Mathematical Model of Parotid Acinar Differentiation

腮腺腺泡分化的数学模型

• 批准号: 8271271
• 负责人: DOUGLAS S DARLING
• 金额: $ 30.99万
• 依托单位: UNIVERSITY OF LOUISVILLE
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-16 至 2014-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8271271
• 关键词: Acinar Cell; Address; Algorithms; American; Biological Response Modifier Therapy; Biology; Cell Differentiation process; Complementary DNA; Computing Methodologies; Confidence Intervals; Coupled; Data; Development; Differentiation Antigens; Embryo; Equation; Foundations; Functional disorder; Gene Expression; Gene Expression Profile; Gene Proteins; Gene Targeting; Gene Transfer; Genes; Genomics; Goals; Histologic; MicroRNAs; Microarray Analysis; Modeling; Molecular; Muscle; Natural regeneration; Neurons; Newborn Infant; Oral; Output; Parotid Gland; Pathway interactions; Patients; Pattern; Pharmaceutical Preparations; Procedures; Process; Publications; RNA; Radiation therapy; Rattus; Regulation; Regulatory Pathway; Research; Reverse Transcriptase Polymerase Chain Reaction; Salivary; Salivary Glands; Serous; Signal Pathway; Signal Transduction; Sjogren' s Syndrome; Small Interfering RNA; Source; Statistical Models; Symptoms; System; Systems Biology; Testing; Time; Tissues; Transfection; Validation; Variant; Western Blotting; Work; Xerostomia; abstracting; cell type; expectation; gene therapy; laser capture microdissection; mathematical model; new technology; parotid cell; predictive modeling; prototype; research study; restoration; salivary acinar cell; salivary cell; transcription factor

Abstract. The long term goal of the proposed project is to define the development of signaling networks that induce differentiation of cells into mature salivary serous acinar cells to allow gene therapy approaches to regenerating or replacing salivary tissue in patients. Millions of patients suffer loss of salivary gland function due to Sjogren's syndrome or radiation therapy. Understanding the differentiation of salivary cells is a necessary step to enable the restoration of diseased or destroyed parotid salivary tissue. Previous work has described terminal differentiation of acinar cells histologically, and by characterizing the expression of markers of differentiation, but has not used genomics-level approaches, or mathematical models, to define regulatory pathways. The primary goal of the current application is to develop formal mathematical and statistical models that will identify networks which cause terminal differentiation of parotid acinar cells. The dynamical mathematical models will serve to generate hypotheses which will be tested, and the model will be repeatedly refined by the incorporation of new data. This proposal is responsive to the RFA "A Systems Approach to Salivary Gland Biology." Our overall hypothesis for these studies is that a mathematical model can identify key regulatory pathways that control parotid acinar cell differentiation. Specific Aim #1 will use Laser Capture Microdissection (LCM) to obtain RNA from embryonic and newborn rat parotid acinar cells for microarray analysis of the patterns of gene expression across the period of differentiation. A coupled Ordinary Differential Equation (ODE) model will be created to describe the hypothetical interactions that direct the process of differentiation. The hypotheses will be tested, and the ODE model refined, by a combination of RT-PCR, IHC, and western blots. Since microRNAs are important regulators of development, Specific Aim #2 will define the expression of microRNAs in acinar cells, and the pattern of changes during differentiation. There are currently no publications describing microRNAs in the parotid. The results will be used to revise the mathematical model of differentiation. Specific Aim #3 will create a statistical algorithm to validate and revise the ODE model by defining the sources of bias and variation as well as by assessing the model's predictive power overall, and in its various sub-modules. This will allow confidence intervals to be associated with different pathways within the ODE model. Specific Aim #4 will use the ODE model to make hypotheses about specific pathways regulating gene expression in the parotid acinar cells. These hypotheses will be tested by transfection and transduction experiments, and the results shall be used to refine and validate the mathematical model. This systems biology approach should identify molecular pathways that drive cytodifferentiation of parotid acinar cells. Project Narrative. The overall goal of this research is to define the molecular mechanisms which control differentiation of cells into secretory salivary acinar cells. This addresses the needs of millions of Americans who suffer from salivary gland dysfunction due to Sj¿gren's Syndrome, radiation therapy, or xerostomia due to essential medications. This research is a necessary foundation for developing new technologies such as gene transfer therapy and biologics for treating or alleviating the oral symptoms of xerostomia.

