Iron–sulfur (Fe–S) clusters are ubiquitous metallocofactors involved in redox chemistry, radical generation and gene regulation. Common methods to monitor Fe–S clusters include spectroscopic analysis of purified proteins and autoradiographic visualization of radiolabeled iron distribution in proteomes. Here, we report a chemoproteomic strategy that monitors changes in the reactivity of Fe–S cysteine ligands to inform on Fe–S cluster occupancy. We highlight the utility of this platform in Escherichia coli by (1) demonstrating global disruptions in Fe–S incorporation in cells cultured under iron-depleted conditions, (2) determining Fe–S client proteins reliant on five scaffold, carrier and chaperone proteins within the Isc Fe–S biogenesis pathway and (3) identifying two previously unannotated Fe–S proteins, TrhP and DppD. In summary, the chemoproteomic strategy described herein is a powerful tool that reports on Fe–S cluster incorporation directly within a native proteome, enabling the interrogation of Fe–S biogenesis pathways and the identification of previously uncharacterized Fe–S proteins.
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MS proteomics data for this study have been deposited in ProteomeXchange via the PRIDE partner repository with the dataset identifier PXD026488. Databases used for MS/MS searches against the E. coli proteome were obtained from the UniProtKB at www.uniprot.org. Source data are provided with this paper.
Beinert, H., Holm, R. H. & Münck, E. Iron–sulfur clusters: nature’s modular, multipurpose structures. Science 277, 653–659 (1997).
Hirst, J. Mitochondrial complex I. Annu. Rev. Biochem. 82, 551–575 (2013).
Landgraf, B. J., McCarthy, E. L. & Booker, S. J. Radical S-adenosylmethionine enzymes in human health and disease. Annu. Rev. Biochem. 85, 485–514 (2016).
Vey, J. L. & Drennan, C. L. Structural insights into radical generation by the radical SAM superfamily. Chem. Rev. 111, 2487–2506 (2011).
Boal, A. K. et al. Redox signaling between DNA repair proteins for efficient lesion detection. Proc. Natl Acad. Sci. USA 106, 15237–15242 (2009).
Crack, J. C., Green, J., Thomson, A. J. & Le Brun, N. E. Iron–sulfur cluster sensor-regulators. Curr. Opin. Chem. Biol. 16, 35–44 (2012).
Beinert, H., Kennedy, M. C. & Stout, C. D. Aconitase as iron−sulfur protein, enzyme, and iron-regulatory protein. Chem. Rev. 96, 2335–2374 (1996).
Flint, D. H. & Allen, R. M. Iron−sulfur proteins with non-redox functions. Chem. Rev. 96, 2315–2334 (1996).
Rouault, T. A. Iron–sulfur proteins hiding in plain sight. Nat. Chem. Biol. 11, 442–445 (2015).
Estellon, J., De Choudens, S. O., Smadja, M., Fontecave, M. & Vandenbrouck, Y. An integrative computational model for large-scale identification of metalloproteins in microbial genomes: a focus on iron–sulfur cluster proteins. Metallomics 6, 1913–1930 (2014).
Sofia, H. J., Chen, G., Hetzler, B. G., Reyes-Spindola, J. F. & Miller, N. E. Radical SAM, a novel protein superfamily linking unresolved steps in familiar biosynthetic pathways with radical mechanisms: functional characterization using new analysis and information visualization methods. Nucleic Acids Res. 29, 1097–1106 (2001).
Frey, P. A., Hegeman, A. D. & Ruzicka, F. J. The radical SAM superfamily. Crit. Rev. Biochem. Mol. Biol. 43, 63–88 (2008).
Zhang, Y. et al. Diphthamide biosynthesis requires an organic radical generated by an iron–sulphur enzyme. Nature 465, 891–896 (2010).
