Featured Publications
Proteotype coevolution and quantitative diversity across 11 mammalian species
Ba Q, Hei Y, Dighe A, Li W, Maziarz J, Pak I, Wang S, Wagner GP, Liu Y. Proteotype coevolution and quantitative diversity across 11 mammalian species. Science Advances 2022, 8: eabn0756. PMID: 36083897, PMCID: PMC9462687, DOI: 10.1126/sciadv.abn0756.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBiological EvolutionGene Expression ProfilingMammalsProteomeProteomicsTranscriptomeConceptsMammalian speciesRNA metabolic processesCommon mammalian speciesUbiquitin-proteasome systemEvolutionary profilingMammalian lineagesProteomic methodsProtein degradationProtein abundanceGene expressionProtein expression levelsHigh interspeciesMetabolic processesCovariation analysisFunctional roleNucleotide levelExpression levelsQuantitative diversityCoevolutionMammalsSpeciesRemarkable variationExpressionTranscriptomeBiological variabilityGlobal and Site-Specific Effect of Phosphorylation on Protein Turnover
Wu C, Ba Q, Lu D, Li W, Salovska B, Hou P, Mueller T, Rosenberger G, Gao E, Di Y, Zhou H, Fornasiero EF, Liu Y. Global and Site-Specific Effect of Phosphorylation on Protein Turnover. Developmental Cell 2020, 56: 111-124.e6. PMID: 33238149, PMCID: PMC7855865, DOI: 10.1016/j.devcel.2020.10.025.Peer-Reviewed Original ResearchConceptsProtein turnoverProtein lifetimeCyclin-dependent kinase substrateStable isotope-labeled amino acidsSite-specific phosphorylationPulse-labeling approachIsotope-labeled amino acidsMass spectrometry-based methodCell fitnessKinase substratePhosphorylation sitesPhosphorylated sitesProteomic methodsCell signalingSpectrometry-based methodsLive cellsAmino acidsPhosphositesRich resourceDisease biologyLabeling approachPhosphorylationModification typesGlutamic acidTurnover
2024
PTMoreR-enabled cross-species PTM mapping and comparative phosphoproteomics across mammals
Wang S, Di Y, Yang Y, Salovska B, Li W, Hu L, Yin J, Shao W, Zhou D, Cheng J, Liu D, Yang H, Liu Y. PTMoreR-enabled cross-species PTM mapping and comparative phosphoproteomics across mammals. Cell Reports Methods 2024, 4: 100859. PMID: 39255793, PMCID: PMC11440062, DOI: 10.1016/j.crmeth.2024.100859.Peer-Reviewed Original ResearchConceptsP-siteSurrounding amino acid sequenceKinase-substrate networkQuantitative phosphoproteomic analysisFunctional enrichment analysisPhosphoproteomic resultsKinase motifsComparative phosphoproteomicsPTM sitesPhosphorylation eventsPhosphoproteomic analysisProteomic analysisEnrichment analysisMammalian speciesSpeciesEvolutionary anglePhosphoproteomeMotifEnvironmental factorsNon-human speciesPTMProteomicsKinaseMammalsProteinNetwork-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis
Rosenberger G, Li W, Turunen M, He J, Subramaniam P, Pampou S, Griffin A, Karan C, Kerwin P, Murray D, Honig B, Liu Y, Califano A. Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis. Nature Communications 2024, 15: 3909. PMID: 38724493, PMCID: PMC11082183, DOI: 10.1038/s41467-024-47957-3.Peer-Reviewed Original ResearchConceptsMechanism of cell responseResistance mechanismsSignaling pathway responsesDrug resistance mechanismsEnzyme/substrate interactionsAdaptive resistance mechanismsNetwork rewiringPhosphorylation stateSignaling pathway activationDrug perturbationsProteomic technologiesSignaling crosstalkPathway responsesInhibitor designPathway activationCancer drug resistance mechanismsCell adaptive responsesAdaptive responsePhosphatase activityNetwork-based methodologyRewiringTherapeutic efficacyPhosphoproteome coverageCell responsesControl mediumThe CUL5 E3 ligase complex negatively regulates central signaling pathways in CD8+ T cells
