Multi-Enzymatic Limited Digestion: The Next-Generation Sequencing for Proteomics?
peer-reviewed · Journal of Proteome Research · 2019
| Date | 2019-06-07 |
| Type | peer-reviewed |
| Venue | Journal of Proteome Research |
| Publisher | American Chemical Society (ACS) |
| Contribution | adjacent |
| DOI | 10.1021/acs.jproteome.9b00044 |
| Citations (OpenAlex) | 47 |
| Venue 2-year citedness | 3.83 |
Abstract
Over the past 40 years, proteomics, generically defined as the field dedicated to the identification and analysis of proteins, has tremendously gained in popularity and potency through advancements in genome sequencing, separative techniques, mass spectrometry, and bioinformatics algorithms. As a consequence, its scope of application has gradually enlarged and diversified to meet specialized topical biomedical subjects. Although the tryptic bottom-up approach is widely regarded as the gold standard for rapid screening of complex samples, its application for precise and confident mapping of protein modifications is often hindered due to partial sequence coverage, poor redundancy in indicative peptides, and lack of method flexibility. We here show how the synergic and time-limited action of a properly diluted mix of multiple enzymes can be exploited in a versatile yet straightforward protocol to alleviate present-day drawbacks. Merging bottom-up and middle-down ideologies, our results highlight broad assemblies of overlapping peptides that enable refined and reliable characterizations of proteins, including variant identification, and their carried modifications, including post-translational modifications, truncations, and cleavages. Beyond this boost in performance, our methodology also offers efficient de novo sequencing capabilities, in view of which we here present a dedicated custom assembly algorithm.
Methods and tools
- MELD: Multi-Enzymatic Limited Digestion uses a diluted, time-limited mix of proteases to produce overlapping peptides, with a custom assembly algorithm that turns them into de novo protein sequences.