Braymer, J. J., Freibert, S. A., Rakwalska-Bange, M. & Lill, R. Mechanistic concepts of iron–sulfur protein biogenesis in biology. Biochim. Biophys. Acta Mol. Cell. Res. 1868, 118863–118690 (2020).
Rouault, T. A. & Maio, N. Biogenesis and functions of mammalian iron–sulfur proteins in the regulation of iron homeostasis and pivotal metabolic pathways. J. Biol. Chem. 292, 12744–12753 (2017).
Yan, L. J., Levine, R. L. & Sohal, R. S. Oxidative damage during aging targets mitochondrial aconitase. Proc. Natl Acad. Sci. USA 94, 11168–11172 (1997).
Broach, R. B. & Jarrett, J. T. Role of the [2Fe–2S]2+ cluster in biotin synthase: mutagenesis of the atypical metal ligand artginine. Biochemistry 45, 14166–14174 (2006).
Rouault, T. A. et al. An iron-sulfur cluster plays a novel regulatory role in the iron-responsive element binding protein. Biometals 5, 131–140 (1992).
Pierik, A. J., Netz, D. J. & Lill, R. Analysis of iron–sulfur protein maturation in eukaryotes. Nat. Protoc. 4, 753–766 (2009).
Stehling, O., Paul, V. D., Bergmann, J., Basu, S. & Lill, R. Biochemical analyses of human iron–sulfur protein biogenesis and of related diseases. Methods Enzymol. 599, 227–263 (2018).
Webert, H. et al. Functional reconstitution of mitochondrial Fe/S cluster synthesis on Isu1 reveals the involvement of ferredoxin. Nat. Commun. 5, 5013 (2014).
Fox, N. G., Chakrabarti, M., McCormick, S. P., Lindahl, P. A. & Barondeau, D. P. The human iron–sulfur assembly complex catalyzes the synthesis of [2Fe–2S] clusters on ISCU2 that can be transferred to acceptor molecules. Biochemistry 54, 3871–3879 (2015).
Weerapana, E. et al. Quantitative reactivity profiling predicts functional cysteines in proteomes. Nature 468, 790–795 (2010).
Weerapana, E., Speers, A. E. & Cravatt, B. F. Tandem orthogonal proteolysis-activity-based protein profiling (TOP-ABPP)—a general method for mapping sites of probe modification in proteomes. Nat. Protoc. 2, 1414–1425 (2007).
Backus, K. M. et al. Proteome-wide covalent ligand discovery in native biological systems. Nature 534, 570–574 (2016).
Deng, X. et al. Proteome-wide quantification and characterization of oxidation-sensitive cysteines in pathogenic bacteria. Cell Host Microbe 13, 358–370 (2013).
Pace, N. J. & Weerapana, E. A competitive chemical-proteomic platform to identify zinc-binding cysteines. ACS Chem. Biol. 9, 258–265 (2014).
Seo, S. W. et al. Deciphering Fur transcriptional regulatory network highlights its complex role beyond iron metabolism in Escherichia coli. Nat. Commun. 5, 4910 (2014).
Vinogradova, E. V. et al. An activity-guided map of electrophile-cysteine interactions in primary human T cells. Cell 182, 1009–1026 (2020).
Boersema, P. J., Raijmakers, R., Lemeer, S., Mohammed, S. & Heck, A. J. Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics. Nat. Protoc. 4, 484–494 (2009).
Abo, M., Li, C. & Weerapana, E. Isotopically-labeled iodoacetamide-alkyne probes for quantitative cysteine-reactivity profiling. Mol. Pharm. 15, 743–749 (2017).
Forouhar, F. et al. Two Fe–S clusters catalyze sulfur insertion by radical-SAM methylthiotransferases. Nat. Chem. Biol. 9, 333–338 (2013).
Becker, A. et al. Iron center, substrate recognition and mechanism of peptide deformylase. Nat. Struct. Biol. 5, 1053–1058 (1998).
