Technical Note: mzML and imzML Libraries for Processing Mass Spectrometry Data with the High-Performance Programming Language Julia.

Julia combines the virtues of high-level and low-level programming languages: The code is human-readable, and the performance of the created binaries competes with machine-orientated compilers. Thus, Julia is popular in "Big Data" sciences. Reading mass spectrometry (MS) data with Julia was impossible until now due to missing libraries. Here, we present a Julia library for importing mass spectrometry (MS) data in HUPO standard mzML and imzML formats and demonstrate its function with direct and ambient ionization MS, liquid chromatography-MS, and MS imaging data on standard platforms (Windows, Linux, and Mac OS). The processing speed of Julia for reading imzML MS imaging files was up to 214 times faster than the comparable code in R. Julia can remove bottlenecks for computationally demanding tasks in large-scale MS-Omics and MS imaging data processing workflows and supports their agile development. In addition, time-critical and complex data evaluation tasks become possible, such as following the real-time monitoring of biological processes and pattern recognition in large MS imaging projects. Our mzML/imzML libraries and code examples are available under the terms of the MIT license from https://github.com/CINVESTAV-LABI/julia_mzML_imzML.

Contrast optimization of mass spectrometry imaging (MSI) data visualization by threshold intensity quantization (TrIQ).

Mass spectrometry imaging (MSI) enables the unbiased characterization of surfaces with respect to their chemical composition. In biological MSI, zones with differential mass profiles hint towards localized physiological processes, such as the tissue-specific accumulation of secondary metabolites, or diseases, such as cancer. Thus, the efficient discovery of 'regions of interest' (ROI) is of utmost importance in MSI. However, often the discovery of ROIs is hampered by high background noise and artifact signals. Especially in ambient ionization MSI, unmasking biologically relevant information from crude data sets is challenging. Therefore, we implemented a Threshold Intensity Quantization (TrIQ) algorithm for augmenting the contrast in MSI data visualizations. The simple algorithm reduces the impact of extreme values ('outliers') and rescales the dynamic range of mass signals. We provide an R script for post-processing MSI data in the imzML community format (https://bitbucket.org/lababi/msi.r) and implemented the TrIQ in our open-source imaging software RmsiGUI (https://bitbucket.org/lababi/rmsigui/). Applying these programs to different biological MSI data sets demonstrated the universal applicability of TrIQ for improving the contrast in the MSI data visualization. We show that TrIQ improves a subsequent detection of ROIs by sectioning. In addition, the adjustment of the dynamic signal intensity range makes MSI data sets comparable.

The emerging role of 3D-printing in ion mobility spectrometry and mass spectrometry.

3D-printing is revolutionizing the rapid prototyping in analytical chemistry. In the last few years, we observed the development of 3D-printed components for ion studies, such as ion sources, ion transfer and ion mobility spectrometry (IMS) devices. Often, 3D-printed gadgets add functions to existing mass spectrometry (MS) systems. Custom adapters improve the sensibility for coupling with ambient ionization and upstream chromatography methods, and sample preparation units optimize the following MS analyses. Besides, 3D-printer parts are suitable for constructing custom analytical robots and mass imaging systems. Some of those assemblies implement new concepts and are commercially not available. An essential aspect of using 3D-printing is the fast turnover of design improvements, which is motivated by permissive licenses. The easy reproducibility and exchange of ideas lead to a community-driven development, which is accompanied by economic advantages for public research and education.

Mass spectrometry imaging of thin-layer chromatography plates using laser desorption/low-temperature plasma ionisation.

Thin-layer chromatography (TLC) is a classic method for the separation and analysis of complex mixtures. Biological assays, chemical derivatisation and spectroscopy techniques are compatible with TLC and provide extra information about isolated compounds. However, coupling TLC to mass spectrometry is hampered by the difficulty to desorb the analytes from the silica surfaces. In this study, we used a multimodal ion source for laser desorption (LD) and low-temperature plasma (LTP) post-ionisation. Efficient desorption was reached by covering the TLC plates with activated carbon. Regions of interest can be analysed by spots, by lines or by area. We show the separation of methylxanthines from coffee, tea and cocoa preparations by TLC, with subsequent mass spectrometry imaging (MSI). Using a lateral resolution of 400 µm × 400 µm, allowed the acquisition of 21 895 spectra in 2.4 h (2.5 pixels per s). Further, we demonstrate the possibility of direct mass fragmentation studies and quantification. We mounted the system on an Open LabBot with a theoretical lateral resolution of 12.5 µm and performed the visualisation of ions of interest and the pixel-wise review of mass spectra with our free software RmsiGUI (). This non-proprietary and modular platform enables the cost-efficient adaption of the system and further development by the community.

Elucidating the Distribution of Plant Metabolites from Native Tissues with Laser Desorption Low-Temperature Plasma Mass Spectrometry Imaging.

Secondary metabolites of plants have important biological functions, which often depend on their localization in tissues. Ideally, a fresh untreated material should be directly analyzed to obtain a realistic view of the true sample chemistry. Therefore, there is a large interest for ambient mass-spectrometry-based imaging (MSI) methods. Our aim was to simplify this technology and to find an optimal combination of desorption/ionization principles for a fast ambient MSI of macroscopic plant samples. We coupled a 405 nm continuous wave (CW) ultraviolet (UV) diode laser to a three-dimensionally (3D) printed low-temperature plasma (LTP) probe. By moving the sample with a RepRap-based sampling stage, we could perform imaging of samples up to 16 × 16 cm2. We demonstrate the system performance by mapping mescaline in a San Pedro cactus ( Echinopsis pachanoi) cross section, tropane alkaloids in jimsonweed ( Datura stramonium) fruits and seeds, and nicotine in tobacco ( Nicotiana tabacum) seedlings. In all cases, the anatomical regions of enriched compound concentrations were correctly depicted. The modular design of the laser desorption (LD)-LTP MSI platform, which is mainly assembled from commercial and 3D-printed components, facilitates its adoption by other research groups. The use of the CW-UV laser for desorption enables fast imaging measurements. A complete tobacco seedling with an image size of 9.2 × 15.0 mm2 was analyzed at a pixel size of 100 × 100 µm2 (14 043 mass scans), in less than 2 h. Natural products can be measured directly from native tissues, which inspires a broad use of LD-LTP MSI in plant chemistry studies.