Periodic Reporting for period 1 - MASS2 (Modern Au-based Surfaces and Secondary ionisation for Mass Spectrometry Imaging of Small molecules)
Reporting period: 2022-06-01 to 2024-05-31
Matrix-assisted laser desorption/ionisation (MALDI) mass spectrometry imaging (MSI) is a modern analytical technique that can map the distribution of numerous biochemical substances in tissue sections. It is increasingly used in life science research as in clinical application due to the untargeted and comprehensive approach that can yield superior density of information compared to conventional histology techniques. However, MALDI inherently suffers from several major limitations such as low ion yields limited to a few classes of polar to mid-polar analytes, strong ion suppression effects, and an impeded detection of low-weight compounds. This hampers the comprehensive analysis for complex biomedical questions. Thus, technical advancements seek to overcome these limitations: Surface-assisted LDI (SALDI) uses photoactive surfaces with unique ablation and ionisation features that can majorly extend the range of detectable compounds, whereas Postionisation (PI) can significantly increase the ion yields for numerous compounds and level out ion suppression. Both techniques have demonstrated their power for MSI application.
MASS2 - Modern Au-based Surfaces and Secondary ionisation for Mass Spectrometry Imaging of Small molecules - aimed to develop a novel means for extensive metabolome and lipidome analysis by SALDI-PI-MSI to overcome limitations of MALDI. For this, the first Objective dealt with the successfully combination of a new PI strategy coined Single-Photon Induced Chemical Ionisation (SPICI) with functionalised Au layers. With this, the chemical coverage of compounds in biomedical tissue sections could be extended, especially for an extended mass range below 500 Da, and with high mass and spatial resolution. Objective 2 aimed for the parameter optimisation and identification of key settings for a comprehensive analysis. As a result, a large number of endogenous analytes were detected that could not be detected with conventional MALDI-MSI or SALDI-MSI systems before. Complex data outputs were analyzed with the versatile in-house developed software package rMSI that facilitated routine data mining, in Objective 3. The new technical possibilities were demonstrated in the analysis of two sample systems of high relevance in the life science research in Objective 4. First, MASS2 allowed monitoring of physiological processes in tumor tissue sections from human bladder cancer at unprecedented analytical depth. Newly identified biomarkers will help the urgent need for prognostic and diagnostic means for cancer. Second, an optimized sample protocol for the analysis and comprehensive spatial biochemical characterisation of zebra fish embryos was developed. This can now serve as a fast and scalable template for, e.g. future toxicology/exposome studies. These comprehensive approaches generate massive data that will reveal new insight of physiological processes underlying the interaction of toxicants with metabolism MASS2 allowed for the creation of a platform to offer these advanced services to cooperation partners in the local and national biomedical research network and contribute to major discoveries in life sciences in comprehensive, multidisciplinary fashion.
MASS2 - Modern Au-based Surfaces and Secondary ionisation for Mass Spectrometry Imaging of Small molecules - aimed to develop a novel means for extensive metabolome and lipidome analysis by SALDI-PI-MSI to overcome limitations of MALDI. For this, the first Objective dealt with the successfully combination of a new PI strategy coined Single-Photon Induced Chemical Ionisation (SPICI) with functionalised Au layers. With this, the chemical coverage of compounds in biomedical tissue sections could be extended, especially for an extended mass range below 500 Da, and with high mass and spatial resolution. Objective 2 aimed for the parameter optimisation and identification of key settings for a comprehensive analysis. As a result, a large number of endogenous analytes were detected that could not be detected with conventional MALDI-MSI or SALDI-MSI systems before. Complex data outputs were analyzed with the versatile in-house developed software package rMSI that facilitated routine data mining, in Objective 3. The new technical possibilities were demonstrated in the analysis of two sample systems of high relevance in the life science research in Objective 4. First, MASS2 allowed monitoring of physiological processes in tumor tissue sections from human bladder cancer at unprecedented analytical depth. Newly identified biomarkers will help the urgent need for prognostic and diagnostic means for cancer. Second, an optimized sample protocol for the analysis and comprehensive spatial biochemical characterisation of zebra fish embryos was developed. This can now serve as a fast and scalable template for, e.g. future toxicology/exposome studies. These comprehensive approaches generate massive data that will reveal new insight of physiological processes underlying the interaction of toxicants with metabolism MASS2 allowed for the creation of a platform to offer these advanced services to cooperation partners in the local and national biomedical research network and contribute to major discoveries in life sciences in comprehensive, multidisciplinary fashion.
