Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data

Clinician-to-clinician connectedness and access to gastric cancer surgery at National Cancer Institute-designated cancer centers

BACKGROUND

For patients with gastric cancer, the pathway from primary care (PC) clinician to gastroenterologist to cancer specialist (medical oncologist or surgeons) is referral dependent. The impact of clinician connectedness on disparities in quality gastric cancer care, such as at National Cancer Institute-designated cancer centers (NCI-CC), remains underexplored. This study evaluated how clinician connectedness influences access to gastrectomy at NCI-CC.

METHODS

Maryland's All-Payer Claims Database was used to evaluate 667 patients who underwent gastrectomy for cancer from 2013 to 2018. Two separate referral linkages, defined as ≥9 shared patients, were examined: (1) PC clinicians to gastroenterologists at NCI-CC and (2) gastroenterologists to cancer specialists at NCI-CC. Multiple logistic regression models determined associations between referral linkages and odds of undergoing gastrectomy at NCI-CC.

RESULTS

Only 15% of gastrectomies were performed at NCI-CC. Patients of gastroenterologists with referral links to cancer specialists at NCI-CC were more likely to be <65 years, male, White, and privately insured. Every additional referral link between PC clinician and gastroenterologist at NCI-CC and between gastroenterologist and cancer specialist at NCI-CC increased the odds of gastrectomy at NCI-CC by 71% and 26%, respectively. Black patients had half the odds as White patients in receiving gastrectomy at NCI-CC; however, adjusting for covariates including clinician-to-clinician connectedness attenuated this observation.

CONCLUSION

Patients of clinicians with low connectedness and Black patients are less likely to receive gastrectomy at NCI-CC. Enhancing clinician connectedness is necessary to address disparities in cancer care. These results are relevant to policy makers, clinicians, and patient advocates striving for health equity.

A pipeline for the development and analysis of extracellular vesicle-based transcriptomic biomarkers in molecular diagnostics

Extracellular vesicles are shed by every cell type and can be found in any biofluid. They contain different molecules that can be utilized as biomarkers, including several RNA species which they protect from degradation. Here, we present a pipeline for the development and analysis of extracellular vesicle-associated transcriptomic biomarkers that our group has successfully applied multiple times. We highlight the key steps of the pipeline and give particular emphasis to the necessary quality control checkpoints, which are linked to numerous available guidelines that should be considered along the workflow. Our pipeline starts with patient recruitment and continues with blood sampling and processing. The purification and characterization of extracellular vesicles is explained in detail, as well as the isolation and quality control of extracellular vesicle-associated RNA. We point out the possible pitfalls during library preparation and RNA sequencing and present multiple bioinformatic tools to pinpoint biomarker signature candidates from the sequencing data. Finally, considerations and pitfalls during the validation of the biomarker signature using RT-qPCR will be elaborated.

Integrative genetic and genomic networks identify microRNA associated with COPD and ILD

Chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD) are clinically and molecularly heterogeneous diseases. We utilized clustering and integrative network analyses to elucidate roles for microRNAs (miRNAs) and miRNA isoforms (isomiRs) in COPD and ILD pathogenesis. Short RNA sequencing was performed on 351 lung tissue samples of COPD (n = 145), ILD (n = 144) and controls (n = 64). Five distinct subclusters of samples were identified including 1 COPD-predominant cluster and 2 ILD-predominant clusters which associated with different clinical measurements of disease severity. Utilizing 262 samples with gene expression and SNP microarrays, we built disease-specific genetic and expression networks to predict key miRNA regulators of gene expression. Members of miR-449/34 family, known to promote airway differentiation by repressing the Notch pathway, were among the top connected miRNAs in both COPD and ILD networks. Genes associated with miR-449/34 members in the disease networks were enriched among genes that increase in expression with airway differentiation at an air-liquid interface. A highly expressed isomiR containing a novel seed sequence was identified at the miR-34c-5p locus. 47% of the anticorrelated predicted targets for this isomiR were distinct from the canonical seed sequence for miR-34c-5p. Overexpression of the canonical miR-34c-5p and the miR-34c-5p isomiR with an alternative seed sequence down-regulated NOTCH1 and NOTCH4. However, only overexpression of the isomiR down-regulated genes involved in Ras signaling such as CRKL and GRB2. Overall, these findings elucidate molecular heterogeneity inherent across COPD and ILD patients and further suggest roles for miR-34c in regulating disease-associated gene-expression.

Comprehensive circulating microRNA profile as a supersensitive biomarker for early-stage lung cancer screening

PURPOSE

 Less-invasive early diagnosis of lung cancer is essential for improving patient survival rates. The purpose of this study is to demonstrate that serum comprehensive miRNA profile is high sensitive biomarker to early-stage lung cancer in direct comparison to the conventional blood biomarker using next-generation sequencing (NGS) technology combined with automated machine learning (AutoML).