Ruzheinikov, S. N. et al. The 1.2 Å structure of a novel quorum-sensing protein, Bacillus subtilis LuxS. J. Mol. Biol. 313, 111–122 (2001).
Yeo, W. S., Lee, J. H., Lee, K. C. & Roe, J. H. IscR acts as an activator in response to oxidative stress for the suf operon encoding Fe–S assembly proteins. Mol. Microbiol. 61, 206–218 (2006).
Burschel, S. et al. Iron–sulfur cluster carrier proteins involved in the assembly of Escherichia coli NADH: ubiquinone oxidoreductase (complex I). Mol. Microbiol. 111, 31–45 (2019).
Maio, N. & Rouault, T. A. Iron–sulfur cluster biogenesis in mammalian cells: new insights into the molecular mechanisms of cluster delivery. Biochim. Biophys. Acta 1853, 1493–1512 (2015).
Puglisi, R. & Pastore, A. The role of chaperones in iron–sulfur cluster biogenesis. FEBS Lett. 592, 4011–4019 (2018).
Silberg, J. J. & Vickery, L. E. Kinetic characterization of the ATPase cycle of the molecular chaperone Hsc66 from Escherichia coli. J. Biol. Chem. 275, 7779–7786 (2000).
Silberg, J. J., Tapley, T. L., Hoff, K. G. & Vickery, L. E. Regulation of the HscA ATPase reaction cycle by the co-chaperone HscB and the iron–sulfur cluster assembly protein IscU. J. Biol. Chem. 279, 53924–53931 (2004).
Bonomi, F., Iametti, S., Morleo, A., Ta, D. & Vickery, L. E. Studies on the mechanism of catalysis of iron–sulfur cluster transfer from IscU [2Fe2S] by HscA/HscB chaperones. Biochemistry 47, 12795–12801 (2008).
Iametti, S., Barbiroli, A. & Bonomi, F. Functional implications of the interaction between HscB and IscU in the biosynthesis of FeS clusters. J. Biol. Inorg. Chem. 20, 1039–1048 (2015).
Maio, N. et al. Cochaperone binding to LYR motifs confers specificity of iron sulfur cluster delivery. Cell Metab. 19, 445–457 (2014).
Maio, N., Kim, K. S., Singh, A. & Rouault, T. A. A single adaptable cochaperone-scaffold complex delivers nascent iron-sulfur clusters to mammalian respiratory chain complexes I–III. Cell Metab. 25, 945–953 (2017).
Hinchliffe, P. & Sazanov, L. A. Organization of iron–sulfur clusters in respiratory complex I. Science 309, 771–774 (2005).
Unden, G. & Bongaerts, J. Alternative respiratory pathways of Escherichia coli: energetics and transcriptional regulation in response to electron acceptors. Biochim. Biophys. Acta 1320, 217–234 (2017).
Sakai, Y., Kimura, S. & Suzuki, T. Dual pathways of tRNA hydroxylation ensure efficient translation by expanding decoding capability. Nat. Commun. 10, 2858 (2019).
Kimura, S., Sakai, Y., Ishiguro, K. & Suzuki, T. Biogenesis and iron-dependency of ribosomal RNA hydroxylation. Nucleic Acids Res. 45, 12974–12986 (2017).
Pelosi, L. et al. Ubiquinone biosynthesis over the entire O2 range: characterization of a conserved O2-independent pathway. mBio 10, e01319-19 (2019).
Locher, K. P. Mechanistic diversity in ATP-binding cassette (ABC) transporters. Nat. Struct. Mol. Biol. 23, 487–493 (2016).
Baba, T. et al. Construction of Escherichia coli K‐12 in‐frame, single‐gene knockout mutants: the Keio collection. Mol. Syst. Biol. 2, 2006.0008 (2006).
Neidhardt, F. C., Bloch, P. L. & Smith, D. F. Culture medium for enterobacteria. J. Bacteriol. 119, 736–747 (1974).
Gibson, D. G. et al. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods 6, 343–345 (2009).
