Quantification Of microRNAs Research Articles

Comprehensive analysis of glycoprotein profiles and their association with cardiovascular disease-related microRNAs in rheumatoid arthritis, metabolic disorders, and controls

Rheumatoid arthritis (RA) is a chronic autoimmune disease that causes joint pain and disability. The connection between RA and cardiovascular (CV) disease is still being studied. This research aims to explore the relationship between CV-related microRNAs, inflammation, and glycosylated proteins to understand RA’s inflammatory pathophysiology concerning CV disease. The study included 219 RA patients, 82 with metabolic disorders, and 64 controls. Clinical evaluations and blood samples were collected. Quantification of microRNAs (Let7a, 24, 96, 103, 125a, 125b, 132, 146, 191, 223, 425, 451) and measurement of glycoproteins (GlycA, GlycB, GlycF) using proton nuclear magnetic resonance (1 H-NMR) were performed. Multivariate linear models were applied. RA patients showed higher glycoprotein levels than those with metabolic disorders and controls. Significant associations between miRNAs 24, 451, Let7a and glycoprotein levels were found in RA patients, particularly in women. Glycoprotein levels were positively correlated with inflammatory markers, highlighting their role in indicating RA severity. This study highlights elevated glycoprotein levels in RA patients, indicating a severe inflammatory pattern. Moreover, glycoproteins were highly associated with CV-disease-related miRNAs, indicating that glycoproteins are involved in both inflammation and CV disease. Finally, the inflammatory profile of glycoproteins was validated as they were highly associated with inflammatory markers of RA.

MicroRNA Quantification as an Accurate and Cost-Effective Method to Diagnose Acral Melanoma

MicroRNA Quantification as an Accurate and Cost-Effective Method to Diagnose Acral Melanoma

EPEN-06. IDENTIFICATION OF CSF MIRNA BIOMARKERS FOR THE EARLY DETECTION OF MEASURABLE RESIDUAL DISEASE IN PAEDIATRIC EPENDYMOMA: A BIOMECA STUDY

Abstract BACKGROUND Ependymoma (EPN) is the second most common malignant paediatric brain tumour. 50% of children relapse. Detection of Measurable Residual Disease (MRD) via MRI is difficult and lacks sensitivity for very early recurrence, necessitating an urgent need for identifying new, robust biomarkers for the early diagnosis, prognosis, and clinical management of disease progression in EPN. We hypothesise that microRNA (miRNA) quantification in the cerebrospinal fluid (CSF) will have clinical utility in the early detection of MRD in these patients. PATIENTS/METHODS A discovery cohort of EPN CSF samples (n=12) from patients enrolled on the SIOP Ependymoma II clinical trial (trials.gov identifier: NCT02265770) and control leukaemia CSF samples (n=8) underwent RNA-sequencing (QIAGEN) after total RNA extraction using QIAGEN miRNeasy Serum/Plasma kit. The EPN cohort consisted of infratentorial (IT; n=9), supratentorial (ST; n=1) and spinal (SP; n=2) cases taken prior to, or at, resection (primary/relapse). RESULTS Raw sequencing data entered a quality-control pipeline (Tally/Cutadapt), followed by alignment to miRBase-v22 (https://mirbase.org/) using Chimira (PMID:26093149). Two outlying (infratentorial) EPN samples were removed, leaving a 10 (IT+ST+SP) versus 8 comparison. Extracted raw counts were normalised across samples using DESeq2 (PMID:25516281) and 87 differentially-expressed miRNAs identified (adj-p<0.05). EPN samples completely segregated from controls on clustering/heatmap analysis. From these 87 miRNAs, a core set of 53 were overlapping in comparisons removing spinal (IT+ST remaining) and supratentorial (IT alone) samples. These miRNAs underwent combined ranking by adjusted-p and abundance (normalised count) values, and top-ranking candidates taken forward for confirmation using highly-sensitive Taqman PCR, prior to validation in additional samples. CONCLUSION Circulating miRNA quantification offers promise for EPN diagnosis and MRD detection. Further CSF study in larger patient cohorts, and serum/plasma analysis, are now warranted.

