxidative stress, which are crucial in maintaining tear film stability. Furthermore, microbiome research has demonstrated reduced microbial diversity and increased pathogenic bacteria, exacerbating inflammatory responses. The integration of multi-omics data allows for the identification of novel biomarkers and therapeutic targets, enabling precision diagnostics and personalized treatments. Therefore, this review highlights the critical importance of multi-omics approaches in deepening our understanding of DED's complex molecular mechanisms and their potential to transform clinical management and therapeutic innovations in this challenging field.

Precision in Tear Fluid Biomarker Discovery: Quantitative Proteomic Profiling of Small-Volume, Individual Samples Using Capillary Tube Collection

Background: Tear fluid, rich in proteins, is a promising source of novel biomarkers for ocular and systemic health. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is the primary method for biomarker discovery. Still, factors such as limited sample volume, extracellular protein contamination, and reflex tearing can significantly impact results. Glass microcapillary tubes minimize these issues. Schirmer strips remain the most common collection method due to existing LC-MS/MS protocol optimization. Methods: In this study, we evaluated multiple digestion protocols for the shotgun quantitative LC-MS/MS analysis of small-volume tear fluid samples collected using glass capillary tubes. Protocol optimization was performed using pooled samples and then compared with the analysis of individual samples. Results: Using the optimized protocol, one μL samples were processed using a timsTOF Pro 2 mass spectrometer (Bruker) coupled online with an Evosep One liquid chromatography system (Evosep), leading to the identification of an average of 361 ± 63 proteins in pooled samples and 525 ± 123 proteins in individual small-volume tear fluid samples. Conclusions: This protocol highlights the practicality of using glass capillary tubes for comprehensive LC-MS/MS-based tear proteomics analysis, paving the way for detailed proteomics characterization of individual tear fluid samples rather than pooled samples. By shifting from pooled to individual samples, this approach greatly accelerates tear biomarker discovery, advancing precision and personalized medicine.

High-Throughput Tear Proteomics via In-Capillary Digestion for Biomarker Discovery

Tear fluid has emerged as a valuable resource for biomarker discovery; however, the limited sample volume, the dynamic composition, and the variability introduced by collection methods all present significant challenges to the analysis and interpretation of the results. A majority of tear proteomic studies have utilized Schirmer strips for tear fluid collection; however, microcapillary collection can provide a superior collection method for proteomic studies when analysis procedures are optimized. We developed a novel, high-throughput in-capillary trypsin digestion workflow that requires as little as 0.5 μL of tear fluid for bottom-up shotgun proteomics. The use of a single microcentrifuge tube for both tear collection and sample processing simplifies sample handling and minimizes both the sample loss and experimental errors associated with sample transfers. This streamlined approach also reduces sample processing time to under 2 h before overnight trypsin digestion, compared to the 5-8 h required by the other methods. Our method uses liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify more proteins with greater efficiency than the existing techniques. With this workflow, we identified 500-800 proteins per 0.5 μL sample without peptide fractionation, allowing for at least three technical replicates. The results showed a four-fold increase in the number of proteins identified in the samples. This approach validates the use of microcapillary tear collection, and the innovative processing technique significantly increases the throughput of tear proteomics for biomarker discovery.

Discovery and Verification of Sjögren's Syndrome Protein Biomarkers in Tears by Targeted LC-MRM

Sjögren's syndrome (SS) is an autoimmune rheumatic disorder characterized by exocrine gland dysfunction, mainly from the lacrimal and salivary glands. The disease causes severe aqueous dry eye syndrome (DED) and is associated with high rates of complications, including corneal ulceration, scaring, and perforation. Systemic complications may occur as well as a higher risk of developing lymphoma. Diagnosis of SS-DED is often delayed and difficult to establish. With the aim of discovering biomarkers to help discriminate SS-DED patients, a combination of untargeted and targeted LC-MS/MS analyses were performed on tear samples collected on Schirmer strips and subjected to tryptic digestion. Following the analysis of three cohorts and the development of two targeted LC-sMRM methods for the verification of putative biomarkers found in the first cohort of samples, 64 proteins could be linked to Sjögren's syndrome, in the hopes of helping to confirm diagnoses as well as potentially stratifying the severity of disease in these patients. Proteins that were increased in SS-DED showed activation of the immune system and alterations in homeostasis. Several proteases and protease inhibitors were found to be significantly changing in SS-DED, as well as a consistent decrease in specific proteins known to be secreted by the lacrimal gland.

Applications of artificial intelligence and bioinformatics methodologies in the analysis of ocular biofluid markers: a scoping review

PURPOSE

This scoping review summarizes the applications of artificial intelligence (AI) and bioinformatics methodologies in analysis of ocular biofluid markers. The secondary objective was to explore supervised and unsupervised AI techniques and their predictive accuracies. We also evaluate the integration of bioinformatics with AI tools.

METHODS

This scoping review was conducted across five electronic databases including EMBASE, Medline, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Web of Science from inception to July 14, 2021. Studies pertaining to biofluid marker analysis using AI or bioinformatics were included.

RESULTS

A total of 10,262 articles were retrieved from all databases and 177 studies met the inclusion criteria. The most commonly studied ocular diseases were diabetic eye diseases, with 50 papers (28%), while glaucoma was explored in 25 studies (14%), age-related macular degeneration in 20 (11%), dry eye disease in 10 (6%), and uveitis in 9 (5%). Supervised learning was used in 91 papers (51%), unsupervised AI in 83 (46%), and bioinformatics in 85 (48%). Ninety-eight papers (55%) used more than one class of AI (e.g. > 1 of supervised, unsupervised, bioinformatics, or statistical techniques), while 79 (45%) used only one. Supervised learning techniques were often used to predict disease status or prognosis, and demonstrated strong accuracy. Unsupervised AI algorithms were used to bolster the accuracy of other algorithms, identify molecularly distinct subgroups, or cluster cases into distinct subgroups that are useful for prediction of the disease course. Finally, bioinformatic tools were used to translate complex biomarker profiles or findings into interpretable data.

