EDGE FGT: Tools for host-microbiome protein-protein interaction discovery

宿主-微生物的相互作用对于正常的生理和免疫系统的发育至关重要，现在有大量证据表明这些相互作用与广泛的宿主表型有关，包括促进植物的耐旱性，鸟类的嗅觉交流与梳理，人类的运动能力和果蝇的交配偏好。高度特异性的微生物相关分子模式（MAMPs），其中许多涉及蛋白质，直接向存在于宿主上皮和宿主免疫组织中的模式识别受体发出信号，直接调节宿主表型。虽然病原体蛋白质-蛋白质相互作用（PPIs）已经得到了很好的研究，但令人惊讶的是，对宿主与其内源性微生物群之间的PPIs的研究却很少。其中研究得最好的例子是与动物toll样受体或植物鞭毛蛋白敏感受体的相互作用，但近年来出现了其他有趣的例子，如植物病原体丁香假单胞菌中E3泛素连接酶的模仿和可降解宿主代谢激素的共生衍生蛋白。近年来，高通量PPI研究产生了大量的实验数据，但只有一小部分代表物种间相互作用，这部分主要是宿主-病原体相互作用，而非人类物种明显缺乏。我们的目标是开发PPI发现工具，并让学生有机会扩展他们的生物信息学技能。在这笔拨款中，我们将建立与测序兼容的超高通量实验筛选方法，用于发现宿主微生物组ppi。我们的平台能够筛选复杂宿主与其微生物群之间大约10^8种可能的相互作用。我们将在人体和根茎微生物组中试验和验证我们的方法。所有资源将向公众提供，并提供培训。同时，我们将开发一套计算工具来分配宿主微生物组基于ppi的功能。我们的目标是扩展和整合我们的PPI推断方法，并建立一个利用推断以及实验验证的PPI和微生物组组成数据的平台，使研究人员能够研究任何植物或动物宿主的宿主-微生物组相互作用。此外，为了扩大学生对计算生物学的整体兴趣，我们将推出一系列以宿主-微生物相互作用为中心的生物信息学黑客马拉松。学生们被黑客马拉松所吸引，根据我们的经验，它们为那些在计算生物学领域一直代表性不足的学生提供了一个很好的接触机会。我们的年度黑客马拉松将以蛋白质结构为灵感的项目为中心，让学生在一个低压力、有趣和包容的环境中参与。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Host-microbe interactions are crucial for normal physiological and immune system development and substantial evidence now links these interactions with a wide range of host phenotypes, including promoting drought tolerance in plants, olfactory communication linked to preening in birds, athletic ability in humans, and mating preferences in fruit flies. Highly specific microbe-associated molecular patterns (MAMPs), many of which involve proteins, directly signal with pattern recognition receptors present on the host epithelium and in host immune tissue, directly modulating host phenotypes. Although pathogen protein-protein interactions (PPIs) have been well studied, the study of PPIs between hosts and their endogenous microbiota is surprisingly lacking. Among the best-studied examples are interactions with animals’ toll-like receptors or plants’ flagellin-sensitive receptor, but other intriguing examples have emerged in recent years, such as mimicry of E3 ubiquitin ligases in the plant pathogen Pseudomonas syringae and commensal-derived proteins that can degrade host metabolic hormones. High-throughput PPI studies have generated substantial experimental data in recent years, yet only a small fraction represents inter-species interactions and this fraction is largely dominated by host-pathogen interactions, with non-human species noticeably lacking. Our goal is to develop tools for PPI discovery and to engage students in opportunities to expand their bioinformatic skills. Within this grant, we will establish sequencing-compatible ultra-high-throughput experimental screening approaches for the discovery of host-microbiome PPIs. Our platforms enable screening the roughly 10^8 possible interactions between a complex host and its microbiome. We will pilot and validate our methods with human and rhizome microbiomes. All resources will be made publicly available and training will be provided. In parallel, we will develop a set of computational tools to assign host-microbiome PPI-based functions. We aim to expand and integrate our PPI inference methods and build a platform that leverages inferred as well as experimentally-verified PPIs and microbiome composition data to allow researchers to investigate the host-microbiome interactome of any plant or animal host. Additionally, to help broaden the overall interest and expose students to computational biology, we will launch a series of bioinformatics hackathon centered around host-microbe interactions. Students are drawn to hackathons and, in our experience, they have served as a great means of exposure for students historically underrepresented in computational biology. Our annual hackathons will center on protein structure-inspired projects for students to engage in a low-stress, fun and inclusive environment.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.