Perspectives and challenges in extracellular vesicles untargeted metabolomics analysis

Monitoring the electroactive cargo of extracellular vesicles can differentiate various cancer cell lines

Extracellular vesicles (EVs) are pivotal in cell-to-cell communication due to the array of cargo contained within these vesicles. EVs are considered important biomarkers for identification of disease, however most measurement approaches have focused on monitoring specific surface macromolecular targets. Our study focuses on exploring the electroactive component present within cargo from EVs obtained from various cancer and non-cancer cell lines using a disk carbon fiber microelectrode. Variations in the presence of oxidizable components were observed when the total cargo from EVs were measured, with the highest current detected in EVs from MCF7 cells. There were differences observed in the types of oxidizable species present within EVs from MCF7 and A549 cells. Single entity measurements showed clear spikes due to the detection of oxidizable cargo within EVs from MCF7 and A549 cells. These studies highlight the promise of monitoring EVs through the presence of varying electroactive components within the cargo and can drive a wave of new strategies towards specific detection of EVs for diagnosis and prognosis of various diseases.

Prediction of mass spectrometry ionization efficiency based on COSMO-RS and machine learning algorithms

Non-targeted analysis of high-resolution mass spectrometry (MS) can identify thousands of compounds, which also gives a huge challenge to their quantification. The aim of this study is to investigate the impact of mass spectrometry ionization efficiency on various compounds in food at different solvent ratios and to develop a predictive model for mass spectrometry ionization efficiency to enable non-targeted quantitative prediction of unknown compounds. This study covered 70 compounds in 14 different mobile phase ratio environments in positive ion mode to analyze the rules of the matrix effect. With the organic phase ratio from low to high, most compounds changed by 1.0 log units in log IE. The addition of formic acid enhanced the signal but also promoted the matrix effect, which often occurred in compounds with strong ionization capacity. It was speculated that the matrix effect was mainly in the form of competitive charge and charged droplet' gasification sites during MS detection. Subsequently, we present a log IE prediction method built using the COSMO-RS software and the artificial neural network (ANN) algorithm to address this difficulty and overcome the shortcomings of previous models, which always ignore the matrix effect. This model was developed following the principles of QSAR modeling recommended by the Organization for Economic Cooperation and Development (OECD). Furthermore, we validated this approach by predicting the log IE of 70 compounds, including those not involved in the log IE model development. The results presented demonstrate that the method we put forward has an excellent prediction accuracy for log IE (R2pred = 0.880), which means that it has the potential to predict the log IE of new compounds without authentic standards.

Regulation of immune responses to infection through interaction between stem cell-derived exosomes and toll-like receptors mediated by microRNA cargoes

Infectious diseases are among the factors that account for a significant proportion of disease-related deaths worldwide. The primary treatment approach to combat microbial infections is the use of antibiotics. However, the widespread use of these drugs over the past two decades has led to the emergence of resistant microbial species, making the control of microbial infections a serious challenge. One of the most important solutions in the field of combating infectious diseases is the regulation of the host's defense system. Toll-like receptors (TLRs) play a crucial role in the first primary defense against pathogens by identifying harmful endogenous molecules released from dying cells and damaged tissues as well as invading microbial agents. Therefore, they play an important role in communicating and regulating innate and adaptive immunity. Of course, excessive activation of TLRs can lead to disruption of immune homeostasis and increase the risk of inflammatory reactions. Targeting TLR signaling pathways has emerged as a new therapeutic approach for infectious diseases based on host-directed therapy (HDT). In recent years, stem cell-derived exosomes have received significant attention as factors regulating the immune system. The regulation effects of exosomes on the immune system are based on the HDT strategy, which is due to their cargoes. In general, the mechanism of action of stem cell-derived exosomes in HDT is by regulating and modulating immunity, promoting tissue regeneration, and reducing host toxicity. One of their most important cargoes is microRNAs, which have been shown to play a significant role in regulating immunity through TLRs. This review investigates the therapeutic properties of stem cell-derived exosomes in combating infections through the interaction between exosomal microRNAs and Toll-like receptors.

