Identifying Protein Phosphorylation Site-Disease Associations Based on Multi-Similarity Fusion and Negative Sample Selection by Convolutional Neural Network.

As one of the most important post-translational modifications (PTMs), protein phosphorylation plays a key role in a variety of biological processes. Many studies have shown that protein phosphorylation is associated with various human diseases. Therefore, identifying protein phosphorylation site-disease associations can help to elucidate the pathogenesis of disease and discover new drug targets. Networks of sequence similarity and Gaussian interaction profile kernel similarity were constructed for phosphorylation sites, as well as networks of disease semantic similarity, disease symptom similarity and Gaussian interaction profile kernel similarity were constructed for diseases. To effectively combine different phosphorylation sites and disease similarity information, random walk with restart algorithm was used to obtain the topology information of the network. Then, the diffusion component analysis method was utilized to obtain the comprehensive phosphorylation site similarity and disease similarity. Meanwhile, the reliable negative samples were screened based on the Euclidean distance method. Finally, a convolutional neural network (CNN) model was constructed to identify potential associations between phosphorylation sites and diseases. Based on tenfold cross-validation, the evaluation indicators were obtained including accuracy of 93.48%, specificity of 96.82%, sensitivity of 90.15%, precision of 96.62%, Matthew's correlation coefficient of 0.8719, area under the receiver operating characteristic curve of 0.9786 and area under the precision-recall curve of 0.9836. Additionally, most of the top 20 predicted disease-related phosphorylation sites (19/20 for Alzheimer's disease; 20/16 for neuroblastoma) were verified by literatures and databases. These results show that the proposed method has an outstanding prediction performance and a high practical value.

Dephosphorylation Switch DNAzyme-RCA Circuit: A Robust Strategy for the Homogeneous and Reliable Detection of FTO Demethylase.

Fat mass and obesity-associated protein (FTO) plays a crucial role in regulating the dynamic modification of N6-methyladenosine (m6A) in eukaryotic mRNA. Sensitive detection of the FTO level and efficient evaluation of the FTO demethylase activity are of great importance to early cancer diagnosis and anticancer drug discovery, which are currently challenged by limited sensitivity/precision and low throughput. Herein, a robust strategy based on the dephosphorylation switch DNAzyme-rolling circle amplification (RCA) circuit, termed DSD-RCA, is developed for highly sensitive detection of FTO and inhibitor screening. Initially, the catalytic activity of DNAzyme is silenced by engineering with an m6A modification in its catalytic core. Only in the presence of target FTO can the methyl group on DNAzyme be eliminated, resulting in the activation of the catalytic activity of DNAzyme and thus cleaving the hairpin substrate to release numerous primers. Different from the conventional methods that use the downstream cleavage primer with the original 3'-hydroxyl end directly as the RCA primer with the problem of high background signal, which should be compensated by additional separation and wash steps in heterogeneous format, our DSD-RCA assay uses the upstream cleavage primer with a 2',3'-cyclic phosphate terminus at the 3'-end serving as an intrinsically blocked 3' end. Only after a dephosphorylation reaction mediated by T4 polynucleotide kinase can the upstream cleavage primers with a resultant 3'-hydroxyl end be extended by RCA. With the high signal-to-noise ratio and homogeneous property, the proposed platform can sensitively detect FTO with a limit of detection of 31.4 pM, and the relative standard deviations (RSDs %) ranging from 0.8 to 2.0% were much lower than the heterogeneous methods. The DSD-RCA method was applied for analyzing FTO in cytoplasmic lysates from different cell lines and tissues of breast cancer patients and further used for screening FTO inhibitors without the need for separation or cleaning, providing an opportunity for achieving high throughput and demonstrating the potential applications of this strategy in disease diagnostics, drug discovery, and biological applications.

A DNAzyme dual-feedback autocatalytic exponential amplification biocircuit for microRNA imaging in living cells.

