Abstract
Analysis by liquid chromatography and tandem mass spectrometry (LC‐MS/MS) can identify and quantify thousands of proteins in microgram‐level samples, such as those comprised of thousands of cells. Identifying proteins by LC‐MS/MS proteomics, however, remains challenging for lowly abundant samples, such as the proteomes of single mammalian cells. To increase the identification rate of peptides in such small samples, we developed DART‐ID. This method implements a data‐driven, global retention time (RT) alignment process to infer peptide RTs across experiments. DART‐ID then incorporates the global RT‐estimates within a principled Bayesian framework to increase the confidence in correct peptide‐spectrum‐matches. Applying DART‐ID to hundreds of samples prepared by the Single Cell Proteomics by Mass Spectrometry (SCoPE‐MS) design increased the peptide and proteome coverage by 30 – 50% at 1% FDR. The newly identified peptides and proteins were further validated by demonstrating that their quantification is consistent with the quantification of peptides identified from high‐quality spectra. DART‐ID can be applied to various sets of experimental designs with similar sample complexities and chromatography conditions, and is freely available online.Support or Funding InformationThis abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
Highlights
Advancements in the sensitivity and discriminatory power of protein mass-spectrometry (MS) have enabled the quantitative analysis of increasingly limited amounts of samples
Using retention time (RT) for identifying peptide sequences starts with estimating the RT for each peptide, and we aimed to maximize the accuracy of RT estimation by optimizing RT alignment
Many existing methods can only align the RTs of two experiments at a time, i.e., pairwise alignment, based on partial least squares minimization, which does not account for the measurement errors in RTs [53]
Summary
Advancements in the sensitivity and discriminatory power of protein mass-spectrometry (MS) have enabled the quantitative analysis of increasingly limited amounts of samples. SCoPE-MS uses a barcoded carrier to boost the MS signal from single-cells and enhance sequence identification [1, 2] While this design allows quantifying hundreds of proteins in single mammalian cells, sequence identification remains challenging because many lowly abundant peptides generate only a few fragment ions that are insufficient for confident identification [3, 4]. We sought to overcome this challenge by using both the retention time (RT) of an ion and its MS/MS spectra to achieve more confident peptide identifications To this end, we developed a novel data-driven Bayesian framework for aligning RTs and for updating peptide confidence. DART-ID minimizes assumptions, aligns RTs with median residual error below 3 seconds, and increases the fraction of cells in which peptides are confidently identified
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