Abstract
Hyperactivated glycolysis is a metabolic hallmark of most cancer cells. Although sporadic information has revealed that glycolytic metabolites possess nonmetabolic functions as signaling molecules, how these metabolites interact with and functionally regulate their binding targets remains largely elusive. Here, we introduce a target-responsive accessibility profiling (TRAP) approach that measures changes in ligand binding-induced accessibility for target identification by globally labeling reactive proteinaceous lysines. With TRAP, we mapped 913 responsive target candidates and 2,487 interactions for 10 major glycolytic metabolites in a model cancer cell line. The wide targetome depicted by TRAP unveils diverse regulatory modalities of glycolytic metabolites, and these modalities involve direct perturbation of enzymes in carbohydrate metabolism, intervention of an orphan transcriptional protein’s activity and modulation of targetome-level acetylation. These results further our knowledge of how glycolysis orchestrates signaling pathways in cancer cells to support their survival, and inspire exploitation of the glycolytic targetome for cancer therapy.
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Data availability
Reprocessed Meltome datasets were accessed with the identifier PXD011929, reprocessed LiP-Quant dataset was accessed with the identifier PXD015446 and our data can be accessed with the identifier IPX0002602000/PXD022568 through the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org). RNA-seq data are stored in the NCBI GEO repository under accession number GSE225738. Source data are provided with this paper.
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Acknowledgements
This research was supported by the National Natural Science Foundation of China (grant 81930109 to H.H., grant 82173783 to H.Y.), the Natural Science Foundation of Jiangsu Province (BK20220088), the National Key Research and Development Program of China (2021YFA1301300), the Fundamental Research Funds for the Central Universities (2632022YC03), the Overseas Expertise Introduction Project for Discipline Innovation (G20582017001) and the Sanming Project of Medicine in Shenzhen (SZSM201801060). We thank Y. Xiao from China Pharmaceutical University, Q. Yu from Harvard University, B. Shan and W. Li from PEAKS Studio for useful discussions. We also acknowledge N. Wang in the Cellular and Molecular Biology Center of China Pharmaceutical University and W. Jiang in the State Key Laboratory of Natural Medicines of China Pharmaceutical University for their technical support.
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H. Hao, H.Y. and G.W. conceived the project. Y.T., N.W., H.Z., C.S., H.Y. and H. Hao designed the experiments. Y.T., N.W., H.Z., H.Y. and M.D. performed the proteomics experiments. Y.T., H.Z., C.S. and C.L. performed the flow cytometry and western blotting experiments. Q.B. performed the SPR experiments. K.Z. and S.C. carried out protein site mutation and purification experiments. H. Hu conducted the conservation analysis. N.W., Y.T., H.S., H.Y. and H. Hao analyzed the experimental data. N.W., H.Y. and H. Hao wrote the paper with input from coauthors.
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Extended data
Extended Data Fig. 1 Benchmarking the TRAP approach in probing ligand-target interactions using RNase and PKM2.
(a) Docking analysis of RNase with its ligand CDP (PDB: 1ROB). (b) Native MS showing CDP and CTP bound to RNase at different affinities. (c) Microscale thermophoresis (MST) showing CTP possessed stronger affinity to RNase than CDP. The experiment was conducted once. (d) Time-resolved intact MS analysis showing impeded mass shift of TRAP-labeled RNase in response to CDP/CTP binding (n indicates the number of TRAP-labeled lysines on RNase). (e) Summarized accessibility changes of lysines (Rtreated/control) in RNase in response to CDP/CTP binding based on quantitative analysis of labeled lysine-containing peptides via TRAP. (f) Crystal structure of FBP (red, sphere)-induced PKM2 tetramerization (grey, cartoon) by an allosteric mechanism (PDB: 4B2D). The measured minimal Euclidean distances suggested that the PKM2-K422 residue (blue, stick) is distant from both FBP and pyruvate (in dashed lines). (g) Summarized accessibility changes of lysines (Rtreated/control) in human recombinant PKM2 in response to FBP incubation based on quantitative analysis of labeled lysine-containing peptides via TRAP. For (e) and (g), data represent the mean ± SEM (n=3 biologically independent samples) and P values were determined using an unpaired two-tailed Student’s t-test.
