Delineating Bovine Milk Derived Microvesicles from Exosomes Using Proteomics.

In the work presented herein, a simple serial-pelleting purification strategy combined with a mass spectrometry-based proteomics analysis was developed as a means of discerning differences in extracellular vesicle (EV) populations found in bovine milk samples. A sequence of ultracentrifugation speeds was used to generate changes in the abundances of EV populations, allowing for the identification of associated proteins. A metric was developed to determine the relative abundances of proteins in large EVs (>200 nm) and small EVs (<200 nm). Of the 476 proteins consistently found in this study, 340 are associated with vesicular components. Of these, 156 were heavily enriched in large EVs, 155 shared between large and small EVs, and 29 heavily enriched in small EVs. Additionally, out of 68 proteins annotated as exosome proteins, 32 were enriched in large EVs, 27 shared between large and small EVs, 5 enriched in small EVs, and 7 were found to be nonvesicular contaminant proteins. The top correlated proteins in the small EV group were predominantly membrane-bound proteins, whereas the top correlated proteins in the large EV group were mostly cytosolic enzymes for molecular processing. This method provides a means of assessing the origins of vesicle components and provides new potential marker proteins within discrete vesicle populations.

Nanoscopic and Functional Characterization of Keratinocyte-Originating Exosomes in the Wound Fluid of Non-Diabetic and Diabetic Chronic Wound Patients.

Exosomes, a class of extracellular vesicles of endocytic origin, play a critical role in paracrine signaling for successful cell-cell crosstalk in vivo. However, limitations in our current understanding of these circulating nanoparticles hinder efficient isolation, characterization, and downstream functional analysis of cell-specific exosomes. In this work, we sought to develop a method to isolate and characterize keratinocyte-originated exosomes (hExoκ) from human chronic wound fluid. Furthermore, we studied the significance of hExoκ in diabetic wounds. LC-MS-MS detection of KRT14 in hExoκ and subsequent validation by Vesiclepedia and Exocarta databases identified surface KRT14 as a reliable marker of hExoκ. dSTORM nanoimaging identified KRT14+ extracellular vesicles (EVκ) in human chronic wound fluid, 23% of which were of exosomal origin. An immunomagnetic two-step separation method using KRT14 and tetraspanin antibodies successfully isolated hExoκ from the heterogeneous pool of EV in chronic wound fluid of 15 non-diabetic and 22 diabetic patients. Isolated hExoκ (Ø75-150nm) were characterized per EV-track guidelines. dSTORM images, analyzed using online CODI followed by independent validation using Nanometrix, revealed hExoκ Ø as 80-145nm. The abundance of hExoκ was low in diabetic wound fluids and negatively correlated with patient HbA1c levels. The hExoκ isolated from diabetic wound fluid showed a low abundance of small bp RNA (<200 bp). Raman spectroscopy underscored differences in surface lipids between non-diabetic and diabetic hExoκ Uptake of hExoκ by monocyte-derived macrophages (MDM) was low for diabetics versus non-diabetics. Unlike hExoκ from non-diabetics, the addition of diabetic hExoκ to MDM polarized with LPS and INFγ resulted in sustained expression of iNOS and pro-inflammatory chemokines known to recruit macrophage (mϕ) This work provides maiden insight into the structure, composition, and function of hExoκ from chronic wound fluid thus providing a foundation for the study of exosomal malfunction under conditions of diabetic complications such as wound chronicity.

Single-chain heteropolymers transport protons selectively and rapidly.

Precise protein sequencing and folding are believed to generate the structure and chemical diversity of natural channels1,2, both of which are essential to synthetically achieve proton transport performance comparable to that seen in natural systems. Geometrically defined channels have been fabricated using peptides, DNAs, carbon nanotubes, sequence-defined polymers and organic frameworks3-13. However, none of these channels rivals the performance observed in their natural counterparts. Here we show that without forming an atomically structured channel, four-monomer-based random heteropolymers (RHPs)14 can mimic membrane proteins and exhibit selective proton transport across lipid bilayers at a rate similar to those of natural proton channels. Statistical control over the monomer distribution in an RHP leads to segmental heterogeneity in hydrophobicity, which facilitates the insertion of single RHPs into the lipid bilayers. It also results in bilayer-spanning segments containing polar monomers that promote the formation of hydrogen-bonded chains15,16 for proton transport. Our study demonstrates the importance of the adaptability that is enabled by statistical similarity among RHP chains and of the modularity provided by the chemical diversity of monomers, to achieve uniform behaviour in heterogeneous systems. Our results also validate statistical randomness as an unexplored approach to realize protein-like behaviour at the single-polymer-chain level in a predictable manner.