Sweet google O’ mine—The importance of online search engines for MS-facilitated, database-independent identification of peptide-encoded book prefaces

Abstract

In the recent year, we felt like we were not truly showing our full potential in our PhD projects, and so we were very happy and excited when YPIC announced the ultimate proteomics challenge. This gave us the opportunity of showing off and procrastinating at the same time:) The challenge was to identify the amino acid sequence of 19 synthetic peptides made up from an English text and then find the book that it came from. For this task we chose to run on an Orbitrap Fusion™ Lumos™ Tribrid™ Mass Spectrometer with two different sensitive MS2 resolutions, each with both HCD and CID fragmentation consecutively. This strategy was chosen because we speculated that multiple MS2 scans at high quality would be beneficial over lower resolution, speed and quantity in the relatively sparse sample. The resulting chromatogram did not reveal 19 sharp distinct peaks and it was not clear to us where to start a manual spectra interpretation. We instead used the de novo option in the MaxQuant software and the resulting output gave us two phrases with words that were specific enough to be searched in the magic Google search engine. Google gave us the name of a very famous physicist, namely Sir Joseph John Thomson, and a reference to his book “Rays of positive electricity” from 1913. We then converted the paragraph we believed to be the right one into a FASTA format and used it with MaxQuant to do a database search. This resulted in 16 perfectly FASTA search-identified peptide sequences, one with a missing PTM and one found as a truncated version. The remaining one was identified within the MaxQuant de novo sequencing results. We thus show in this study that our workflow combining de novo spectra analysis algorithms with an online search engine is ideally suited for all applications where users want to decipher peptide-encoded prefaces of 20th century science books.