抽象的。 拟议项目的长期目标是定义信令网络的发展 将细胞分化为成熟的唾液浆液性腺泡细胞，使基因治疗方法成为可能 再生或替换患者的唾液组织。数百万患者遭受唾液腺功能丧失 由于干燥综合征或放射治疗。理解唾液细胞的分化是一个 修复患病或被破坏的腮腺唾液组织的必要步骤。以前的工作有 描述了腺泡细胞在组织学上的终末分化，并通过表征标志物的表达 但没有使用基因组学水平的方法或数学模型来定义调控 小路。当前应用程序的主要目标是开发正式的数学和统计模型 这将识别导致腮腺腺泡细胞终末分化的网络。《动力》 数学模型将用于生成将被检验的假设，并且该模型将被重复 通过纳入新数据进行了提炼。这项提议是对RFA“系统方法”的响应 我们对这些研究的总体假设是，一个数学模型可以识别 控制腮腺腺泡细胞分化的关键调控途径。第一个特定目标将使用激光捕获 显微切割(LCM)从胚胎和新生大鼠腮腺腺泡细胞中提取RNA用于基因芯片 分析基因在整个分化时期的表达模式。一种耦合常微分器 将创建方程(ODE)模型来描述指导过程的假设交互作用 差异化。假说将得到检验，ODE模型将通过RT-PCR、IHC、 和西方的印迹。由于microRNAs是发育的重要调节器，具体目标2将定义 腺泡细胞中microRNAs的表达及其在分化过程中的变化。目前有 没有文献描述腮腺中的microRNAs。结果将被用来修正数学模型 差异化。具体目标#3将创建一个统计算法，通过以下方式验证和修订ODE模型 定义偏差和偏差的来源，以及通过全面评估模型的预测能力，以及在 它的各个子模块。这将允许置信度间隔与 ODE模型。具体目标#4将使用ODE模型来提出关于特定途径调控的假设 腮腺腺泡细胞的基因表达。这些假说将通过转基因和转导来检验。 实验，并将结果用于精炼和验证数学模型。这个系统生物学 方法应确定驱动腮腺腺泡细胞分化的分子途径。项目叙事。 本研究的总体目标是明确控制细胞分化的分子机制。 细胞分化为分泌性唾液腺泡细胞。这解决了数百万美国人的需求 干燥综合征、放射治疗引起的唾液腺功能障碍，或因高血压引起的口干症 药物。这项研究是开发基因转移等新技术的必要基础 治疗或减轻口干症口腔症状的疗法和生物制品。

项目成果

A systems biology approach identifies a regulatory network in parotid acinar cell terminal differentiation.

• DOI: 10.1371/journal.pone.0125153
• 发表时间: 2015
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Metzler MA;Venkatesh SG;Lakshmanan J;Carenbauer AL;Perez SM;Andres SA;Appana S;Brock GN;Wittliff JL;Darling DS
• 通讯作者: Darling DS

On Permutation Procedures for Strong Control in Multiple Testing with Gene Expression Data.

关于基因表达数据多重测试中强控制的排列程序。

• DOI: 10.4310/sii.2013.v6.n1.a8
• 发表时间: 2013
• 期刊: Statistics and its interface
• 影响因子: 0.8
• 作者: Rempala,GrzegorzA;Yang,Yuhong
• 通讯作者: Yang,Yuhong

Algebraic methods for inferring biochemical networks: a maximum likelihood approach.

• DOI: 10.1016/j.compbiolchem.2009.07.014
• 发表时间: 2009-10
• 期刊: COMPUTATIONAL BIOLOGY AND CHEMISTRY
• 影响因子: 3.1
• 作者: Craciun, Gheorghe;Pantea, Casian;Rempala, Grzegorz A.
• 通讯作者: Rempala, Grzegorz A.

Use of multiple time points to model parotid differentiation.

使用多个时间点来模拟腮腺分化。

• DOI: 10.1016/j.gdata.2015.05.005
• 发表时间: 2015
• 期刊: Genomics data
• 作者: Metzler,MelissaA;Appana,Savitri;Brock,GuyN;Darling,DouglasS
• 通讯作者: Darling,DouglasS