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Transient expression in Nicotiana benthamiana offers a robust platform for the rapid production of complex secondary metabolites. It has proven highly effective in helping identify genes associated with pathways responsible for synthesizing various valuable natural compounds. While this approach has seen considerable success, it has yet to be applied to uncovering genes involved in anthocyanin biosynthetic pathways. This is because only a single anthocyanin, delphinidin 3‐O‐rutinoside, can be produced in N. benthamiana by activation of anthocyanin biosynthesis using transcription factors. The production of other anthocyanins would necessitate the suppression of certain endogenous flavonoid biosynthesis genes while transiently expressing others. In this work, we present a series of tools for the reconstitution of anthocyanin biosynthetic pathways in N. benthamiana leaves. These tools include constructs for the expression or silencing of anthocyanin biosynthetic genes and a mutant N. benthamiana line generated using CRISPR. By infiltration of defined sets of constructs, the basic anthocyanins pelargonidin 3‐O‐glucoside, cyanidin 3‐O‐glucoside and delphinidin 3‐O‐glucoside could be obtained in high amounts in a few days. Additionally, co‐infiltration of supplementary pathway genes enabled the synthesis of more complex anthocyanins. These tools should be useful to identify genes involved in the biosynthesis of complex anthocyanins. They also make it possible to produce novel anthocyanins not found in nature. As an example, we reconstituted the pathway for biosynthesis of Arabidopsis anthocyanin A5, a cyanidin derivative and achieved the biosynthesis of the pelargonidin and delphinidin variants of A5, pelargonidin A5 and delphinidin A5.

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In biological discovery and engineering research, there is a need to spatially and/or temporally regulate transgene expression. However, the limited availability of promoter sequences that are uniquely active in specific tissue-types and/or at specific times often precludes co-expression of >multiple transgenes in precisely controlled developmental contexts. Here, we developed a system for use in rice that comprises synthetic designer transcription activator-like effectors (dTALEs) and cognate synthetic TALE-activated promoters (STAPs). The system allows multiple transgenes to be expressed from different STAPs, with the spatial and temporal context determined by a single promoter that drives expression of the dTALE. We show that two different systems—dTALE1-STAP1 and dTALE2-STAP2—can activate STAP-driven reporter gene expression in stable transgenic rice lines, with transgene transcript levels dependent on both dTALE and STAP sequence identities. The relative strength of individual STAP sequences is consistent between dTALE1 and dTALE2 systems but differs between cell-types, requiring empirical evaluation in each case. dTALE expression leads to off-target activation of endogenous genes but the number of genes affected is substantially less than the number impacted by the somaclonal variation that occurs during the regeneration of transformed plants. With the potential to design fully orthogonal dTALEs for any genome of interest, the dTALE-STAP system thus provides a powerful approach to fine-tune the expression of multiple transgenes, and to simultaneously introduce different synthetic circuits into distinct developmental contexts.

Agriculture is by far the biggest water consumer on our planet, accounting for 70 percent of all freshwater withdrawals. Climate change and a growing world population increase pressure on agriculture to use water more efficiently (‘more crop per drop’). Water‐use efficiency (WUE) and drought tolerance of crops are complex traits that are determined by many physiological processes whose interplay is not well understood. Here we describe a combinatorial engineering approach to optimize signaling networks involved in the control of stress tolerance. Screening a large population of combinatorially transformed plant lines, we identified a combination of calcium‐dependent protein kinase genes that confers enhanced drought stress tolerance and improved growth under water‐limiting conditions. Targeted introduction of this gene combination into plants increased plant survival under drought and enhanced growth under water‐limited conditions. Our work provides an efficient strategy for engineering complex signaling networks to improve plant performance under adverse environmental conditions, which does not depend on prior understanding of network function.

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Hypericin is a molecule of high pharmaceutical importance that is synthesized and stored in dark glands (DGs) of St. John's wort (Hypericum perforatum). Understanding which genes are involved in dark gland development and hypericin biosynthesis is important for the development of new Hypericum extracts that are highly demanded for medical applications. We identified two transcription factors, whose expression is strictly synchronized with the differentiation of DGs. We correlated the content of hypericin, pseudohypericin, endocrocin, skyrin glycosides and several flavonoids with gene expression and DG development to obtain a revised model for hypericin biosynthesis. Here we report for the first‐time genotypes which are polymorphic for the presence/total‐absence (G+/G‐) of DGs in their placental tissues (PTs). DG development was characterized in PTs using several microscopy techniques. Fourier‐transformed infrared microscopy was established as a novel method to precisely locate polyaromatic compounds, such as hypericin, in plant tissues. In addition, we obtained transcriptome and metabolome profiles of unprecedented resolution in Hypericum. This study addresses for the first time the development of dark glands and identifies genes that constitute strong building blocks for the further elucidation of hypericin synthesis, its manipulation in plants, its engineering in microbial systems, and its applications in medical research.

A crucial feature of plant performance is its strong dependence on the availability of essential mineral nutrients, affecting multiple vital functions. Indeed, mineral-nutrient deficiency is one of the major stress factors affecting plant growth and development. Thereby, nitrogen and potassium represent the most abundant mineral contributors, critical for plant survival. While studying plant responses to nutrient deficiency, one should keep in mind that mineral nutrients, along with their specific metabolic roles, are directly involved in maintaining cell ion homeostasis, which relies on a finely tuned equilibrium between cytosolic and vacuolar ion pools. Therefore, in this chapter we briefly summarize the role of the ion homeostasis system in cell responses to environmental deficiency of nitrate and potassium ions. Special attention is paid to the implementation of plant responses via NO3− and K+ root transport and regulation of ion distribution in cell compartments. These responses are strongly dependent on plant species, as well as severity and duration of nutrient deficiency.

The chapter “Mass Spectrometry Data Processing” focuses on the mass spectrometry data processing workflow. The first step consists of processing the raw MS data using conversion of vendor formats to open standards, followed by feature detection, optionally retention time correction and grouping of features across samples leading to a feature matrix amenable for statistical analysis. The metabolomics community has developed several open source software packages capable of processing large-scale data commonly occurring in metabolomics studies. In the second stage, features of interest are identified, i.e., annotated with names of metabolites, or compound classes. Tandem MS or LC-MS/MS fragmentation data provides structural hints. The MS/MS spectra can be used to search in open and commercial spectral libraries. If no reference spectra are available, in-silico annotation tools or more recently machine learning approaches can be used.

The structure of the microtubule cytoskeleton provides valuable information related to morphogenesis of cells. The cytoskeleton organizes into diverse patterns that vary in cells of different types and tissues, but also within a single tissue. To assess differences in cytoskeleton organization methods are needed that quantify cytoskeleton patterns within a complete cell and which are suitable for large data sets. A major bottleneck in most approaches, however, is a lack of techniques for automatic extraction of cell contours. Here, we present a semi-automatic pipeline for cell segmentation and quantification of microtubule organization. Automatic methods are applied to extract major parts of the contours and a handy image editor is provided to manually add missing information efficiently. Experimental results prove that our approach yields high-quality contour data with minimal user intervention and serves a suitable basis for subsequent quantitative studies.