Identification of Genetic Markers of Susceptibility to Intracellular Bacterial Infection Using the Collaborative Cross Mouse Model

使用协作交叉小鼠模型鉴定细胞内细菌感染易感性的遗传标记

• 批准号: 10672355
• 负责人: Elke BergmannLeitner
• 金额: $ 17.17万
• 依托单位: GENEVA FOUNDATION
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10672355
• 关键词: Acceleration; Animal Disease Models; Animal Model; Anti-Bacterial Agents; Antigens; Artificial Intelligence; Bacteria; Bacterial Infections; Biological Models; Body Temperature; Body Weight decreased; Boutonneuse Fever; Cells; Clinical; Collaborations; Communicable Diseases; Computer Analysis; Data; Data Analyses; Disease; Disease susceptibility; Exhibits; Foundations; Frequencies; Future; Gene Targeting; Genes; Genetic; Genetic Determinism; Genetic Markers; Genetic Variation; Genome; Genomics; Health; Human; Immune; Immune response; Immune system; Immunity; Immunologics; Immunology; Immunotherapeutic agent; Inbred Mouse; Inbreeding; Individual; Infection; Interruption; Intravenous; Laboratories; Literature; Liver; Machine Learning; Maps; Maryland; Methods; Mining; Modeling; Molecular; Mouse Strains; Mus; Organ; Outcome; Output; Pathology; Phenotype; Population; Predisposition; Prognostic Marker; Public Health; Quantitative Trait Loci; Randomized; Recombinants; Reproducibility; Research; Research Personnel; Resistance; Resistance to infection; Resolution; Resources; Rickettsia; Rickettsia Infections; Rickettsia conorii; Rocky Mountain Spotted Fever; Role; Seminal; Serum; Spleen; System; Therapeutic; Therapeutic Intervention; Tick-Borne Diseases; Time; Universities; Vaccines; Variant; Work; acute infection; adaptive immune response; bioinformatics tool; biomarker identification; chemokine; cohort; comparative genomics; cytokine; data integration; diagnostic biomarker; disease phenotype; diversity and equity; genetic analysis; genetic approach; genomic locus; human disease; human model; human pathogen; insight; mouse genome; mouse model; multidisciplinary; novel; pathogen; peripheral blood; prophylactic; resilience; response; reverse genetics; targeted treatment; therapeutic development; therapeutic evaluation; tick-borne; tool; trait; transcriptomics; vaccine development

PROJECT SUMMARY Identification of the genetic and molecular mechanisms governing immunity against intracellular bacteria is imperative for understanding the host-pathogen-interplay and forms the basis for the development of therapeutic countermeasures. Previous attempts at increasing our understanding of this topic have relied on targeted interruption of individual genes or analysis natural genetic variability in natural populations. Herein, we propose to employ 1) animal models with pre-defined genetic variability, 2) cutting edge immunoprofiling, 3) comparative genomics, and 4) computational analyses to identify the immunological and genetic basis of sensitivity to Rickettsia infection. This approach employs the collaborative cross (CC) mice. This mouse resource involves a cohort of recombinant-inbred lines generated by randomizing the genetic diversity of existing inbred mouse resources. This pre-defined genetic diversity has significantly accelerated discovery of genetic determinants that regulate immunity against several pathogens as well as other non-infectious diseases. The CC mouse resource is distinct from other animal models as its high genetic diversity is comparable to that of human populations. Unlike in outbred animal models, each CC line reproducibly exhibits distinct phenotypes of disease susceptibility and immune profiles to pathogens. Our multi-disciplinary team will screen CC lines to establish the range of responses to the tick-borne human pathogen Rickettsia conorii. Using murine models of Rickettsia infection with well-established phenotypic difference in susceptibility to infection, we will screen initially CC mouse lines to encompass a detailed assessment of the disease phenotype (bacterial load, weight loss, body temperature, survival) and immunoprofiling of peripheral blood, spleen, and liver as relevant, representative organ. CC lines with extreme clinical and immunological phenotypes will then be selected for longitudinal in-depth immunoprofiling. Here, changes in the frequency of activated innate and antigen-specific adaptive cells, cytokine profiles in serum, and antibacterial activities of immune cells will be assessed throughout infection and disease resolution. Computational data integration and bioinformatics tools (machine learning) will be applied to establish the immune landscape of Rickettsia-specific immune responses to identify immune correlates that govern disease phenotype of each CC line. The short-term impact of the proposed work will be the identification of novel murine models that emulate differential immune responses to infection. These tools will enable researchers to test therapeutics and/or vaccines in a diverse system that, for the first time, has the potential to forecast responses in humans. Computational analysis will be performed to identify quantitative trait loci associated with disease phenotype and disease-specific immunoprofiles. This information will be the basis for the future identification of genes responsible for immunity against intracellular bacteria, which will have a significant long- term impact on our understanding of multiple rickettsial diseases.

项目摘要 对细胞内细菌免疫的遗传和分子机制的鉴定是 了解宿主-病原体相互作用的必要性，并形成治疗药物开发的基础 对策以前试图增加我们对这一主题的理解依赖于有针对性的 中断单个基因或分析自然群体中的自然遗传变异。在此，我们建议 采用1）具有预定遗传变异性的动物模型，2）最先进的免疫分析，3）比较 基因组学，和4）计算分析，以确定敏感性的免疫学和遗传基础， 立克次体感染。该方法采用协作杂交（CC）小鼠。此鼠标资源涉及一个 通过将现有近交系小鼠的遗传多样性随机化而产生的重组近交系群 资源这种预先定义的遗传多样性大大加快了发现遗传决定因素的速度， 调节对几种病原体以及其他非传染性疾病的免疫力。CC鼠标资源 与其他动物模型不同，因为其高遗传多样性与人类种群相当。 与远交动物模型不同，每个CC系可重复地表现出不同的疾病易感性表型 和对病原体的免疫特性。我们的多学科团队将筛选CC系列，以确定 对蜱传播的人类病原体康氏立克次体的反应。使用立克次体感染的小鼠模型， 由于在感染易感性方面存在明确的表型差异，我们将初步筛选CC小鼠品系， 包括疾病表型的详细评估（细菌负荷，体重减轻，体温， 存活）和作为相关代表性器官的外周血、脾和肝的免疫谱分析。CC线 具有极端临床和免疫表型的患者将被选择进行纵向深入研究。 免疫分析在这里，激活的先天性和抗原特异性适应性细胞，细胞因子 在整个感染和疾病过程中，将评估血清中的免疫细胞谱和免疫细胞的抗菌活性 分辨率将应用计算数据集成和生物信息学工具（机器学习）， 立克次体特异性免疫反应的免疫格局，以确定控制立克次体的免疫相关因素 每个CC系的疾病表型。拟议工作的短期影响将是确定新的 模拟对感染的不同免疫反应的鼠模型。这些工具将使研究人员能够 在一个多样化的系统中测试疗法和/或疫苗，这是第一次有可能预测 人类的反应。将进行计算分析，以确定与以下相关的数量性状基因座： 疾病表型和疾病特异性免疫谱。这些信息将成为未来的基础 鉴定负责对细胞内细菌免疫的基因，这将具有显著的长期- 长期影响我们对多种立克次体疾病的认识。