Dr. Tan is a computational biologist who develops computational tools to quantitatively assess cell identity, improve stem cell engineering, and understand cancer heterogeneity. As a Ph.D. student, Dr. Tan routinely performs computational and quantitative analysis on scRNA-seq data, which has resulted in several publications. Currently, at her postdoctoral position, Dr. Tan integrated single-cell omics with multiplexed image data to understand high dimensional tissue architecture in cancer. Dr.Tan's long-term aims are to integrate multi-omics to understand how different cell types and their interactions contribute to development and disease.

Stanford Advisors

Lab Affiliations

All Publications

  • Computational Approaches for Connecting Maternal Stress to Preterm Birth. Clinics in perinatology Mirzaei, A., Hiller, B. C., Stelzer, I. A., Thiele, K., Tan, Y., Becker, M. 2024; 51 (2): 345-360


    Multiple studies have hinted at a complex connection between maternal stress and preterm birth (PTB). This article describes the potential of computational methods to provide new insights into this relationship. For this, we outline existing approaches for stress assessments and various data modalities available for profiling stress responses, and review studies that sought either to establish a connection between stress and PTB or to predict PTB based on stress-related factors. Finally, we summarize the challenges of computational methods, highlighting potential future research directions within this field.

    View details for DOI 10.1016/j.clp.2024.02.003

    View details for PubMedID 38705645

  • T cell-mediated curation and restructuring of tumor tissue coordinates an effective immune response. Cell reports Hickey, J. W., Haist, M., Horowitz, N., Caraccio, C., Tan, Y., Rech, A. J., Baertsch, M. A., Rovira-Clavé, X., Zhu, B., Vazquez, G., Barlow, G., Agmon, E., Goltsev, Y., Sunwoo, J. B., Covert, M., Nolan, G. P. 2023; 42 (12): 113494


    Antigen-specific T cells traffic to, are influenced by, and create unique cellular microenvironments. Here we characterize these microenvironments over time with multiplexed imaging in a melanoma model of adoptive T cell therapy and human patients with melanoma treated with checkpoint inhibitor therapy. Multicellular neighborhood analysis reveals dynamic immune cell infiltration and inflamed tumor cell neighborhoods associated with CD8+ T cells. T cell-focused analysis indicates T cells are found along a continuum of neighborhoods that reflect the progressive steps coordinating the anti-tumor immune response. More effective anti-tumor immune responses are characterized by inflamed tumor-T cell neighborhoods, flanked by dense immune infiltration neighborhoods. Conversely, ineffective T cell therapies express anti-inflammatory cytokines, resulting in regulatory neighborhoods, spatially disrupting productive T cell-immune and -tumor interactions. Our study provides in situ mechanistic insights into temporal tumor microenvironment changes, cell interactions critical for response, and spatial correlates of immunotherapy outcomes, informing cellular therapy evaluation and engineering.

    View details for DOI 10.1016/j.celrep.2023.113494

    View details for PubMedID 38085642

  • Treatment management for BRAF-mutant melanoma patients with tumor recurrence on adjuvant therapy: a multicenter study from the prospective skin cancer registry ADOREG. Journal for immunotherapy of cancer Haist, M., Stege, H., Rogall, F., Tan, Y., von Wasielewski, I., Klespe, K. C., Meier, F., Mohr, P., Kähler, K. C., Weichenthal, M., Hauschild, A., Schadendorf, D., Ugurel, S., Lodde, G., Zimmer, L., Gutzmer, R., Debus, D., Schilling, B., Kreuter, A., Ulrich, J., Meiss, F., Herbst, R., Forschner, A., Leiter, U., Pfoehler, C., Kaatz, M., Ziller, F., Hassel, J. C., Tronnier, M., Sachse, M., Dippel, E., Terheyden, P., Berking, C., Heppt, M. V., Kiecker, F., Haferkamp, S., Gebhardt, C., Simon, J. C., Grabbe, S., Loquai, C. 2023; 11 (9)