METHODS

We first evaluated the reproducibility of our measurement system using Pearson's correlation coefficients between samples derived from a single pooled RNA sample. To generate comprehensive miRNA profile, we performed NGS analysis of miRNAs in 262 serum samples. Among the discovery set (57 patients with lung cancer and 57 healthy controls), 1123 miRNA-based diagnostic models for lung cancer detection were constructed and screened using AutoML technology. The diagnostic faculty of the best performance model was evaluated by inspecting the validation samples (74 patients with lung cancer and 74 healthy controls).

RESULTS

The Pearson's correlation coefficients between samples derived from the pooled RNA sample ≥ 0.98. In the validation analysis, the best model showed a high AUC score (0.98) and a high sensitivity for early stage lung cancer (85.7%, n = 28). Furthermore, in comparison to carcinoembryonic antigen (CEA), a conventional blood biomarker for adenocarcinoma, the miRNA-based model showed higher sensitivity for early-stage lung adenocarcinoma (CEA, 27.8%, n = 18; miRNA-based model, 77.8%, n = 18).

CONCLUSION

The miRNA-based diagnostic model showed a high sensitivity for lung cancer, including early-stage disease. Our study provides the experimental evidence that serum comprehensive miRNA profile can be a highly sensitive blood biomarker for early-stage lung cancer.

The hitchhikers' guide to RNA sequencing and functional analysis

DNA and RNA sequencing technologies have revolutionized biology and biomedical sciences, sequencing full genomes and transcriptomes at very high speeds and reasonably low costs. RNA sequencing (RNA-Seq) enables transcript identification and quantification, but once sequencing has concluded researchers can be easily overwhelmed with questions such as how to go from raw data to differential expression (DE), pathway analysis and interpretation. Several pipelines and procedures have been developed to this effect. Even though there is no unique way to perform RNA-Seq analysis, it usually follows these steps: 1) raw reads quality check, 2) alignment of reads to a reference genome, 3) aligned reads' summarization according to an annotation file, 4) DE analysis and 5) gene set analysis and/or functional enrichment analysis. Each step requires researchers to make decisions, and the wide variety of options and resulting large volumes of data often lead to interpretation challenges. There also seems to be insufficient guidance on how best to obtain relevant information and derive actionable knowledge from transcription experiments. In this paper, we explain RNA-Seq steps in detail and outline differences and similarities of different popular options, as well as advantages and disadvantages. We also discuss non-coding RNA analysis, multi-omics, meta-transcriptomics and the use of artificial intelligence methods complementing the arsenal of tools available to researchers. Lastly, we perform a complete analysis from raw reads to DE and functional enrichment analysis, visually illustrating how results are not absolute truths and how algorithmic decisions can greatly impact results and interpretation.

Time Course Analysis of Transcriptome in Human Myometrium Depending on Labor Duration and Correlating With Postpartum Blood Loss

The maintenance of coordinated powerful episodic contractions of the uterus is the crucial factor for normal labor. The uterine contractility is gradually enhanced with the progression of labor, which is related to the gene expression of the myometrium. Competing endogenous RNA (ceRNA) can also regulate the gene expression. To better understand the role of ceRNA network in labor, transcriptome sequencing was performed on the myometrium of 17 parturients at different labor durations (0–24 h). From this, expression levels of mRNA, long non-coding RNA (lncRNA), circular RNA (circRNA), and microRNA (miRNA) were correlated with labor duration. Then, targeting relationships between mRNAs, lncRNAs, circRNAs, and miRNAs were predicted, and the ceRNA regulatory network was established. The mRNA expression patterns associated with cervical dilation and postpartum bleeding were further investigated. This analysis identified 932 RNAs positively correlated with labor duration (859 mRNAs, 28 lncRNAs, and 45 circRNAs) and 153 RNAs negatively correlated with labor duration (122 mRNAs, 28 lncRNAs, and 3 miRNAs). These mRNAs were involved in protein metabolism, transport, and cytoskeleton functions. According to the targeting relationship among these ceRNAs and mRNAs, a ceRNA network consisting of 3 miRNAs, 72 mRNAs, 2 circRNAs, and 1 lncRNA was established. In addition, two mRNA expression patterns were established using time-series analysis of mRNA expression in different phases of cervical dilation. A ceRNA network analysis for blood loss was performed; postpartum bleeding was closely related to inflammatory response, angiogenesis, and hemostasis. This study identified human myometrial transcriptome and established the ceRNA regulatory network depending on labor duration and highlighted the dynamic changes that occur at ceRNAs during parturition, which need to be considered more in the future to better understand how changes in gene expression are relevant to functional changes in human myometrium at labor.

