Profiling and Mapping Core

剖析和映射B芯 项目负责人：李京姬和D·布兰奇·穆迪 联合调查员：雅各布·梅菲尔德 抽象-剖析和映射核心B 现代传染病研究基本上依赖于主要病原体的基因组图谱。与 整体代谢组谱分析工具的最新进展，全面绘制了M。 结核(结核分枝杆菌)代谢组现在是可行的。核心B支持基于质谱学的结核分枝杆菌分析 用于支持项目1、2和3的代谢物，这些项目分别侧重于发现、药物和诊断。这个 CORE将进行整个生物体的脂组和代谢组谱分析，存档数据集，并使用现代 构建结核分枝杆菌代谢脂组学图谱的生物信息学方法。地图由结构化列表组成 所有代谢物亚类，每个类别内所有命名代谢物的列表，以及所有命名代谢物的链接 代谢物转化为质量值和其他生物变量。我们之前生成了MycoMap数据库， 这是现有的183个分枝杆菌代谢物类别的最大图谱，这些代谢物类别与19.5万个准确质量有关 价值观。现在，我们将通过添加在项目1、2和3中生成的新发现的脂类来扩展数据库。 支持项目1和项目2，我们将解决Mycolate外膜类脂图，它描述了 位于宿主-病原体屏障并参与药物渗透的化合物。支持项目1和项目3， 该核心将测量南非患者结核分枝杆菌菌株之间的代谢物变异，以产生 人结核分枝杆菌株血脂变异数据库。这个数据库将描述血脂的流行和变化 在人类社区中流行的菌株中识别通过宿主选择控制的血脂并支持 诊断学发展。

Profiling and Mapping Core B Project Leaders: Kyu Rhee and D. Branch Moody Co-investigators: Jacob Mayfield ABSTRACT - Profiling and Mapping Core B Modern infectious disease research relies fundamentally on genomic maps of the major pathogens. With the recent development of whole-organism metabolomics profiling tools, comprehensively mapping the M. tuberculosis (Mtb) metabolome is now feasible. Core B supports mass spectrometry-based profiling of Mtb metabolites to support Projects 1, 2 and 3 that focus on discovery, drugs and diagnostics, respectively. The Core will carry out whole-organism lipidomic and metabolomic profiling, archive datasets and use modern bioinformatic methods to generate metabo-lipidomic maps of Mtb. Maps are comprised of a structured listing of all metabolite subclasses, a list of all named metabolites within each class, and links of all named metabolites to mass values and other biological variables. We previously generated the MycoMap Database, which is the largest existing map of 183 mycobacterial metabolite classes linked to ~195,000 accurate mass values. We will now expand the database by adding newly discovered lipids generated in Projects 1, 2 and 3. Supporting Projects 1 and 2, we will solve the Mycolate Outer Membrane Lipid Map, which describes compounds located at the host-pathogen barrier and involved in drug penetration. Supporting Projects 1 and 3, the core will measure metabolite variation among Mtb strains from South African patients to generate the Human Mtb Strain Lipid Variation Database. This database will describe the prevalence and variation of lipids among strains circulating in human communities to identify lipids under control by host selection and to support diagnostics development.