Benchmarking blood collection tubes and processing intervals for extracellular vesicle performance metrics.

The analysis of extracellular vesicles (EV) in blood samples is under intense investigation and holds the potential to deliver clinically meaningful biomarkers for health and disease. Technical variation must be minimized to confidently assess EV-associated biomarkers, but the impact of pre-analytics on EV characteristics in blood samples remains minimally explored. We present the results from the first large-scale EV Blood Benchmarking (EVBB) study in which we systematically compared 11 blood collection tubes (BCT; six preservation and five non-preservation) and three blood processing intervals (BPI; 1, 8 and 72 h) on defined performance metrics (n = 9). The EVBB study identifies a significant impact of multiple BCT and BPI on a diverse set of metrics reflecting blood sample quality, ex-vivo generation of blood-cell derived EV, EV recovery and EV-associated molecular signatures. The results assist the informed selection of the optimal BCT and BPI for EV analysis. The proposed metrics serve as a framework to guide future research on pre-analytics and further support methodological standardization of EV studies.

Epithelial to mesenchymal transition influences fibroblast phenotype in colorectal cancer by altering miR-200 levels in extracellular vesicles.

Colorectal cancer (CRC) with a mesenchymal gene expression signature has the greatest propensity for distant metastasis and is characterised by the accumulation of cancer-associated fibroblasts in the stroma. We investigated whether the epithelial to mesenchymal transition status of CRC cells influences fibroblast phenotype, with a focus on the transfer of extracellular vesicles (EVs), as a controlled means of cell-cell communication. Epithelial CRC EVs suppressed TGF-ß-driven myofibroblast differentiation, whereas mesenchymal CRC EVs did not. This was driven by miR-200 (miR-200a/b/c, -141), which was enriched in epithelial CRC EVs and transferred to recipient fibroblasts. Ectopic miR-200 expression or ZEB1 knockdown, in fibroblasts, similarly suppressed myofibroblast differentiation. Supporting these findings, there was a strong negative correlation between miR-200 and myofibroblastic markers in a cohort of CRC patients in the TCGA dataset. This was replicated in mice, by co-injecting epithelial or mesenchymal CRC cells with fibroblasts and analysing stromal markers of myofibroblastic phenotype. Fibroblasts from epithelial tumours contained more miR-200 and expressed less ACTA2 and FN1 than those from mesenchymal tumours. As such, these data provide a new mechanism for the development of fibroblast heterogeneity in CRC, through EV-mediated transfer of miRNAs, and provide an explanation as to why CRC tumours with greater metastatic potential are CAF rich.

MISpheroID: a knowledgebase and transparency tool for minimum information in spheroid identity.

Spheroids are three-dimensional cellular models with widespread basic and translational application across academia and industry. However, methodological transparency and guidelines for spheroid research have not yet been established. The MISpheroID Consortium developed a crowdsourcing knowledgebase that assembles the experimental parameters of 3,058 published spheroid-related experiments. Interrogation of this knowledgebase identified heterogeneity in the methodological setup of spheroids. Empirical evaluation and interlaboratory validation of selected variations in spheroid methodology revealed diverse impacts on spheroid metrics. To facilitate interpretation, stimulate transparency and increase awareness, the Consortium defines the MISpheroID string, a minimum set of experimental parameters required to report spheroid research. Thus, MISpheroID combines a valuable resource and a tool for three-dimensional cellular models to mine experimental parameters and to improve reproducibility.

Robust sequential biophysical fractionation of blood plasma to study variations in the biomolecular landscape of systemically circulating extracellular vesicles across clinical conditions.

Separating extracellular vesicles (EV) from blood plasma is challenging and complicates their biological understanding and biomarker development. In this study, we fractionate blood plasma by combining size-exclusion chromatography (SEC) and OptiPrep density gradient centrifugation to study clinical context-dependent and time-dependent variations in the biomolecular landscape of systemically circulating EV. Using pooled blood plasma samples from breast cancer patients, we first demonstrate the technical repeatability of blood plasma fractionation. Using serial blood plasma samples from HIV and ovarian cancer patients (n = 10) we next show that EV carry a clinical context-dependent and/or time-dependent protein and small RNA composition, including miRNA and tRNA. In addition, differential analysis of blood plasma fractions provides a catalogue of putative proteins not associated with systemically circulating EV. In conclusion, the implementation of blood plasma fractionation allows to advance the biological understanding and biomarker development of systemically circulating EV.

Unravelling the proteomic landscape of extracellular vesicles in prostate cancer by density-based fractionation of urine.

