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Updated: May 21, 2025

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq
Published on: March 12, 2021
Phylogeny-metabolism dual-directed single-cell genomics for dissecting and mining ecosystem function by
Xiaoyan Jing1,2,3,4, Yanhai Gong1,2,3,4, Zhidian Diao1,2,3,4
1Single-Cell Center, CAS Key Laboratory of Biofuels, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266000, China.
Abstract:
Microbiome-wide association studies (MWASs) have uncovered microbial markers linked to ecosystem traits, but the mechanisms underlying their functions can remain elusive. This is largely due to challenges in validating their in situ metabolic activities and tracing such activities to individual genomes. Here, we introduced a phylogeny-metabolism dual-directed single-cell genomics approach called fluorescence-in situ-hybridization-guided single-cell Raman-activated sorting and sequencing (FISH-scRACS-seq). It directly localizes individual cells from target taxon via an FISH probe for marker organism, profiles their in situ metabolic functions via single-cell Raman spectra, sorts cells of target taxonomy and target metabolism, and produces indexed, high-coverage, and precisely-one-cell genomes. From cyclohexane-contaminated seawater, cells representing the MWAS-derived marker taxon of γ-Proteobacteria and that are actively degrading cyclohexane in situ were directly identified via FISH and Raman, respectively, then sorted and sequenced for one-cell full genomes. In such a Pseudoalteromonas fuliginea cell, we discovered a three-component cytochrome P450 system that can convert cyclohexane to cyclohexanol in vitro, representing a previously unknown group of cyclohexane-degrading enzymes and organisms. Therefore, by unveiling enzymes, pathways, genomes, and their in situ cellular functions specifically for those organisms with ecological relevance at one-cell resolution, FISH-scRACS-seq is a rational and generally applicable approach to dissecting and mining microbiota functions.
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