Abstract
This technical note describes the fast and sensitive quantitation of a large panel of peptides in human plasma using the SCIEX 7500+ triple quadrupole mass spectrometry system. Peptide quantitation is well-established on triple quadruple platforms and is used extensively for biomarker research1. To ensure accurate quantitative performance, typically a minimum of two Multiple Reaction Monitoring (MRM) transitions are used for each peptide, which limits the number of peptides in the assay. The speed of the SCIEX 7500+ system maximizes the number of concurrent MRMs, which enables the analysis of very large panels of peptides. A multiplexed assay was developed with 2,836 multiple reaction monitoring (MRM) transitions for 709 peptides, both native and heavy-labeled, from 530 human plasma proteins using a 20-minute microflow liquid chromatography (LC) gradient. Using fast MRM scanning (combined dwell and pause times of 3.5 msec per MRM transition) on the SCIEX 7500+ system, >97% of the monitored labeled peptides were quantified with area coefficient of variation (CV) <10%, and the median CV across all transitions was 2.5%.
These results demonstrate the industry-leading performance of the SCIEX 7500+ system for accurate and precise absolute quantitation of large peptide panels, making it the ideal system for disease biomarker research.
Key features of large panel peptide quantitation using microflow LC and the SCIEX 7500+ system
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Faster analysis: Ultra-fast MRM acquisitions enabled by the SCIEX 7500+ system, with combined dwell and pause times as low as 3.5 msec per MRM transition, allows for fast multiplexed quantitative assays of large analyte panels
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Improved quantitative performance:Next-level quantitative precision and accuracy demonstrated using >2,800 MRM transitions to quantify 709 tryptic peptides in human plasma using a 20-minute microflow LC gradient, where >97% of the heavy labeled peptides had area CVs <10% and the median CV across all peptides was 2.5%
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High sensitivity: 5x less sample loadings required for the SCIEX 7500+ with microflow LC using a 0.15 mm ID column at a flow rate of 1.5 µL/min when compared to analytical flow LC
Introduction
After the discovery of potential protein biomarkers using unbiased proteomics analysis, verification of these candidate biomarkers in large numbers of samples is required. These targeted assays are typically performed using multiple reaction monitoring (MRM) with a triple quadrupole mass spectrometer, which provides high sensitivity and specificity for detecting low abundance proteins through proteotypic tryptic peptides1. Heavy-labeled proteotypic peptides are often spiked in for absolute quantitation, whereby protein concentrations are measured by comparing the response of the labeled peptide with the response of its native, light, counterpart. Throughput is essential as large numbers of samples need to be analyzed before a clinical application is possible. In this technical note, we demonstrate how the SCIEX 7500+ system provides excellent quantitative precision using only a 3.5 msec combined pause and dwell time. Scheduling MRM transitions with a 60-second window around the expected retention times allowed for the quantitation of 709 light/heavy peptide pairs with a 20-minute microflow LC gradient run. Using a 0.15 mm ID microflow column at 1.5 μL/min flow rate increases sensitivity while still offering a robust method.
Methods
Samples and reagents: Human pooled plasma K2EDTA was acquired from BioIVT. Top 14 Abundant Protein Depletion Midi spin columns from Thermo Fisher were used for plasma depletion. Trypsin/Lys-C protease mix was purchased from Promega. PQ500 heavy-labeled peptides were purchased from Biognosys.
Sample preparation: Depletion of the top 14 most abundant proteins was performed with the depletion spin columns using the manufacturer's protocol. The remaining proteins were digested following a filter-aided sample preparation (FASP) protocol described in the literature.2 After drying the tryptic peptides, they were dissolved with 0.1% formic acid in water to a concentration of 0.88 μg/μL, and PQ500 peptides were spiked in. The standard spike-in ratio of the manufacturer is 4 μL PQ500 mix to 12 μL of the (depleted) plasma digest diluted to an estimated protein concentration of 0.88 μg/μL, which was equivalent to 1.06 μL plasma. This ratio is referred to in this technical note as "1x". Additional samples were prepared with the same plasma digest concentration but PQ500 peptides at 0.05x, 0.25x, and 2x ratios to determine linearity around the 1x ratio spike in amount. The higher sensitivity from using microflow LC allowed for a further 4x dilution with 0.1% formic acid before injection. In addition, the amount injected per analysis was also lower than recommended (2 μL instead of 3 μL). For this technical note, only non-alkylated peptides, i.e., peptides without cysteines, were analyzed.