CONCLUSION

AI analysis of biofluid markers displayed diagnostic accuracy, provided insight into mechanisms of molecular etiologies, and had the ability to provide individualized targeted therapeutic treatment for patients. Given the progression of AI towards use in both research and the clinic, ophthalmologists should be broadly aware of the commonly used algorithms and their applications. Future research may be aimed at validating algorithms and integrating them in clinical practice.

Using machine learning model explanations to identify proteins related to severity of meibomian gland dysfunction

Meibomian gland dysfunction is the most common cause of dry eye disease and leads to significantly reduced quality of life and social burdens. Because meibomian gland dysfunction results in impaired function of the tear film lipid layer, studying the expression of tear proteins might increase the understanding of the etiology of the condition. Machine learning is able to detect patterns in complex data. This study applied machine learning to classify levels of meibomian gland dysfunction from tear proteins. The aim was to investigate proteomic changes between groups with different severity levels of meibomian gland dysfunction, as opposed to only separating patients with and without this condition. An established feature importance method was used to identify the most important proteins for the resulting models. Moreover, a new method that can take the uncertainty of the models into account when creating explanations was proposed. By examining the identified proteins, potential biomarkers for meibomian gland dysfunction were discovered. The overall findings are largely confirmatory, indicating that the presented machine learning approaches are promising for detecting clinically relevant proteins. While this study provides valuable insights into proteomic changes associated with varying severity levels of meibomian gland dysfunction, it should be noted that it was conducted without a healthy control group. Future research could benefit from including such a comparison to further validate and extend the findings presented here.

Expanded biochemical analyses of human tear fluid: Polyvalent faces of the schirmer strip

The tear film forms a protective barrier between the ocular surface and the external environment. Despite its small volume, recent advancements in preanalytical and analytical procedures have enabled its in-depth analysis using multiple approaches. However, the diversity of tear film collection methods and the lack of standardization in pre-analytical methods represent the main obstacles to reproducible results and comparison among different studies. In this study, we first improved the pre-analytical procedures for the extraction of various molecular entities from Schirmer strips (ScS). Subsequently, our investigation focused on analyzing the molecular variances that might occur between two primary tear collection methods: capillary tube (CT) and ScS. Additionally, we examined different parts of the ScS to underscore these variations, which could serve as crucial factors for developing a standardized, optimized protocol for sample processing. Our results show that the inclusion of surfactants in the extraction process enhanced both the yield of protein extraction and the number of proteins identified in ScS, by effectively lysing the cells and improving the solubility of several intracellular proteins. In addition to proteins, nucleic acids could also be recovered for gene expression analyses, particularly from the bulb region of the ScS which is placed in the cul-de-sac. Despite their diluted nature, extracts from ScS remain a suitable material for retrieving tear proteins such as IL-17A at levels as low as the fg/mL range, thanks to highly sensitive immunoassays. Collection methods can affect measured tear protein levels. Lactoferrin is found in higher percentages in capillary electrophoresis analysis of tears collected using ScS compared to tears collected by CT (39.6 ± 4.8% versus 31 ± 4.4%).

Targeted Workflow Investigating Variations in the Tear Proteome by Liquid Chromatography Tandem Mass Spectrometry

Proteins in tears have an important role in eye health and have been shown as a promising source of disease biomarkers. The goal of this study was to develop a robust, sensitive, and targeted method for profiling tear proteins to examine the variability within a group of healthy volunteers over three days. Inter-individual and inter-day variabilities were examined to contribute to understanding the normal variations in the tear proteome, as well as to establish which proteins may be better candidates as eventual biomarkers of specific diseases. Tear samples collected on Schirmer strips were subjected to bottom-up proteomics, and resulting peptides were analyzed using an optimized targeted method measuring 226 proteins by liquid chromatography-scheduled multiple reaction monitoring. This method was developed using an in-house database of identified proteins from tears compiled from high-resolution data-dependent liquid chromatography tandem mass spectrometry data. The measurement of unique peptide signals can help better understand the dynamics of each of these proteins in tears. Some interesting trends were seen in specific pathways or protein classes, including higher variabilities for those involved in glycolysis, glutathione metabolism, and cytoskeleton proteins and lower variation for those involving the degradation of the extracellular matrix. The overall aim of this study was to contribute to the field of tear proteomics with the development of a novel and targeted method that is highly amenable to the clinical laboratory using high flow LC and commonly used triple quadrupole mass spectrometry while ensuring that protein quantitation was reported based on unique peptides for each protein and robust peak areas with data normalization. These results report on variabilities on over 200 proteins that are robustly detected in tear samples from healthy volunteers with a simple sample preparation procedure.

Current uses of artificial intelligence in the analysis of biofluid markers involved in corneal and ocular surface diseases: a systematic review

Corneal and ocular surface diseases (OSDs) carry significant psychosocial and economic burden worldwide. We set out to review the literature on the application of artificial intelligence (AI) and bioinformatics for analysis of biofluid biomarkers in corneal and OSDs and evaluate their utility in clinical decision making. MEDLINE, EMBASE, Cochrane and Web of Science were systematically queried for articles using AI or bioinformatics methodology in corneal and OSDs and examining biofluids from inception to August 2021. In total, 10,264 articles were screened, and 23 articles consisting of 1058 individuals were included. Using various AI/bioinformatics tools, changes in certain tear film cytokines that are proinflammatory such as increased expression of apolipoprotein, haptoglobin, annexin 1, S100A8, S100A9, Glutathione S-transferase, and decreased expression of supportive tear film components such as lipocalin-1, prolactin inducible protein, lysozyme C, lactotransferrin, cystatin S, and mammaglobin-b, proline rich protein, were found to be correlated with pathogenesis and/or treatment outcomes of dry eye, keratoconus, meibomian gland dysfunction, and Sjögren's. Overall, most AI/bioinformatics tools were used to classify biofluids into diseases subgroups, distinguish between OSD, identify risk factors, or make predictions about treatment response, and/or prognosis. To conclude, AI models such as artificial neural networks, hierarchical clustering, random forest, etc., in conjunction with proteomic or metabolomic profiling using bioinformatics tools such as Gene Ontology or Kyoto Encylopedia of Genes and Genomes pathway analysis, were found to inform biomarker discovery, distinguish between OSDs, help define subgroups with OSDs and make predictions about treatment response in a clinical setting.

