Imangaliyev Sultan, Keijser Bart, Crielaard Wim, Tsivtsivadze Evgeni
Top Institute Food and Nutrition, Wageningen, The Netherlands; Research Group Microbiology and Systems Biology, TNO Earth, Environmental and Life Sciences, Zeist, The Netherlands; Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam, Amsterdam, The Netherlands.
Top Institute Food and Nutrition, Wageningen, The Netherlands; Research Group Microbiology and Systems Biology, TNO Earth, Environmental and Life Sciences, Zeist, The Netherlands.
Methods. 2015 Jul 15;83:28-35. doi: 10.1016/j.ymeth.2015.03.017. Epub 2015 Apr 2.
We use Human Microbiome Project (HMP) cohort (Peterson et al., 2009) to infer personalized oral microbial networks of healthy individuals. To determine clustering of individuals with similar microbial profiles, co-regularized spectral clustering algorithm is applied to the dataset. For each cluster we discovered, we compute co-occurrence relationships among the microbial species that determine microbial network per cluster of individuals. The results of our study suggest that there are several differences in microbial interactions on personalized network level in healthy oral samples acquired from various niches. Based on the results of co-regularized spectral clustering we discover two groups of individuals with different topology of their microbial interaction network. The results of microbial network inference suggest that niche-wise interactions are different in these two groups. Our study shows that healthy individuals have different microbial clusters according to their oral microbiota. Such personalized microbial networks open a better understanding of the microbial ecology of healthy oral cavities and new possibilities for future targeted medication. The scripts written in scientific Python and in Matlab, which were used for network visualization, are provided for download on the website http://learning-machines.com/.
我们使用人类微生物组计划（HMP）队列（彼得森等人，2009年）来推断健康个体的个性化口腔微生物网络。为了确定具有相似微生物谱的个体的聚类情况，将共正则化谱聚类算法应用于该数据集。对于我们发现的每个聚类，我们计算个体每个聚类中决定微生物网络的微生物物种之间的共现关系。我们的研究结果表明，从不同生态位获取的健康口腔样本在个性化网络水平上的微生物相互作用存在若干差异。基于共正则化谱聚类的结果，我们发现两组个体的微生物相互作用网络拓扑结构不同。微生物网络推断的结果表明，这两组个体在生态位特异性相互作用方面存在差异。我们的研究表明，健康个体根据其口腔微生物群具有不同的微生物聚类。这种个性化的微生物网络有助于更好地理解健康口腔的微生物生态学，并为未来的靶向药物治疗提供了新的可能性。用于网络可视化的用科学Python和Matlab编写的脚本可在网站http://learning-machines.com/上下载。