Identification of Radiation-Induced miRNA Biomarkers Using the CGL1 Cell Model System

MicroRNAs (miRNAs) have emerged as a potential class of biomolecules for diagnostic biomarker applications. miRNAs are small non-coding RNA molecules, produced and released by cells in response to various stimuli, that demonstrate remarkable stability in a wide range of biological fluids, in extreme pH fluctuations, and after multiple freeze–thaw cycles. Given these advantages, identification of miRNA-based biomarkers for radiation exposures can contribute to the development of reliable biological dosimetry methods, especially for low-dose radiation (LDR) exposures. In this study, an miRNAome next-generation sequencing (NGS) approach was utilized to identify novel radiation-induced miRNA gene changes within the CGL1 human cell line. Here, irradiations of 10, 100, and 1000 mGy were performed and the samples were collected 1, 6, and 24 h post-irradiation. Corroboration of the miRNAome results with RT-qPCR verification confirmed the identification of numerous radiation-induced miRNA expression changes at all doses assessed. Further evaluation of select radiation-induced miRNAs, including miR-1228-3p and miR-758-5p, as well as their downstream mRNA targets, Ube2d2, Ppp2r2d, and Id2, demonstrated significantly dysregulated reciprocal expression patterns. Further evaluation is needed to determine whether the candidate miRNA biomarkers identified in this study can serve as suitable targets for radiation biodosimetry applications.

Differential Expression of MicroRNAs in Dark-Cutting Meat from Beef Carcasses

“Dark-cutting” meat in beef carcasses can result from conditions such as long-term stress and depleted glycogen stores, but some aspects of the physiological mechanisms that cause dark-cutting phenotypes remain poorly understood. Certain responses to stress factors in fully developed tissues are known to be regulated by specific microRNAs. We investigated microRNA expression in Longissimus lumborum biopsies from carcasses derived from a contemporary group of 78 steers from which a high incidence of dark-cutting meat occurred. Our objective was to identify any potential microRNA signatures that reflect the impact of environmental factors and stresses on genetic signaling networks and result in dark-cutting beef (also known as dark, firm, and dry, or DFD) in some animals. MicroRNA expression was quantified by Illumina NextSeq small RNA sequencing. When RNA extracts from DFD muscle biopsy samples were compared with normal, non-DFD (NON) samples, 29 differentially expressed microRNAs were identified in which expression was at least 20% different in the DFD samples (DFD/NON fold ratio ≤0.8 or ≥1.2). When correction for multiple testing was applied, a single microRNA bta-miR-2422 was identified at a false discovery probability (FDR) of 5.4%. If FDR was relaxed to 30%, additional microRNAs were differentially expressed (bta-miR-10174-5p, bta-miR-1260b, bta-miR-144, bta-miR-142-5p, bta-miR-2285at, bta-miR-2285e, bta-miR-3613a). These microRNAs may play a role in regulating aspects of stress responses that ultimately result in dark-cutting beef carcasses.

A MicroRNA Next-Generation-Sequencing Discovery Assay (miND) for Genome-Scale Analysis and Absolute Quantitation of Circulating MicroRNA Biomarkers

The plasma levels of tissue-specific microRNAs can be used as diagnostic, disease severity and prognostic biomarkers for chronic and acute diseases and drug-induced injury. Thereby, the combination of diverse microRNAs into biomarker signatures using multivariate statistics seems especially powerful from the perspective of tissue and condition specific microRNA shedding into the plasma. Although next-generation sequencing (NGS) technology enables one to analyse circulating microRNAs on a genome-scale level, it suffers from potential biases (e.g., adapter ligation bias) and lacks absolute transcript quantitation as well as tailor-made quality controls. In order to develop a robust NGS discovery assay for genome-scale quantitation of circulating microRNAs, we first evaluated the sensitivity, repeatability and ligation bias of four commercially available small RNA library preparation protocols. The protocol from RealSeq Biosciences was selected based on its performance and usability and coupled with a novel panel of exogenous small RNA spike-in controls to enable quality control and absolute quantitation, thus ensuring comparability of data across independent NGS experiments. The established microRNA Next-Generation-Sequencing Discovery Assay (miND) was validated for its relative accuracy, precision, analytical measurement range and sequencing bias and was considered fit-for-purpose for microRNA biomarker discovery. Summarized, all these criteria were met, and thus, our analytical platform is considered fit-for-purpose for microRNA biomarker discovery from biofluids in the setting of any diagnostic, prognostic or patient stratification need. The established miND assay was tested on serum, cerebrospinal fluid (CSF), synovial fluid (SF) and extracellular vesicles (EV) extracted from cell culture medium of primary cells and proved its potential to be used across different sample types.

MiRNA-122 Promotes Ischemia-Reperfusion Injury after Lung Transplantation via the Toll-like Receptor Signaling Pathway

OBJECTIVE

MiRNAs have been recently implicated in the pathogenesis of ischemia-reperfusion (IR) injury. This study aimed to investigate the miRNA expression profiles in the early stages after lung transplantation (LT) and to study the involvement of the Toll-like receptor (TLR) signaling pathway in lung IR injury following LT.

METHODS

We established the left LT model in mice and selected the miRNA-122 as a research target. The mice were injected with a miRNA-122-specific inhibitor, following which pathological changes in the lung tissue were studied using different lung injury indicators. In addition, we performed deep sequencing of transplanted lung tissues to identify differentially expressed (DE) miRNAs and their target genes. These target genes were used to further perform gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis.

