Janina Oetjen

Exploring Three-Dimensional Matrix-Assisted Laser Desorption/Ionization Imaging Mass Spectrometry Data: Three-Dimensional Spatial Segmentation of Mouse Kidney

Three-dimensional (3D) imaging has a significant impact on many challenges of life sciences. Three-dimensional matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) is an emerging label-free bioanalytical technique capturing the spatial distribution of hundreds of molecular compounds in 3D by providing a MALDI mass spectrum for each spatial point of a 3D sample. Currently, 3D MALDI-IMS cannot tap its full potential due to the lack efficient computational methods for constructing, processing, and visualizing large and complex 3D MALDI-IMS data. We present a new pipeline of efficient computational methods, which enables analysis and interpretation of a 3D MALDI-IMS data set. Construction of a MALDI-IMS data set was done according to the state-of-the-art protocols and involved sample preparation, spectra acquisition, spectra preprocessing, and registration of serial sections. For analysis and interpretation of 3D MALDI-IMS data, we applied the spatial segmentation approach which is well-accepted in analysis of two-dimensional (2D) MALDI-IMS data. In line with 2D data analysis, we used edge-preserving 3D image denoising prior to segmentation to reduce strong and chaotic spectrum-to-spectrum variation. For segmentation, we used an efficient clustering method, called bisecting k-means, which is optimized for hierarchical clustering of a large 3D MALDI-IMS data set. Using the proposed pipeline, we analyzed a central part of a mouse kidney using 33 serial sections of 3.5 μm thickness after the PAXgene tissue fixation and paraffin embedding. For each serial section, a 2D MALDI-IMS data set was acquired following the standard protocols with the high spatial resolution of 50 μm. Altogether, 512 495 mass spectra were acquired that corresponds to approximately 50 gigabytes of data. After registration of serial sections into a 3D data set, our computational pipeline allowed us to reveal the 3D kidney anatomical structure based on mass spectrometry data only. Finally, automated analysis discovered molecular masses colocalized with major anatomical regions. In the same way, the proposed pipeline can be used for analysis and interpretation of any 3D MALDI-IMS data set in particular of pathological cases.

2D and 3D MALDI-imaging: conceptual strategies for visualization and data mining.

3D imaging has a significant impact on many challenges in life sciences, because biology is a 3-dimensional phenomenon. Current 3D imaging-technologies (various types MRI, PET, SPECT) are labeled, i.e. they trace the localization of a specific compound in the body. In contrast, 3D MALDI mass spectrometry-imaging (MALDI-MSI) is a label-free method imaging the spatial distribution of molecular compounds. It complements 3D imaging labeled methods, immunohistochemistry, and genetics-based methods. However, 3D MALDI-MSI cannot tap its full potential due to the lack of statistical methods for analysis and interpretation of large and complex 3D datasets. To overcome this, we established a complete and robust 3D MALDI-MSI pipeline combined with efficient computational data analysis methods for 3D edge preserving image denoising, 3D spatial segmentation as well as finding colocalized m/z values, which will be reviewed here in detail. Furthermore, we explain, why the integration and correlation of the MALDI imaging data with other imaging modalities allows to enhance the interpretation of the molecular data and provides visualization of molecular patterns that may otherwise not be apparent. Therefore, a 3D data acquisition workflow is described generating a set of 3 different dimensional images representing the same anatomies. First, an in-vitro MRI measurement is performed which results in a three-dimensional image modality representing the 3D structure of the measured object. After sectioning the 3D object into N consecutive slices, all N slices are scanned using an optical digital scanner, enabling for performing the MS measurements. Scanning the individual sections results into low-resolution images, which define the base coordinate system for the whole pipeline. The scanned images conclude the information from the spatial (MRI) and the mass spectrometric (MALDI-MSI) dimension and are used for the spatial three-dimensional reconstruction of the object performed by image registration techniques. Different strategies for automatic serial image registration applied to MS datasets are outlined in detail. The third image modality is histology driven, i.e. a digital scan of the histological stained slices in high-resolution. After fusion of reconstructed scan images and MRI the slice-related coordinates of the mass spectra can be propagated into 3D-space. After image registration of scan images and histological stained images, the anatomical information from histology is fused with the mass spectra from MALDI-MSI. As a result of the described pipeline we have a set of 3 dimensional images representing the same anatomies, i.e. the reconstructed slice scans, the spectral images as well as corresponding clustering results, and the acquired MRI. Great emphasis is put on the fact that the co-registered MRI providing anatomical details improves the interpretation of 3D MALDI images. The ability to relate mass spectrometry derived molecular information with in vivo and in vitro imaging has potentially important implications. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

MRI-compatible pipeline for three-dimensional MALDI imaging mass spectrometry using PAXgene fixation

