Saxena Deepak, Caufield Page W, Li Yihong, Brown Stuart, Song Jinmei, Norman Robert
Department of Basic Science and Craniofacial Biology, New York University College of Dentistry, New York, NY 10010, USA.
J Clin Microbiol. 2008 Sep;46(9):2868-73. doi: 10.1128/JCM.01000-08. Epub 2008 Jul 2.
Streptococcus mutans is one of several members of the oral indigenous biota linked with severe early childhood caries (S-ECC). Because most humans harbor S. mutans, but not all manifest disease, it has been proposed that the strains of S. mutans associated with S-ECC are genetically distinct from those found in caries-free (CF) children. The objective of this study was to identify common DNA fragments from S. mutans present in S-ECC but not in CF children. Using suppressive subtractive hybridization, we found a number of DNA fragments (biomarkers) present in 88 to 95% of the S-ECC S. mutans strains but not in CF S. mutans strains. We then applied machine learning techniques including support vector machines and neural networks to identify the biomarkers with the most predictive power for disease status, achieving a 92% accurate classification of the strains as either S-ECC or CF associated. The presence of these gene fragments in 90 to 100% of the 26 S-ECC isolates tested suggested their possible functional role in the pathogenesis of S. mutans associated with dental caries.
变形链球菌是与重度幼儿龋（S-ECC）相关的几种口腔固有生物群成员之一。由于大多数人都携带着变形链球菌，但并非所有人都表现出疾病症状，因此有人提出，与S-ECC相关的变形链球菌菌株在基因上与无龋（CF）儿童中发现的菌株不同。本研究的目的是鉴定存在于S-ECC患儿而非CF儿童体内的变形链球菌的常见DNA片段。使用抑制性消减杂交技术，我们发现了一些DNA片段（生物标志物），这些片段存在于88%至95%的S-ECC变形链球菌菌株中，但不存在于CF变形链球菌菌株中。然后，我们应用包括支持向量机和神经网络在内的机器学习技术，来识别对疾病状态具有最强预测能力的生物标志物，实现了将菌株准确分类为与S-ECC或CF相关的准确率达到92%。在测试的26株S-ECC分离株中，90%至100%存在这些基因片段，这表明它们在与龋齿相关的变形链球菌发病机制中可能具有功能作用。
