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MALDI mass spectrometry imaging workflow for the aquatic model organisms Danio rerio and Daphnia magna

Title data

Schirmer, Elisabeth ; Ritschar, Sven ; Ochs, Matthias ; Laforsch, Christian ; Schuster, Stefan ; Römpp, Andreas:
MALDI mass spectrometry imaging workflow for the aquatic model organisms Danio rerio and Daphnia magna.
In: Scientific Reports. Vol. 12 (4 May 2022) Issue 1 . - No. 7288.
ISSN 2045-2322
DOI: https://doi.org/10.1038/s41598-022-09659-y

Official URL: Volltext

Project information

Project title:
Project's official titleProject's id
SFB 1357 Mikroplastik391977956
INST 91/373-1-FUGGNo information
Open Access PublizierenNo information

Project financing: Deutsche Forschungsgemeinschaft
Open Access funding enabled and organized by Projekt DEAL.

Abstract in another language

Lipids play various essential roles in the physiology of animals. They are also highly dependent on cellular metabolism or status. It is therefore crucial to understand to which extent animals can stabilize their lipid composition in the presence of external stressors, such as chemicals that are released into the environment. We developed a MALDI MS imaging workflow for two important aquatic model organisms, the zebrafish (Danio rerio) and water flea (Daphnia magna). Owing to the heterogeneous structure of these organisms, developing a suitable sample preparation workflow is a highly non-trivial but crucial part of this work and needs to be established first. Relevant parameters and practical considerations in order to preserve tissue structure and composition in tissue sections are discussed for each application. All measurements were based on high mass accuracy enabling reliable identification of imaged compounds. In zebrafish we demonstrate that a detailed mapping between histology and simultaneously determined lipid composition is possible at various scales, from extended structures such as the brain or gills down to subcellular structures such as a single axon in the central nervous system. For D. magna we present for the first time a MALDI MSI workflow, that demonstrably maintains tissue integrity during cryosectioning of non-preserved samples, and allows the mapping of lipids in the entire body and the brood chamber inside the carapace. In conclusion, the lipid signatures that we were able to detect with our method provide an ideal basis to analyze changes caused by pollutants in two key aquatic model organisms.

Further data

Item Type: Article in a journal
Refereed: Yes
Institutions of the University: Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Biology > Chair Animal Ecology I > Chair Animal Ecology I - Univ.-Prof. Dr. Christian Laforsch
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Biology > Chair Animal Physiology > Chair Animal Physiology - Univ.-Prof. Dr. Stefan Schuster
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Biology > Chair Bioanalytical Sciences and Food Analytics > Chair Bioanalytical Sciences and Food Analytics - Univ.-Prof. Dr. Andreas Römpp
Research Institutions > Research Centres > Bayreuth Center of Ecology and Environmental Research- BayCEER
Research Institutions > Collaborative Research Centers, Research Unit > SFB 1357 - MIKROPLASTIK
Faculties
Faculties > Faculty of Biology, Chemistry and Earth Sciences
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Biology
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Biology > Chair Animal Ecology I
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Biology > Chair Animal Physiology
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Biology > Chair Bioanalytical Sciences and Food Analytics
Research Institutions
Research Institutions > Research Centres
Research Institutions > Collaborative Research Centers, Research Unit
Result of work at the UBT: Yes
DDC Subjects: 500 Science > 570 Life sciences, biology
500 Science > 590 Animals (Zoology)
Date Deposited: 27 May 2022 08:26
Last Modified: 24 Nov 2022 12:48
URI: https://eref.uni-bayreuth.de/id/eprint/69774