Design and characterization of bacterial population dynamics in solid tumor models

项目摘要 越来越清楚的是，细菌在人类健康中扮演着重要的角色。虽然人们很自然地会关注如何 肠道细菌影响疾病，耐人寻味的fi发现阐明了细菌栖息在固体中的程度 肿瘤。在肺、胰腺、乳房、口腔、胆囊、卵巢、肝脏和结直肠中检测到微生物。 癌症。本地化被归因于几种机制，包括偏好厌氧或兼性 厌氧细菌在肿瘤的缺氧核心生长，细菌营养物质的存在，缺乏免疫监测- Lance，以及肿瘤组织周围结构不良的血管系统的渗漏。这一趋势对 对实体肿瘤的定位表明，细菌可以被改造成精确和强大的药物生产和 从实体肿瘤环境中输送。这与合成生物学20年来的进步相吻合， 该公司倾向于专注于微生物工程。然而，关于肿瘤微环境如何 影响细菌生长的因素在很大程度上是未知的。微环境会影响细菌的基因表达。 工程疗法的功能性是非常重要的，而且很难想象一个预测性的框架。 在没有对细菌如何对环境做出反应的定量了解的情况下进行工程细菌疗法 一个正在生长的肿瘤。我们将使用一种已有安全记录的益生菌菌株来开发一种新的 一类生物传感器，用于非侵入性地研究肿瘤微环境中的细菌生长。最初，我们 将开发基于裂解的生物传感器，对特定的fic肿瘤环境目标做出反应：缺氧，pH，葡萄糖， 和乳酸(目标1)。我们还将设计一种可感应的群体感应(QS)系统，以实现外部控制 细菌种群动态，包括在需要时消除特定fic菌株的能力(目标1)。 这些菌株结合在一起，将使我们能够调节和监测体内的种群动态，使两种正义- 维护本地环境和维护外部控制开关。我们将使用一个 建立了体外器官模型(AIM 2)和两个临床相关的实体瘤生长动物模型。 此外，我们将使用我们之前开发的dynOMICS技术来筛选这两种肿瘤提取物 建立动物模型并构建第二套生物传感器，用于监测肿瘤环境(目标2)。这些 生物传感器随后将在动物模型中进行测试。我们将可视化大肠肿瘤中的细菌种群。 用基因工程产生荧光素酶的细菌建立模型，以便使用我们的ES- 既定方法(目标3)。我们还将建立在最近报道的技术的基础上，利用该技术对细菌进行fi改造 通过添加气泡与超声一起使用，允许对工程背衬进行高分辨率成像- 特里亚。我们将使用超声方法来研究NASH诱导的肝细胞癌 使用高脂饮食在20周时诱导小鼠肝细胞癌(目标4)。这个项目将从数量上描述 细菌菌株如何感知、反应和在肿瘤中生长。这一成果将为未来建立一个平台 探索由生长在实体肿瘤内的细菌产生和提供的治疗方法。

Project Summary It is increasingly clear that bacteria play an important role in human health. While it is natural to focus on how intestinal bacteria affect disease, intriguing findings have elucidated the extent to which bacteria inhabit solid tumors. Microbes have been detected in lung, pancreatic, breast, oral, gallbladder, ovarian, liver, and colorectal cancers. Localization has been ascribed to several mechanisms, including preference for anaerobic or facultative anaerobic bacteria to grow in the hypoxic core of tumors, presence of bacterial nutrients, lack of immune surveil- lance, and leakiness of the often poorly structured vasculature surrounding neoplastic tissue. This tendency for localization to solid tumors suggests that bacteria could be engineered for precise and robust drug production and delivery from within the solid tumor environment. This dovetails with 20 years of progress in synthetic biology, which has tended to focus on microbial engineering. However, information on how the tumor microenvironment affects bacterial growth is largely unknown. The microenvironment will affect bacterial gene expression that ul- timately underlies the functionality of engineered therapies, and it is difficult to imagine a predictive framework for engineered bacterial therapies without a quantitative understanding of how bacteria react to the environment of a growing tumor. We will use a probiotic strain of E. coli with an established safety record to develop a novel class of biosensors to noninvasively investigate bacterial growth in the tumor microenvironment. Initially, we will develop lysis-based biosensors that respond to specific tumor environment targets: hypoxia, pH, glucose, and lactate (Aim 1). We will also engineer an inducible quorum sensing (QS) system that enables external control of bacterial population dynamics, including the ability to eliminate a specific strain whenever desired (Aim 1). Together these strains will allow us to modulate and monitor population dynamics in vivo, enabling both sens- ing of the local environment and maintenance of an external control switch. We will test these strains using an established in vitro organoid model (Aim 2) and in two clinically relevant animal models for solid tumor growth. Additionally, we will use our previously developed dynOMICS technology to screen tumor extract from the two animal models and construct a second suite of biosensors for monitoring the tumor environment (Aim 2). These biosensors will then be tested in the animal models. We will visualize bacterial populations in a colorectal tumor model with bacteria that are engineered to produce luciferase in order to monitor colony dynamics using our es- tablished methods (Aim 3). We will also build on recently reported technology whereby bacteria are modified for use with ultrasound through addition of gas vesicles that permit high resolution imaging of the engineered bac- teria. We will use the ultrasound method to investigate NASH-induced hepatocellular carcinoma (HCC) where a high-fat diet is used to induce HCC at 20 weeks in mice (Aim 4). This project will quantitatively characterize how bacterial strains sense, respond, and grow in the tumors. The results will establish a platform for future exploration of therapies that are produced and delivered by bacteria that grow within solid tumors.