Chromatography: The samples were analyzed using a Waters ACQUITY M-Class system in trap and elute nanoflow LC mode. A Waters nanoEase M/Z Symmetry C18 100 Å, 5 μm, 180 μm x 20 mm trap column was used in combination with a Phenomenex Kinetex XB-C18 100 Å, 2.6 μm, 0.15 mm x 15 cm microflow LC column. 2 μL sample was loaded on the trap from a 10 μL loop using 1 minute of loading at 10 μL/min of 0.1% formic acid in water. A 20-minute gradient at 1.5 μL/min from 1-28% mobile phase B was run for the separation, using 0.1% formic acid in water as mobile phase A and 0.1% formic acid in acetonitrile as mobile phase B. The column and trap were washed at 80% mobile phase B for 1.5 minutes and re-equilibrated at 1% mobile phase B for 6 minutes. The column temperature was maintained at 40°C. All analyses were performed in triplicate.
Mass Spectrometry: All analyses were performed using the SCIEX 7500+ system with an OptiFlow Pro ion source with micro E Lens™ and microflow probe with low micro electrode. Two fragments for each peptide were selected for optimal quantitation with Skyline software, using Zeno SWATH DIA data previously acquired on the ZenoTOF 7600+ system for the PQ500 peptides in a plasma digest3. Collision energies were calculated using the dynamic collision energy equation for peptides integrated in the SCIEX OS software. Ion source and MS method parameters for the final scheduled MRM method used are listed in Table 1.
Data processing: Data were processed using the Analytics module of SCIEX OS version 3.4. The two selected fragment ion signals for each heavy or light peptide were summed for quantitation and integrated using the Autopeak integration method.
Proteins quantified
Digested HeLa cell lysate was used to characterize the various SPD workflows using Zeno SWATH DIA on the ZenoTOF 7600 system. For these experiments, 200 and 50 ng sample loads were used (Figures 1 and 3, respectively). This characterization permits users to select the workflows and required sample amounts that best match the throughput and depth of proteome coverage for their experimental needs.
For both loading amounts, as the SPD was reduced and the sample analysis time increased, the number of proteins identified and quantified increased (Figure 3). When the throughput was reduced from 200 to 30 SPD, 102% and 82% more proteins were identified at <1% FDR at 50 and 200 ng loads, respectively. More importantly, the number of proteins quantified at <20% CV also greatly increased, with 77% and 80% more quantified at 50 and 200 ng loads, respectively.
For a 50 ng load of HeLa digest (Figure 3), the 30 SPD workflow provided maximal proteome coverage. With Zeno SWATH DIA, 5727 protein groups were detected, 4232 of which were quantified at <20% CV (Figure 3). With this load and SPD workflow, 74% of detected proteins were reliably quantified.
With a higher load, run times were easily accelerated. Using the 100 SPD workflow and a sample load of 200 ng of HeLa digest (Figure 1), 5499 protein groups were detected and 4870 (88%) were reproducibly quantified with <20% CV. This method therefore provided both proteome coverage and high sample throughput. When the throughput was reduced to 30 SPD and 200 ng of HeLa digest was loaded, 7014 protein groups were detected, 6189 (88%) of which were quantified with <20% CV.
