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- W4385875706 abstract "Summary 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 DNA 3 , contemporary methodologies for the characterization of generic biological entities remain conspicuously constrained, with low throughput 4 , compromised lysis efficiency 5 , and highly fragmented genomes 6 . 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 barcodes, (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 summary, the presented conceptually new workflow offers a toolbox based on droplet microfluidics to tackle the persistent challenges in high-throughput profiling to generic applications, which hold immense promise for diverse biological entities, especially hard-to-lyse cells." @default.
- W4385875706 created "2023-08-17" @default.
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- W4385875706 date "2023-08-15" @default.
- W4385875706 modified "2023-10-04" @default.
- W4385875706 title "High-throughput generic single-entity sequencing using droplet microfluidics" @default.
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- W4385875706 doi "https://doi.org/10.1101/2023.08.15.549386" @default.
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