Spatially resolved multiomics profiling of microbes and their host tissue

微生物及其宿主组织的空间分辨多组学分析

基本信息

  • 批准号:
    10713736
  • 负责人:
  • 金额:
    $ 39.45万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-09-21 至 2028-07-31
  • 项目状态:
    未结题

项目摘要

PROJECT SUMMARY/ABSTRACT Microbial cell populations can be highly heterogeneous, which is crucial for strain survival in complex conditions such as antibiotic treatment. Apparently, the cell-to-cell heterogeneity cannot be revealed using traditional bulk sequencing techniques. Single-cell based approaches for microbial cells are emerging to tackle this question, however, the spatial context information, crucial for understanding the microbe-host interactions, is not collected. As of current, we still lack high resolution spatial omics tools to study microbes and their residing mammalian host. Most currently available NGS based spatial transcriptome platforms are not compatible with bacteria profiling due to three reasons: 1) Bacteria cell walls are highly diverse in thickness and composition, which prevents the reagents such as reverse transcriptase and primers to enter the cell, especially for Gram Positive ones with thick cell walls; 2) mRNAs of bacteria cells are sparse and have short half-life; 3) bacteria mRNA lacks poly-A tail in RNA sequence. During the past 5 years, I developed DBiT-seq (Deterministic barcoding in tissue), the first high resolution spatial proteo-transcriptome platform, which have been widely applied to neuroscience, development, and cancer studies in human. I further reported the Spatial-CITE-seq technique which can co-mapping ~300 surface proteins and the whole transcriptome of various tissue types. I propose in the next five years the development of a new spatial sequencing technology called microDBiT, which will be the first spatial proteo-transcriptome platform that can map microbes and the host cells within the spatial context. At the initial stage, we will design and use the slides of cultured Gram positive bacteria S.aureus and negative bacteria E. coli as a model to optimize the key steps of microDBiT protocol, including cell wall digestion, mRNA polyadenylation, reverse transcription and in cell ligation. We will next develop the microDBiT protocol for microbe and host cell co-mapping using gut tissues obtained from bacteria colonized germ-free C57BL/6 mice. Lastly, we will apply the microDBiT to map out the gene expression profile of pathogens and the patient cells in inflammatory bowel disease (IBD). Since metabolites of microbes are considered important pathways that influence the host cell behavior, we will meanwhile include an antibody panel of host receptors and study how the metabolites will influence the gene expression of host cells. This technique will ultimately enable high-throughput and high-resolution characterization of spatial heterogeneity of microbes and their interaction with the host cells. In the long run, we will build microDBiT into a comprehensive platform that could be applied to diverse microbe and host systems at different omics levels (Genomics, Transcriptomics, Epigenomics, etc.).
项目总结/文摘

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)

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Yang Liu其他文献

Formal Verification of Process Layer with Petri nets and Z
使用 Petri 网和 Z 对过程层进行形式化验证
An efficient p-ECR move based on maximum likelihood by neighbor joining
基于邻居加入最大似然的高效 p-ECR 移动
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    3
  • 作者:
    Yang Liu;Jian-Fu Li;Mao-Zu Guo,
  • 通讯作者:
    Mao-Zu Guo,
Secure multi-label data classification in cloud by additionally homomorphic encryption
通过额外的同态加密在云中保护多标签数据分类
  • DOI:
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Yi Liu Yu Luo;Youwen Zhu;Yang Liu;Xingxin Li
  • 通讯作者:
    Xingxin Li
Requirement Verification of Networked Software Goals with Multi-valued Logic
具有多值逻辑的网络化软件目标的需求验证

Yang Liu的其他文献

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{{ truncateString('Yang Liu', 18)}}的其他基金

Mapping the Cellular Responses to DNA Double-Strand Breaks Using On-Demand CRISPR technologies and High-resolution Fluorescence Microscopy
使用按需 CRISPR 技术和高分辨率荧光显微镜绘制细胞对 DNA 双链断裂的反应
  • 批准号:
    10715720
  • 财政年份:
    2023
  • 资助金额:
    $ 39.45万
  • 项目类别:
Climate & Health Actionable Research and Translation Center
气候
  • 批准号:
    10835460
  • 财政年份:
    2023
  • 资助金额:
    $ 39.45万
  • 项目类别:
Climate & Health Actionable Research and Translation Center
气候
  • 批准号:
    10835461
  • 财政年份:
    2023
  • 资助金额:
    $ 39.45万
  • 项目类别:
Super-Resolution Imaging of Higher-Order Heterochromatin Structure for Early Detection of Lung Carcinogenesis
高阶异染色质结构的超分辨率成像用于早期检测肺癌
  • 批准号:
    10435645
  • 财政年份:
    2022
  • 资助金额:
    $ 39.45万
  • 项目类别:
Imaging nanoscale chromatin folding in early carcinogenesis
早期致癌过程中纳米级染色质折叠的成像
  • 批准号:
    10398183
  • 财政年份:
    2020
  • 资助金额:
    $ 39.45万
  • 项目类别:
Imaging nanoscale chromatin folding in early carcinogenesis
早期致癌过程中纳米级染色质折叠的成像
  • 批准号:
    10605199
  • 财政年份:
    2020
  • 资助金额:
    $ 39.45万
  • 项目类别:
Imaging nanoscale chromatin folding in early carcinogenesis
早期致癌过程中纳米级染色质折叠的成像
  • 批准号:
    10223251
  • 财政年份:
    2020
  • 资助金额:
    $ 39.45万
  • 项目类别:
Three dimensional nanoscale nuclear architecture mapping based taxonomy of precursor lesions for predicting colorectal cancer risk
基于三维纳米级核结构映射的前体病变分类法用于预测结直肠癌风险
  • 批准号:
    9756510
  • 财政年份:
    2019
  • 资助金额:
    $ 39.45万
  • 项目类别:
Three dimensional nanoscale nuclear architecture mapping based taxonomy of precursor lesions for predicting colorectal cancer risk
基于三维纳米级核结构映射的前体病变分类法用于预测结直肠癌风险
  • 批准号:
    10590702
  • 财政年份:
    2019
  • 资助金额:
    $ 39.45万
  • 项目类别:
Three dimensional nanoscale nuclear architecture mapping based taxonomy of precursor lesions for predicting colorectal cancer risk
基于三维纳米级核结构映射的前体病变分类法用于预测结直肠癌风险
  • 批准号:
    10373010
  • 财政年份:
    2019
  • 资助金额:
    $ 39.45万
  • 项目类别:

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开发针对革兰氏菌和革兰氏菌的保护性单克隆抗体
  • 批准号:
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