Anh Hai Vu

Plants produce valuable natural products used for a wide variety of industrial applications. Thus, 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 datasets can only be used to indirectly correlate gene expression levels with metabolite concentrations at the single-cell level. In this proof-of-concept study, performed on cells derived from the leaves of the medicinal plant Catharanthus roseus , 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. Protoplasts are sorted into 96-well plates using a microfluidics-based robot and then lysed under conditions that are suitable for both scMS and SMART-seq single-cell protocols. 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.

Single-cell mass spectrometry can be used to track stable-isotope incorporation into structurally complex plant natural products at the single cell level.

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.

Plants produce an extraordinary array of natural products (specialized metabolites). Notably, these structurally complex molecules are not evenly distributed throughout plant tissues but are instead synthesized and stored in specific cell types. Elucidating both the biosynthesis and function of natural products would be greatly facilitated by tracking the location of these metabolites at the cell-level resolution. However, detection, identification, and quantification of metabolites in single cells, particularly from plants, have remained challenging. Here, we show that we can definitively identify and quantify the concentrations of 16 molecules from four classes of natural products in individual cells of leaf, root, and petal of the medicinal plant Catharanthus roseus using a plate-based single-cell mass spectrometry method. We show that identical natural products show substantially different patterns of cell-type localization in different tissues. Moreover, we show that natural products are often found in a wide range of concentrations across a population of cells, with some natural products at concentrations of over 100 mM per cell. This single-cell mass spectrometry method provides a highly resolved picture of plant natural product biosynthesis partitioning at a cell-specific resolution.

Advances in omics technologies now permit the 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. Here, using a complementary, multi-omics approach, we interrogated the monoterpene indole alkaloid (MIA) biosynthetic pathway in Catharanthus roseus, a source of leading anticancer drugs. We identified clusters of genes involved in MIA biosynthesis on the eight C. roseus chromosomes and extensive gene duplication of MIA pathway genes. Clustering was not limited to the linear genome, and through chromatin interaction data, MIA pathway genes were present within the same topologically associated domain, permitting the identification of a secologanin transporter. Single-cell RNA-sequencing revealed sequential cell-type-specific partitioning of the leaf MIA biosynthetic pathway that, when coupled with a single-cell metabolomics approach, permitted the identification of a reductase that yields the bis-indole alkaloid anhydrovinblastine. We also revealed cell-type-specific expression in the root MIA pathway.

In this work, high-performance liquid chromatography in combination with inductively coupled plasma dynamic reaction cell quadrupole mass spectrometry was introduced and optimized for speciation analysis of five major arsenic species including arsenobetain (AsB), arsenite (As(III)), monomethylarsonic (MMA), dimethylarsenonic acid (DMA), and arsenate (As(V)) in rice samples. Five arsenic compounds were separated on a Hamilton PRP X100 strong anion-exchange column employed with the mobile phase that is compatible with mass spectrometry, containing ammonium carbonate, methanol, and disodium ethylenediaminetetraacetic acid. Arsenic compounds were detected online by inductively coupled plasma dynamic reaction cell quadrupole mass spectrometry utilizing oxygen as the reaction gas at a flow rate of 0.7 mL·min⁻¹. Five selected arsenic species were baseline separated at the optimum experimental conditions. The excellent LOD and LOQ values of the developed method were achieved in the range of 0.5 to 2.9 μg·kg⁻¹ and 1.7 to 9.6 μg·kg⁻¹ for all species of arsenic, respectively. The ionization effect in plasma during chromatographic gradient elution was systematically investigated by using postcolumn injector. Arsenic compounds in rice samples were extracted by diluted nitric acid at elevated temperature. The extraction efficiency and the interconversion of target compounds during sample preparation were also assessed. The full validation of the developed method was performed by using certified reference material, BRC 211, from European Institute of Reference and Standard for speciation analysis. The recovery of all selected arsenic species was in the range of 70 to 135.5%. The validated method was also applied to analyze rice samples collected from some contaminated rice fields. The results showed that As(III), DMA, and As(V) were found in all rice samples. Average concentration (range) of inorganic arsenic and DMA in all rice samples were 130.3 (65.5–228.1) and 32 (8.2–133.01) μg·kg⁻¹, respectively. However, total concentration of inorganic arsenic in most of investigated rice samples was below the maximum residual level according to US-FDA and European Union standards.

A high-performance liquid chromatography (HPLC) in combination with inductively coupled plasma mass spectrometry (ICP-MS) as an elemental specific detector was used for the speciation analysis of arsenic compounds in urine and serum samples from Vietnam. Five arsenic species including arsenite (As^III), arsenate (As^V), monomethylarsonic acid (MMA), dimethylarsinic acid (DMA), and arsenobetaine (AsB) were studied. A gradient elution of ammonium carbonate ((NH₄)₂CO₃), ethylenediaminetetraacetic acid disodium salt (Na₂EDTA), and methanol at pH 9.0 utilizing Hamilton PRP-X100 strong anion-exchange column allowed the chromatographic separation of five arsenic species. In this study, urine and serum samples were prepared by dilution in solvent and protein precipitation by trichloroacetic acid, respectively. The extraction efficiency was greater than 91% for urine matrix, and recoveries from spiked samples were in the range of 94–139% for the arsenic species in human serum. The method limit of detection (MDL) and limit of quantification (MQL), which were calculated by signal to noise ratio, were found to be 0.3–1.5 and 1.0–5.0 ng·mL⁻¹, respectively. The concentration of arsenic species in 17 pairs of urine and serum samples from Vietnam was also quantified and evaluated. The major species of arsenic in the urine and serum samples were AsB and DMA.