    Adjuvant therapy with immune-checkpoint inhibitors (CPI) or BRAF/MEK-directed targeted therapy (TT) improves recurrence-free survival (RFS) for patients with advanced, BRAFV600-mutant (BRAFmut) resected melanoma. However, 40% of these patients will develop distant metastases (DM) within 5 years, which require systemic therapy. Little data exist to guide the choice of upfront adjuvant therapy or treatment management upon DM. This study evaluated the efficacy of subsequent treatments following tumor recurrence upon upfront adjuvant therapy.For this multicenter cohort study, we identified 515 BRAFmut patients with resected stage III melanoma who were treated with PD-1 inhibitors (anti-PD1) or TT in the adjuvant setting. Disease characteristics, treatment regimens, details on tumor recurrence, subsequent treatment management, and survival outcomes were collected within the prospective, real-world skin cancer registry ADOReg. Primary endpoints included progression-free survival (PFS) following DM and best tumor response to first-line (1L) treatments.Among 515 eligible patients, 273 patients received adjuvant anti-PD1 and 242 adjuvant TT. At a median follow-up of 21 months, 54.6% of anti-PD1 patients and 36.4% of TT patients recurred, while 39.6% (anti-PD1) and 29.3% (TT) developed DM. Risk of recurrence was significantly reduced in patients treated with TT compared with anti-PD1 (adjusted HR 0.52; 95% CI 0.40 to 0.68, p<0.001). Likewise, median RFS was significantly longer in TT-treated patients (31 vs 17 months, p<0.001). Patients who received TT as second adjuvant treatment upon locoregional recurrence had a longer RFS2 as compared with adjuvant CPI (41 vs 6 months, p=0.009). Patients who recurred at distant sites following adjuvant TT showed favorable response rates (42.9%) after switching to 1L ipilimumab+nivolumab (ipi+nivo). Patients with DM during adjuvant anti-PD1 achieved response rates of 58.7% after switching to 1L TT and 35.3% for 1L ipi+nivo. Overall, median PFS was significantly longer in patients who switched treatments for stage IV disease (median PFS 9 vs 5 months, p=0.004).BRAFmut melanoma patients who developed DM upon upfront adjuvant therapy achieve favorable tumor control and prolonged PFS after switching treatment modalities in the first-line setting of stage IV disease. Patients with locoregional recurrence benefit from complete resection of recurrence followed by a second adjuvant treatment with TT.

    View details for DOI 10.1136/jitc-2023-007630

    View details for PubMedID 37730278

    View details for PubMedCentralID PMC10510881

  • Large-scale correlation network construction for unraveling the coordination of complex biological systems NATURE COMPUTATIONAL SCIENCE Becker, M., Nassar, H., Espinosa, C., Stelzer, I. A., Feyaerts, D., Berson, E., Bidoki, N. H., Chang, A. L., Saarunya, G., Culos, A., De Francesco, D., Fallahzadeh, R., Liu, Q., Kim, Y., Maric, I., Mataraso, S. J., Payrovnaziri, S., Phongpreecha, T., Ravindra, N. G., Stanley, N., Shome, S., Tan, Y., Thuraiappah, M., Xenochristou, M., Xue, L., Shaw, G., Stevenson, D., Angst, M. S., Gaudilliere, B., Aghaeepour, N. 2023
  • Large-scale correlation network construction for unraveling the coordination of complex biological systems. Nature computational science Becker, M., Nassar, H., Espinosa, C., Stelzer, I. A., Feyaerts, D., Berson, E., Bidoki, N. H., Chang, A. L., Saarunya, G., Culos, A., De Francesco, D., Fallahzadeh, R., Liu, Q., Kim, Y., Marić, I., Mataraso, S. J., Payrovnaziri, S. N., Phongpreecha, T., Ravindra, N. G., Stanley, N., Shome, S., Tan, Y., Thuraiappah, M., Xenochristou, M., Xue, L., Shaw, G., Stevenson, D., Angst, M. S., Gaudilliere, B., Aghaeepour, N. 2023; 3 (4): 346-359


    Advanced measurement and data storage technologies have enabled high-dimensional profiling of complex biological systems. For this, modern multiomics studies regularly produce datasets with hundreds of thousands of measurements per sample, enabling a new era of precision medicine. Correlation analysis is an important first step to gain deeper insights into the coordination and underlying processes of such complex systems. However, the construction of large correlation networks in modern high-dimensional datasets remains a major computational challenge owing to rapidly growing runtime and memory requirements. Here we address this challenge by introducing CorALS (Correlation Analysis of Large-scale (biological) Systems), an open-source framework for the construction and analysis of large-scale parametric as well as non-parametric correlation networks for high-dimensional biological data. It features off-the-shelf algorithms suitable for both personal and high-performance computers, enabling workflows and downstream analysis approaches. We illustrate the broad scope and potential of CorALS by exploring perspectives on complex biological processes in large-scale multiomics and single-cell studies.