Liao X, Li W, Zhou H, Rajendran B, Li A, Ren J, Luan Y, Calderwood D, Turk B, Tang W, Liu Y, Wu D. The CUL5 E3 ligase complex negatively regulates central signaling pathways in CD8+ T cells. Nature Communications 2024, 15: 603. PMID: 38242867, PMCID: PMC10798966, DOI: 10.1038/s41467-024-44885-0.Peer-Reviewed Original ResearchConceptsCD8+ T cellsT cellsCancer immunotherapyMouse CD8+ T cellsAnti-tumor immunityTumor growth inhibition abilityAnti-tumor effectsInhibition of neddylationCD8Effector functionsTCR stimulationIL2 signalingCentral signaling pathwaysCore signaling pathwaysEffector activityNegative regulatory mechanismsTranslational implicationsImmunotherapyGrowth inhibition abilityCytokine signalingTCRProteomic alterationsSignaling pathwayCancerCRISPR-based screens
2023
The SysteMHC Atlas v2.0, an updated resource for mass spectrometry-based immunopeptidomics
Huang X, Gan Z, Cui H, Lan T, Liu Y, Caron E, Shao W. The SysteMHC Atlas v2.0, an updated resource for mass spectrometry-based immunopeptidomics. Nucleic Acids Research 2023, 52: d1062-d1071. PMID: 38000392, PMCID: PMC10767952, DOI: 10.1093/nar/gkad1068.Peer-Reviewed Original Research
2021
A peptidoform based proteomic strategy for studying functions of post‐translational modifications
Liu Y. A peptidoform based proteomic strategy for studying functions of post‐translational modifications. Proteomics 2021, 22: e2100316. PMID: 34878717, PMCID: PMC8959388, DOI: 10.1002/pmic.202100316.Peer-Reviewed Original ResearchDeveloping a Bimolecular Affinity Purification Strategy to Isolate 26S Proteasome Holocomplexes for Complex-Centric Proteomic Analysis
Yu C, Wang X, Li W, Liu Y, Huang L. Developing a Bimolecular Affinity Purification Strategy to Isolate 26S Proteasome Holocomplexes for Complex-Centric Proteomic Analysis. Analytical Chemistry 2021, 93: 13407-13413. PMID: 34550675, PMCID: PMC8999942, DOI: 10.1021/acs.analchem.1c03551.Peer-Reviewed Original ResearchProteasome Endopeptidase ComplexProteomicsData-independent acquisition-based proteome and phosphoproteome profiling across six melanoma cell lines reveals determinants of proteotypes
Gao E, Li W, Wu C, Shao W, Di Y, Liu Y. Data-independent acquisition-based proteome and phosphoproteome profiling across six melanoma cell lines reveals determinants of proteotypes. Molecular Omics 2021, 17: 413-425. PMID: 33728422, PMCID: PMC8205956, DOI: 10.1039/d0mo00188k.Peer-Reviewed Original ResearchBoxCarmax: A High-Selectivity Data-Independent Acquisition Mass Spectrometry Method for the Analysis of Protein Turnover and Complex Samples
Salovska B, Li W, Di Y, Liu Y. BoxCarmax: A High-Selectivity Data-Independent Acquisition Mass Spectrometry Method for the Analysis of Protein Turnover and Complex Samples. Analytical Chemistry 2021, 93: 3103-3111. PMID: 33533601, PMCID: PMC8959401, DOI: 10.1021/acs.analchem.0c04293.Peer-Reviewed Original ResearchConceptsData-independent acquisitionProtein turnoverDIA mass spectrometryStable isotope labelingValuable biological insightsRelative protein quantificationSerum starvation stressIsotopic labeling approachSILAC experimentsStarvation stressConventional DIA methodGas-phase separation strategyBiological insightsDegradation regulationIsotope labelingCultured cellsAmino acidsDIA-MSProtein quantificationLabeling approachPeptide pairsCell culturesBiological investigationsMultiplexed acquisitionComplex samples
