Purification and Identification of Membrane Proteins from Urinary Extracellular Vesicles using Triton X-114 Phase Partitioning

Surface Proteome of Extracellular Vesicles and Correlation Analysis Reveal Breast Cancer Biomarkers

Breast cancer (BC) is the second most frequently diagnosed cancer and accounts for approximately 25% of new cancer cases in Canadian women. Using biomarkers as a less-invasive BC diagnostic method is currently under investigation but is not ready for practical application in clinical settings. During the last decade, extracellular vesicles (EVs) have emerged as a promising source of biomarkers because they contain cancer-derived proteins, RNAs, and metabolites. In this study, EV proteins from small EVs (sEVs) and medium EVs (mEVs) were isolated from BC MDA-MB-231 and MCF7 and non-cancerous breast epithelial MCF10A cell lines and then analyzed by two approaches: global proteomic analysis and enrichment of EV surface proteins by Sulfo-NHS-SS-Biotin labeling. From the first approach, proteomic profiling identified 2459 proteins, which were subjected to comparative analysis and correlation network analysis. Twelve potential biomarker proteins were identified based on cell line-specific expression and filtered by their predicted co-localization with known EV marker proteins, CD63, CD9, and CD81. This approach resulted in the identification of 11 proteins, four of which were further investigated by Western blot analysis. The presence of transmembrane serine protease matriptase (ST14), claudin-3 (CLDN3), and integrin alpha-7 (ITGA7) in each cell line was validated by Western blot, revealing that ST14 and CLDN3 may be further explored as potential EV biomarkers for BC. The surface labeling approach enriched proteins that were not identified using the first approach. Ten potential BC biomarkers (Glutathione S-transferase P1 (GSTP1), Elongation factor 2 (EEF2), DEAD/H box RNA helicase (DDX10), progesterone receptor (PGR), Ras-related C3 botulinum toxin substrate 2 (RAC2), Disintegrin and metalloproteinase domain-containing protein 10 (ADAM10), Aconitase 2 (ACO2), UTP20 small subunit processome component (UTP20), NEDD4 binding protein 2 (N4BP2), Programmed cell death 6 (PDCD6)) were selected from surface proteins commonly identified from MDA-MB-231 and MCF7, but not identified in MCF10A EVs. In total, 846 surface proteins were identified from the second approach, of which 11 were already known as BC markers. This study supports the proposition that Evs are a rich source of known and novel biomarkers that may be used for non-invasive detection of BC. Furthermore, the presented datasets could be further explored for the identification of potential biomarkers in BC.

Proteomic dissection of large extracellular vesicle surfaceome unravels interactive surface platform

The extracellular vesicle (EV) surface proteome (surfaceome) acts as a fundamental signalling gateway by bridging intra- and extracellular signalling networks, dictates EVs' capacity to communicate and interact with their environment, and is a source of potential disease biomarkers and therapeutic targets. However, our understanding of surface protein composition of large EVs (L-EVs, 100-800 nm, mean 310 nm, ATP5F1A, ATP5F1B, DHX9, GOT2, HSPA5, HSPD1, MDH2, STOML2), a major EV-subtype that are distinct from small EVs (S-EVs, 30-150 nm, mean 110 nm, CD44, CD63, CD81, CD82, CD9, PDCD6IP, SDCBP, TSG101) remains limited. Using a membrane impermeant derivative of biotin to capture surface proteins coupled to mass spectrometry analysis, we show that out of 4143 proteins identified in density-gradient purified L-EVs (1.07-1.11 g/mL, from multiple cancer cell lines), 961 proteins are surface accessible. The surface molecular diversity of L-EVs include (i) bona fide plasma membrane anchored proteins (cluster of differentiation, transporters, receptors and GPI anchored proteins implicated in cell-cell and cell-ECM interactions); and (ii) membrane surface-associated proteins (that are released by divalent ion chelator EDTA) implicated in actin cytoskeleton regulation, junction organization, glycolysis and platelet activation. Ligand-receptor analysis of L-EV surfaceome (e.g., ITGAV/ITGB1) uncovered interactome spanning 172 experimentally verified cognate binding partners (e.g., ANGPTL3, PLG, and VTN) with highest tissue enrichment for liver. Assessment of biotin inaccessible L-EV proteome revealed enrichment for proteins belonging to COPI/II-coated ER/Golgi-derived vesicles and mitochondria. Additionally, despite common surface proteins identified in L-EVs and S-EVs, our data reveals surfaceome heterogeneity between the two EV-subtype. Collectively, our study provides critical insights into diverse proteins operating at the interactive platform of L-EVs and molecular leads for future studies seeking to decipher L-EV heterogeneity and function.

