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

• 批准号: 10713736
• 负责人: Yang Liu
• 金额: $ 39.45万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 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
• 来源: https://reporter.nih.gov/project-details/10713736
• 关键词: Antibiotic Therapy; Antibodies; Bacteria; Bar Codes; C57BL/6 Mouse; Cell Wall; Cells; Cellular Indexing of Transcriptomes and Epitopes by Sequencing; Complex; Development; Digestion; Escherichia coli; Gene Expression; Gene Expression Profile; Genomics; Germ-Free; Gram-Positive Bacteria; Half-Life; Heterogeneity; Human; Inflammatory Bowel Diseases; Ligation; Malignant Neoplasms; Maps; Membrane Proteins; Messenger RNA; Microbe; Modeling; Neurosciences; Pathway interactions; Patients; Peptide Sequence Determination; Poly(A) Tail; Polyadenylation Pathway; Population; Protocols documentation; RNA Sequences; RNA-Directed DNA Polymerase; Reagent; Reporting; Resolution; Reverse Transcription; Slide; Spatial Distribution; Staphylococcus aureus; System; Techniques; Technology; Thick; Tissues; cell behavior; design; epigenomics; host-microbe interactions; microbial; multiple omics; pathogen; polyadenylated messenger RNA; prevent; receptor; sequencing platform; tool; transcriptome; transcriptome sequencing; transcriptomics

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/摘要 微生物细胞群体可以是高度异质的，这对于菌株在复杂环境中的存活至关重要。 如抗生素治疗。显然，细胞与细胞的异质性不能用 传统的批量测序技术。基于单细胞的微生物细胞方法正在出现，以解决 然而，这个问题，空间背景信息，对于理解微生物-宿主相互作用至关重要， 没有收集。到目前为止，我们仍然缺乏高分辨率的空间组学工具来研究微生物及其代谢。 哺乳动物宿主大多数目前可用的基于NGS的空间转录组平台不是 由于以下三个原因与细菌谱分析相容：1）细菌细胞壁的厚度高度不同 以及防止试剂如逆转录酶和引物进入细胞的组合物， 尤其是革兰氏阳性菌细胞壁较厚; 2）细菌细胞的mRNA稀疏， 3）细菌mRNA在RNA序列中缺少poly-A尾。在过去的5年里，我开发了DBiT-seq （组织中的确定性条形码），第一个高分辨率空间蛋白质转录组平台， 广泛应用于人类神经科学、发育和癌症研究。我进一步报告说， Spatial-CITE-seq技术可以共定位约300个表面蛋白和整个转录组， 各种组织类型。我建议在未来五年内开发一种新的空间测序技术 称为microDBiT，这将是第一个空间蛋白质转录组平台，可以映射微生物和 空间背景中的宿主细胞。在初期阶段，我们将设计和使用培养革兰氏菌的载玻片， 阳性菌为金黄色葡萄球菌，阴性菌为大肠杆菌。coli作为模型，优化microDBiT的关键步骤 包括细胞壁消化、mRNA多聚腺苷酸化、逆转录和细胞内连接。我们将 接下来，开发microDBiT协议，用于使用从以下获得的肠道组织进行微生物和宿主细胞共映射： 细菌定殖于无菌C57 BL/6小鼠。最后，我们将应用microDBiT来定位基因 炎症性肠病（IBD）中病原体和患者细胞的表达谱。由于代谢物 的微生物被认为是影响宿主细胞行为的重要途径，我们将同时包括 宿主受体的抗体组，并研究代谢物如何影响宿主的基因表达 细胞该技术最终将实现空间的高通量和高分辨率表征。 微生物的异质性及其与宿主细胞的相互作用。从长远来看，我们将把microDBiT打造成 一个全面的平台，可应用于不同组学水平的各种微生物和宿主系统 （基因组学、转录组学、表观基因组学等）。