Decoding nanoscale cellular messages – advancing extracellular vesicles towards mainstream medicine.

Current medicine, which is predominantly based on small molecule drugs, has only taken us so far in beating disease and tissue degeneration. Extracellular vesicles (EVs), which are highly specialised yet ubiquitous nanoscale messengers secreted by cells have emerged as the new generation of medicine. The problem is, their power cannot be harnessed because they are heterogeneous, and little is known about them. EVs deliver a multitude of biological signals that can direct biological responses and function of neighbouring cells. In this way EVs mediate communication between cells, hence they can be described as a cellular ‘language’, or cellular ‘postal network’. By understanding how EVs are produced and what is inside them – deciphering the messages they contain – we will be able to ‘join cellular conversations’ and potentially develop new therapeutics or diagnostic tools. Despite substantial progress in analytical techniques, characterization of individual vesicles (of sizes below 200 nm) and EV subpopulations has proven to be elusive. This critical limitation curbs the progress in both fundamental science and in clinical translation of EVs, for which nanoscale characterization of the biological signals packaged into EVs and their heterogeneity is essential.

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AFM-IR (nanoIR) decodes cellular ‘Enigma’ code

To characterize individual vesicles we developed methodology that utilizes ultra-high resolution capability of atomic force microscopy nanoinfrared spectroscopy. For the first time we determined differences between individual vesicles and their subpopulations. We showed that using this method we can measure, differences in molecular composition and structure of EVs secreted by different cell types of placenta stem cells, secreted by stem cells cultured under different conditions, as well as differences in EVs obtained using different isolation protocols and from different body fluids and tissues. Notably, we also showed that our method can distinguish protein aggregates from EVs, hence is suitable to validate isolation and purification protocols for EVs.

Because AFM-IR provides information about all components packaged inside EVs, EV membrane and compounds attached to the membrane, it virtually works like nanoscale decoding machine, which deciphers cellular messages that are packaged into individual EV. In this way we will be able in the future to capture the therapeutic potential of EVs to empower our body to heal itself.

Specifically, our study showed that EVs isolated from different types of placenta stem cells, which are exposed to different level of oxidative stress, have major differences in protein, RNA/DNA and lipid contents. We further studies the effect of purification of EVs using size exclusion chromatography, and indeed we demonstrated that the molecular composition, i.e. protein, is substantially different for purified EVs. Our work showed that AFM-IR outperforms existing protocols for interrogating EV composition and structures, and assessing EV purity. Despite this technique does not enable identification of specific miRNAs, it provides a robust data on protein structure, total RNA, DNA and lipid content and their molecular variations. Analyzing these variations at nanoscale may also provide a robust evidence of pathological processes. The fact that only few microliters of samples are required is an added benefit for the use of this technique in diagnosis or prognosis of diseases such as preeclampsia, cancer, multiple sclerosis or dementia. Our method characterizes with unmatched resolution (single vesicle) and is ‘probe free’, avoiding the bias and major limitation of molecular/fluorescent probes. 

Fig. 1. Differences in molecular composition of individual EVs; AFM-IR.

Taken together, there is a potential for AFM-IR to be utilized as highly sensitive, precise and relatively fast measurement of EV structure and composition to determine the most effective EVs purification protocols as well as to gain new knowledge how they are produced to be able to harness their power for diagnostic and therapeutic applications.

Wojciech Chrzanowski

Associate Professor, The University of Sydney

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