    View details for DOI 10.1038/s43588-023-00429-y

    View details for PubMedID 38116462

    View details for PubMedCentralID PMC10727505

  • Annotation of spatially resolved single-cell data with STELLAR. Nature methods Brbic, M., Cao, K., Hickey, J. W., Tan, Y., Snyder, M. P., Nolan, G. P., Leskovec, J. 2022


    Accurate cell-type annotation from spatially resolved single cells is crucial to understand functional spatial biology that is the basis of tissue organization. However, current computational methods for annotating spatially resolved single-cell data are typically based on techniques established for dissociated single-cell technologies and thus do not take spatial organization into account. Here we present STELLAR, a geometric deep learning method for cell-type discovery and identification in spatially resolved single-cell datasets. STELLAR automatically assigns cells to cell types present in the annotated reference dataset and discovers novel cell types and cell states. STELLAR transfers annotations across different dissection regions, different tissues and different donors, and learns cell representations that capture higher-order tissue structures. We successfully applied STELLAR to CODEX multiplexed fluorescent microscopy data and multiplexed RNA imaging datasets. Within the Human BioMolecular Atlas Program, STELLAR has annotated 2.6million spatially resolved single cells with dramatic time savings.

    View details for DOI 10.1038/s41592-022-01651-8

    View details for PubMedID 36280720

  • Revealing the impact of lifestyle stressors on the risk of adverse pregnancy outcomes with multitask machine learning. Frontiers in pediatrics Becker, M., Dai, J., Chang, A. L., Feyaerts, D., Stelzer, I. A., Zhang, M., Berson, E., Saarunya, G., De Francesco, D., Espinosa, C., Kim, Y., Maric, I., Mataraso, S., Payrovnaziri, S. N., Phongpreecha, T., Ravindra, N. G., Shome, S., Tan, Y., Thuraiappah, M., Xue, L., Mayo, J. A., Quaintance, C. C., Laborde, A., King, L. S., Dhabhar, F. S., Gotlib, I. H., Wong, R. J., Angst, M. S., Shaw, G. M., Stevenson, D. K., Gaudilliere, B., Aghaeepour, N. 2022; 10: 933266


    Psychosocial and stress-related factors (PSFs), defined as internal or external stimuli that induce biological changes, are potentially modifiable factors and accessible targets for interventions that are associated with adverse pregnancy outcomes (APOs). Although individual APOs have been shown to be connected to PSFs, they are biologically interconnected, relatively infrequent, and therefore challenging to model. In this context, multi-task machine learning (MML) is an ideal tool for exploring the interconnectedness of APOs on the one hand and building on joint combinatorial outcomes to increase predictive power on the other hand. Additionally, by integrating single cell immunological profiling of underlying biological processes, the effects of stress-based therapeutics may be measurable, facilitating the development of precision medicine approaches.Objectives: The primary objectives were to jointly model multiple APOs and their connection to stress early in pregnancy, and to explore the underlying biology to guide development of accessible and measurable interventions.Materials and Methods: In a prospective cohort study, PSFs were assessed during the first trimester with an extensive self-filled questionnaire for 200 women. We used MML to simultaneously model, and predict APOs (severe preeclampsia, superimposed preeclampsia, gestational diabetes and early gestational age) as well as several risk factors (BMI, diabetes, hypertension) for these patients based on PSFs. Strongly interrelated stressors were categorized to identify potential therapeutic targets. Furthermore, for a subset of 14 women, we modeled the connection of PSFs to the maternal immune system to APOs by building corresponding ML models based on an extensive single cell immune dataset generated by mass cytometry time of flight (CyTOF).Results: Jointly modeling APOs in a MML setting significantly increased modeling capabilities and yielded a highly predictive integrated model of APOs underscoring their interconnectedness. Most APOs were associated with mental health, life stress, and perceived health risks. Biologically, stressors were associated with specific immune characteristics revolving around CD4/CD8 T cells. Immune characteristics predicted based on stress were in turn found to be associated with APOs.Conclusions: Elucidating connections among stress, multiple APOs simultaneously, and immune characteristics has the potential to facilitate the implementation of ML-based, individualized, integrative models of pregnancy in clinical decision making. The modifiable nature of stressors may enable the development of accessible interventions, with success tracked through immune characteristics.

