Random Display of Gut Microflora Proteins to Analyze Obesity

描述(申请人提供)：研究DNA和RNA的微阵列方法使生物学发生了革命性的变化，但用于研究蛋白质的类似的、高度平行的阵列进展缓慢。我建议结合现有的高通量测序、固相DNA扩增和无细胞表达技术来创建一种新型的高密度蛋白质阵列，其中克隆蛋白质特征是由固定化DNA模板原位产生的。这种随机寻址的蛋白质阵列将具有必要的特征密度，以便能够通过活性、结合和底物依赖分析来并行测量数百万蛋白质的性质。蛋白质的特性和表达水平将用现有的高通量测序方法来阐明。这些蛋白质阵列可以用来研究各种以前难以进入的系统中的蛋白质属性和表达水平，包括细菌群落。这样的群落对人类健康很重要；例如，肥胖个体拥有一套与瘦个体不同的肠道微生物区系，能够获得更多的食物能量。肥胖影响着三分之一的美国人，是糖尿病、心脏病、高血压和某些类型癌症的危险因素。肠道菌群组成的差异可能会导致肥胖，但要理清肠道中发生的复杂代谢过程是困难的。肠道包含500到1000个不同的物种，估计总共蕴藏着200万到400万个基因--这个数字远远超过了传统的生化分析的能力。为了迎接这一挑战，我将使用随机寻址的蛋白质阵列来比较瘦和肥胖肠道微生物群的蛋白质活性和表达谱。因此，我提出了以下具体目标：1)利用桥式PCR产生随机寻址的DNA特征；2)固定模板DNA的无细胞转录和翻译；以及3)肥胖相关蛋白补体的功能分析。使用随机编址的蛋白质阵列应该有助于更好地理解肥胖，这项技术最终可能成为高通量分析蛋白质功能的广泛使用的工具。与公共健康相关这项研究试图理解肥胖，因为它与肠道内的细菌有关，这些细菌有助于消化我们吃的食物。这项提案描述了一项新技术，该技术应该能发现为什么某些类型的肠道细菌与肥胖有关。更好地了解这一肥胖的潜在原因可能会导致有效的治疗。

DESCRIPTION (provided by applicant): Microarray methods for studying DNA and RNA have revolutionized biology, but progress towards analogous, highly parallel arrays for studying proteins has been slower. I propose combining existing high throughput sequencing, solid-phase DNA amplification and cell-free expression technologies to create a new type of high density protein array in which clonal protein features are generated in situ from immobilized DNA templates. Such a randomly addressed protein array would have the feature density necessary to enable parallel measurement of the properties of millions of proteins via activity, binding and substrate dependence assays. Protein identity and expression levels would be elucidated with existing high throughput sequencing methods. These protein arrays could be used to study protein properties and expression levels in a wide variety of previously difficult to access systems, including bacterial communities. Such communities are important in human health; for example, obese individuals harbor a set of gut microflora that is distinct from that of lean individuals and capable of harvesting more food energy. Obesity affects a third of Americans and is a risk factor for diabetes, heart disease, hypertension, and some types of cancers. Differences in gut microflora composition likely contribute to obesity, but disentangling the complex metabolic processes occurring in the gut is difficult. The gut contains 500-1000 different species estimated to collectively harbor between 2 and 4 million genes - a number that far exceeds the capacity of traditional biochemical analysis. To meet this challenge, I will use randomly addressed protein arrays to compare the protein activity and expression profiles of lean versus obese gut microflora. Therefore, I propose the following specific aims: 1) generation of randomly addressed DNA features using bridge PCR; 2) cell-free transcription and translation of immobilized template DNA; and 3) functional analysis of the obesity associated protein complement. Usage of randomly addressed protein arrays should facilitate a better understanding of obesity and this technology could eventually become a widely used tool for high throughput analysis of protein function. PUBLIC HEALTH RELEVANCE This research seeks to understand obesity as it relates to the bacteria inside the gut that help digest the food we eat. This proposal describes a novel technology that should discover why certain types of gut bacteria are associated with obesity. A better understanding of this potential cause of obesity could lead to an effective treatment.