Extended Data Fig. 2 TRAP identified PKM2 as the target of TEPP-46 and pinpointed the binding site.
(a) Crystal structure suggesting the binding site of TEPP-46 (red, sphere) as PKM2-K305 (PDB: 3U2Z). The TRAP-assigned TRP bearing K305 was colored in blue. (b) Correlation analysis between SASA and labeling occupancy of lysine residues of PKM2 without (left panel) and with TEPP-46 (right panel). The Pearson’s correlation coefficients (r) and statistical significance of correlation (P) determined by unpaired two-tailed Student’s t-test are shown. In agreement with the decreased SASA, labeling occupancy of PKM2-K305 (in red), the binding site of TEPP-46, was also markedly reduced following TEPP-46 incubation. Specifically, labeling occupancy of each K was estimated by calculating the ratio between abundance of the peptides bearing this labeled K residue and summed abundance of the labeled K-containing peptides as well as those carrying this unlabeled K residue. (c) TRAP identified the labeled K305 and K311-bearing TRPs in human recombinant PKM2, both of which signified markedly decreased accessibility at K305/K311 following TEPP-46 incubation. RTEPP-46/control were calculated based on n=3 biologically independent samples, while representative EICs of the TRPs and the non-TRPs bearing K115/K188 are shown. (d) Summarized accessibility changes of lysines (Rtreated/control) using data in (c). (e) Rtreated/control of the labeled K305-containing TRP in E. coli lysates following TEPP-46 treatment (n=5 biologically independent samples). (f) Dose-responsive accessibility change curves for TEPP-46’s target candidates that were assigned by single-dose TRAP experiment shown in Fig. 1h (the bona fide target PKM2 excepted). The experiment was conducted once. For (d) and (e), data represent the mean ± SEM and P values were determined using an unpaired two-tailed Student’s t-test.
Extended Data Fig. 3 TRAP complements thermal stability-based target discovery approaches.
(a) Analysis of protein melting behaviors using the human HEK293T cell meltome data (PXD011929) identified five clusters as shown here and in Fig. 2a. (b) Nonmelters displaying resistance to thermal denaturation were identified in the meltome data of HaCaT, HepG2 and colon cancer spheroids cells (PXD011929). (c) GO BP analysis of the nonmelters shown in (b) using a modified Fisher’s Exact test from DAVID bioinformatics website. (d) Dose-responsive TRAP detected dose-dependent increased abundance of the TRPtype C of PSMB1-K164, implying dose-dependent decreased accessibility at K164 following bortezomib incubation. The experiment was conducted once. (e) Dose-responsive TRAP curves for bortezomib’s target candidates that were assigned by single-dose TRAP experiment shown in Fig. 2f (the bona fide target PSMB1 excepted). The experiment was conducted once.
Extended Data Fig. 4 TRAP complements proteolytic stability-based target discovery approaches.
(a) FT% distribution plots of the re-analyzed publicly available LiP-Quant proteome datasets (PXD015446). The numbers of the identified proteins were listed as n and suggested good proteome coverage. (b) Crystal structures of human ATP1A1 in the E1 (PDB: 7E1Z) and E2 states (PDB: 7E20). The identified TRPtype A bearing K91 was colored in red. (c) TRAP analysis identified the labeled K91-bearing TRPtype A spanning D75-R94 of ATP1A1. Its Rtreated/control showed dose-dependent response to digoxin incubation. Data represent the mean ± SEM (n=4 biologically independent samples) and P values were determined using an unpaired two-tailed Student’s t-test. (d) Illustrated protein coverage of ATP1A1 (PDB: 7E1Z) detected by TRAP and LiP. Only labeled lysine-bearing TRPtype A and LiP-produced HT peptides were used for sequence mapping.