Frazzon, J. & Dean, D. R. Formation of iron–sulfur clusters in bacteria: an emerging field in bioinorganic chemistry. Curr. Opin. Chem. Biol. 7, 166–173 (2003).
Edwards, A. & Haas, W. Multiplexed quantitative proteomics for high-throughput comprehensive proteome comparisons of human cell lines. Methods Mol. Biol. 1394, 1–13 (2016).
Eng, J. K., McCormack, A. L. & Yates, J. R. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom. 5, 976–989 (1994).
Tabb, D. L., McDonald, W. H. & Yates, J. R. DTASelect and Contrast: tools for assembling and comparing protein identifications from shotgun proteomics. J. Proteome Res. 1, 21–26 (2002).
Käll, L., Canterbury, J. D., Weston, J., Noble, W. S. & MacCoss, M. J. Semi-supervised learning for peptide identification from shotgun proteomics datasets. Nat. Methods 4, 923–925 (2007).
Qian, Y. et al. An isotopically tagged azobenzene-based cleavable linker for quantitative proteomics. ChemBioChem 14, 1410–1414 (2013).
Bak, D. W., Pizzagalli, M. D. & Weerapana, E. Identifying functional cysteine residues in the mitochondria. ACS Chem. Biol. 12, 947–957 (2017).
We thank all members of the E.W. laboratory for discussions and feedback. This work was supported by NIH grant R35GM134964 to E.W.
The authors declare no competing interests.
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Extended Data Fig. 1 A functional catalogue of the E. coli Fe–S proteome.
The 144 members of the E. coli Fe-S proteome categorized by cluster function (see Supplementary Dataset 1). General Fe-S proteins/complexes (blue) are represented as cartoon diagrams displaying the approximate orientation of all (metallo)cofactors, with a list of individual Fe-S family members presented in the associated green boxes. Abbreviations: XDH, xanthine dehydrogenase; DMSO, dimethyl sulfoxide reductase; SDH, succinate dehydrogenase; FRD, fumarate reductase; GltS, glutamate synthase; NiFe, dinuclear nickel-iron center; SAM, S-adenosylmethionine; Moco, molybdenum cofactor.
Extended Data Fig. 2 Cysteine labeling and protein abundance changes in the E. coli Fe-S proteome upon iron-depletion.
a, b, Intracellular (a) iron and (b) zinc concentration determined by ICP-OES for E. coli grown under iron-replete (control) (gray) or iron-depleted (green) conditions. Significance is calculated as *** p < 0.005 (p = 2.2E-05), paired t-test (two-tailed) from n = 3 biological replicates. Error bars represent the standard error of the mean. c, Reductive dimethylation (ReDiMe) proteomic platform employed to measure protein abundance changes upon growth of E. coli under iron-depletion conditions. d, IsoTOP-ABPP proteomic platform employed to measure cysteine labeling changes upon growth of E. coli under iron-depletion conditions. e, Waterfall plot of log2 L/H ratio (RP) changes for all quantified proteins from an iron-depleted E. coli proteome (see Supplementary Dataset 2). Proteins with RP>|0.5| are highlighted in red. f, Gene-ontology analysis of processes enriched in proteins with RP>0.5. Processes involved in iron import and homeostasis are highlighted in red. g, Pie chart analysis of the number of quantified Fe-S proteins with RP<−0.5 (red), RP ~ 0.0 (gray), and RP>0.5 (green).
