Real-Time Search enables a new gold standard for TMT quantitation accuracy on the Orbitrap Eclipse Tribrid mass spectrometer
Applications | 2020 | Thermo Fisher ScientificInstrumentation
Isobaric labeling strategies such as Tandem Mass Tags (TMT) enable simultaneous identification and quantitation of proteins from multiple samples in a single LC-MS run. Accurate quantitation using TMT depends critically on the purity of precursor ion populations and specificity in fragment selection. While synchronous precursor selection (SPS) MS³ methods improved accuracy over MS², non-specific co-isolated fragments and slower scan rates remained limiting factors. Integration of on-the-fly peptide identification via Real-Time Search on the Orbitrap Eclipse Tribrid mass spectrometer establishes a new gold standard for TMT quantitation accuracy, proteome coverage, and throughput.
This study aimed to assess the performance of Real-Time Search for SPS MS³ quantitation on the Orbitrap Eclipse Tribrid platform. Key goals included:
An EASY-nLC 1200 system coupled to a 50 cm EASY-Spray C18 column was used for peptide separation under a 50 min gradient (8–32% acetonitrile). Samples were analyzed on an Orbitrap Eclipse Tribrid mass spectrometer controlled by Instrument Control Software v3.3. Real-Time Search was implemented between MS² and MS³ scans, using the Comet search engine to match MS² spectra against a FASTA database in under 5 ms per spectrum. Triggered MS³ events were performed only upon positive peptide identifications. Post-acquisition data processing in Proteome Discoverer 2.3 with SEQUEST HT ensured a 1% FDR.
Real-Time Search for SPS MS³ delivered a 55% increase in peptide and 53% increase in protein identifications versus classical SPS MS³, approaching MS²-only depth while maintaining superior quantitation accuracy. The IFI improved to 0.95, indicating a 95% interference-free measurement. Real-Time Search selectively chose fragment ions matching the identified peptide, raising SPS specificity from 32% to 91%. Implementation with TMTpro 16plex reagents on a 120 min gradient increased quantified proteins by 26%, and reduced coefficient of variation across 16 channels to under 5%. Quantitation accuracy was maintained at large spike-in ratios, critical for applications such as single-cell proteomics.
The combination of on-instrument real-time searching, advanced deconvolution algorithms, and high-resolution analyzers paves the way for:
Real-Time Search for SPS MS³ on the Orbitrap Eclipse Tribrid mass spectrometer establishes a new benchmark in isobaric quantitation. It unites rapid on-the-fly peptide identification with selective MS³ triggering, yielding superior accuracy, depth, and throughput. Compatibility with TMTpro 16plex extends these benefits to larger cohorts and complex experimental designs.
1. Thompson A, Schafer J, Kuhn K, et al. Anal Chem. 2003;75(8):1895-1904.
2. Bantscheff M, Boesche M, Eberhard D, et al. Mol Cell Proteomics. 2008;7(9):1702-1713.
3. McAlister GC, Nusinow DP, Jedrychowski MP, et al. Anal Chem. 2014;86(14):7150-7158.
4. Li J, Van Vranken JG, Pontano Vaites L, et al. Nat Methods. 2020;17(4):399-404.
5. Robitaille AM, Choi J, Viner R, et al. Thermo Fisher Scientific Technical Note 72968, 2019.
6. Eng JK, Jahan TA, Hoopmann MR. Proteomics. 2013;13(1):22-24.
7. Erickson BK, Mintseris J, Schweppe DK, et al. J Proteome Res. 2019;18(3):1299-1306.
8. Schweppe DK, Eng JK, Bailey D, et al. J Proteome Res. 2020.
9. Paulo JA, O’Connell JD, Gygi SP. J Am Soc Mass Spectrom. 2016;27(10):1620-1625.
10. Gygi JP, Yu Q, Navarrete-Perea J, et al. J Proteome Res. 2019;18(2):687-693.
11. Kelstrup CD, Aizikov K, Batth TS, et al. Proteomics. 2018;17(11):4008-4016.
12. Grinfeld D, Aizikov K, Kreutzmann A, et al. Anal Chem. 2017;89(2):1202-1211.
13. Yu C, Huszagh A, Viner R, et al. Anal Chem. 2016;88(20):10301-10308.
14. Dou M, Clair G, Tsai CF, et al. Anal Chem. 2019;91(20):13119-13127.
LC/HRMS, LC/MS, LC/MS/MS, LC/Orbitrap
IndustriesClinical Research
ManufacturerThermo Fisher Scientific
Summary
Importance of the Topic
Isobaric labeling strategies such as Tandem Mass Tags (TMT) enable simultaneous identification and quantitation of proteins from multiple samples in a single LC-MS run. Accurate quantitation using TMT depends critically on the purity of precursor ion populations and specificity in fragment selection. While synchronous precursor selection (SPS) MS³ methods improved accuracy over MS², non-specific co-isolated fragments and slower scan rates remained limiting factors. Integration of on-the-fly peptide identification via Real-Time Search on the Orbitrap Eclipse Tribrid mass spectrometer establishes a new gold standard for TMT quantitation accuracy, proteome coverage, and throughput.