UNLABELLED MALDI imaging mass spectrometry (MALDI-imaging) has emerged as a spatially-resolved label-free bioanalytical technique for direct analysis of biological samples and was recently introduced for analysis of 3D tissue specimens. We present a new experimental and computational pipeline for molecular analysis of tissue specimens which integrates 3D MALDI-imaging, magnetic resonance imaging (MRI), and histological staining and microscopy, and evaluate the pipeline by applying it to analysis of a mouse kidney. To ensure sample integrity and reproducible sectioning, we utilized the PAXgene fixation and paraffin embedding and proved its compatibility with MRI. Altogether, 122 serial sections of the kidney were analyzed using MALDI-imaging, resulting in a 3D dataset of 200GB comprised of 2million spectra. We show that elastic image registration better compensates for local distortions of tissue sections. The computational analysis of 3D MALDI-imaging data was performed using our spatial segmentation pipeline which determines regions of distinct molecular composition and finds m/z-values co-localized with these regions. For facilitated interpretation of 3D distribution of ions, we evaluated isosurfaces providing simplified visualization. We present the data in a multimodal fashion combining 3D MALDI-imaging with the MRI volume rendering and with light microscopic images of histologically stained sections. BIOLOGICAL SIGNIFICANCE Our novel experimental and computational pipeline for 3D MALDI-imaging can be applied to address clinical questions such as proteomic analysis of the tumor morphologic heterogeneity. Examining the protein distribution as well as the drug distribution throughout an entire tumor using our pipeline will facilitate understanding of the molecular mechanisms of carcinogenesis.

Benchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry

BackgroundThree-dimensional (3D) imaging mass spectrometry (MS) is an analytical chemistry technique for the 3D molecular analysis of a tissue specimen, entire organ, or microbial colonies on an agar plate. 3D-imaging MS has unique advantages over existing 3D imaging techniques, offers novel perspectives for understanding the spatial organization of biological processes, and has growing potential to be introduced into routine use in both biology and medicine. Owing to the sheer quantity of data generated, the visualization, analysis, and interpretation of 3D imaging MS data remain a significant challenge. Bioinformatics research in this field is hampered by the lack of publicly available benchmark datasets needed to evaluate and compare algorithms.FindingsHigh-quality 3D imaging MS datasets from different biological systems at several labs were acquired, supplied with overview images and scripts demonstrating how to read them, and deposited into MetaboLights, an open repository for metabolomics data. 3D imaging MS data were collected from five samples using two types of 3D imaging MS. 3D matrix-assisted laser desorption/ionization imaging (MALDI) MS data were collected from murine pancreas, murine kidney, human oral squamous cell carcinoma, and interacting microbial colonies cultured in Petri dishes. 3D desorption electrospray ionization (DESI) imaging MS data were collected from a human colorectal adenocarcinoma.ConclusionsWith the aim to stimulate computational research in the field of computational 3D imaging MS, selected high-quality 3D imaging MS datasets are provided that could be used by algorithm developers as benchmark datasets.

On the Importance of Mathematical Methods for Analysis of MALDI-Imaging Mass Spectrometry Data

In the last decade, matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS), also called as MALDI-imaging, has proven its potential in proteomics and was successfully applied to various types of biomedical problems, in particular to histopathological label-free analysis of tissue sections. In histopathology, MALDI-imaging is used as a general analytic tool revealing the functional proteomic structure of tissue sections, and as a discovery tool for detecting new biomarkers discriminating a region annotated by an experienced histologist, in particular, for cancer studies. A typical MALDI-imaging data set contains 10⁸ to 10⁹ intensity values occupying more than 1 GB. Analysis and interpretation of such huge amount of data is a mathematically, statistically and computationally challenging problem. In this paper we overview some computational methods for analysis of MALDI-imaging data sets. We discuss the importance of data preprocessing, which typically includes normalization, baseline removal and peak picking, and hightlight the importance of image denoising when visualizing IMS data.

Rapid Recovery of Cyanobacterial Pigments in Desiccated Biological Soil Crusts following Addition of Water

We examined soil surface colour change to green and hydrotaxis following addition of water to biological soil crusts using pigment extraction, hyperspectral imaging, microsensors and 13C labeling experiments coupled to matrix-assisted laser desorption and ionization time of flight-mass spectrometry (MALD-TOF MS). The topsoil colour turned green in less than 5 minutes following water addition. The concentrations of chlorophyll a (Chl a), scytonemin and echinenon rapidly increased in the top <1 mm layer while in the deeper layer, their concentrations remained low. Hyperspectral imaging showed that, in both wet and dehydrated crusts, cyanobacteria formed a layer at a depth of 0.2–0.4 mm and this layer did not move upward after wetting. 13C labeling experiments and MALDI TOF analysis showed that Chl a was already present in the desiccated crusts and de novo synthesis of this molecule started only after 2 days of wetting due to growth of cyanobacteria. Microsensor measurements showed that photosynthetic activity increased concomitantly with the increase of Chl a, and reached a maximum net rate of 92 µmol m−2 h−1 approximately 2 hours after wetting. We conclude that the colour change of soil crusts to green upon water addition was not due to hydrotaxis but rather to the quick recovery and reassembly of pigments. Cyanobacteria in crusts can maintain their photosynthetic apparatus intact even under prolonged periods of desiccation with the ability to resume their photosynthetic activities within minutes after wetting.

MALDI imaging mass spectrometry: discrimination of pathophysiological regions in traumatized skeletal muscle by characteristic peptide signatures.

