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Biology subjects

Foell, M. C.

Publications and source records attributed to Foell, M. C..

5 recordsLinked to original sources

In Situ, Antibody-Independent, and Multiplexed Characterization of Amyloid Plaques by MALDI MS/MS Imaging Using iprm-PASEF

BackgroundAmyloidosis collectively describes a heterogeneous group of protein aggregation-based diseases involving the misfolding and extracellular accumulation of fibril-forming amyloid proteins. The tissue deposition of these fibrils occurs either localized (limited to one organ) or systemically, impairing organ function and, in severe cases, leading to organ failure. Identification of the amyloidogenic protein leading to the correct subtyping is challenging but crucial for treatment decisions. Imaging parallel reaction monitoring (iprm)-parallel accumulation-serial fragmentation (PASEF) is a novel method for matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry imaging (MSI) that enables the fast, spatially resolved, multiplexed, and antibody-independent identification of peptides and proteins in situ. In this proof-of-concept study, we demonstrate the applicability of iprm-PASEF for the in situ characterization of amyloidosis. MethodsA multiplexed iprm-PASEF panel (comprising trapped ion mobility spectrometry (TIMS) and m/z values) for characterizing amyloid plaques by MALDI-MSI was compiled. The panel included nine peptide entries of amyloidosis-associated proteins (vitronectin, apolipoprotein E, serum amyloid P component) and the prevalent amyloidosis-subtype proteins serum amyloid A, transthyretin, and immunoglobulin light chain 2. The multiplexed iprm-PASEF panel was applied to a tissue microarray (TMA) assembled from formalin-fixed, paraffin-embedded (FFPE) specimens, comprising biopsies of amyloidosis-positive tissues from 18 patients, including six different tissue types, and representing the following amyloidosis subtypes: ATTR (transthyretin amyloidosis), AL (immunoglobulin light chain amyloidosis), and AA (secondary amyloidosis). For comparison and co-localization, congo red staining was performed on adjacent slides. ResultsMALDI TIMS MS1 imaging was acquired from the amyloidosis TMA, providing an m/z feature list containing 1390 entries that was subsequently refined to only include m/z features likely stemming from amyloidosis-related peptides. Further, we focused on optimal usage of the m/z and ion mobility range to increase the number of targeted peptides. The final iprm-PASEF panel comprised 10 entries ranging from m/z 887.51 - 1,986.85 and 1/K0 1.4 - 2.1 V{middle dot}s/cm2; targeting nine peptides from six different amyloidosis-related proteins. Apolipoprotein E, serum amyloid P component, and immunoglobulin light chain 1/2 were included with two entries. Transthyretin, vitronectin, and serum amyloid A were covered by one peptide. One entry was included as a positive control targeting actin A. We applied the iprm-PASEF (MS2 mode) panel to the amyloidosis TMA and fragment (MS2) spectra were analyzed by the search engine MASCOT. Eight out of ten peptides derived from vitronectin, apolipoprotein E, serum amyloid A, serum amyloid P component, and transthyretin were successfully identified with MASCOT scores above 18. Comparison to Congo red staining indicated a more localized and heterogeneous pattern of amyloid-associated proteins (vitronectin, apolipoprotein E, serum amyloid P component) by iprm-PASEF. Compared to the clinical annotation, transthyretin and serum amyloid A were only found in their respective subtypes. In total, it was possible to describe the spatial distribution of five different amyloid-associated proteins, thereby further characterizing Congo red-positive amyloid plaques in one single iprm-PASEF measurement. Conclusion and perspectiveThis proof-of-concept study demonstrates feasibility for in situ, antibody-independent, and multiplexed proteomic typing of amyloidosis plaques. Future enlargement of the multiplex panel is likely to increase the number of targetable amyloid proteins and to probe for the presence of post-translational modifications. The present study highlights the value of iprm-PASEF for MALDI imaging strategies.

molecular biology↗

Spatial Proteomics by Trapped Ion Mobility supported MALDI MS/MS Imaging: A First Glance into Multiplexed and Spatial Peptide Identification

