Oxidative stress-induced changes in the transcriptomic profile of extracellular vesicles.

Extracellular vesicles (EVs) have been proposed to play dual roles in cellular homeostasis, functioning both to remove unwanted intracellular molecules, and to enable communication between cells as a means of modulating cellular responses in different physiological and pathological scenarios. EVs contain a broad range of cargoes, including multiple biotypes of RNA, which can vary depending on the cell status, and may function as signalling molecules. In this study, we carried out comparative transcriptomic analysis of Drosophila EVs and cells, demonstrating that the RNA profile of EVs is distinct from cells and shows dose-dependent changes in response to oxidative stress. We identified a high abundance of snoRNAs in EVs, alongside an enrichment of intronic and untranslated regions (UTRs) of mRNAs under stress. We also observed an increase in the relative abundance of either aberrant or modified mRNAs under stress. These findings suggest that EVs may function both for the elimination of specific cellular RNAs, and for the incorporation of RNAs that may hold signalling potential.

Combination of RCA and DNAzyme for Dual-Signal Isothermal Amplification of Exosome RNA.

The RNA contained in exosomes plays a crucial role in information transfer between cells in various life activities. The accurate detection of low-abundance exosome RNA (exRNA) is of great significance for cell function studies and the early diagnosis of diseases. However, their intrinsic properties, such as their short length and high sequence homology, represent great challenges for exRNA detection. In this paper, we developed a dual-signal isothermal amplification method based on rolling circle amplification (RCA) coupled with DNAzyme (RCA-DNAzyme). The sensitive detection of low-abundance exRNA, the specific recognition of their targets and the amplification of the detection signal were studied and explored. By designing padlock probes to specifically bind to the target exRNA, while relying on the ligation reaction to enhance recognition, the precise targeting of exosome RNA was realized. The combination of RCA and DNAzyme could achieve a twice-as-large isothermal amplification of the signal compared to RCA alone. This RCA-DNAzyme assay could sensitively detect a target exRNA at a concentration as low as 527 fM and could effectively distinguish the target from other miRNA sequences. In addition, this technology was successfully proven to be effective for the quantitative detection of miR-21 by spike recovery, providing a new research approach for the accurate detection of low-abundance exRNA and the exploration of unknown exRNA functions.

exRNA-eCLIP intersection analysis reveals a map of extracellular RNA binding proteins and associated RNAs across major human biofluids and carriers.

Although the role of RNA binding proteins (RBPs) in extracellular RNA (exRNA) biology is well established, their exRNA cargo and distribution across biofluids are largely unknown. To address this gap, we extend the exRNA Atlas resource by mapping exRNAs carried by extracellular RBPs (exRBPs). This map was developed through an integrative analysis of ENCODE enhanced crosslinking and immunoprecipitation (eCLIP) data (150 RBPs) and human exRNA profiles (6,930 samples). Computational analysis and experimental validation identified exRBPs in plasma, serum, saliva, urine, cerebrospinal fluid, and cell-culture-conditioned medium. exRBPs carry exRNA transcripts from small non-coding RNA biotypes, including microRNA (miRNA), piRNA, tRNA, small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), Y RNA, and lncRNA, as well as protein-coding mRNA fragments. Computational deconvolution of exRBP RNA cargo reveals associations of exRBPs with extracellular vesicles, lipoproteins, and ribonucleoproteins across human biofluids. Overall, we mapped the distribution of exRBPs across human biofluids, presenting a resource for the community.

Extracellular communication between brain cells through functional transfer of Cre mRNA mediated by extracellular vesicles.

In the central nervous system (CNS), the crosstalk between neural cells is mediated by extracellular mechanisms, including brain-derived extracellular vesicles (bdEVs). To study endogenous communication across the brain and periphery, we explored Cre-mediated DNA recombination to permanently record the functional uptake of bdEVs cargo over time. To elucidate functional cargo transfer within the brain at physiological levels, we promoted the continuous secretion of physiological levels of neural bdEVs containing Cre mRNA from a localized region in the brain by in situ lentiviral transduction of the striatum of Flox-tdTomato Ai9 mice reporter of Cre activity. Our approach efficiently detected in vivo transfer of functional events mediated by physiological levels of endogenous bdEVs throughout the brain. Remarkably, a spatial gradient of persistent tdTomato expression was observed along the whole brain, exhibiting an increment of more than 10-fold over 4 months. Moreover, bdEVs containing Cre mRNA were detected in the bloodstream and extracted from brain tissue to further confirm their functional delivery of Cre mRNA in a novel and highly sensitive Nanoluc reporter system. Overall, we report a sensitive method to track bdEV transfer at physiological levels, which will shed light on the role of bdEVs in neural communication within the brain and beyond.

