Introduction to science behind FastEV

Extracellular vesicles and complexity of plasma as a biomarker source

Extracellular vesicles (EVs) execute multifaceted functions in health and disease. These secretory nano-sized vesicles carry and protect diverse cargo including variable RNAs, DNA, proteins, lipids and metabolites. This cargo is suitable for multiomics analyses. As it may also contain molecular tags revealing the cellular or tissue origins, EVs offer a rich and traceable source for biomarkers. Another benefit is that EVs can be obtained with minimally invasive or non-invasive methods e.g. from plasma, making repeated sampling possible. All factors combined, EVs offer great potential for diagnostics.

Heterogeneity of EVs - EVs and their subclasses

A recently emerged feature of EVs is their great heterogeneity. EVs have been divided into subclasses according to their biogenesis (including e.g. microvesicles, exosomes, apoptotic bodies and exomeres). It is also evident that in addition to biogenetic route, the secretion rate and molecular contents depend on the pathophysiological status of the parent cells, for example disease status, cell cycle stage, senescence and impact of stress conditions e.g. radiation, oxidative stress, immune challenge. The number of publications demonstrating the heterogeneity and changes in EV populations/contents in various conditions and diseases is increasing rapidly and covers all biomolecular classes (mRNA, small RNA, (glyco)proteins, lipids, metabolites).​​

The complexity of EVs futher increases, when we consider the most typical sample type in biomarker discovery, plasma. Plasma contains a mixture of EVs derived from different tissues and cellular origins. The available EV populations in circulation is a result of EV secretion and uptake impacted by a great number of spatio-temporal and physiological factors.​
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Other circulating cell free carriers of important molecular cargo

In addition to heterogeneity of EVs, it is important to acknowledge that plasma contains other components, including, but not limited to:​

  • proteins (complexes, aggregates) ​​
  • cell-free RNA, especially in ribonucleoproteins (e.g. Ago2/miR) and HDL​​
  • cell-free DNA​​
  • lipoproteins ​​
  • mitochondria (free and in EVs)​​
  • possibly: bacteria, their OMVs and viruses​​
  • platelets, if the preanalytics have not been executed well​
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For example, it has been estimated that for every EV, there are probably >1 M lipoproteins alone, and therefore EVs form only a minuscule part of the molecular information carrier cocktail present in cell free plasma. What part of plasma transcriptome these different carriers (or various fractions of plasma) contain is relatively poorly understood. This includes novel or relatively less studied transcripts such as microbial nucleic acids. Complicating the interpretation, EVs may harbor some components typically detected from other carriers, such as mitochondrial or viral transcripts. However, e.g. regarding plasma mRNA transcriptome, EVs may still contain an important and exclusive part.

Interactions on EVs

The complexity of plasma as a source for EVs and biomarkers in plasma increases further with the recent evidence that EVs carry more or less loosely attached cargo on their outer surface, corona. The large surface area enables EVs to act as interaction platforms for various plasma components including albumin, immunoglobulins, complement proteins, coagulation factors, cytokines, chemokines, enzymes, lipoproteins, ribonucleoproteins and DNA. Recent evidence suggests that this extracellular cargo is dynamic and can reflect the pathophysiological state of the individual.

Ideally, biomarker discovery could benefit of this added layer of complexity.
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EV isolation– impact on biomarker discovery

Preanalytical factors, including the chosen method of EV isolation, have a major impact on the results of biomarker discovery. For plasma, anticoagulants, centrifugation steps, containers, temperatures, transport, freezing, storage and thawing procedures/times may affect the available population of biomarkers carriers. For EV isolation, no standard methods exist, thus novel methods are being developed in response to laborious workflows, low throughput or yields, impure or otherwise unsuitable out-puts. For example, traditional ultracentrifugation workflows – closest to gold standard – are laborious, low or medium throughput and prone to operator/equipment induced variation. The result is that outputs from different EV isolations vary in terms of yield, purity, concentration, EV population, molecular cargo and biomarker candidates.​​

For biomarker discovery, high throughput is essential. However, only a few new EV methods address this problem. Instead, most methods focus on improving the purity of the EV output. In the light of possible biologically meaningful interactions between different biomarker cargo carriers, it needs to be asked when is purity essential and when is it unnecessary? ​

Image source: 123rf and University of Helsinki

This consideration concerns the preferred inclusion/exclusion of corona of the circulating EVs, molecular cargo in vs outside of EVs ​and typical cargo of other carriers, such as that of lipoproteins. Theoretically, when applying highly purifying methods, the cargo inside the minuscule EV containers is highlighted. Stripping EVs of surface associated molecules is a relatively common procedure, e.g. applying proteinase K and nuclease treatments before RNA/DNA isolations to destroy “non-EV” nucleic acids. This may strip the EVs of their natural cargo and interactome on surface. On the other end come methods such as precipitation with PEG, that produce outputs containing EV and abundant contaminations. While some of the contaminations may interfere with the downstream analytics, the isolates may retain the EV surface biomarkerome better than the highly stripped samples.

The difficult question is, which cargo is more important and when? Even the newest high throughput EV isolation methods produce only one kind of outputs (per method), with more or less corona, interactome and contaminations, thus they bring one combination of molecular information carriers on the analytical plate.

In summary, it is very difficult to predict where best biomarkers are carried and how they can be caught in each individual case – testing different methods one by one takes a lot of time and resources. The idea with the FastEV biomarker discovery platform is to prowide a shortcut to the best method avoiding the maze of complexity, uncertainty and laborious time-consuming testing.

How FastEV can help to identify the best workflow for detecting biomarkers

FastEV covers a wide range of chemical conditions to fractionate information carriers within plasma. It produces an array of different outputs in terms of EV purity (presence of corona and other biomolecular information carriers), EV yields and molecular contents, such as small RNA subtypes. The outputs are amenable to a wide selection of molecular content analysis, including smallRNAseq, RNAseq, EVArray, Lectin array and Nano flow cytometry.

FastEV can be applied in high-throughput 96-well plate format.

Therefore, FastEV can be applied to quickly test what is the best condition to separate cases from controls or to enrich preknown targets – thereby, it greatly cuts down the cost, time and resources required to find the optimal method for each specific case. The optimal FastEV condition can be used easily for thousands of samples allowing high impact biomarker discovery studies.

See FastEV workflow

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