Efficient DNA assembly methods are essential tools for synthetic biology and metabolic engineering. Among several recently developed methods that allow assembly of multiple DNA fragments in a single step, DNA assembly using type IIS enzymes provides many advantages for complex pathway engineering. In particular, it provides the ability for the user to quickly assemble multigene constructs using a series of simple one-pot assembly steps starting from libraries of cloned and sequenced parts. We describe here a protocol for assembly of multigene constructs using the modular cloning system (MoClo). Making constructs using the MoClo system requires to first define the structure of the final construct to identify all basic parts and vectors required for the construction strategy. Basic parts that are not yet available need to be made. Multigene constructs are then assembled using a series of one-pot assembly steps with the set of identified parts and vectors.

Elucidating the molecular mechanisms underlying plant disease development has become an important aspect of phytoplasma research in the last years. Especially unraveling the function of phytoplasma effector proteins has gained interesting insights into phytoplasma-host interaction at the molecular level. Here, we describe how to analyze and visualize the interaction of a phytoplasma effector with its proteinaceous host partner using bimolecular fluorescence complementation (BiFC) in Nicotiana benthamiana mesophyll protoplasts. The protocol comprises a description of how to isolate protoplasts from leaves and how to transform these protoplasts with BiFC expression vectors containing the phytoplasma effector and the host interaction partner, respectively. If an interaction occurs, a fluorescent YFP-complex is reconstituted in the protoplast, which can be visualized using fluorescence microscopy.

A method for selective and sensitive quantification of amino acids is described. The combination of established derivatization procedures of secondary and primary amino groups with 9-fluorenylmethoxycarbonyl chloride (Fmoc-Cl) and subsequent detection of derivatized amino acids by LC-ESI-MS/MS using multiple reaction monitoring provides high selectivity. The attachment of an apolar moiety enables purification of derivatized amino acids from matrix by a single solid-phase extraction step, which increases sensitivity by reduced ion suppression during LC-ESI-MS/MS detection. Additionally, chromatography of all amino acids can be performed on reversed-phase HPLC columns using eluents without additives, which are known to cause significant decreases in signal to noise ratios. The method has been routinely applied for amino acid profiling of low amounts of liquids and tissues of various origins with a sample throughput of about 50–100 samples a day. In addition to a detailed description of the method, some representative examples are presented.

The microtubule cytoskeleton plays important roles in cell morphogenesis. To investigate the mechanisms of cytoskeletal organization, for example, during growth or development, in genetic studies, or in response to environmental stimuli, image analysis tools for quantitative assessment are needed. Here, we present a method for texture measure-based quantification and comparative analysis of global microtubule cytoskeleton patterns and subsequent visualization of output data. In contrast to other approaches that focus on the extraction of individual cytoskeletal fibers and analysis of their orientation relative to the growth axis, CytoskeletonAnalyzer2D quantifies cytoskeletal organization based on the analysis of local binary patterns. CytoskeletonAnalyzer2D thus is particularly well suited to study cytoskeletal organization in cells where individual fibers are difficult to extract or which lack a clearly defined growth axis, such as leaf epidermal pavement cells. The tool is available as ImageJ plugin and can be combined with publicly available software and tools, such as R and Cytoscape, to visualize similarity networks of cytoskeletal patterns.

Morphological analysis of cell shapes requires segmentation of cell contours from input images and subsequent extraction of meaningful shape descriptors that provide the basis for qualitative and quantitative assessment of shape characteristics. Here, we describe the publicly available ImageJ plugin PaCeQuant and its associated R package PaCeQuantAna, which provides a pipeline for fully automatic segmentation, feature extraction, statistical analysis, and graphical visualization of cell shape properties. PaCeQuant is specifically well suited for analysis of jigsaw puzzle-like leaf epidermis pavement cells from 2D input images and supports the quantification of global, contour-based, skeleton-based, and pavement cell-specific shape descriptors.