High-throughput generic single-entity sequencing using droplet microfluidics

bioRxiv (Cold Spring Harbor Laboratory)(2023)

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摘要
Single-cell sequencing has revolutionized our understanding of cellular heterogeneity by providing a micro-level perspective over the past decades. Although heterogeneity is essential for various biological communities, the currently demonstrated platform predominantly focuses on eukaryotic cells without cell walls and their transcriptomics 1,2, leaving significant gaps in the study of omics from other single biological entities such as bacteria and viruses. Due to the difficulty of isolating and acquiring their DNA3, contemporary methodologies for the characterization of generic biological entities remain conspicuously constrained, with low throughput4, compromised lysis efficiency5, and highly fragmented genomes6. Herein, we present the Generic Single Entity Sequencing platform (GSE-seq), which boasts ample versatility, high throughput, and high coverage, and is enabled by an innovative workflow, addressing the critical challenges in single entities sequencing: (1) one-step manufacturing of massive barcode, (2) degradable hydrogel-based in situ sample processing and whole genome amplification, (3) integrated in-drop library preparation, (4) compatible long-read sequencing. By GSE-seq, we have achieved a significant milestone by enabling high-throughput, long-read single-entity profiling of dsDNA and ssDNA from single virus sequencing (SV-seq) and single bacteria sequencing (SB-seq) of the human gut and marine sediment for the first time. Notably, our analysis uncovered previously overlooked viral and bacterial dark matter and phage-host interactions. In this study, we propose a new concept and toolbox to tackle the persistent challenges of applying high-throughput profiling based on droplet microfluidics to generic applications, which hold immense promise for diverse biological entities, especially hard-to-lyse cells. ### Competing Interest Statement Guoping Wang, Liuyang Zhao, Fuyang Qu, Yi-Ping Ho, and Jun Yu, are the inventors in the pending patent application related this work.
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high-throughput,single-entity
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