Assessing the Concordance Between Urogenital and Vaginal Microbiota: Can Urine Specimens Be Used as a Proxy for Vaginal Samples?
Assessing the Concordance Between Urogenital and Vaginal Microbiota: Can Urine Specimens Be Used as a Proxy for Vaginal Samples?
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DOI：
10.3389/fcimb.2021.671413
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发表时间：
2021
影响因子：
5.7
通讯作者：
Brotman RM
中科院分区：
文献类型：
--
作者：
Brown SE;Robinson CK;Shardell MD;Holm JB;Ravel J;Ghanem KG;Brotman RM
阴道微生物群在预防生殖道感染方面发挥着关键作用;然而，许多基于人群的女性健康研究并没有收集阴道样本。尿液样本的分子检测揭示了常见的阴道细菌。我们试图评估归档随机采集和清洁采集尿液样本的社区状态类型分配与育龄和围绝经期/绝经后女性配对阴道样本的一致程度。使用存档样本，我们评估了三项研究中女性的微生物群一致性：两项研究采用配对的阴道中期/随机捕获尿液（N=91名育龄参与者和N=13名绝经后参与者），一项研究采用配对的阴道中期/清洁捕获尿液（N=99名育龄参与者）。通过对16 S rRNA基因V3-V4区域的扩增子进行测序来表征微生物群组成，并将其分配给群落状态类型。利用群落状态类型的一致性和Yue-Clayton θ指数来衡量配对样本的相似性。微生物组组成分析II表明哪些分类群在配对的阴道和尿液样品中相对丰富。在育龄妇女中，随机捕获和清洁捕获尿液与配对阴道中段拭子的5种社区状态类型的一致性分别为89.0%和86.9%，Kappa统计表明几乎完全一致（κrandom-catch=.85，κclean-catch=.81，p<0.0001）。少数样本对不一致（23/190，12%），不一致对倾向于在分类为L的样本之间。惰性主导和/或低乳酸菌状态。当将微生物群二分为乳杆菌占主导地位的微生物群与低乳杆菌微生物群时，以及分别评估低乳杆菌群落状态IV型的三种亚型时，一致性和一致性保持相似。配对尿液/阴道样本的中位数相似性较高（θrandom-catch= 0.85，θclean-catch= 0.88），随机捕获和清洁捕获相似性评分的比较显示无显著差异（p= 0.80）。绝经后/绝经后女性的一致性和相似性较低，但一致性仍然很高（76.9%一致性，κrandom-catch= 0.64，θrandom-catch= 0.62）。分类学水平的分析证实了这些发现。随机捕获和清洁捕获尿液样本显示出与配对的阴道中段样本在细菌组成上的实质性一致，这表明泌尿生殖道微生物群可能是通过群落状态类型评估阴道微生物群整体组成的可靠代表。这些数据表明，尿液样本，适当的解释，可以作为替代开发的初步数据和假设生成的研究。
The vaginal microbiota play a key role in defense against reproductive tract infections; however, many population-based women’s health studies do not collect vaginal samples. Molecular examinations of urine samples have revealed common vaginal bacteria. We sought to assess the extent that community state type assignments of archived random-catch and clean-catch urine samples agreed with the paired vaginal samples in both reproductive-age and peri/post-menopausal women. Using archived samples, we evaluated the microbiota concordance among women in three studies: two with paired mid-vaginal/random-catch urine (N=91 reproductive-age participants and N=13 peri/post-menopausal participants), and one with paired mid-vaginal/clean-catch urine (N=99 reproductive-age participants). Microbiota composition was characterized by sequencing amplicons of the 16S rRNA gene V3-V4 regions and assigned to community state types. Similarity of paired samples was gauged using agreement of community state types and Yue-Clayton θ indices. Analysis of Composition of Microbiomes II indicated which taxa were differently relatively abundant in paired vaginal and urine samples. In reproductive-age women, random-catch and clean-catch urines were 89.0% and 86.9% concordant on five community state types with paired mid-vaginal swabs, and Kappa statistics indicated almost perfect agreement (κrandom-catch=.85, κclean-catch=.81, p<0.0001). A small number of pairs of samples were discordant (23/190, 12%), and discordant pairs tended to be between samples classified to L. iners-dominated and/or low-Lactobacillus states. Concordance and agreement remained similar when dichotomizing the microbiota to Lactobacillus-dominated versus low-Lactobacillus microbiota, as well as when evaluating separately the three subtypes of the low-Lactobacillus community state type IV. Median similarity of paired urine/vaginal samples was high (θrandom-catch=.85, θclean-catch=.88), and a comparison of the random-catch and clean-catch similarity scores showed no significant difference (p=.80). Concordance and similarity were lower for peri/post-menopausal women, but agreement remained substantial (76.9% concordant, κrandom-catch= 0.64, θrandom-catch=.62). Taxonomic-level analysis confirmed these findings. Random-catch and clean-catch urine samples showed substantial agreement on bacterial composition to paired mid-vaginal samples, indicating that the genitourinary microbiota may be a reliable proxy for assessing the overall composition of the vaginal microbiota via community state types. This data suggests that urine samples can, with proper interpretation, be utilized as a surrogate for developing preliminary data and hypothesis-generating studies.
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影响因子：
48
作者：
Callahan BJ;McMurdie PJ;Rosen MJ;Han AW;Johnson AJ;Holmes SP
通讯作者：
Holmes SP
影响因子：
4.6
作者：
Ammitzbøll N;Bau BPJ;Bundgaard-Nielsen C;Villadsen AB;Jensen AM;Leutscher PDC;Glavind K;Hagstrøm S;Arenholt LTS;Sørensen S
通讯作者：
Sørensen S
影响因子：
17.1
作者：
Gajer P;Brotman RM;Bai G;Sakamoto J;Schütte UM;Zhong X;Koenig SS;Fu L;Ma ZS;Zhou X;Abdo Z;Forney LJ;Ravel J
通讯作者：
Ravel J
影响因子：
5.2
作者：
Gliniewicz, Karol;Schneider, G. Maria;Forney, Larry J.
通讯作者：
Forney, Larry J.
影响因子：
3.1
作者：
Crowder, Hannah R.;Brown, Sarah E.;Brotman, Rebecca M.
通讯作者：
Brotman, Rebecca M.