Quantification of multiple microRNAs by microchip electrophoresis assisted by strand displacement amplification

MicroRNAs (miRNAs) are increasingly recognized as potential biomarkers for the early diagnosis of cancer. However, the concurrent detection of multiple miRNAs in biological samples presents a significant challenge due to their high homogeneity and low abundance. This study introduced a novel approach combining strand displacement amplification (SDA) with microchip electrophoresis (MCE) for the simultaneous quantitation of trace levels of three miRNAs associated with cancer: miRNA-21, miRNA-145, and miRNA-221. Specifically designed probes were utilized to selectively capture the target miRNAs, thereby initiating the SDA process in a single solution without cross-interference. Under optimized conditions, the SDA-MCE method achieved the limit of detection (LOD) as low as 0.02 fM (S/N = 3) and the limit of quantitation (LOQ) as low as 0.1 fM across a broad linear range spanning from 0.1 fM to 1 pM. The SDA reaction was completed in approximately 1.5 h, and all target products were separated within 135 s through MCE. Application of this method for the simultaneous detection of these three miRNAs in human lung cancer cell samples yielded satisfactory results. Featuring high sensitivity, rapid analysis, minimal reagent consumption, and straightforward operation, the proposed MCE-SDA strategy holds considerable promise for multi-miRNAs detection applications.

Quantification of MicroRNA in a Single Living Cell via Ionic Current Rectification-Based Nanopore for Triple Negative Breast Cancer Diagnosis.

Accurate analysis of microRNAs (miRNAs) at the single-cell level is extremely important for deeply understanding their multiple and intricate biological functions. Despite some advancements in analyzing single-cell miRNAs, challenges such as intracellular interferences and insufficient detection limits still remain. In this work, an ultrasensitive nanopore sensor for quantitative single-cell miRNA-155 detection is constructed based on ionic current rectification (ICR) coupled with enzyme-free catalytic hairpin assembly (CHA). Benefiting from the enzyme-free CHA amplification strategy, the detection limit of the nanopore sensor for miRNA-155 reaches 10 fM and the nanopore sensor is more adaptable to complex intracellular environments. With the nanopore sensor, the concentration of miRNA-155 in living single cells is quantified to realize the early diagnosis of triple-negative breast cancer (TNBC). Furthermore, the nanopore sensor can be applied in screening anticancer drugs by tracking the expression level of miRNA-155. This work provides an adaptive and universal method for quantitatively analyzing intracellular miRNAs, which will greatly improve our understanding of cell heterogeneity and provide a more reliable scientific basis for exploring major diseases at the single-cell level.

A Sensitive Technique Unravels the Kinetics of Activation and Trans-Cleavage of CRISPR-Cas Systems.

Activation of the CRISPR-Cas13a system requires the formation of a crRNA-Cas13a ribonucleoprotein (RNP) complex and the binding of an RNA activator to the RNP. These two binding processes play a crucial role in the performance of the CRISPR-Cas13a system. However, the binding kinetics remain poorly understood, and a main challenge is the lack of a sensitive method for real-time measurements of the dynamically formed active CRISPR-Cas13a enzyme. We describe here a new method to study the binding kinetics and report the rate constants (kon and koff) and dissociation constant (Kd) for the binding between Cas13a and its activator. The method is able to unravel and quantify the kinetics of binding and cleavage separately, on the basis of measuring the real-time trans-cleavage rates of the CRISPR-Cas system and obtaining the real-time concentrations of the active CRISPR-Cas ternary complex. We further discovered that once activated, the Cas13a system operates at a wide range of temperatures (7-37 °C) with fast trans-cleavage kinetics. The new method and findings are important for diverse applications of the Cas13a system, such as the demonstrated quantification of microRNA at ambient temperatures (e.g., 25 °C).

A Sensitive Technique Unravels the Kinetics of Activation and Trans‐Cleavage of CRISPR‐Cas Systems

AbstractActivation of the CRISPR‐Cas13a system requires the formation of a crRNA‐Cas13a ribonucleoprotein (RNP) complex and the binding of an RNA activator to the RNP. These two binding processes play a crucial role in the performance of the CRISPR‐Cas13a system. However, the binding kinetics remain poorly understood, and a main challenge is the lack of a sensitive method for real‐time measurements of the dynamically formed active CRISPR‐Cas13a enzyme. We describe here a new method to study the binding kinetics and report the rate constants (kon and koff) and dissociation constant (Kd) for the binding between Cas13a and its activator. The method is able to unravel and quantify the kinetics of binding and cleavage separately, on the basis of measuring the real‐time trans‐cleavage rates of the CRISPR‐Cas system and obtaining the real‐time concentrations of the active CRISPR‐Cas ternary complex. We further discovered that once activated, the Cas13a system operates at a wide range of temperatures (7–37 °C) with fast trans‐cleavage kinetics. The new method and findings are important for diverse applications of the Cas13a system, such as the demonstrated quantification of microRNA at ambient temperatures (e.g., 25 °C).

