不同妊娠状态下女性口腔微生物的结构差异性

【背景】妊娠期妇女口腔微生物改变与口腔疾病及全身性疾病之间有显著相关性。【目的】比较不同妊娠状态下女性口腔微生物结构的差异，探讨该差异与不同妊娠状态间的关联性。【方法】选取18名孕妇和9名非孕妇为研究对象（28.2±3）岁]，分为妊娠期糖尿病组gestational diabetes mellitus，GDM，年龄（28.9±3.6）岁，孕周（30.1±3.2）周]、妊娠期非糖尿病组non-diabetic pregnant women，PW，年龄（27.9±3.0）岁，孕周（28.6±4.7）周]和非妊娠期非糖尿病组non-pregnant women，NPW，年龄（27.7±2.1）岁]，每组9名，收集口腔唾液（saliva，S）和龈上牙菌斑（supragingival dental plaque，D），采取Illumina Novaseq测序平台针对细菌16S rRNA基因的V3-V4可变区进行测序，以SILVA为参考数据库使用朴素贝叶斯分类器对特征序列进行分类学注释，利用QIIME软件对样本进行生物信息学分析。【结果】三组中唾液及牙菌斑微生物差异比较显示：D-GDM中二氧化碳嗜纤维菌属检出量高于D-PW，而月形单胞菌属检出量显著低于D-PW；S-GDM中产气单胞菌属、拟杆菌属等厌氧菌属检出量高于S-PW，韦荣氏菌属检出量低于S-PW；D-PW中纤毛菌属、普氏菌属和月形单胞菌属检出量显著高于D-NPW；D-NPW中产气单胞菌属、放线杆菌属、二氧化碳嗜纤维杆菌属、奈瑟菌属、链球菌属和劳特罗氏菌属等检出量高于D-PW；S-PW中韦荣菌属、普氏菌属、链球菌属和卟啉单胞菌属检出量低于S-NPW；D-GDM中福赛斯坦纳菌属、纤毛菌属检出量高于D-NPW，劳特罗氏菌属检出量低于D-NPW；S-GDM中密螺旋体属、弯曲杆菌属检出量高于S-NPW，链球菌属低于S-NPW。在种水平上，S-GDM菌群中具核梭杆菌检出量显著高于S-PW，S-GDM菌群中牙龈卟啉单胞菌及福赛斯坦纳菌检出量与S-PW差异无统计学意义，产黑普氏菌检出量低于S-PW；S-PW中牙龈卟啉单胞菌、产黑普氏菌和福赛斯坦纳菌检出量均显著高于S-NPW。【结论】孕妇妊娠期糖尿病将增加口腔微生物群厌氧菌检出率，GDM与牙龈卟啉单胞菌、福赛斯坦纳菌和产黑普氏菌等牙周炎致病菌相关性不能确定。

Differences in oral microbiota structure of females in different states of pregnancy

Background] The oral microbiota changes have significant correlations with oral diseases and systemic diseases in pregnant women. Objective] To compare the oral microbiota structure of females in different pregnancy states and explore the correlation between the structure difference and different pregnancy states. Methods] Eighteen pregnant women and nine non-pregnant women were selected for the study and assigned into three groups (n=9):gestational diabetes mellitus (GDM, mean age of (28.9±3.6) years, mean pregnancy of (30.1±3.2) weeks), non-diabetic pregnant women (PW, mean age of (27.9±3.0) years, mean pregnancy of (28.6±4.7) weeks) and non-pregnant women (NPW, mean age of (27.7±2.1) years). Oral saliva (S) and supragingival dental plaque (D) samples were collected. The Illumina Novaseq platform was used to sequence the V3-V4 variable region of bacterial 16S rRNA. SILVA was used for the taxonomical annotation of the characteristic sequences, and QIIME was employed to perform the bioinformatics analysis. Results] The D-GDM samples had higher detection rate of Capnocytophage and lower detection rate of Selenomonas than the D-PW samples. The S-GDM samples had higher detection rate of anaerobic bacteria such as Aeromonas and Bacteroides than the S-PW samples and lower detection rate of Veillonella than the S-PW samples. The D-PW samples had higher detection rates of Leptotrichia, Prevotella, and Selenomonas and lower detection rates of Aeromonas, Actinobacillus, Capnocytophage, Neisseria, Lautropia, and Streptococcus than the D-NPW samples. The S-PW samples had lower detection rate of Veillonella, Prevotella, Streptococcus, and Porphyromonas than the S-NPW samples. The D-GDM samples had high detection rate of Tannerella and Leptotrichia and lower detection rate of Roseburia than the D-NPW samples. The S-GDM samples had high detection rates of Treponema and Campylobacter and lower detection rate of Streptococcus than the S-NPW samples. At the species level, the S-GDM samples had higher detection rate of Fusobacterium nucleatum, similar detection rates of Porphyromonas gingivalis and Tannerella forsythia, and lower detection rate of Prevotella nigrescens than the S-PW samples. The S-PW samples had high detection rates of P. gingivalis, P. nigrescens, and T. forsythia than the S-NPW samples.Conclusion] GDM will increase the detection rate of anaerobic bacteria in the oral cavity, and the correlations between GDM and periodontitis-causing bacteria such as P. gingivalis, T. forsythia, and P. nigrescens are uncertain.