RESULTS

A total of 12 DE miRNAs were selected, and 2476 target genes were identified. The GO enrichment analysis predicted 6063 terms, and the KEGG analysis predicted 1554 biological pathways. Compared with the control group, inhibiting the expression of miRNA-122 significantly reduced the lung injury and lung wet/dry ratio (P<0.05). In addition, the activity of myeloperoxidase and the expression levels of tumor necrosis factor-alpha and TLR2/4 were decreased (P<0.05); whereas the expression of interleukin-10 was increased (P<0.05). Furthermore, the inhibition of miRNA-122 suppressed the IR injury-induced activation of the TLR signaling pathway.

CONCLUSION

Our findings showed the differential expression of several miRNAs in the early inflammatory response following LT. Of these, miRNA-122 promoted IR injury following LT, whereas its inhibition prevented IR injury in a TLR-dependent manner.

Circulating exosomal microRNA expression patterns distinguish cardiac sarcoidosis from myocardial ischemia

Objective

Cardiac sarcoidosis is difficult to diagnose, often requiring expensive and inconvenient advanced imaging techniques. Circulating exosomes contain genetic material, such as microRNA (miRNA), that are derived from diseased tissues and may serve as potential disease-specific biomarkers. We thus sought to determine whether circulating exosome-derived miRNA expression patterns would distinguish cardiac sarcoidosis (CS) from acute myocardial infarction (AMI).

Methods

Plasma and serum samples conforming to CS, AMI or disease-free controls were procured from the Biologic Specimen and Data Repository Information Coordinating Center repository and National Jewish Health. Next generation sequencing (NGS) was performed on exosome-derived total RNA (n = 10 for each group), and miRNA expression levels were compared after normalization using housekeeping miRNA. Quality assurance measures excluded poor quality RNA samples. Differentially expressed (DE) miRNA patterns, based upon >2-fold change (p < 0.01), were established in CS compared to controls, and in CS compared to AMI. Relative expression of several DE-miRNA were validated by qRT-PCR.

Results

Despite the advanced age of the stored samples (~5–30 years), the quality of the exosome-derived miRNA was intact in ~88% of samples. Comparing plasma exosomal miRNA in CS versus controls, NGS yielded 18 DE transcripts (12 up-regulated, 6 down-regulated), including miRNA previously implicated in mechanisms of myocardial injury (miR-92, miR-21) and immune responses (miR-618, miR-27a). NGS further yielded 52 DE miRNA in serum exosomes from CS versus AMI: 5 up-regulated in CS; 47 up-regulated in AMI, including transcripts previously detected in AMI patients (miR-1-1, miR-133a, miR-208b, miR-423, miR-499). Five miRNAs with increased DE in CS included two isoforms of miR-624 and miR-144, previously reported as markers of cardiomyopathy.

Conclusions

MiRNA patterns of exosomes derived from CS and AMI patients are distinct, suggesting that circulating exosomal miRNA patterns could serve as disease biomarkers. Further studies are required to establish their specificity relative to other cardiac disorders.

RATEmiRs: the rat atlas of tissue-specific and enriched miRNAs for discerning baseline expression exclusivity of candidate biomarkers

MicroRNAs (miRNAs) are small RNAs that regulate mRNA expression and have been targeted as biomarkers of organ damage and disease. To explore the utility of miRNAs to assess injury to specific tissues, a tissue atlas of miRNA abundance was constructed. The Rat Atlas of Tissue-specific and Enriched miRNAs (RATEmiRs) catalogues miRNA sequencing data from 21 and 23 tissues in male and female Sprague-Dawley rats, respectively. RATEmiRs identifies tissue-enriched (TE), tissue-specific (TS), or organ-specific (OS) miRNAs via comparisons of one or more tissue or organ vs others. We provide a brief overview of RATEmiRs and present how to use it to detect miRNA expression abundance of candidate biomarkers as well as to compare the expression of miRNAs between rat and human. The database is available at https://www.niehs.nih.gov/ratemirs/.

Assessment of methods for serum extracellular vesicle small RNA sequencing to support biomarker development

Extracellular vesicles (EVs) have great potential as a source for clinically relevant biomarkers since they can be readily isolated from biofluids and carry microRNA (miRNA), mRNA, and proteins that can reflect disease status. However, the biological and technical variability of EV content is unknown making comparisons between healthy subjects and patients difficult to interpret. In this study, we sought to establish a laboratory and bioinformatics analysis pipeline to analyse the small RNA content within EVs from patient serum that could serve as biomarkers and to assess the biological and technical variability of EV RNA content in healthy individuals. We sequenced EV small RNA from multiple individuals (biological replicates) and sequenced multiple replicates per individual (technical replicates) using the Illumina Truseq protocol. We observed that the replicates of samples clustered by subject indicating that the biological variability (~95%) was greater than the technical variability (~0.50%). We observed that ~30% of the sequencing reads were miRNAs. We evaluated the technical parameters of sequencing by spiking the EV RNA preparation with a mix of synthetic small RNA and demonstrated a disconnect between input concentration of the spike-in RNA and sequencing read frequencies indicating that bias was introduced during library preparation. To determine whether there are differences between library preparation platforms, we compared the Truseq with the Nextflex protocol that had been designed to reduce bias in library preparation. While both methods were technically robust, the Nextflex protocol reduced the bias and exhibited a linear range across input concentrations of the synthetic spike-ins. Altogether, our results indicate that technical variability is much smaller than biological variability supporting the use of EV small RNAs as potential biomarkers. Our findings also indicate that the choice of library preparation method leads to artificial differences in the datasets generated invalidating the comparability of sequencing data across library preparation platforms.

