Semiquantitative Analysis for High-Speed Mapping Applications of Biological Samples Using LA-ICP-TOFMS.
Dino MetarapiAndreas SchweikertAna JeršeMartin SchaierJohannes Teun van ElterenGunda KoellenspergerSarah TheinerMartin ŠalaPublished in: Analytical chemistry (2023)
Laser ablation (LA) in combination with inductively coupled plasma time-of-flight mass spectrometry (ICP-TOFMS) enables monitoring of elements from the entire mass range for every pixel, regardless of the isotopes of interest for a certain application. This provides nontargeted multi-element (bio-)imaging capabilities and the unique possibility to screen for elements that were initially not expected in the sample. Quantification of a large range of elements is limited as the preparation of highly multiplexed calibration standards for bioimaging applications by LA-ICP-(TOF)MS is challenging. In this study, we have developed a workflow for semiquantitative analysis by LA-ICP-TOFMS based on multi-element gelatin micro-droplet standards. The presented approach is intended for the mapping of biological samples due to the requirement of matrix-matched standards for accurate quantification in LA-ICPMS, a prerequisite that is given by the use of gelatin-based standards. A library of response factors was constructed based on 72 elements for the semiquantitative calculations. The presented method was evaluated in two stages: (i) on gelatin samples with known elemental concentrations and (ii) on real-world samples that included prime examples of bioimaging (mouse spleen and tumor tissue). The developed semiquantification approach was based on 10 elements as calibration standards and provided the determination of 136 nuclides of 63 elements, with errors below 25%, and for half of the nuclides, below 10%. A web application for quantification and semiquantification of LA-ICP(-TOF)MS data was developed, and a detailed description is presented to easily allow others to use the presented method.
Keyphrases
- high speed
- high resolution
- high throughput
- emergency department
- quantum dots
- wastewater treatment
- molecular dynamics
- atomic force microscopy
- hyaluronic acid
- molecularly imprinted
- artificial intelligence
- electronic health record
- big data
- low cost
- high resolution mass spectrometry
- machine learning
- liquid chromatography
- density functional theory
- drug induced