Dark-field imaging and fluorescence dual-mode detection of microRNA-21 in living cells by core-satellite plasmonic nanoprobes

The in situ precise quantification and simultaneous imaging of low abundance microRNAs (miRNAs) within living cells is critical for cancer diagnosis, yet it remains a significant challenge. Leveraging the excellent sensitivity and spatiotemporal resolution of dark-field microscopy (DFM) and fluorescence imaging, we have successfully devised a novel detection approach using dual-signal reporter probes (DSRPs). These probes allow for highly sensitive detection of miRNA-21 in living cells via toehold-mediated strand displacement cascades. The DSRPs were constructed by Au nanoparticles and Ag nanoclusters core-satellite nanostructures. After the recognition of miRNA-21, the strand displacement cascades were triggered, inducing the disassembly of the Au/Ag core-satellite nanostructure with apparent scattering intensity decrease and peak wavelength shifts. Additionally, the fluorescence of Ag clusters could be recovered and further enhanced when in close proximity to specific guanine-rich strands. The dual-signal response capability enables the accurate detection of miRNA-21 from 1 fM to 1 nM, with a limit of detection reached 0.75 fM. DFM and fluorescent imaging of living cells efficiently confirms the applicable detection of miRNA-21 in complex detection media. The biosensor based on DSRPs represents a promising nanoplatform for visual monitoring and imaging of biomolecules in living cells, even at the single particle level.

A target-triggered mimic nucleic acid enzyme enables versatile and sequence-independent biosensing

Simultaneous quantification of multiple microRNAs (miRNAs) is very important because lots of pathologies are associated with abnormal expressions of several miRNAs. In this work, we proposed an enzyme-assisted cleavage of nucleic acids signal amplification (TMNAE enzyme sensing) based method enable simple, highly sensitive and selective multiple miRNAs detection. Two unmodified probes and analyte were assembled into a Y-shaped structure that contains a nicking endonuclease recognition site in the complementary region of the unmodified probe and two side arms complementary to reporter probe. Thus, it enables the loading of a Nicking endonuclease (NEase) on the complementary region of the unmodified probe, localization to a specific locus through hybridization of the side arms with reporter probe, and cleavage thereof. NEase is employed to recycle the process of Y-shaped structure assisted digestion of reporter probe, thus, resulting in a significant fluorescence signal amplification through which one analyte molecule cleaves thousands of reporter probe molecules. We demonstrate the efficiency of this TMNAE enzyme sensing strategy for rapid direct quantification of multiple sequence specific miRNAs in homogeneous solution with the detection limit in the femtomolar range, nearly 4 orders of magnitude lower than that of conventional hybridization assay methods. This assay also has the ability to discriminate the target from other miRNAs or even single-base mismatched sequences. Moreover, the TMNAE enzyme sensing strategy can be used to detect other molecules apart from nucleic acids. The detection of thrombin in biological samples showed a LOD of as low as 1 nM. Overall, our proposed TMNAE enzyme sensing strategy provides a versatile, reliable, simple, highly sensitive, and selective detection method and shows promising application in molecular disease diagnosis and biomedicine.

SA-ODG platform: a semi-automated and PCR-free method to analyse microRNAs in solid tissues.

Over the past two decades, numerous techniques have been developed for analysing microRNAs in body fluids and tissues. However, these techniques still face technical challenges, particularly when compared to well-established techniques for proteins and metabolites. Recently, the ODG platform was introduced, which is an innovative technology that allows for the direct detection and quantification of microRNAs in liquid biopsies without requiring extraction or amplification. This study presents the implementation of the ODG platform within a semi-automated protocol to create the "SA-ODG" platform, enhancing the efficiency and precision of microRNA testing while reducing hands-on time required by laboratory staff. For the first time, the SA-ODG platform has been used to directly quantify microRNAs in solid tissues. The results demonstrate precise analysis of miR-122-5p in mouse liver tissues using SA-ODG. These developments represent a crucial step forward in advancing the field of extraction and amplification-free microRNA detection and quantification.