Integrated analysis highlights multiple long non‑coding RNAs and their potential roles in the progression of human esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a prevalent aggressive malignant tumor with poor prognosis. Investigations into the molecular changes that occur as a result of the disease, as well as identification of novel biomarkers for its diagnosis and prognosis, are urgently required. Long non‑coding RNAs (lncRNAs) have been reported to play a critical role in tumor progression. The present study performed data mining analyses for ESCC via an integrated study of accumulated datasets and identification of the differentially expressed lncRNAs from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The identified intersection of differentially expressed genes (lncRNAs, miRNAs and mRNAs) in ESCC tissues between the GEO and TCGA datasets was investigated. Based on these intersected lncRNAs, the present study constructed a competitive endogenous RNA (ceRNA) network of lncRNAs in ESCC. A total of 81 intersection lncRNAs were identified; 67 of these were included in the ceRNA network. Functional analyses revealed that these 67 key lncRNAs primarily dominated cellular biological processes. The present study then analyzed the associations between the expression levels of these 67 key lncRNAs and the clinicopathological characteristics of the ESCC patients, as well as their survival time using TCGA. The results revealed that 31 of these lncRNAs were associated with tumor grade, tumor‑node‑metastasis (TNM) stage and lymphatic metastasis status (P<0.05). In addition, 15 key lncRNAs were demonstrated to be associated with survival time (P<0.05). Finally, 5 key lncRNAs were selected for validation of their expression levels in 30 patients newly diagnosed with ESCC via reverse transcription‑quantitative PCR (RT‑qPCR). The results suggested that the fold changes in the trends of up‑ and downregulation between GEO, TCGA and RT‑qPCR were consistent. In addition, it was also demonstrated that a select few of these 5 key lncRNAs were significantly associated with TNM stage and lymph node metastasis (P<0.05). The results of the clinically relevant analysis and the aforementioned bioinformatics were similar, hence proving that the bioinformatics analysis used in the present study is credible. Overall, the results from the present study may provide further insight into the functional characteristics of lncRNAs in ESCC through bioinformatics integrative analysis of the GEO and TCGA datasets, and reveal potential diagnostic and prognostic biomarkers for ESCC.

miRBaseMiner, a tool for investigating miRBase content

microRNAs are small non-coding RNA molecules playing a central role in gene regulation. miRBase is the standard reference source for analysis and interpretation of experimental studies. However, the richness and complexity of the annotation is often underappreciated by users. Moreover, even for experienced users, the size of the resource can make it difficult to explore annotation to determine features such as species coverage, the impact of specific characteristics and changes between successive releases. A further consideration is that each new miRBase release contains entries that have had limited review and which may subsequently be removed in a future release to ensure the quality of annotation. To aid the miRBase user, we developed a software tool, miRBaseMiner, for investigating miRBase annotation and generating custom annotation sets. We apply the tool to characterize each release from v9.2 to v22 to examine how annotation has changed across releases and highlight some of the annotation features that users should keep in mind when using for miRBase for data analysis. These include: (1) entries with identical or very similar sequences; (2) entries with multiple annotated genome locations; (3) hairpin precursor entries with extremely low-estimated minimum free energy; (4) entries possessing reverse complementary; (5) entries with 3ʹ poly(A) ends. As each of these factors can impact the identification of dysregulated features and subsequent clinical or biological conclusions, miRBaseMiner is a valuable resource for any user using miRBase as a reference source.

MicroRNA Expression Profiles in External Cervical Resorption

INTRODUCTION

External cervical resorption (ECR) has been challenging for its diagnosis, prevention, and treatment. Its etiology and pathogenesis are largely unknown. This study characterized microRNA (miRNA) expression patterns of human tissues from ECR lesions and identified potential messenger RNA targets and pathways.

METHODS

Granulomatous tissues from ECR (n = 5) and their adjacent nonaffected asymptomatic gingival connective tissues (n = 5) were collected. Similarly, chronic periodontitis (CP) and control samples were collected (n = 3). Quantitative reverse transcription polymerase chain reaction array analysis compared the expression profiles of 88 miRNAs between diseases. Differentially expressed miRNAs were identified using the Student t test. Bioinformatics for messenger RNA (miRWalk) and KEGG pathway analyses were performed to identify predicted target genes and biological/cellular functions and signaling pathways.

