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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.

Medicago truncatula, owing to its small diploid genome (∼500 Mbp), short life cycle, and high natural diversity makes it a good model plant and has opened the door of opportunities for scientists interested in studying legume biology. But over the years, challenges are also being faced for genetic manipulation of this plant. Many genetic manipulation protocols have been published involving Agrobacterium tumefaciens, a pathogen causing tumor disease in plants. These protocols apart from being difficult to achieve, are also time consuming. Nowadays, an easy, less time consuming and highly reproducible Agrobacterium rhizogenes based method is in use by many research groups. This method generates composite plants having transformed roots on a wild‐type shoot. Here, stable transformed lines that can be propagated over time are not achieved by this method, but for root‐development or root–microbe interaction studies this method has proven to be a useful tool for the community. In addition, transformed roots can be propagated by root organ cultures (ROCs), wherein transformed roots are propagated on sucrose containing media without any shoot part. Occasionally, even stable transgenic plants can be regenerated from transgenic roots. In this chapter, developments and improvements of various transformation protocols are discussed. The suitability of composite plants is highlighted by a study on mycorrhization of transformed and non‐transformed roots, which did not show differences in the mycorrhization rate and developmental stages of the arbuscular mycorrhizal (AM) fungus inside the roots as well as in transcript accumulation and metabolite levels of roots. Finally, applications of the A. rhizogenes based transformation method are discussed.

Mass spectrometry coupled with LC (liquid chromatography) separation has developed into a technique routinely applied for targeted as well as for nontargeted analysis of complex biological samples, not only in plant biochemistry. Earlier on, LC‐MS (liquid chromatography–mass spectrometry) was mostly part of the efforts for identification of one or few unknown metabolites of interest as part of a phytochemical study. As a major strategy, unknown compounds had to be purified in sufficient quantities. The purified fractions were then subjected to LC‐MS/MS as part of the structural elucidation, mostly complemented by NMR (nuclear magnetic resonance) analysis. With the advance of mass spectrometry instrumentation, LC‐MS is now widely applied for analysis of crude plant extracts and large numbers (100s to 1000s) of samples. It has become an essential part of metabolomic studies (see Metabolomics), aiming at the comprehensive coverage of the metabolite profiles of cells, tissues, or organs. Owing to the huge chemical diversity of small molecules, conditions for the extraction will restrict the subfraction of the metabolome, which can be actually analyzed. The conditions for LC have to be adjusted to allow good separation of the particular metabolites from the respective extract. Major consideration will be the selection of an appropriate column and suitable eluents, the establishment of gradient profiles, temperature conditions, and so on.

Plant glandular trichomes are epidermal differentiations that are dedicated to the production of specialized metabolites, which constitute a first line of defense against pathogens and herbivores. The secretions of these metabolic factories are chemically very diverse, including of terpenoid, fatty acid, or phenylpropanoid origins. They find uses in various industrial areas, for example as pharmaceutical, flavor, or fragrance ingredients or as insecticides. Recent progress in the elucidation of biosynthesis pathways for these compounds has opened up novel opportunities for metabolic engineering in microorganisms as well as in plants.

Transcription activator‐like effectors (TALEs) can be programmed to bind specific DNA sequences. This property was used to construct libraries of synthetic TALE‐activated promoters (STAPs), which drive varying levels of gene expression. After a brief description of these promoters, we explore how these STAPs can be used for various applications in plant synthetic biology, in particular for the coordinated expression of multiple genes for metabolic engineering and in the design and implementation of gene regulatory networks.

There is growing interest in the application of plant functional trait-based approaches for development of sustainable land-use strategies. In this context, one crucial task is to identify and measure plant traits, which respond to land-use intensity (response traits) and simultaneously have an impact on ecosystem functions (effect traits). We hypothesized that species-specific leaf chemical composition, which may function both as response and effect trait, can be derived from Attenuated Total Reflection Fourier Transform Infrared (ATR-FTIR) spectroscopy tools in combination with multivariate statistical methods We investigated leaf ATR-FTIR spectra of two grasses, Poa pratensis L. and Dactylis glomerata L., and one forb, Achillea millefolium L. collected in grassland plots along a land-use intensity gradient in three regions of Germany. ATR-FTIR spectra appear to function as biochemical fingerprints unique to each species. The spectral response to land-use intensity was not consistent among species and less apparent in the two grasses than in the forb species. Whereas land-use intensification enhanced protein and cellulose content in A. millefolium, giving rise to changes in six spectral bands in the frequency range of 1088–1699 cm−1, only cellulose content increased in D. glomerata, affecting the bands of 1385–1394 cm−1. Poa pratensis spectra exhibited minimal changes under the influence of land-use, only in the spectral bands of 1373–1375 cm−1 associated with suberin-like aliphatic compounds. Our findings suggest that some species’ leaf chemical composition is responsive to land-use intensity, and thus, may have a predictive value for ecosystem services provided by those species within grassland vegetation (i.e., herbage yield quality).

This chapter discusses theoretical analyses and experimental studies of biologically and medicinally relevant macrocyclic compounds (MCs). The most important groups of macrocyclic natural products—excluding cyclopeptides—are discussed on the basis of selected examples. A common principle in the biosynthesis of most natural MCs is the primary synthesis of a linear precursor, followed by macrocyclization. Modification of the MC then leads to the final natural product. The chapter also focuses on the aspects of structure‐activity relationships (SAR) of macrocycles derived from chemoinformatic analyses and related theoretical methods. It further reviews the few examples that clearly show how chemoinformatics and modeling techniques, such as docking studies, can contribute essential information for drug design to improve their properties (mostly bioavailability or potency) and help to analyze and understand SAR of MCs. Finally, the chapter explores known aspects of quantitative SAR (QSAR) related to anticancer activities, antibiotics, HIV treatments, and other diseases.