Computational Biology and Medical Ecology Lab, State Key Lab of Genetic Resources and Evolution, Kunming Institute of Zoology, The Chinese Academy of Sciences, Kunming, 650223, China.
Sci Rep. 2017 Oct 16;7(1):13259. doi: 10.1038/s41598-017-12959-3.
Recent advances in the HMP (human microbiome project) research have revealed profound implications of the human microbiome to our health and diseases. We postulated that there should be distinctive features associated with healthy and/or diseased microbiome networks. Following Occam's razor principle, we further hypothesized that triangle motifs or trios, arguably the simplest motif in a complex network of the human microbiome, should be sufficient to detect changes that occurred in the diseased microbiome. Here we test our hypothesis with six HMP datasets that cover five major human microbiome sites (gut, lung, oral, skin, and vaginal). The tests confirm our hypothesis and demonstrate that the trios involving the special nodes (e.g., most abundant OTU or MAO, and most dominant OTU or MDO, etc.) and interactions types (positive vs. negative) can be a powerful tool to differentiate between healthy and diseased microbiome samples. Our findings suggest that 12 kinds of trios (especially, dominantly inhibitive trio with mixed strategy, dominantly inhibitive trio with pure strategy, and fully facilitative strategy) may be utilized as in silico biomarkers for detecting disease-associated changes in the human microbiome, and may play an important role in personalized precision diagnosis of the human microbiome associated diseases.
人类微生物组计划（HMP）研究的最新进展揭示了人类微生物组对我们健康和疾病的深远影响。我们推测，健康和/或患病的微生物组网络应该具有独特的特征。根据奥卡姆剃刀原理，我们进一步假设三角形基序或三元组（可以说是人类微生物组复杂网络中最简单的基序）足以检测到患病微生物组中发生的变化。在这里，我们使用涵盖五个主要人体微生物组部位（肠道、肺部、口腔、皮肤和阴道）的六个 HMP 数据集来检验我们的假设。测试结果证实了我们的假设，并表明涉及特殊节点（例如，最丰富的 OTU 或 MAO，以及最占优势的 OTU 或 MDO 等）和相互作用类型（阳性与阴性）的三元组可以成为区分健康和患病微生物组样本的有力工具。我们的研究结果表明，12 种三元组（特别是混合策略占主导地位的抑制性三元组、纯策略占主导地位的抑制性三元组和完全促进性策略）可用作检测人类微生物组中与疾病相关变化的计算生物标志物，并可能在与人类微生物组相关疾病的个性化精准诊断中发挥重要作用。
