Biology subjects

Jia, D.

Publications and source records attributed to Jia, D..

11 recordsLinked to original sources

bioRxiv2018

Testing the Gene Expression Classification of the EMT Spectrum

The epithelial-mesenchymal transition (EMT) plays a central role in cancer metastasis and drug resistance - two persistent clinical challenges. Epithelial cells can undergo a partial or full EMT, attaining either a hybrid epithelial/mesenchymal (E/M) or mesenchymal phenotype, respectively. Recent studies have emphasized that hybrid E/M cells may be more aggressive than their mesenchymal counterparts. However, mechanisms driving hybrid E/M phenotypes remain largely elusive. Here, to better characterize the hybrid E/M phenotype(s) and tumor aggressiveness, we integrate two computational methods - (a) RACIPE - to identify the robust gene expression patterns emerging from the dynamics of a given gene regulatory network, and (b) EMT scoring metric - to calculate the probability that a given gene expression profile displays a hybrid E/M phenotype. We apply the EMT scoring metric to RACIPE-generated gene expression data generated from a core EMT regulatory network and classify the gene expression profiles into relevant categories (epithelial, hybrid E/M, mesenchymal). This categorization is broadly consistent with hierarchical clustering readouts of RACIPE-generated gene expression data. We show that the EMT scoring metric can be used to distinguish between samples composed of exclusively hybrid E/M cells and those containing mixtures of epithelial and mesenchymal subpopulations using the RACIPE-generated gene expression data.

systems biology↗

bioRxiv2018

JNK-IN-8, a c-Jun N-terminal kinase inhibitor, improves functional recovery through suppressing neuroinflammation in ischemic stroke

c-Jun N-terminal kinase (JNK), a mitogen activated protein kinase, is activated in ischemia brain injury and plays an important role in cerebral ischemic injury. Emerging studies demonstrated that JNK-IN-8 (a specific JNK inhibitor) regulates traumatic brain injury through controlling neuronal apoptosis and inflammation. However, the role of JNK-IN-8 in ischemic stroke and the underlying mechanisms of JNK-IN-8 involving neuroprotection remain poorly understood. In the present study, male rats were subjected to tMCAO (transient middle cerebral artery occlusion) followed by treatment with JNK-IN-8, and then the modified improved neurological function score (mNSS), the Foot-fault test and the level of inflammatory cytokines (IL-1{beta}, IL-6 and TNF-) were assessed. We found that JNK-IN-8-treated rats with MCAO exerted a significant improvement in spatial learning as measured by the improved mNSS, and showed sensorimotor functional recovery as measured by the Foot-fault test. JNK-IN-8 also exerted anti-inflammatory effects as indicated by decreased activation of microglia and the decreased expresson of IL-6, IL-1{beta} and TNF-. Furthermore, JNK-IN-8 suppressed the activation of JNK and subsequent activation of NF-{kappa}B signaling as indicated by the decreased level of phosphorylated JNK (p-JNK) and p65. These data suggest that JNK-IN-8 suppressed neuroinflammation and improved neurological function by inhibiting JNK/NF-{kappa}B pathway after ischemic brain injury, thus offering a new target for prevention of ischemic brain injury.

cancer biology↗

bioRxiv2018

Towards Decoding the Metabolic Plasticity in Cancer: Coupling of Gene Regulation and Metabolic Pathways

Metabolic plasticity enables cancer cells to switch their metabolism phenotypes between glycolysis and oxidative phosphorylation (OXPHOS) during tumorigenesis and metastasis. However, it is still largely unknown how cancer cells orchestrate gene regulation to balance their glycolysis and OXPHOS activities for better survival. Here, we establish a theoretical framework to model the coupling of gene regulation and metabolic pathways in cancer. Our modeling results demonstrate a direct association between the activities of AMPK and HIF-1, master regulators of OXPHOS and glycolysis respectively, with the activities of three metabolic pathways: glucose oxidation, glycolysis and fatty acid oxidation (FAO). Guided by the model, we develop metabolic pathway signatures to quantify the activities of glycolysis, FAO and the citric acid cycle of tumor samples by evaluating the expression levels of enzymes involved in corresponding processes. The association of AMPK/HIF-1 activity with metabolic pathway activity, predicted by the model and verified by analyzing the gene expression and metabolite abundance data of patient samples, is further validated by in vitro studies of aggressive triple negative breast cancer cell lines.