Pre-analytical sample handling effects on tear fluid protein levels

Tear fluid is emerging as a source of non-invasive biomarkers, both for ocular and systemic conditions. Accurate quantification of tear proteins can be improved by standardizing methods to collect and process tear fluid. The aim of this study was to determine sample handling factors that may influence the tear protein biomarker profile. Tear fluid was collected using Schirmer's strips. Tear proteins were extracted by elution through centrifugation. Total protein content was determined using the bicinchoninic acid assay. Key concepts that apply to the entire sample processing cycle are tear sampling, tear storage, protein extraction and data normalization. Differences in wetting or migration length were observed between Schirmer's strips from different manufacturers, and between protein-free and protein-rich solutions. One unit of migration length (mm) did not correspond to one unit of volume (µL). A positive correlation (r = 0.6671, p < 0.0001) was observed between migration length and total tear protein content. The most beneficial storage conditions were strips that were not stored (+ 21.8%), or underwent 'wet' storage (+ 11.1%). Protein recovery was the highest in 400 µL extraction buffer and independent of protein molecular weight. This study helps to explain inter- and intra-variability that is often seen with tear biomarker research. This information is critical to ensure accuracy of test results, as tear biomarkers will be used for patient management and in clinical trials in the near future. This study also highlights the need for standardization of Schirmer's strip manufacturing, tear fluid processing and analyte concentration normalization.

Tear proteomic analysis of young glasses, orthokeratology, and soft contact lens wearers

Contact lens-related ocular surface complications occur more often in teenagers and young adults. The purpose of this study was to determine changes in tear proteome of young patients wearing glasses (GL), orthokeratology lenses (OK), and soft contact lenses (SCL). Twenty-two young subjects (10-26 years of age) who were established GL, OK, and SCL wearers were recruited. Proteomic data were collected using a data-independent acquisition-parallel accumulation serial fragmentation workflow. In total, 3406 protein groups were identified, the highest number of proteins identified in Schirmer strip tears to date. Eight protein groups showed higher abundance, and 11 protein groups showed lower abundance in the SCL group compared to the OK group. In addition, the abundance of 82 proteins significantly differed in children compared to young adult GL wearers, among which 67 proteins were higher, and 15 proteins were lower in children. These 82 proteins were involved in inflammation, immune, and glycoprotein metabolic biological processes. In summary, this work identified over 3000 proteins in Schirmer Strip tears. The results indicated that tear proteomes were altered by orthokeratology and soft contact wear and age, which warrants further larger-scale study on the ocular surface responses of teenagers and young adults separately to contact lens wear. SIGNIFICANCE: In this work, we examined the tear proteomes of young patients wearing glasses, orthokeratology lenses, and soft contact lenses using a data-independent acquisition-parallel accumulation serial fragmentation (diaPASEF) workflow and identified 3406 protein groups in Schirmer strip tears. Nineteen protein groups showed significant abundance changes between orthokeratology and soft contact lens wearers. Moreover, eighty-two protein groups significantly differed in abundance in children and young adult glasses wearers. As a pilot study, this work provides a deep coverage of tear proteome and suggests the need to investigate ocular responses to contact lens wear separately for children and young adults.

Analysis and comparison of tear protein profiles in dogs using different tear collection methods

BACKGROUND

Tear proteomic analysis has become an important tool in medical and veterinary research. The tear collection method could influence the tear protein profile. This study aims to evaluate the protein profiles of dog tears collected using microcapillary tubes (MT), Schirmer tear strips (ST), and ophthalmic sponges (OS).

METHODS

The tear samples were collected using MT, ST, and OS. Tear protein profiles were analyzed using two-dimensional electrophoresis (2-DE) and the different protein spots' expression was compared. Fourteen protein spots were identified using liquid chromatography-tandem mass spectrometry (LC-MS/MS).

RESULTS

Tear protein concentrations ranged from 2.80 to 4.03 μg/μL, with no statistically significant differences among collection methods. Protein expression in each collection method differed in terms of both the number and intensity of the spots. There were 249, 327, and 330 protein spots found from tears collected with MT, ST, and OS, respectively. The proteins albumin, haptoglobin, and lactoferrin identified from OS were found to have higher spot intensities than other methods of collection. The use of MT demonstrated the downregulation of nine proteins.

CONCLUSIONS

The recent study supported that tear protein analysis is affected by different tear collection methods. Although ST is commonly used for tear collection, it provides insufficient information to study particular tear proteins.

Changes in Tear Proteomic Profile in Ocular Diseases

The search for proteomic biomarkers in ocular disease is one of the most important research directions in recent years. Reliable biomarkers can be an immense adjuvant for both diagnostic and therapeutic approaches. There is no more readily available ocular tissue for proteomic analysis than tear film, which makes an interesting target for the biomarker search. Tear film is a complex fluid consisting of a superficial lipid layer, which covers the aqueous-mucous layer. Its complexity makes it a perfect candidate for all the "omics" approaches. Glaucoma, cataract, age-related macular degeneration, and other diseases are commonly thought to have a multifactorial background. Currently, no reliable non-invasive tests are available that would help physicians with screening and further patient management. The aim of the study is to present modern methods of measuring biomarkers in tears, with particular emphasis on spectrometric methods, and to discuss their diagnostic and therapeutic usefulness.

