Biology subjects

Vu, A. H.

Publications and source records attributed to Vu, A. H..

6 recordsLinked to original sources

bioRxiv2026

Label-Free All-Electrical Tracking of Individual and Collective Cell Migration on a Megapixel CMOS Capacitance Sensor

Label-free tracking of adherent cell migration could enable important insights into biological processes such as tissue repair, inflammatory response, or cancer progression. Nevertheless, visualizing unlabeled animal cells using optical microscopy remains challenging due to low contrast as well as frequent changes in cell shape and number. A promising alternative uses electrical capacitance measurements, which are sensitive to cell adhesion to electrode surfaces. However, prior examples often utilized electrodes with areas larger than single cells, resulting in averaged readouts over multiple cells. Here, we demonstrate label-free, live-cell tracking using a capacitance sensor array with more than 1 million pixels on a 10 micron pitch across an area larger than 1 square centimeter. We show that single cell morphology can be clearly segmented, and then used to reconstruct migration and proliferation dynamics using optical flow. We further track the spreading of multicellular spheroids, revealing fast-moving peripheral regions led by a collective leader cell "front." Finally, we demonstrate label-free imaging of millimeter-scale honeycomb-shaped tissues without the multi-image stitching often required for conventional microscopy. We utilize mutual capacitance measurements with electrically-programmable electrode spacing to reconstruct topographical features of these engineered tissues. Overall, CMOS capacitance imaging arrays enables label-free imaging spanning from single cells to large tissues, in a portable and scalable format for settings where optical microscopy may be difficult to access.

bioengineering↗

bioRxiv2025

Single cell mass spectrometry reveals intercellular compartmentalization of camptothecin biosynthesis in the tree Camptotheca acuminata

The medicinal tree Camptotheca acuminata produces camptothecin, a monoterpenoid indole al- kaloid (MIA) precursor for several leading chemotherapeutic agents (Lorence and Nessler 2004). Alt- hough the biosynthesis of camptothecin remains poorly understood, a putative route has been hypothe- sized based on in planta metabolite profiling and feeding studies (Fig. 1a) (Sheriha and Rapoport 1976; Sadre et al. 2016). However, pathways proposed on whole-tissue or organ-level metabolomic and tran- scriptomic data lack resolution on the intricate, cell-specific compartmentalization of natural products biosynthesis. Such gaps could be addressed by single cell technologies, which have recently shown tremendous potential to transform gene discovery in herbaceous plants (Li et al. 2023; Zhan et al. 2023; Vu et al. 2024; Wu et al. 2024; McClune et al. 2025). Nevertheless, single cell mass spectrometry (scMS) has not been adapted for woody species, largely due to the challenges associated with their highly lignified tissue and complex cellular architecture. In this study, we developed an scMS pipeline for the woody tree C. acuminata to investigate the intercellular organization of camptothecin biosynthesis. O_FIG O_LINKSMALLFIG WIDTH=144 HEIGHT=200 SRC="FIGDIR/small/661346v1_fig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@17f7710org.highwire.dtl.DTLVardef@161c469org.highwire.dtl.DTLVardef@1a5ee1borg.highwire.dtl.DTLVardef@b361b9_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 1.C_FLOATNO Single cell metabolomics of Camptotheca acuminata. (a) Proposed camptothecin biosynthetic pathway. (b) Schematic experimental pipeline. (c) Dot plots showing concentrations of key metabolites in single cells across organs. Each data point rep- resents a protoplast. For each metabolite, dots were offset from the center based on the distribution of concentrations among sin- gle cells. (N.D.: not detected). (d) Stacked bars showing concentrations in individual cells of loganic acid, secologanic acid, strictosidinic acid, strictosamide, pumiloside, and camptothecin). Cells are organized into groups with loganic acid only (A), secologanic acid only (B), loganic and secologanic (C), strictosidinic acid only (D), and other alkaloids (strictosamide, pumiloside, and camptothecin) (E). In each group, cells are ordered by total metabolite concentration with highest concentration in the center and lower producers closer to the edges. Panel widths scale with the number of cells in each group, and colours cor- respond to individual metabolites. C_FIG

