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Figure 2.1 Tissue-specific miRNAs in mammals. Human tissue-specific miRNAs that were described as part of the human miRNA tissue atlas study (Ludwig et al. 2016) (light grey circle with dotted/dashed line) were cross-referenced with miRNA atlas studies that examine tissue-specific miRNAs in mouse (medium grey circle with dashed line) and rat (dark grey circle with solid line). Those miRNAs that transverse all three circles are ideal cross-species biomarkers for toxicological studies.

Both prokaryotic and eukaryotic cells release membrane-enclosed microvesicles that package a variety of different cellular-derived components, including nucleic acids, proteins, and lipids. The vesicles range in size (from small 50–150 nm exosomes to large 1,000–10,000 nm tumor cell-derived oncosomes), location of biogenesis, and content. These vesicles play important roles in cellular communications and their content is enriched in small non-coding RNAs (such as miRNAs, lncRNAs, snoRNAs, piRNA, snRNAs, etc.), but also in intact mRNAs and in fragmented tRNAs, mRNAs, lncRNAs, rRNAs, and other nucleic acids (Turchinovich et al. 2019). The roles of these packaged contents are not entirely clear for all RNA species; however, many studies have demonstrated that some of these RNAs can mediate differential responses in recipient cells. Many studies have focused on miRNAs in this paracrine role (reviewed in O’Brien et al. 2020) which therefore may make them serve as putative biomarkers of “active” release due to homeostatic, responsive, and perturbed cellular states. A number of characterization studies have been performed to determine the RNA contents of extracellular microvesicles isolated from human plasma, saliva, and urine, as well as cell lines of different lineages (see reviews in Amorim et al. 2017 and Turchinovich et al. 2019). In one of the first studies that use deep sequencing to profile extracellular vesicle (EV) RNAs, small RNAs were reported to dominate these “shuttle”-derived fractions; however, the distribution was different from that of the parent mouse dendritic cells co-cultured with cognate T cells (Nolte-’t Hoen et al. 2012). Importantly, whereas miRNAs dominated the intracellular small RNA content (~55% of the reads), miRNAs were only the fourth most populated of the EV-derived small RNAs, at around 10% of the total reads. Later studies have both supported and contradicted these findings. For example, Sork et al. (2018) also described different patterns of intracellular small, ribosomal, and other RNAs versus those found in EVs. Of the total reads, small RNAs were a minority; they were noted in the five cell cultures assessed, ranging from ~ 2% to ~ 40% of the reads. However, 58%–83% of the small RNA EV reads were attributed to miRNAs, many of these reflecting those found in the parent cell, with some notable exceptions such as miR-451a. The disagreements between different studies could be due to cell types, methods, and the analyses used. Overall, from a biomarker perspective, the content of these EVs reflects the cellular state and can be specific to a cell type by partially reflecting the transcriptome (Sork et al. 2018; Srinivasan et al. 2019); yet the EVs differ in intracellular RNA content from the source cell (Guduric-Fuchs et al. 2012; Zhang et al. 2010). Therefore packaging these EVs is not merely representative of the RNA cellular milieu; it is rather an active process that may be influenced by cellular responses to stressors.

Many recent studies have focused on determining mechanisms that are involved in EV formation and RNA packaging. The initial formation varies for the different types of EVs. For example, intraluminal vesicles form through the invagination of endosomes known as multivesicular bodies (MVBs), which are then guided by cytoskeletal components and degraded by giant intracellular lysosomes or released into the extracellular space after fusion with the plasma membrane (see reviews in Janas et al. 2015 and O’Brien et al. 2020). Other EVs, such as microvesicles, larger oncosomes, and apoptotic bodies, form directly from the plasma membrane itself. During these processes, RNAs are selectively packaged by the vesiculation machinery through different interactions. These vesicles are enriched with cholesterol, sphingomyelin, glycosphingolipids, and phosphatidylcholine comprised of saturated fatty acids when they are derived from raft-like regions of the MVBs and the plasma membrane. Ceramides, which preferentially locate on the outside rafts of MVBs, are thought to associate with ribonucleoprotein (RNP) complexes and may help selectively package RNA into EVs (Kosaka et al. 2013). Both RNA sequence and RNA secondary structure can mediate this selection (Janas et al. 2006). The sumoylated heterogenous nuclear RNP (specifically, hnRNPA2B1) can recognize the GGAG motif in miRNAs (e.g., miR-198 and -601) and subsequently transfer into exosomes (Villarroya-Beltri et al. 2013) without itself being packaged (Zhou et al. 2020). Sumoylated hnRNPA1 may work in a similar fashion (Li et al. 2004). Also, the synaptotagmin-binding cytoplasmic RNA-interacting protein (SYNCRIP) mediated the sorting of miRNAs bearing the GGCU motif in hepatocyte cell culture (Santangelo et al. 2016). These seed sequences, also termed “EXO-motifs,” are located in the 3ʹ sites of miRNAs (Janas et al. 2006), whereas the sites that mediate mRNA targeting (and primary function) are located in the 5ʹ end. This suggests that the loading of miRNAs into vesicles could occur even if there were very different mRNA targeting functions. It has also been noted in B cells that the post-transcriptional addition of uracil at the 3ʹ end of the miRNA sequence preferentially sorts into exosomes, whereas adenylated miRNAs remain cell-bound (Koppers-Lalic et al. 2014). Other RNA-binding proteins implicated in preferential RNA loading include AGO2 (McKenzie et al. 2016), annexin A2 (Hagiwara et al. 2015), major vault protein (Statello et al. 2018), YBX1 (Kossinova et al. 2017; Shurtleff et al. 2016; Yanshina et al. 2018), lupus La protein (Temoche-Diaz et al. 2019), and Arc1 (Ashley et al. 2018) (see review in O’Brien et al. 2020).