Quercetin improves lacrimal gland function through its anti-oxidant actions: Evidence from animal studies, and a pilot study in healthy human volunteers

Anti-oxidant properties of polyphenols have been gaining medical attention as a preventive factor against aging and/or lifestyle diseases. In this study, we examined the anti-oxidant activity of quercetin improved tear function through its effects on the lacrimal gland in mice and humans. Six week-old diabetic mice, a model for decreased tear production, were fed for 12 weeks ad libitum with an experimental diet containing 0.5% quercetin. As a result, the tear volume was significantly improved compared to the control, despite no changes in body weight, food intake, lacrimal gland morphology or biochemical serum parameters. Moreover, significantly higher SOD-1 and SOD-2 protein levels were detected in the lacrimal glands of quercetin-treated mice by western blot. In addition, quercetin treatment of mouse corneal cell lines exposed to oxidative stress resulted in dose-dependent inhibition of ROS production and enhanced cell survival. Finally, we examined quercetin pharmacokinetics, specifically its presence in serum and tears subsequent to onion consumption in healthy volunteers, and found that the distribution of quercetin and its metabolite shifted from serum to tear following onion intake. An improvement in tear film stability also resulted following the intake by these healthy volunteers of a new, quercetin-rich onion cultivar ("Quergold") in powder form. These results suggested that quercetin improved tear function through its effects on the lacrimal gland in mice and humans.

Mass spectrometry-based tear proteomics for noninvasive biomarker discovery

The lacrimal film has attracted increasing interest in the last decades as a potential source of biomarkers of physiopathological states, due to its accessibility, moderate complexity, and responsiveness to ocular and systemic diseases. High-performance liquid chromatography-mass spectrometry (LC-MS) has led to effective approaches to tear proteomics, despite the intrinsic limitations in sample amounts. This review focuses on the recent progress in strategy and technology, with an emphasis on the potential for personalized medicine. After an introduction on lacrimal-film composition, examples of applications to biomarker discovery are discussed, comparing approaches based on pooled-sample and single-tear analysis. Then, the most critical steps of the experimental pipeline, that is, tear collection, sample fractionation, and LC-MS implementation, are discussed with reference to proteome-coverage optimization. Advantages and challenges of the alternative procedures are highlighted. Despite the still limited number of studies, tear quantitative proteomics, including single-tear investigation, could offer unique contributions to the identification of low-invasiveness, sustained-accessibility biomarkers, and to the development of personalized approaches to therapy and diagnosis.

Comparison of Different Mass Spectrometry Workflows for the Proteomic Analysis of Tear Fluid

The tear film is a multi-layer fluid that covers the corneal and conjunctival epithelia of the eye and provides lubrication, nutrients, and protection from the outside environment. Tear fluid contains a high concentration of proteins and has thus been recognized as a potential source of biomarkers for ocular disorders due to its proximity to disease sites on the ocular surface and the non-invasive nature of its collection. This is particularly true in the case of dry eye disease, which directly impacts the tear film and its components. Proteomic analysis of tear fluid is challenging mainly due to the wide dynamic range of proteins and the small sample volumes. However, recent advancements in mass spectrometry have revolutionized the field of proteomics enabling unprecedented depth, speed, and accuracy, even with small sample volumes. In this study using the Orbitrap Fusion Tribrid mass spectrometer, we compared four different mass spectrometry workflows for the proteomic analysis of tear fluid collected via Schirmer strips. We were able to establish a method of in-strip protein digestion that identified >3000 proteins in human tear samples from 11 healthy subjects. Our method offers a significant improvement in the number of proteins identified compared to previously reported methods without pooling samples.

Metabolic phenotyping of tear fluid as a prognostic tool for personalised medicine exemplified by T2DM patients

Background/aims

Concerning healthcare approaches, a paradigm change from reactive medicine to predictive approaches, targeted prevention, and personalisation of medical services is highly desirable. This raises demand for biomarker signatures that support the prediction and diagnosis of diseases, as well as monitoring strategies regarding therapeutic efficacy and supporting individualised treatments. New methodological developments should preferably rely on non-invasively sampled biofluids like sweat and tears in order to provide optimal compliance, reduce costs, and ensure availability of the biomaterial. Here, we have thus investigated the metabolic composition of human tears in comparison to finger sweat in order to find biofluid-specific marker molecules derived from distinct secretory glands. The comprehensive investigation of numerous biofluids may lead to the identification of novel biomarker signatures. Moreover, tear fluid analysis may not only provide insight into eye pathologies but may also be relevant for the prediction and monitoring of disease progression and/ or treatment of systemic disorders such as type 2 diabetes mellitus.

Methods

Sweat and tear fluid were sampled from 20 healthy volunteers using filter paper and commercially available Schirmer strips, respectively. Finger sweat analysis has already been successfully established in our laboratory. In this study, we set up and evaluated methods for tear fluid extraction and analysis using high-resolution mass spectrometry hyphenated with liquid chromatography, using optimised gradients each for metabolites and eicosanoids. Sweat and tears were systematically compared using statistical analysis. As second approach, we performed a clinical pilot study with 8 diabetic patients and compared them to 19 healthy subjects.

Results

Tear fluid was found to be a rich source for metabolic phenotyping. Remarkably, several molecules previously identified by us in sweat were found significantly enriched in tear fluid, including creatine or taurine. Furthermore, other metabolites such as kahweol and various eicosanoids were exclusively detectable in tears, demonstrating the orthogonal power for biofluid analysis in order to gain information on individual health states. The clinical pilot study revealed that many endogenous metabolites that have previously been linked to type 2 diabetes such as carnitine, tyrosine, uric acid, and valine were indeed found significantly up-regulated in tears of diabetic patients. Nicotinic acid and taurine were elevated in the diabetic cohort as well and may represent new biomarkers for diabetes specifically identified in tear fluid. Additionally, systemic medications, like metformin, bisoprolol, and gabapentin, were readily detectable in tears of patients.

Conclusions

The high number of identified marker molecules found in tear fluid apparently supports disease development prediction, developing preventive approaches as well as tailoring individual patients’ treatments and monitoring treatment efficacy. Tear fluid analysis may also support pharmacokinetic studies and patient compliance control.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00272-7.