biochemistry↗

bioRxiv2025

Single-cell metabolome and RNA-seq multiplexing on single plant cells

Plants produce valuable natural products used for a wide variety of industrial applications. Since these molecules have important applications in a variety of industrial sectors, there is enormous interest in elucidating the biosynthetic pathways that are responsible for the production of these compounds. Identification of the genes that comprise these biosynthetic pathways has been enabled by gene-to-metabolite networks that are generated from transcriptomic and metabolomic datasets. Recent advances in both single-cell RNA-seq (scRNA-seq) and single-cell mass spectrometry metabolomics (scMS) have enabled the measurement of either gene expression or metabolite levels in individual cells. However, these individual datasets can only be used to indirectly correlate gene expression levels with metabolite concentrations at the single cell level. Here we demonstrate that both scRNA-seq and scMS can be applied to the same plant cell, thereby enabling direct comparisons between gene expression and metabolite levels. This multiplexing approach reveals both qualitative and quantitative correlations between metabolite levels and biosynthetic gene expression in individual cells. This integrated approach sheds light on the underlying processes driving complex plant biosynthesis.

plant biology↗

bioRxiv2025

Single cell omics extends metabolic regulon via orthologous transcription factors from a pair of medicinal plant species

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

plant biology↗

bioRxiv2024

Quantitative single cell mass spectrometry reveals the dynamics of plant natural product biosynthesis

Plants produce an extraordinary array of complex natural products (specialized metabolites). Since the biosynthetic genes that are responsible for synthesis of these molecules are often localized to rare or distinct cell types, recently developed single cell RNA-sequencing (scRNA-seq) approaches have tremendous potential to resolve these complex pathways. In contrast, detection, identification, and quantification of metabolites in single cells has remained challenging. Here, we report a robust method for single cell mass spectrometry in which we rigorously characterize and quantify the concentrations of four classes of natural products in individual cells of leaf, root, and petal of the medicinal plant Catharanthus roseus. These single cell mass spectrometry datasets reveal information about the biosynthetic processes that cannot be determined from the corresponding scRNA-seq data alone, providing a highly resolved picture of natural product biosynthesis at cell-specific resolution.

biochemistry↗

bioRxiv2022

Single-cell multi-omics enabled discovery of alkaloid biosynthetic pathway genes in the medical plant Catharanthus roseus

Advances in omics technologies now permit generation of highly contiguous genome assemblies, detection of transcripts and metabolites at the level of single cells, and high-resolution determination of gene regulatory features including 3-dimensional chromatin interactions. Using a complementary, multi-omics approach, we interrogated the monoterpene indole alkaloid (MIA) biosynthetic pathway in Catharanthus roseus, a source of leading anti-cancer drugs. We identified not only new clusters of genes involved in MIA biosynthesis on the eight C. roseus chromosomes but also rampant gene duplication including paralogs of MIA pathway genes. Clustering was not limited to the linear genome and through chromatin interaction data, MIA pathway genes were shown to be present within the same topologically associated domain, permitting identification of a secologanin transporter. Single cell RNA-sequencing revealed exquisite and sequential cell-type specific partitioning of the leaf MIA biosynthetic pathway that, when coupled with a newly developed single cell metabolomics approach, permitted identification of a reductase that yields the bis-indole alkaloid anhydrovinblastine. Last, we revealed cell-type specific expression in the root MIA pathway that is conferred in part by neo- and sub-functionalization of paralogous MIA pathway genes. This study highlights how a suite of omic approaches, including single cell gene expression and metabolomics, can efficiently link sequence with function in complex, specialized metabolic pathways of plants.

plant biology↗