Objectives and Overview
This study aimed to assess the performance of Real-Time Search for SPS MS³ quantitation on the Orbitrap Eclipse Tribrid platform. Key goals included:
- Evaluating improvements in peptide and protein identification rates compared with classical SPS MS³.
- Measuring quantitation accuracy via the Pierce TMT11plex Yeast Digest Standard and calculating the Interference Free Index (IFI).
- Demonstrating compatibility with next-generation TMTpro 16plex reagents for expanded multiplexing.
Methodology and Instrumentation
An EASY-nLC 1200 system coupled to a 50 cm EASY-Spray C18 column was used for peptide separation under a 50 min gradient (8–32% acetonitrile). Samples were analyzed on an Orbitrap Eclipse Tribrid mass spectrometer controlled by Instrument Control Software v3.3. Real-Time Search was implemented between MS² and MS³ scans, using the Comet search engine to match MS² spectra against a FASTA database in under 5 ms per spectrum. Triggered MS³ events were performed only upon positive peptide identifications. Post-acquisition data processing in Proteome Discoverer 2.3 with SEQUEST HT ensured a 1% FDR.
Used Instrumentation
- Orbitrap Eclipse Tribrid mass spectrometer
- EASY-nLC 1200 chromatography system
- EASY-Spray C18 50 cm × 75 µm column and EASY-Spray ion source
- Thermo Scientific Pierce TMT11plex Yeast Digest Standard
- TMTpro 16plex Label Reagent Set
- Proteome Discoverer 2.3 software with SEQUEST HT and Comet search engines
Main Results and Discussion
Real-Time Search for SPS MS³ delivered a 55% increase in peptide and 53% increase in protein identifications versus classical SPS MS³, approaching MS²-only depth while maintaining superior quantitation accuracy. The IFI improved to 0.95, indicating a 95% interference-free measurement. Real-Time Search selectively chose fragment ions matching the identified peptide, raising SPS specificity from 32% to 91%. Implementation with TMTpro 16plex reagents on a 120 min gradient increased quantified proteins by 26%, and reduced coefficient of variation across 16 channels to under 5%. Quantitation accuracy was maintained at large spike-in ratios, critical for applications such as single-cell proteomics.
Benefits and Practical Applications
- Enhanced quantitative accuracy through real-time peptide validation and fragment selection.
- Greater proteome coverage with minimal increase in cycle time.
- Expanded multiplexing capacity up to 16 samples, facilitating large-scale biological studies.
- Improved throughput ideal for drug–dose responses, thermal profiling, and single-cell analyses.
Future Trends and Opportunities
The combination of on-instrument real-time searching, advanced deconvolution algorithms, and high-resolution analyzers paves the way for:
- Integration with emerging isobaric labels beyond 16plex.
- Automated adaptive acquisition schemes driven by machine learning.
- Broader application to post-translational modification profiling in real time.
- Enhanced single-cell and spatial proteomics workflows with higher sensitivity.
Conclusion
Real-Time Search for SPS MS³ on the Orbitrap Eclipse Tribrid mass spectrometer establishes a new benchmark in isobaric quantitation. It unites rapid on-the-fly peptide identification with selective MS³ triggering, yielding superior accuracy, depth, and throughput. Compatibility with TMTpro 16plex extends these benefits to larger cohorts and complex experimental designs.
References
1. Thompson A, Schafer J, Kuhn K, et al. Anal Chem. 2003;75(8):1895-1904.
2. Bantscheff M, Boesche M, Eberhard D, et al. Mol Cell Proteomics. 2008;7(9):1702-1713.
3. McAlister GC, Nusinow DP, Jedrychowski MP, et al. Anal Chem. 2014;86(14):7150-7158.
4. Li J, Van Vranken JG, Pontano Vaites L, et al. Nat Methods. 2020;17(4):399-404.
5. Robitaille AM, Choi J, Viner R, et al. Thermo Fisher Scientific Technical Note 72968, 2019.
6. Eng JK, Jahan TA, Hoopmann MR. Proteomics. 2013;13(1):22-24.
7. Erickson BK, Mintseris J, Schweppe DK, et al. J Proteome Res. 2019;18(3):1299-1306.
8. Schweppe DK, Eng JK, Bailey D, et al. J Proteome Res. 2020.
9. Paulo JA, O’Connell JD, Gygi SP. J Am Soc Mass Spectrom. 2016;27(10):1620-1625.
10. Gygi JP, Yu Q, Navarrete-Perea J, et al. J Proteome Res. 2019;18(2):687-693.
11. Kelstrup CD, Aizikov K, Batth TS, et al. Proteomics. 2018;17(11):4008-4016.
12. Grinfeld D, Aizikov K, Kreutzmann A, et al. Anal Chem. 2017;89(2):1202-1211.
13. Yu C, Huszagh A, Viner R, et al. Anal Chem. 2016;88(20):10301-10308.
14. Dou M, Clair G, Tsai CF, et al. Anal Chem. 2019;91(20):13119-13127.
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