Proteomic Analysis of Tears and Conjunctival Cells Collected with Schirmer Strips Using timsTOF Pro: Preanalytical Considerations

This study aimed to investigate the human proteome profile of samples collected from whole (W) Schirmer strips (ScS) and their two parts—the bulb (B) and the rest of the strip (R)—with a comprehensive proteomic approach using a trapped ion mobility mass spectrometer, the timsTOF Pro. Eight ScS were collected from two healthy subjects at four different visits to be separated into three batches, i.e., 4W, 4B, and 4R. In total, 1582 proteins were identified in the W, B, and R batches. Among all identified proteins, binding proteins (43.4%) and those with catalytic activity (42.2%) constituted more than 80% of the molecular functions. The most represented biological processes were cellular processes (31.2%), metabolic processes (20.8%), and biological regulation (13.1%). Enzymes were the most represented protein class (41%), consisting mainly of hydrolases (47.5%), oxidoreductases (22.1%), and transferases (16.7%). The bulb (B), which is in contact with the conjunctiva, might collect both tear and cell proteins and therefore promote the identification of more proteins. Processing B and R separately before mass spectrometry (MS) analysis, combined with the high data acquisition speed and the addition of ion-mobility-based separation in the timsTOF Pro, can bring a new dimension to biomarker investigations of a limited sample such as tear fluid.

Looking deeper into ocular surface health: an introduction to clinical tear proteomics analysis

Ocular surface diseases are becoming more prevalent worldwide. Reasons for this include the ongoing population ageing and increasing use of digital displays, although ophthalmologists have a wide selection of tools, which can be implemented in the evaluation of the ocular surface health, methods, which enable the in-depth study of biological functions are gaining more interest. These new approaches are needed, since the individual responses to ocular surface diseases and treatments can vary from person to person, and the correlations between clinical signs and symptoms are often low. Modern mass spectrometry (MS) methods can produce information on hundreds of tear proteins, which in turn can provide valuable information on the biological effects occurring on the ocular surface. In this review article, we will provide an overview of the different aspects, which are part of a successful tear proteomics study design and equip readers with a better understanding of the methods most suited for their MS-based tear proteomics study in the field of ophthalmology and ocular surface.

HBFP: a new repository for human body fluid proteome

Body fluid proteome has been intensively studied as a primary source for disease biomarker discovery. Using advanced proteomics technologies, early research success has resulted in increasingly accumulated proteins detected in different body fluids, among which many are promising biomarkers. However, despite a handful of small-scale and specific data resources, current research is clearly lacking effort compiling published body fluid proteins into a centralized and sustainable repository that can provide users with systematic analytic tools. In this study, we developed a new database of human body fluid proteome (HBFP) that focuses on experimentally validated proteome in 17 types of human body fluids. The current database archives 11 827 unique proteins reported by 164 scientific publications, with a maximal false discovery rate of 0.01 on both the peptide and protein levels since 2001, and enables users to query, analyze and download protein entries with respect to each body fluid. Three unique features of this new system include the following: (i) the protein annotation page includes detailed abundance information based on relative qualitative measures of peptides reported in the original references, (ii) a new score is calculated on each reported protein to indicate the discovery confidence and (iii) HBFP catalogs 7354 proteins with at least two non-nested uniquely mapping peptides of nine amino acids according to the Human Proteome Project Data Interpretation Guidelines, while the remaining 4473 proteins have more than two unique peptides without given sequence information. As an important resource for human protein secretome, we anticipate that this new HBFP database can be a powerful tool that facilitates research in clinical proteomics and biomarker discovery.

Database URL:https://bmbl.bmi.osumc.edu/HBFP/

Changes in tear protein profile in dogs with keratoconjunctivitis sicca following topical treatment using cyclosporine A

Background and Aim

Keratoconjunctivitis sicca (KCS) is a chronic inflammatory ocular disease that occurs in many dog breeds worldwide. This study aimed to investigate the tear protein pattern of healthy dogs, KCS dogs, and KCS dogs after treatment with cyclosporine A (CsA).

Materials and Methods

Twenty-eight dogs of any breed were enrolled in the study. The subjects were divided into three groups: Healthy, KCS, and CsA-treated dogs. Tear samples were collected using Schirmer strips. Tear proteins extracted from the strips were analyzed using two-dimensional electrophoresis. For the first dimension, total protein from tears was separated by isoelectric focusing. The second dimension was performed using 12.5% sodium dodecyl sulfate-polyacrylamide gel electrophoresis. The gel images were analyzed and the protein spots of differential expression were manually cut for protein annotation using mass spectrometry.

Results

In total, 12 protein spots were excised and subjected to protein identification. Associated with KCS, six protein spots were a downregulated protein, namely, lysozyme. The other six protein spots were upregulated in KCS dogs, consisting of heat shock protein beta-1, protein S100-A12, and keratin type II cytoskeletal 1 and 5. After treatment with CsA for 45 days, the lysozyme protein was still decreasing and the inflammation protein (S100-A12) was not identified.

Conclusion

Inflammatory tear proteins and proteins involved in cellular stress were present in KCS dogs and appeared to be reduced in medicated eyes. Treatment with topical CsA in the short term may not improve the activity of antibacterial proteins. Changes in the expression patterns of these four proteins might be useful for disease severity and progression assessment, as well as for exploring a novel method for dry eye management in dogs.

Human tear fluid analysis for clinical applications: progress and prospects

Introduction: Human blood and saliva are increasingly under investigation for the detection of biomarkers for early diagnosis of non-communicable (e.g.cancers) and communicable diseases like COVID-19. Exploring the potential application of human tears, an easily accessible body fluid, for the diagnosis of various diseases is the need of the hour.Areas covered: This review deals with a comprehensive account of applications of tear analysis using different techniques, their comparison and overall progress achieved till now. The techniques used for tear fluid analysis are HPLC/UPLC/SDS-PAGE, CE, etc., together with ELISA, Mass Spectrometry, etc. But, with advances in instrumentation and data processing methods, it has become easy to couple the various separation methods with highly sensitive optical techniques for the analysis of body fluids.Expert opinion: Tear analysis can provide valuable information about the health condition of the eyes since it contains several molecular constituents, and their relative concentrations may alter under abnormal conditions. Tear analysis has the advantage that it is totally non-invasive. This study recommends tear fluid as a reliable clinical sample to be probed by highly sensitive optical techniques to diagnose different health conditions, with special emphasis on eye diseases.

