Protein Contaminants Matter: Building Universal Protein Contaminant Libraries for DDA and DIA Proteomics

Mass
spectrometry-based proteomics is constantly challenged by
the presence of contaminant background signals. In particular, protein
contaminants from reagents and sample handling are almost impossible
to avoid. For data-dependent acquisition (DDA) proteomics, an exclusion
list can be used to reduce the influence of protein contaminants.
However, protein contamination has not been evaluated and is rarely
addressed in data-independent acquisition (DIA). How protein contaminants
influence proteomic data is also unclear. In this study, we established
new protein contaminant FASTA and spectral libraries that are applicable
to all proteomic workflows and evaluated the impact of protein contaminants
on both DDA and DIA proteomics. We demonstrated that including our
contaminant libraries can reduce false discoveries and increase protein
identifications, without influencing the quantification accuracy in
various proteomic software platforms. With the pressing need to standardize
proteomic workflow in the research community, we highly recommend
including our contaminant FASTA and spectral libraries in all bottom-up
proteomic data analysis. Our contaminant libraries and a step-by-step
tutorial to incorporate these libraries in various DDA and DIA data
analysis platforms can be valuable resources for proteomic researchers,
freely accessible at https://github.com/HaoGroup-ProtContLib.