systems biology↗

bioRxiv2018

Destabilization of Ran C-terminus promotes GTP loading and occurs in multiple Ran cancer mutations

Ran (Ras-related nuclear protein) plays several important roles in nucleo-cytoplasmic transport, mitotic spindle formation, nuclear envelope/nuclear pore complex assembly, and other diverse functions in the cytoplasm, as well as in cellular transformation when activated. Unlike other Ras superfamily proteins, Ran contains an auto-inhibitory C-terminal tail, which packs against its G domain and bias Ran towards binding GDP over GTP. The biological importance of this C-terminal tail is not well understood. By disrupting the interaction between the C-terminus and the G domain, we were able to generate Ran mutants that are innately active and potently bind to RanBP1 (Ran Binding Protein 1), nuclear export factor CRM1 and nuclear import factor KPNB1. In contrast to previously reported activated Ran mutants, the C-terminus destabilized mutants are hydrolysis competent in cells, support nuclear transport, and do not form nuclear rim staining. Crystal structures show that one of these C-terminal mutations slightly changes its mode of binding to RanBP1. Finally, a high percentage of Ran C-terminus mutations from cancer patients were found to be destabilizing and hyperactivating, suggesting that Ran C-destabilization might be an unprecedented cellular transformation mechanism in affected cancers. This study also highlights a new drug design strategy towards treating patients with hyperactivated Ras proteins including K-Ras.

biochemistry↗

bioRxiv2018

Distinct RanBP1 nuclear export and cargo dissociation mechanisms between fungi and animals

Ran binding protein 1 (RanBP1), the primary effector of nuclear GTPase Ran, is a cytoplasmic-enriched and nuclear-cytoplasmic shuttling protein, playing important roles in nuclear transport through preventing RanGTP from being trapped with karyopherin proteins and dissociating cargoes from nuclear export factor CRM1. Much of what we know about RanBP1 is learned from fungi. Here we show that animal RanBP1 has distinct cargo dissociation and nuclear export mechanisms. In contrast to CRM1-RanGTP sequestration mechanism of cargo dissociation in fungi, animal RanBP1 solely sequesters RanGTP from nuclear export complexes. In fungi, RanBP1, CRM1 and RanGTP form a 1:1:1 nuclear export complex; in contrast, animal RanBP1, CRM1 and RanGTP form a 1:1:2 nuclear export complex. The key feature for the two mechanistic changes from fungi to animals is the loss of affinity between RanBP1-RanGTP and CRM1, since residues mediating their interaction in fungi are not conserved in animals. The biological significances of these different mechanisms in fungi and animals are also studied and discussed. Our study illustrates how orthologous proteins may play conserved functions through distinct routes, and may provide directions for design of antifungal medicines.

biochemistry↗

bioRxiv2018

Germline silencing of UASt depends on the piRNA pathway

One of the most extensively used techniques in Drosophila is the Gal4/UAS binary system, which allows tissue-specific misexpression or knockdown of specific genes of interest. The original UAS vector, UASt, can only be activated for transgene expression in somatic tissues and not in the germline cells. Rorth (1998) generated UASp, a modified UAS vector that is responsive to Gal4 in both somatic and germline tissues, by replacing both the hsp70 promoter and the SV40 3UTR with the P transposase promoter and the K10 3UTR respectively. At present, the mechanisms by which UASt is silenced in germline cells are not fully understood. Here, we report that the piRNA pathway is involved in suppressing UASt expression in ovarian germline cells. Individually knocking down or mutating components of the piRNA biogenesis pathway (e.g., Piwi, AGO3, Aub, Spn-E, and Vasa) resulted in the expression of the UASt-reporter (GFP or RFP) in the germline. An RNA-seq analysis of small RNAs revealed that the hsp70 promoter of UASt is targeted by piRNAs, and in the aub mutant ovary, the amount of piRNAs targeting the hsp70 promoter is reduced by around 40 folds. In contrast, the SV40 3UTR of the UASt, which happens to be targeted by the Nonsense-mediated RNA decay (NMD) pathway, is not responsible for germline UASt suppression, as UASt-reporters with NMD-insensitive 3UTRs fail to show germline expression. Taken together, our studies reveal a crucial role of the piRNA pathway, potentially via the suppression of the hsp70 promoter, in germline UASt silencing in Drosophila ovaries.

