Blocking of targeted microRNAs from next-generation sequencing libraries

Highly abundant microRNAs (miRNAs) in small RNA sequencing libraries make it difficult to obtain efficient measurements of more lowly expressed species. We present a new method that allows for the selective blocking of specific, abundant miRNAs during preparation of sequencing libraries. This technique is specific with little off-target effects and has no impact on the reproducibility of the measurement of non-targeted species. In human plasma samples, we demonstrate that blocking of highly abundant hsa-miR-16–5p leads to improved detection of lowly expressed miRNAs and more precise measurement of differential expression overall. Furthermore, we establish the ability to target a second abundant miRNA and to multiplex the blocking of two miRNAs simultaneously. For small RNA sequencing, this technique could fill a similar role as do ribosomal or globin removal technologies in messenger RNA sequencing.     

220-plex microRNA expression profile of a single cell

Here we describe a protocol for the detection of the microRNA (miRNA) expression profile of a single cell by stem-looped real-time PCR, which is specific to mature miRNAs. A single cell is first lysed by heat treatment without further purification. Then, 220 known miRNAs are reverse transcribed into corresponding cDNAs by stem-looped primers. This is followed by an initial PCR step to amplify the cDNAs and generate enough material to permit separate multiplex detection. The diluted initial PCR product is used as a template to check individual miRNA expression by real-time PCR. This sensitive technique permits miRNA expression profiling from a single cell, and allows analysis of a few cells from early embryos as well as individual cells (such as stem cells). It can also be used when only nanogram amounts of rare samples are available. The protocol can be completed in 7 d.     

Multiplexed Nanometric 3D Tracking of Microbeads Using an FFT-Phasor Algorithm

Many single-molecule biophysical techniques rely on nanometric tracking of microbeads to obtain quantitative information about the mechanical properties of biomolecules such as chromatin fibers. Their three-dimensional (3D) position can be resolved by holographic analysis of the diffraction pattern in wide-field imaging. Fitting this diffraction pattern to Lorenz-Mie scattering theory yields the bead’s position with nanometer accuracy in three dimensions but is computationally expensive. Real-time multiplexed bead tracking therefore requires a more efficient tracking method, such as comparison with previously measured diffraction patterns, known as look-up tables. Here, we introduce an alternative 3D phasor algorithm that provides robust bead tracking with nanometric localization accuracy in a z range of over 10 μm under nonoptimal imaging conditions. The algorithm is based on a two-dimensional cross correlation using fast Fourier transforms with computer-generated reference images, yielding a processing rate of up to 10,000 regions of interest per second. We implemented the technique in magnetic tweezers and tracked the 3D position of over 100 beads in real time on a generic CPU. The accuracy of 3D phasor tracking was extensively tested and compared to a look-up table approach using Lorenz-Mie simulations, avoiding experimental uncertainties. Its easy implementation, efficiency, and robustness can improve multiplexed biophysical bead-tracking applications, especially when high throughput is required and image artifacts are difficult to avoid.     

Biological signalling activity measurements using mass spectrometry

MS (mass spectrometry) techniques are rapidly evolving to high levels of performance and robustness. This is allowing the application of these methods to the interrogation of signalling networks with unprecedented depth and accuracy. In the present review we discuss how MS-based multiplex quantification of kinase activities and phosphoproteomics provide complementary means to assess biological signalling activity. In addition, we discuss how a wider application of these analytical concepts to quantify kinase signalling will result in a more comprehensive understanding of normal and disease biology at the system level.     

