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观点:利用肠道微生物群预测饮食、益生元和益生菌干预的个性化反应。

Perspective: Leveraging the Gut Microbiota to Predict Personalized Responses to Dietary, Prebiotic, and Probiotic Interventions.

机构信息

Institute for Systems Biology, Seattle, WA, USA.

Department of Bioengineering, University of Washington, Seattle, WA, USA.

出版信息

Adv Nutr. 2022 Oct 2;13(5):1450-1461. doi: 10.1093/advances/nmac075.

Abstract

Humans often show variable responses to dietary, prebiotic, and probiotic interventions. Emerging evidence indicates that the gut microbiota is a key determinant for this population heterogeneity. Here, we provide an overview of some of the major computational and experimental tools being applied to critical questions of microbiota-mediated personalized nutrition and health. First, we discuss the latest advances in in silico modeling of the microbiota-nutrition-health axis, including the application of statistical, mechanistic, and hybrid artificial intelligence models. Second, we address high-throughput in vitro techniques for assessing interindividual heterogeneity, from ex vivo batch culturing of stool and continuous culturing in anaerobic bioreactors, to more sophisticated organ-on-a-chip models that integrate both host and microbial compartments. Third, we explore in vivo approaches for better understanding of personalized, microbiota-mediated responses to diet, prebiotics, and probiotics, from nonhuman animal models and human observational studies, to human feeding trials and crossover interventions. We highlight examples of existing, consumer-facing precision nutrition platforms that are currently leveraging the gut microbiota. Furthermore, we discuss how the integration of a broader set of the tools and techniques described in this piece can generate the data necessary to support a greater diversity of precision nutrition strategies. Finally, we present a vision of a precision nutrition and healthcare future, which leverages the gut microbiota to design effective, individual-specific interventions.

摘要

人类对饮食、益生元和益生菌干预的反应常常存在差异。新出现的证据表明,肠道微生物群是这种人群异质性的关键决定因素。在这里,我们提供了一些主要的计算和实验工具的概述,这些工具被应用于关键的微生物群介导的个性化营养和健康问题。首先,我们讨论了在微生物群-营养-健康轴的计算模型方面的最新进展,包括统计、机制和混合人工智能模型的应用。其次,我们解决了用于评估个体间异质性的高通量体外技术,从粪便的离体批量培养和厌氧生物反应器中的连续培养,到更复杂的整合宿主和微生物区室的器官芯片模型。第三,我们探讨了更好地理解个性化、微生物群介导的饮食、益生元和益生菌反应的体内方法,从非人类动物模型和人类观察性研究,到人类喂养试验和交叉干预。我们强调了一些现有的、面向消费者的精准营养平台的例子,这些平台目前正在利用肠道微生物群。此外,我们还讨论了如何整合更广泛的工具和技术,以生成支持更多样化精准营养策略所需的数据。最后,我们提出了一个利用肠道微生物群来设计有效、个体特异性干预措施的精准营养和医疗保健的未来愿景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d826/9526856/ca8aca836bd4/nmac075fig1.jpg

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