genetics↗

bioRxiv2018

Interconnected feedback loops among ESRP1, HAS2, and CD44 regulate epithelial-mesenchymal plasticity in cancer

Aberrant activation of epithelial-mesenchymal transition (EMT) in carcinoma cells contributes to increased migration and invasion, metastasis, drug resistance, and tumor-initiating capacity. EMT is not always a binary process, rather cells may exhibit a hybrid epithelial/mesenchymal (E/M) phenotype. ZEB1 - a key transcription factor driving EMT - can both induce and maintain a mesenchymal phenotype. Recent studies have identified two novel autocrine feedback loops utilizing ESRP1, HAS2, and CD44 that maintain high levels of ZEB1. However, how the crosstalk between these feedback loops alters the dynamics of epithelial-hybrid-mesenchymal transition remains elusive. Here, using an integrated theoretical-experimental framework, we identify that these feedback loops can enable cells to stably maintain a hybrid E/M phenotype. Moreover, computational analysis identifies the regulation of ESRP1 as a crucial node, a prediction that is validated by two complementary experiments showing that (a) overexpression of ESRP1 reverts EMT in MCF10A cells treated with TGF{beta} for 21 days, and (b) knockdown of ESRP1 in stable hybrid E/M H1975 cells drives EMT. Finally, in multiple breast cancer datasets, high levels of ESRP1, ESRP1/HAS2, and ESRP1/ZEB1 correlates with poor prognosis, supporting the relevance of ZEB1/ESRP1 and ZEB1/HAS2 axes in tumor progression. Together, our results unravel how these interconnected feedback loops act in concert to regulate ZEB1 levels and to drive the dynamics of epithelial-hybrid-mesenchymal transition.

cancer biology↗

bioRxiv2017

Modularity of the metabolic gene network as a prognostic biomarker for hepatocellular carcinoma

Abnormal metabolism is an emerging hallmark of cancer. Cancer cells utilize both aerobic glycolysis and oxidative phosphorylation (OXPHOS) for energy production and biomass synthesis. Understanding the metabolic reprogramming in cancer can help design therapies to target metabolism and thereby to improve prognosis. We have previously argued that more malignant tumors are usually characterized by a more modular expression pattern of cancer-associated genes. In this work, we analyzed the expression patterns of metabolism genes in terms of modularity for 371 hepatocellular carcinoma (HCC) samples from the Cancer Genome Atlas (TCGA). We found that higher modularity significantly correlated with glycolytic phenotype, later tumor stages, higher metastatic potential, and cancer recurrence, all of which contributed to poorer prognosis. Among patients with recurred tumor, we found the correlation of higher modularity with worse prognosis during early to mid-progression. Furthermore, we developed metrics to calculate individual modularity, which was shown to be predictive of cancer recurrence and patients survival and therefore may serve as a prognostic biomarker. Our overall conclusion is that more aggressive HCC tumors, as judged by decreased host survival probability, had more modular expression patterns of metabolic genes. These results may be used to identify cancer driver genes and for drug design.

cancer biology↗

bioRxiv2017

RACIPE: A computational tool for Modeling Gene Regulatory Circuits using Randomization