Extended Data Fig. 5 Characterizing the TRAP-assigned glycolytic targetome using the multiplexed-TRAP data.
(a) Wide TRAP-labeling coverage of lysines based on analysis of the second batch of the multiplexed-TRAP data. (b-c) Chemical accessibility of proteinaceous lysines assessed by the labeled fraction of lysine residues for each quantified protein using the first (b) and second (c) batches of the multiplexed-TRAP data. (d) Analysis of TRAP labeling preference for high-order structures using the second batch of the multiplexed-TRAP data. (e) Summary of the numbers of glycolytic metabolite-protein interactions detected by TRAP. (f-g) Box plots (center lines mark the median, box borders represent the first and third quartiles, and the whiskers indicate the minimum and maximum values) of sequence coverage (f) and the number of detected unique peptides (g) for known glycolytic targets (retrieved from BRENDA, species: human) that can and cannot be identified by TRAP (unpaired two-tailed Student’s t-test).
Extended Data Fig. 6 Functional assessment and validation of the identified glycolytic metabolite-target interactions belonging to the carbohydrate metabolism pathway.
(a) GO MF analysis of the TRAP-identified glycolytic targetome showing enrichment in proteins ascribed to catalytic activity. (b) KEGG pathway annotation summarized the enriched pathways for the targets ascribed to catalytic activity. (c) Illustration of how the boundary of active site is defined using the multiplexed-TRAP data. The minimal Euclidean distances between the TRPs of the TRAP-identified targets that use the assayed metabolites as substrates and the corresponding active site (retrievable from PDB) were measured, and the resultant median of the collected distances was used to represent the active site boundary that can be probed by TRAP. (d) Summarized Rtreated/control values of the TRPs in PKM2 via the multiplexed-TRAP analysis of HCT116 cell lysates following FBP, F6P and G6P incubation, respectively. Of note, the letter before K denotes the type of the classified TRPs. (e) Relative (Rel.) PKM2 activity at different FBP concentrations normalized to the activity without FBP. (f) TRAP analysis delivering the Rtreated/control of the TRPtype B carrying PKM2-K433 following 3PG incubation. (g) DrugBank and non-DrugBank fractions of the quantified proteome (n=4778) vs. the TRAP-assigned glycolytic targetome (n=913) using the multiplexed-TRAP data. For (d, e, f), data represent the mean ± SEM (n=3 biologically independent samples). For (d, f), P values were determined using an unpaired two-tailed Student’s t-test.
Extended Data Fig. 7 Functional and structural characterization of the lactate-TRIM28 interaction.
(a) Gene expression profile of TRIM28 across given cancer types and paired normal tissues retrieved from the TCGA and the GTEx projects were plotted using GEPIA. (b) GEPIA-based analysis implying that high TRIM28 gene expression level is unfavored for patients’ survival for the examined cancer types using Log-rank test (median cutoff). (c) Summarized Rtreated/control values of the TRPs assigned for lactate via the LFQ-TRAP analysis of human recombinant TRIM28 (upper panel, all peptides shown here are TRPType A candidates) and the multiplexed-TRAP analysis of HCT116 cell lysates (bottom panel, the letter before K denotes the type of the classified TRPs). Data represent the mean ± SEM (n=3 biologically independent samples) and P values were determined using an unpaired two-tailed Student’s t-test.
Extended Data Fig. 8 Glycolytic metabolites binding regulated targetome acetylation.
(a) Fraction of lysines in quantified peptides vs. lysines in TRPs of the glycolytic targetome based on PTM annotation with iPTMnet. (b) Percentage of lysine acetylation in non-TRPs vs. TRPs retrieved from the same glycolytic target (n=913). Data represent the mean ± SEM and P value was determined by a paired, two-tailed Student’s t-test. (c) GO analysis showing diverse subcellular locations for the fraction of TRAP-assigned glycolytic targets that have been assigned as acetylation carriers by iPTMnet. The subcellular distribution pattern resembles that of the whole glycolytic targetome. (d) Distribution pattern of MFs summarized for the whole glycolytic targetome vs. MFs of the glycolytic targetome that have been documented as acetylation carriers by iPTMnet. (e) Number of acetylated lysines in TRPs of each assayed glycolytic metabolite based on iPTMnet.