A Scalable High-Throughput Isoelectric Fractionation Platform for Extracellular Nanocarriers: Comprehensive and Bias-Free Isolation of Ribonucleoproteins from Plasma, Urine, and Saliva.

Extracellular nanocarriers (extracellular vesicles (EVs), lipoproteins, and ribonucleoproteins) of protein and nucleic acids mediate intercellular communication and are clinically adaptable as distinct circulating biomarkers. However, the overlapping size and density of the nanocarriers have so far prevented their efficient physical fractionation, thus impeding independent downstream molecular assays. Here, we report a bias-free high-throughput and high-yield continuous isoelectric fractionation nanocarrier fractionation technique based on their distinct isoelectric points. This nanocarrier fractionation platform is enabled by a robust and tunable linear pH profile provided by water-splitting at a bipolar membrane and stabilized by flow without ampholytes. The linear pH profile that allows easy tuning is a result of rapid equilibration of the water dissociation reaction and stabilization by flow. The platform is automated with a machine learning procedure to allow recalibration for different physiological fluids and nanocarriers. The optimized technique has a resolution of 0.3 ΔpI, sufficient to separate all nanocarriers and even subclasses of nanocarriers. Its performance is then evaluated with several biofluids, including plasma, urine, and saliva samples. Comprehensive, high-purity (plasma: >93%, urine: >95% and saliva: >97%), high-yield (plasma: >78%, urine: >87% and saliva: >96%), and probe-free isolation of ribonucleoproteins in 0.75 mL samples of various biofluids in 30 min is demonstrated, significantly outperforming affinity-based and highly biased gold standards having low yield and day-long protocols. Binary fractionation of EVs and different lipoproteins is also achieved with similar performance.

Machine Learning Analysis of RNA-seq Data for Diagnostic and Prognostic Prediction of Colon Cancer.

Data from omics studies have been used for prediction and classification of various diseases in biomedical and bioinformatics research. In recent years, Machine Learning (ML) algorithms have been used in many different fields related to healthcare systems, especially for disease prediction and classification tasks. Integration of molecular omics data with ML algorithms has offered a great opportunity to evaluate clinical data. RNA sequence (RNA-seq) analysis has been emerged as the gold standard for transcriptomics analysis. Currently, it is being used widely in clinical research. In our present work, RNA-seq data of extracellular vesicles (EV) from healthy and colon cancer patients are analyzed. Our aim is to develop models for prediction and classification of colon cancer stages. Five different canonical ML and Deep Learning (DL) classifiers are used to predict colon cancer of an individual with processed RNA-seq data. The classes of data are formed on the basis of both colon cancer stages and cancer presence (healthy or cancer). The canonical ML classifiers, which are k-Nearest Neighbor (kNN), Logistic Model Tree (LMT), Random Tree (RT), Random Committee (RC), and Random Forest (RF), are tested with both forms of the data. In addition, to compare the performance with canonical ML models, One-Dimensional Convolutional Neural Network (1-D CNN), Long Short-Term Memory (LSTM), and Bidirectional LSTM (BiLSTM) DL models are utilized. Hyper-parameter optimizations of DL models are constructed by using genetic meta-heuristic optimization algorithm (GA). The best accuracy in cancer prediction is obtained with RC, LMT, and RF canonical ML algorithms as 97.33%. However, RT and kNN show 95.33% performance. The best accuracy in cancer stage classification is achieved with RF as 97.33%. This result is followed by LMT, RC, kNN, and RT with 96.33%, 96%, 94.66%, and 94%, respectively. According to the results of the experiments with DL algorithms, the best accuracy in cancer prediction is obtained with 1-D CNN as 97.67%. BiLSTM and LSTM show 94.33% and 93.67% performance, respectively. In classification of the cancer stages, the best accuracy is achieved with BiLSTM as 98%. 1-D CNN and LSTM show 97% and 94.33% performance, respectively. The results reveal that both canonical ML and DL models may outperform each other for different numbers of features.