The Landscape of Biomimetic Nanovesicles in Brain Diseases

Brain diseases, such as brain tumors, neurodegenerative diseases, cerebrovascular diseases, and brain injuries, are caused by various pathophysiological changes, which pose a serious health threat. Brain disorders are often difficult to treat due to the presence of the blood-brain barrier (BBB). Biomimetic nanovesicles (BNVs), including endogenous extracellular vesicles (EVs) derived from various cells and artificial nanovesicles, possess the ability to penetrate the BBB and thus can be utilized for drug delivery to the brain. BNVs, especially endogenous EVs, are widely distributed in body fluids and usually carry various disease-related signal molecules such as proteins, RNA, and DNA, and may also be analyzed to understand the etiology and pathogenesis of brain diseases. This review covers the exhaustive classification and characterization of BNVs and pathophysiological roles involved in various brain diseases, and emphatically focuses on nanotechnology-integrated BNVs for brain disease theranostics, including various diagnosis strategies and precise therapeutic regulations (e.g., immunity regulation, disordered protein clearance, anti-neuroinflammation, neuroregeneration, angiogenesis, and the gut-brain axis regulation). The remaining challenges and future perspectives regarding the nanotechnology-integrated BNVs for the diagnosis and treatment of brain diseases are also discussed and outlined.

Exosomes and microvesicles in kidney transplantation: the long road from trash to gold

Kidney transplantation significantly enhances the survival rate and quality of life of patients with end-stage kidney disease. The ability to predict post-transplantation rejection events in their early phases can reduce subsequent allograft loss. Therefore, it is critical to identify biomarkers of rejection processes that can be acquired on routine analysis of samples collected by non-invasive or minimally invasive procedures. It is also important to develop new therapeutic strategies that facilitate optimisation of the dose of immunotherapeutic drugs and the induction of allograft immunotolerance. This review explores the challenges and opportunities offered by extracellular vesicles (EVs) present in biofluids in the discovery of biomarkers of rejection processes, as drug carriers and in the induction of immunotolerance. Since EVs are highly complex structures and their composition is affected by the parent cell's metabolic status, the importance of defining standardised methods for isolating and characterising EVs is also discussed. Understanding the major bottlenecks associated with all these areas will promote the further investigation of EVs and their translation into a clinical setting.

Investigation of rare earth-based magnetic nanocomposites for specific enrichment of exosomes from human plasma

Exosomes, also known as small extracellular vesicles, are widely present in a variety of body fluids (e.g., blood, urine, and saliva). Exosomes are becoming an alternative promising source of diagnostic markers for disease rich in cargo of metabolites, proteins, and nucleic acids. However, due to the low abundance and structure similarity with protein complex, the efficient isolation of exosomes is one of the most important issues for biomedical applications. With a higher order of f-orbitals in rare earth element, it will have strong adsorption toward the phosphate group on the surface of the phospholipid bilayer of exosomes. In this study, we systematically investigated the ability of various rare earths interacting with phosphate-containing molecules and plasma exosomes. One of the best binding europium was selected and used to synthesize core-shell magnetic nanomaterials (Fe3O4@SiO2@Eu2O3) for the enrichment of exosomes from human plasma. The developed nanomaterials exhibited higher enrichment capacity, less time consumption and more convenient handling compared to commonly used ultracentrifugation method. The nanomaterials were applied to separate exosomes from the plasma of patients with hepatocellular carcinoma and healthy controls for metabolomics study with high-resolution mass spectrometry, where 70 differentially expressed metabolites were identified, involving amino acid and lipid metabolic pathway. We anticipated the rare earth-based materials to be an alternative approach on exosome isolation for disease diagnosis or postoperative clinical monitoring.

Heterogeneous MXene Hybrid-Oriented Exosome Isolation and Metabolic Profiling for Early Screening, Subtyping and Follow-up Evaluation of Bladder Cancer

Exosome metabolite-based noninvasive liquid biopsy is an emerging research hotspot that tends to substitute current means in clinics. Nanostructure-based mass spectrometry enables continuous exosome isolation and metabolic profiling with superior analysis speed and high efficiency. Herein, we construct a heterogeneous MXene hybrid that possesses ternary binding sites for exosome capture and outstanding matrix performance for metabolite analysis. Upon optimizing experimental conditions, the average extraction of exosomes and their metabolic patterns from a 60 mL urine sample is completed within 45 s (40 samples per batch for 30 min). According to the exosomal metabolic patterns and the subsequently established biomarker panel, we distinguish early bladder cancer (BCa) from healthy controls with an area under the curve (AUC) value greater than 0.995 in model training and validation sets. As well, we realize subtype classification of BCa in the blind test on metabolic patterns, with an AUC value of 0.867. We also explore the significant biomarkers that are sensitive to follow-up patients, which indeed present reverse change levels compared with pathological progression. This study has the potential to guide the development of the liquid biopsy approach.