Due to formation of fibrosis and the loss of contractile muscle tissue, severe muscle injuries often result in insufficient healing marked by a significant reduction of muscle force and motor activity. Our previous studies demonstrated that the local transplantation of mesenchymal stromal cells into an injured skeletal muscle of the rat improves the functional outcome of the healing process. Since, due to the lack of sufficient markers, the accurate discrimination of pathophysiological regions in injured skeletal muscle is inadequate, underlying mechanisms of the beneficial effects of mesenchymal stromal cell transplantation on primary trauma and trauma adjacent muscle area remain elusive. For discrimination of these pathophysiological regions, formalin‐fixed injured skeletal muscle tissue was analyzed by MALDI imaging MS. By using two computational evaluation strategies, a supervised approach (ClinProTools) and unsupervised segmentation (SCiLS Lab), characteristic m/z species could be assigned to primary trauma and trauma adjacent muscle regions. Using “bottom‐up” MS for protein identification and validation of results by immunohistochemistry, we could identify two proteins, skeletal muscle alpha actin and carbonic anhydrase III, which discriminate between the secondary damage on adjacent tissue and the primary traumatized muscle area. Our results underscore the high potential of MALDI imaging MS to describe the spatial characteristics of pathophysiological changes in muscle.

Molecular and chemical dialogues in bacteria-protozoa interactions

Protozoan predation of bacteria can significantly affect soil microbial community composition and ecosystem functioning. Bacteria possess diverse defense strategies to resist or evade protozoan predation. For soil-dwelling Pseudomonas species, several secondary metabolites were proposed to provide protection against different protozoan genera. By combining whole-genome transcriptome analyses with (live) imaging mass spectrometry (IMS), we observed multiple changes in the molecular and chemical dialogues between Pseudomonas fluorescens and the protist Naegleria americana. Lipopeptide (LP) biosynthesis was induced in Pseudomonas upon protozoan grazing and LP accumulation transitioned from homogeneous distributions across bacterial colonies to site-specific accumulation at the bacteria-protist interface. Also putrescine biosynthesis was upregulated in P. fluorescens upon predation. We demonstrated that putrescine induces protozoan trophozoite encystment and adversely affects cyst viability. This multifaceted study provides new insights in common and strain-specific responses in bacteria-protozoa interactions, including responses that contribute to bacterial survival in highly competitive soil and rhizosphere environments.

Mass spectrometric characterization of the covalent modification of the nitrogenase Fe‐protein in Azoarcus sp. BH72

Nitrogenase Fe‐protein modification was analyzed in the endophytic β‐proteobacterium Azoarcus sp. BH72. Application of modern MS techniques localized the modification in the peptide sequence and revealed it to be an ADP‐ribosylation on Arg102 of one subunit of nitrogenase Fe‐protein. A double digest with trypsin and endoproteinase Asp‐N was necessary to obtain an analyzable peptide because the modification blocked the trypsin cleavage site at this residue. Furthermore, a peptide extraction protocol without trifluoroacetic acid was crucial to acquire the modified peptide, indicating an acid lability of the ADP‐ribosylation. This finding was supported by the presence of a truncated version of the original peptide with Arg102 exchanged by ornithine. Site‐directed mutagenesis verified that the ADP‐ribosylation occurred on Arg102. With our approach, we were able to localize a labile modification within a large peptide of 31 amino acid residues. The present study provides a method suitable for the identification of so far unknown protein modifications on nitrogenases or other proteins. It represents a new tool for the MS analysis of protein mono‐ADP‐ribosylations.

Characterization of the DraT/DraG System for Posttranslational Regulation of Nitrogenase in the Endophytic Betaproteobacterium Azoarcus sp. Strain BH72

DraT/DraG-mediated posttranslational regulation of the nitrogenase Fe protein by ADP-ribosylation has been described for a few diazotrophic bacteria belonging to the class Alphaproteobacteria. Here we present for the first time the DraT/DraG system of a betaproteobacterium, Azoarcus sp. strain BH72, a diazotrophic grass endophyte. Its genome harbors one draT ortholog and two physically unlinked genes coding for ADP-ribosylhydrolases. Northern blot analysis revealed cotranscription of draT with two genes encoding hypothetical proteins. Furthermore, draT and draG2 were expressed under all studied conditions, whereas draG1 expression was nitrogen regulated. By using Western blot analysis of deletion mutants and nitrogenase assays in vivo, we demonstrated that DraT is required for the nitrogenase Fe protein modification but not for the physiological inactivation of nitrogenase activity. A second mechanism responsible for nitrogenase inactivation must operate in this bacterium, which is independent of DraT. Fe protein demodification was dependent mainly on DraG1, corroborating the assumption from phylogenetic analysis that DraG2 might be mostly involved in processes other than the posttranslational regulation of nitrogenase. Nitrogenase in vivo reactivation was impaired in a draG1 mutant and a mutant lacking both draG alleles after anaerobiosis shifts and subsequent adjustment to microaerobic conditions, suggesting that modified dinitrogenase reductase was inactive. Our results demonstrate that the DraT/DraG system, despite some differences, is functionally conserved in diazotrophic proteobacteria.