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Spatially Resolved Protein Biomarkers of Thymus Compartmentalization Identified via Integrated MALDI Imaging and Proteomics

ABSTRACT: The identification of spatially resolved proteomes has seen recent breakthroughs, yet challenges remain, particularly in combining protein identification with localization in a single experimental run. Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) ad-dresses these limitations, allowing spatial mapping of proteins directly on tissue sections without the need for antibodies. This study introduces a novel approach to map protein changes in thym-ic tissue, particularly following chemotherapy treatment, by combining mass spectrometry imag-ing (MALDI-MSI) with liquid chromatography-mass spectrometry (LC-MS/MS). We developed a scoring system to match molecular signals from MALDI-MSI with proteomic data, allowing for precise identification of proteins involved in thymic function. Our results reveal key changes in protein expression, particularly in areas related to cell migration, cytoskeletal remodeling, and thymic regeneration. By analyzing the distribution of proteins like Keratin 8 (KRT8), Nucleoporin TPR, Cysteine- and Glycine-Rich Protein 3 (CSPR3), and Tubulin-Associated Chaperone-A (TBCA), we were able to observe shifts in thymic compartment architecture, highlighting the im-pact of chemotherapy on thymic tissue. This approach offers a new way to visualize and under-stand thymic remodeling and regeneration, with potential applications for monitoring chemother-apy effects and identifying biomarkers for monitoring thymic recovery.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Thymus

SUBMITTER: Simone Sidoli

LAB HEAD: Simone Sidoli

PROVIDER: PXD058296 | Pride | 2025-10-30

REPOSITORIES: Pride

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			Action	DRS
	20230203_Jenny_George_196a_Left_1.raw	Raw
	20230203_Jenny_George_196a_Right_2.raw	Raw
	20230203_Jenny_George_198_1_Left_bottom_4.raw	Raw
	20230203_Jenny_George_198_1_Left_top_3.raw	Raw
	20230203_Jenny_George_198_1_Right_L_5.raw	Raw

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Project description:Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has recently gained prominence for its ability to provide molecular and spatial information in tissue sections. This technology has the potential to uncover novel insights into proteins and other molecules in biological and immunological pathways activated along diseases with a complex host-pathogen interaction, such as animal tuberculosis. Thus, the present study conducted a data analysis of protein signature in granulomas of cattle and pigs naturally infected with Mycobacterium tuberculosis complex (MTC), identifying biological and immunological signalling pathways activated throughout the disease. Lymph nodes from four pigs and cattle, positive for MTC by bacteriological culture and/or real-time PCR, were processed for histopathological examination and MALDI-MSI. Protein identities were assigned using the MaTisse database, and protein-protein interaction networks were visualized using the STRING database. Gene ontology (GO) analysis was carried out to determine biological and immunological signalling pathways in which these proteins could participate together with KEGG analysis. Distinct proteomic profiles between cattle and pig granulomas were displayed. Noteworthy, the GO analysis revealed also common pathways among both species, such as â€œComplement activation, alternative pathwayâ€� and â€œTricarboxylic acid cycleâ€�, which highlights pathways that are conserved among different species infected by MTC. In addition, species-specific terms were identified in the current study, such as â€œNatural killer cell degranulationâ€� in cattle or those related to platelet and neutrophils recruitment and activation in pigs. Overall, this study provides insights into the immunopathogenesis of tuberculosis in cattle and pigs, opening new areas of research and highlighting the importance, among others, of the complement activation pathway and the regulation of natural killer cell and neutrophil-mediated immunity in this disease.

Project description:Gliomas represent 80% of all malignant cerebral tumors and are classified within different malignity grade. Glioblastoma, the most aggressive group, represent more than half of all gliomas but remain a heterogeneous group. Indeed, patient survival can reach from several months to a few years after surgery and chemotherapy. To study gliomas, MALDI mass spectrometry imaging is an interesting technique, allowing the analysis of tumor heterogeneity. In this study, MALDI-MSI is coupled with spatially-resolved microproteomic within the objective to identify subgroups of glioblastomas patients in order to help diagnosis and prognostic. Molecular images are generated from thin tissue section in order to determine the spatial localization of digested peptides. Thanks to unsupervised statistical analysis, we then generated hierarchical clustering of homogeneous molecular regions. According to these regions, spatially resolved proteomic gave access to large scale protein identification and relative quantification. Hierarchical clustering reveal three molecular region within all the tumors sample : region red which represent 33% of surface of all sample, region yellow (25.7%) and region blue (40.8%). Consequently, 3 groups of patient can be determined: group A composed mostly of region red (13/50 patients), group B composed mostly of region yellow (9/50 patients) and group C composed mostly of region blue (24/50 patients). Spatially resolved proteomic was performed and the 147 extractions were analyzed by nano-LC MS/MS. Two-way ANOVA test reveal panel of proteins specifically overexpressed in each region. Protein overexpressed in region red are associated with neurogenesis; protein overexpressed in region yellow are associated with an activation of the immune system and protein overexpressed in region blue are involved with viral processes. To conclude, the combination of MALDI-MSI and microproteomic provides new information on these tumors, allowing us to differentiate three group of patient. In the future, these data will permit to build a more precise classification, a better medical care for patients and the identification of potential new therapeutic targets.

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Spatially Resolved Protein Biomarkers of Thymus Compartmentalization Identified via Integrated MALDI Imaging and Proteomics

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