RESULTS

Three miRNAs (miR-20a-5p, miR-210-3p, and miR-99a-4p) were significantly down-regulated and 1 miRNA (miR-122-5p) was significantly up-regulated in ECR (P < .05). One up-regulated and 1 down-regulated miRNA reached the significance threshold in CP. A comparison of miRNA expression in ECR and CP identified 3 differentially expressed miRNAs, indicating differences in disease pathobiology. Inflammation-associated Wnt, PI3K-Akt, mitogen-activated protein kinases signaling, and bone formation-associated transforming growth factor beta pathways were identified and predicted to be modulated by differentially expressed miRNAs in both ECR and CP. Biological processes unique to each disease entity were identified, such as T- and B-cell receptor signaling pathways, osteoclast differentiation, and extracellular matrix-receptor interaction for CP. Glycosaminoglycan biosynthesis, mineral absorption, and insulin signaling pathways for ECR were identified.

CONCLUSIONS

This proof-of-principle in vivo study indicated that ECR has both common and unique miRNA expression profiles in comparison with CP, which are predicted to target genes regulating inflammation, immunity, and metabolism of mineralized tissues.

A urinary extracellular vesicle microRNA biomarker discovery pipeline; from automated extracellular vesicle enrichment by acoustic trapping to microRNA sequencing

Development of a robust automated platform for enrichment of extracellular vesicles from low sample volume that matches the needs for next-generation sequencing could remove major hurdles for genomic biomarker discovery. Here, we document a protocol for urinary EVs enrichment by utilizing an automated microfluidic system, termed acoustic trap, followed by next-generation sequencing of microRNAs (miRNAs) for biomarker discovery. Specifically, we compared the sequencing output from two small RNA library preparations, NEXTFlex and CATS, using only 130 pg of input total RNA. The samples prepared using NEXTflex was found to contain larger number of unique miRNAs that was the predominant RNA species whereas rRNA was the dominant RNA species in CATS prepared samples. A strong correlation was found between the miRNA expressions of the acoustic trap technical replicate in the NEXTFlex prepared samples, as well as between the acoustic trap and ultracentrifugation enrichment methods. Together, these results demonstrate a robust and automated strategy for biomarker discovery from small volumes of urine.

High-throughput, Efficient, and Unbiased Capture of Small RNAs from Low-input Samples for Sequencing

MicroRNAs hold great promise as biomarkers of disease. However, there are few efficient and robust methods for measuring microRNAs from low input samples. Here, we develop a high-throughput sequencing protocol that efficiently captures small RNAs while minimizing inherent biases associated with library production. The protocol is based on early barcoding such that all downstream manipulations can be performed on a pool of many samples thereby reducing reagent usage and workload. We show that the optimization of adapter concentrations along with the addition of nucleotide modifications and random nucleotides increases the efficiency of small RNA capture. We further show, using unique molecular identifiers, that stochastic capture of low input RNA rather than PCR amplification influences the biased quantitation of intermediately and lowly expressed microRNAs. Our improved method allows the processing of tens to hundreds of samples simultaneously while retaining high efficiency quantitation of microRNAs in low input samples from tissues or bodily fluids.

Transcriptome Sequencing Approaches to Elucidate Host-Microbe Interactions in Opportunistic Human Fungal Pathogens

Infections caused by opportunistic human fungal pathogens are a source of increasing medical concern, due to their growing incidence, the emergence of novel pathogenic species, and the lack of effective diagnostics tools. Fungal pathogens are phylogenetically diverse, and their virulence mechanisms can differ widely across species. Despite extensive efforts, the molecular bases of virulence in pathogenic fungi and their interactions with the human host remain poorly understood for most species. In this context, next-generation sequencing approaches hold the promise of helping to close this knowledge gap. In particular, high-throughput transcriptome sequencing (RNA-Seq) enables monitoring the transcriptional profile of both host and microbes to elucidate their interactions and discover molecular mechanisms of virulence and host defense. Here, we provide an overview of transcriptome sequencing techniques and approaches, and survey their application in studying the interplay between humans and fungal pathogens. Finally, we discuss novel RNA-Seq approaches in studying host-pathogen interactions and their potential role in advancing the clinical diagnostics of fungal infections.

Transcriptomic response of breast cancer cells to anacardic acid

Anacardic acid (AnAc), a potential dietary agent for preventing and treating breast cancer, inhibited the proliferation of estrogen receptor α (ERα) positive MCF-7 and MDA-MB-231 triple negative breast cancer cells. To characterize potential regulators of AnAc action, MCF-7 and MDA-MB-231 cells were treated for 6 h with purified AnAc 24:1n5 congener followed by next generation transcriptomic sequencing (RNA-seq) and network analysis. We reported that AnAc-differentially regulated miRNA transcriptomes in each cell line and now identify AnAc-regulated changes in mRNA and lncRNA transcript expression. In MCF-7 cells, 80 AnAc-responsive genes were identified, including lncRNA MIR22HG. More AnAc-responsive genes (886) were identified in MDA-MB-231 cells. Only six genes were commonly altered by AnAc in both cell lines: SCD, INSIG1, and TGM2 were decreased and PDK4, GPR176, and ZBT20 were increased. Modeling of AnAc-induced gene changes suggests that AnAc inhibits monounsaturated fatty acid biosynthesis in both cell lines and increases endoplasmic reticulum stress in MDA-MB-231 cells. Since modeling of downregulated genes implicated NFκB in MCF-7, we confirmed that AnAc inhibited TNFα-induced NFκB reporter activity in MCF-7 cells. These data identify new targets and pathways that may account for AnAc’s anti-proliferative and pro-apoptotic activity.