In this project, I installed and adapted a new prototype of a SPICI postionisation module and combined it with surface-assisted LDI-MSI. The SPICI module was previously developed in cooperation with the University of Münster, Germany for the new version of the ion source installed in our MS system - the Spectroglyph Dual MALDI/ESI Injector. In the work group, we designed a new class E amplifier for the PI source and then, I optimized the system for LDI-PI-MSI – first, with classic organic matrices, and thereafter, with gold nanolayers, which were deposited on thin tissue sections by gas phase deposition. As a sample system for the optimisation process, I prepared a series of homogeneous tissue samples from cow brain that served as a standard and quality control throughout the whole project.
LDI-SPICI-MSI proved to be successful, after identification of critical parameters, e.g. in-source pressure, dopant concentration, and delay between the ablation laser and VUV pulse initiating the postionisation reaction. I could achieve major postionisation effects on glycerophopholipids and other lipids by adding acetone as a dopant, similar to the use of organic matrix.
For the next objective, I investigated the use of different dopants and different nanostructured layers in order to enhance less polar groups of analytes with the PI step. However, the ion funnel could not operate stably with dopants initiating electron transfer reactions, and even though postionisation effects were visible, I had to conclude that SPICI is limited to the use of proton transfer agents such as acetone and isopropanol in this ion funnel ion source. I next investigated different sputtering times, i.e. different thicknesses of deposited Au nanostructures and identified that the sputtering times used for LDI-MSI without PI yielded the strongest PI signals as well, confirming this sample preparation step as universal between both measurement modes. The use of other nano-layers did not yield better PI signals than Au.
One major observation in this work package was that – unlike the common glycerophospholipids – smaller metabolites <500 Da could successfully be postionized without the use of a chemical dopant in the gas phase. This also majorly reduced the intensity of background ion signals, allowing me to measure spatial metabolomics in a mass range previously not accessible. With this augmentation of analytical depth, I could successfully finish the second objective of MASS2, demonstrated on the analysis of animal tissue sections with high morphological distribution of numerous chemical compounds.
The acquired data was analyzed with the dedicated in-house software rMSI that allowed for identification of key parameters to detected the greatest analytical depth based on statistical means. Also, the reproducibility and reliability of the measurement strategy was monitored in this fashion. Therefore, I wrote a universal templated for a markdown in R language that included several analytical steps and facilitated the data analysis and the overview of technical advance. The detected signals were tentatively annotated based on data bases and with acquired MS/MS spectra, and the detected analyte classes listed in tables, indicating the measurement parameters for a successful detection, e.g. the used matrix, polarity, and dopant.
As the last step, a large set of UBC tissue was measured with Au-nanostructured LDI-MSI and yielded a high level of data quality for the entire set. The data analysis assessed the intra-tumor heterogeneity with unsupervised image segmentation strategies, and identified new prognostic and diagnostic biomarkers. For the second sample set of ZFE, we identified an optimal tissue embedding media allowing for an assay of up to 100 sections on a single MSI slide and compared the analytical depths of different MS systems (Orbitrap Exploris and timsTOF flex) using different matrices (DAN,NOR,DHB) and Au-nano structures in both ion modes. Furthermore, we conducted postionisation with LDI-SPICI-MSI combined with Au-nanostructures for spatial metabolomics in the smallest mass range <300Da complementary to the commercial MALDI-2 technique.
LDI-SPICI-MSI proved to be successful, after identification of critical parameters, e.g. in-source pressure, dopant concentration, and delay between the ablation laser and VUV pulse initiating the postionisation reaction. I could achieve major postionisation effects on glycerophopholipids and other lipids by adding acetone as a dopant, similar to the use of organic matrix.
For the next objective, I investigated the use of different dopants and different nanostructured layers in order to enhance less polar groups of analytes with the PI step. However, the ion funnel could not operate stably with dopants initiating electron transfer reactions, and even though postionisation effects were visible, I had to conclude that SPICI is limited to the use of proton transfer agents such as acetone and isopropanol in this ion funnel ion source. I next investigated different sputtering times, i.e. different thicknesses of deposited Au nanostructures and identified that the sputtering times used for LDI-MSI without PI yielded the strongest PI signals as well, confirming this sample preparation step as universal between both measurement modes. The use of other nano-layers did not yield better PI signals than Au.