CHICKN: extraction of peptide chromatographic elution profiles from large scale mass spectrometry data by means of Wasserstein compressive hierarchical cluster analysis

Background

The clustering of data produced by liquid chromatography coupled to mass spectrometry analyses (LC-MS data) has recently gained interest to extract meaningful chemical or biological patterns. However, recent instrumental pipelines deliver data which size, dimensionality and expected number of clusters are too large to be processed by classical machine learning algorithms, so that most of the state-of-the-art relies on single pass linkage-based algorithms.

Results

We propose a clustering algorithm that solves the powerful but computationally demanding kernel k-means objective function in a scalable way. As a result, it can process LC-MS data in an acceptable time on a multicore machine. To do so, we combine three essential features: a compressive data representation, Nyström approximation and a hierarchical strategy. In addition, we propose new kernels based on optimal transport, which interprets as intuitive similarity measures between chromatographic elution profiles.

Conclusions

Our method, referred to as CHICKN, is evaluated on proteomics data produced in our lab, as well as on benchmark data coming from the literature. From a computational viewpoint, it is particularly efficient on raw LC-MS data. From a data analysis viewpoint, it provides clusters which differ from those resulting from state-of-the-art methods, while achieving similar performances. This highlights the complementarity of differently principle algorithms to extract the best from complex LC-MS data.

Comparison of urinary extracellular vesicle isolation methods for transcriptomic biomarker research in diabetic kidney disease

Urinary Extracellular Vesicles (uEV) have emerged as a source for biomarkers of kidney damage, holding potential to replace the conventional invasive techniques including kidney biopsy. However, comprehensive studies characterizing uEV isolation methods with patient samples are rare. Here we compared performance of three established uEV isolation workflows for their subsequent use in transcriptomics analysis for biomarker discovery in diabetic kidney disease. We collected urine samples from individuals with type 1 diabetes with macroalbuminuria and healthy controls. We isolated uEV by Hydrostatic Filtration Dialysis (HFD), ultracentrifugation (UC), and a commercial kit- based isolation method (NG), each with different established urine clearing steps. Purified EVs were analysed by electron microscopy, nanoparticle tracking analysis, and Western blotting. Isolated RNAs were subjected to miRNA and RNA sequencing. HFD and UC samples showed close similarities based on mRNA sequencing data. NG samples had a lower number of reads and different mRNA content compared to HFD or UC. For miRNA sequencing data, satisfactory miRNA counts were obtained by all methods, but miRNA contents differed slightly. This suggests that the isolation workflows enrich specific subpopulations of miRNA-rich uEV preparation components. Our data shows that HFD,UC and the kit-based method are suitable methods to isolate uEV for miRNA-seq. However, only HFD and UC were suitable for mRNA-seq in our settings.

Proteomics of Extracellular Vesicles: Update on Their Composition, Biological Roles and Potential Use as Diagnostic Tools in Atherosclerotic Cardiovascular Diseases

Extracellular vesicles (EVs) are lipid-bound vesicles released from cells under physiological and pathological conditions. Basing on biogenesis, dimension, content and route of secretion, they can be classified into exosomes, microvesicles (MVs) and apoptotic bodies. EVs have a key role as bioactive mediators in intercellular communication, but they are also involved in other physiological processes like immune response, blood coagulation, and tissue repair. The interest in studying EVs has increased over the years due to their involvement in several diseases, such as cardiovascular diseases (CVDs), and their potential role as biomarkers in diagnosis, therapy, and in drug delivery system development. Nowadays, the improvement of mass spectrometry (MS)-based techniques allows the characterization of the EV protein composition to deeply understand their role in several diseases. In this review, a critical overview is provided on the EV’s origin and physical properties, as well as their emerging functional role in both physiological and disease conditions, focusing attention on the role of exosomes in CVDs. The most important cardiac exosome proteomic studies will be discussed giving a qualitative and quantitative characterization of the exosomal proteins that could be used in future as new potential diagnostic markers or targets for specific therapies.