Extended Data Fig. 3 Cysteine reactivity under iron-depletion is independent of lysate preparation and IA-alkyne labeling conditions.
a, Two-dimensional proteomic dataset for the E. coli proteome grown under iron-replete (control) conditions (see Supplementary Dataset 3). All quantified cysteine residues are plotted in the main graph (annotated Fe-S cluster cysteine ligands - green circles, non-annotated cysteine residues - light gray small circles). Inset to right: cysteine residues with no protein abundance data (annotated Fe-S cluster cysteine ligands - green circles, non-annotated cysteine residues - light gray small circles). Inset below: proteins with no cysteine reactivity data (annotated Fe-S protein - red circles, non-annotated proteins - light gray small). b,c, Comparison plot of cysteine reactivity ratios (iron-depleted versus iron-replete) for quantified Fe-S ligands (green circles) from lysates IA-alkyne labeled under standard aerobic (x-axis) versus (b) anaerobic or (c) reducing conditions (y-axis) (see Supplementary Dataset 2).
Extended Data Fig. 4 Cysteine reactivity changes for the ligands of the two Fe-S clusters of biotin synthase.
a, Rc values for Fe-S cysteine ligands on the Fe-S protein, BioB. b, Crystal structure of E. coli BioB with clusters and cysteine residues highlighted (Insets: AdoMet radical [4Fe-4S] cluster – green and auxiliary [4Fe-4S] cluster – orange).
Extended Data Fig. 5 suf operon expression in E. coli isc genetic deletion strains.
a, Structural organization of the E. coli isc and suf operons. b, Proposed model of suf operon function and regulation by the IscU client protein and transcription factor, IscR. c, Protein abundance changes for scaffold complex proteins from the suf operon across all experimental growth conditions and deletion strains.
Extended Data Fig. 6 Reactivity profile of cysteine residues involved in Fe-S ligation.
a, Proteomic workflow for measuring the cysteine reactivity of Fe-S cluster ligands in an iron-depleted E. coli proteome labeled with 100 µM IA-Light or 10 µM IA-Heavy. b, Cysteine reactivity curve for all quantified cysteine residues (light gray) from an iron-depleted E. coli proteome (see Supplementary Dataset 9). Fe-S cluster cysteine ligands are highlighted (green circles). c,d Violin plot of L/H ratios for unique groups of (c) functional cysteine residues, including Fe-S ligands (red), active site residues (blue), zinc ligands (purple), disulfides (green), and iron ligands (yellow) and (d) Fe-S ligands from Fe-S client proteins (red) and Fe-S scaffold proteins (yellow). The median R value for each functional group of cysteine residues is displayed as a dashed line, while the average R values (red) and number of unique values (black) are indicated for each group.
Extended Data Fig. 7 Biochemical characterization of the putative Fe-S protein DppD.
a, Organization of the dpp and opp operons. b, the protein domain structure of the nucleotide-binding subunits, DppD/F and OppD/F. Conserved cysteine residues in the C-terminal extension (orange) are shown as red lines. c, AlphaFold structural model of DppD (AF-P0AAG0-F1). The four conserved c-terminal cysteine residues are highlighted. d, Representative SDS-PAGE analysis of purified E. coli DppD (experiment independently repeated twice). e, Visible color of purified E. coli DppD protein. f, ICP-OES analysis of the iron content of purified E. coli DppD from n = 3 experimental replicates. Error bars represent the standard error of the mean. g, UV-visible absorbance spectrum of as-isolated E. coli DppD.
Supplementary Figs. 1–3 and Tables 1 and 2.
MS-based proteomic data.
Source Data Fig. 1
UV-visible spectroscopy data.
Source Data Fig. 1
Unprocessed SDS–PAGE gels.
Source Data Fig. 6
ICP-OES, UV-visible spectroscopy and EPR spectroscopy data.
Source Data Fig. 6
Unprocessed SDS–PAGE gels.
Source Data Extended Data Fig./Table 2
Source Data Extended Data Fig. 7
ICP-OES and UV-visible spectroscopy data.
Source Data Extended Data Fig. 7
Unprocessed SDS–PAGE gels.
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Bak, D.W., Weerapana, E. Monitoring Fe–S cluster occupancy across the E. coli proteome using chemoproteomics. Nat Chem Biol 19, 356–366 (2023). https://doi.org/10.1038/s41589-022-01227-9