Autocatalytic biocircuit are powerful tools for analysing intracellular biomarkers, but these tools are constrained by limitations in amplification capacity and intracellular delivery efficiency. In this work, we developed a DNAzyme-based dual-feedback autocatalytic exponential amplification biocircuit sustained by a honeycomb MnO2 nanosponge (EDA2@hMNS) for live-cell imaging of intracellular low-abundance microRNAs (miRNA). The EDA2 biocircuit comprises a blocked DNAzyme (b-DNAzyme), a Fuel strand and a Substrate strand. In the EDA2 biocircuit, target miRNAs are recycled and feedback for rounds of DNAzymatic amplification, and the DNAzymatic reactions continuously generate target miRNA analogues for dual-feedback to achieve multiple parallel cascade DNAzymatic reactions that improve amplification capacity substantially. In addition, the hMNS ensures high loading and delivery efficiency of biocircuit probes into living cells and also provides sufficient Mn2+ DNAzyme cofactor from in situ decomposition by intracellular glutathione (GSH). The EDA2@hMNS realized a detection limit of 17 pM, which is 288-fold lower than the b-DNAzyme lacking the DNAzymatic amplification. These results demonstrate the great promise for this critical tool in analysing low-abundance biomarkers and cancer diagnostics.

On-Site-Activated Transmembrane Logic DNA Nanodevice Enables Highly Specific Imaging of Cancer Cells by Targeting Tumor-Related Nucleolin and Intracellular MicroRNA.

The ability to specifically image cancer cells is essential for cancer diagnosis; however, this ability is limited by the false positive associated with single-biomarker sensors and off-site activation of "always active" nucleic acid probes. Herein, we propose an on-site, activatable, transmembrane logic DNA (TLD) nanodevice that enables dual-biomarker sensing of tumor-related nucleolin and intracellular microRNA for highly specific cancer cell imaging. The TLD nanodevice is constructed by assembling a tetrahedral DNA nanostructure containing a linker (L)-blocker (B)-DNAzyme (D)-substrate (S) unit. AS-apt, a DNA strand containing an elongated segment and the AS1411 aptamer, is pre-anchored to nucleolin protein, which is specifically expressed on the membrane of cancer cells. Initially, the TLD nanodevice is firmly sealed by the blocker containing an AS-apt recognition zone, which prevents off-site activation. When the nanodevice encounters a target cancer cell, AS-apt (input 1) binds to the blocker and unlocks the sensing ability of the nanodevice for miR-21 (input 2). The TLD nanodevice achieves dual-biomarker sensing from the cell membrane to the cytoplasm, thereby ensuring cancer cell-specific imaging. This TLD nanodevice represents a promising strategy for the highly reliable analysis of intracellular biomarkers and a promising platform for cancer diagnosis and related biomedical applications.

DNAzyme-Amplified Cascade Catalytic Hairpin Assembly Nanosystem for Sensitive MicroRNA Imaging in Living Cells.

Sensitive imaging of microRNAs (miRNAs) in living cells is significant for accurate cancer clinical diagnosis and prognosis research studies, but it is challenged by inefficient intracellular delivery, instability of nucleic acid probes, and limited amplification efficiency. Herein, we engineered a DNAzyme-amplified cascade catalytic hairpin assembly (CHA)-based nanosystem (DCC) that overcomes these challenges and improves the imaging sensitivity. This enzyme-free amplification nanosystem is based on the sequential activation of DNAzyme amplification and CHA. MnO2 nanosheets were used as nanocarriers for the delivery of nucleic acid probes, which can resist the degradation by nucleases and supply Mn2+ for the DNAzyme reaction. After entering into living cells, the MnO2 nanosheets can be decomposed by intracellular glutathione (GSH) and release the loaded nucleic acid probes. In the presence of target miRNA, the locking strand (L) was hybridized with target miRNA, and the DNAzyme was released, which then cleaved the substrate hairpin (H1). This cleavage reaction resulted in the formation of a trigger sequence (TS) that can activate CHA and recover the fluorescence readout. Meanwhile, the DNAzyme was released from the cleaved H1 and bound to other H1 for new rounds of DNAzyme-based amplification. The TS was also released from CHA and involved in the new cycle of CHA. By this DCC nanosystem, low-abundance target miRNA can activate many DNAzyme and generate numerous TS for CHA, resulting in sensitive and selective analysis of miRNAs with a limit of detection of 5.4 pM, which is 18-fold lower than that of the traditional CHA system. This stable, sensitive, and selective nanosystem holds great potential for miRNA analysis, clinical diagnosis, and other related biomedical applications.

