Fluorescence activation imaging of localization, distribution, and level of miRNA in various organelles inside cells

iLoc-miRNA: extracellular/intracellular miRNA prediction using deep BiLSTM with attention mechanism

The location of microRNAs (miRNAs) in cells determines their function in regulation activity. Studies have shown that miRNAs are stable in the extracellular environment that mediates cell-to-cell communication and are located in the intracellular region that responds to cellular stress and environmental stimuli. Though in situ detection techniques of miRNAs have made great contributions to the study of the localization and distribution of miRNAs, miRNA subcellular localization and their role are still in progress. Recently, some machine learning-based algorithms have been designed for miRNA subcellular location prediction, but their performance is still far from satisfactory. Here, we present a new data partitioning strategy that categorizes functionally similar locations for the precise and instructive prediction of miRNA subcellular location in Homo sapiens. To characterize the localization signals, we adopted one-hot encoding with post padding to represent the whole miRNA sequences, and proposed a deep bidirectional long short-term memory with the multi-head self-attention algorithm to model. The algorithm showed high selectivity in distinguishing extracellular miRNAs from intracellular miRNAs. Moreover, a series of motif analyses were performed to explore the mechanism of miRNA subcellular localization. To improve the convenience of the model, a user-friendly web server named iLoc-miRNA was established (http://iLoc-miRNA.lin-group.cn/).

Transboundary Pathogenic microRNA Analysis Framework for Crop Fungi Driven by Biological Big Data and Artificial Intelligence Model

Plant fungal diseases have been affecting the world's agricultural production and economic levels for a long time, such as rice blast, gray tomato mold, potato late blight etc. Recent studies have shown that fungal pathogens transmit microRNA as an effector to host plants for infection. However, bioassay-based verification analysis is time-consuming and challenging, and it is difficult to analyze from a global perspective. With the accumulation of fungal and plant-related data, data analysis methods can be used to analyze pathogenic fungal microRNA further. Based on the microRNA expression data of fungal pathogens infecting plants before and after, this paper discusses the selection strategy of sample data, the extraction strategy of pathogenic fungal microRNA, the prediction strategy of a fungal pathogenic microRNA target gene, the bicluster-based fungal pathogenic microRNA functional analysis strategy and experimental verification methods. A general analysis pipeline based on machine learning and bicluster-based function module was proposed for plant-fungal pathogenic microRNA.The pipeline proposed in this paper is applied to the infection process of Magnaporthe oryzae and the infection process of potato late blight. It has been verified to prove the feasibility of the pipeline. It can be extended to other relevant crop pathogen research, providing a new idea for fungal research on plant diseases. It can be used as a reference for understanding the interaction between fungi and plants.

Catalytic hairpin assembly indirectly covalent on Fe3O4@C nanoparticles with signal amplification for intracellular detection of miRNA

Fluorescence resonance energy transfer, a promising method for in situ imaging of miRNA in living cells, has intrinsic limitation on sensitivity and selectivity. Herein, a fluorescent amplification strategy based on catalyzed hairpin assembly indirectly covalent on Fe₃O₄@C nanoparticles via short single-stranded DNA was investigated for cellular miRNA detection in living cells, integrating non-enzyme target-active releasing for amplifying the signal output, highly quenching efficiency of Fe₃O₄@C nanoparticles with low background, ssDNA assisted fluorescent group-fueled chain releasing from Fe₃O₄@C nanoparticles with enhanced fluorescence response. The designed platform exhibits highly sensitive in a wide linear concentration range of 0.450 pM-190 pM and is highly specific for miRNA-20a detection with the ability of discriminating one mistake base. Additionally, the CHA-Fe₃O₄@C was successfully applied in imaging visualization of miRNA-20a in the living cell. The strategy provides a promising bioassay approach for clinical research.

Neurodevelopmental toxicity assessments of alkyl phenanthrene and Dechlorane Plus co-exposure in zebrafish

Alkyl phenanthrene (A-Phen) and Dechlorane Plus (DP) are ubiquitous environmental pollutants that widely co-exist in the environment. It has been established that both A-Phen and DP elicit neurotoxicity, but the potential interactive toxicity of these contaminants is not well-known. To determine whether a mixture of A-Phen and DP would exhibit interactive effects on neurodevelopment, we co-exposed 3-methylphenanthrene (3-MP), a representative of A-Phen, with DP. Our results illustrated that exposure to 5 or 20 μg/L 3-MP alone or in combination with 60 μg/L DP caused neurobehavioral anomalies in zebrafish. In accordance with the behavioral deficits, 3-MP alone or co-exposed with DP significantly decreased axonal growth of secondary motoneurons, altered intracellular Ca²⁺ homeostasis and induced cell apoptosis in the muscle of zebrafish. Additionally, 3-MP alone or co-exposed with DP significantly increased reactive oxygen species (ROS) and the mRNA levels of apoptosis-related genes. These findings indicate that 3-MP alone or co-exposed with DP induces neurobehavioral deficits through the combined effects on neuronal connectivity and muscle function. Chemical analysis revealed significant increases in 3-MP and DP bioaccumulation in zebrafish co-exposed with 3-MP and DP. Elevated bioaccumulation resulting from mixture exposure may represent a significant contribution of the synergistic effects observed in combined chemical exposure.

miR-150-5p promotes the proliferation and epithelial-mesenchymal transition of cervical carcinoma cells via targeting SRCIN1

Cervical carcinoma is one of the most universal cancers among women. Recent researches have reported that microRNA-150-5p (miR-150-5p) is up-regulated in diverse carcinomas containing cervical carcinoma. The purpose of this study was to further investigate the potential role of miR-150-5p in the progress of cervical carcinoma cells including proliferation and epithelial-mesenchymal transition (EMT).The ability of miR-150-5p to promote carcinogenesis was analyzed using quantitative reverse transcription polymerase chain reaction (qRT-PCR) and western blot assays, respectively. Bioinformatics analyses predicted and identified whether SRC kinase signaling inhibitor 1 (SRCIN1) was served as a potential target of miR-150-5p. C-33A and HeLa cells were utilized to determine the function of miR-150-5p through targeting SRCIN1. Among the aberrantly expressed miRNAs, miR-150-5p was significantly revealed differential expression in cervical carcinoma cell lines and was closely relevant to cell growth regulation. Furthermore, we found that SRCIN1 overexpression could obviously inhibit the proliferation and EMT of cervical cancer cells triggered by miR-150-5p mimics as well as accelerated the apoptosis of cervical carcinoma cells. In conclusion, our data demonstrated that miR-150-5p could promote the proliferation and EMT of cervical carcinoma cells via targeting SRCIN1. Thus, miR-150-5p may hold a promise as a prognostic biomarker and potential therapeutic target for cervical carcinoma.