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Updated: Jun 4, 2025
JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Bottom-Up Proteomics Workflow for Studying Multi-organism Systems
Hongxia Bai1, Leonard B Collins2, Marcos Rogério André3,4
1Department of Chemistry, North Carolina State University, Raleigh, NC, USA.
This study introduces a novel proteomics workflow to analyze protein changes in fleas infected with Bartonella henselae. The method helps understand host-pathogen interactions in multi-organism research.
Area of Science:
- Proteomics
- Microbiology
- Vector-borne diseases
Background:
- Discovery proteomics is crucial for understanding complex biological interactions.
- Studying host-pathogen relationships requires advanced analytical techniques.
Purpose of the Study:
- To develop and detail a bottom-up proteomics workflow for analyzing differential protein expression.
- To investigate protein expression changes in cat fleas (Ctenocephalides felis felis) experimentally infected with Bartonella henselae.
Main Methods:
- Bottom-up proteomics workflow.
- Nano liquid chromatography-tandem mass spectrometry (nanoLC-MS/MS).
- Label-free quantification and Proteome Discoverer software for data analysis.
Main Results:
- Successfully identified and quantified differential protein expression in infected fleas.
- Established a reproducible methodology for multi-organism proteomic studies.
Conclusions:
- The developed proteomics workflow is effective for examining host-pathogen interactions.
- This protocol provides a foundation for diverse multi-organism proteomic investigations.
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