    View details for DOI 10.3389/fped.2022.933266

    View details for PubMedID 36582513

  • Gene Regulatory Network Analysis and Engineering Directs Development and Vascularization of Multilineage Human Liver Organoids CELL SYSTEMS Velazquez, J. J., LeGraw, R., Moghadam, F., Tan, Y., Kilbourne, J., Maggiore, J. C., Hislop, J., Liu, S., Cats, D., Lopes, S., Plaisier, C., Cahan, P., Kiani, S., Ebrahimkhani, M. R. 2021; 12 (1): 41-+


    Pluripotent stem cell (PSC)-derived organoids have emerged as novel multicellular models of human tissue development but display immature phenotypes, aberrant tissue fates, and a limited subset of cells. Here, we demonstrate that integrated analysis and engineering of gene regulatory networks (GRNs) in PSC-derived multilineage human liver organoids direct maturation and vascular morphogenesis in vitro. Overexpression of PROX1 and ATF5, combined with targeted CRISPR-based transcriptional activation of endogenous CYP3A4, reprograms tissue GRNs and improves native liver functions, such as FXR signaling, CYP3A4 enzymatic activity, and stromal cell reactivity. The engineered tissues possess superior liver identity when compared with other PSC-derived liver organoids and show the presence of hepatocyte, biliary, endothelial, and stellate-like cell populations in single-cell RNA-seq analysis. Finally, they show hepatic functions when studied in vivo. Collectively, our approach provides an experimental framework to direct organogenesis in vitro by systematically probing molecular pathways and transcriptional networks that promote tissue development.

    View details for DOI 10.1016/j.cels.2020.11.002

    View details for Web of Science ID 000610099400004

    View details for PubMedID 33290741

    View details for PubMedCentralID PMC8164844

  • Strategies for Accurate Cell Type Identification in CODEX Multiplexed Imaging Data. Frontiers in immunology Hickey, J. W., Tan, Y., Nolan, G. P., Goltsev, Y. 2021; 12: 727626


    Multiplexed imaging is a recently developed and powerful single-cell biology research tool. However, it presents new sources of technical noise that are distinct from other types of single-cell data, necessitating new practices for single-cell multiplexed imaging processing and analysis, particularly regarding cell-type identification. Here we created single-cell multiplexed imaging datasets by performing CODEX on four sections of the human colon (ascending, transverse, descending, and sigmoid) using a panel of 47 oligonucleotide-barcoded antibodies. After cell segmentation, we implemented five different normalization techniques crossed with four unsupervised clustering algorithms, resulting in 20 unique cell-type annotations for the same dataset. We generated two standard annotations: hand-gated cell types and cell types produced by over-clustering with spatial verification. We then compared these annotations at four levels of cell-type granularity. First, increasing cell-type granularity led to decreased labeling accuracy; therefore, subtle phenotype annotations should be avoided at the clustering step. Second, accuracy in cell-type identification varied more with normalization choice than with clustering algorithm. Third, unsupervised clustering better accounted for segmentation noise during cell-type annotation than hand-gating. Fourth, Z-score normalization was generally effective in mitigating the effects of noise from single-cell multiplexed imaging. Variation in cell-type identification will lead to significant differential spatial results such as cellular neighborhood analysis; consequently, we also make recommendations for accurately assigning cell-type labels to CODEX multiplexed imaging.