Robust Eye Center Localization through Face Alignment and Invariant Isocentric Patterns

The localization of eye centers is a very useful cue for numerous applications like face recognition, facial expression recognition, and the early screening of neurological pathologies. Several methods relying on available light for accurate eye-center localization have been exploited. However, despite the considerable improvements that eye-center localization systems have undergone in recent years, only few of these developments deal with the challenges posed by the profile (non-frontal face). In this paper, we first use the explicit shape regression method to obtain the rough location of the eye centers. Because this method extracts global information from the human face, it is robust against any changes in the eye region. We exploit this robustness and utilize it as a constraint. To locate the eye centers accurately, we employ isophote curvature features, the accuracy of which has been demonstrated in a previous study. By applying these features, we obtain a series of eye-center locations which are candidates for the actual position of the eye-center. Among these locations, the estimated locations which minimize the reconstruction error between the two methods mentioned above are taken as the closest approximation for the eye centers locations. Therefore, we combine explicit shape regression and isophote curvature feature analysis to achieve robustness and accuracy, respectively. In practical experiments, we use BioID and FERET datasets to test our approach to obtaining an accurate eye-center location while retaining robustness against changes in scale and pose. In addition, we apply our method to non-frontal faces to test its robustness and accuracy, which are essential in gaze estimation but have seldom been mentioned in previous works. Through extensive experimentation, we show that the proposed method can achieve a significant improvement in accuracy and robustness over state-of-the-art techniques, with our method ranking second in terms of accuracy. According to our implementation on a PC with a Xeon 2.5Ghz CPU, the frame rate of the eye tracking process can achieve 38 Hz.     

A Facile and Specific Assay for Quantifying MicroRNA by an Optimized RT-qPCR Approach

Background

The spatiotemporal expression patterns of microRNAs (miRNAs) are important to the verification of their predicted function. RT-qPCR is the accepted technique for the quantification of miRNA expression; however, stem-loop RT-PCR and poly(T)-adapter assay, the two most frequently used methods, are not very convenient in practice and have poor specificity, respectively.

Results

We have developed an optimal approach that integrates these two methods and allows specific and rapid detection of tiny amounts of sample RNA and reduces costs relative to other techniques. miRNAs of the same sample are polyuridylated and reverse transcribed into cDNAs using a universal poly(A)-stem-loop RT primer and then used as templates for SYBR® Green real-time PCR. The technique has a dynamic range of eight orders of magnitude with a sensitivity of up to 0.2 fM miRNA or as little as 10 pg of total RNA. Virtually no cross-reaction is observed among the closely-related miRNA family members and with miRNAs that have only a single nucleotide difference in this highly specific assay. The spatial constraint of the stem-loop structure of the modified RT primer allowed detection of miRNAs directly from cell lysates without laborious total RNA isolation, and the poly(U) tail made it possible to use multiplex RT reactions of mRNA and miRNAs in the same run.

Conclusions

The cost-effective RT-qPCR of miRNAs with poly(A)-stem-loop RT primer is simple to perform and highly specific, which is especially important for samples that are precious and/or difficult to obtain.     

MicroRNAs Are Part of the Regulatory Network that Controls EGF Induced Apoptosis,Including Elements of the JAK/STAT Pathway,in A431 Cells

MiRNAs are known to regulate gene expression and in the context of cancer have been shown to regulate metastasis, cell proliferation and cell death. In this report we describe potential miRNA regulatory roles with respect to induction of cell death by pharmacologic dose of Epidermal Growth Factor (EGF). Our previous work suggested that multiple pathways are involved in the induction of apoptosis, including interferon induced genes, cytokines, cytoskeleton and cell adhesion and TP53 regulated genes. Using miRNA time course expression profiling of EGF treated A431 cells and coupling this to our previous gene expression and proteomic data, we have been able to implicate a number of additional miRNAs in the regulation of apoptosis. Specifically we have linked miR-134, miR-145, miR-146b-5p, miR-432 and miR-494 to the regulation of both apoptotic and anti-apoptotic genes expressed as a function of EGF treatment. Whilst additional miRNAs were differentially expressed, these had the largest number of apoptotic and anti-apoptotic targets. We found 5 miRNAs previously implicated in the regulation of apoptosis and our results indicate that an additional 20 miRNAs are likely to be involved based on their correlated expression with targets. Certain targets were linked to multiple miRNAs, including PEG10, BTG1, ID1, IL32 and NCF2. Some miRNAs that target the interferon pathway were found to be down regulated, consistent with a novel layer of regulation of interferon pathway components downstream of JAK/STAT. We have significantly expanded the repertoire of miRNAs that may regulate apoptosis in cancer cells as a result of this work.     

