Spray-Based Application of Matrix to Agar-Based Microbial Samples for Reproducible Sample Adherence in MALDI MSI
Justin N Jens1, Daniel J Breiner1, Vanessa V Phelan1
1Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, Aurora, Colorado 80045, United States.
Matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging (MSI) for microbes is improved with a new robotic sprayer method. This technique enhances sample adherence, allowing broader media use and larger area analysis for microbial metabolite studies.
Area of Science:
- Microbiology
- Analytical Chemistry
- Metabolomics
Background:
- Microbial mass spectrometry imaging (MSI) aids in understanding metabolite roles in microbial competition via spatial distribution.
- Matrix-assisted laser desorption ionization (MALDI) is the primary ionization method for microbial MSI.
- Current limitations include poor agar sample adherence to MALDI targets due to medium components and microbial metabolites, restricting media choices.
Purpose of the Study:
- To develop an improved method for microbial MSI analysis.
- To overcome limitations in sample adherence for MALDI MSI.
- To enable microbial growth on diverse media for MSI analysis.
Main Methods:
- A three-step process involving a robotic sprayer for matrix application was developed.
- This method enhances the adherence of agar-based microbial samples to MALDI targets.
- The technique facilitates MSI analysis over larger sample surface areas.
Main Results:
- The robotic spraying method significantly improves agar sample adherence to MALDI targets.
- This advancement allows for the use of a wider range of microbial growth media.
- The improved adherence enables MSI analysis of larger microbial sample areas.
Conclusions:
- The new robotic spraying technique expands the applicability of MALDI MSI for microbial studies.
- Researchers can now utilize diverse media for microbial growth and subsequent MSI analysis.
- This method enhances the potential for generating biological hypotheses regarding microbial competition and metabolite functions.
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