Aptamer-based technology for gastric cancer theranostics

Gastric cancer is one of the most common causes of cancer death worldwide. This cancer exhibits high molecular and phenotype heterogeneity. The overall survival rate for gastric cancer is very low because it is always diagnosed in the advanced stages. Therefore, early detection and treatment are of great significance. Currently, biomedical studies have tapped the potential clinical applicability of aptamer-based technology for gastric cancer diagnosis and targeted therapy. Herein, we summarize the enrichment and evolution of relevant aptamers, followed by documentation of the recent developments in aptamer-based techniques for early diagnosis and precision therapy for gastric cancers.

Exploring the Metabolic Differences between Cisplatin- and UV Light-Induced Apoptotic Bodies in HK-2 Cells by an Untargeted Metabolomics Approach

Among the extracellular vesicles, apoptotic bodies (ABs) are only formed during the apoptosis and perform a relevant role in the pathogenesis of different diseases. Recently, it has been demonstrated that ABs from human renal proximal tubular HK-2 cells, either induced by cisplatin or by UV light, can lead to further apoptotic death in naïve HK-2 cells. Thus, the aim of this work was to carry out a non-targeted metabolomic approach to study if the apoptotic stimulus (cisplatin or UV light) affects in a different way the metabolites involved in the propagation of apoptosis. Both ABs and their extracellular fluid were analyzed using a reverse-phase liquid chromatography-mass spectrometry setup. Principal components analysis showed a tight clustering of each experimental group and partial least square discriminant analysis was used to assess the metabolic differences existing between these groups. Considering the variable importance in the projection values, molecular features were selected and some of them could be identified either unequivocally or tentatively. The resulting pathways indicated that there are significant, stimulus-specific differences in metabolites abundancies that may propagate apoptosis to healthy proximal tubular cells; thus, we hypothesize that the share in apoptosis of these metabolites might vary depending on the apoptotic stimulus.

A survey to evaluate parameters governing the selection and application of extracellular vesicle isolation methods

Extracellular vesicles (EVs) continue to gain interest across the scientific community for diagnostic and therapeutic applications. As EV applications diversify, it is essential that researchers are aware of challenges, in particular the compatibility of EV isolation methods with downstream applications and their clinical translation. We report outcomes of the first cross-comparison study looking to determine parameters (EV source, starting volume, operator experience, application and implementation parameters such as cost and scalability) governing the selection of popular EV isolation methods across disciplines. Our findings highlighted an increased clinical focus, with 36% of respondents applying EVs in therapeutics and diagnostics. Data indicated preferential selection of ultracentrifugation for therapeutic applications, precipitation reagents in clinical settings and size exclusion chromatography for diagnostic applications utilising biofluids. Method selection was influenced by operator experience, with increased method diversity when EV research was not the respondents primary focus. Application and implementation criteria were indicated to be major influencers in method selection, with UC and SEC chosen for their abilities to process large and small volumes, respectively. Overall, we identified parameters influencing method selection across the breadth of EV science, providing a valuable overview of practical considerations for the effective translation of research outcomes.

Extracellular vesicles from human plasma for biomarkers discovery: Impact of anticoagulants and isolation techniques

Extracellular vesicles (EVs) isolated from plasma are increasingly recognized as promising circulating biomarkers for disease discovery and progression, as well as for therapeutic drug delivery. The scientific community underlined the necessity of standard operative procedures for the isolation and storage of the EVs to ensure robust results. The understanding of the impact of the pre-analytical variables is still limited and some considerations about plasma anticoagulants and isolation methods are necessary. Therefore, we performed a comparison study between EVs isolated by ultracentrifugation and by affinity substrate separation from plasma EDTA and sodium citrate. The EVs were characterized by Nano Tracking Analysis, Western Blot, cytofluorimetric analysis of surface markers, and lipidomic analysis. While anticoagulants did not significantly alter any of the analyzed parameters, the isolation methods influenced EVs size, purity, surface markers expression and lipidomic profile. Compared to ultracentrifugation, affinity substrate separation yielded bigger particles highly enriched in tetraspanins (CD9, CD63, CD81), fatty acids and glycerolipids, with a predominant LDL- and vLDL-like contamination. Herein, we highlighted that the isolation method should be carefully evaluated prior to study design and the need of standardized operative procedures for EVs isolation and application to biomarkers discovery.

