Nutritional landscape and community interactions in the vaginal microbiome

阴道微生物组的营养状况和群落相互作用

基本信息

项目摘要

PROJECT SUMMARY The vaginal tract is a harsh, polymicrobial ecosystem that has an active immune response, is rich in cervicovaginal mucins, and has a robust microbiota. Bacterial persistence within this environment requires the ability of organisms to adapt to changes in nutrient availability and to interact with the other members of the microbiota. The vaginal microbiota is classified by five community state types, in which state types I, II, III, and V are dominated by Lactobacillus species, while community state type IV is marked by increased community diversity and is loosely termed “dysbiotic”. Our definition of what constitutes vaginal health is evolving; however, our understanding of the fundamental principles that impact community structure and function, and the role individual microbes have in community stability is unknown. Determining the interactions that contribute to persistence within this dynamic environment is challenging, as these are multifactorial in nature. Here, we propose interdisciplinary approaches to understand the microbial ecology of the vaginal tract and advance our basic knowledge of vaginal health. Our objective is to determine how the nutritional landscape within the vagina impacts microbial community assembly, structure, and interactions, that together, contribute to persistent colonization. We will define metal availability within the vaginal tract and use these data to understand how changes in the environment shape composition and function of bacterial communities. From this, we will identify differential importance of bioavailable metals for persistence and expansion of community members. We will investigate the mechanisms of metal ion homeostasis and determine their impact on cellular metabolism, cooperation, and competition within microbial communities. We will develop in silica models and validate mechanisms of metabolic interaction between members of the vaginal microbiota and determine the role of these interactions in community synergy. Our goal is to define how vaginal ecology drives community interactions and crosstalk to promote colonization in this complex environment. These findings have the potential to link metal availability, cellular metabolism, and microbial community structure in vivo. Together, this proposal will use synthetic vaginal communities to profile the genetic, physiological, and ecological mechanisms that drive microbial interactions in the vaginal mucosa. These findings will provide a better understanding of the ecological factors that contribute to vaginal community composition, stability, and interactions. This work will advance our fundamental knowledge and identify relevant therapeutic targets that could serve to promote efforts in maintaining vaginal health.
项目总结

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Lindsey Renae Burcham其他文献

Lindsey Renae Burcham的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

相似海外基金

Developing a Census Based Generative Geodemographic Classification System
开发基于人口普查的生成地理人口分类系统
  • 批准号:
    ES/Z50273X/1
  • 财政年份:
    2024
  • 资助金额:
    $ 36.54万
  • 项目类别:
    Research Grant
Postdoctoral Fellowship: EAR-PF: Establishing a new eruption classification with a multimethod approach
博士后奖学金:EAR-PF:用多种方法建立新的喷发分类
  • 批准号:
    2305462
  • 财政年份:
    2024
  • 资助金额:
    $ 36.54万
  • 项目类别:
    Fellowship Award
Classification of contemporary Kansai dialects
当代关西方言的分类
  • 批准号:
    24K03842
  • 财政年份:
    2024
  • 资助金额:
    $ 36.54万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
BBSRC-NSF/BIO: An AI-based domain classification platform for 200 million 3D-models of proteins to reveal protein evolution
BBSRC-NSF/BIO:基于人工智能的域分类平台,可用于 2 亿个蛋白质 3D 模型,以揭示蛋白质进化
  • 批准号:
    BB/Y000455/1
  • 财政年份:
    2024
  • 资助金额:
    $ 36.54万
  • 项目类别:
    Research Grant
BBSRC-NSF/BIO: An AI-based domain classification platform for 200 million 3D-models of proteins to reveal protein evolution
BBSRC-NSF/BIO:基于人工智能的域分类平台,可用于 2 亿个蛋白质 3D 模型,以揭示蛋白质进化
  • 批准号:
    BB/Y001117/1
  • 财政年份:
    2024
  • 资助金额:
    $ 36.54万
  • 项目类别:
    Research Grant
From single-cell transcriptomic to single-cell fluxomic: characterising metabolic dysregulations for breast cancer subtype classification
从单细胞转录组到单细胞通量组:表征乳腺癌亚型分类的代谢失调
  • 批准号:
    EP/Y001613/1
  • 财政年份:
    2024
  • 资助金额:
    $ 36.54万
  • 项目类别:
    Research Grant
Enhanced X-ray material classification using SiPMs and fast scintillators
使用 SiPM 和快速闪烁体增强 X 射线材料分类
  • 批准号:
    2905969
  • 财政年份:
    2024
  • 资助金额:
    $ 36.54万
  • 项目类别:
    Studentship
Particle classification and identification in cryoET of crowded cellular environments
拥挤细胞环境中 CryoET 中的颗粒分类和识别
  • 批准号:
    BB/Y514007/1
  • 财政年份:
    2024
  • 资助金额:
    $ 36.54万
  • 项目类别:
    Research Grant
EAGER: IMPRESS-U: Exploratory Research in Robust Machine Learning for Object Detection and Classification
EAGER:IMPRESS-U:用于对象检测和分类的鲁棒机器学习的探索性研究
  • 批准号:
    2415299
  • 财政年份:
    2024
  • 资助金额:
    $ 36.54万
  • 项目类别:
    Standard Grant
OAC Core: Enhancing Network Security by Implementing an ML Malware Detection and Classification Scheme in P4 Programmable Data Planes and SmartNICs
OAC 核心:通过在 P4 可编程数据平面和智能网卡中实施 ML 恶意软件检测和分类方案来增强网络安全
  • 批准号:
    2403360
  • 财政年份:
    2024
  • 资助金额:
    $ 36.54万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了