Computational models identifying within-host evolution of pathogens using high-throughput DNA sequencing

使用高通量 DNA 测序识别病原体宿主内进化的计算模型

• 批准号: RGPIN-2017-04860
• 负责人: Long, Quan
• 金额: $ 3.5万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=744268
• 关键词: Computational; models; identifying; within; host

Antimicrobial resistance (AMR) is a global threat to animals. However, its occurrence and transmission are poorly understood for pathogens infecting important animals, e.g. beef and dairy cattle. Each infection represents a population of multiple strains of a pathogen with different sensitivities to antimicrobials. Often AMR occurs when this within-host population evolves under the selective pressure of drug treatments in conjunction with immune responses. Huge leaps in next-generation DNA sequencing (NGS) technology allow us to sequence within-host populations of a pathogen without the need to grow them in the laboratory (i.e., uncultured), offering materials to speed up the characterization of within-host evolution and transmission of AMR. However, the lack of suitable computational models blocks this promising research. First, in the uncultured sample, pathogen DNA of multiple strains is collected and sequenced together in pools. To access genomic information at individual-level, novel computational methods are needed to estimate the identity and frequency of strains or haplotypes. This is a fundamental technical roadblock to many critical analyses in pooled sequencing. Second, assuming the above technical barriers are conquered, to scientifically examine genes and strains under selection, standard population genetic models developed for multicellular organisms need to be extended in the context of within-host pathogen evolution. For instance, what should we use as a neutral (without selection) expectation of strain or haplotype diversity, and how do we best estimate alleles of ancestors, the founding strains of the pathogen acquired by a host? My long-term goal is to understand the mechanism of AMR by genomic analysis of within- and between-host evolution and ultimately contribute to its prevention and control in agriculture. Supported by this NSERC Discovery Grant, my first short-term goal is to develop novel computational models to resolve the methodological challenges described. This paves the way for my second short-term goal to benefit the research of AMR of Treponema spp. and E. coli that infect cattle in Alberta, by identifying genetic underpinnings of within-host selection.Fundamentally, the proposed work augments the standard theoretical models of pathogen evolution to better account for within-host environments. Practically, the ability to identify genes that confer AMR will be relevant to agricultural practice in Canada.

抗生素耐药性（AMR）是对动物的全球性威胁。然而，对于感染重要动物（例如肉牛和奶牛）的病原体，其发生和传播知之甚少。每种感染都代表了一种病原体的多个菌株，这些菌株对抗菌剂具有不同的敏感性。通常，当这种宿主内群体在药物治疗的选择性压力下与免疫反应相结合时，就会发生AMR。下一代DNA测序（NGS）技术的巨大飞跃使我们能够对病原体的宿主内种群进行测序，而无需在实验室中培养它们（即，未培养的），提供材料，以加快表征宿主内的演变和AMR的传播。然而，缺乏合适的计算模型阻碍了这一有前途的研究。首先，在未培养的样品中，收集多个菌株的病原体DNA并在池中一起测序。为了获得个体水平的基因组信息，需要新的计算方法来估计菌株或单倍型的身份和频率。这是合并测序中许多关键分析的基本技术障碍。第二，假设上述技术障碍被克服，科学地检查基因和菌株的选择，标准的多细胞生物体开发的群体遗传模型，需要在宿主内病原体进化的背景下进行扩展。例如，我们应该使用什么作为菌株或单倍型多样性的中性（无选择）预期，以及我们如何最好地估计祖先的等位基因，即宿主获得的病原体的创始菌株？我的长期目标是通过对宿主内和宿主间进化的基因组分析来了解AMR的机制，并最终为农业上的预防和控制做出贡献。在NSERC发现基金的支持下，我的第一个短期目标是开发新的计算模型来解决所描述的方法学挑战。这为我的第二个短期目标铺平了道路，即有利于密螺旋体AMR的研究。 和E.大肠杆菌感染的牛在阿尔伯塔，通过识别宿主内选择的遗传基础。从根本上说，拟议的工作增强了病原体进化的标准理论模型，以更好地解释宿主内环境。实际上，鉴定赋予AMR的基因的能力将与加拿大的农业实践有关。