Critical role of mass spectrometry proteomics in tear biomarker discovery for multifactorial ocular diseases (Review)

The tear film is a layer of body fluid that maintains the homeostasis of the ocular surface. The superior accessibility of tears and the presence of a high concentration of functional proteins make tears a potential medium for the discovery of non-invasive biomarkers in ocular diseases. Recent advances in mass spectrometry (MS) have enabled determination of an in-depth proteome profile, improved sensitivity, faster acquisition speed, proven variety of acquisition methods, and identification of disease biomarkers previously lacking in the field of ophthalmology. The use of MS allows efficient discovery of tear proteins, generation of reproducible results, and, more importantly, determines changes of protein quantity and post-translation modifications in microliter samples. The present review compared techniques for tear collection, sample preparation, and acquisition applied for the discovery of tear protein markers in normal subjects and multifactorial conditions, including dry eye syndrome, diabetic retinopathy, thyroid eye disease and primary open-angle glaucoma, which require an early diagnosis for treatment. It also summarized the contribution of MS to early discovery by means of disease-related protein markers in tear fluid and the potential for transformation of the tear MS-based proteome to antibody-based assay for future clinical application.

Human body-fluid proteome: quantitative profiling and computational prediction

Empowered by the advancement of high-throughput bio technologies, recent research on body-fluid proteomes has led to the discoveries of numerous novel disease biomarkers and therapeutic drugs. In the meantime, a tremendous progress in disclosing the body-fluid proteomes was made, resulting in a collection of over 15 000 different proteins detected in major human body fluids. However, common challenges remain with current proteomics technologies about how to effectively handle the large variety of protein modifications in those fluids. To this end, computational effort utilizing statistical and machine-learning approaches has shown early successes in identifying biomarker proteins in specific human diseases. In this article, we first summarized the experimental progresses using a combination of conventional and high-throughput technologies, along with the major discoveries, and focused on current research status of 16 types of body-fluid proteins. Next, the emerging computational work on protein prediction based on support vector machine, ranking algorithm, and protein-protein interaction network were also surveyed, followed by algorithm and application discussion. At last, we discuss additional critical concerns about these topics and close the review by providing future perspectives especially toward the realization of clinical disease biomarker discovery.

Quantifying Sample Collection and Processing Impacts on Fiber-Based Tear Fluid Chemical Analysis

Purpose

Noninvasive analyses of tear fluid from humans and animal models in clinical and research settings most commonly use absorbent material for collection and processing. Still, the impact of these analytical techniques on tear chemical analyses remains largely unknown. The purpose of this study was to quantify the impacts of phenol red thread fiber-based tear sample collection and processing on the primary amine content.

Methods

Human tears were collected by placing the folded end of phenol red thread on the palpebral conjunctiva of the right eye for 20 seconds. The wetted thread was then processed using elution or extraction, and capillary electrophoresis with light-emitting diode-induced fluorescence detection was used for analysis and quantitation.

Results

Distinct processing methods impacted tear analysis differently. Primary amines adsorbed onto the thread partitioned in a chromatographic manner and thus any single portion of the wetted thread might not be representative of the whole sample. Quantitative assessment of five small molecule standards after on-thread processing showed significant overestimation of the actual concentration, with increased accuracy for larger volume samples. Yet collection of larger tear volumes introduced error in volume determination owing to evaporation and reduced small molecule separation resolution.

Conclusions

These results indicated that absorption-based tear fluid collection and processing significantly alter chemical content analysis, suggesting that the impacts of methods used should be regularly evaluated to standardize results drawn from different studies.

Translational Relevance

This study identifies potential inconsistencies and inaccuracies in tear analyses that are widespread across the published literature and clinical care.

Tear Proteomic Predictive Biomarker Model for Ocular Graft Versus Host Disease Classification

Purpose

Diagnosis of ocular graft-versus-host disease (oGVHD) is hampered by a lack of clinically-validated biomarkers. This study aims to predict disease severity on the basis of tear protein expression in mild oGVHD.

Methods

Forty-nine patients with and without chronic oGVHD after AHCT were recruited to a cross-sectional observational study. Patients were stratified using NIH guidelines for oGVHD severity: NIH 0 (none; n = 14), NIH 1 (mild; n = 9), NIH 2 (moderate; n = 16), and NIH 3 (severe; n = 10). The proteomic profile of tears was analyzed using liquid chromatography-tandem mass spectrometry. Random forest and penalized logistic regression were used to generate classification and prediction models to stratify patients according to disease severity.

Results

Mass spectrometry detected 785 proteins across all samples. A random forest model used to classify patients by disease grade achieved F1-measure values for correct classification of 0.95 (NIH 0), 0.8 (NIH 1), 0.74 (NIH 2), and 0.83 (NIH 3). A penalized logistic regression model was generated by comparing patients without oGVHD and those with mild oGVHD and applied to identify potential biomarkers present early in disease. A panel of 13 discriminant markers achieved significant diagnostic accuracy in identifying patients with moderate-to-severe disease.

Conclusions

Our work demonstrates the utility of tear protein biomarkers in classifying oGVHD severity and adds further evidence indicating ocular surface inflammation as a main driver of oGVHD clinical phenotype.

Translational Relevance

Expression levels of a 13-marker tear protein panel in AHCT patients with mild oGVHD may predict development of more severe oGVHD clinical phenotypes.

Development of a Quantitative Immunoassay for Tear Lacritin Proteoforms

Purpose

Lacritin is a tear glycoprotein with pro-tearing and pro-ocular surface homeostasis activities that is selectively deficient in most dry eye tears. Proteoforms include an active monomer, inactive polymers, and a splice variant termed lacritin-c. Quantitation of the different proteoforms of tear lacritin may provide a diagnostic tool for ocular diseases. Here, we report the development of an immunoassay for the quantification of multiple lacritin proteoforms in human tear samples.