Improved prediction of radiation pneumonitis by combining biological and radiobiological parameters using a data-driven Bayesian network analysis

Grade 2 and higher radiation pneumonitis (RP2) is a potentially fatal toxicity that limits efficacy of radiation therapy (RT). We wished to identify a combined biomarker signature of circulating miRNAs and cytokines which, along with radiobiological and clinical parameters, may better predict a targetable RP2 pathway. In a prospective clinical trial of response-adapted RT for patients (n = 39) with locally advanced non-small cell lung cancer, we analyzed patients’ plasma, collected pre- and during RT, for microRNAs (miRNAs) and cytokines using array and multiplex enzyme linked immunosorbent assay (ELISA), respectively. Interactions between candidate biomarkers, radiobiological, and clinical parameters were analyzed using data-driven Bayesian network (DD-BN) analysis. We identified alterations in specific miRNAs (miR-532, -99b and -495, let-7c, -451 and -139-3p) correlating with lung toxicity. High levels of soluble tumor necrosis factor alpha receptor 1 (sTNFR1) were detected in a majority of lung cancer patients. However, among RP patients, within 2 weeks of RT initiation, we noted a trend of temporary decline in sTNFR1 (a physiological scavenger of TNFα) and ADAM17 (a shedding protease that cleaves both membrane-bound TNFα and TNFR1) levels. Cytokine signature identified activation of inflammatory pathway. Using DD-BN we combined miRNA and cytokine data along with generalized equivalent uniform dose (gEUD) to identify pathways with better accuracy of predicting RP2 as compared to either miRNA or cytokines alone. This signature suggests that activation of the TNFα-NFκB inflammatory pathway plays a key role in RP which could be specifically ameliorated by etanercept rather than current therapy of non-specific leukotoxic corticosteroids.     

Betaine Significantly Improves Multiplex Tetra-Primer ARMS-PCR Methods

The tetra-primer ARMS-PCR method offers significant advantages over the commonly used methods to genotype single nucleotide polymorphisms. It offers fast and cost-effective detection and requires minimum level of expertise and basic instrumentation. The benefits of TP-ARMS-PCR increase exponentially upon multiplexing. However, several complications preclude the common use of multiplex TP-ARMS-PCR methods, primarily the lack of robustness and the difficulty of optimization. We have previously developed triplex and quadruplex TP-ARMS-PCR methods involving the simultaneous detection of up to three SNPs in a single reaction and utilized Betaine, a PCR additive used to enable amplification of GC-rich templates with strong secondary structures, in an attempt to facilitate method development and optimization. In the present communication, we introduced experimental data demonstrating the important effects of Betaine on our previous methods and its potential to overcome the ruggedness and robustness issues commonly found in TP-ARMS-PCR methods, and highlighted the general benefits of Betaine with respect to TP-ARMS-PCR. Our data support the routine inclusion of Betaine in all TP-ARMS-PCR methods, especially when multiplexing is concerned.     

Performance comparison and evaluation of software tools for microRNA deep-sequencing data analysis

With the development of next-generation sequencing (NGS) techniques, many software tools have emerged for the discovery of novel microRNAs (miRNAs) and for analyzing the miRNAs expression profiles. An overall evaluation of these diverse software tools is lacking. In this study, we evaluated eight software tools based on their common feature and key algorithms. Three deep-sequencing data sets were collected from different species and used to assess the computational time, sensitivity and accuracy of detecting known miRNAs as well as their capacity for predicting novel miRNAs. Our results provide useful information for researchers to facilitate their selection of the optimal software tools for miRNA analysis depending on their specific requirements, i.e. novel miRNAs discovery or miRNA expression profile analysis of sequencing data sets.