Extracellular communication between brain cells through functional transfer of Cre mRNA.

In the central nervous system (CNS), the crosstalk between neural cells is mediated by extracellular mechanisms, including brain-derived extracellular vesicles (bdEVs). To study endogenous communication across the brain and periphery, we explored Cre-mediated DNA recombination to permanently record the functional uptake of bdEVs cargo overtime. To elucidate functional cargo transfer within the brain at physiological levels, we promoted the continuous secretion of physiological levels of neural bdEVs containing Cre mRNA from a localized region in the brain by in situ lentiviral transduction of the striatum of Flox-tdTomato Ai9 mice reporter of Cre activity. Our approach efficiently detected in vivo transfer of functional events mediated by physiological levels of endogenous bdEVs throughout the brain. Remarkably, a spatial gradient of persistent tdTomato expression was observed along the whole brain exhibiting an increment of more than 10-fold over 4 months. Moreover, bdEVs containing Cre mRNA were detected in the bloodstream and extracted from brain tissue to further confirm their functional delivery of Cre mRNA in a novel and highly sensitive Nanoluc reporter system. Overall, we report a sensitive method to track bdEVs transfer at physiological levels which will shed light on the role of bdEVs in neural communication within the brain and beyond.

Extracellular RNA as a kind of communication molecule and emerging cancer biomarker.

Extracellular RNA (exRNA) is a special form of RNA in the body. RNA carries information about genes and metabolic regulation in the body, which can reflect the real-time status of cells. This characteristic renders it a biomarker for disease diagnosis, treatment, and prognosis. ExRNA is transported through extracellular vesicles as a signal medium to mediate communication between cells. Tumor cells can release more vesicles than normal cells, thereby promoting tumor development. Depending on its easy detection, the advantages of non-invasive molecular diagnostic technology can be realized. In this systematic review, we present the types, vectors, and biological value of exRNA. We briefly describe new methods of tumor diagnosis and treatment, as well as the difficulties faced in the progress of such research. This review highlights the groundbreaking potential of exRNA as a clinical biomarker.

Performance of Salivary Extracellular RNA Biomarker Panels for Gastric Cancer Differs between Distinct Populations.

Gastric cancer (GC) has the fifth highest incidence among cancers and is the fourth leading cause of cancer-related death GC has predominantly a higher number of cases in certain ethnic groups such as the Korean population. GC found at an early stage is more treatable and has a higher survival rate as compared with GC found at a late stage. However, a diagnosis of GC is often delayed due to the lack of early symptoms and available screening programs in United States. Extracellular RNA (exRNA) is an emerging paradigm; exRNAs have the potential to serve as biomarkers in panels aimed at early detection of cancer. We previously reported the successful use of a panel of salivary exRNA for detecting GC in a high-prevalence Korean cohort, and that genetic changes reflected cancer-associated salivary exRNA changes. The current study is a case-control study of salivary exRNA biomarkers for detecting GC in an ethnically distinct U.S. cohort. A model constructed for the U.S. cohort combined demographic characteristics and salivary miRNA and mRNA biomarkers for GC and yielded an area under the receiver operating characteristic (ROC) curve (AUC) of 0.78. However, the constituents of this model differed from that constructed for the Korean cohort, thus, emphasizing the importance of population-specific biomarker development and validation.

Multiplexed mRNA analysis of brain-derived extracellular vesicles upon experimental stroke in mice reveals increased mRNA content with potential relevance to inflammation and recovery processes.

