Real-Time Search-Assisted Acquisition on a Tribrid Mass Spectrometer Improves Coverage in Multiplexed Single-Cell Proteomics

Abstract

In the young field of single-cell proteomics (scMS), there is a great need for improved global proteome characterization, both in terms of proteins quantified per cell and quantitative performance thereof. The recently introduced real-time search (RTS) on the Orbitrap Eclipse Tribrid mass spectrometer in combination with SPS-MS3 acquisition has been shown to be beneficial for the measurement of samples that are multiplexed using isobaric tags. Multiplexed scMS requires high ion injection times and high-resolution spectra to quantify the single-cell signal; however, the carrier channel facilitates peptide identification and thus offers the opportunity for fast on-the-fly precursor filtering before committing to the time-intensive quantification scan. Here, we compared classical MS2 acquisition against RTS-SPS-MS3, both using the Orbitrap Eclipse Tribrid MS with the FAIMS Pro ion mobility interface and present a new acquisition strategy termed RETICLE (RTS enhanced quant of single cell spectra) that makes use of fast real-time searched linear ion trap scans to preselect MS1 peptide precursors for quantitative MS2 Orbitrap acquisition. We show that classical MS2 acquisition is outperformed by both RTS-SPS-MS3 through increased quantitative accuracy at similar proteome coverage, and RETICLE through higher proteome coverage, with the latter enabling the quantification of over 1000 proteins per cell at an MS2 injection time of 750 ms using a 2 h gradient.

Keywords: SPS-MS3; TMT; isobaric tag quantification; multiplexing; real-time search; single-cell proteomics.

Graphical abstract

Fig. 1

Method trees of the three acquisition methods. Methods were created using the Xcalibur Instrument Setup of the Orbitrap Eclipse Tribrid Mass Spectrometer. One acquisition cycle is shown (FAIMS CV -50). The second acquisition cycle with FAIMS CV -70 has identical settings, except lower cycle time. RTS-MS3 and RETICLE both make use of fast LIT MS2 scans (46 ms, and 23 ms max. IT, respectively) that are subjected to RTS which subsequently triggers MS3 or MS2 acquisition.

Fig. 2

Comparison of scMS performance between the acquisition methods. A, design of the multiplexed diluted standard. B, number of acquired quantification spectra differs between the methods, as does the identification rate thereof, influencing the average number of proteins quantified in the “single-cell” channels. C, Close-out option implemented in RTS influences the distribution of peptides across proteins.

Fig. 3

Comparison of acquisition methods using a diluted standard.A, protein expression matrix of each method measured in triplicates. Proteins in the rows were sorted by the mean log2 S/N across all methods and each individual row shows the same protein with its mean log2 S/N across all “single-cells” in each LC-MS run. Heatmap was downsampled by removing every second row to visualize individual missing values. Full heatmap shown in supplemental Fig. S3. B, differential protein expression analysis between BLAST and LSC of each method using the bulk-measured reference dataset for validation. TP=true positive, FP=false positive, TN=true negative, FN=false negative (see Experimental Procedures). C, cumulative distribution of true positive DE proteins ordered by mean log2 S/N across all methods. Proteins on the x-axis are the same for each method and represent the union of all testable proteins across all methods that are DE in the bulk-measured reference. D, ratio compression measured by dividing log2FC in scMS by log2FC in the bulk-measured reference. Common true positive proteins that were upregulated in BLASTS were used. Outlier not shown. E, absolute log2FC difference between scMS and the bulk-measured reference. The intersection of testable proteins across all methods was used and binned by mean log2 S/N across all methods. Outlier not shown.

Fig. 4

Comparison of acquisition methods using scMS samples.A, FACS strategy to sample single cells from three different populations of the OCI-AML8227 cell-culture system. B, number of proteins quantified in each cell per method. C, top: Distribution of S/N across proteins quantified in each method. For each method, proteins were ranked by their mean log2 S/N across all cells (different proteins for each method). Bottom: Cumulative distribution of DE proteins using the same protein ranking as top. DE analysis was performed on CD34+CD38+ population versus the rest of the cells. D, PCA analysis of the scMS dataset of each method with proteins from different rank bins. Proteins were ranked as in C and binned into quintiles. Missing values were imputed and protein expression was scaled. Separation of the different populations was measured by the silhouette coefficients of all cells in PCA space (first 10 PCs). Points show means and bars show standard deviation. PC1 & PC2 are shown on cell-scatterplots on the right. E, Venn diagram of proteins quantified in the three best methods. F, pairwise correlations of expression profiles of ribosomal proteins (40S & 60S) across single cells in each method. Pearson correlation was calculated from imputed and scaled protein expression.