Methods in Brief Three-dimensional feature matching improves coverage for single-cell proteomics based on ion mobility ﬁltering

Single-cell proteomics (scProteomics) promises to advance our understanding of cell functions within complex biological systems. However, a major challenge of current methods is their inability to identify and provide accurate quantitative information for low-abundance proteins. Herein, we describe an ion-mobility-enhanced mass spectrometry acquisition and peptide identiﬁcation method, transferring identiﬁcation based on FAIMS ﬁltering (TIFF), to improve the sensitivity and accuracy of label-free scProteomics. TIFF ex-tends the ion accumulation times for peptide ions by ﬁltering out singly charged ions. The peptide identities are assigned by a three-dimensional MS1 feature matching approach (retention time, accurate mass, and FAIMS compensation voltage). The TIFF method enabled unbiased proteome analysis to a depth of >1,700 proteins in single HeLa cells, with >1,100 proteins consistently identiﬁed. As a demonstration, we applied the TIFF method to obtain temporal proteome proﬁles of >150 single murine macrophage cells during lipopolysaccharide stimulation and identiﬁed time-dependent proteome changes. A digested peptides were acidiﬁed by 0.5% triﬂuoroacetic acid (TFA) at ﬁnal concentration, then desalted using C18 SPE tips. After concentrated, the BCA assay was performed to estimate the ﬁnal concentration of the peptides. Using the nanoPOTS robot, 0.2 ng and 10 ng of the peptides from each leukemia cell line were loaded on the nanowell/microwell chips and completely dried by a vacuum system (Williams et al., 2020). For single-cell analysis, single and 50 FACS-sorted cells on the chip were processed on the nanoPOTS platform for single cells and spectral library, respectively. To extract proteins, we ﬁrst added a lysis buffer containing 0.2% n-Dodecyl b-D-maltoside (DDM) and 5 mM DTT in 0.5 3 PBS and 25 mM NH 4 HCO 3 buffer in each well, then incubated for 1 hr at 70 (cid:4) C. Denatured and reduced proteins were alkylated with 10 mM IAA in the dark for 30 min at RT. Double enzymatic digestions were performed by incubating with LysC of 254 ms and an AGC target of 1E6. To analyze pooled samples for generating the spectral libraries, the selected precursor ions with +2 to +7 charges were fragmented by a 30% level of high energy dissociation (HCD) and scanned at 60,000 resolution with an IT of 118 ms and an AGC target of 1E5. When single-cell level (0.2 ng) peptides were injected, fragmented peptide ions were scanned at 120,000 resolution with an IT of 246 ms and an AGC target of 1E5. For the TIFF method, the ionized peptides were fractionated by the FAIMSpro interface using a 2-CV (-45, -65 V) method or a 4-CV (-45, -55, -65, -75 V) method. Fractionated ions with a mass range 350-1500 m/z were scanned at 120,000 resolution with an IT of 254 ms and an AGC target of 1E6. For the pooled samples for generating a spectral library, a single CV was used for each LC-MS run. Precursor ions with intensities > 1E4 were selected for fragmentation by 30% HCD and scanned in an ion trap with an AGC of 2E4 and an IT of 150 ms. For single-cell samples, cycle times of 1.5 s and 0.6 s were used for the 2-CV and 4-CV methods, respectively. Precursor ions with intensities > 1E4 were fragmented by 30% HCD and scanned with an AGC of 2E4 and an IT of 254 ms. batch correction was applied to remove the batch effects between chips using ComBat algorithm from the SVA package (v3.36.0). The missing values were imputed using the function of imputeMissing() and UMAP (the uniform manifold approximation and projection)-based dimensional reduction analysis was performed using the romicsUmapPlot() function in the RomicsProcessor package. For the statistics, ANOVA test was applied with a Benjamini-Hochberg FDR < 0.001 and a S 0 =5; we applied a highly signiﬁcant level to a large number of macrophage cells data in which the group was clearly distinguished by the duration of LPS treatment to give a statistical role to the difference between the median value.