Exosomes─Nature's Lipid Nanoparticles, a Rising Star in Drug Delivery and Diagnostics

Exosomes are a subgroup of nanosized extracellular vesicles enclosed by a lipid bilayer membrane and secreted by most eukaryotic cells. They represent a route of intercellular communication and participate in a wide variety of physiological and pathological processes. The biological roles of exosomes rely on their bioactive cargos, including proteins, nucleic acids, and lipids, which are delivered to target cells. Their distinctive properties─innate stability, low immunogenicity, biocompatibility, and good biomembrane penetration capacity─allow them to function as superior natural nanocarriers for efficient drug delivery. Another notably favorable clinical application of exosomes is in diagnostics. They hold various biomolecules from host cells, which are indicative of pathophysiological conditions; therefore, they are considered vital for biomarker discovery in clinical diagnostics. Here, we use data from the CAS Content Collection and provide a landscape overview of the current state and delineate trends in research advancement on exosome applications in therapeutics and diagnostics across time, geography, composition, cargo loading, and development pipelines. We discuss exosome composition and pathway, from their biogenesis and secretion from host cells to recipient cell uptake. We assess methods for exosome isolation and purification, their clinical applications in therapy and diagnostics, their development pipelines, the exploration goals of the companies, the assortment of diseases they aim to treat, development stages of their research, and publication trends. We hope this review will be useful for understanding the current knowledge in the field of medical applications of exosomes, in an effort to further solve the remaining challenges in fulfilling their potential.

Advances of engineered extracellular vesicles-based therapeutics strategy

Extracellular vesicles (EVs) are a heterogeneous population of lipid bilayer membrane-bound vesicles which encapsulate bioactive molecules, such as nucleic acids, proteins, and lipids. They mediate intercellular communication through transporting internally packaged molecules, making them attractive therapeutics carriers. Over the last decades, a significant amount of research has implied the potential of EVs servings as drug delivery vehicles for nuclear acids, proteins, and small molecular drugs. However, several challenges remain unresolved before the clinical application of EV-based therapeutics, including lack of specificity, stability, biodistribution, storage, large-scale manufacturing, and the comprehensive analysis of EV composition. Technical development is essential to overcome these issues and enhance the pre-clinical therapeutic effects. In this review, we summarize the current advancements in EV engineering which demonstrate their therapeutic potential.

Small extracellular vesicles as a multicomponent biomarker platform in urinary tract carcinomas

Extracellular vesicles are a large group of nano-sized vesicles released by all cells. The variety of possible cargo (mRNAs, miRNAs, lncRNAs, proteins, and lipids) and the presence of surface proteins, signaling molecules, and receptor ligands make them a rich source of biomarkers for malignancy diagnosis. One of the groups gathering the most interest in cancer diagnostic applications is small extracellular vesicles (sEVs), with ≤200 nm diameter, mainly composed of exosomes. Many studies were conducted recently, evaluating the diagnostic potential of sEVs in urinary tract carcinomas (UTCs), discovering and clinically evaluating various classes of biomarkers. The amount of research concerning different types of UTCs understandably reflects their incidence. sEV cargos getting the most interest are non-coding RNAs (miRNA and lncRNA). However, implementation of other approaches such as metabolomic and proteomic analysis is also evaluated. The results of many studies indicate that sEVs have an essential role in the cancer process and possess many possible diagnostic and prognostic applications for UTC. The relative ease of obtaining biofluids rich in sEVs (urine and blood) confirms that sEVs are essential for UTC detection in the liquid biopsy approach. A noticeable rise in research quality is observed as more researchers are aware of the research standardization necessity, which is essential for considering the clinical application of their findings.

Exosome Metabolic Patterns on Aptamer-Coupled Polymorphic Carbon for Precise Detection of Early Gastric Cancer

Gastric cancer (GC) presents high mortality worldwide because of delayed diagnosis. Currently, exosome-based liquid biopsy has been applied in diagnosis and monitoring of diseases including cancers, whereas disease detection based on exosomes at the metabolic level is rarely reported. Herein, the specific aptamer-coupled Au-decorated polymorphic carbon (CoMPC@Au-Apt) is constructed for the capture of urinary exosomes from early GC patients and healthy controls (HCs) and the subsequent exosome metabolic pattern profiling without extra elution process. Combining with machine learning algorithm on all exosome metabolic patterns, the early GC patients are excellently discriminated from HCs, with an accuracy of 100% for both the discovery set and blind test. Ulteriorly, three key metabolic features with clear identities are determined as a biomarker panel, obtaining a more than 90% diagnostic accuracy for early GC in the discovery set and validation set. Moreover, the change law of the key metabolic features along with GC development is revealed through making a comparison among HCs and GC at early stage and advanced stage, manifesting their monitoring ability toward GC. This work illustrates the high specificity of exosomes and the great prospective of exosome metabolic analysis in disease diagnosis and monitoring, which will promote exosome-driven precision medicine toward practical clinical application.

