Introduction: Mass spectrometry imaging (MSI) as a label-free and powerful imaging technique enables in situ evaluation of a tissue metabolome and/or proteome, becoming increasingly popular in the detection of plant endogenous molecules.
Objective: The characterisation of structure and spatial information of endogenous molecules in plants are both very important aspects to better understand the physiological mechanism of plant organism.
Methods: Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a commonly-used tissue imaging technique, which requires matrix to assist in situ detection of a variety of molecules on the surface of a tissue section. In previous studies, MALDI-MSI was mostly used for the detection of molecules from animal tissue sections, compared to plant samples due to cell structural limitations, such as plant cuticles, epicuticular waxes, and cell walls. Despite the enormous progress that has been made in tissue imaging, there is still a challenge for MALDI-MSI suitable for the imaging of endogenous compounds in plants.
Results: This review summarises the recent advances in MALDI-MSI, focusing on the application of in situ detection of endogenous molecules in different plant organs, i.e. root, stem, leaf, flower, fruit, and seed.
Conclusion: Further improvements on instrumentation sensitivity, matrix selection, image processing and sample preparation will expand the application of MALDI-MSI in plant research.
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http://dx.doi.org/10.1002/pca.2759 | DOI Listing |
Cell Biochem Biophys
January 2025
Department of Zoology, MMV, Banaras Hindu University, Varanasi, 221005, UP, India.
Putranjiva roxburghii is an important medicinal plant utilized for remedy of female reproductive ailments. Its seed extract is being used as a uterine health booster due to the presence of several pharmaceutically important phytochemicals. However, the presence of phytochemicals in its leaf is still unexplored.
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January 2025
Jiangsu Collaborative Innovation Center of Biomedical Functional Materials, Jiangsu Key Laboratory of Biomedical Materials, School of Chemistry and Materials Science, Nanjing Normal University, Nanjing, 210023, China.
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View Article and Find Full Text PDFSci Rep
January 2025
Department of Dermatology, Dermatology Hospital of Zhejiang Province, Huzhou, 313299, China.
Although an ongoing understanding of psoriasis vulgaris (PV) pathogenesis, little is known about the proteomic differences between moderate and severe psoriasis. In this cross-sectional study, we evaluated the proteomic differences between moderate and severe psoriasis using data-independent acquisition mass spectrometry (DIA-MS). 173 differentially expressed proteins (DEPs) were significantly differentially expressed between the two groups.
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January 2025
Mechanisms, Biomarkers and Models Section - Genome Stability Group, Department of Environment and Health, Istituto Superiore di Sanità, Viale Regina Elena, 299 - 00161, Rome, Italy.
The WRN protein is vital for managing perturbed replication forks. Replication Protein A strongly enhances WRN helicase activity in specific in vitro assays. However, the in vivo significance of RPA binding to WRN has largely remained unexplored.
View Article and Find Full Text PDFNat Commun
January 2025
Institute for Experimental Immunology and Imaging, University Hospital Essen, Essen, Germany.
Multimodal imaging by matrix-assisted laser desorption ionisation mass spectrometry imaging (MALDI MSI) and microscopy holds potential for understanding pathological mechanisms by mapping molecular signatures from the tissue microenvironment to specific cell populations. However, existing software solutions for MALDI MSI data analysis are incomplete, require programming skills and contain laborious manual steps, hindering broadly applicable, reproducible, and high-throughput analysis to generate impactful biological discoveries. Here, we present msiFlow, an accessible open-source, platform-independent and vendor-neutral software for end-to-end, high-throughput, transparent and reproducible analysis of multimodal imaging data.
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