High-throughput proteomics of nanogram-scale samples with Zeno SWATH DIA
The ability to conduct high-quality proteomic experiments in high throughput has opened new avenues in clinical research, drug discovery, and systems biology. Next to an increase in quantitative precision, recent developments in high-throughput proteomics have also gained proteomic depth, to the extent that earlier gaps between classic and high-throughput experiments have significantly narrowed. Here we introduce and benchmark Zeno SWATH, a data-independent acquisition technique that employs a linear ion trap pulsing (Zeno trap pulsing) in order to increase proteomic depth and dynamic range in proteomic experiments. Combined with the high acquisition speed, these gains in sensitivity are particularly attractive for conducting high-throughput proteomics experiments with high chromatographic flow rates and fast gradients. We demonstrate that when combined with either micro-flow- or analytical-flow-rate chromatography, Zeno SWATH increases protein identification in complex samples 5- to 10-fold when compared to current SWATH acquisition methods on the same instrument. Using 20-min micro-flow chromatography, Zeno SWATH identified > 6,000 proteins from a 62.5 ng load of human cell lysate with more than 5,000 proteins consistently quantified in triplicate injections with a median CV of 6%. Using 5-min analytical-flow-rate chromatography (800 µl/min), Zeno SWATH identified 4,907 proteins from a triplicate injection of 2 µg of a human cell lysate; or more than 3,000 proteins from 250 ng tryptic digest. Zeno SWATH hence facilitates precise proteomic experiments with small sample amounts using a fast and robust high flow-rate chromatographic method, broadening the application space that requires precise proteomic experiments on a large scale.
Steps to reproduce
All raw data from ZenoTOF 7600 system (Data are available via ProteomeXchange with identifier PXD036786) were acquired by SCIEX OS (v 2.1.6) (note that SciexOS 3.0 which supports Zeno SWATH is the commercial software that are available on market) processed with DIA-NN (v1.8 beta 20) using mass accuracy of 20 and 12 ppm at the MS2 and MS1 level, respectively, scan window of 7, protein inference disabled (spectral library as described above) or relaxed (library-free, with additional command --relaxed-prot-inf), quantification strategy of "Robust LC (high precision)" and library generation set as “IDs, RT& IM profiling”. All other settings were kept default. The high-flow K562 benchmark data were analysed using the DDA-based library described above, with MBR disabled. Specifically, the ‘Deep learning-based spectra, RTs and IMs prediction’ option was activated in DIA-NN, to replace all spectra and retention times in the public spectral library with in silico predicted ones. Further, the protein annotation in the library was replaced using the ‘Reannotate’ function in DIA-NN with the annotation from the Human UniProt isoform sequence database (UP000005640, 19 October 2021). The processing was performed using the MBR mode in DIA-NN, that is a two-step analysis wherein a spectral library (an empirical or in silico predicted) is first refined based on the DIA experiment in question, and subsequently used to reanalyse it. For the analysis of microflow K562 acquisition as well as samples from other species, the respective FASTA databases from Uniprot (human: UP000005640 （10 March 2022) yeast: UP000002311_559292 (28 September 2021) E. coli: UP000000625 (19 October 2021); chickpea: UP000087171_3827 (22 October 2021)) were used by DIA-NN in library-free mode. Specifically, following the two-step MBR approach described previously , an in silico spectral library is first generated by DIA-NN from the FASTA file(s); this library is then refined based on the DIA dataset and subsequently used to reanalyse the dataset, to obtain the final results