A Knowledge-Graph-Based Multimodal Deep Learning Framework for Identifying Drug-Drug Interactions.

The identification of drug-drug interactions (DDIs) plays a crucial role in various areas of drug development. In this study, a deep learning framework (KGCN_NFM) is presented to recognize DDIs using coupling knowledge graph convolutional networks (KGCNs) with neural factorization machines (NFMs). A KGCN is used to learn the embedding representation containing high-order structural information and semantic information in the knowledge graph (KG). The embedding and the Morgan molecular fingerprint of drugs are then used as input of NFMs to predict DDIs. The performance and effectiveness of the current method have been evaluated and confirmed based on the two real-world datasets with different sizes, and the results demonstrate that KGCN_NFM outperforms the state-of-the-art algorithms. Moreover, the identified interactions between topotecan and dantron by KGCN_NFM were validated through MTT assays, apoptosis experiments, cell cycle analysis, and molecular docking. Our study shows that the combination therapy of the two drugs exerts a synergistic anticancer effect, which provides an effective treatment strategy against lung carcinoma. These results reveal that KGCN_NFM is a valuable tool for integrating heterogeneous information to identify potential DDIs.

Dual-Locked DNAzyme Platform for In Vitro and In Vivo Discrimination of Cancer Cells.

Imaging of tumor-associated microRNAs (miRNAs) can provide abundant information for cancer diagnosis, whereas the occurrence of trace amounts of miRNAs in normal cells inevitably causes an undesired false-positive signal in the discrimination of cancer cells during miRNA imaging. In this study, we propose a dual-locked (D-locked) platform consisting of the enzyme/miRNA-D-locked DNAzyme sensor and the honeycomb MnO2 nanosponge (hMNS) nanocarrier for highly specific cancer cell imaging. For a proof-of-concept demonstration, apurinic/apyrimidinic endonuclease 1 (APE1) and miR-21 were chosen as key models. The hMNS nanocarrier can efficiently release the D-locked DNAzyme sensor in living cells due to the decomposition of hMNS by glutathione, which can also supply Mn2+ for DNAzyme cleavage. Ascribing to the smart design of the D-locked DNAzyme sensor, the fluorescence signal can only be generated by the synergistic response of APE1 and miR-21 that are overexpressed in cancer cells. Compared with the miRNA single-locked DNAzyme sensor and the small-molecule (ATP)/miRNA D-locked DNAzyme sensor, the proposed enzyme (APE1)/miRNA D-locked DNAzyme sensor exhibited 2.6-fold and 2.4-fold higher discrimination ratio (Fcancer/Fnormal) for cancer cell discrimination, respectively. Owing to the superior performance, the D-locked strategy can selectively generate a fluorescence signal in cancer cells, facilitating accurate discrimination of cancer both in vitro and in vivo. Furthermore, this D-locked platform is easily adaptable toward other target molecules by redesigning the DNA sequences. The outstanding performance and expansibility of this D-locked platform holds promising prospects for cancer diagnosis and related biomedical applications.

Light-Controlled Recruitable Hybridization Chain Reaction on Exosome Vehicles for Highly Sensitive MicroRNA Imaging in Living Cells.

Sensitive imaging of intracellular microRNA (miRNA) in living cells is of great significance. Isothermal hybridization chain reaction (HCR)-based methods, although have been widely used to monitor intracellular low-abundance miRNA, are still subjected to the challenges of limited signal amplification efficiency and compromised imaging resolution. In this work, we design a light-controlled recruitable HCR (LCR-HCR) strategy that enables us to well overcome these limitations. Exosomes as delivery and recruitment vehicles are modified with three cholesterol-modified hairpins (H1, H2, and H3), in which H1 is for anchoring target miRNA and H2 and H3 with photocleavable linkers (PC-linkers) are designed for spatiotemporal HCR. By controllably releasing probes with high local concentrations to efficiently trigger HCR and further recruiting the generated double-stranded DNA (dsDNA) polymers instead of dispersion in the cytoplasm, the LCR-HCR method can significantly improve the imaging contrast by confining all of the reactants on exosome vehicles. For a proof-of-concept demonstration, the miR-21 was analyzed by LCR-HCR with a limit of detection (LOD) down to 3.3 pM (corresponding to 165 amol per 50 µL) in vitro and four times higher response than traditional HCR in vivo. In general, the LCR-HCR method provides a powerful tool for sensitive miRNA imaging in living cells and cancer diagnosis.

