Building expression constructs for transgenesis is one of the fundamental day-to-day tasks in modern biology. Traditionally it is based on a multitude of type II restriction endonucleases and T4 DNA ligase. Especially in case of long inserts and applications requiring high-throughput, this approach is limited by the number of available unique restriction sites and the need for designing individual cloning strategies for each project. Several alternative cloning systems have been developed in recent years to overcome these issues, including the type IIS enzyme based Golden Gate technique. Here we introduce our GreenGate system for rapidly assembling plant transformation constructs, which is based on the Golden Gate method. GreenGate cloning is simple and efficient since it uses only one type IIS restriction endonuclease, depends on only six types of insert modules (plant promoter, N-terminal tag, coding sequence, C-terminal tag, plant terminator and plant resistance cassette), but at the same time allows assembling several expression cassettes in one binary destination vector from a collection of pre-cloned building blocks. The system is cheap and reliable and when combined with a library of modules considerably speeds up cloning and transgene stacking for plant transformation.

Chemical cross-linking mass spectrometry (XL-MS) provides protein structural information by identifying covalently linked proximal amino acid residues on protein surfaces. The information gained by this technique is complementary to other structural biology methods such as x-ray crystallography, NMR and cryo-electron microscopy[1]. The extension of traditional quantitative proteomics methods with chemical cross-linking can provide information on the structural dynamics of protein structures and protein complexes. The identification and quantitation of cross-linked peptides remains challenging for the general community, requiring specialized expertise ultimately limiting more widespread adoption of the technique. We describe a general method for targeted quantitative mass spectrometric analysis of cross-linked peptide pairs. We report the adaptation of the widely used, open source software package Skyline, for the analysis of quantitative XL-MS data as a means for data analysis and sharing of methods. We demonstrate the utility and robustness of the method with a cross-laboratory study and present data that is supported by and validates previously published data on quantified cross-linked peptide pairs. This advance provides an easy to use resource so that any lab with access to a LC-MS system capable of performing targeted quantitative analysis can quickly and accurately measure dynamic changes in protein structure and protein interactions.

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