Increasing the throughput of sensitive proteomics by plexDIA

Abstract

Current mass-spectrometry methods enable high-throughput proteomics of large sample amounts, but proteomics of low sample amounts remains limited in depth and throughput. We aimed to increase the throughput of high-sensitivity proteomics while achieving high proteome coverage and quantitative accuracy. We developed a general experimental and computational framework, plexDIA, for simultaneously multiplexing the analysis of both peptides and samples. Multiplexed analysis with plexDIA increases throughput multiplicatively with the number of labels without reducing proteome coverage or quantitative accuracy. Specifically, plexDIA using 3-plex nonisobaric mass tags enables quantifying 3-fold more protein ratios among nanogram-level samples. Using 1 hour active gradients and first-generation Q Exactive, plexDIA quantified about 8,000 proteins in each sample of labeled 3-plex sets. Furthermore, plexDIA increases the consistency of protein quantification, resulting in over 2-fold reduction of missing data across samples. We applied plexDIA to quantify proteome dynamics during the cell division cycle in cells isolated based on their DNA content. The high sensitivity and accuracy of plexDIA detected many classical cell cycle proteins and discovered new ones. These results establish a general framework for increasing the throughput of highly sensitive and quantitative protein analysis.

Scaling Up Single-Cell Proteomics

“…These advantages will likely motivate the development of higher plex reagents for single-cell proteomics. While such development requires significant investments for isobaric mass tags ( 37 ), nonisobaric isotopologous mass tags may be easier to develop and may enable both high sensitivity and high throughput ( 54 ).

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“…The throughput can be increased by (i) parallel analysis of single cells via sample multiplexing, parallel analysis of peptides via DIA, and (iii) shorter separation times, which reduce the MS time per labeled set. Combining the gains from these three approaches can multiplicatively increase the throughput of single-cell proteomics ( 54 ). DIA, data-independent acquisition.…”

“…Experimental strategies that minimize set-specific biases can further minimize batch effects. For example, nonisobaric multiplexing avoids biases because of coisolating isobarically labeled peptides ( 54 ). While such experimental design strategies can reduce batch effects, some batch effects will remain and may require computational corrections.…”

“…2 ). Such decrease will reduce the number of peptides that can be analyzed by data-dependent acquisition but may support high-throughput analysis by data-independent acquisition (DIA) ( 4 , 54 ), as demonstrated with bulk samples ( 51 , 55 ). The high flow rates used with ultra-fast bulk DIA analysis are incompatible with maximizing MS sensitivity, but nonetheless shorter gradients may speed up single-cell analysis as well.…”

“…This combination may be achieved by multiplexed DIA performed on short gradients: It multiplies the advantages of sample multiplexing, parallel peptide analysis, and short MS analysis time per sample ( 1 , 4 , 54 ). Multiplexing DIA with 3-plex nonisobaric isotopologous mass tags allows for threefold increased throughput without reduction of proteome coverage or quantitative accuracy ( 54 ). This strategy, termed plexDIA, allows for accurate protein quantification at both MS1 and MS2 levels ( 54 ).…”