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ChipFilter: Microfluidic-Based Comprehensive Sample Preparation Methodology for Microbial Consortia
Ranjith Kumar Ravi Kumar1, Massamba Mbacke Ndiaye1, Iman Haddad1
1Spectrométrie de Masse Biologique et Protéomique, LPC, UMR ESPCI CNRS 8249, 10 rue Vauquelin, F-75005 Paris, France.
A novel microfluidic ChipFilter device enables direct cell lysis and protein digestion for metaproteomics. This method enhances microbial protein identification, even from low-density samples, improving microbiome functional analysis.
Area of Science:
- Microbiology
- Proteomics
- Analytical Chemistry
Background:
- Metaproteomics offers functional insights into microbiomes but faces challenges in protein extraction from complex samples.
- Current methods struggle with low cell densities and heterogeneous microbial communities.
Purpose of the Study:
- To evaluate a ChipFilter microfluidic device for direct microbial cell lysis and protein digestion in metaproteomic workflows.
- To assess the efficiency of the ChipFilter coupled with LC-MS/MS for identifying microbial proteins.
Main Methods:
- Utilized a ChipFilter microfluidic device for direct cell lysis and in-situ protein digestion.
- Employed liquid chromatography tandem mass spectrometry (LC-MS/MS) for peptide identification and quantification.
- Tested the system with pure cultures (E. coli, B. subtilis, S. cerevisiae) and a complex 17-species gut microbiome mixture.
Main Results:
- The ChipFilter system successfully identified microbial proteins directly from lysed cells.
- Higher numbers of proteins and peptides were identified compared to standard protocols, particularly at low cell densities.
- The ChipFilter preparation identified and quantified 16 out of 17 species in a complex gut microbiome sample.
Conclusions:
- The ChipFilter microfluidic device is an effective tool for metaproteomic analysis of microbiomes.
- This approach overcomes technical challenges in protein extraction, especially for low-volume or low-cell-density samples.
- The method facilitates improved functional characterization of microbial communities.
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