RNA Sequencing Analysis of Salivary Extracellular RNA

Ultrasensitive Detection of MicroRNA in Human Saliva via Rolling Circle Amplification Using a DNA-Decorated Graphene Oxide Sensor

MicroRNAs (miRNAs) are a family of conserved small noncoding RNAs whose expression is associated with many diseases, including cancer. Salivary miRNAs are gaining popularity as noninvasive diagnostic biomarkers for cancer and other systemic disorders, but their use is limited by their low abundance and complicated detection procedure. Herein, we present a novel self-assembly approach based on rolling circle amplification (RCA) and graphene oxide (GO) for the ultrasensitive detection of miRNA21 and miRNA16 (miRNA oral cancer biomarkers in human saliva). First, target miRNA hybridizes with the RCA template. In the presence of DNA polymerase, the RCA reaction is induced and sequences matching the template are generated. Then, a nicking enzyme cuts the long ssDNA product into tiny pieces to obtain the amplified products. The DNA-decorated GO sensor was fabricated by preabsorbing the ssDNA fluorescence-labeled probe on the GO surface, resulting in fluorescence quenching. The DNA-decorated GO sensor could detect the amplified product via the self-assembly of dsDNA, leading to the desorption and recovery of the fluorescence-labeled probe. Under optimal conditions, the proposed system exhibited ultrasensitive detection; the detection limits of miRNA16 and miRNA21 were 8.81 and 3.85 fM, respectively. It showed a wide range of detection between 10 fM and 100 pM for miRNA16 and between 10 fM and 1 nM for miRNA16. It demonstrated high selectivity, distinguishing between 1- and 3-mismatch nucleotides in target miRNA. Overall, our proposed DNA-decorated GO sensor can accurately detect the salivary miRNAs and may potentially be used for the diagnosis and screening of early-stage oral cancer.

Downregulated Circulating Long Non-coding RNA GAS6-AS1 Screens and Predicts Acute Myocardial Infarction

BACKGROUND

Acute myocardial infarction seriously threatens human health and life quality, which needs novel biomarkers to improve its early detection and development prediction. This study aimed to assess the potential of long non-coding RNA GAS6-AS1 in discriminating acute myocardial infarction patients and predicting patients' outcomes.

METHODS

The circulating expression of GAS6-AS1 in 83 acute myocardial infarction patients and 62 healthy individuals was evaluated using polymerase chain reaction. The value of GAS6-AS1 in the distinguishing acute myocardial infarction patients was evaluated with receiver operating characteristic analysis, and its prognosis predictive potential was assessed by Kaplan-Meier and Cox analysis. Additionally, the correlation of GAS6-AS1 with patients' critical features was evaluated by Spearman's correlation analysis.

RESULTS

Significant downregulation of GAS6-AS1 was observed in the plasma of acute myocardial infarction patients relative to healthy individuals. Reduced GAS6-AS1 could discriminate acute myocardial infarction patients from healthy controls and indicate patients' unoptimistic prognosis. Moreover, GAS6-AS1 was found to be negatively cor-related with the levels of creatine kinase, creatine kinasemyocardial bland, lactic dehy-drogenase, hydroxybutyrate dehydrogenase, troponin T, and positively correlated with the ejection fraction of acute myocardial infarction patients.

CONCLUSION

Changes in circulating GAS6-AS1 in acute myocardial infarction served as a potential diagnostic and prognostic biomarker of acute myocardial infarction.

RNA Sequencing Analysis of Saliva exRNA

Next-generation sequencing (NGS) methodologies are rapidly developing. However, RNA Sequencing of saliva is challenging due to low abundance and integrity of extracellular RNA, as well as large amounts of bacterial RNAs that may be encountered in saliva. In addition, the literature about human salivary extracellular RNA is very scarce. Therefore, in our chapter, we present the most appropriate protocols for saliva collection, pre- and post-processing, including bioinformatic analysis of salivary RNA Sequencing data. However, the choice of the proper method for RNA extraction, cDNA library preparation, and computational pipeline can make a significant impact on the final quality of data and their interpretation.

Examining potential confounding factors in gene expression analysis of human saliva and identifying potential housekeeping genes

Isolation of RNA from whole saliva, a non-invasive and easily accessible biofluid that is an attractive alternative to blood for high-throughput biodosimetry of radiological/nuclear victims might be of clinical significance for prediction and diagnosis of disease. In a previous analysis of 12 human samples we identified two challenges to measuring gene expression from total RNA: (1) the fraction of human RNA in whole saliva was low and (2) the bacterial contamination was overwhelming. To overcome these challenges, we performed selective cDNA synthesis for human RNA species only by employing poly(A)+-tail primers followed by qRT-PCR. In the current study, this approach was independently validated on 91 samples from 61 healthy donors. Additionally, we used the ratio of human to bacterial RNA to adjust the input RNA to include equal amounts of human RNA across all samples before cDNA synthesis, which then ensured comparable analysis using the same base human input material. Furthermore, we examined relative levels of ten known housekeeping genes, and assessed inter- and intra-individual differences in 61 salivary RNA isolates, while considering effects of demographical factors (e.g. sex, age), epidemiological factors comprising social habits (e.g. alcohol, cigarette consumption), oral hygiene (e.g. flossing, mouthwash), previous radiological diagnostic procedures (e.g. number of CT-scans) and saliva collection time (circadian periodic). Total human RNA amounts appeared significantly associated with age only (P ≤ 0.02). None of the chosen housekeeping genes showed significant circadian periodicity and either did not associate or were weakly associated with the 24 confounders examined, with one exception, 60% of genes were altered by mouthwash. ATP6, ACTB and B2M represented genes with the highest mean baseline expression (Ct-values ≤ 30) and were detected in all samples. Combining these housekeeping genes for normalization purposes did not decrease inter-individual variance, but increased the robustness. In summary, our work addresses critical confounders and provides important information for the successful examination of gene expression in human whole saliva.