2020
SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles
Rosenberger G, Heusel M, Bludau I, Collins BC, Martelli C, Williams EG, Xue P, Liu Y, Aebersold R, Califano A. SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles. Cell Systems 2020, 11: 589-607.e8. PMID: 33333029, PMCID: PMC8034988, DOI: 10.1016/j.cels.2020.11.006.Peer-Reviewed Original ResearchConceptsProtein-protein interactionsProtein complexesCell statesProtein complex dynamicsNative protein complexesMacromolecular complex formationPaper's transparent peer review processProtein interaction networksSEC-SWATHMultiple cell statesNetwork-centric analysisCellular processesInteraction networksMass spectrometric data analysisProteome OrganizationMolecular mechanismsRegulatory roleMass spectrometric analysisNetwork-based studyMultiplexed characterizationComplex formationSpectrometric data analysisSpectrometric analysisAlgorithmic toolkitState-specific changesNAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses
Wang S, Li W, Hu L, Cheng J, Yang H, Liu Y. NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses. Nucleic Acids Research 2020, 48: e83-e83. PMID: 32526036, PMCID: PMC7641313, DOI: 10.1093/nar/gkaa498.Peer-Reviewed Original ResearchMulti-in-One: Multiple-Proteases, One-Hour-Shot Strategy for Fast and High-Coverage Phosphoproteomic Investigation
Gao X, Li Q, Liu Y, Zeng R. Multi-in-One: Multiple-Proteases, One-Hour-Shot Strategy for Fast and High-Coverage Phosphoproteomic Investigation. Analytical Chemistry 2020, 92: 8943-8951. PMID: 32479063, DOI: 10.1021/acs.analchem.0c00906.Peer-Reviewed Original ResearchSelection of Features with Consistent Profiles Improves Relative Protein Quantification in Mass Spectrometry Experiments*
Tsai TH, Choi M, Banfai B, Liu Y, MacLean B, Dunkley T, Vitek O. Selection of Features with Consistent Profiles Improves Relative Protein Quantification in Mass Spectrometry Experiments*. Molecular & Cellular Proteomics 2020, 19: 944-959. PMID: 32234965, PMCID: PMC7261813, DOI: 10.1074/mcp.ra119.001792.Peer-Reviewed Original ResearchConceptsRelative protein quantificationData-independent acquisitionData-dependent acquisitionMass spectrometry-based proteomicsSpectrometry-based proteomicsProtein quantificationOverall protein profileAbundant proteinsProtein profilesManual curationProteinMass spectrometry experimentsReproducibility of conclusionsBiological investigationsAbundanceSpectrometry experimentsIsoform‐resolved correlation analysis between mRNA abundance regulation and protein level degradation
Salovska B, Zhu H, Gandhi T, Frank M, Li W, Rosenberger G, Wu C, Germain P, Zhou H, Hodny Z, Reiter L, Liu Y. Isoform‐resolved correlation analysis between mRNA abundance regulation and protein level degradation. Molecular Systems Biology 2020, 16: e9170. PMID: 32175694, PMCID: PMC7073818, DOI: 10.15252/msb.20199170.Peer-Reviewed Original ResearchConceptsProtein degradationGenome-wide correlation analysisGene dosage variationProtein abundance levelsStable isotope-labeled amino acidsIndividual protein isoformsSpecific biological processesAlternative splicing isoformsData-independent acquisition mass spectrometryIsotope-labeled amino acidsAcquisition mass spectrometryProtein degradation ratesIntron retentionCellular functionsProtein isoformsSplicing isoformsCellular organellesTranscriptome variabilitySame geneTurnover controlRegulatory mechanismsBiological processesSpecific mRNAsTight associationAbundance levelsA Global Screen for Assembly State Changes of the Mitotic Proteome by SEC-SWATH-MS
