Resolving Oral Bacteria Interactions with a High-Throughput Low-Cost Single-Cell Transcriptomics Approach

采用高通量低成本单细胞转录组学方法解决口腔细菌相互作用

• 批准号: 10678379
• 负责人: Anna Kuchina
• 金额: $ 27.15万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10678379
• 关键词: Acute; Address; Affect; Architecture; Bacteria; Bacterial Adhesins; Bar Codes; Binding; Biological; Biological Models; Bypass; Cell Communication; Cell Separation; Cell Size; Cell Wall; Cells; Coculture Techniques; Communities; Complex; Disease; Environment; Eukaryota; Fusobacterium nucleatum; Future; Gene Expression; Gene Expression Regulation; Genes; Genetic Transcription; Genome; Goals; Homeostasis; Human Microbiome; In Vitro; Life Style; Ligation; Measures; Messenger RNA; Methodology; Methods; Microbe; Microbiology; Microfluidics; Modeling; Modernization; Morphology; Noise; Oral; Oral cavity; Organism; Outcome; Parasites; Pathogenicity; Pathway interactions; Peptidoglycan; Porphyromonas gingivalis; Probability; Prokaryotic Cells; Protocols documentation; RNA; Radiation; Research; Resolution; Sampling; Science; Signal Transduction; Stress; Study models; System; Techniques; Technology; Testing; Time; Viral; Virulence; Virulence Factors; cell type; clinically relevant; combinatorial; cost; dental biofilm; design; differential expression; experimental study; extracellular; fungus; human microbiota; in vivo Model; innovation; insight; instrumentation; interest; laboratory equipment; member; microbial; microbiota; microorganism interaction; novel; oral bacteria; oral microbial community; periodontopathogen; periopathogen; single-cell RNA sequencing; transcriptome; transcriptome sequencing; transcriptomics

1 Abstract 2 Interactions among the microbiota within human microbiome are what define the community function during 3 healthy homeostasis and changes in these relationships can result in increased virulence leading to disease. 4 Bacteria from different species in the oral cavity make up the diverse plaque biofilms and are well known to 5 recognize and bind each other when grown together or artificially mixed (aggregation). Many studies rely on this 6 model to determine how cell-cell interactions affect each member. However, a major limitation to understanding 7 how direct binding between microbes may regulate expression within a simple dual bacteria:bacteria interaction 8 is the fact that there are mixed cell states within the co-culture. In reality, there is not a controlled 1:1 relationship, 9 and not all cells within the culture are directly bound to another cell. Many cells will remain free but still influenced 10 by soluble metabolites and signals in the shared media environment. When bulk transcriptomics are applied to 11 measure the gene expression of such mixed cultures, the average expression of all the cell states together 12 generates noise that interferes with the true signal of interest – what is occurring in specific biological states, 13 such as cells that are attached to each other. This results in a high probability that a true positive will be 14 missed and the inability to confidently attribute observed changes to the cells of interest. Ultimately this problem 15 represents a universal issue in all microbiology that has largely been ignored to date mainly due to the 16 technological limitations of physically capturing only the cells of interest as well as the biological limitation of low 17 bacterial mRNA content. Here we propose to leverage a recent breakthrough in single-cell transcriptomics 18 (scRNAseq) that has been developed for prokaryotes and successfully applied to monocultures and artificially 19 mixed non-interacting bacteria (MPI Kuchina et al., Science 2021), designated MicroSPLiT (microbial split-pool 20 ligation transcriptomics). MicroSPLiT was achieved through overcoming major challenges specific to bacteria, 21 such as their low mRNA content, diversity in cell size, and cell wall architecture. This technique is designed to 22 be high throughput, profiling tens of thousands of cells in a single experiment, low-cost, and importantly, an 23 approach achievable by any lab with only basic laboratory equipment. The goal of this study is to leverage and 24 expand upon this very recent, highly innovative breakthrough to: 1) Overcome a major universal problem in 25 microbiology by developing a comprehensive approach to determine true cell-cell binding interactions at the 26 single-cell level, and 2) apply this technique to gain insight into several important interactions between oral 27 microbial species including known periopathogens and those between recently discovered ultrasmall, reduced 28 genome parasitic oral bacteria and their bacterial host. Overall, the outcomes of this project are expected to 29 directly advance our understanding of the regulation of genes between physically interacting microbiota and 30 develop a protocol for the research community to be able to utilize this new widely accessible approach. 31

1篇摘要 2.人体微生物组内微生物之间的相互作用是定义人体内微生物群落功能的因素。 3健康的体内平衡和这些关系的变化可能导致致病力增加，从而导致疾病。 4来自口腔中不同物种的细菌构成了不同的菌斑生物膜，并且众所周知， 5在一起生长或人工混合时（聚集）相互识别并结合。许多研究都依赖于此 6模型，以确定细胞间相互作用如何影响每个成员。然而，理解的一个主要局限是， 7微生物之间的直接结合如何调节简单的双重细菌内的表达：细菌相互作用 8是在共培养物内存在混合细胞状态的事实。事实上，并没有一个受控的1：1关系， 9，并且并非培养物中的所有细胞都直接与另一细胞结合。许多细胞将保持自由，但仍然受到影响 10通过在共享介质环境中的可溶性代谢物和信号。当批量转录组学应用于 11测量这种混合培养物的基因表达，所有细胞状态的平均表达加在一起 12产生干扰感兴趣的真实信号的噪声-在特定生物状态下发生的事情， 13、如细胞相互连接。这导致真阳性的概率很高， 14个缺失，并且无法自信地将观察到的变化归因于感兴趣的细胞。最终这个问题 15代表了所有微生物学中的一个普遍问题，迄今为止在很大程度上被忽视，主要是由于 16物理上仅捕获感兴趣的细胞的技术限制以及低捕获率的生物学限制。 17细菌mRNA含量。在这里，我们建议利用单细胞转录组学的最新突破 18（scRNaseq）已针对原核生物开发并成功应用于单培养和人工培养 19种混合的非相互作用细菌（MPI Kuchina等人，Science 2021），命名为MicroSPLiT（微生物分液池 20个连接转录组学）。MicroSPLiT是通过克服细菌特有的主要挑战而实现的， 21，如它们的低mRNA含量，细胞大小和细胞壁结构的多样性。这项技术旨在 22是高通量的，在单个实验中分析数万个细胞，低成本，重要的是， 23方法可由任何实验室实现，只有基本的实验室设备。这项研究的目的是利用和 24扩展这个最近的，高度创新的突破：1）克服一个主要的普遍问题， 25微生物学通过开发一种全面的方法来确定真正的细胞-细胞结合相互作用， 26单细胞水平，和2）应用这种技术来深入了解口腔之间的几个重要的相互作用 27种微生物，包括已知的病原体和最近发现的超小，减少 28个基因组的寄生性口腔细菌及其细菌宿主。总体而言，预计该项目的成果将 29直接推进了我们对物理相互作用的微生物群之间基因调控的理解， 30.为研究界制定一项议定书，使其能够利用这一新的可广泛使用的方法。 31