Department of Pathology, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA.
Kaleido Biosciences, Lexington, MA, 02421, USA.
Genome Med. 2020 Jul 3;12(1):59. doi: 10.1186/s13073-020-00758-x.
Dietary glycans, widely used as food ingredients and not directly digested by humans, are of intense interest for their beneficial roles in human health through shaping the microbiome. Characterizing the consistency and temporal responses of the gut microbiome to glycans is critical for rationally developing and deploying these compounds as therapeutics.
We investigated the effect of two chemically distinct glycans (fructooligosaccharides and polydextrose) through three clinical studies conducted with 80 healthy volunteers. Stool samples, collected at dense temporal resolution (~ 4 times per week over 10 weeks) and analyzed using shotgun metagenomic sequencing, enabled detailed characterization of participants' microbiomes. For analyzing the microbiome time-series data, we developed MC-TIMME2 (Microbial Counts Trajectories Infinite Mixture Model Engine 2.0), a purpose-built computational tool based on nonparametric Bayesian methods that infer temporal patterns induced by perturbations and groups of microbes sharing these patterns.
Overall microbiome structure as well as individual taxa showed rapid, consistent, and durable alterations across participants, regardless of compound dose or the order in which glycans were consumed. Significant changes also occurred in the abundances of microbial carbohydrate utilization genes in response to polydextrose, but not in response to fructooligosaccharides. Using MC-TIMME2, we produced detailed, high-resolution temporal maps of the microbiota in response to glycans within and across microbiomes.
Our findings indicate that dietary glycans cause reproducible, dynamic, and differential alterations to the community structure of the human microbiome.
作为食品成分广泛使用且不能被人体直接消化的膳食糖聚糖，通过塑造微生物组，对人类健康具有有益作用，因此受到了强烈关注。准确描述微生物组对糖聚糖的一致性和时间响应，对于合理开发和应用这些化合物作为治疗方法至关重要。
我们通过 80 名健康志愿者参与的三项临床研究，研究了两种化学结构不同的糖（低聚果糖和聚右旋糖）的作用。采集粪便样本，以密集的时间分辨率（10 周内每周约 4 次）收集，并通过 shotgun 宏基因组测序进行分析，从而能够详细描述参与者的微生物组。为了分析微生物组时间序列数据，我们开发了 MC-TIMME2（微生物计数轨迹无限混合模型引擎 2.0），这是一种基于非参数贝叶斯方法的专用计算工具，用于推断由扰动和共享这些模式的微生物群引起的时间模式。
无论化合物剂量或聚糖摄入顺序如何，所有参与者的整体微生物组结构以及个体分类群都迅速、一致且持久地发生变化。聚右旋糖还会引起微生物碳水化合物利用基因丰度的显著变化，但低聚果糖则不会。使用 MC-TIMME2，我们在微生物组内和跨微生物组产生了详细的、高分辨率的糖聚糖响应时间图谱。
我们的研究结果表明，饮食糖聚糖会引起人类微生物组群落结构的可重复、动态和差异变化。