Cell-Selective Encapsulation within Metal-Organic Framework Shells via Precursor-Functionalized Aptamer Identification for Whole-Cell Cancer Vaccine.

Single-cell encapsulation is an emerging technology to endow cells with various functions, of which developing new applications in vivo is in high demand. Currently, metal-organic frameworks (MOFs) that are used as nanometric shells to coat living cells, however, have not realized cell-selective encapsulation. Here, a biocompatible and selective cell encapsulation strategy based on precursor-functionalized nucleolin aptamer and in situ MOF mineralization on the aptamer-identified cancer cell surface are developed. After MOF coating, the encapsulated cancer cells undergo immunogenic cell death, which is found associated with the changed cell stiffness (indicated by Young's modulus). The immunogenic dead cancer cells are used as whole-cell cancer vaccines (WCCVs), forming the integral WCCV-in-shell structure with enhanced immunogenicity ascribing from the surface-exposed calreticulin to promote dendritic cell recruitment, antigen presentation, and T-cell activation. The major activation pathways in the immune response are identified including tumor necrosis factor signaling pathway, cytokine-cytokine receptor interaction, and Toll-like receptor signaling pathway, suggesting the potential adjuvant effect of the MOF shells. After vaccination, WCCV-in-shell shows much better tumor immunoprophylaxis than either the imperfectly coated cancer cells or the traditional WCCV. This strategy is promising for the universal and facile development of novel whole-cell vaccines.

Highly Sensitive Fluorescence Detection of Global 5-Hydroxymethylcytosine from Nanogram Input with Strongly Emitting Copper Nanotags.

Quantitative analysis of 5-hydroxymethylcytosine (5hmC) has remarkable clinical significance to early cancer diagnosis; however, it is limited by the requirement in current assays for large amounts of starting material and expensive instruments requring expertise. Herein, we present a highly sensitive fluorescence method, termed hmC-TACN, for global 5hmC quantification from several nanogram inputs based on terminal deoxynucleotide transferase (TdT)-assisted formation of fluorescent copper (Cu) nanotags. In this method, 5hmC is labeled with click tags by T4 phage ß-glucosyltransferase (ß-GT) and cross-linked with a random DNA primer via click chemistry. TdT initiates the template-free extension along the primer at the modified 5hmC site and then generates a long polythymine (T) tail, which can template the production of strongly emitting Cu nanoparticles (CuNPs). Consequently, an intensely fluorescent tag containing numerous CuNPs can be labeled onto the 5hmC site, providing the sensitive quantification of 5hmC with a limit of detection (LOD) as low as 0.021% of total nucleotides (S/N = 3). With only a 5 ng input (∼1000 cells) of genomic DNA, global 5hmC levels were accurately determined in mouse tissues, human cell lines (including normal and cancer cells of breast, lung, and liver), and urines of a bladder cancer patient and healthy control. Moreover, as few as 100 cells can also be distinguished between normal and cancer cells. The hmC-TACN method has great promise of being cost effective and easily mastered, with low-input clinical utility, and even for the microzone analysis of tumor models.

A MOF-Shell-Confined I-Motif-Based pH Probe (MOFC-i) Strategy for Sensitive and Dynamic Imaging of Cell Surface pH.

Dynamic imaging of cell surface pH is extremely challenging due to the slight changes in pH and the fast diffusion of secreted acid to the extracellular environment. In this work, we construct a novel metal-organic framework (MOF)-shell-confined i-motif-based pH probe (MOFC-i) strategy that enables sensitive and dynamic imaging of cell surface pH. The CY3- and CY5-labeled i-motif, which is hybridized via its short complementary chain with two-base mismatches, is optimized for sensing at physiological pH. After efficiently anchoring the optimized pH probes onto the cell membrane with the aid of cholesterol groups, a biocompatible microporous MOF shell is then formed around the cell by cross-linking ZIF-8 nanoparticles via tannic acid. The microporous MOF shell can confine secreted acid without inhibiting the normal physiological activities of cells; thus, the MOFC-i strategy can be used to monitor dynamic changes in the cell surface pH of living cells. Furthermore, this method can not only clearly distinguish the different metabolic behaviors of cancer cells and normal cells but also reveal drug effects on the cell surface pH or metabolism, providing promising prospects in pH-related diagnostics and drug screening.