One major observation in this work package was that – unlike the common glycerophospholipids – smaller metabolites <500 Da could successfully be postionized without the use of a chemical dopant in the gas phase. This also majorly reduced the intensity of background ion signals, allowing me to measure spatial metabolomics in a mass range previously not accessible. With this augmentation of analytical depth, I could successfully finish the second objective of MASS2, demonstrated on the analysis of animal tissue sections with high morphological distribution of numerous chemical compounds.
The acquired data was analyzed with the dedicated in-house software rMSI that allowed for identification of key parameters to detected the greatest analytical depth based on statistical means. Also, the reproducibility and reliability of the measurement strategy was monitored in this fashion. Therefore, I wrote a universal templated for a markdown in R language that included several analytical steps and facilitated the data analysis and the overview of technical advance. The detected signals were tentatively annotated based on data bases and with acquired MS/MS spectra, and the detected analyte classes listed in tables, indicating the measurement parameters for a successful detection, e.g. the used matrix, polarity, and dopant.
As the last step, a large set of UBC tissue was measured with Au-nanostructured LDI-MSI and yielded a high level of data quality for the entire set. The data analysis assessed the intra-tumor heterogeneity with unsupervised image segmentation strategies, and identified new prognostic and diagnostic biomarkers. For the second sample set of ZFE, we identified an optimal tissue embedding media allowing for an assay of up to 100 sections on a single MSI slide and compared the analytical depths of different MS systems (Orbitrap Exploris and timsTOF flex) using different matrices (DAN,NOR,DHB) and Au-nano structures in both ion modes. Furthermore, we conducted postionisation with LDI-SPICI-MSI combined with Au-nanostructures for spatial metabolomics in the smallest mass range <300Da complementary to the commercial MALDI-2 technique.
In the first two work packages, MASS2 yielded the development of a powerful alternative approach for MSI. Au-based LDI-SPICI-MSI offers a superior analytical depth for the characterisation of biological tissue sections. The technique is versatile and can be measured at high laser repetition rates with highest reproducibility and analytical quality. Especially the spatial detection of smallest metabolites <500 mDa offers unpreceded insights in cellular communication and, e.g. the progression of diseases. The system allows furthermore for analyte characterisation with tandem MS. The potential of LDI-SPICI-MSI was demonstrated on different animal tissue sections such as mouse cerebellum and pancreas sections. The developed packages for the facilitated and versatile data mining are open-source and shared on our github profile. In two pilot studies, we analyzed a large cohort of urinary bladder cancer tissue sections and developed an optimized protocol for the analysis of zebra fish embryos. Our results revealed benefits of the LDI-MSI approach for optimized tissue characterisation, in combination with multimodalities and patient meta data. MASS2 revealed several tentative biomarkers of Urinary Bladder Cancer that will be considered in follow-up studies to aid the prognostics of this devastating disease. Further research is needed to validate the results and broaden the impact, implementation into clinical routine analysis.
MASS2 established a new line of research at the host institute covering all steps of the analysis from controlled sample preparation, revolutionary data acquisition, and adapted data mining. The developed measurement protocols present a stable routine for validated comprehensive biochemical analysis. They facilitate, e.g. targeted toxicological studies, and ease the detection of biomarkers in this biological model. This constitutes a major contribution to the local network of biomedical research in Catalonia. The new prototype of the SPICI ion source module will be available for academic partners in collaboration with the University of Münster and Spectroglyph, LLC. All of the results of MASS where or will be published and shared with peers on national and international conferences for an enhanced exchange of knowledge and good use of technical resources with collaboration partners benefiting from the results of this MSCA.
MASS2 established a new line of research at the host institute covering all steps of the analysis from controlled sample preparation, revolutionary data acquisition, and adapted data mining. The developed measurement protocols present a stable routine for validated comprehensive biochemical analysis. They facilitate, e.g. targeted toxicological studies, and ease the detection of biomarkers in this biological model. This constitutes a major contribution to the local network of biomedical research in Catalonia. The new prototype of the SPICI ion source module will be available for academic partners in collaboration with the University of Münster and Spectroglyph, LLC. All of the results of MASS where or will be published and shared with peers on national and international conferences for an enhanced exchange of knowledge and good use of technical resources with collaboration partners benefiting from the results of this MSCA.