Technical and Methodological Aspects of Cell-Free Nucleic Acids Analyzes

Analyzes of cell-free nucleic acids (cfNAs) have shown huge potential in many biomedical applications, gradually entering several fields of research and everyday clinical care. Many biological properties of cfNAs can be informative to gain deeper insights into the function of the organism, such as their different types (DNA, RNAs) and subtypes (gDNA, mtDNA, bacterial DNA, miRNAs, etc.), forms (naked or vesicle bound NAs), fragmentation profiles, sequence composition, epigenetic modifications, and many others. On the other hand, the workflows of their analyzes comprise many important steps, from sample collection, storage and transportation, through extraction and laboratory analysis, up to bioinformatic analyzes and statistical evaluations, where each of these steps has the potential to affect the outcome and informational value of the performed analyzes. There are, however, no universal or standard protocols on how to exactly proceed when analyzing different cfNAs for different applications, at least according to our best knowledge. We decided therefore to prepare an overview of the available literature and products commercialized for cfNAs processing, in an attempt to summarize the benefits and limitations of the currently available approaches, devices, consumables, and protocols, together with various factors influencing the workflow, its processes, and outcomes.

The Extracellular RNA Communication Consortium: Establishing Foundational Knowledge and Technologies for Extracellular RNA Research

The Extracellular RNA Communication Consortium (ERCC) was launched to accelerate progress in the new field of extracellular RNA (exRNA) biology and to establish whether exRNAs and their carriers, including extracellular vesicles (EVs), can mediate intercellular communication and be utilized for clinical applications. Phase 1 of the ERCC focused on exRNA/EV biogenesis and function, discovery of exRNA biomarkers, development of exRNA/EV-based therapeutics, and construction of a robust set of reference exRNA profiles for a variety of biofluids. Here, we present progress by ERCC investigators in these areas, and we discuss collaborative projects directed at development of robust methods for EV/exRNA isolation and analysis and tools for sharing and computational analysis of exRNA profiling data.

exceRpt: A Comprehensive Analytic Platform for Extracellular RNA Profiling

Small RNA sequencing has been widely adopted to study the diversity of extracellular RNAs (exRNAs) in biofluids; however, the analysis of exRNA samples can be challenging: they are vulnerable to contamination and artifacts from different isolation techniques, present in lower concentrations than cellular RNA, and occasionally of exogenous origin. To address these challenges, we present exceRpt, the exRNA-processing toolkit of the NIH Extracellular RNA Communication Consortium (ERCC). exceRpt is structured as a cascade of filters and quantifications prioritized based on one's confidence in a given set of annotated RNAs. It generates quality control reports and abundance estimates for RNA biotypes. It is also capable of characterizing mappings to exogenous genomes, which, in turn, can be used to generate phylogenetic trees. exceRpt has been used to uniformly process all ∼3,500 exRNA-seq datasets in the public exRNA Atlas and is available from genboree.org and github.gersteinlab.org/exceRpt.

Characterization of Human Salivary Extracellular RNA by Next-generation Sequencing

BACKGROUND

It was recently discovered that abundant and stable extracellular RNA (exRNA) species exist in bodily fluids. Saliva is an emerging biofluid for biomarker development for noninvasive detection and screening of local and systemic diseases. Use of RNA-Sequencing (RNA-Seq) to profile exRNA is rapidly growing; however, no single preparation and analysis protocol can be used for all biofluids. Specifically, RNA-Seq of saliva is particularly challenging owing to high abundance of bacterial contents and low abundance of salivary exRNA. Given the laborious procedures needed for RNA-Seq library construction, sequencing, data storage, and data analysis, saliva-specific and optimized protocols are essential.

METHODS

We compared different RNA isolation methods and library construction kits for long and small RNA sequencing. The role of ribosomal RNA (rRNA) depletion also was evaluated.

RESULTS

The miRNeasy Micro Kit (Qiagen) showed the highest total RNA yield (70.8 ng/mL cell-free saliva) and best small RNA recovery, and the NEBNext library preparation kits resulted in the highest number of detected human genes [5649-6813 at 1 reads per kilobase RNA per million mapped (RPKM)] and small RNAs [482-696 microRNAs (miRNAs) and 190-214 other small RNAs]. The proportion of human RNA-Seq reads was much higher in rRNA-depleted saliva samples (41%) than in samples without rRNA depletion (14%). In addition, the transfer RNA (tRNA)-derived RNA fragments (tRFs), a novel class of small RNAs, were highly abundant in human saliva, specifically tRF-4 (4%) and tRF-5 (15.25%).

CONCLUSIONS

Our results may help in selection of the best adapted methods of RNA isolation and small and long RNA library constructions for salivary exRNA studies.