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High-throughput intracellular biopsy of microRNAs for dissecting the temporal dynamics of cellular heterogeneity.

ABSTRACT: The capability to analyze small RNAs responsible for post-transcriptional regulation of genes expression is essential for characterizing cellular phenotypes. Here, we describe an intracellular biopsy technique (inCell-Biopsy) for fast, multiplexed, and highly sensitive profiling of microRNAs (miRNAs). The technique uses an array of diamond nanoneedles that are functionalized with size-dependent RNA binding proteins, working as "fishing rods" to directly pull miRNAs out of cytoplasm while keeping the cells alive, thus enabling quasi-single-cell miRNA analysis. Each nanoneedle works as a reaction chamber for parallel in situ amplification, visualization, and quantification of miRNAs as low as femtomolar, which is sufficient to detect miRNAs of a single-copy intracellular abundance with specificity to single-nucleotide variation. Using inCell-Biopsy, we analyze the temporal miRNA transcriptome over the differentiation of embryonic stem cells (ESCs). The combinatorial miRNA expression patterns derived by inCell-Biopsy identify emerging cell subpopulations differentiated from ESCs and reveal the dynamic evolution of cellular heterogeneity.

SUBMITTER: Wang Z

PROVIDER: S-EPMC7286670 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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High-throughput intracellular biopsy of microRNAs for dissecting the temporal dynamics of cellular heterogeneity.

Wang Zixun Z Qi Lin L Yang Yang Y Lu Mingxing M Xie Kai K Zhao Xi X Cheung Elvis Hung Chi EHC Wang Yuan Y Jiang Xuezhen X Zhang Wenjun W Huang Linfeng L Wang Xin X Shi Peng P

Science advances 20200610 24

The capability to analyze small RNAs responsible for post-transcriptional regulation of genes expression is essential for characterizing cellular phenotypes. Here, we describe an intracellular biopsy technique (inCell-Biopsy) for fast, multiplexed, and highly sensitive profiling of microRNAs (miRNAs). The technique uses an array of diamond nanoneedles that are functionalized with size-dependent RNA binding proteins, working as "fishing rods" to directly pull miRNAs out of cytoplasm while keeping ...[more]

PMID: 32577522

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Project description:ObjectiveHigh-throughput electronic phenotyping algorithms can accelerate translational research using data from electronic health record (EHR) systems. The temporal information buried in EHRs is often underutilized in developing computational phenotypic definitions. This study aims to develop a high-throughput phenotyping method, leveraging temporal sequential patterns from EHRs.Materials and methodsWe develop a representation mining algorithm to extract 5 classes of representations from EHR diagnosis and medication records: the aggregated vector of the records (aggregated vector representation), the standard sequential patterns (sequential pattern mining), the transitive sequential patterns (transitive sequential pattern mining), and 2 hybrid classes. Using EHR data on 10 phenotypes from the Mass General Brigham Biobank, we train and validate phenotyping algorithms.ResultsPhenotyping with temporal sequences resulted in a superior classification performance across all 10 phenotypes compared with the standard representations in electronic phenotyping. The high-throughput algorithm's classification performance was superior or similar to the performance of previously published electronic phenotyping algorithms. We characterize and evaluate the top transitive sequences of diagnosis records paired with the records of risk factors, symptoms, complications, medications, or vaccinations.DiscussionThe proposed high-throughput phenotyping approach enables seamless discovery of sequential record combinations that may be difficult to assume from raw EHR data. Transitive sequences offer more accurate characterization of the phenotype, compared with its individual components, and reflect the actual lived experiences of the patients with that particular disease.ConclusionSequential data representations provide a precise mechanism for incorporating raw EHR records into downstream machine learning. Our approach starts with user interpretability and works backward to the technology.

Project description:Reoviruses are non-enveloped viruses with wide host range, can cause serious infections in animals, plants and microorganism, e.g., aquareovirus, which is capable of causing serious haemorrhagic in aquatic animals. To date, the entry process of aquareovirus infection remains obscure. Real-time single-virus tracking are effective tools for exploring the details in viral infection process, which are crucial for understanding the pathogenic mechanism. Here, we used quantum dots-based single particle tracking technology combined with biochemical assays and ultrastructural observation to reveal unobservable infection steps and map dynamic interactions between a reovirus, Scophthalmus maximus reovirus (SMReV), and its host cell in real time. The results showed that the single membrane-bound reovirus particle can enter into the cell within several seconds through nascent clathrin-caoted pits, and most of the particles could internalize into cytoplasm within 30 min post-infection. The specific inhibitors analysis also showed that entry of SMREV depended on clathrin-mediated endocytosis rather than cavolin-mediated endocytosis. The motion analysis of internalized single particle indicated that the reovirus initially experienced slow and directed motion in the actin-enriched cell periphery, while it underwent relatively faster and directed movement toward the cell interior, suggesting that transport of SMReV was dependent on the cytoskeleton. Further, dual-labeling of virus and cytoskeleton and inhibitor analysis both demonstrated that transport of internalized SMReV was firstly dependent on actin filaments at the cell periphery, and then on microtubules toward the cell interior. Then visualization of SMReV trafficking in the endosomes revealed that the internalized reovirus particles were sorted from early endosomes to late endosomes, then part of them were delivered to lysosome. This study for the first time revealed the entry pathway, intracellular dynamic and the infection fate of fish reovirus in host cell in real time and in situ, which provided new insights into the infection mechanism of non-enveloped viruses.

Dataset Information

High-throughput intracellular biopsy of microRNAs for dissecting the temporal dynamics of cellular heterogeneity.

Publications

High-throughput intracellular biopsy of microRNAs for dissecting the temporal dynamics of cellular heterogeneity.

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