Researchers at the University of Wisconsin-Madison have developed a method called “deep proteome sequencing” that offers unprecedented characterization of the proteins that show up in standard proteomics experiments. The motivation for the project was the team’s observation that the average shotgun proteomics experiment failed to distinguish different protein variants and isoforms.
The study, published in Nature Biotechnology, used six different human cell types and six proteases. The team then analyzed the peptides by employing different mass spectrometry methods. The researchers identified more than 1 million peptides from 17,717 different protein groups. From these data, they were able to detect approximately 80% of the sequences of all individual proteins within those samples—a vast increase over standard approaches that sequence only ~20% of proteins.
Achieving this more complete picture is the Holy Grail of proteomics. “In the field of mass spectrometry and proteomics, there has always been a goal of detecting all proteins that are present in a sample, then fully sequencing all the individual proteins present,” senior author Joshua Coon says. “But we really haven’t been detecting the whole protein, just small pieces of it.”
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“Data generated from this study represent the deepest proteomics map collected to date,” Coon adds. “These methods and resources lay the foundation for comprehensive mapping of protein diversity and are expected to catalyze future research efforts.”
The research team created an online, publicly available resource called deep-sequencing.app, in which scientists can query any gene and examine the corresponding peptides and protein modifications that are associated with that gene.