Cancer cell identification by facile imaging of intracellular reductive substances with fluorescent nanosensor.

Ascorbic acid (AA) and glutathione (GSH), the most abundant intracellular reductive substances, have been widely used as biomarkers for cancer cells identification. The current methods relying on imaging of AA or GSH alone to identify cancer cells may cause systematic errors, since a mutual conversion relationship exists between AA and GSH. In this work, we propose a fluorescent nanosensor for the simultaneous imaging of intracellular reductive substances including AA and GSH. Biocompatible fluorescent silicon nanoparticles (SiNPs) with rich surface amine and carboxyl groups were synthesized. The fluorescence of the SiNP was initially quenched by chelation of Fe3+ ions, forming SiNP/Fe3+ complex as the fluorescent nanosensor. Upon the redox reaction with reductive substances, the nanosensor showed sensitively fluorescent recovery. Moreover, benefited from the efficient cellular uptake of the SiNP/Fe3+ and the overexpressed intracellular reductive substances in cancer cells, the fluorescent nanosensor was used to accurately identify the human breast carcinoma (MCF-7) cells from normal mammary epithelial (MCF-10A) cells by imaging of intracellular AA and GSH simultaneously. This strategy would be promising in imaging-guided precision cancer diagnosis.

Toehold-mediated ligation-free rolling circle amplification enables sensitive and rapid imaging of messenger RNAs in situ in cells.

In situ analysis of tumor-related messenger RNAs (mRNAs) is significant in identifying cancer cells at the genetic level in the early stage. Rolling circle amplification (RCA)-based methods are primary tools for in situ mRNA assay, however, the necessary ligation reaction not only shows low ligation efficiency, but also greatly prolongs the assay time that increases the risk of cells losing and mRNAs leakage. In this work, we propose a novel toehold-mediated ligation-free RCA (TMLFRCA) on a designed structure-switchable dumbbell-shaped probe (SDP). Target mRNA can specifically activate SDP from its circular form by toehold strand displacement, thereby initiates in situ RCA for mRNA imaging with the help of a short DNA primer. For the proof-of-concept demonstration, the TK1 mRNA was sensitively detected by TMLFRCA in less than 3.5 h with a limit of detection (LOD) of 0.39 fM (corresponds to 2.39×108copiesL-1), and significantly improved specificity capable for distinguishing single base difference. The sensitivity of the TMLFRCA for TK1 mRNA in situ assay is ∼29-fold and ∼7-fold higher than that of FISH and ligase-assisted RCA method, respectively, which enables the TMLFRCA method capability of highly sensitive and specific distinction mRNA expression levels between cancer cells and normal cells. We believe this TMLFRCA strategy would be of great value in both basic research and clinical diagnosis.

Novel Potential Small Molecule-MiRNA-Cancer Associations Prediction Model Based on Fingerprint, Sequence, and Clinical Symptoms.

As an important biomarker in organisms, miRNA is closely related to various small molecules and diseases. Research on small molecule-miRNA-cancer associations is helpful for the development of cancer treatment drugs and the discovery of pathogenesis. It is very urgent to develop theoretical methods for identifying potential small molecular-miRNA-cancer associations, because experimental approaches are usually time-consuming, laborious, and expensive. To overcome this problem, we developed a new computational method, in which features derived from structure, sequence, and symptoms were utilized to characterize small molecule, miRNA, and cancer, respectively. A feature vector was construct to characterize small molecule-miRNA-cancer association by concatenating these features, and a random forest algorithm was utilized to construct a model for recognizing potential association. Based on the 5-fold cross-validation and benchmark data set, the model achieved an accuracy of 93.20 ± 0.52%, a precision of 93.22 ± 0.51%, a recall of 93.20 ± 0.53%, and an F1-measure of 93.20 ± 0.52%. The areas under the receiver operating characteristic curve and precision recall curve were 0.9873 and 0.9870. The real prediction ability and application performance of the developed method have also been further evaluated and verified through an independent data set test and case study. Some potential small molecules and miRNAs related to cancer have been identified and are worthy of further experimental research. It is anticipated that our model could be regarded as a useful high-throughput virtual screening tool for drug research and development. All source codes can be downloaded from https://github.com/LeeKamlong/Multi-class-SMMCA.