Detergent Resistant Membrane Domains in Broccoli Plasma Membrane Associated to the Response to Salinity Stress

Detergent-resistant membranes (DRMs) microdomains, or “raft lipids”, are key components of the plasma membrane (PM), being involved in membrane trafficking, signal transduction, cell wall metabolism or endocytosis. Proteins imbibed in these domains play important roles in these cellular functions, but there are few studies concerning DRMs under abiotic stress. In this work, we determine DRMs from the PM of broccoli roots, the lipid and protein content, the vesicles structure, their water osmotic permeability and a proteomic characterization focused mainly in aquaporin isoforms under salinity (80 mM NaCl). Based on biochemical lipid composition, higher fatty acid saturation and enriched sterol content under stress resulted in membranes, which decreased osmotic water permeability with regard to other PM vesicles, but this permeability was maintained under control and saline conditions; this maintenance may be related to a lower amount of total PIP1 and PIP2. Selective aquaporin isoforms related to the stress response such as PIP1;2 and PIP2;7 were found in DRMs and this protein partitioning may act as a mechanism to regulate aquaporins involved in the response to salt stress. Other proteins related to protein synthesis, metabolism and energy were identified in DRMs independently of the treatment, indicating their preference to organize in DMRs.

Enhanced and sustainable pretreatment for bioconversion and extraction of resveratrol from peanut skin using ultrasound-assisted surfactant aqueous system with microbial consortia immobilized on cellulose

In this study, the ultrasound-assisted surfactant aqueous system coupled with microbial consortia immobilized by cellulose has been created as an enhanced and sustainable method for the bioconversion and extraction of resveratrol from peanut skin. Based on central composite design, and several single-factor experiments, we derived the optimal bioconversion and extraction system. Microbial consortia consist of Yeast CICC 1912, Aspergillus oryzae 3.951 and Aspergillus niger 3.3148 were chosen to be immobilized using cellulose. Other treatment conditions include concentration of surfactant as 3% (w/v), temperature as 30 °C, time as 36 h, ultrasonic power as 250 W and liquid to solid ratio as 25:1 mL/g. Under these conditions, we achieved a promising yield of resveratrol 96.58 μg/g, which is 4.02 folds compared to the untreated sample. This sustainable and green method not only enhanced the production of resveratrol but also improved the safety and reliability of the bioconversion and extraction process. Our novel method has shown great potential to realize large-scale bioconversion and extraction of bioactive compounds from plant waste.

Surfaceome of Exosomes Secreted from the Colorectal Cancer Cell Line SW480: Peripheral and Integral Membrane Proteins Analyzed by Proteolysis and TX114

Exosomes are important bidirectional cell-cell communicators in normal and pathological physiology. Although exosomal surface membrane proteins (surfaceome) enable target cell recognition and are an attractive source of disease marker, they are poorly understood. Here, a comprehensive surfaceome analysis of exosomes secreted by the colorectal cancer cell line SW480 is described. Sodium carbonate extraction/Triton X-114 phase separation and mild proteolysis (proteinase K, PK) of intact exosomes is used in combination with label-free quantitative mass spectrometry to identify 1025 exosomal proteins of which 208 are predicted to be integral membrane proteins (IMPs) according to TOPCONS and GRAVY scores. Interrogation of UniProt database-annotated proteins reveals 124 predicted peripherally-associated membrane proteins (PMPs). Surprisingly, 108 RNA-binding proteins (RBPs)/RNA nucleoproteins (RNPs) are found in the carbonate/Triton X-114 insoluble fraction. Mild PK treatment of SW480-GFP labeled exosomes reveal 58 proteolytically cleaved IMPs and 14 exoplasmic PMPs (e.g., CLU/GANAB/LGALS3BP). Interestingly, 18 RBPs/RNPs (e.g., EIF3L/RPL6) appear bound to the outer exosome surface since they are sensitive to PK proteolysis. The finding that outer surface-localized miRNA Let-7a-5p is RNase A-resistant, but degraded by a combination of RNase A/PK treatment suggests exosomal miRNA species also reside on the outer surface of exosomes bound to RBPs/RNPs.