Methods

Basal tears collected on Schirmer test strips with anesthesia were eluted by diffusion and centrifugation under optimized conditions. Tear protein concentrations were determined, and 2.56 µg of each sample was separated by SDS-PAGE followed by western blot analysis. Blots were challenged with anti-Pep Lac N-term antibodies. Detection was with fluorescent secondary antibodies visualized by the LI-COR Odyssey CLx imaging system and quantified with standard curves of recombinant lacritin.

Results

The percent total lacritin (ng lacritin/100 ng total protein) ranged from 1.8% to 14.8%. Monomer, lacritin-c, and polymer proteoform percent total protein ranged from 1.1% to 6.3%, 0.3% to 5.4%, and 0.7% to 5.7%, respectively. Monomer lacritin was detected at concentrations of 6 to 176 µM, with lacritin-c and polymer proteoforms at 2 to 46 µM and 1 to 23 µM, respectively.

Conclusions

This assay greatly exceeds the power and sensitivity of our prior lacritin enzyme-linked immunosorbent assay that was not capable of distinguishing monomer from polymers and lacritin-c proteoforms.

Translational Relevance

A new method has been developed to quantitate multiple proteoforms of tear lacritin in preparation for analyses of samples from clinical trials.

Comparative analysis of the tear protein profile in herpes simplex virus type 1 epithelial keratitis

BACKGROUND

Herpes simplex virus type 1 (HSV-1) keratitis is a major cause of corneal blindness in the world, and an in-depth understanding of its pathogenesis may help improve existing diagnosis and treatment. The purpose of this study is to compare and analysis the total tear protein profile of HSV-1 epithelial keratitis patients, and to quantify the potential candidate biomarkers of HSV-1 epithelial keratitis.

METHODS

We investigated the proteome in tear fluid from three HSV-1 epithelial keratitis patients and three healthy control subjects using nano-scale liquid chromatography-tandem mass spectrometry (nLC-MS/MS) analysis. Functional annotation of differentially expressed proteins was done with the Gene Ontology (GO) analysis. ELISA was done to quantify the potential candidate biomarkers in 26 clinical cases.

RESULTS

Tear fluid from three HSV-1 epithelial keratitis patients and three healthy control subjects contained a total of 1275 proteins and 326 proteins were unique to tear fluid of HSV-1 epithelial keratitis patients. Bioinformatics analysis revealed that tear proteins from HSV-1 epithelial keratitis patients may be involved in metabolic processes, antigen presentation, inflammatory response, and in the TNF-mediated and T cell receptor pathways. Furthermore, IL1A, IL12B, DEFB4A, and CAMP, which are associated with the inflammatory response and inhibition of viral infection, were significantly more abundant in the HSV-1 epithelial keratitis patients than in the healthy control subjects.

CONCLUSIONS

This study reports the proteomic profile of tears in HSV-1 epithelial keratitis for the first time and identifies a number of unique differentially expressed proteins.

Review of proteomics approach to eye diseases affecting the anterior segment

Visual impairment and blindness is a major health burden worldwide, and major ocular diseases causing visual impairment pertain to the anterior segment of the eye. Anterior segment ocular diseases are common, yet complex entities. Although many treatment options and surgical techniques are available for these ailments, the underlying cause and pathogenesis is still unclear. Finding ways to fundamentally treat these patients and rectify the underlying dysregulations leading to the disease may help cure patients completely without major complications. Proteomics approaches are a novel way to distinguish dysregulated proteins in a variety of biological tissues in a hypothesis-free manner, thus helping to find the responsible pathways leading to a certain disease. The aim of the current study is to review the available knowledge in scientific literature regarding the proteomics studies done on anterior segment eye diseases and suggest potential clinical implications to exploit the results of these studies. SIGNIFICANCE: Anterior segment ocular diseases are responsible for a major proportion of visual impairment and blindness worldwide. Although ophthalmologists have several treatment options that can alleviate or control the progression of these diseases, no definite cure is available for most of them. Moreover, because these diseases are progressive, prompt diagnosis is of utmost important. Proteomics studies enable us to identify and quantify the dysregulated proteins in a biological specimen in a hypothesis-free manner. Understanding the dysregulated protein pathways shines a light on the pathogenesis of the disease. Moreover, these dysregulated proteins may act as biomarkers to help in diagnosis and treatment follow-up. Hence, in this article we sought out to review the available scientific literature regarding the proteomics studies of anterior segment ocular diseases and to identify potential applications of proteomic studies in clinic.

An eye on the dog as the scientist's best friend for translational research in ophthalmology: Focus on the ocular surface

Preclinical animal studies provide valuable opportunities to better understand human diseases and contribute to major advances in medicine. This review provides a comprehensive overview of ocular parameters in humans and selected animals, with a focus on the ocular surface, detailing species differences in ocular surface anatomy, physiology, tear film dynamics and tear film composition. We describe major pitfalls that tremendously limit the translational potential of traditional laboratory animals (i.e., rabbits, mice, and rats) in ophthalmic research, and highlight the benefits of integrating companion dogs with clinical analogues to human diseases into preclinical pharmacology studies. This One Health approach can help accelerate and improve the framework in which ophthalmic research is translated to the human clinic. Studies can be conducted in canine subjects with naturally occurring or noninvasively induced ocular surface disorders (e.g., dry eye disease, conjunctivitis), reviewed herein, and tear fluid can be easily retrieved from canine eyes for various bioanalytical purposes. In this review, we discuss common tear collection methods, including capillary tubes and Schirmer tear strips, and provide guidelines for tear sampling and extraction to improve the reliability of analyte quantification (drugs, proteins, others).

Recent progress in the analysis of protein deamidation using mass spectrometry

Deamidation is a nonenzymatic and spontaneous posttranslational modification (PTM) that introduces changes in both structure and charge of proteins, strongly associated with aging proteome instability and degenerative diseases. Deamidation is also a common PTM occurring in biopharmaceutical proteins, representing a major cause of degradation. Therefore, characterization of deamidation alongside its inter-related modifications, isomerization and racemization, is critically important to understand their roles in protein stability and diseases. Mass spectrometry (MS) has become an indispensable tool in site-specific identification of PTMs for proteomics and structural studies. In this review, we focus on the recent advances of MS analysis in protein deamidation. In particular, we provide an update on sample preparation, chromatographic separation, and MS technologies at multi-level scales, for accurate and reliable characterization of protein deamidation in both simple and complex biological samples, yielding important new insight on how deamidation together with isomerization and racemization occurs. These technological progresses will lead to a better understanding of how deamidation contributes to the pathology of aging and other degenerative diseases and the development of biopharmaceutical drugs.

