Live-cell Microarray for high-throughput observation of metabolic signatures

用于单细胞动态多参数检测的高通量活细胞微阵列筛选技术 提出了代谢表型。该提案通过扩大范围， 的签名提供给LINCS中心一个三明治微阵列，被称为“Cellarium”， 用于分析单个活细胞。三明治的底层支撑着细胞， 在玻璃中蚀刻的浅微孔。三明治的顶层将电池密封在150皮升的 微孔，并纳入细胞外荧光传感器的多参数检测的代谢 分析物、氧、pH和葡萄糖。当这两层被压缩时， 以及允许动态测量跨膜通量的扁平金属弹簧， 细胞内探针。单细胞分析直接揭示了代谢反应的异质性， 同基因细胞群内的扰动对于生物推断是至关重要的。这个微阵列是一个 用于导出标准化的多参数数据集的可扩展工具，所述标准化的多参数数据集可以被集成到协调的 进入LINCS。该项目的具体目标是：1）开发一次性微阵列（“Cellarium”）， 动态，高通量，多参数代谢测量的扰动诱导的签名， 活单细胞; 2）修改商业微阵列扫描仪以读出Cellarium; 3）验证 该技术通过同时监测O2、pH、葡萄糖 和ATP响应; 4）通过分析单个细胞的代谢特征的分布来验证平台。 5）制定书面和图形化的标准操作程序， 能够生成可再现的数据; 6）与LINCS合作伙伴一起积极参与仪器 开发过程，以确保有效的设备和方法翻译。

High throughput live-cell microarray screening technology for dynamic, multiparameter sensing cf single-cell metabolic phenotypes is proposed. The proposal addresses Common Fund priorities by extending the range of signatures available to the LINCS centers. A sandwich microarray, called the "Cellarium" will be developed and used to analyze individual live cells. The bottom layer ofthe sandwich supports cells in shallow microwells etched in glass. The top layer ofthe sandwich seals the cells in the 150-picoliter microwells, and incorporates extracellular fluorescent sensors for multiparameter detection ofthe metabolic analytes, oxygen, pH and glucose. Chemical isolation is achieved when the two layers are compressed together with a flat metal spring allowing dynamic measurement of transmembrane fluxes without Intracellular probes. Single-cell analysis which directly reveals heterogeneity in metabolic response to perturbations within an isogenic cell population is critical to biological inference. This microarray is an extensible tool for deriving a standardized multiparameter set of data that can be integrated in a coordinated way into LINCS. The specific aims ofthe project are: 1) develop a disposable microarray ("Cellarium") for dynamic, high throughput, multiparameter metabolic measurements of perturbation-induced signatures of live single cells; 2) modify a commercial microarray scanner to read out the Cellarium; 3) verify the effectiveness of this technology across a range of cell types by simultaneously monitoring 02, pH, glucose and ATP responses; 4) validate the platform by analyzing the distribution of metabolic signatures of single cells in response to perturbations; 5) develop written and graphical standard operating procedures that enable reproducible data generation; 6) develop active participation with LINCS partners in the instrument development process to ensure efficient device and methods translation.