Heusel M, Frank M, Köhler M, Amon S, Frommelt F, Rosenberger G, Bludau I, Aulakh S, Linder MI, Liu Y, Collins BC, Gstaiger M, Kutay U, Aebersold R. A Global Screen for Assembly State Changes of the Mitotic Proteome by SEC-SWATH-MS. Cell Systems 2020, 10: 133-155.e6. PMID: 32027860, PMCID: PMC7042714, DOI: 10.1016/j.cels.2020.01.001.Peer-Reviewed Original ResearchConceptsSEC-SWATHHundreds of complexesThousands of proteinsAssembly state changesMitotic proteomeProtein complexesProteomic studiesGlobal screenHuman cellsComplex remodelingHigher-level organizationBiological researchKey hallmarksBiochemical reactionsInteractive exploration toolProteinFunctional stateSpecific changesComplexesProteomeCellsMitosisHallmarkRemodelingInterphase
2019
motifeR: An Integrated Web Software for Identification and Visualization of Protein Posttranslational Modification Motifs
Wang S, Cai Y, Cheng J, Li W, Liu Y, Yang H. motifeR: An Integrated Web Software for Identification and Visualization of Protein Posttranslational Modification Motifs. Proteomics 2019, 19: e1900245. PMID: 31622013, DOI: 10.1002/pmic.201900245.Peer-Reviewed Original ResearchConceptsUser-friendly web toolWeb softwarePublic datasetsBioinformatics backgroundLarge datasetsWeb toolMotif discoveryOptional featuresDatasetPresentation of motivesExponential growthLocation probabilitySoftwareKinase-substrate relationsModification sitesProtein post-translational modificationsPost-translational modificationsUsabilityUsersToolToolkitNetworkModification motifsPhosphoproteomic datasetsSite enrichmentBreast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry
Bouchal P, Schubert OT, Faktor J, Capkova L, Imrichova H, Zoufalova K, Paralova V, Hrstka R, Liu Y, Ebhardt HA, Budinska E, Nenutil R, Aebersold R. Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry. Cell Reports 2019, 28: 832-843.e7. PMID: 31315058, PMCID: PMC6656695, DOI: 10.1016/j.celrep.2019.06.046.Peer-Reviewed Original ResearchCombining Rapid Data Independent Acquisition and CRISPR Gene Deletion for Studying Potential Protein Functions: A Case of HMGN1
Mehnert M, Li W, Wu C, Salovska B, Liu Y. Combining Rapid Data Independent Acquisition and CRISPR Gene Deletion for Studying Potential Protein Functions: A Case of HMGN1. Proteomics 2019, 19: e1800438. PMID: 30901150, DOI: 10.1002/pmic.201800438.Peer-Reviewed Original ResearchConceptsChromosomal protein HMG-14DIA-MSDIA mass spectrometryPotential protein functionsCRISPR-Cas gene editingImmune regulation processesCancer cellsExtracellular proteomeChromatin structureHistone inactivationFunctional annotationProtein functionCellular functionsRegulation eventsImportant functional implicationsHMG 14Gene knockoutEnrichment analysisData-independent acquisitionHMGN1Protein deletionCRISPR experimentsGene editingStress pathwaysIndependent acquisitionAssessing the Relationship Between Mass Window Width and Retention Time Scheduling on Protein Coverage for Data-Independent Acquisition
Li W, Chi H, Salovska B, Wu C, Sun L, Rosenberger G, Liu Y. Assessing the Relationship Between Mass Window Width and Retention Time Scheduling on Protein Coverage for Data-Independent Acquisition. Journal Of The American Society For Mass Spectrometry 2019, 30: 1396-1405. PMID: 31147889, DOI: 10.1007/s13361-019-02243-1.Peer-Reviewed Original Research