Fluorescence on-off-on with small and charge-tunable nanoparticles enables highly sensitive intracellular microRNA imaging in living cells.

Nanomaterial-based on-off-on fluorescence sensing strategies are significant particularly in intracellular nucleic acids imaging assay. There still remains challenge to rationally balance fluorescence quenching efficiency and recovery dynamics. We assume that the performance of on-off-on fluorescence sensing strategy can be fundamentally improved on small zero-dimensional (0D) nanomaterial with precisely modulated surface charge. For a proof-of-concept demonstration, silicon nanoparticle (SiNP) with ~4 nm was synthesized and used as the quencher model, of which the surface charge density was modulated by modification of triphenylphosphonium (TPP). The influence of particle size, surface charge and charge density of the nanomaterials on sensing performance was systematically investigated. The strategy showed a low limit of detection (LOD) as 26 pM for target model miR-494, which is one of the lowest in nanomaterial-based on-off-on sensing platforms. And the LOD is even comparable to amplification-based methods in a greatly shortened assay time (2.5 h). The miR-494 expresses in cancerous and normal living cells of human cervical carcinoma (HeLa), human lung carcinoma (A549), human breast cancer (MCF-7), and normal human mammary epithelial (MCF-10A) cells were imaged and localized with significantly improved sensitivity and specificity. These excellent performances insure it a promising candidate as convenient and non-enzymatic sensing platform for miRNA-associated disease detection and early diagnosis.

A protein triggering exponential amplification reaction enables label- and wash-free one-pot protein assay with high sensitivity.

Methods capable of sensitive and facile quantification of low-abundant proteins play critical roles in disease diagnosis and treatment. Herein, on a rationally designed aptamer-based hairpin structure-switching template, we developed a protein triggering exponential amplification reaction (PTEXPAR) method. The platelet-derived growth factor BB (PDGF-BB) is used as model analyte in the current proof-of-concept experiments. This method can detect PDGF-BB specifically with a detection limit as low as 4.9 fM. Additionally, the proposed PTEXPAR strategy allows label- and wash-free one-pot quantification of protein within ~35 min. Moreover, it is potentially universal because hairpin template can be easily designed for other proteins by changing the corresponding aptamer sequence.

Seq-SymRF: a random forest model predicts potential miRNA-disease associations based on information of sequences and clinical symptoms.

Increasing evidence indicates that miRNAs play a vital role in biological processes and are closely related to various human diseases. Research on miRNA-disease associations is helpful not only for disease prevention, diagnosis and treatment, but also for new drug identification and lead compound discovery. A novel sequence- and symptom-based random forest algorithm model (Seq-SymRF) was developed to identify potential associations between miRNA and disease. Features derived from sequence information and clinical symptoms were utilized to characterize miRNA and disease, respectively. Moreover, the clustering method by calculating the Euclidean distance was adopted to construct reliable negative samples. Based on the fivefold cross-validation, Seq-SymRF achieved the accuracy of 98.00%, specificity of 99.43%, sensitivity of 96.58%, precision of 99.40% and Matthews correlation coefficient of 0.9604, respectively. The areas under the receiver operating characteristic curve and precision recall curve were 0.9967 and 0.9975, respectively. Additionally, case studies were implemented with leukemia, breast neoplasms and hsa-mir-21. Most of the top-25 predicted disease-related miRNAs (19/25 for leukemia; 20/25 for breast neoplasms) and 15 of top-25 predicted miRNA-related diseases were verified by literature and dbDEMC database. It is anticipated that Seq-SymRF could be regarded as a powerful high-throughput virtual screening tool for drug research and development. All source codes can be downloaded from https://github.com/LeeKamlong/Seq-SymRF .

Polymerization retardation isothermal amplification strategy enables the sensitive and facile investigation of the flanking sequence preference of ten-eleven translocation 2 protein.