MotivationOne of the major challenges in traditional mathematical modeling of gene regulatory circuits is the insufficient knowledge of kinetic parameters. These parameters are often inferred from existing experimental data and/or educated guesses, which can be time-consuming and error-prone, especially for large networks.\n\nResultsWe present a computational tool based on our newly developed method named random circuit perturbation (RACIPE), to explore the robust dynamical features of gene regulatory circuits without the requirement of detailed kinetic parameters. RACIPE generates an ensemble of circuit models with distinct random parameters and uniquely identifies robust dynamical properties by statistical analysis. Here, we discuss software implementation and illustrate the usage of RACIPE on coupled toggle-switch circuits and a published circuit of B-lymphopoiesis. We expect RACIPE to contribute to a more comprehensive and unbiased understanding of gene regulatory mechanisms.\n\nAvailabilityRACIPE is a free open source software distributed under (Apache 2.0) license and can be downloaded from GitHub (https://github.com/simonhb1990/RACIPE-1.0).\n\nContactMingyang.Lu@jax.org, Herbert.Levine@rice.edu or jonuchic@rice.edu

systems biology↗

bioRxiv2017

Distinguishing Mechanisms Underlying EMT Tristability

BackgroundThe Epithelial-Mesenchymal Transition (EMT) endows epithelial-looking cells with enhanced migratory ability during embryonic development and tissue repair. EMT can also be co-opted by cancer cells to acquire metastatic potential and drug-resistance. Recent research has argued that epithelial (E) cells can undergo either a partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype that typically displays collective migration, or a complete EMT to adopt a mesenchymal (M) phenotype that shows individual migration. The core EMT regulatory network - miR-34/SNAIL/miR-200/ZEB1 - has been identified by various studies, but how this network regulates the transitions among the E, E/M, and M phenotypes remains controversial. Two major mathematical models - ternary chimera switch (TCS) and cascading bistable switches (CBS) - that both focus on the miR-34/SNAIL/miR-200/ZEB1 network, have been proposed to elucidate the EMT dynamics, but a detailed analysis of how well either or both of these two models can capture recent experimental observations about EMT dynamics remains to be done.\n\nResultsHere, via an integrated experimental and theoretical approach, we first show that both these two models can be used to understand the two-step transition of EMT - E[->]E/M[->]M, the different responses of SNAIL and ZEB1 to exogenous TGF-{beta} and the irreversibility of complete EMT. Next, we present new experimental results that tend to discriminate between these two models. We show that ZEB1 is present at intermediate levels in the hybrid E/M H1975 cells, and that in HMLE cells, overexpression of SNAIL is not sufficient to initiate EMT in the absence of ZEB1 and FOXC2.\n\nConclusionsThese experimental results argue in favor of the TCS model proposing that miR-200/ZEB1 behaves as a three-way decision-making switch enabling transitions among the E, hybrid E/M and M phenotypes.

cancer biology↗

bioRxiv2016

Interrogating the Topological Robustness of Gene Regulatory Circuits

One of the most important roles of cells is performing their cellular tasks properly for survival. Cells usually achieve robust functionality, for example cell-fate decision-making and signal transduction, through multiple layers of regulation involving many genes. Despite the combinatorial complexity of gene regulation, its quantitative behavior has been typically studied on the basis of experimentally-verified core gene regulatory circuitry, composed of a small set of important elements. It is still unclear how such a core circuit operates in the presence of many other regulatory molecules and in a crowded and noisy cellular environment. Here we report a new computational method, named random circuit perturbation (RACIPE), for interrogating the robust dynamical behavior of a gene regulatory circuit even without accurate measurements of circuit kinetic parameters. RACIPE generates an ensemble of random kinetic models corresponding to a fixed circuit topology, and utilizes statistical tools to identify generic properties of the circuit. By applying RACIPE to simple toggle-switch-like motifs, we observed that the stable states of all models converge to experimentally observed gene state clusters even when the parameters are strongly perturbed. RACIPE was further applied to a proposed 22-gene network of the Epithelial-to-Mesenchymal transition (EMT), from which we identified four experimentally observed gene states, including the states that are associated with two different types of hybrid Epithelial/Mesenchymal phenotypes. Our results suggest that dynamics of a gene circuit is mainly determined by its topology, not by detailed circuit parameters. Our work provides a theoretical foundation for circuit-based systems biology modeling. We anticipate RACIPE to be a powerful tool to predict and decode circuit design principles in an unbiased manner, and to quantitatively evaluate the robustness and heterogeneity of gene expression.

systems biology↗