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.

[1]  Luke P. Lee,et al.  Discovering the Secret of Diseases by Incorporated Tear Exosomes Analysis via Rapid-Isolation System: iTEARS. , 2022, ACS nano.

[2]  M. Kjaer,et al.  Circadian regulation of protein cargo in extracellular vesicles , 2022, Science advances.

[3]  L. Tong,et al.  Dry eye disease and proteomics. , 2022, The ocular surface.

[4]  T. Tomonaga,et al.  Comprehensive proteomic profiling of plasma and serum phosphatidylserine-positive extracellular vesicles reveals tissue-specific proteins , 2022, iScience.

[5]  Venkata. N. P. Vemuri,et al.  Cell types of origin of the cell-free transcriptome , 2022, Nature Biotechnology.

[6]  Xiaomei Yan,et al.  Single-particle analysis of tear fluid reveals abundant presence of tissue factor-exposing extracellular vesicles with strong coagulation activity. , 2021, Talanta.

[7]  H. C. Beck,et al.  LAMP2A regulates the loading of proteins into exosomes , 2021, bioRxiv.

[8]  C. Lindskog,et al.  A single–cell type transcriptomics map of human tissues , 2021, Science Advances.

[9]  R. Grandori,et al.  Mass spectrometry‐based tear proteomics for noninvasive biomarker discovery , 2021, Mass spectrometry reviews.

[10]  Luke P. Lee,et al.  Exosome detection via the ultrafast-isolation system: EXODUS , 2021, Nature Methods.

[11]  W. Hung,et al.  The RNA binding protein FMR1 controls selective exosomal miRNA cargo loading during inflammation , 2020, The Journal of cell biology.

[12]  Liang-Sheng Hu,et al.  Detection of Tear Components Using Matrix-Assisted Laser Desorption Ionization/Time-of-Flight Mass Spectrometry for Rapid Dry Eye Diagnosis. , 2020, Journal of proteome research.

[13]  M. Gao,et al.  Deconstruction of heterogeneity of size-dependent exosome subpopulations from human urine by profiling N-glycoproteomics and phosphoproteomics simultaneously. , 2020, Analytical chemistry.

[14]  S. Shippy,et al.  Tear analysis as the next routine body fluid test , 2020, Eye.

[15]  Yoon‐Kyoung Cho,et al.  EV-Ident: Identifying tumor-specific extracellular vesicles by size fractionation and single-vesicle analysis. , 2020, Analytical chemistry.

[16]  Hirobumi Sunayama,et al.  Antibody-conjugated signaling nanocavities fabricated by dynamic molding for detecting cancers using small extracellular vesicle markers from tears. , 2020, Journal of the American Chemical Society.

[17]  S. Badylak,et al.  Lipidomics and RNA sequencing reveal a novel subpopulation of nanovesicle within extracellular matrix biomaterials , 2020, Science Advances.

[18]  C. Okamoto,et al.  Tears - more to them than meets the eye: why tears are a good source of biomarkers in Parkinson's disease. , 2020, Biomarkers in medicine.

[19]  Joan W. Miller,et al.  Genetic LAMP2 deficiency accelerates the age-associated formation of basal laminar deposits in the retina , 2019, Proceedings of the National Academy of Sciences.

[20]  M. Marchisio,et al.  Multi-Omics Approach for Studying Tears in Treatment-Naïve Glaucoma Patients , 2019, International journal of molecular sciences.

[21]  M. Onofrj,et al.  Proteomics characterization of extracellular vesicles sorted by flow cytometry reveals a disease-specific molecular cross-talk from cerebrospinal fluid and tears in multiple sclerosis. , 2019, Journal of proteomics.

[22]  H. Girault,et al.  MALDI Detection of Exosomes: A Potential Tool for Cancer Studies , 2019, Chem.

[23]  M. Yashiro,et al.  A Pretreatment-Free, Polymer-Based Platform Prepared by Molecular Imprinting and Post-Imprinting Modifications for Sensing Intact Exosomes. , 2019, Angewandte Chemie.

[24]  Jing Xu,et al.  Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines , 2018, Journal of Extracellular Vesicles.

[25]  R. Mader,et al.  MALDI-MS Protein Profiling of Chemoresistance in Extracellular Vesicles of Cancer Cells. , 2018, Analytical chemistry.

[26]  M. Montanari,et al.  Pigment epithelium-derived factor hinders photoreceptor cell death by reducing intracellular calcium in the degenerating retina , 2018, Cell Death & Disease.

[27]  Su Chul Jang,et al.  Subpopulations of extracellular vesicles and their therapeutic potential. , 2018, Molecular aspects of medicine.

[28]  André M. N. Silva,et al.  Identification of distinct nanoparticles and subsets of extracellular vesicles by asymmetric flow field-flow fractionation , 2018, Nature Cell Biology.

[29]  Graça Raposo,et al.  Shedding light on the cell biology of extracellular vesicles , 2018, Nature Reviews Molecular Cell Biology.

[30]  A. Bandyopadhyay,et al.  Balancing functions of annexin A6 maintain equilibrium between hypertrophy and apoptosis in cardiomyocytes , 2015, Cell Death and Disease.

[31]  G. von Heijne,et al.  Tissue-based map of the human proteome , 2015, Science.

[32]  A. Levey,et al.  Proteomics of protein post-translational modifications implicated in neurodegeneration , 2014, Translational Neurodegeneration.

[33]  C. Bremer,et al.  Alarmin S100A8/S100A9 as a biomarker for molecular imaging of local inflammatory activity , 2014, Nature Communications.

[34]  J. Chiu,et al.  GADD45α and annexin A1 are involved in the apoptosis of HL-60 induced by resveratrol. , 2011, Phytomedicine : international journal of phytotherapy and phytopharmacology.

[35]  R. Nieuwland,et al.  Cell-derived vesicles exposing coagulant tissue factor in saliva. , 2011, Blood.

[36]  De-Quan Li,et al.  Dry eye-induced conjunctival epithelial squamous metaplasia is modulated by interferon-gamma. , 2007, Investigative ophthalmology & visual science.

[37]  Lokesh Kumar,et al.  Mfuzz: A software package for soft clustering of microarray data , 2007, Bioinformation.

[38]  B. Walcott The Lacrimal Gland and Its Veil of Tears. , 1998, News in physiological sciences : an international journal of physiology produced jointly by the International Union of Physiological Sciences and the American Physiological Society.

[39]  J. Gruenberg,et al.  ALIX and the multivesicular endosome: ALIX in Wonderland. , 2014, Trends in cell biology.