Active DNA demethylation process critically relies on the intrinsic properties of ten-eleven translocation proteins (Tets), particularly the flanking sequence preference. Challenged by the fact that the proximate bases to the 5-methylcytosine (5mC) are multitudinous and their influence on the Tets/DNA interplay is minute, the current methodologies are very limited in terms of cost, sensitivity and efficiency. Herein, we propose a polymerization retardation isothermal amplification (PRIA) strategy that enables sensitive and fast study of the flanking sequence preference of Tet. By arranging DNA polymerase to repetitively pass DNA strands through an isothermal replication-scission amplification reaction, the tiny difference in the Tet/DNA interplay can be consecutively accumulated and amplified. Low amount sample (80 ng) even multiple samples can be simultaneously analyzed within 10 h on an easily accessible laboratory real-time quantitative PCR instrument. For a proof-of-concept study, the binding preference (PB) of Tet2 for XmCGX, (X = C, G, T, A) was analyzed by PRIA and computational analysis, showing an order of AmCGT > TmCGA ≈ GmCGC > CmCGG. Furthermore, the binding and oxidation preference in Tet/DNA interplay process was individually considered. By comparative evaluation of the total flanking sequence preference (PT) and the PB, for the first time, we revealed that Tet2 has a lower oxidation preference (PO) to proximal flanking bases and the main contributor to PT of Tet2 is PB. The PRIA strategy, due to its reliable, cost-effective, high efficiency and low sample input, would hopefully advance epigenetic researches and other relative studies.

A new QCM signal enhancement strategy based on streptavidin@metal-organic framework complex for miRNA detection.

Sensitive and selective detection of miRNA is of great significance for the early diagnosis of human diseases, especially for cancers. Quartz crystal microbalance (QCM) is an effective tool for detecting biological molecules; however, the application of QCM for miRNA detection is still very limited. One of the great needs for QCM detection is to further improve the QCM signal. Herein, for the first time, we promote a new signal enhancement strategy for the detection of miRNA by QCM. First, a hairpin biotin-modified DNA was used as a probe DNA, which exposes the biotin site when interacting with target miRNA. Then, a streptavidin@metal-organic framework (SA@MOF) complex formed by electrostatic attractions between SA and a MOF was introduced into the QCM detection system. The SA@MOF complexes serve as both a signal amplifier and a specific recognition element via specific biotin-SA interactions. The strategy was applied to the detection of a colorectal cancer marker, miR-221, by using a stable Zr(IV)-MOF, UiO-66-NH2. The detection linear range was 10 fM-1 nM, the detection limit was 6.9 fM, and the relative standard deviation (RSD) (n = 5) was lower than 10% in both simulated conditions and the real serum environment. Furthermore, the detection limit reached 0.79 aM when coupled with the isothermal exponential amplification reaction (EXPAR).

Sandwich immunoassay coupled with isothermal exponential amplification reaction: An ultrasensitive approach for determination of tumor marker MUC1.

An ultrasensitive strategy based on sandwich immunoassay coupled with isothermal exponential amplification reaction (IMEXPAR) is proposed for the determination of tumor protein Mucin 1 (MUC1). An immuno-PCR plate was prepared from modification of the primary MUC1-antibody (Ab1) onto the inner-well of the PCR plate. A biotinylated secondary MUC1-antibody tagged with the biotinylated EXPAR primer (P-Ab2) was prepared through biotin-streptavidin reaction. In the presence of target MUC1, sandwich-type combinations were specifically formed in the immuno-PCR plate. With further addition of amplification template, polymerase and nicking enzyme, EXPAR was specifically triggered, producing numerous primer replica in minutes, and greatly enhanced fluorescence of SYBR Green I. The proposed strategy has a good linear relationship with the logarithm of the MUC1 concentration ranging from 3 pM to 3 nM with a limit of detection of 1.63 pM (S/N = 3), which is two orders of magnitude lower than those of other methods. Owing to the specificity of immuno-reaction and EXPAR, the selectivity of the strategy is favorable, even if for the homologous protein. The proposed strategy was further applied for the MUC1 determination in human serum, and a satisfactory recovery range of 98.7%-105.3% was obtained. The strategy can be facilely extended to the ultrasensitive determination of various proteins.