4.8 Article

Quantitative Accuracy and Precision in Multiplexed Single-Cell Proteomics

期刊

ANALYTICAL CHEMISTRY
卷 94, 期 5, 页码 2434-2443

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.1c04174

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资金

  1. EPIC-XS - Horizon 2020 program of the European Union [823839]
  2. Austrian Science Fund by ERA-CAPS [I 3686-B25-MEIOREC]

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Advancements in single-cell proteomics workflows have enhanced sensitivity and reproducibility for characterizing unknown biological phenomena. The introduction of multiplexed single-cell proteomics has led to a trend of combining single-cell measurements with abundant carriers to improve precursor selection and identification accuracy, although extreme carrier spikes may affect quantitative accuracy. Narrowly titrated carrier spikes have been found to provide comparable sensitivity with superior accuracy, while alternative multiplexing strategies can help evaluate data quality. Ultimately, optimized experimental designs for multiplexed proteomics of trace samples can lead to improved quantitative accuracy and elevated replicate overlap.
Single-cell proteomics workflows have considerably improved in sensitivity and reproducibility to characterize as-yet unknown biological phenomena. With the emergence of multiplexed single-cell proteomics, studies increasingly present single-cell measurements in conjunction with an abundant congruent carrier to improve the precursor selection and enhance identifications. While these extreme carrier spikes are often >100x more abundant than the investigated samples, the total ion current undoubtably increases but the quantitative accuracy possibly is affected. We here focus on narrowly titrated carrier spikes (i.e., <20x) and assess their elimination for a comparable sensitivity with superior accuracy. We find that subtle changes in the carrier ratio can severely impact the measurement variability and describe alternative multiplexing strategies to evaluate data quality. Lastly, we demonstrate elevated replicate overlap while preserving acquisition throughput at an improved quantitative accuracy with DIA-TMT and discuss optimized experimental designs for multiplexed proteomics of trace samples. This comprehensive benchmarking gives an overview of currently available techniques and guides the conceptualization of the optimal single-cell proteomics experiment.

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