A Set of Global Metabolomic Biomarker Candidates to Predict the Risk of Dry Eye Disease

Purpose

We used ultraperformance liquid chromatography coupled with quadrupole/time-of-flight tandem mass spectrometry (UPLC-Q/TOF-MS/MS) to analyze the metabolic profile of reflex tears obtained from patients with dry eye disorders.

Methods

We performed a cross-sectional study involving 113 subjects: 85 patients diagnosed with dry eye syndrome (dry eye group) and 28 healthy volunteers (control group). Reflex tears (20–30 μl) were collected from the tear meniscus of both eyes of each subject using a Schirmer I test strip. MS data were acquired with a standard workflow by UPLC-Q/TOF-MS/MS. Metabolites were quantitatively analyzed and matched with entries in the Metlin, Massbank, and HMDB databases. Least absolute shrinkage and selection operator (LASSO) regression was conducted to detect important metabolites. Multiple logistic regression was used to identify the significant metabolic biomarker candidates for dry eye syndrome. Open database sources, including the Kyoto Encyclopedia of Genes and Genomes and MetaboAnalyst, were used to identify metabolic pathways.

Results

After the LASSO regression and multiple logistic regression analysis, 4 of 20 metabolic biomarker candidates were significantly correlated with Ocular Surface Disease Index score, 42 of 57 with fluorescein breakup time, and 26 of 57 with fluorescein staining. By focusing on the overlap of these three sets, 48 of 51 metabolites contributed to the incidence of dry eye and there were obvious changes in different age groups. Metabolic pathway analysis revealed that the main pathways were glucose metabolism, amino acid metabolism, and glutathione metabolism.

Conclusion

Dry eye syndrome induces changes in the metabolic profile of tears, and the trend differs with age. This evidence reveals the relationship between changes in metabolites, symptoms of dry eye syndrome, and age.

Altered mucins and aquaporins indicate dry eye outcome in patients undergoing Vitreo-retinal surgery

Vitreo-retinal (VR) surgeries induce conjunctival changes. However, there are no study reports regarding prevalence and severity of dry eye after these surgeries. This study evaluated dry eye outcome after VR surgery. Patients undergoing VR surgery classified as scleral buckle and microincision vitrectomy surgery (n = 44, mean age: 56.09±10.2 years) were recruited. Dry eye evaluation was done before and 8 weeks after surgery (2 weeks after omitting topical eye drops). Conjunctival imprint cytology for goblet cell count and tear Mucin 5AC (MUC5AC) protein estimation was done. Gene expressions of MUC5AC, MUC4, MUC16, Aquaporin 4 (AQP4) and AQP5 were analyzed in the conjunctival imprint cells by qPCR. None of the patients exhibited clinical signs of dry eye after VR surgery. But the conjunctival goblet cell density (GCD) was significantly lowered post-VR surgery (63% cases, **p = 0.012) with no alterations in the tear MUC5AC protein. Post-VR surgery, the conjunctival cell gene expression of MUC4, MUC16 and AQP4 were significantly increased (*p = 0.025, *p = 0.05 and *p = 0.02 respectively) and AQP5 was significantly lowered (*p = 0.037), with no change in MUC5AC expression. Tear cytokines were significantly increased post-VR surgery (anti-inflammatory: IL1RA, IL4, IL5, IL9, FGF; PDGFbb and pro-inflammatory: IL2, IL6, IL15, GMCSF and IFNg). Though clinical signs of dry eye were not observed after VR surgery, ocular surface changes in the form of reduced GCD, altered MUC5AC, MUC4, MUC16, AQP4, AQP5 and cytokines are suggestive of dry eye outcome at the molecular level especially inpatients aged above 51 years, especially female gender and those who are diabetic.

Dry Eye Disease: Emerging Approaches to Disease Analysis and Therapy

Dry eye disease (DED) is among the most common ocular disorders affecting tens of millions of individuals worldwide; however, the condition remains incompletely understood and treated. Valuable insights have emerged from multidisciplinary approaches, including immunometabolic analyses, microbiome analyses, and bioengineering. Furthermore, we have seen new developments in clinical assessment approaches and treatment strategies in the recent past. Here, we review the emerging frontiers in the pathobiology and clinical management of DED.

Integrated Tear Proteome and Metabolome Reveal Panels of Inflammatory-Related Molecules via Key Regulatory Pathways in Dry Eye Syndrome

Dry eye syndrome (DES) is a growing public health concern with a high global prevalence; however, the fundamental processes involved in its pathogenic mechanisms remain poorly understood. In the present study, we applied nanoscale liquid chromatography and quadrupole time-of-flight tandem mass spectrometry (nanoLC/Q-TOF-MS/MS) and ultraperformance LC/Q-TOF-MS/MS technologies on tear samples obtained from 18 dry eye patients and 19 healthy controls for integrated proteomic and metabolomic analyses. Overall, 1031 tear proteins were detected, while 190 proteins were determined to be significantly expressed in dry eye patients. Further functional analysis suggested that various biological processes were highly expressed and involved in the pathogenesis of DES, especially immune and inflammatory processes. In total, 156 named metabolites were identified, among which 34 were found to be significantly changed in dry eye patients. The results highlighted the key elements, especially inflammatory-related proteins and metabolites that played important roles in the development of DES. Further, the regulatory roles of primary pathways, including complement and coagulation cascades, glycolysis/gluconeogenesis, and amino acid metabolism, were also identified as processes involved in DES. Collectively, our work not only provided insight into the potential biomarkers of DES for diagnostic and prognostic purposes but extended our knowledge of the physiopathology of this syndrome.