Rapid Characterization and Quantification of Extracellular Vesicles by Fluorescence-Based Microfluidic Diffusion Sizing

Single-molecule digital sizing of proteins in solution

The physical characterization of proteins in terms of their sizes, interactions, and assembly states is key to understanding their biological function and dysfunction. However, this has remained a difficult task because proteins are often highly polydisperse and present as multicomponent mixtures. Here, we address this challenge by introducing single-molecule microfluidic diffusional sizing (smMDS). This approach measures the hydrodynamic radius of single proteins and protein assemblies in microchannels using single-molecule fluorescence detection. smMDS allows for ultrasensitive sizing of proteins down to femtomolar concentrations and enables affinity profiling of protein interactions at the single-molecule level. We show that smMDS is effective in resolving the assembly states of protein oligomers and in characterizing the size of protein species within complex mixtures, including fibrillar protein aggregates and nanoscale condensate clusters. Overall, smMDS is a highly sensitive method for the analysis of proteins in solution, with wide-ranging applications in drug discovery, diagnostics, and nanobiotechnology.

Multiparametric Orthogonal Characterization of Extracellular Vesicles by Liquid Chromatography Combined with In-Line Light Scattering and Fluorescence Detection

Extracellular vesicles (EVs) are membrane-enclosed biological nanoparticles with potential as diagnostic markers and carriers for therapeutics. Characterization of EVs poses severe challenges due to their complex structure and composition, requiring the combination of orthogonal analytical techniques. Here, we demonstrate how liquid chromatography combined with multi-angle light scattering (MALS) and fluorescence detection in one single apparatus can provide multiparametric characterization of EV samples, including concentration of particles, average diameter of the particles, protein amount to particle number ratio, presence of EV surface markers and lipids, EV shape, and sample purity. The method requires a small amount of sample of approximately 107 EVs, limited handling of the sample and data analysis time in the order of minutes; it is fully automatable and can be applied to both crude and purified samples.

Extracellular vesicle-mediated intercellular and interorgan crosstalk of pancreatic islet in health and diabetes

Diabetes mellitus (DM) is a systemic metabolic disease with high mortality and morbidity. Extracellular vesicles (EVs) have emerged as a novel class of signaling molecules, biomarkers and therapeutic agents. EVs-mediated intercellular and interorgan crosstalk of pancreatic islets plays a crucial role in the regulation of insulin secretion of β-cells and insulin action in peripheral insulin target tissues, maintaining glucose homeostasis under physiological conditions, and it's also involved in pathological changes including autoimmune response, insulin resistance and β-cell failure associated with DM. In addition, EVs may serve as biomarkers and therapeutic agents that respectively reflect the status and improve function and viability of pancreatic islets. In this review, we provide an overview of EVs, discuss EVs-mediated intercellular and interorgan crosstalk of pancreatic islet under physiological and diabetic conditions, and summarize the emerging applications of EVs in the diagnosis and treatment of DM. A better understanding of EVs-mediated intercellular and interorgan communication of pancreatic islets will broaden and enrich our knowledge of physiological homeostasis maintenance as well as the development, diagnosis and treatment of DM.

Viral Vectors, Exosomes, and Vexosomes: Potential Armamentarium for Delivering CRISPR/Cas to Cancer Cells

The underlying cause of cancer is genetic disruption, so gene editing technologies, particularly CRISPR/Cas systems can be used to go against cancer. The field of gene therapy has undergone many transitions over its 40-year history. Despite its many successes, it has also suffered many failures in the battle against malignancies, causing really adverse effects instead of therapeutic outcomes. At the tip of this double-edged sword are viral and non-viral-based vectors, which have profoundly transformed the way scientists and clinicians develop therapeutic platforms. Viruses such as lentivirus, adenovirus, and adeno-associated viruses are the most common viral vectors used for delivering the CRISPR/Cas system into human cells. In addition, among non-viral vectors, exosomes, especially tumor-derived exosomes (TDEs), have proven to be quite effective at delivering this gene editing tool. The combined use of viral vectors and exosomes, called vexosomes, seems to be a solution to overcoming the obstacles of both delivery systems.

High-Yield Production of Extracellular Vesicle Subpopulations with Constant Quality Using Batch-Refeed Cultures

The conventional manufacturing of extracellular vesicles (EVs) is characterized by low yields and batch-to-batch variability, hampering fundamental research on EVs and their practical applications. Perfusion operations have huge potential to address these limitations and increase the productivity and quality of EVs. In this study, perfusion cultures are simulated with batch-refeed systems and their productivity is compared with that achieved using batch cultures. It is shown that a shift from batch to batch-refeed system can increase the space-time yields of a target EV subpopulation characterized by CD81 and CD63 biomarkers by threefold. Moreover, it is demonstrated that the method facilitates the consistent production of the target EVs from cells maintained under constant conditions for 13 days. These results indicate that the use of perfusion cultures is a promising strategy to increase the manufacturing yield of EVs and control the production of specific EV subpopulations with constant quality attributes, thereby improving reproducibility.

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.

