1. Multi-Enzymatic Limited Digestion: The Next-Generation Sequencing for Proteomics?
- Author
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Raphaël La Rocca, Nicolas Smargiasso, Elodie Grifnée, Dominique Baiwir, Rémi Longuespée, Denis Morsa, Edwin De Pauw, Tyler A. Zimmerman, Marie-Alice Meuwis, Emeline Hanozin, and Gabriel Mazzucchelli
- Subjects
Proteomics ,0301 basic medicine ,Flexibility (engineering) ,030102 biochemistry & molecular biology ,Computer science ,High-Throughput Nucleotide Sequencing ,General Chemistry ,Computational biology ,Biochemistry ,DNA sequencing ,03 medical and health sciences ,030104 developmental biology ,Sequence Analysis, Protein ,Tandem Mass Spectrometry ,Redundancy (engineering) ,Humans ,De novo sequencing ,Amino Acid Sequence ,Peptides ,Protein Processing, Post-Translational ,Algorithms - 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.
- Published
- 2019
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