Driving Single Cell Proteomics Forward with Innovation

Abstract

Current single-cell mass spectrometry (MS) methods can quantify thousands of peptides per single cell while detecting peptide-like features that may support the quantification of 10-fold more peptides. This 10-fold gain might be attained by innovations in data acquisition and interpretation even while using existing instrumentation. This perspective discusses possible directions for such innovations with the aim to stimulate community efforts for increasing the coverage and quantitative accuracy of single proteomics while simultaneously decreasing missing data. Parallel improvements in instrumentation, sample preparation, and peptide separation will afford additional gains. Together, these synergistic routes for innovation project a rapid growth in the capabilities of MS based single-cell protein analysis. These gains will directly empower applications of single-cell proteomics to biomedical research.

Keywords: data acquisition; data interpretation; peptide identity propagation; single-cell proteomics; ultrasensitive proteomics.

Figure 1.

Number of precursor ions analyzed by shotgun methods decline steeply with increasing ion accumulation times. The graphs show theoretical simulations of the maximum number of MS2 scans that could be performed as a function of MS2 ion accumulation times. The simulations are for a 60 min active gradient, assuming 256 ms MS1 survey scans, full duty cycles, and two TopN methods, either 5 or 20 MS2 scans per duty cycle.

Figure 2.

Approaches for peptide sequence identification offer a tradeoff between sensitivity and specificity. Approaches using extracted ion current, such as IceR, are likely to offer higher sensitivity of peptide sequence propagation. In contrast, approaches using more features, such as DART-ID, are likely to offer higher reliability of peptide sequence identification.