Simple In-Cell Processing Enables Deep Proteome Analysis of Low-Input <i>Caenorhabditis elegans</i>
<i>Caenorhabditis elegans</i> is a widely used genetic model organism; however, the worm cuticle complicates extraction of intracellular proteins, a prerequisite for typical bottom-up proteomics. Conventional physical disruption procedures are not only time-consuming but can also cause significant sample loss, making it difficult to perform proteomics with low-input samples. Here, for the first time, we present an on-filter in-cell (OFIC) processing approach that can digest <i>C. elegans</i> proteins directly in the cells of the organism after methanol fixation. With OFIC processing and single-shot LC-MS analysis, we identified over 9400 proteins from a sample of only 200 worms, the largest <i>C. elegans</i> proteome reported to date that did not require fractionation or enrichment. We systematically evaluated the performance of the OFIC approach by comparing it to conventional lysis-based methods. Our data suggest superior performance of OFIC processing for <i>C. elegans</i> proteome identification and quantitation. We further evaluated the OFIC approach with even lower-input samples, including single worms. Then, we used this method to determine how the proteome is impacted by loss of superoxide dismutase <i>sod-1</i>, the ortholog of human <i>SOD1</i>, a gene associated with amyotrophic lateral sclerosis. Analysis of 8800 proteins from only 50 worms as the initial input showed that loss of <i>sod-1</i> affects the abundance of proteins required for stress response, ribosome biogenesis, and metabolism. In conclusion, our streamlined OFIC approach, which can be broadly applied to other systems, minimizes sample loss while offering the simplest workflow reported to date for <i>C. elegans</i> proteomics.
Authors
- Jessica E. Tanis (ORCID: https://orcid.org/0000-0002-7993-1013)
- Malek Elsayyid
- Yanbao Yu (ORCID: https://orcid.org/0000-0003-2994-1974)
Institutions
- University of Delaware (US)
Publication Details
- Journal
- Analytical Chemistry
- Published
- 2025-04-21
- DOI
- https://doi.org/10.1021/acs.analchem.4c05003
- Citations
- 11
- Primary Topic
- Genetics, Aging, and Longevity in Model Organisms
- Type
- article
- Field-Weighted Citation Impact
- 10.49
Funders
- National Institute of General Medical Sciences