Mathematical modeling of Mycobacterium tuberculosis dissemination

研究综述 结核病（TB）是由结核分枝杆菌（Mtb）引起的一种疾病，仍然是一种主要的感染， 世界上最严重的人类疾病。在肺部一个部位的初始局部感染后，结核分枝杆菌不知何故消失了， 在肺中生长并经常扩散到肺外。事实上，肺外结核是肺结核的一个标志， 儿童和免疫功能低下的成年人是很难诊断和治疗的。我们对结核病的了解 然而，肺内和肺外的传播仍然有限。在这个提案中，我们组建了一个团队， 具有计算生物学（Ganusov、Aitchison、Duffy、兰斯顿）和结核病发病机制方面专业知识的科学家 （Urdahl，谢尔曼，Behar），以提供对结核分枝杆菌在肺中传播的机制的定量理解 系统地。为此，我们将使用一些高度创新的技术，如i）一种新的动物 TB模型：用超低剂量（ULD，1-3个集落形成单位，CFU）的Mtb沿着一组 ii）具有复制时钟质粒的Mtb菌株H37 Rv-pBP 10，允许估计 细菌在体内被消除的速度，和iii）基于mRNA的基因特征， 鼠肺和人类结核病进展风险。通过三个互补的具体目标，我们将促进- 对结核分枝杆菌如何从沉积物中传播的基本过程进行详细的定量了解 从肺泡到整个肺和全身。在目标1中，我们将确定结核分枝杆菌传播的途径 使用一种新的ULD感染小鼠模型，该模型比许多其他模型更能模拟人类感染， 动物模型特别是，我们将区分肺结核传播的替代假设 例如“气泡模型”（其中Mtb在肺叶之间局部扩散）和“再播种模型”（其中 结核病在全身传播后通过血液传播到肺的不同部位）。在目标2中， 确定不同细胞群（包括结核分枝杆菌特异性CD 4 T细胞应答）对结核分枝杆菌感染动力学的贡献。 在用常规剂量（CD，150 CFU）的Mtb感染的小鼠中Mtb全身传播。参数化 最佳拟合模型我们将使用来自携带复制时钟质粒pBP 10的Mtb H37 Rv的实验的数据。 最后，在目标3中，我们将尝试改进我们最近获得的基于mRNA的基因签名， 使用基于最新图论的数据降维方法在小鼠肺中的CFU。我们将 我还进行了实验，并定义了一个新的特征，预测小鼠中的传播性结核病，并测试其准确性 使用猴子和人类的数据。总之，通过结合高度创新的实验数据， 涉及新技术的实验（超低剂量感染，条形码菌株，复制时钟质粒， 基于微阵列的基因签名），我们将提供一个定量的了解如何结核分枝杆菌传播的 肺和全身性的。

Research Summary Tuberculosis (TB), a disease caused by the bacteria Mycobacterium tuberculosis (Mtb), remains a major infec- tious disease of humans in the world. After the initial local infection of one site in the lung Mtb somehow dissem- inates in the lung and often spreads beyond the lung. In fact, extrapulmonary TB is a hallmark of the disease in young children and immunocompromised adults that is difficult to diagnose and treat. Our understanding of Mtb dissemination, both within the lung and beyond, remains limited, however. In this proposal we assembled a team of scientists with expertise in computational biology (Ganusov, Aitchison, Duffy, Langston) and TB pathogenesis (Urdahl, Sherman, Behar) to provide quantitative understanding of mechanisms of Mtb dissemination the lung and systemically. To this end, we will be using a number of highly innovative techniques such as i) a novel animal model of TB: infection of mice with an ultra low dose (ULD, 1-3 colony forming units, CFU) of Mtb along with a set of 50 barcoded Mtb strains, ii) an Mtb strain H37Rv-pBP10 with the replication clock plasmid, allowing to estimate how quickly bacteria are eliminated in vivo, and iii) mRNA-based gene signatures predicting bacterial numbers in murine lungs and TB disease progression risk in humans. With three complementary specific aims we will pro- vide detailed, quantitative understanding of fundamental processes of how Mtb disseminates from the deposition in lung alveoli to the whole lung and systemically. In Aim 1 we will determine the pathway of Mtb dissemination within the lung using a novel model of ULD-infected mice that mimics better human infection than many other animal models. In particular, we will discriminate between alternative hypotheses of Mtb spread in the lungs such the “bubble model” (in which Mtb spreads locally between lung lobes) and the “reseeding model” (in which Mtb spreads hematogenously to different parts of the lung after disseminating systemically). In Aim 2 we will determine the contribution of different cell populations, including Mtb-specific CD4 T cell response, to kinetics of Mtb dissemination systemically in mice infected with conventional doses (CD, 150 CFU) of Mtb. To parameterize best fit models we will use data from experiments with Mtb H37Rv carrying the replication clock plasmid pBP10. Finally, in Aim 3 we will attempt to improve on our recently derived mRNA-based gene signatures predicting CFU in murine lungs using cutting-edge graph theory-based methods of data dimensionality reduction. We will also perform experiments and define a new signature predicting disseminated TB in mice, and test its accuracy using data from monkeys and humans. Taken together, by combining experimental data from highly innovative experiments involving novel techniques (ultra low dose infections, barcoded strains, replication clock plasmid, microarray-based gene signatures) we will provide a quantitative understanding of how Mtb disseminates in the lung and systemically in the body.