Extended Data Fig. 9 Validation of ENO1 as the binding target of G3P.
(a) Summarized Rtreated/control values of the TRPs in ENO1 assigned for G3P using the multiplexed-TRAP data. Of note, the letter before K denotes the Type A/B/C of TRPs. Data represent the mean ± SEM (n=3 biologically independent samples) and P values were determined using an unpaired two-tailed Student’s t-test. (b) Thermal shift assay validating the engagement of G3P (500 μM) with ENO1 using HCT116 cell lysates. Experiments were repeated (n=3 biologically independent samples) with one representative sample shown. (c) Thermal shift assay showing G3P-mediated stabilization of ENO1 using HCT116 cell lysates. Experiments were repeated (n=2 biologically independent samples) with one representative sample shown. (d) Volcano plot of the TRPs of G3P (500 μM) assigned by TRAP analysis of the human recombinant ENO1 (n=3 biologically independent samples). TRPs (RG3P/control >1.5 or <0.67, p <0.05 by unpaired two-sided Student’s t-test) were determined and highlighted in red. (e) SPR analysis showing weakened affinity of G3P to the ENO1 carrying K330E point mutation (Mutant-ENO1). The experiment was conducted once.
Extended Data Fig. 10 Metabolomic and immunoblotting analysis verified the ability of pyruvate in entering HCT116 cells and rescuing TSA-induced apoptosis.
(a) EICs of intracellular pyruvate in HCT116 cells without and with pyruvate administration for 24 hr (n=3 biologically independent samples). (b) Relative ion abundance of intracellular pyruvate using data in (a). Data represent the mean ± SEM (n=3 biological samples) and P value was determined using an unpaired two-tailed Student’s t-test. (c) Gating strategy to sort TSA-induced apoptotic HCT116 cells without and with pyruvate pretreatment as specified in Fig. 6g. (d) Representative immunoblots of the apoptotic protein markers, including cleaved PARP and cleaved caspase-9, in HCT116 cells treated as specified in Fig. 6g. β-Tubulin was used as the loading control. Statistical analyses of the band intensities of the protein markers are shown in the bottom panel, where data represent the mean ± SEM (n=3 independent experiments) and P values were determined using ordinary one-way ANOVA with Tukey’s multiple comparisons test.
Supplementary information
Supplementary Dataset 1
Analysis of LiP-resisting proteins by assessing FT% from four publicly available LiP-proteome datasets.
Supplementary Dataset 2
Summary of glycolytic targetome and TRPs assigned by TRAP in HCT116 cells.
Supplementary Dataset 3
Summarized interactions of the known and quantified glycolytic metabolites-enzymatic targets as retrieved from BRENDA.
Supplementary Dataset 4
KEGG pathway analysis of the TRAP-assigned glycolytic targetome with catalytic activity.
Supplementary Dataset 5
Summary of the minimal Euclidean distances measured between the detected TRPs of enzymatic targets that use the examined metabolites as substrates and their active sites.
Supplementary Dataset 6
RNA-seq analysis of TRIM28-dependent gene expression changes in response to lactate treatment in HCT116 cells.
Source data
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Statistical source data.
Source Data Fig. 2
Statistical source data.
Source Data Fig. 6
Unprocessed western blots.
Source Data Extended Data Fig. 10
Unprocessed western blots.
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Tian, Y., Wan, N., Zhang, H. et al. Chemoproteomic mapping of the glycolytic targetome in cancer cells. Nat Chem Biol 19, 1480–1491 (2023). https://doi.org/10.1038/s41589-023-01355-w
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DOI: https://doi.org/10.1038/s41589-023-01355-w
