Biology subjects

Deng, W.

Publications and source records attributed to Deng, W..

93 records · Page 6Linked to original sources

bioRxiv2018

Aberrant calcium signaling in astrocytes inhibits neuronal excitability in a human Down syndrome stem cell model

Down syndrome (DS) is a devastating genetic disorder causing severe cognitive impairment. The staggering array of effects associated with an extra copy of human chromosome 21 (HSA21) complicates mechanistic understanding of DS pathophysiology. We developed an in vitro system to examine the interplay of neurons and astrocytes in a fully recapitulated HSA21 trisomy model differentiated from DS patient-derived induced pluripotent stem cells (iPSCs). By combining calcium imaging with genetic approaches, we utilized this system to investigate the functional defects of DS astroglia and their effects on neuronal excitability. We found that, compared with control isogenic astroglia, DS astroglia exhibited more-frequent spontaneous calcium fluctuations, which reduced the excitability of co-cultured neurons. DS astrocytes exerted this effect on both DS and healthy neurons. Neuronal activity could be rescued by abolishing astrocytic spontaneous calcium activity either chemically by blocking adenosine-mediated astrocyte-neuron signaling or genetically by knockdown of inositol triphosphate (IP3) receptors or S100{beta}, a calcium binding protein coded on HSA21. Our results suggest a novel mechanism by which DS alters the function of astrocytes, which subsequently disturbs neuronal excitability. Furthermore, our study establishes an all-optical neurophysiological platform for studying human neuron-astrocyte interactions associated with neurological disorders.\n\nSignificant statementDown syndrome (DS) is the most common genetic disorder caused by trisomy of chromosome 21 (HSA21). Problems with cognitive impairment, have not been properly addressed due to the inability to fully recapitulate HSA21, which is further confounded by the snapshot views of morphological changes of brain cells in isolation obtained from current studies. The brain develops neural networks consisting of neurons and glial cells that work together. To understand how DS affects the neural networks, we used DS patient-derived stem cells and calcium imaging to investigate functional defects of DS astrocytes and their effects on neuronal excitability. Our study has significant implication in understanding functional defects during brain development underlying DS.

neuroscience↗

bioRxiv2017

GEM: A manifold learning based framework for reconstructing spatial organizations of chromosomes

Decoding the spatial organizations of chromosomes has crucial implications for studying eukaryotic gene regulation. Recently, Chromosomal conformation capture based technologies, such as Hi-C, have been widely used to uncover the interaction frequencies of genomic loci in high-throughput and genome-wide manner and provide new insights into the folding of three-dimensional (3D) genome structure. In this paper, we develop a novel manifold learning framework, called GEM (Genomic organization reconstructor based on conformational Energy and Manifold learning), to elucidate the underlying 3D spatial organizations of chromosomes from Hi-C data. Unlike previous chromatin structure reconstruction methods, which explicitly assume specific relationships between Hi-C interaction frequencies and spatial distances between distal genomic loci, GEM is able to reconstruct an ensemble of chromatin conformations by directly embedding the neigh-boring affinities from Hi-C space into 3D Euclidean space based on a manifold learning strategy that considers both the fitness of Hi-C data and the biophysical feasibility of the modeled structures, which are measured by the conformational energy derived from our current biophysical knowledge about the 3D polymer model. Extensive validation tests on both simulated interaction frequency data and experimental Hi-C data of yeast and human demonstrated that GEM not only greatly outperformed other state-of-art modeling methods but also reconstructed accurate chromatin structures that agreed well with the hold-out or independent Hi-C data and sparse geometric restraints derived from the previous fluorescence in situ hybridization (FISH) studies. In addition, as GEM can generate accurate spatial organizations of chromosomes by integrating both experimentally-derived spatial contacts and conformational energy, we for the first time extended our modeling method to recover long-range genomic interactions that are missing from the original Hi-C data. All these results indicated that GEM can provide a physically and physiologically valid 3D representations of the organizations of chromosomes and thus serve as an effective and useful genome structure reconstructor.

bioinformatics↗

bioRxiv2017

Quantifying Spontaneous Metastasis In A Syngeneic Mouse Melanoma Model Using Real Time PCR

Modeling metastasis in vivo with animals is a priority for both revealing mechanisms of tumor dissemination and developing therapeutic methods. While conventional intravenous injection of tumor cells provides an efficient and consistent system for studying tumor cell extravasation and colonization, studying spontaneous metastasis derived from orthotopic tumor sites has the advantage of modeling more aspects of the metastatic cascade, but is challenging as it is difficult to detect small numbers of metastatic cells. In this work, we developed an approach for quantifying spontaneous metastasis in the syngeneic mouse B16 system using real time PCR. We first transduced B16 cells with lentivirus expressing firefly luciferase Luc2 gene for bioluminescence imaging. Next, we developed a real time quantitative PCR (qPCR) method for the detection of luciferase-expressing, metastatic tumor cells in mouse lungs and other organs. To illustrate the approach, we quantified lung metastasis in both spontaneous and experimental scenarios using B16F0 and B16F10 cells in C57BL/6Ncrl and NOD-Scid Gamma (NSG) mice. We tracked B16 melanoma metastasis with both bioluminescence imaging and qPCR, which were found to be self-consistent. Using this assay, we can quantitatively detect one Luc2 positive tumor cells out of 104 tissue cells, which corresponds to a metastatic burden of 1.8x104 metastatic cells per whole mouse lung. More importantly, the qPCR method was at least a factor of 10 more sensitive in detecting metastatic cell dissemination and should be combined with bioluminescence imaging as a high-resolution, end-point method for final metastatic cell quantitation. Given the rapid growth of primary tumors in many mouse models, assays with improved sensitivity can provide better insight into biological mechanisms that underpin tumor metastasis.

cancer biology↗