The scientific community currently defines the human microbiome as all the bacteria, viruses, fungi, archaea, and eukaryotes that occupy the human body. When considering the variable locations, composition, diversity, and abundance of our microbial symbionts, the sheer volume of microorganisms reaches hundreds of trillions. With the onset of next generation sequencing (NGS), also known as high-throughput sequencing (HTS) technologies, the barriers to studying the human microbiome lowered significantly, making in-depth microbiome research accessible. Certain locations on the human body, such as the gastrointestinal, oral, nasal, and skin microbiomes have been heavily studied through community-focused projects like the Human Microbiome Project (HMP). In particular, the gastrointestinal microbiome (GM) has received significant attention due to links to neurological, immunological, and metabolic diseases, as well as cancer. Though HTS technologies allow deeper exploration of the GM, data informing the functional characteristics of microbiota and resulting effects on human function or disease are still sparse. This void is compounded by microbiome variability observed among humans through factors like genetics, environment, diet, metabolic activity, and even exercise; making GM research inherently difficult to study. This chapter describes an interdisciplinary approach to GM research with the goal of mitigating the hindrances of translating findings into a clinical setting. By applying tools and knowledge from microbiology, metagenomics, bioinformatics, machine learning, predictive modeling, and clinical study data from children with treatment-resistant epilepsy, we describe a proof-of-concept approach to clinical translation and precision application of GM research.

科学界目前将人体微生物组定义为占据人体的所有细菌、病毒、真菌、古细菌和真核生物。当考虑到我们微生物共生体的可变位置、组成、多样性和丰度时，微生物的绝对数量达到数百万亿。随着新一代测序 (NGS)，也称为高通量测序 (HTS) 技术的出现，研究人类微生物组的障碍显着降低，使深入的微生物组研究成为可能。人体的某些部位，例如胃肠道、口腔、鼻腔和皮肤微生物组，已经通过以社区为重点的项目（如人类微生物组计划 (HMP)）进行了大量研究。特别是，由于与神经、免疫和代谢疾病以及癌症的联系，胃肠道微生物组 (GM) 受到了极大的关注。尽管 HTS 技术允许对转基因进行更深入的探索，但有关微生物群功能特征及其对人类功能或疾病的影响的数据仍然很少。通过遗传、环境、饮食、代谢活动甚至运动等因素在人类中观察到的微生物组变异加剧了这种空白。使转基因研究本质上难以研究。本章描述了转基因研究的跨学科方法，其目标是减轻将研究结果转化为临床环境的障碍。通过应用微生物学、宏基因组学、生物信息学、机器学习、预测建模中的工具和知识，