Bioinformatics strategies for studying the molecular mechanisms of fungal extracellular vesicles with a focus on infection and immune responses

Fungal extracellular vesicles (EVs) are released during pathogenesis and are found to be an opportunistic infection in most cases. EVs are immunocompetent with their host and have paved the way for new biomedical approaches to drug delivery and the treatment of complex diseases including cancer. With computing and processing advancements, the rise of bioinformatics tools for the evaluation of various parameters involved in fungal EVs has blossomed. In this review, we have complied and explored the bioinformatics tools to analyze the host-pathogen interaction, toxicity, omics and pathogenesis with an array of specific tools that have depicted the ability of EVs as vector/carrier for therapeutic agents and as a potential theme for immunotherapy. We have also discussed the generation and pathways involved in the production, transport, pathogenic action and immunological interactions of EVs in the host system. The incorporation of network pharmacology approaches has been discussed regarding fungal pathogens and their significance in drug discovery. To represent the overview, we have presented and demonstrated an in silico study model to portray the human Cryptococcal interactions.

Extracellular Vesicles and Their Relationship with the Heart-Kidney Axis, Uremia and Peritoneal Dialysis

Cardiorenal syndrome (CRS) is described as primary dysfunction in the heart culminating in renal injury or vice versa. CRS can be classified into five groups, and uremic toxin (UT) accumulation is observed in all types of CRS. Protein-bound uremic toxin (PBUT) accumulation is responsible for permanent damage to the renal tissue, and mainly occurs in CRS types 3 and 4, thus compromising renal function directly leading to a reduction in the glomerular filtration rate (GFR) and/or subsequent proteinuria. With this decrease in GFR, patients may need renal replacement therapy (RRT), such as peritoneal dialysis (PD). PD is a high-quality and home-based dialysis therapy for patients with end-stage renal disease (ESRD) and is based on the semi-permeable characteristics of the peritoneum. These patients are exposed to factors which may cause several modifications on the peritoneal membrane. The presence of UT may harm the peritoneum membrane, which in turn can lead to the formation of extracellular vesicles (EVs). EVs are released by almost all cell types and contain lipids, nucleic acids, metabolites, membrane proteins, and cytosolic components from their cell origin. Our research group previously demonstrated that the EVs can be related to endothelial dysfunction and are formed when UTs are in contact with the endothelial monolayer. In this scenario, this review explores the mechanisms of EV formation in CRS, uremia, the peritoneum, and as potential biomarkers in peritoneal dialysis.

Characterising Alzheimer's disease through integrative NMR- and LC-MS-based metabolomics

Background

Alzheimer's Disease (AD) is a complex and multifactorial disease and novel approaches are needed to illuminate the underlying pathology. Metabolites comprise the end-product of genes, transcripts, and protein regulations and might reflect disease pathogenesis. Blood is a common biofluid used in metabolomics; however, since extracellular vesicles (EVs) hold cell-specific biological material and can cross the blood-brain barrier, their utilization as biological material warrants further investigation. We aimed to investigate blood- and EV-derived metabolites to add insigts to the pathological mechanisms of AD.

Methods

Blood samples were collected from 10 AD and 10 Mild Cognitive Impairment (MCI) patients, and 10 healthy controls. EVs were enriched from plasma using 100,000×g, 1 h, 4 °C with a wash. Metabolites from serum and EVs were measured using liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy. Multivariate and univariate analyses were employed to identify altered metabolites in cognitively impaired individuals.

Results

While no significant EV-derived metabolites were found differentiating patients from healthy individuals, six serum metabolites were found important; valine (p = 0.001, fold change, FC = 0.8), histidine (p = 0.001, FC = 0.9), allopurinol riboside (p = 0.002, FC = 0.2), inosine (p = 0.002, FC = 0.3), 4-pyridoxic acid (p = 0.006, FC = 1.6), and guanosine (p = 0.004, FC = 0.3). Pathway analysis revealed branched-chain amino acids, purine and histidine metabolisms to be downregulated, and vitamin B6 metabolism upregulated in patients compared to controls.

Conclusion

Using a combination of LC-MS and NMR methodologies we identified several altered mechanisms possibly related to AD pathology. EVs require additional optimization prior to their possible utilization as a biological material for AD-related metabolomics studies.