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Highly multiplexed spatial mapping of microbial communities
Nature ( IF 64.8 ) Pub Date : 2020-12-02 , DOI: 10.1038/s41586-020-2983-4
Hao Shi 1 , Qiaojuan Shi 1 , Benjamin Grodner 1 , Joan Sesing Lenz 1 , Warren R Zipfel 1 , Ilana Lauren Brito 1 , Iwijn De Vlaminck 1
Affiliation  

Mapping the complex biogeography of microbial communities in situ with high taxonomic and spatial resolution poses a major challenge because of the high density 1 and rich diversity 2 of species in environmental microbiomes and the limitations of optical imaging technology 3 – 6 . Here we introduce high-phylogenetic-resolution microbiome mapping by fluorescence in situ hybridization (HiPR-FISH), a versatile technology that uses binary encoding, spectral imaging and decoding based on machine learning to create micrometre-scale maps of the locations and identities of hundreds of microbial species in complex communities. We show that 10-bit HiPR-FISH can distinguish between 1,023 isolates of Escherichia coli , each fluorescently labelled with a unique binary barcode. HiPR-FISH, in conjunction with custom algorithms for automated probe design and analysis of single-cell images, reveals the disruption of spatial networks in the mouse gut microbiome in response to treatment with antibiotics, and the longitudinal stability of spatial architectures in the human oral plaque microbiome. Combined with super-resolution imaging, HiPR-FISH shows the diverse strategies of ribosome organization that are exhibited by taxa in the human oral microbiome. HiPR-FISH provides a framework for analysing the spatial ecology of environmental microbial communities at single-cell resolution. High-phylogenetic-resolution microbiome mapping by fluorescence in situ hybridization (HiPR-FISH) enables the spatial mapping of hundreds of species of microorganisms and shows how microbial networks in the mouse gut are affected by antibiotic treatment.

中文翻译:

微生物群落的高度多重空间映射

由于环境微生物组中物种的高密度 1 和丰富的多样性 2 以及光学成像技术的局限性 3 – 6 ,以高分类学和空间分辨率原位绘制微生物群落的复杂生物地理学是一项重大挑战。在这里,我们介绍了通过荧光原位杂交 (HiPR-FISH) 进行的高系统发育分辨率微生物组映射,这是一种基于机器学习使用二进制编码、光谱成像和解码来创建数百个位置和身份的微米级地图的多功能技术。复杂群落中的微生物物种。我们证明 10 位 HiPR-FISH 可以区分 1,023 个大肠杆菌分离株,每个分离株都用独特的二进制条形码进行荧光标记。HiPR-FISH,结合用于自动探针设计和单细胞图像分析的定制算法,揭示了小鼠肠道微生物组中空间网络的破坏以响应抗生素治疗,以及人类口腔菌斑微生物组中空间结构的纵向稳定性。结合超分辨率成像,HiPR-FISH 显示了人类口腔微生物组中分类单元所展示的核糖体组织的多样化策略。HiPR-FISH 提供了一个框架,用于以单细胞分辨率分析环境微生物群落的空间生态学。通过荧光原位杂交 (HiPR-FISH) 进行的高系统发育分辨率微生物组作图能够对数百种微生物进行空间作图,并显示小鼠肠道中的微生物网络如何受到抗生素治疗的影响。
更新日期:2020-12-02
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