    View details for DOI 10.3389/fimmu.2021.727626

    View details for PubMedID 34484237

  • Transcriptome Dynamics of Hematopoietic Stem Cell Formation Revealed Using a Combinatorial Runx1 and Ly6a Reporter System STEM CELL REPORTS Chen, M. J., da Rocha, E., Cahan, P., Kubaczka, C., Hunter, P., Sousa, P., Mullin, N. K., Fujiwara, Y., Minh Nguyen, Tan, Y., Zhou, Y., North, T. E., Zon, L., Daley, G. Q., Schlaeger, T. M. 2020; 14 (5): 956-971


    Studies of hematopoietic stem cell (HSC) development from pre-HSC-producing hemogenic endothelial cells (HECs) are hampered by the rarity of these cells and the presence of other cell types with overlapping marker expression profiles. We generated a Tg(Runx1-mKO2; Ly6a-GFP) dual reporter mouse to visualize hematopoietic commitment and study pre-HSC emergence and maturation. Runx1-mKO2 marked all intra-arterial HECs and hematopoietic cluster cells (HCCs), including pre-HSCs, myeloid- and lymphoid progenitors, and HSCs themselves. However, HSC and lymphoid potential were almost exclusively found in reporter double-positive (DP) cells. Robust HSC activity was first detected in DP cells of the placenta, reflecting the importance of this niche for (pre-)HSC maturation and expansion before the fetal liver stage. A time course analysis by single-cell RNA sequencing revealed that as pre-HSCs mature into fetal liver stage HSCs, they show signs of interferon exposure, exhibit signatures of multi-lineage differentiation gene expression, and develop a prolonged cell cycle reminiscent of quiescent adult HSCs.

    View details for DOI 10.1016/j.stemcr.2020.03.020

    View details for Web of Science ID 000533148900015

    View details for PubMedID 32302558

    View details for PubMedCentralID PMC7220988

  • Ligustrazine Prevents Intervertebral Disc Degeneration via Suppression of Aberrant TGF beta Activation in Nucleus Pulposus Cells BIOMED RESEARCH INTERNATIONAL Liu, S., Cheng, Y., Tan, Y., Dong, J., Bian, Q. 2019; 2019: 5601734


    Aberrant transforming growth factor β (TGFβ) activation is detrimental to both nucleus pulposus (NP) cells and cartilage endplates (CEPs), which can lead to intervertebral disc degeneration (IDD). Ligustrazine (LIG) reduces the expression of inflammatory factors and TGFβ1 in hypertrophic CEP to prevent IDD. In this study, we investigate the effects of LIG on NP cells and the TGFβ signaling.LIG was injected to the lumbar spinal instability (LSI) mouse model. The effect of LIG was evaluated by intervertebral disc (IVD) score in the LSI mouse model. The expression of activated TGFβ was examined using immunostaining with pSmad2/3 antibody. The upright posture (UP) rat model was also treated and evaluated in the same manner to assess the effect of LIG. In ex vivo study, IVDs from four-week old mice were isolated and treated with 10-5, 10-6, and 10-7 M of LIG. We used western blot to detect activated TGFβ expression. TGFβ-treated human nucleus pulposus cells (HNPCs) were cotreated with optimized dose of LIG in vitro. Immunofluorescence staining was performed to determine pSmad2/3, connective tissue growth factor (CCN2), and aggrecan (ACAN) expression levels.IVD score and the percentage of pSmad2/3+ NP cells were low in LIG-treated LSI mice in comparison with LSI mice, but close to the levels in the Sham group. Similarly, LIG reduced the overexpression of TGFβ1 in NP cells. The inhibitory effect of LIG was dose dependent. A dose of 10-5 M LIG not only strongly attenuated Smad2/3 phosphorylation in TGFβ-treated IVD ex vivo but also suppressed pSmad2/3, CCN2, and ACAN expression in TGFβ-treated NP cells in vitro.LIG prevents IDD via suppression of TGFβ overactivation in NP cells.

    View details for DOI 10.1155/2019/5601734

    View details for Web of Science ID 000503421400003

    View details for PubMedID 31886227

    View details for PubMedCentralID PMC6914881

  • SingleCellNet: A Computational Tool to Classify Single Cell RNA-Seq Data Across Platforms and Across Species CELL SYSTEMS Tan, Y., Cahan, P. 2019; 9 (2): 207-+


    Single-cell RNA-seq has emerged as a powerful tool in diverse applications, from determining the cell-type composition of tissues to uncovering regulators of developmental programs. A near-universal step in the analysis of single-cell RNA-seq data is to hypothesize the identity of each cell. Often, this is achieved by searching for combinations of genes that have previously been implicated as being cell-type specific, an approach that is not quantitative and does not explicitly take advantage of other single-cell RNA-seq studies. Here, we describe our tool, SingleCellNet, which addresses these issues and enables the classification of query single-cell RNA-seq data in comparison to reference single-cell RNA-seq data. SingleCellNet compares favorably to other methods in sensitivity and specificity, and it is able to classify across platforms and species. We highlight SingleCellNet's utility by classifying previously undetermined cells, and by assessing the outcome of a cell fate engineering experiment.

