An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics

Abstract

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100×) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ∼2500 proteins and precise quantification of ∼1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

Low cell number proteomic analysis using in-cell protease digests reveals a robust signature for cell cycle state classification

“…6E). The abundance pattern of RRM2 is consistent with previous proteomic studies and targeted degradation of RRM2 in late G2/early mitosis by the cyclin F-SCF complex [5] [26]. Example proteins from this cluster include TPX2 and Aurora A kinase (Fig.…”

“…The advanced PRIMMUS method presented here significantly reduces the number of cells required, i.e. ~10 3 versus ~10 5 .…”

“…~3,000 proteins were identified from 10 HeLa cells using 'nanodroplet processing in one pot for trace samples' (nanoPOTS) [4]. Single cell proteomic analysis using nanoPOTS with tandem mass tag (TMT) booster channels has been recently described [5]. NanoPOTS requires microfabricated glass chips, robotics that can handle picoliter volumes and sample storage in prepacked nano-LC columns.…”

Optimizing accuracy and depth of protein quantification in experiments using isobaric carriers

“…6a. This effect of an increased MS2 AGC target is consistent with previous observations [23], and previously used analytical parameters for SCoPE-MS and SCoPE2 analysis have corresponding to the high AGC target regime [10,17]. In this regime, the isobaric carrier does not limit MS2 accumulation times .…”

Single-cell Proteomics: Progress and Prospects

“…The field has advanced rapidly since those initial reports. More than 1000 protein groups can now be reliably profiled from single cells using both label-free (13), and isobaric labeling workflows (14)(15)(16), and ~6000 protein groups can be profiled from samples comprising just a few hundred cells (17). Thus, a tradeoff still exists between sample size and proteome coverage, but it has dramatically shifted in favor of much smaller samples.…”