Isolation of narrow subpopulations of cells using molecular computing cascades

使用分子计算级联分离狭窄的细胞亚群

• 批准号: 8444393
• 负责人: Milan N Stojanovic
• 金额: $ 19.59万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-01 至 2015-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8444393
• 关键词: Address; Affinity; Antibodies; Autoimmune Diseases; Autoimmunity; Basic Science; Benchmarking; Biological Models; Biological Sciences; Biomedical Engineering; CD19 gene; CD28 gene; CD3 Antigens; Cell Line; Cell Separation; Cell surface; Cells; Communities; Complement 3d Receptors; Development; Disease; Dyes; Engineering; Evaluation; Failure; Flow Cytometry; Fluorescein; Funding; Gray unit of radiation dose; IL2RA gene; Immunoglobulin D; Immunology; Label; Lymphocyte; Lymphocyte Subset; Malignant Neoplasms; Medicine; Memory B-Lymphocyte; Methods; Molecular; Monitor; Natural Killer Cells; One-Step dentin bonding system; Organ; Pathogenesis; Peripheral Blood Mononuclear Cell; Population; Procedures; Protocols documentation; Reagent; Research; Sea; Series; Surface; T-Lymphocyte; TNFRSF6 gene; TNFSF5 gene; Techniques; Therapeutic; Tissue Therapy; Translating; base; interest; operation; programs; scale up; self organization

DESCRIPTION (provided by applicant): We describe here sets of molecules that compute the state of the cell surface. The sets can be programmed to self-organize on cell surfaces displaying antibody-based targeting moieties in a way that results in unique tags (labels) displayed on the surfaces of arbitrarily narrow subpopulations of cells. The decision to display or not the tag will depend on antibodies that are present, i.e., on the multiple cell surface markers that define uniquely the targeted cells via their presence or absence. The resulting tag can be used to isolate in a single step the targeted cells in the presence of other subpopulations. This single-step method for isolation of cells based on multiple surface markers will have unique advantages over existing methods because of its scalability, efficacy, and mildness. We will study the scope and limitations of new technique on an example of therapeutically interesting subpopulations of lymphocytes, comparing our technique with existing methods and multistep protocols: Aim 1: in which the molecules will compute the presence of multiple markers on a cell surface. We will start with evaluation of up to three markers on CD4+CD25+ and CD4+CD25+CD154+ T- cells. We will then demonstrate the ability to isolate groups of cells based on the intensity of a marker, separating two fractions of NK cells (CD56dim and CD56high), developing sets of molecules with thresholding (cut off value) function. Aim 2: in which molecules will evaluate both the presence and absence of markers. After initial optimization on a model system, we will demonstrate the ability to isolate narrow subpopulations of conventional memory B-cells (CD19+CD21+CD27+IgD-) and recently characterized unconventional memory B-cells (CD19+CD21-/lowCD27-IgD-CD95+). Our reagents can be combined with any moiety used for targeting cell-surface markers with only minimal optimization. Thus, through our results we will introduce the biomedical community to a highly modular approach to isolating narrow populations of cells using of-the- shelf reagents. The method will have wide applications in basic science research, personalized medicine, and biomedical engineering.

描述（由申请人提供）：我们在此描述了计算细胞表面状态的分子组。这些组可以被编程为在细胞表面上自组织，显示基于抗体的靶向部分，从而在任意狭窄的细胞亚群的表面上显示独特的标签（标记）。决定显示或 标签不依赖于存在的抗体，即依赖于通过其存在或不存在来唯一定义目标细胞的多个细胞表面标记。所得标签可用于在存在其他亚群的情况下一步分离目标细胞。这种基于多个表面标记物的单步分离细胞方法由于其可扩展性、有效性和温和性，将比现有方法具有独特的优势。我们将以治疗上感兴趣的淋巴细胞亚群为例，研究新技术的范围和局限性，并将我们的技术与现有方法和多步骤方案进行比较： 目标 1：其中分子将计算细胞表面上多个标记的存在。我们将从评估 CD4+CD25+ 和 CD4+CD25+CD154+ T 细胞上最多三个标记物开始。然后，我们将展示根据标记强度分离细胞组、分离两部分 NK 细胞（CD56dim 和 CD56high）、开发具有阈值（截止值）功能的分子组的能力。目标 2：分子将评估标记的存在和不存在。在对模型系统进行初步优化后，我们将展示分离传统记忆 B 细胞 (CD19+CD21+CD27+IgD-) 的狭窄亚群和最近表征的非常规记忆 B 细胞 (CD19+CD21-/lowCD27-IgD-CD95+) 的能力。 我们的试剂可以与用于靶向细胞表面标记的任何部分组合，只需进行最小程度的优化。因此，通过我们的结果，我们将向生物医学界介绍一种高度模块化的方法，使用现成的试剂分离狭窄的细胞群。该方法将在基础科学研究、个性化医疗和生物医学工程等方面具有广泛的应用。