    View details for DOI 10.1016/j.cels.2019.06.004

    View details for Web of Science ID 000483697600008

    View details for PubMedID 31377170

    View details for PubMedCentralID PMC6715530

  • SCD1 and SCD2 Form a Complex That Functions with the Exocyst and RabE1 in Exocytosis and Cytokinesis PLANT CELL Mayers, J., Hu, T., Wang, C., Cardenas, J. J., Tan, Y., Pan, J., Bednarek, S. Y. 2017; 29 (10): 2610-2625


    Although exocytosis is critical for the proper trafficking of materials to the plasma membrane, relatively little is known about the mechanistic details of post-Golgi trafficking in plants. Here, we demonstrate that the DENN (Differentially Expressed in Normal and Neoplastic cells) domain protein STOMATAL CYTOKINESIS DEFECTIVE1 (SCD1) and SCD2 form a previously unknown protein complex, the SCD complex, that functionally interacts with subunits of the exocyst complex and the RabE1 family of GTPases in Arabidopsis thaliana Consistent with a role in post-Golgi trafficking, scd1 and scd2 mutants display defects in exocytosis and recycling of PIN2-GFP. Perturbation of exocytosis using the small molecule Endosidin2 results in growth inhibition and PIN2-GFP trafficking defects in scd1 and scd2 mutants. In addition to the exocyst, the SCD complex binds in a nucleotide state-specific manner with Sec4p/Rab8-related RabE1 GTPases and overexpression of wild-type RabE1 rescues scd1 temperature-sensitive mutants. Furthermore, SCD1 colocalizes with the exocyst subunit, SEC15B, and RabE1 at the cell plate and in distinct punctae at or near the plasma membrane. Our findings reveal a mechanism for plant exocytosis, through the identification and characterization of a protein interaction network that includes the SCD complex, RabE1, and the exocyst.

    View details for DOI 10.1105/tpc.17.00409

    View details for Web of Science ID 000414861100025

    View details for PubMedID 28970336

    View details for PubMedCentralID PMC5774579

  • Assessment of engineered cells using CellNet and RNA-seq NATURE PROTOCOLS Radley, A. H., Schwab, R. M., Tan, Y., Kim, J., Lo, E. W., Cahan, P. 2017; 12 (5): 1089-1102


    CellNet is a computational platform designed to assess cell populations engineered by either directed differentiation of pluripotent stem cells (PSCs) or direct conversion, and to suggest specific hypotheses to improve cell fate engineering protocols. CellNet takes as input gene expression data and compares them with large data sets of normal expression profiles compiled from public sources, in regard to the extent to which cell- and tissue-specific gene regulatory networks are established. CellNet was originally designed to work with human or mouse microarray expression data for 21 cell or tissue (C/T) types. Here we describe how to apply CellNet to RNA-seq data and how to build a completely new CellNet platform applicable to, for example, other species or additional cell and tissue types. Once the raw data have been preprocessed, running CellNet takes only several minutes, whereas the time required to create a completely new CellNet is several hours.

    View details for DOI 10.1038/nprot.2017.022

    View details for Web of Science ID 000400371100009

    View details for PubMedID 28448485

    View details for PubMedCentralID PMC5765439

  • Understanding development and stem cells using single cell-based analyses of gene expression DEVELOPMENT Kumar, P., Tan, Y., Cahan, P. 2017; 144 (1): 17-32


    In recent years, genome-wide profiling approaches have begun to uncover the molecular programs that drive developmental processes. In particular, technical advances that enable genome-wide profiling of thousands of individual cells have provided the tantalizing prospect of cataloging cell type diversity and developmental dynamics in a quantitative and comprehensive manner. Here, we review how single-cell RNA sequencing has provided key insights into mammalian developmental and stem cell biology, emphasizing the analytical approaches that are specific to studying gene expression in single cells.