Portable fluorescent lateral flow assay for ultrasensitive point-of-care analysis of acute myocardial infarction related microRNA

Point-of-care quantitative analysis of tracing microRNA disease-biomarkers remains a great challenge in the clinical diagnosis. In this paper, we developed a portable fluorescent lateral flow assay for ultrasensitive quantified detection of acute myocardial infarction related microRNAs in bio-samples. SiO2@DQD (bilayer quantum dots assembly with SiO2 core) based fluorescent lateral flow strip was fabricated as the analysis tool. In order to quantify the tracing microRNA in biosamples, a catalytic hairpin assembly and CRISPR/Cas12a cascade amplification method was performed and combined with the fabricated SiO2@DQD lateral flow strip. Thus, our platform gathered double advantages of portability and ultrasensitive quantification. Based on our strips, target myocardial biomarker microRNA-133a can be detected with a detection limit of 0.32 fM, which was almost 1000-fold sensitive compared with previous reported microRNAs-lateral flow strips. Significantly, this portable fluorescent strip can directly detect microRNAs in serum without any pretreatment and PCR amplification steps. When spiked in serum samples, a recovery of 99.65 %-102.38 % can be obtained. Therefore, our method offers a potential tool for ultrasensitive quantification of diseases related microRNA in the point-of-care diseases diagnosis field.

Precise quantification of microRNAs based on proximity ligation of AuNPs-immobilized DNA probes.

MiRNAs are critical regulators of target gene expression in many biological processes and are considered promising biomarkers for diseases. In this study, we developed a simple, specific, and sensitive miRNA detection method based on proximity ligation reaction, which is easy to operate. The method uses a pair of target-specific DNA probes immobilized on the same gold nanoparticles (AuNPs), which hybridize to the target miRNA. Hybridization brings the probes close together, allowing the formation of a continuous DNA sequence that can be amplified by Quantitative Real-time PCR (qPCR). This method eliminates the need for complex reverse transcription design and achieves high specificity for discriminating single base mismatches between miRNAs through a simple procedure. This method can sensitively measure three different miRNAs with a detection limit of 20 aM, providing high versatility and sensitivity, even distinguishing single-base variations among members of the miR-200 family with high selectivity. Due to its high selectivity and sensitivity, this method has important implications for the investigation of miRNA biological functions and related biomedical research.

Improving biosensor accuracy and speed using dynamic signal change and theory-guided deep learning

False results and time delay are longstanding challenges in biosensing. While classification models and deep learning may provide new opportunities for improving biosensor performance, such as measurement confidence and speed, it remains a challenge to ensure that predictions are explainable and consistent with domain knowledge. Here, we show that consistency of deep learning classification model predictions with domain knowledge in biosensing can be achieved by cost function supervision and enables rapid and accurate biosensing using the biosensor dynamic response. The impact and utility of the methodology were validated by rapid and accurate quantification of microRNA (let-7a) across the nanomolar (nM) to femtomolar (fM) concentration range using the dynamic response of cantilever biosensors. Data augmentation and cost function supervision based on the consistency of model predictions and experimental observations with the theory of surface-based biosensors improved the F1 score, precision, and recall of a recurrent neural network (RNN) classifier by an average of 13.8%. The theory-guided RNN (TGRNN) classifier enabled quantification of target analyte concentration and false results with an average prediction accuracy, precision, and recall of 98.5% using the initial transient or entire dynamic response, which is indicative of high prediction accuracy and low probability of false-negative and false-positive results. Classification scores were used to establish new relationships among biosensor performance characteristics (e.g., measurement confidence) and design parameters (e.g., inputs and hyperparameters of classification models and data acquisition parameters) that may be used for characterizing biosensor performance.

Reduction of Biosensor False Responses and Time Delay Using Dynamic Response and Theory-Guided Machine Learning.

Here, we provide a new methodology for reducing false results and time delay of biosensors, which are barriers to industrial, healthcare, military, and consumer applications. We show that integrating machine learning with domain knowledge in biosensing can complement and improve the biosensor accuracy and speed relative to the performance achieved by traditional regression analysis of a standard curve based on the biosensor steady-state response. The methodology was validated by rapid and accurate quantification of microRNA across the nanomolar to femtomolar range using the dynamic response of cantilever biosensors. Theory-guided feature engineering improved the performance and efficiency of several classification models relative to the performance achieved using traditional feature engineering methods (TSFRESH). In addition to the entire dynamic response, the technique enabled rapid and accurate quantification of the target analyte concentration and false-positive and false-negative results using the initial transient response, thereby reducing the required data acquisition time (i.e., time delay). We show that model explainability can be achieved by combining theory-guided feature engineering and feature importance analysis. The performance of multiple classifiers using both TSFRESH- and theory-based features from the biosensor's initial transient response was similar to that achieved using the entire dynamic response with data augmentation. We also show that the methodology can guide design of experiments for high-performance biosensing applications, specifically, the selection of data acquisition parameters (e.g., time) based on potential application-dependent performance thresholds. This work provides an example of the opportunities for improving biosensor performance, such as reducing biosensor false results and time delay, using explainable machine learning models supervised by domain knowledge in biosensing.

