VISTA (Vaginal Inference of Subspecies and Typing Algorithm) mgCST and mgSs reference models

Data and code to run the VISTA and the app: https://github.com/JHolm-Lab/VISTA<b>Citation</b>: Williams A, Maros A, France MT, Ravel J, Holm JB.2026. Not all vaginal microbiomes are equal: functional context shapes immune landscapes. mBio 17:e03645-25. https://doi.org/10.1128/mbio.03645-25<br>Unlike other parts of the body, a healthy vaginal microbiome is usually simple, with just a few types of bacteria—mostly <i>Lactobacillus</i> species. When the vaginal microbiome becomes more diverse and includes bacteria like <i>Gardnerella</i>, <i>Sneathia</i>, <i>Prevotella</i>, or <i>“Candidatus Lachnocurva vaginae”</i>, it’s considered less optimal and can increase the risk of reproductive and urinary health problems.<br>To describe these differences, scientists often use a system called <b>Community State Types (CSTs)</b>, which groups vaginal microbiomes based on the types and amounts of lactic acid–producing bacteria they contain. For example:CST I: mostly <i>Lactobacillus crispatus</i>CST II: mostly <i>Lactobacillus gasseri</i>CST III: mostly <i>Lactobacillus iners</i>CST IV: mostly diverse anaerobic bacteriaCST V: mostly <i>Lactobacillus jensenii</i>However, this system doesn’t capture the full complexity. Many strains and species in the vaginal microbiome go undetected with traditional methods. These hidden differences can be important for understanding how the microbiome affects health.To dig deeper, researchers look at the <b>genetic makeup</b> of the bacteria—specifically, the full set of genes found in each species. These genetic groupings are called <b>metagenomic subspecies (mgSs)</b>. When you combine all the mgSs in a sample, you get a <b>metagenomic Community State Type (mgCST)</b>, which gives a more detailed picture of how the microbiome might be influencing health.<br>This software package, VISTA (Vaginal Inference of Subspecies and Typing Algorithm), allows for classification of vaginal metagenomes to mgCSTs.

用于运行VISTA及相关应用程序的数据与代码。与身体其他部位不同，健康的阴道微生物组通常结构简单，仅包含少数几种细菌——其中大部分为<i>乳杆菌属（Lactobacillus）</i>物种。当阴道微生物组多样性增加，且包含<i>加德纳菌属（Gardnerella）</i>、<i>斯奈蒂亚菌属（Sneathia）</i>、<i>普雷沃菌属（Prevotella）</i>或<i>"阴道候选弯杆菌（Candidatus Lachnocurva vaginae）"</i>等细菌时，其状态被认为是非最优的，并可能增加生殖及泌尿系统健康问题的风险。<br>为描述这些差异，科学家们常采用<b>群落状态类型（Community State Types, CSTs）</b>系统——该系统根据阴道微生物组中乳酸菌的种类及数量对其进行分组。例如：CST I：主要为<i>卷曲乳杆菌（Lactobacillus crispatus）</i>CST II：主要为<i>加氏乳杆菌（Lactobacillus gasseri）</i>CST III：主要为<i>惰性乳杆菌（Lactobacillus iners）</i>CST IV：主要为多样的厌氧菌CST V：主要为<i>詹氏乳杆菌（Lactobacillus jensenii）</i>然而，该系统无法捕捉全部复杂性。阴道微生物组中的许多菌株及物种难以通过传统方法检测到，而这些隐藏的差异对于理解微生物组如何影响健康至关重要。<br>为深入研究，研究者们分析细菌的<b>基因组成</b>——具体而言，是每个物种所含的全部基因。这些基因分组被称为<b>宏基因组亚种（metagenomic subspecies, mgSs）</b>。将样本中所有mgSs组合起来，即可得到<b>宏基因组群落状态类型（metagenomic Community State Type, mgCST）</b>，它能更详细地揭示微生物组对健康的潜在影响。<br>本软件包VISTA（阴道亚种推断与分型算法，Vaginal Inference of Subspecies and Typing Algorithm）可实现阴道宏基因组向mgCSTs的分类。