    View details for DOI 10.1242/dev.133058

    View details for Web of Science ID 000393454900005

    View details for PubMedID 28049689

    View details for PubMedCentralID PMC5278625

  • MONENSIN SENSITIVITY1 (MON1)/CALCIUM CAFFEINE ZINC SENSITIVITY1 (CCZ1)-Mediated Rab7 Activation Regulates Tapetal Programmed Cell Death and Pollen Development PLANT PHYSIOLOGY Cui, Y., Zhao, Q., Xie, H., Wong, W., Wang, X., Gao, C., Ding, Y., Tan, Y., Ueda, T., Zhang, Y., Jiang, L. 2017; 173 (1): 206-218


    Programmed cell death (PCD)-triggered degradation of plant tapetum is essential for microspore development and pollen coat formation; however, little is known about the cellular mechanism regulating tapetal PCD Here, we demonstrate that Rab7-mediated vacuolar transport of tapetum degradation-related cysteine proteases is crucial for tapetal PCD and pollen development in Arabidopsis (Arabidopsis thaliana), with the following evidence: (1) The monensin sensitivity1 (mon1) mutants, which are defective in Rab7 activation, showed impaired male fertility due to a combined defect in both tapetum and male gametophyte development. (2) In anthers, MON1 showed preferential high level expression in tapetal cell layers and pollen. (3) The mon1 mutants exhibited delayed tapetum degeneration and tapetal PCD, resulting in abnormal pollen coat formation and decreased male fertility. (4) MON1/CALCIUM CAFFEINE ZINC SENSITIVITY1 (CCZ1)-mediated Rab7 activation was indispensable for vacuolar trafficking of tapetum degradation-related cysteine proteases, supporting that PCD-triggered tapetum degeneration requires Rab7-mediated vacuolar trafficking of these cysteine proteases. (5) MON1 mutations also resulted in defective pollen germination and tube growth. Taken together, tapetal PCD and pollen development require successful MON1/CCZ1-mediated vacuolar transport in Arabidopsis.

    View details for DOI 10.1104/pp.16.00988

    View details for Web of Science ID 000394135800018

    View details for PubMedID 27799422

    View details for PubMedCentralID PMC5210713

  • MON1/CCZ1-mediated Rab7 activation regulates tapetal PCD and pollen development in Arabidopsis Plant Physiology Cui, Y. 2017
  • Valproate-Induced Neurodevelopmental Deficits in Xenopus laevis Tadpoles JOURNAL OF NEUROSCIENCE James, E. J., Gu, J., Ramirez-Vizcarrondo, C. M., Hasan, M., Truszkowski, T. S., Tan, Y., Oupravanh, P. M., Khakhalin, A. S., Aizenman, C. D. 2015; 35 (7): 3218-3229


    Autism spectrum disorder (ASD) is increasingly thought to result from low-level deficits in synaptic development and neural circuit formation that cascade into more complex cognitive symptoms. However, the link between synaptic dysfunction and behavior is not well understood. By comparing the effects of abnormal circuit formation and behavioral outcomes across different species, it should be possible to pinpoint the conserved fundamental processes that result in disease. Here we use a novel model for neurodevelopmental disorders in which we expose Xenopus laevis tadpoles to valproic acid (VPA) during a critical time point in brain development at which neurogenesis and neural circuit formation required for sensory processing are occurring. VPA is a commonly prescribed antiepileptic drug with known teratogenic effects. In utero exposure to VPA in humans or rodents results in a higher incidence of ASD or ASD-like behavior later in life. We find that tadpoles exposed to VPA have abnormal sensorimotor and schooling behavior that is accompanied by hyperconnected neural networks in the optic tectum, increased excitatory and inhibitory synaptic drive, elevated levels of spontaneous synaptic activity, and decreased neuronal intrinsic excitability. Consistent with these findings, VPA-treated tadpoles also have increased seizure susceptibility and decreased acoustic startle habituation. These findings indicate that the effects of VPA are remarkably conserved across vertebrate species and that changes in neural circuitry resulting from abnormal developmental pruning can cascade into higher-level behavioral deficits.

    View details for DOI 10.1523/JNEUROSCI.4050-14.2015

    View details for Web of Science ID 000349992800034

    View details for PubMedID 25698756

    View details for PubMedCentralID PMC4331635