ARMOUR - A Rice miRNA: mRNA Interaction Resource

ARMOUR was developed as A Rice miRNA:mRNA interaction resource. This informative and interactive database includes the experimentally validated expression profiles of miRNAs under different developmental and abiotic stress conditions across seven Indian rice cultivars. This comprehensive database covers 689 known and 1664 predicted novel miRNAs and their expression profiles in more than 38 different tissues or conditions along with their predicted/known target transcripts. The understanding of miRNA:mRNA interactome in regulation of functional cellular machinery is supported by the sequence information of the mature and hairpin structures. ARMOUR provides flexibility to users in querying the database using multiple ways like known gene identifiers, gene ontology identifiers, KEGG identifiers and also allows on the fly fold change analysis and sequence search query with inbuilt BLAST algorithm. ARMOUR database provides a cohesive platform for novel and mature miRNAs and their expression in different experimental conditions and allows searching for their interacting mRNA targets, GO annotation and their involvement in various biological pathways. The ARMOUR database includes a provision for adding more experimental data from users, with an aim to develop it as a platform for sharing and comparing experimental data contributed by research groups working on rice.

Small RNA populations revealed by blocking rRNA fragments in Drosophila melanogaster reproductive tissues

RNA interference (RNAi) is a complex and highly conserved regulatory mechanism mediated via small RNAs (sRNAs). Recent technical advances in high throughput sequencing have enabled an increasingly detailed analysis of sRNA abundances and profiles in specific body parts and tissues. This enables investigations of the localized roles of microRNAs (miRNAs) and small interfering RNAs (siRNAs). However, variation in the proportions of non-coding RNAs in the samples being compared can hinder these analyses. Specific tissues may vary significantly in the proportions of fragments of longer non-coding RNAs (such as ribosomal RNA or transfer RNA) present, potentially reflecting tissue-specific differences in biological functions. For example, in Drosophila, some tissues contain a highly abundant 30nt rRNA fragment (the 2S rRNA) as well as abundant 5’ and 3’ terminal rRNA fragments. These can pose difficulties for the construction of sRNA libraries as they can swamp the sequencing space and obscure sRNA abundances. Here we addressed this problem and present a modified “rRNA blocking” protocol for the construction of high-definition (HD) adapter sRNA libraries, in D. melanogaster reproductive tissues. The results showed that 2S rRNAs targeted by blocking oligos were reduced from >80% to < 0.01% total reads. In addition, the use of multiple rRNA blocking oligos to bind the most abundant rRNA fragments allowed us to reveal the underlying sRNA populations at increased resolution. Side-by-side comparisons of sequencing libraries of blocked and non-blocked samples revealed that rRNA blocking did not change the miRNA populations present, but instead enhanced their abundances. We suggest that this rRNA blocking procedure offers the potential to improve the in-depth analysis of differentially expressed sRNAs within and across different tissues.

Discovery of microRNAs associated with the antiviral immune response of Atlantic cod macrophages

MicroRNAs (miRNAs) are known to play important immunoregulatory roles in teleosts, although miRNAs involved in the antiviral immune response of Atlantic cod (Gadus morhua) were previously uncharacterised. Using deep sequencing and qPCR, the present study was conducted to identify miRNAs responsive to the viral mimic, polyriboinosinic polyribocytidylic acid (pIC) in Atlantic cod macrophages. Macrophage samples isolated from Atlantic cod (n=3) and treated with pIC or phosphate buffered saline (PBS control) for 24 and 72h were used for miRNA profiling. Following deep sequencing, DESeq2 analyses identified four (miR-731-3p, miR-125b-3-3p, miR-150-3p and miR-462-3p) and two (miR-2188-3p and miR-462-3p) significantly differentially expressed miRNAs at 24 and 72h post-stimulation (HPS), respectively. Sequencing-identified miRNAs were subjected to qPCR validation using a larger number of biological replicates (n=6) exposed to pIC or PBS over time (i.e. 12, 24, 48 and 72 HPS). As in sequencing, miR-731-3p, miR-462-3p and miR-2188-3p showed significant up-regulation by pIC. The sequencing results were not qPCR-validated for miR-125b-3-3p and miR-150-3p as up- and down-regulated miRNAs at 24 HPS, respectively; however, qPCR results showed significant up-regulation in response to pIC stimulation at later time points (i.e. 48 and/or 72 HPS). We also used qPCR to assess the expression of other miRNAs that were previously shown as immune responsive in other vertebrates. qPCR results at 48 and/or 72 HPS revealed that miR-128-3-5p, miR-214-1-5p and miR-451-3p were induced by pIC, whereas miR-30b-3p and miR-199-1-3p expression were repressed in response to pIC. The present study identified ten pIC-stimulated miRNAs, suggesting them as important in antiviral immune responses of Atlantic cod macrophages. Some pIC-responsive miRNAs identified in this study were predicted to target putative immune-related genes of Atlantic cod (e.g. miR-30b-3p targeting herc4), although the regulatory functions of these miRNAs need to be validated by future studies.