Extracellular vesicles (EVs) are lipid bilayer-enclosed structures that represent newly discovered means for cell-to-cell communication as well as promising disease biomarkers and therapeutic tools. Apart from proteins, lipids, and metabolites, EVs can deliver genetic information such as mRNA, eliciting a response in the recipient cells. In the present study, we have analyzed the mRNA content of brain-derived EVs (BDEVs) isolated 72 h after experimental stroke in mice and compared them to controls (shams) using nCounter® Nanostring panels, with or without prior RNA isolation. We found that both panels show similar results when comparing upregulated mRNAs in stroke. Notably, the highest upregulated mRNAs were related to processes of stress and immune system responses, but also to anatomical structure development, cell differentiation, and extracellular matrix organization, thus indicating that regenerative mechanisms already take place at this time-point. The five top overrepresented mRNAs in stroke mice were confirmed by RT-qPCR and, interestingly, found to be full-length. We could reveal that the majority of the mRNA cargo in BDEVs was of microglial origin and predominantly present in small BDEVs (≤ 200 nm in diameter). However, the EV population with the highest increase in the total BDEVs pool at 72 h after stroke was of oligodendrocytic origin. Our study shows that nCounter® panels are a good tool to study mRNA content in tissue-derived EVs as they can be carried out even without previous mRNA isolation, and that the mRNA cargo of BDEVs indicates a possible participation in inflammatory but also recovery processes after stroke.

The Role of Epigenetic and Biological Biomarkers in the Diagnosis of Periodontal Disease: A Systematic Review Approach.

The aim of this systemic review was to collate and analyze existing data from published literature sources to identify the current understanding of the role of epigenetic and biological biomarkers in periodontal disease and diagnostics. A comprehensive searching strategy was undertaken in Embase, Medline, The Dentistry and Oral Sciences and CINAHL databases. Grey literature searching strategies were also employed. Articles published in the English language between 2017−2020 were included. A total of 1014 studies were returned of which 15 studies were included. All included articles were cross-sectional, case−control studies. Relevant data were extracted according to various demographic and methodological factors including cohort size, oral biofluid sampled, number of examiners, smoking status and reported outcomes. A measure of the biomarker levels and corresponding significance were documented where possible. This review identified that exRNA has the greatest diagnostic potential, with four biomarkers (SPRR1A, lnc-TET3-2:1, FAM25A, CRCT1) displaying sensitivity of >71% and specificity of 100% in the assessed samples (p < 0.001) for gingivitis. This work also identifies the need for a unified approach to future research to draw meaningful comparison. Further investigations are warranted to definitively validate exRNA data and for the development of an exRNA-specific point-of-care diagnostic test.

Circulating RNAs in prostate cancer patients.

Growing bodies of evidence have demonstrated that the identification of prostate cancer (PCa) biomarkers in the patients' blood and urine may remarkably improve PCa diagnosis and progression monitoring. Among diverse cancer-derived circulating materials, extracellular RNA molecules (exRNAs) represent a compelling component to investigate cancer-related alterations. Once outside the intracellular environment, exRNAs circulate in biofluids either in association with protein complexes or encapsulated inside extracellular vesicles (EVs). Notably, EV-associated RNAs (EV-RNAs) were used for the development of several assays (such as the FDA-approved Progensa Prostate Cancer Antigen 3 (PCA3 test) aiming at improving early PCa detection. EV-RNAs encompass a mixture of species, including small non-coding RNAs (e.g. miRNA and circRNA), lncRNAs and mRNAs. Several methods have been proposed to isolate EVs and relevant RNAs, and to perform RNA-Seq studies to identify potential cancer biomarkers. However, EVs in the circulation of a cancer patient include a multitude of diverse populations that are released by both cancer and normal cells from different tissues, thereby leading to a heterogeneous EV-RNA-associated transcriptional signal. Decrypting the complexity of such a composite signal is nowadays the major challenge faced in the identification of specific tumor-associated RNAs. Multiple deconvolution algorithms have been proposed so far to infer the enrichment of cancer-specific signals from gene expression data. However, novel strategies for EVs sorting and sequencing of RNA associated to single EVs populations will remarkably facilitate the identification of cancer-related molecules. Altogether, the studies summarized here demonstrate the high potential of using EV-RNA biomarkers in PCa and highlight the urgent need of improving technologies and computational approaches to characterize specific EVs populations and their relevant RNA cargo.

Molecular Determinants for RNA Release into Extracellular Vesicles.