An Update on Isolation Methods for Proteomic Studies of Extracellular Vesicles in Biofluids

Extracellular vesicles (EVs) are lipid bilayer enclosed particles which present in almost all types of biofluids and contain specific proteins, lipids, and RNA. Increasing evidence has demonstrated the tremendous clinical potential of EVs as diagnostic and therapeutic tools, especially in biofluids, since they can be detected without invasive surgery. With the advanced mass spectrometry (MS), it is possible to decipher the protein content of EVs under different physiological and pathological conditions. Therefore, MS-based EV proteomic studies have grown rapidly in the past decade for biomarker discovery. This review focuses on the studies that isolate EVs from different biofluids and contain MS-based proteomic analysis. Literature published in the past decade (2009.1-2019.7) were selected and summarized with emphasis on isolation methods of EVs and MS analysis strategies, with the aim to give an overview of MS-based EV proteomic studies and provide a reference for future research.

A sequential separation strategy for facile isolation and comprehensive analysis of human urine N-glycoproteome

Urine is an attractive and non-invasive alternative source to tissue, blood or other biofluids for biomarker screening in clinical research. In normal human adult urine, 48% of the total urinary protein is in the sediment, 49% is soluble and the remaining 3% is contained in urinary extracellular vesicles (EVs). The soluble proteins and EV proteins in urine have attracted particular attention in recent years as cancer diagnostics. Furthermore, considering the important role of N-glycoproteins in practically all physiological processes, including regulating receptor-ligand binding, cell-cell interactions, inflammatory response and tumour progression, N-glycoproteome in human urine is an invaluable target for monitoring the physiological status and pathological changes of the kidney and urinary tract. Given the different origins of the soluble proteins and EV proteins in the urine, different N-glycoproteome patterns exist. Therefore, isolating the soluble N-glycoproteins and EV N-glycoproteins for separate analysis will provide a more specific and comprehensive view and provide a deeper understanding of human urinary N-glycoproteome. In this work, we developed a sequential separation method that isolates urinary soluble proteins and EV proteins via stepwise ultrafiltration based on their obvious size difference. A facile and reproducible protein isolation was achieved using this strategy. Subsequent N-glycoproteome enrichment and identification revealed distinct patterns in the two sub-proteomes of urine with more than 60% differential N-glycopeptides. A more comprehensive picture of the urinary N-glycoproteome with close to 1800 identified N-glycopeptides was obtained by this new analysis strategy, therefore making it advantageous for urinary biomarker screening. Graphical abstract A sequential separation method that isolates urinary soluble proteins and EV proteins via stepwise ultrafiltration was developed in this work. Subsequent N-glycopeptides enrichment and mass spectrometry analysis reveals distinct N-glycoproteome patterns in the two sub-proteomes of urine and a deep mapping of close to 1800 N-glycopeptides.

[Effect of outer membrane vesicles derived from Escherichia coli on proliferation, apoptosis and migration of human neuroblastoma SK-N-SH cells in vitro]

OBJECTIVE

To investigate the effect of outer membrane vesicles derived from Escherichia coli on proliferation, apoptosis and migration of human neuroblastoma SK-N-SH cells in vitro.

METHODS

The outer membrane vesicles (OMVs) were obtained from wild-type Escherichia coli with ultracentrifugation method, and the morphology of the OMVs was observed by transmission electron microscopy and the vesicle diameter was determined using MALVERN ZEN3690. Human neuroblastoma SK-N-SH cells were treated with the OMVs at low (100 µg/mL), moderate (500 µg/mL) and high (1000 µg/mL) doses, and 24, 48 and 72 h later, the cell proliferation activity was detected with MTT assay. The expressions of apoptosis-related marker caspase-3 was detected using Western blotting, and TUNEL assay was performed to detect the cell apoptosis. The migration capacity of SK-N-SH cells was evaluated using Transwell migration assay.

RESULTS

The isolated OMVs showed a circular or elliptical hollow structure with double-layer membrane and a diameter range of 30-450 nm. Compared with the control cells, SK-N-SH cells treated with the OMVs showed significantly lowered cell proliferation capacity with enhanced expression of caspase-3. Treatment of the cells with the OMVs resulted in increased cell apoptosis and significantly lowered migration capacity (P<0.05).

CONCLUSION

The OMVs derived from Escherichia coli can produce cytotoxicity against SK-N-SH cells and might serve as a therapeutic agent for refractory neuroblastoma.