2018 YPIC Challenge: A case study in characterizing an unknown protein sample
Year: 2019
Type: preprint
Abstract: For the 2018 YPIC Challenge contestants were invited to try to decipher two unknown English questions encoded by a synthetic protein expressed in Escherichia coli. In addition to deciphering the sentence, contestants were asked to determine the 3D structure and determine any post-translation modifications left by the host organism. We present how we analyzed this unknown sample using a tryptic digest with dynamic exclusion disabled to increase the signal-to-noise ratio of the measured molecules. Subsequently, spectral clustering was used to generate high-quality consensus spectra and condense the acquired MS/MS spectral data. De novo spectrum identification was used to determine the English questions encoded by the synthetic protein, and any post-translational modifications introduced by E. coli on the synthetic protein were detected using spectral networking. Although the synthetic protein sample for the 2018 YPIC Challenge is not of biological interest, the experimental and computational strategy presented here can be directly used to analyze samples for which no protein sequence information is available or when the identity of the sample is unknown. All software and code to perform the bioinformatics analysis is available as open source, and a self-contained Jupyter notebook is provided to fully recreate the analysis.
Authors: Lindsay Pino, Andy Lin, Wout Bittremieux
Language: English
Subfield: Spectroscopy
Field: Chemistry
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4246595284