Surpassing 10 000 identified and quantified proteins in a single run by optimizing current LC-MS instrumentation and data analysis strategy

Muntel, Jan; Gandhi, Tejas; Verbeke, Lynn; Bernhardt, Oliver M.; Treiber, Tobias; Bruderer, Roland; Reiter, Lukas

doi:10.1039/c9mo00082h

Cited by 153 publications

(193 citation statements)

References 73 publications

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“…However, given the RT calibration step in EncyclopeDIA, this discrepancy caused no issue. Hybrid spectral libraries were very recently reported to improve proteome coverage [29,37,41]. Here, we shown this to greatly facilitate dual-proteome profiling, as such complex proteome mixtures pose an enormous challenge to DDA, making DDA-only libraries far from comprehensive.…”

Section: Dia Improves Quantification Of Low Abundant Proteinsmentioning

confidence: 83%

“…Hybrid spectral libraries are essentially merged libraries comprising results of different DDA or DIA analysis workflows, e.g. combining predicted spectral libraries with experimental libraries [41], or DDA-based and DIA-only spectral libraries [29]. Here, the MS²PIP-predicted spectral library search, PECAN analysis and obtained MaxQuant DDA results were merged to generate a single hybrid library.…”

Section: Dia-only Workflows and Predicted Spectral Libraries Can Joinmentioning

confidence: 99%

“…We compared the performance of MS 2 PIP-predicted and DDA-based spectral libraries, and, to improve on DDA sensitivity, we extended the spectral library [28] by including MS2 spectra obtained from pre-fractionated LC-MS/MS DDA data of Salmonella grown under different infection-relevant conditions. Lastly, by integrating (predicted) DDA libraries and library-independent approaches, a hybrid DDA-based spectral library was created [29], which could achieve an up to 2-to 3-fold increase in consistently quantified human or spiked in Salmonella proteins and peptides.…”

Section: Introductionmentioning

confidence: 99%

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The use of hybrid data-dependent and -independent acquisition spectral libraries empower dual-proteome profiling

Willems

Fels

Staes

et al. 2020

Preprint

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In the context of bacterial infections, it is imperative that physiological responses can be studied in an integrated manner, meaning a simultaneous analysis of both the host and the pathogen responses. To improve the sensitivity of detection, data-independent acquisition (DIA) based proteomics was found to outperform data-dependent acquisition (DDA) workflows in identifying and quantifying low abundant proteins. Here, by making use of representative bacterial pathogen/host proteome samples, we report an optimized hybrid library generation workflow for data-independent acquisition mass spectrometry relying on the use of data-dependent and in silico predicted spectral libraries. When compared to searching DDA experiment-specific libraries only, the use of hybrid libraries significantly improved peptide detection to an extent suggesting that infection relevant host-pathogen conditions could be profiled in sufficient depth without the need of a priori bacterial pathogen enrichment when studying the bacterial proteome.

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Section: Dia Improves Quantification Of Low Abundant Proteinsmentioning

confidence: 83%

Section: Dia-only Workflows and Predicted Spectral Libraries Can Joinmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The use of hybrid data-dependent and -independent acquisition spectral libraries empower dual-proteome profiling

Willems

Fels

Staes

et al. 2020

Preprint

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“…Since recent progress has produced new MS instrumentation with higher resolution at faster speed, both the identification and the quantification of peptides in DIA can benefit from the increased quality of MS1 (21,22). In particular, high quality and quantitative MS1 and MS2 data now enable statistical inference of differential peptide and protein abun- 1 The abbreviations used are: LC-MS, liquid chromatography-mass spectrometry; DDA, data-dependent acquisition; DIA, data-independent acquisition; SWATH, sequential window acquisition of all theoretical fragment ions; MP, mixed proteomes; SFC and LFC, small/large fold change; OT, orbitrap; TTOF, triple quadrupole time of flight; CV, coefficient of variation; BH, Benjamini-Hochberg; FDR, false discovery rate.…”

Section: Graphical Abstractmentioning

confidence: 99%

Combining Precursor and Fragment Information for Improved Detection of Differential Abundance in Data Independent Acquisition

Huang

Bruderer

Muntel

et al. 2020

Molecular & Cellular Proteomics

Self Cite

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In bottom-up, label-free discovery proteomics, biological samples are acquired in a data-dependent (DDA) or data-independent (DIA) manner, with peptide signals recorded in an intact (MS1) and fragmented (MS2) form. While DDA has only the MS1 space for quantification, DIA contains both MS1 and MS2 at high quantitative quality. DIA profiles of complex biological matrices such as tissues or cells can contain quantitative interferences, and the interferences at the MS1 and the MS2 signals are often independent. When comparing biological conditions, the interferences can compromise the detection of differential peptide or protein abundance and lead to false positive or false negative conclusions.We hypothesized that the combined use of MS1 and MS2 quantitative signals could improve our ability to detect differentially abundant proteins. Therefore, we developed a statistical procedure incorporating both MS1 and MS2 quantitative information of DIA. We benchmarked the performance of the MS1-MS2-combined method to the individual use of MS1 or MS2 in DIA using four previously published controlled mixtures, as well as in two previously unpublished controlled mixtures. In the majority of the comparisons, the combined method outperformed the individual use of MS1 or MS2. This was particularly true for comparisons with low fold changes, few replicates, and situations where MS1 and MS2 were of similar quality. When applied to a previously unpublished investigation of lung cancer, the MS1-MS2-combined method increased the coverage of known activated pathways.Since recent technological developments continue to increase the quality of MS1 signals (e.g. using the BoxCar scan mode for Orbitrap instruments), the combination of the MS1 and MS2 information has a high potential for future statistical analysis of DIA data.

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“…In this study, DDA runs were collected on the TripleTOF 5600 instrument, which is primarily used for the purpose of analyzing SWATH-MS data. The human spectral library built with DDA runs on TripletOF 5600 has been used for targeted analysis of DIA data acquired on Orbitrap platform [41][42][43] . However, the analysis results based on the TripleTOF-generated library may be sub-optimal due to the differential fragmentation patterns from distinct MS platforms.…”

Section: Control Of False-discovery Rate (Fdr)mentioning

confidence: 99%

Generation of a murine SWATH-MS spectral library to quantify more than 11,000 proteins

Zhong

Qiu

et al. 2020

Sci Data

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targeted SWatH-MS data analysis is critically dependent on the spectral library. Comprehensive spectral libraries of human or several other organisms have been published, but the extensive spectral library for mouse, a widely used model organism is not available. Here, we present a large murine spectral library covering more than 11,000 proteins and 240,000 proteotypic peptides, which included proteins derived from 9 murine tissue samples and one murine L929 cell line. This resource supports the quantification of 67% of all murine proteins annotated by UniProtKB/Swiss-Prot. Furthermore, we applied the spectral library to SWATH-MS data from murine tissue samples. Data are available via SWATHAtlas (PASS01441).

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Surpassing 10 000 identified and quantified proteins in a single run by optimizing current LC-MS instrumentation and data analysis strategy

Abstract: Optimization of chromatography and data analysis resulted in more than 10 000 proteins in a single shot at a validated FDR of 1% (two-species test) and revealed deep insights into the testis cancer physiology.

Cited by 153 publications

References 73 publications

The use of hybrid data-dependent and -independent acquisition spectral libraries empower dual-proteome profiling

The use of hybrid data-dependent and -independent acquisition spectral libraries empower dual-proteome profiling

Combining Precursor and Fragment Information for Improved Detection of Differential Abundance in Data Independent Acquisition

Generation of a murine SWATH-MS spectral library to quantify more than 11,000 proteins

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