Extracellular vesicles (EVs) are important for intercellular communication and act as vehicles for biological material, such as various classes of coding and non-coding RNAs, a few of which were shown to selectively target into vesicles. However, protein factors, mechanisms, and sequence elements contributing to this specificity remain largely elusive. Here, we use a reporter system that results in different types of modified transcripts to decipher the specificity determinants of RNAs released into EVs. First, we found that small RNAs are more efficiently packaged into EVs than large ones, and second, we determined absolute quantities for several endogenous RNA transcripts in EVs (U6 snRNA, U1 snRNA, Y1 RNA, and GAPDH mRNA). We show that RNA polymerase III (pol III) transcripts are more efficiently secreted into EVs compared to pol II-derived transcripts. Surprisingly, our quantitative analysis revealed no RNA accumulation in the vesicles relative to the total cellular levels, based on both overexpressed reporter transcripts and endogenous RNAs. RNA appears to be EV-associated only at low copy numbers, ranging between 0.02 and 1 molecule per EV. This RNA association may reflect internal EV encapsulation or a less tightly bound state at the vesicle surface.

Secret messengers: Extracellular RNA communication in the immune system.

One of the hallmarks of the immune system is a dynamic landscape of cellular communication through the secretion of soluble factors, production of cell-bound ligands, and expression of surface receptors. This communication affects all aspects of immune cell behavior, integrates the responses of immune cells in tissues, and is fundamental to orchestrating effective immunity. Recent pioneering work has shown that the transfer of ribonucleic acids (RNAs) constitutes a novel mode of cellular communication. This communication involves diverse RNA species, with short noncoding RNAs especially enriched in the extracellular space. These RNAs are highly stable and selectively packaged for secretion. Transferred RNAs have functions in target cells that both mirror their cell-intrinsic roles and adopt novel mechanisms of action. These extracellular RNAs both impact the behavior of individual immune cells and participate in local and systemic immune responses. The impacts of RNA communication on immune cells and disease states have important implications for the development of novel clinical biomarkers and innovative therapeutic designs in immune-related disease. In this review, we will discuss the foundation of knowledge that is establishing RNA communication as an active and functional process in the immune system.

Distinct Extracellular RNA Profiles in Different Plasma Components.

Circulating extracellular RNAs (exRNAs) have great potential to serve as biomarkers for a wide range of diagnostic, therapeutic, and prognostic applications. So far, knowledge of the difference among different sources of exRNAs is limited. To address this issue, we performed a sequential physical and biochemical precipitation to collect four fractions (platelets and cell debris, the thrombin-induced precipitates, extracellular vesicles, and supernatant) from each of 10 plasma samples. From total RNAs of the 40 fractions, we prepared ligation-free libraries to profile full spectrum of all RNA species, without size selection and rRNA reduction. Due to complicated RNA composition in these libraries, we utilized a successive stepwise alignment strategy to map the RNA sequences to different RNA categories, including miRNAs, piwi-interacting RNAs, tRNAs, rRNAs, lincRNAs, snoRNAs, snRNAs, other ncRNAs, protein coding RNAs, and circRNAs. Our data showed that each plasma fraction had its own unique distribution of RNA species. Hierarchical cluster analyses using transcript abundance demonstrated similarities in the same plasma fraction and significant differences between different fractions. In addition, we observed various unique transcripts, and novel predicted miRNAs among these plasma fractions. These results demonstrate that the distribution of RNA species and functional RNA transcripts is plasma fraction-dependent. Appropriate plasma preparation and thorough inspection of different plasma fractions are necessary for an exRNA-based biomarker study.

Isolation, Extraction and Deep-Sequencing Analysis of Extracellular RNAs (exRNAs) from Human Plasma.

Extracellular RNAs (exRNAs) are secreted by nearly all cell types and are now known to play multiple physiological roles. Human plasma, a readily available sample for biomedical analysis, was reported to contain various subpopulations of exRNA, some of which are most likely components of plasma ribonucleoproteins (RNPs), while others are encapsulated into extracellular vesicles (EVs) of different size, origin, and composition. Unbiased analysis of exRNA composition can be performed with prefractionation of plasma exRNA followed by library preparation, sequencing, and bioinformatics analysis. In addition to "mature," adaptor ligation-competent RNA species (5'-P/3'-OH), human plasma contains a substantial proportion of degraded RNA fragments, featuring 5'-OH/3'-P or cyclophosphate extremities, which can be made competent for ligation using appropriate treatment. Polyethylene glycol (PEG)-based precipitation kits for EV isolation yield a fraction that is highly contaminated by large RNPs and EV-associated RNAs. Purer EV preparations are obtained by using Proteinase K and RNase A treatment, as well as by size-exclusion chromatography (SEC).