High-Yield Separation of Extracellular Vesicles Using Programmable Zwitterionic Coacervates

Programmable coacervates based on zwitterionic polymers are designed as dynamic materials for ion exchange bioseparation. These coacervates are proposed as promising materials for the purification of soft nanoparticles such as liposomes and extracellular vesicles (EVs). It is shown that the stimulus-responsiveness of the coacervates and the recruitment of desired molecules can be independently programmed by polymer design. Moreover, the polymeric coacervates can recruit and release intact liposomes, human EVs, and nanoalgosomes in high yields and separate vesicles from different types of impurities, including proteins and nucleic acids. This approach combines the speed and simplicity of precipitation methods and the programmability of chromatography with the gentleness of aqueous two-phase separation, thereby guaranteeing product stability. This material represents a promising alternative for providing a low-shear, gentle, and selective purification method for EVs.

Improving extracellular vesicles production through a Bayesian optimization-based experimental design

With the growing demand and diversity of biological drugs, developing optimal processes for their accelerated production with minimal resource utilization is a pressing challenge. Typically, such optimization involves multiple target properties, such as production yield, biological activity, and product purity. Therefore, strategic experimental design techniques that can characterize the parameter space while simultaneously arriving at the optimal process satisfying multiple target properties are required. To achieve this, we propose the use of a multi-objective batch Bayesian optimization (MOBBO) algorithm and illustrate its successful application for the production of extracellular vesicles (EVs) from a 3D culture of mesenchymal stem cells (MSCs) considering three objectives, namely to maximize the vesicle-to-protein ratio, maximize the enzymatic activity of the MSC-EV protein CD73, and minimize the amount of calregulin impurities. We show that the optimal combination of the process parameters to address the intended objectives could be achieved with only 32 experiments. For the four parameters considered (i.e., microcarrier concentration, seeding density, centrifugation time, and impeller speed), this number of experiments is comparable to or lower than the classical design of experiments (DoE) and the traditional one-factor-at-a-time (OFAT) approach. We illustrate how the algorithm adaptively samples in the process parameter space, selectively excluding unfavorable regions, thus minimizing the number of experiments required to reach optimal conditions. Finally, we compare the obtained solutions to the literature data and present possible applications of the collected data for other modeling activities such as Quality by Design, process monitoring, control, and scale-up.

Microfluidic Strategies for Extracellular Vesicle Isolation: Towards Clinical Applications

Extracellular vesicles (EVs) are double-layered lipid membrane vesicles released by cells. Currently, EVs are attracting a lot of attention in the biological and medical fields due to their role as natural carriers of proteins, lipids, and nucleic acids. Thus, they can transport useful genomic information from their parental cell through body fluids, promoting cell-to-cell communication even between different organs. Due to their functionality as cargo carriers and their protein expression, they can play an important role as possible diagnostic and prognostic biomarkers in various types of diseases, e.g., cancers, neurodegenerative, and autoimmune diseases. Today, given the invaluable importance of EVs, there are some pivotal challenges to overcome in terms of their isolation. Conventional methods have some limitations: they are influenced by the starting sample, might present low throughput and low purity, and sometimes a lack of reproducibility, being operator dependent. During the past few years, several microfluidic approaches have been proposed to address these issues. In this review, we summarize the most important microfluidic-based devices for EV isolation, highlighting their advantages and disadvantages compared to existing technology, as well as the current state of the art from the perspective of the use of these devices in clinical applications.

FULL-MDS: Fluorescent Universal Lipid Labeling for Microfluidic Diffusional Sizing

Microfluidic diffusional sizing (MDS) is a recent and powerful method for determining the hydrodynamic sizes and interactions of biomolecules and nanoparticles. A major benefit of MDS is that it can report the size of a fluorescently labeled target even in mixtures with complex, unpurified samples. However, a limitation of MDS is that the target itself has to be purified and covalently labeled with a fluorescent dye. Such covalent labeling is not suitable for crude extracts such as native nanodiscs directly obtained from cellular membranes. In this study, we introduce fluorescent universal lipid labeling for MDS (FULL-MDS) as a sparse, noncovalent labeling method for determining particle size. We first demonstrate that the inexpensive and well-characterized fluorophore, Nile blue, spontaneously partitions into lipid nanoparticles without disrupting their structure. We then highlight the key advantage of FULL-MDS by showing that it yields robust size information on lipid nanoparticles in crude cell extracts that are not amenable to other sizing methods. Furthermore, even for synthetic nanodiscs, FULL-MDS is faster, cheaper, and simpler than existing labeling schemes.

Isolation of Extracellular Vesicles From Microalgae: A Renewable and Scalable Bioprocess

Extracellular vesicles (EVs) play a crucial role as potent signal transducers among cells, with the potential to operate cross-species and cross-kingdom communication. Nanoalgosomes are a subtype of EVs recently identified and isolated from microalgae. Microalgae represent a natural bioresource with the capacity to produce several secondary metabolites with a broad range of biological activities and commercial applications. The present study highlights the upstream and downstream processes required for the scalable production of nanoalgosomes from cultures of the marine microalgae Tetraselmis chuii. Different technical parameters, protocols, and conditions were assessed to improve EVs isolation by tangential flow filtration (TFF), aiming to enhance sample purity and yield. The optimization of the overall bioprocess was enhanced by quality control checks operated through robust biophysical and biochemical characterizations. Further, we showed the possibility of recycling by TFF microalgae cells post-EVs isolation for multiple EV production cycles. The present results highlight the potential of nanoalgosome production as a scalable, cost-effective bioprocess suitable for diverse scientific and industrial exploitations.