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Deep Learning Predicts Peptide Transmission Profiles through FAIMS Directly from Sequence

ABSTRACT: Peptide ion mobility adds an extra dimension of separation to mass spectrometry-based proteomics. The ability to accurately pre-dict peptide ion mobility would be useful to expedite assay development and to discriminate true answers in database search. There are methods to accurately predict peptide ion mobility through drift tube devices, but methods to predict mobility through high-field asymmetric waveform ion mobility (FAIMS) are underexplored. Here, we successfully model peptide ions’ FAIMS mobility using a multi-label multi-output classification scheme to account for non-normal transmission distributions. We trained two models from over 100,000 human peptide precursors: a random forest and a long-term short-term memory (LSTM) neural network. Both models had different strengths, and the ensemble average of model predictions produced higher F2 score than either model alone. Finally, we explore cases where the models make mistakes, and demonstrate predictive performance of F2=0.66 (AUROC=0.928) on a new test dataset of nearly 40,000 different E. coli peptide ions.

INSTRUMENT(S): Orbitrap Fusion

ORGANISM(S): Homo Sapiens (human) Escherichia Coli Caenorhabditis Elegans Saccharomyces Cerevisiae (baker's Yeast)

SUBMITTER: Pavel Sinitcyn

LAB HEAD: Joshua J.

PROVIDER: PXD055252 | Pride | 2025-01-16

REPOSITORIES: pride

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			Action	DRS
	20220505_PS_K562_IT_CV15.raw	Raw
	20220505_PS_K562_IT_CV16.raw	Raw
	20220505_PS_K562_IT_CV17.raw	Raw
	20220505_PS_K562_IT_CV18.raw	Raw
	20220505_PS_K562_IT_CV19.raw	Raw

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Human and E. coli peptides used for predicting FAIMS CVs

Project description:Peptide ion mobility adds an extra dimension of separation to mass spectrometry-based proteomics. The ability to accurately predict peptide ion mobility would be useful to expedite assay development, or as an additional constraint for peptide identification. Although there are methods to accurately predict peptide mobility in drift tube ion mobility, more work is needed to predict mobility through the high-field asymmetric waveform ion mobility (FAIMS). Here, we show that prediction of peptide FAIMS ion mobility is not a simple regression due to peptides observed at multiple mobilities, but we successfully model this problem as multi-label classification. We trained two separate models, a random forest and a long-term short-term memory neural network. Both models had different strengths, and the ensemble average of model predictions produced higher f2 score than either model alone. Finally, we explore why the models are wrong, and demonstrate predictive performance of f2=0.66 (AUROC = 0.928) on a new test dataset of nearly 40,000 different E. coli peptides.

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Project description:High-field asymmetric waveform ion mobility spectrometry (FAIMS) has gained popularity in the proteomics field for its capability to improve mass spectrometry sensitivity and to decrease peptide co-fragmentation. The recent implementation of FAIMS on Tribrid Orbitrap instruments enhanced proteome coverage and increased the precision of quantitative measurements. However, the FAIMS interface has not been available on older generation Orbitrap mass spectrometers such as the Q-Exactive. Here, we report the integration of the FAIMS-Pro device with embedded electrical and gas connections to a Q-Exactive HF mass spectrometer. Proteomic experiments performed on HeLa tryptic digests with the modified mass spectrometer improved signal to noise and reduced interfering ions resulting in an increase of 42% in peptide identification. FAIMS was also combined with segmented ion fractionation where 150 m/z windows were analyzed in turn to further increase the depth of proteome analysis by reducing the proportion of chimeric MS/MS spectra from 50% to 27%. We also demonstrate the application of FAIMS to improve quantitative measurements when using isobaric peptide labeling.

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Project description:Identification of K-Ras and B-Raf mutations in colorectal cancer (CRC) is essential to predict patients' response to anti-EGFR therapy and formulate appropriate therapeutic strategies to improve prognosis and survival. Here, we combined parallel reaction monitoring (PRM) with high-field asymmetric waveform ion mobility (FAIMS) to enhance mass spectrometry sensitivity and improve the identification of low-abundance K-Ras and B-Raf mutations in biological samples without immunoaffinity enrichment. In targeted LC-MS/MS analyses, FAIMS reduced the occurrence of interfering ions and enhanced precursor ion purity, resulting in a three-fold improvement in the detection limit for K-Ras and B-Raf mutated peptides. In addition, ion mobility separation of isomeric peptides using FAIMS facilitated the unambiguous identification of K-Ras G12D and G13D peptides. The application of targeted LC-MS/MS analyses using FAIMS is demonstrated for the detection and quantitation of B-Raf V600E, K-Ras G12D, G13D, and G12V in CRC cell lines and primary specimens.

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Project description:The insertion of ion mobility spectrometry (IMS) between LC and MS can improve peptide identification in both proteomics and phosphoproteomics by providing structural information that is complementary to LC and MS, because IMS separates ions on the basis of differences in their shapes and charge states. However, it is necessary to know how phosphate groups affect the peptide collision cross sections (CCS) in order to accurately predict phosphopeptide CCS values and to maximize the usefulness of IMS. In this work, we systematically characterized the CCS values of 4,433 pairs of mono-phosphopeptide and corresponding unphosphorylated peptide ions using trapped ion mobility spectrometry (TIMS). Nearly one-third of the mono-phosphopeptide ions evaluated here showed smaller CCS values than their unphosphorylated counterparts, even though phosphorylation results in a mass increase of 80 Da. Significant changes of CCS upon phosphorylation occurred mainly in structurally extended peptides with large numbers of basic groups, possibly reflecting intramolecular interactions between phosphate and basic groups.

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Evaluation and Optimization of High-Field Asymmetric Waveform Ion Mobility Spectrometry for Multiplexed Quantitative Site-specific N-glycoproteomics

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