Extracellular vesicles (EV) are increasingly being recognized as important vehicles of intercellular communication and promising diagnostic and prognostic biomarkers in cancer. Despite this enormous clinical potential, the plethora of methods to separate EV from biofluids, providing material of highly variable purity, and lacking knowledge regarding methodological repeatability pose a barrier to clinical translation. Urine is considered an ideal proximal fluid for the study of EV in urological cancers due to its direct contact with the urogenital system. We demonstrate that density-based fractionation of urine by bottom-up Optiprep density gradient centrifugation separates EV and soluble proteins with high specificity and repeatability. Mass spectrometry-based proteomic analysis of urinary EV (uEV) in men with benign and malignant prostate disease allowed us to significantly expand the known human uEV proteome with high specificity and identifies a unique biological profile in prostate cancer not uncovered by the analysis of soluble proteins. In addition, profiling the proteome of EV separated from prostate tumour conditioned medium and matched uEV confirms the specificity of the identified uEV proteome for prostate cancer. Finally, a comparative proteomic analysis with uEV from patients with bladder and renal cancer provided additional evidence of the selective enrichment of protein signatures in uEV reflecting their respective cancer tissues of origin. In conclusion, this study identifies hundreds of previously undetected proteins in uEV of prostate cancer patients and provides a powerful toolbox to map uEV content and contaminants ultimately allowing biomarker discovery in urological cancers.

Analyzing bacterial extracellular vesicles in human body fluids by orthogonal biophysical separation and biochemical characterization.

Gram-negative and Gram-positive bacteria release a variety of membrane vesicles through different formation routes. Knowledge of the structure, molecular cargo and function of bacterial extracellular vesicles (BEVs) is primarily obtained from bacteria cultured in laboratory conditions. BEVs in human body fluids have been less thoroughly investigated most probably due to the methodological challenges in separating BEVs from their matrix and host-derived eukaryotic extracellular vesicles (EEVs) such as exosomes and microvesicles. Here, we present a step-by-step procedure to separate and characterize BEVs from human body fluids. BEVs are separated through the orthogonal implementation of ultrafiltration, size-exclusion chromatography (SEC) and density-gradient centrifugation. Size separates BEVs from bacteria, flagella and cell debris in stool; and blood cells, high density lipoproteins (HDLs) and soluble proteins in blood. Density separates BEVs from fibers, protein aggregates and EEVs in stool; and low-density lipoproteins (LDLs), very-low-density lipoproteins (VLDLs), chylomicrons, protein aggregates and EEVs in blood. The procedure is label free, maintains the integrity of BEVs and ensures reproducibility through the use of automated liquid handlers. Post-separation BEVs are characterized using orthogonal biochemical endotoxin and Toll-like receptor-based reporter assays in combination with proteomics, electron microscopy and nanoparticle tracking analysis (NTA) to evaluate BEV quality, abundance, structure and molecular cargo. Separation and characterization of BEVs from body fluids can be done within 72 h, is compatible with EEV analysis and can be readily adopted by researchers experienced in basic molecular biology and extracellular vesicle analysis. We anticipate that this protocol will expand our knowledge on the biological heterogeneity, molecular cargo and function of BEVs in human body fluids and steer the development of laboratory research tools and clinical diagnostic kits.

Performance assessment of total RNA sequencing of human biofluids and extracellular vesicles.

RNA profiling has emerged as a powerful tool to investigate the biomarker potential of human biofluids. However, despite enormous interest in extracellular nucleic acids, RNA sequencing methods to quantify the total RNA content outside cells are rare. Here, we evaluate the performance of the SMARTer Stranded Total RNA-Seq method in human platelet-rich plasma, platelet-free plasma, urine, conditioned medium, and extracellular vesicles (EVs) from these biofluids. We found the method to be accurate, precise, compatible with low-input volumes and able to quantify a few thousand genes. We picked up distinct classes of RNA molecules, including mRNA, lncRNA, circRNA, miscRNA and pseudogenes. Notably, the read distribution and gene content drastically differ among biofluids. In conclusion, we are the first to show that the SMARTer method can be used for unbiased unraveling of the complete transcriptome of a wide range of biofluids and their extracellular vesicles.

The generation and use of recombinant extracellular vesicles as biological reference material.

Recent years have seen an increase of extracellular vesicle (EV) research geared towards biological understanding, diagnostics and therapy. However, EV data interpretation remains challenging owing to complexity of biofluids and technical variation introduced during sample preparation and analysis. To understand and mitigate these limitations, we generated trackable recombinant EV (rEV) as a biological reference material. Employing complementary characterization methods, we demonstrate that rEV are stable and bear physical and biochemical traits characteristic of sample EV. Furthermore, rEV can be quantified using fluorescence-, RNA- and protein-based technologies available in routine laboratories. Spiking rEV in biofluids allows recovery efficiencies of commonly implemented EV separation methods to be identified, intra-method and inter-user variability induced by sample handling to be defined, and to normalize and improve sensitivity of EV enumerations. We anticipate that rEV will aid EV-based sample preparation and analysis, data normalization, method development and instrument calibration in various research and biomedical applications.