Reproducible mass spectrometry data processing and compound annotation in MZmine 3.

Untargeted mass spectrometry (MS) experiments produce complex, multidimensional data that are practically impossible to investigate manually. For this reason, computational pipelines are needed to extract relevant information from raw spectral data and convert it into a more comprehensible format. Depending on the sample type and/or goal of the study, a variety of MS platforms can be used for such analysis. MZmine is an open-source software for the processing of raw spectral data generated by different MS platforms. Examples include liquid chromatography-MS, gas chromatography-MS and MS-imaging. These data might typically be associated with various applications including metabolomics and lipidomics. Moreover, the third version of the software, described herein, supports the processing of ion mobility spectrometry (IMS) data. The present protocol provides three distinct procedures to perform feature detection and annotation of untargeted MS data produced by different instrumental setups: liquid chromatography-(IMS-)MS, gas chromatography-MS and (IMS-)MS imaging. For training purposes, example datasets are provided together with configuration batch files (i.e., list of processing steps and parameters) to allow new users to easily replicate the described workflows. Depending on the number of data files and available computing resources, we anticipate this to take between 2 and 24 h for new MZmine users and nonexperts. Within each procedure, we provide a detailed description for all processing parameters together with instructions/recommendations for their optimization. The main generated outputs are represented by aligned feature tables and fragmentation spectra lists that can be used by other third-party tools for further downstream analysis.

Lessons learned in a decade: Medical-toxicological view of tattooing.

Tattooing has been part of the human culture for thousands of years, yet only in the past decades has it entered the mainstream of the society. With the rise in popularity, tattoos also gained attention among researchers, with the aim to better understand the health risks posed by their application. 'A medical-toxicological view of tattooing'-a work published in The Lancet almost a decade ago, resulted from the international collaboration of various experts in the field. Since then, much understanding has been achieved regarding adverse effects, treatment of complications, as well as their regulation for improving public health. Yet major knowledge gaps remain. This review article results from the Second International Conference on Tattoo Safety hosted by the German Federal Institute for Risk Assessment (BfR) and provides a glimpse from the medical-toxicological perspective, regulatory strategies and advances in the analysis of tattoo inks.

On-tissue dataset-dependent MALDI-TIMS-MS2 bioimaging.

Trapped ion mobility spectrometry (TIMS) adds an additional separation dimension to mass spectrometry (MS) imaging, however, the lack of fragmentation spectra (MS2) impedes confident compound annotation in spatial metabolomics. Here, we describe spatial ion mobility-scheduled exhaustive fragmentation (SIMSEF), a dataset-dependent acquisition strategy that augments TIMS-MS imaging datasets with MS2 spectra. The fragmentation experiments are systematically distributed across the sample and scheduled for multiple collision energies per precursor ion. Extendable data processing and evaluation workflows are implemented into the open source software MZmine. The workflow and annotation capabilities are demonstrated on rat brain tissue thin sections, measured by matrix-assisted laser desorption/ionisation (MALDI)-TIMS-MS, where SIMSEF enables on-tissue compound annotation through spectral library matching and rule-based lipid annotation within MZmine and maps the (un)known chemical space by molecular networking. The SIMSEF algorithm and data analysis pipelines are open source and modular to provide a community resource.

Mobility-resolved broadband dissociation and parallel reaction monitoring for laser desorption/ionization-mass spectrometry - Tattoo pigment identification supported by trapped ion mobility spectrometry.

In this work, trapped ion mobility spectrometry (TIMS) was introduced to facilitate tandem mass spectrometry (MS2) experiments for laser desorption/ionization-mass spectrometry (LDI-MS) as mobility-resolved fragmentation. The mobility separation of desorbed ions was followed by subsequent fragmentation using data-independent broadband collision-induced dissociation (bbCID) or targeted fragmentation through a prototypic version of parallel reaction monitoring-parallel accumulation serial fragmentation (prm-PASEF) for LDI. Both mobility-resolved fragmentation options, TIMS-bbCID and prm-PASEF, were applied to LDI point measurements to identify organic pigments in tattoo inks. Furthermore, the prototypic prm-PASEF algorithm was used in imaging applications to increase confidence in annotating organic tattoo pigments in skin samples with adverse reactions. Due to less complex spectra in matrix-free LDI, both fragmentation methods yielded fast and reliable MS2 identification workflows. TIMS-bbCID was especially beneficial for the rapid acquisition of multiple fragment spectra. For the targeted prm-PASEF approach, analytes' mobilities needed to be collected prior to simplified fragmentation. Therefore, a reference list for 14 pigments was created. The possible number of experiments per thin section and the associated savings in analysis time compared to conventional MS2 were particularly suitable for the imaging application. Furthermore, the mobility dimension enabled a new orthogonal identification parameter, increasing the annotation confidence of tattoo pigments through compound specific mobilities.

Tattoo Pigment Identification in Inks and Skin Biopsies of Adverse Reactions by Complementary Elemental and Molecular Bioimaging with Mass Spectral Library Matching.

Tattooing has become increasingly popular throughout society. Despite the recognized issue of adverse reactions in tattoos, regulations remain challenging with limited data available and a missing positive list. The diverse chemical properties of mostly insoluble inorganic and organic pigments pose an outstanding analytical challenge, which typically requires extensive sample preparation. Here, we present a multimodal bioimaging approach combining micro X-ray fluorescence (µXRF) and laser desorption ionization-mass spectrometry (LDI-MS) to detect the elemental and molecular composition in the same sample. The pigment structures directly absorb the laser energy, eliminating the need for matrix application. A computational data processing workflow clusters spatially resolved LDI-MS scans to merge redundant information into consensus spectra, which are then matched against new open mass spectral libraries of tattoo pigments. When applied to 13 tattoo inks and 68 skin samples from skin biopsies in adverse tattoo reactions, characteristic signal patterns of isotopes, ion adducts, and in-source fragments in LDI-MS1 scans yielded confident compound annotations across various pigment classes. Combined with µXRF, pigment annotations were achieved for all skin samples with 14 unique structures and 2 inorganic pigments, emphasizing the applicability to larger studies. The tattoo-specific spectral libraries and further information are available on the tattoo-analysis.github.io website.