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Plant Proteomic Data Acquisition and Data Analyses: Lessons from Spaceflight
Proma Basu1,2,3, Colin P S Kruse1,2,4, Darron R Luesse5
1Department of Environmental and Plant Biology, Ohio University, Athens, OH, USA.
Methods in Molecular Biology (Clifton, N.J.)
|October 14, 2021
Summary
This study details proteomics methods for protein extraction from Arabidopsis thaliana seedlings, applicable to spaceflight and ground experiments. It offers analysis techniques to reveal complex regulatory patterns beyond transcriptomics.
Area of Science:
- Plant molecular biology
- Biochemistry
- Proteomics
Background:
- Proteomics enables identification and quantification of proteins in biological samples.
- It is widely used in model organisms to study physiological processes and signaling pathways.
- Proteomics offers a global view of cellular regulatory processes and can identify candidate genes and protein isoforms.
Purpose of the Study:
- To provide protocols for protein extraction from Arabidopsis thaliana seedlings.
- To describe data analysis techniques for proteomics experiments.
- To validate these methods for both ground-based and spaceflight experiments.
Main Methods:
- Protein extraction protocols for soluble and membrane proteins from Arabidopsis thaliana seedlings.
- Mass spectrometry/mass spectrometry (MS/MS) data acquisition and analysis.
- Software utilization for gathering structural data on proteins.
- Differential abundance and network-based analyses of proteomics data.
Main Results:
- Established protocols for protein extraction from plant seedlings.
- Detailed basic analysis and quality metrics for MS/MS data.
- Outlined avenues for post-MS/MS data analysis.
- Demonstrated the utility of network-based approaches for uncovering regulatory patterns.
Conclusions:
- The described proteomics protocols are robust for Arabidopsis thaliana seedlings.
- These methods are adaptable for various experimental settings, including spaceflight.
- Proteomics, especially with network-based analysis, provides insights into regulatory mechanisms beyond other omics data.

