Extracellular vesicles (EVs) are increasingly tested as therapeutic vehicles and biomarkers, but still EV subtypes are not fully characterised. To isolate EVs with few co-isolated entities, a combination of methods is needed. However, this is timeconsuming and requires large sample volumes, often not feasible in most clinical studies or in studies where small sample volumes are available. Therefore, we compared EVs rendered by five commonly used methods based on different principles from conditioned cell medium and 250 µl or 3 ml plasma, that is, precipitation (Exo-Quick ULTRA), membrane affinity (exoEasy Maxi Kit), size-exclusion chromatography (qEVoriginal), iodixanol gradient (OptiPrep), and phosphatidylserine affinity (MagCapture). EVs were characterised by electron microscopy, Nanoparticle Tracking Analysis, Bioanalyzer, flow cytometry, and LC-MS/MS. The different methods yielded samples of different morphology, particle size, and proteomic profile. For the conditioned medium, Izon 35 isolated the highest number of EV proteins followed by exoEasy, which also isolated fewer non-EV proteins. For the plasma samples, exoEasy isolated a high number of EV proteins and few non-EV proteins, while Izon 70 isolated the most EV proteins. We conclude that no method is perfect for all studies, rather, different methods are suited depending on sample type and interest in EV subtype, in addition to sample volume and budget.

BackgroundCigarette smoke causes both acute and chronic changes of the immune system. Excluding recent smoking is therefore important in clinical studies with chronic inflammation as primary focus. In this context, it is common to ask the study subjects to refrain from smoking within a certain time frame prior to sampling. The duration of the smoking cessation is typically from midnight the evening before, i.e. 8 hours from sampling. As it has been shown that a proportion of current smokers underestimates or denies smoking, objective assessment of recent smoking status is of great importance. Our aim was to extend the use of exhaled carbon monoxide (CObreath), a well-established method for separating smokers from non-smokers, to assessment of recent smoking status.Methods and FindingsThe time course of CObreath decline was investigated by hourly measurements during one day on non-symptomatic smokers and non-smokers (6+7), as well as by measurements on three separate occasions on non-smokers (n = 29), smokers with normal lung function (n = 38) and smokers with chronic obstructive pulmonary disease (n = 19) participating in a clinical study. We used regression analysis to model the decay, and receiver operator characteristics analysis for evaluation of model performance. The decline was described as a mono-exponential decay (r2 = 0.7) with a half-life of 4.5 hours. CO decline rate depends on initial CO levels, and by necessity a generic cut-off is therefore crude as initial CObreath varies a lot between individuals. However, a cut-off level of 12 ppm could classify recent smokers from smokers having refrained from smoking during the past 8 hours with a specificity of 94% and a sensitivity of 90%.ConclusionsWe hereby describe a method for classifying recent smokers from smokers having refrained from smoking for >8 hours that is easy to implement in a clinical setting.

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Here, we present a method for in-depth human plasma proteome analysis based on high-resolution isoelectric focusing HiRIEF LC-MS/MS, demonstrating high proteome coverage, reproducibility and the potential for liquid biopsy protein profiling. By integrating genomic sequence information to the MS-based plasma proteome analysis, we enable detection of single amino acid variants and for the first time demonstrate transfer of multiple protein variants between mother and fetus across the placenta. We further show that our method has the ability to detect both low abundance tissue-annotated proteins and phosphorylated proteins in plasma, as well as quantitate differences in plasma proteomes between the mother and the newborn as well as changes related to pregnancy.

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Recognition of nucleic acids by endosomal Toll-like receptors (TLR) is essential to combat pathogens, but requires strict control to limit inflammatory responses. The mechanisms governing this tight regulation are unclear. We found that single-stranded oligonucleotides (ssON) inhibit endocytic pathways used by cargo destined for TLR3/4/7 signaling endosomes. Both ssDNA and ssRNA conferred the endocytic inhibition, it was concentration dependent, and required a certain ssON length. The ssON-mediated inhibition modulated signaling downstream of TLRs that localized within the affected endosomal pathway. We further show that injection of ssON dampens dsRNA-mediated inflammatory responses in the skin of non-human primates. These studies reveal a regulatory role for extracellular ssON in the endocytic uptake of TLR ligands and provide a mechanistic explanation of their immunomodulation. The identified ssON-mediated interference of endocytosis (SOMIE) is a regulatory process that temporarily dampens TLR3/4/7 signaling, thereby averting excessive immune responses.

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