RATIONALEIn spatial proteomics, matrix-assisted laser desorption/ionization (MALDI) imaging enables rapid and cost-effective peptide measurements. Yet, in situ peptide identification remains challenging. Therefore, this study aims to integrate the trapped ion mobility spectrometry (TIMS)-based parallel accumulation-serial fragmentation (PASEF) into MALDI imaging of tryptic peptides to enable multiplexed MS/MS imaging. METHODSAn initial MALDI TIMS MS1 survey measurement was performed, followed by a manual generation of a precursor list containing mass over charge values and ion mobility windows. Inside the dual TIMS system, submitted precursors were trapped, separately eluted by their ion mobility and analyzed in a quadrupole time-of-flight device, thereby enabling multiplexed MALDI MS/MS imaging. Finally, precursors were identified by peptide to spectrum matching. RESULTSThis study presents the first multiplexed MALDI TIMS MS/MS imaging (iprm-PASEF) of tryptic peptides. Its applicability was showcased on two histomorphologically distinct tissue specimens in a 4-plex and 5-plex setup. Precursors were successfully identified by the search engine MASCOT in one single MALDI imaging experiment for each respective tissue. Peptide identifications were corroborated by liquid-chromatography tandem mass spectrometry experiments and fragment co-localization analyses. CONCLUSIONSIn this study, we present a novel pipeline, based on iprm-PASEF that allows the multiplexed and spatial identification of tryptic peptides in MALDI imaging. Hence, it marks a first step towards the integration of MALDI imaging into the emerging field of spatial proteomics.

biochemistry↗

Cardinal v3 - a versatile open source software for mass spectrometry imaging analysis

Cardinal v3 is an open source software for reproducible analysis of mass spectrometry imaging experiments. A major update from its previous versions, Cardinal v3 supports most mass spectrometry imaging workflows. Its analytical capabilities include advanced data processing such as mass re-calibration, advanced statistical analyses such as single-ion segmentation and rough annotation-based classification, and memory-efficient analyses of large-scale multi-tissue experiments.

bioinformatics↗

Democratizing Data-Independent Acquisition Proteomics Analysis on Public Cloud Infrastructures Via The Galaxy Framework

Data-independent acquisition (DIA) has become an important approach in global, mass spectrometric proteomic studies because it provides in-depth insights into the molecular variety of biological systems. However, DIA data analysis remains challenging due to the high complexity and large data and sample size, which require specialized software and large computing infrastructures. Most available open-source DIA software necessitate basic programming skills and cover only a fraction of the analysis steps, often yielding a complex of multiple software tools, severely limiting usability and reproducibility. To overcome this hurdle, we have integrated a suite of DIA tools in the Galaxy framework for reproducible and version-controlled data processing. The DIA suite includes OpenSwath, PyProphet, diapysef and swath2stats. We have compiled functional Galaxy pipelines for DIA processing, which provide a web-based graphical user interface to these pre-installed and pre-configured tools for their usage on freely accessible, powerful computational resources of the Galaxy framework. This approach also enables seamless sharing workflows with full configuration in addition to sharing raw data and results. We demonstrate usability of the all-in-one DIA pipeline in Galaxy by the analysis of a spike-in case study dataset. Additionally, extensive training material is provided, to further increase access for the proteomics community.

bioinformatics↗

Accessible and reproducible mass spectrometry imaging data analysis in Galaxy

BackgroundMass spectrometry imaging is increasingly used in biological and translational research as it has the ability to determine the spatial distribution of hundreds of analytes in a sample. Being at the interface of proteomics/metabolomics and imaging, the acquired data sets are large and complex and often analyzed with proprietary software or in-house scripts, which hinder reproducibility. Open source software solutions that enable reproducible data analysis often require programming skills and are therefore not accessible to many MSI researchers.\n\nFindingsWe have integrated 18 dedicated mass spectrometry imaging tools into the Galaxy framework to allow accessible, reproducible, and transparent data analysis. Our tools are based on Cardinal, MALDIquant, and scikit-image and enable all major MSI analysis steps such as quality control, visualization, preprocessing, statistical analysis, and image co-registration. Further, we created hands-on training material for use cases in proteomics and metabolomics. To demonstrate the utility of our tools, we re-analyzed a publicly available N-linked glycan imaging dataset. By providing the entire analysis history online, we highlight how the Galaxy framework fosters transparent and reproducible research.\n\nConclusionThe Galaxy framework has emerged as a powerful analysis platform for the analysis of MSI data with ease of use and access together with high levels of reproducibility and transparency.

bioinformatics↗