介绍

背景

“组学”技术在细菌性阴道病（BV）研究中的应用揭示了健康患者和细菌性阴道病患者阴道微生物组在组成和规模上的巨大差异。与专注于单个或少数物种的扩增子测序和霰弹枪宏基因组方法相比，在全系统水平上研究阴道微生物组的转录组可以深入了解活跃表达的功能以及健康和疾病状态之间的差异。

结果

我们对来自三项研究的阴道亚转录组进行了荟萃分析，分为探索性（n = 42）和验证性（n = 297）数据集，考虑了测序数据的组成性质以及健康和细菌性阴道炎微生物组之间的规模差异。在探索性数据集上进行差异表达分析，我们确定了与健康状态和BV相关的微生物采用的多种策略来逃避宿主阳离子抗菌肽（camp）；bv相关物种抵抗和抵消阴道低pH值的推测机制；以及破坏阴道上皮完整性以建立粘附和生物膜形成位点的潜在方法。此外，我们在BV种群中发现了几个不同的功能亚群，这些亚群由参与运动、趋化性、生物膜形成和辅因子生物合成的基因区分。在使用KEGG同源术语而不是群落状态类型在验证数据集中定义健康和BV的分子状态后，差异表达分析证实了早期关于健康和BV微生物组中CAMP抗性和损害上皮屏障完整性的观察结果，并支持了BV群体中运动与非运动亚群的存在。这些发现与所使用的酶分类系统（KEGG或EggNOG）无关。

结论

我们的研究结果强调，在考虑微生物组在疾病中的作用时，需要关注功能而不是分类差异，并确定作为潜在细菌性脑膜炎治疗靶点的进一步研究途径。

Background
The application of ‘-omics’ technologies to study bacterial vaginosis (BV) has uncovered vast differences in composition and scale between the vaginal microbiomes of healthy and BV patients. Compared to amplicon sequencing and shotgun metagenomic approaches focusing on a single or few species, investigating the transcriptome of the vaginal microbiome at a system-wide level can provide insight into the functions which are actively expressed and differential between states of health and disease.

Results
We conducted a meta-analysis of vaginal metatranscriptomes from three studies, split into exploratory (n = 42) and validation (n = 297) datasets, accounting for the compositional nature of sequencing data and differences in scale between healthy and BV microbiomes. Conducting differential expression analyses on the exploratory dataset, we identified a multitude of strategies employed by microbes associated with states of health and BV to evade host cationic antimicrobial peptides (CAMPs); putative mechanisms used by BV-associated species to resist and counteract the low vaginal pH; and potential approaches to disrupt vaginal epithelial integrity so as to establish sites for adherence and biofilm formation. Moreover, we identified several distinct functional subgroups within the BV population, distinguished by genes involved in motility, chemotaxis, biofilm formation and co-factor biosynthesis. After defining molecular states of health and BV in the validation dataset using KEGG orthology terms rather than community state types, differential expression analysis confirmed earlier observations regarding CAMP resistance and compromising epithelial barrier integrity in healthy and BV microbiomes and also supported the existence of motile vs. non-motile subgroups in the BV population. These findings were independent of the enzyme classification system used (KEGG or EggNOG).

Conclusions
Our findings highlight a need to focus on functional rather than taxonomic differences when considering the role of microbiomes in disease and identify pathways for further research as potential BV treatment targets.

代码

文章提供了画图代码和输入数据：

• https://github.com/scottdossantos/dossantos2024study/tree/main： 从该链接下载脚本；

参考

• Vaginal metatranscriptome meta-analysis reveals functional BV subgroups and novel colonisation strategies