Absolute quantification of microRNAs based on mass transport limitation under a laminar flow SPR system

As an important biomarker for diagnostics and therapeutics of various diseases, the low-cost, quantitative detection method of microRNAs (miRNAs) has recently caught broad attention. However, their small size and low abundance still derive challenges to quantification detection. In this study, we developed an ultrasensitive and multiplexed surface plasmon resonance (SPR) biosensor for quantifying miRNAs without standard. We introduced the mass transport limitation (MTL) strategy for the absolute quantification of miRNAs. We first explore the mechanism of DNA capture and the condition for triggering MTL on the SPR biosensor. We demonstrated that probes of 22–25 nt in length with fewer influences of the secondary structure provide better triggering of MTL. For proof of concept studies, let-7a, miR-155 and miR-21 were selected as candidate targets. Based on the structure and kinetics analysis, we demonstrate the best capture probe efficiency, and this biosensor’s limit of detection (LOD) is 500 fM without any signal amplification. Furthermore, our biosensor achieves multiplex detection, which could detect three targets simultaneously. The quantitative results of miRNA indicated the great prospects of our biosensor in nucleic acid-related early diagnosis and biosensing.

LC-MS-Based Direct Quantification of MicroRNAs in Rat Blood.

MicroRNA (miRNA) has recently garnered significant research attention, owing to its potential as a diagnostic biomarker and therapeutic target. Liquid chromatography-mass spectrometry (LC-MS) offers accurate quantification, multiplexing capacity, and high compatibility with various matrices. These advantages establish it as a preferred technique for detecting miRNA in biological samples. In this study, we presented an LC-MS method for directly quantifying seven miRNAs (rno-miR-150, 146a, 21, 155, 223, 181a, and 125a) associated with immune and inflammatory responses in rat whole blood. To ensure miRNA stability in the samples and efficiently purify target analytes, we compared Trizol- and proteinase K-based extraction methods, and the Trizol extraction proved to be superior in terms of analytical sensitivity and convenience. Chromatographic separation was carried out using an oligonucleotide C18 column with a mobile phase composed of N-butyldimethylamine, 1,1,1,3,3,3-hexafluoro-2-propanol, and methanol. For MS detection, we performed high-resolution full scan analysis using an orbitrap mass analyzer with negative electrospray ionization. The established method was validated by assessing its selectivity, linearity, limit of quantification, accuracy, precision, recovery, matrix effect, carry-over, and stability. The proposed assay was then applied to simultaneously monitor target miRNAs in lipopolysaccharide-treated rats. Although potentially less sensitive than conventional methods, such as qPCR and microarray, this direct-detection-based LC-MS method can accurately and precisely quantify miRNA. Given these promising results, this method could be effectively deployed in various miRNA-related applications.

Single-microbead space-confined digital quantification strategy (SMSDQ) for counting microRNAs at the single-molecule level

Quantification of microRNAs (miRNAs) at the single-molecule level is of great significance for clinical diagnostics and biomedical research. The challenges lie in the limits to transforming single-molecule measurements into quantitative signals. To address these limits, here, we report a new approach called a Single Microbead-based Space-confined Digital Quantification (SMSDQ) to measure individual miRNA molecules by counting gold nanoparticles (AuNPs) with localized surface plasmon resonance (LSPR) light-scattering imaging. One miRNA target hybridizes with the alkynyl-modified capture DNA probe immobilized on a microbead (60 μm) and the azide-modified report DNA probe anchored on AuNP (50 nm), respectively. Through the click reaction between the alkynyl and azide group, a single microbead can covalently link the AuNPs in the confined space within the view of the microscope. By digitally counting the light-scattering spots of AuNPs, we demonstrated the proposed approach with single-molecule detection sensitivity and high specificity of single-base discrimination. Taking the advantages of ultrahigh sensitivity, specificity, and the digital detection manner, the approach is suitable for evaluating cell heterogeneity and small variations of miRNA expression and has been successfully applied to direct quantification of miRNAs in one-tenth single-cell lysates and serum samples without RNA-isolated and nucleic acid amplification steps.

