Browsing by Author "Wang, Yinxue"

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    Aberrant Calcium Signaling in Astrocytes Inhibits Neuronal Excitability in a Human Down Syndrome Stem Cell Model
    Mizuno, Grace O.; Wang, Yinxue; Shi, Guilai; Wang, Yizhi; Sun, Junqing; Papadopoulos, Stelios; Broussard, Gerard J.; Unger, Elizabeth K.; Deng, Wenbin; Weick, Jason; Bhattacharyya, Anita; Chen, Chao-Yin; Yu, Guoqiang; Looger, Loren L.; Tian, Lin (Elsevier, 2018-07-10)
    Down syndrome (DS) is a genetic disorder that causes cognitive impairment. The staggering effects associated with an extra copy of human chromosome 21 (HSA21) complicates mechanistic understanding of DS pathophysiology. We examined the neuronastrocyte interplay in a fully recapitulated HSA21 trisomy cellular model differentiated from DS-patientderived induced pluripotent stem cells (iPSCs). By combining calciumimaging with genetic approaches, we discovered the functional defects of DS astroglia and their effects on neuronal excitability. Compared with control isogenic astroglia, DS astroglia exhibited more-frequent spontaneous calcium fluctuations, which reduced the excitability of co-cultured neurons. Furthermore, suppressed neuronal activity could be rescued by abolishing astrocytic spontaneous calcium activity either chemically by blocking adenosine-mediated signaling or genetically by knockdown of inositol triphosphate (IP3) receptors or S100B, a calcium binding protein coded on HSA21. Our results suggest a mechanism by which DS alters the function of astrocytes, which subsequently disturbs neuronal excitability.
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    Automated Functional Analysis of Astrocytes from Chronic Time-Lapse Calcium Imaging Data
    Wang, Yinxue; Shi, Guilai; Miller, David J.; Wang, Yizhi; Wang, Congchao; Broussard, Gerard J.; Wang, Yue; Tian, Lin; Yu, Goquiang (Frontiers, 2017-07-14)
    Recent discoveries that astrocytes exert proactive regulatory effects on neural information processing and that they are deeply involved in normal brain development and disease pathology have stimulated broad interest in understanding astrocyte functional roles in brain circuit. Measuring astrocyte functional status is now technically feasible, due to recent advances in modern microscopy and ultrasensitive cell-type specific genetically encoded Ca²⁺ indicators for chronic imaging. However, there is a big gap between the capability of generating large dataset via calcium imaging and the availability of sophisticated analytical tools for decoding the astrocyte function. Current practice is essentially manual, which not only limits analysis throughput but also risks introducing bias and missing important information latent in complex, dynamic big data. Here, we report a suite of computational tools, called Functional AStrocyte Phenotyping (FASP), for automatically quantifying the functional status of astrocytes. Considering the complex nature of Ca²⁺ signaling in astrocytes and low signal to noise ratio, FASP is designed with data-driven and probabilistic principles, to flexibly account for various patterns and to perform robustly with noisy data. In particular, FASP explicitly models signal propagation, which rules out the applicability of tools designed for other types of data. We demonstrate the effectiveness of FASP using extensive synthetic and real data sets. The findings by FASP were verified by manual inspection. FASP also detected signals that were missed by purely manual analysis but could be confirmed by more careful manual examination under the guidance of automatic analysis. All algorithms and the analysis pipeline are packaged into a plugin for Fiji (ImageJ), with the source code freely available online at https://github.com/VTcbil/FASP.
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    Automated Identification and Tracking of Motile Oligodendrocyte Precursor Cells (OPCs) from Time-lapse 3D Microscopic Imaging Data of Cell Clusters in vivo
    Wang, Yinxue (Virginia Tech, 2021-06-02)
    Advances in time-lapse 3D in vivo fluorescence microscopic imaging techniques enables the observation and investigation into the migration of Oligodendrocyte precursor cells (OPCs) and its role in the central nervous system. However, current practice of image-based OPC motility analysis heavily relies on manual labeling and tracking on 2D max projection of the 3D data, which suffers from massive human labor, subjective biases, weak reproducibility and especially information loss and distortion. Besides, due to the lack of OPC specific genetically encoded indicator, OPCs can only be identified from other oligodendrocyte lineage cells by their observed motion patterns. Automated analytical tools are needed for the identification and tracking of OPCs. In this dissertation work, we proposed an analytical framework, MicTracker (Migrating Cell Tracker), for the integrated task of identifying, segmenting and tracking migrating cells (OPCs) from in vivo time-lapse fluorescence imaging data of high-density cell clusters composed of cells with different modes of motions. As a component of the framework, we presented a novel strategy for cell segmentation with global temporal consistency enforced, tackling the challenges caused by highly clustered cell population and temporally inconsistently blurred boundaries between touching cells. We also designed a data association algorithm to address the violation of usual assumption of small displacements. Recognizing that the violation was in the mixed cell population composed of two cell groups while the assumption held within each group, we proposed to solve the seemingly impossible mission by de-mixing the two groups of cell motion modes without known labels. We demonstrated the effectiveness of MicTracker in solving our problem on in vivo real data.