Library-free protein identification from Zeno SWATH DIA data
An emerging workflow powered by improvements in software algorithms is the library-free approach for processing DIA data. Here, DIA-NN software was used to convert a FASTA file in silico to a spectral library to use for data processing. The Zeno SWATH DIA data from these experiments were processed with both the in silico library and a spectral library generated from experimental ZenoTOF 7600 system data.6 These results were also compared with those generated by processing the data using thePan Human library (Figure 4,top).7
Analysis of the data generated with a sample load of 200 ng HeLa digest on column revealed good performance with the library-free approach. Analysis using the in silico generated library provided protein identification results similar to those yielded by analysis with the 2 experimentally generated libraries (Figure 4). At 30 SPD, 6417 proteins were identified at <1% FDR using the library-free approach, whereas 7014 proteins were identified with the ZenoTOF 7600 library.
A key advantage of the Zeno SWATH DIA approach for protein identification is the ability to also obtain quantification information from the Zeno MS/MS data, as shown in Figure 4. Typically, 90% of the proteins identified were also quantified with <20% CV when 200 ng of sample was loaded for all throughput workflows.
The library-free approach is a very effective search strategy, as it enables the identification and quantification of proteins without the prerequisite of generating sample and cohort-specific libraries.
Peptide precursors quantified
Finally, the impact of SPD and load on the numbers of peptide precursors quantified was examined (Figure 5). For a 200 ng load, ~15,000 precursors were quantified at 200 SPD and ~42,000 at 30 SPD (Figure 5). The most significant improvement occurred when reducing throughput from 100 to 60 SPD, as identifications increased 43%.
In terms of SPD throughput and different proteomic loads, lower loads favored higher SPDs. A throughput of 60 SPD offered balance between performance in detection and quantification. Lower SPD throughputs and higher loads led to increases in protein detection and quantification, as expected. The protein and peptide data presented here can be used as guidance to select appropriate sample loads and required throughputs to meet future study needs.
Conclusions
The ZenoTOF 7600 system using Zeno SWATH DIA provides excellent depth of proteome coverage with high quantitative reproducibility, due to the increase in MS/MS sensitivity with the Zeno trap enabled. Here, Zeno SWATH DIA was coupled with the Evosep One system to demonstrate compatibility with this system and to highlight various workflows for high-throughput, quantitative proteomics applications.
- Sample load and throughput were varied by testing 2 sample loads (50 and 200 ng on column) of HeLa digest at 30, 60, 100 and 200 SPD
- As expected, as run times increased and sample throughput decreased, the depth of proteome coverage increased
- When 200 ng of sample was loaded at 30 SPD, ~7000 proteins were detected at <1% FDR, ~6200 of which were quantified with <20% CV
- Analysis of Zeno SWATH DIA data, collected following separation on the Evosep One system, with the library-free workflow yielded comparable results to the typical library-based approaches
References
- Large-scale, targeted, peptide quantification of 804 peptides with high reproducibility, using Zeno MS/MS. SCIEX technical note, RUO-MKT-02-13346-A.
- Going library-free for protein identification using Zeno SWATH DIA and in silico-generated spectral libraries. SCIEX technical note, RUO-MKT-02-14675-A.
- Zeno MS/MS with microflow chromatography powers the Zeno SWATH DIA workflow for more proteins quantified. SCIEX technical note, RUO-MKT-02-14668-A.
- Processing ZenoTOF 7600 system data with DIA-NN software. SCIEX community post, RUO-MKT-18-14611-A.
- Demichev V et al. (2019) DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput. Nature Methods, 17, 41-44.
- Large-scale protein identification using microflow chromatography on the ZenoTOF 7600 system. SCIEX technical note, RUO-MKT-02-14415-A.
- Data from two fractionation experiments of two human cell lines (Hela, K562) were each processed into a single search result in the ProteinPilot app in OneOmics suite. The search results for each cell line were then merged, and retention time aligned using the Extractor application to create a final ion library.
- Creating a library from a FASTA file for library-free data analysis. SCIEX community post, RUO-MKT-18-14611-A.
- Rosenberger G et al (2014) A repository of assays to quantify 10,000 human proteins by SWATH-MS. Scientific data. 1, 140031.