A Framework Nucleic Acid-Mediated Multimodal Tandem Multivariate Signal Amplification Strategy for Simultaneous Absolute Quantification of Three Different MicroRNAs in a Single Cell.

The simultaneous quantification of multiple microRNAs (miRNA) in a single cell can help scientists understand the relationship between different miRNA groups and different types of cancers from an miRNA omics perspective at the single-cell level. However, there currently remains a challenge in developing techniques for the simultaneous absolute quantification of multiple miRNAs in single cells. Herein, we propose a framework nucleic acid (FNA)-mediated multimodal tandem multivariate signal amplification strategy for simultaneous absolute quantification of three different miRNAs in a single cell. In this study, DNA hexahedron FNAs (DHFs) and DNA tetrahedron FNAs (DTFs) were first prepared, multiple DNA hairpins and substrates were then connected to the hexahedron frame nucleic acid as the target recognition units, and three substrates with labeled FAM fluorophores on the tetrahedral frame nucleic acid served as signal output units. After the two types of FNAs entered the cell, they reacted with three different miRNAs (miRNA-155, miRNA-373, and miRNA-21) and multimodal tandem multivariate signal amplification was initiated simultaneously, reducing the detection limit of the three miRNAs to 8 × 10-15, 2 × 10-15, and 1 × 10-15 M, respectively. The detection sensitivity of the three miRNAs was simultaneously increased by six orders of magnitude, reaching the quantitative requirement of trace miRNAs in single cells. Combined with single-cell injection, membrane melting, and intracellular component separation technology on a microchip electrophoresis platform, we achieved the simultaneous absolute quantification of three different miRNAs in a single cell, thereby providing an important novel method that can be used to conduct single-cell research.

Spatiotemporal quantitative microRNA-155 imaging reports immune-mediated changes in a triple-negative breast cancer model.

MicroRNAs are small non-coding RNAs and represent key players in physiology and disease. Aberrant microRNA expression is central to the development and progression of cancer, with various microRNAs proposed as potential cancer biomarkers and drug targets. There is a need to better understand dynamic microRNA expression changes as cancers progress and their tumor microenvironments evolve. Therefore, spatiotemporal and non-invasive in vivo microRNA quantification in tumor models would be highly beneficial. We developed an in vivo microRNA detector platform in which the obtained signals are positively correlated to microRNA presence, and which permitted stable expression in cancer cells as needed for long-term experimentation in tumor biology. It exploits a radionuclide-fluorescence dual-reporter for quantitative in vivo imaging of a microRNA of choice by radionuclide tomography and fluorescence-based downstream ex vivo tissue analyses. We generated and characterized breast cancer cells stably expressing various microRNA detectors and validated them in vitro. We found the microRNA detector platform to report on microRNA presence in cells specifically and accurately, which was independently confirmed by real-time PCR and through microRNA modulation. Moreover, we established various breast tumor models in animals with different levels of residual immune systems and observed microRNA detector read-outs by imaging. Applying the detector platform to the progression of a triple-negative breast cancer model, we found that miR-155 upregulation in corresponding tumors was dependent on macrophage presence in tumors, revealing immune-mediated phenotypic changes in these tumors as they progressed. While applied to immunooncology in this work, this multimodal in vivo microRNA detector platform will be useful whenever non-invasive quantification of spatiotemporal microRNA changes in living animals is of interest.

Single cell quantification of microRNA from small numbers of non-invasively sampled primary human cells

Expression levels of microRNAs (miRNAs) in single cells are low and conventional miRNA detection methods require amplification that can be complex, time-consuming, costly and may bias results. Single cell microfluidic platforms have been developed; however, current approaches are unable to absolutely quantify single miRNA molecules expressed in single cells. Herein, we present an amplification-free sandwich hybridisation assay to detect single miRNA molecules in single cells using a microfluidic platform that optically traps and lyses individual cells. Absolute quantification of miR-21 and miR-34a molecules was achieved at a single cell level in human cell lines and validated using real-time qPCR. The sensitivity of the assay was demonstrated by quantifying single miRNA molecules in nasal epithelial cells and CD3+ T-cells, as well as nasal fluid collected non-invasively from healthy individuals. This platform requires ~50 cells or ~30 µL biofluid and can be extended for other miRNA targets therefore it could monitor miRNA levels in disease progression or clinical studies.