Plant Biotechnology JournalPlant BiologyPeer-reviewed journal article
Single cell multi-omics reveals rare biosynthetic cell types in the medicinal tree Camptotheca acuminata
Van‐Hung BuiiD, Joshua C. WoodiD, Brieanne VaillancourtiD, John P. HamiltoniD, Lemor H. Carlton, Thu‐Thuy T. DangiD, C. Robin BuelliD, Chenxin LiiD
Abstract
Camptotheca acuminata Decne is a woody medicinal tree that produces over a hundred bioactive compounds, including camptothecin, which has been used as the starting material to semi-synthesize many leading anticancer drugs (Lorence and Nessler 2004). Camptothecin and its derivatives are potent inhibitors of DNA topoisomerase I and are widely used for the treatment of lung, cervical, ovarian, and colon cancers. Camptothecin biosynthesis in C. acuminata involves complex catalytic steps, most of which remain undeciphered. In this pathway, tryptamine and secologanic acid are coupled, leading to strictosidinic acid. The formation of strictosidinic acid is catalyzed by strictosidine/strictosidine acid syn-thase enzymes (STR) (Fig. 1A). While a biosynthetic route for the conversion of the indole ring to the quinoline ring has been proposed, most of the underlying biosynthetic genes have yet to be identified (Fig. 1A) (Sadre et al. 2016). In addition, the cell type specificity of this pathway also remains undescribed. Here, we generated a single cell multiome (RNA-seq and Assay for Transposase Accessible Chromatin by sequencing [ATAC-seq] from the same nuclei) to probe the cell type specificity of camptothecin biosyn-thetic genes. O_FIG O_LINKSMALLFIG WIDTH=149 HEIGHT=200 SRC="FIGDIR/small/650021v2_fig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@81dcf0org.highwire.dtl.DTLVardef@1d03ae1org.highwire.dtl.DTLVardef@1c9b0a9org.highwire.dtl.DTLVardef@6d5238_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 1.C_FLOATNO Single cell multi-ome of Camptotheca acuminata leaf. (A) The proposed biosynthetic pathway for camptotheci . Solid arrows indicate previously characterized enzymatic steps. Dashed arrows indicate proposed enzymatic steps (see Table S7 for gene name abbreviations). (B) Uniform Manifold Approximation and Projection (UMAP) of nuclei of the single nuclei RNA-seq dataset (n = 4,012), color coded by cell clusters. (C) Gene expression heatmap of MIA biosynthetic genes across cell clusters. Rows are expressed biosynthetic genes, which are ordered from upstream to downstream. Color scale shows the average scaled expression of each gene at each cell cluster. Cell clusters are sorted by cell types. Dot size indicates the percentage of cells where a given gene is detected. The predicted cell type for each cell cluster is annotated by the color strip below the x-axis. Box highlights expression of STR genes. (D) Heat map showing accessibility of cell type marker peaks across cell clusters. Each row is an ATAC-seq peak. Each column is a cell cluster. Color scale is maxed out at 90th percentile of normalized ATAC-seq signal. The predicted cell type for each cell cluster is annotated by the color strip below the x-axis, with the same color palette as (B). (E) Heatmap showing gene expression across cell clusters. Each row is a gene within 2-kb of a STR+ marker peak. Each column is a cell cluster. The predicted cell type for each cell cluster is annotated by the color strip below the x-axis, with the same color palette as (B). (F) DNA motif enriched in STR+ marker peaks, as well as a reference MYB motif. C_FIG
- organism: plant (other)
- assay: scRNA-seq
- assay: ATAC-seq
- research focus: cell type annotation
- approach: deep learning
- approach: statistical model
- Citations
- 7
- FWCI
- 2.09
- Field percentile
- top 12%
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