Defining stable microbial communities through functional interrogation of microbiomes

胃肠道（GIT）是一个复杂而稳定的微生物群落的家园，为宿主带来了许多益处。在过去的80年里，通过饮食补充亚治疗剂量的抗生素（抗生素生长促进剂; AGP），提高了生产效率并减少了肠道感染，从而增加了牲畜GIT中的微生物群落。然而，由于对抗生素耐药性（AMR）上升的担忧，AGP正在逐步淘汰;迫切需要替代品。由于需要在GIT中移植和坚持，与粪便微生物组移植的成功有关，注意力已经从使用单一菌株益生菌转移到合成微生物群落。在这个为期五年的研究计划中，我们建议开发有效的基因组和计算管道，以确定稳定的微生物群落，这些微生物群落可用于为家禽的GIT发展提供种子，并帮助建立健康和富有成效的微生物组。提出了三个目标：目标1。开发创新的计算工具，用于准确推断微生物组的分类和功能组成。元转录组学数据集有能力产生对微生物组功能的机械见解。为了充分利用它们的潜力，我们将开发基于集成方法的下一代工具，其中功能和分类注释被自举以提供准确的分类。目标2.构建基于系统的模型，以揭示微生物组内的功能依赖性。为了更好地了解微生物组的功能，使用来自Aim 1的注释，我们将生成微生物群落代谢的预测模型。应用在家禽的背景下，这些模型将使我们能够快速预测改变社区组成的功能影响，以及宿主营养物质获取的任何后果。AIM3.设计新颖的社区益生菌以改善家禽健康。通过社区荟萃分析确定的稳定关联微生物的集团将通过Aim 2中建立的预测代谢模型进行研究，以确定促进家禽肠道健康的合成微生物群落。这些社区的效力将通过已建立的战略伙伴关系得到验证。支持这项研究计划的是一个才华横溢的计算生物学家团队，包括本科生和研究生，以及博士后研究员。开发高性能计算，微生物组分析和系统生物学的互补技能，该计划的学员将获得多样化的培训经验，为他们在学术界和工业界的众多职业机会做好准备。与家禽健康专家建立合作关系，该计划将为推动微生物组动态的分子相互作用提供基本见解，并建立促进家禽健康的新合成社区。

The gastrointestinal tract (GIT) is home to a complex, yet stable, community of microbes conferring numerous benefits to their host. Over the past 80 years, microbial communities in the GITs of livestock have been augmented through dietary supplementation of sub-therapeutic doses of antibiotics (antibiotic growth promotants; AGPs), enhancing production efficiency and reducing enteric infections. However, due to concerns over the rise of anti-microbial resistance (AMR), AGPs are being phased out; alternatives are urgently required. With a need to engraft and persist in the GIT, allied to the success of fecal microbiome transplants, attention has shifted from the use of single strain probiotics, to synthetic microbial communities. In this five-year research program, we propose to develop effective genomic and computational pipelines to identify stable microbial communities that can be used to seed the developing GIT of poultry and help establish a healthy and productive microbiome. Three aims are proposed: AIM1. Develop innovative computational tools for accurately inferring taxonomic and functional compositions of microbiomes. Metatranscriptomics datasets have the power to yield mechanistic insights into microbiome function. To fully exploit their potential, we will develop next generation tools, based on ensemble methods, in which functional and taxonomic annotations are reciprocally bootstrapped to deliver accurate classifications. AIM2. Construct systems-based models to reveal functional dependencies within microbiomes. To better understand microbiome functionality, using annotations derived from Aim1, we will generate predictive models of microbial community metabolism. Applied in the context of poultry, these models will allow us to rapidly predict the functional impact of altering community composition, together with any consequence in nutrient acquisition by the host. AIM3. Design novel community probiotics to improve poultry health. Cliques of stably associating microbes, identified through community meta-analyses, will be investigated through predictive metabolic models established in Aim2, to identify synthetic microbial communities that promote poultry gut health. The efficacy of these communities will be validated through established strategic partnerships. Supporting this program of research is a talented team of computational biologists, including undergraduate and graduate students, together with postdoctoral fellows. Developing complementary skills in high-performance computing, microbiome analysis and systems biology, trainees in this program will receive a diverse training experience, preparing them for a multitude of career opportunities in academia, as well as industry. Together with established collaborations with experts in poultry health, this program will deliver fundamental insights into the molecular interactions that drive microbiome dynamics and establish new synthetic communities that promote poultry health.