Green pesticide: Tapping to the promising roles of plant secreted small RNAs and responses towards extracellular DNA.

The diverse roles of non-coding RNA and DNA in cross-species communication is yet to be revealed. Once thought to only involve intra-specifically in regulating gene expression, the evidence that these genetic materials can also modulate gene expression between species that belong to different kingdoms is accumulating. Plants send small RNAs to the pathogen or parasite when they are being attacked, targeting essential mRNAs for infection or parasitism of the hosts. However, the same survival mechanism is also deployed by the pathogen or parasite to destabilize plant immune responses. In plants, it is suggested that exposure to extracellular self-DNA impedes growth, while to extracellular non-self-DNA induces the modulation of reactive oxygen species, expression of resistance related genes, epigenetic mechanism, or suppression of disease severity. Exploring the potential of secreted RNA and extracellular DNA as a green pesticide could be a promising alternative if we are to provide food for the future global population without further damaging the environment. Hence, some studies on plant secreted RNA and responses towards extracellular DNA are discussed in this review. The precise mode of action of entry and the following cascade of signaling once the plant cell is exposed to secreted RNA or extracellular DNA could be an interesting topic for future research.

RI-SEC-seq: Comprehensive Profiling of Nonvesicular Extracellular RNAs with Different Stabilities.

Exosomes and other extracellular vesicles (EVs) are considered the main vehicles transporting RNAs in extracellular samples, including human bodily fluids. However, a major proportion of extracellular RNAs (exRNAs) do not copurify with EVs and remain in ultracentrifugation supernatants of cell-conditioned medium or blood serum. We have observed that nonvesicular exRNA profiles are highly biased toward those RNAs with intrinsic resistance to extracellular ribonucleases. These highly resistant exRNAs are interesting from a biomarker point of view, but are not representative of the actual bulk of RNAs released to the extracellular space. In order to understand exRNA dynamics and capture both stable and unstable RNAs, we developed a method based on size-exclusion chromatography (SEC) fractionation of RNase inhibitor (RI)-treated cell-conditioned medium (RI-SEC-seq). This method has allowed us to identify and study extracellular ribosomes and tRNAs, and offers a dynamical view of the extracellular RNAome which can impact biomarker discovery in the near future. Graphical abstract: Overview of the RI-SEC-seq protocol: sequencing of size-exclusion chromatography fractions from nonvesicular extracellular samples treated or not with RNase inhibitors (+/- RI).

Extracellular vesicles and extracellular RNA in aging and age-related disease.

Circulating factors are well known to influence aging and age-related disease. As part of the Aging Science Talks: Science for the Community series, data was presented on two types of circulating functional biomarkers: extracellular RNA (exRNA) and extracellular vesicles (EVs). EVs in the context of type 2 diabetes mellitus was also discussed, as this is an area of interest due to the growing global epidemic of this age-related disease.

Glioma-Derived miRNA-Containing Extracellular Vesicles Induce Angiogenesis by Reprogramming Brain Endothelial Cells.

Glioblastoma (GBM) is characterized by aberrant vascularization and a complex tumor microenvironment. The failure of anti-angiogenic therapies suggests pathways of GBM neovascularization, possibly attributable to glioblastoma stem cells (GSCs) and their interplay with the tumor microenvironment. It has been established that GSC-derived extracellular vesicles (GSC-EVs) and their cargoes are proangiogenic in vitro. To further elucidate EV-mediated mechanisms of neovascularization in vitro, we perform RNA-seq and DNA methylation profiling of human brain endothelial cells exposed to GSC-EVs. To correlate these results to tumors in vivo, we perform histoepigenetic analysis of GBM molecular profiles in the TCGA collection. Remarkably, GSC-EVs and normal vascular growth factors stimulate highly distinct gene regulatory responses that converge on angiogenesis. The response to GSC-EVs shows a footprint of post-transcriptional gene silencing by EV-derived miRNAs. Our results provide insights into targetable angiogenesis pathways in GBM and miRNA candidates for liquid biopsy biomarkers.