Alterations in Bronchial Airway miRNA Expression for Lung Cancer Detection

We have previously shown that gene expression alterations in normal-appearing bronchial epithelial cells can serve as a lung cancer detection biomarker in smokers. Given that miRNAs regulate airway gene expression responses to smoking, we evaluated whether miRNA expression is also altered in the bronchial epithelium of smokers with lung cancer. Using epithelial brushings from the mainstem bronchus of patients undergoing bronchoscopy for suspected lung cancer (as part of the AEGIS-1/2 clinical trials), we profiled miRNA expression via small-RNA sequencing from 347 current and former smokers for which gene expression data were also available. Patients were followed for one year postbronchoscopy until a final diagnosis of lung cancer (n = 194) or benign disease (n = 153) was made. Following removal of 6 low-quality samples, we used 138 patients (AEGIS-1) as a discovery set to identify four miRNAs (miR-146a-5p, miR-324-5p, miR-223-3p, and miR-223-5p) that were downregulated in the bronchial airway of lung cancer patients (ANOVA P < 0.002, FDR < 0.2). The expression of these miRNAs is significantly more negatively correlated with the expression of their mRNA targets than with the expression of other nontarget genes (K-S P < 0.05). Furthermore, these mRNA targets are enriched among genes whose expression is elevated in cancer patients (GSEA FDR < 0.001). Finally, we found that the addition of miR-146a-5p to an existing mRNA biomarker for lung cancer significantly improves its performance (AUC) in the 203 samples (AEGIS-1/2) serving an independent test set (DeLong P < 0.05). Our findings suggest that there are miRNAs whose expression is altered in the cytologically normal bronchial epithelium of smokers with lung cancer, and that they may regulate cancer-associated gene expression differences. Cancer Prev Res; 10(11); 651-9. ©2017 AACR.

Integrative microRNA and gene profiling data analysis reveals novel biomarkers and mechanisms for lung cancer

BACKGROUND

Studies on the accuracy of microRNAs (miRNAs) in diagnosing non-small cell lung cancer (NSCLC) have still controversial. Therefore, we conduct to systematically identify miRNAs related to NSCLC, and their target genes expression changes using microarray data sets.

METHODS

We screened out five miRNAs and six genes microarray data sets that contained miRNAs and genes expression in NSCLC from Gene Expression Omnibus.

RESULTS

Our analysis results indicated that fourteen miRNAs were significantly dysregulated in NSCLC. Five of them were up-regulated (miR-9, miR-708, miR-296-3p, miR-892b, miR-140-5P) while nine were down-regulated (miR-584, miR-218, miR-30b, miR-522, miR486-5P, miR-34c-3p, miR-34b, miR-516b, miR-592). The integrating diagnosis sensitivity (SE) and specificity (SP) were 82.6% and 89.9%, respectively. We also found that 4 target genes (p < 0.05, fold change > 2.0) were significant correlation with the 14 discovered miRNAs, and the classifiers we built from one training set predicted the validation set with higher accuracy (SE = 0.987, SP = 0.824).

CONCLUSIONS

Our results demonstrate that integrating miRNAs and target genes are valuable for identifying promising biomarkers, and provided a new insight on underlying mechanism of NSCLC. Further, our well-designed validation studies surely warrant the investigation of the role of target genes related to these 14 miRNAs in the prediction and development of NSCLC.

Screening on the differentially expressed miRNAs in zebrafish (Danio rerio) exposed to trace β-diketone antibiotics and their related functions

The toxicity of β-diketone antibiotics (DKAs) to larval and adult zebrafish (Danio rerio) was investigated by miRNA sequencing and bioinformatics analyses. In control and DKA-exposed groups, 215 differentially expressed miRNAs were screened, and 4076 differential target genes were predicted. Among 51 co-differentially expressed genes, 45 were annotated in KOG functional classification, and 34 in KEGG pathway analysis. The homology analysis of 20 miRNAs with human hsa-miRNAs demonstrated 17 high homologous sequences. The expression levels of 12 miRNAs by qRT-PCR were consistent with those by sRNA-seq. A regulatory network for 4 positive miRNA genes (dre-miR-10, -96, -92 and -184) was plotted, and the high-degree of connectivity between miRNA-gene pairs suggests that these miRNAs play critical roles during zebrafish development. The consistent expression of dre-miR-184 and dre-miR-96 was proved in 120-hpf zebrafish brain, gill, otoliths and lateral line neuromast by qRT-PCR, miRNA-seq, W-ISH and ISH. DKA-exposure led to vacuolation of interstitial cells, reduced number of neurons, glial cell proliferation and formation of glial scar, and the obvious abnormality of cell structure might result from abnormal expression of differentially expressed miRNAs. In general, chronic DKA-exposure resulted in comprehensively toxic effects on larval and adult zebrafish tissues, especially for nervous system.