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Optimizing single-cell RNA sequencing methods for human colon biopsies: droplet-based vs. picowell-based platforms. | LitMetric

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Article Abstract

Background & Aims: Single-cell RNA sequencing (scRNA) has empowered many insights into gastrointestinal microenvironments. However, profiling human biopsies using droplet-based scRNA (D-scRNA) is challenging since it requires immediate processing to minimize epithelial cell damage. In contrast, picowell-based (P-scRNA) platforms permit short-term frozen storage before sequencing. We compared P- and D-scRNA platforms on cells derived from human colon biopsies.

Methods: Endoscopic rectosigmoid mucosal biopsies were obtained from two adults and conducted D-scRNA (10X Chromium) and P-scRNA (Honeycomb HIVE) in parallel using an individual's pool of single cells (> 10,000 cells/participant). Three experiments were performed to evaluate 1) P-scRNA with cells under specific storage conditions (immediately processed [fresh], vs. frozen at -20C vs. -80C [2 weeks]); 2) fresh P-scRNA versus fresh D-scRNA; and 3) P-scRNA stored at -80C with fresh D-scRNA.

Results: Significant recovery of loaded cells was achieved for fresh (80.9%) and -80C (48.5%) P-scRNA and D-scRNA (76.6%), but not -20C P-scRNA (3.7%). However, D-scRNA captures more typeable cells among recovered cells (71.5% vs. 15.8% Fresh and 18.4% -80C P-scRNA), and these cells exhibit higher gene coverage at the expense of higher mitochondrial read fractions across most cell types. Cells profiled using D-scRNA demonstrated more consistent gene expression profiles among the same cell type than those profiled using P-scRNA. Significant intra-cell-type differences were observed in profiled gene classes across platforms.

Conclusions: Our results highlight non-overlapping advantages of P-scRNA and D-scRNA and underscore the need for innovation to enable high-fidelity capture of colonic epithelial cells. The platform-specific variation highlights the challenges of maintaining rigor and reproducibility across studies that use different platforms.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11230261PMC
http://dx.doi.org/10.1101/2024.06.24.600526DOI Listing

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