Metallomics Reviews
Proteome-scale mapping of iron-binding proteins in bread wheat: a translational review for microbial metallomics
What was reviewed and who was studied
This is an original computational study of the bread wheat (Triticum aestivum) proteome that identifies and classifies putative iron-binding proteins. The dataset comprised 100,344 proteins retrieved from Ensembl Plants; no human/animal cohorts were involved. The primary “matrix” is the in-silico wheat proteome; there were no biological specimens. Sequential and structural screening (MetalloPred → Phyre2 homology modeling → MIB metal-binding site prediction), interaction visualization (Ligand Explorer), coordination analysis, and functional localization/annotation were applied in a cross-sectional, observational design.
Major findings
From 100,344 proteins, 602 met a stringent MetalloPred threshold; 196 were structurally modeled; 130 high-integrity models were retained.
| Category | Result |
|---|---|
| Proteins screened | 100,344 total proteins examined |
| Passed initial iron-binding screen (MetalloPred) | 602 proteins |
| Structurally modeled | 196 proteins |
| High-integrity structural models retained | 130 proteins |
| Predicted Fe²⁺ binders | 129 proteins |
| Predicted Fe³⁺ binders | 126 proteins |
| Predicted to bind both Fe²⁺ and Fe³⁺ | 125 proteins |
| Main liganding residues | Glutamate (Glu), Histidine (His), Aspartate (Asp), Cysteine (Cys) |
| Fe²⁺ coordination counts | Free 33; Deviated 29; Octahedral 6; Square planar 6; Tetrahedral 5; Trigonal planar 3; Trigonal bipyramidal 3 |
| Fe³⁺ coordination counts | Free 36; Deviated 36; Tetrahedral 10; Square planar 7; Trigonal bipyramidal 3; Trigonal planar 1 |
| Predicted subcellular localization | Cytoplasm 44%; Nucleus 35%; Chloroplast 8%; Mitochondria 7% |
| Functional classes represented | Enzymes (multiple EC groups), gene regulation/expression, signaling, transport/ion transfer (incl. Fe–S ferredoxins), storage (ferritin-like) |
A large wheat proteome screen narrowed 100k+ proteins to 130 high-quality iron-binding candidates. Most predicted sites use Glu, His, Asp, and Cys, and many proteins can bind both Fe²⁺ and Fe³⁺. Coordination shapes vary, with many “free/deviated” sites and smaller sets of classic geometries. Predicted locations skew to cytoplasm and nucleus, spanning enzymes, regulators, transporters (including Fe–S), and storage proteins.
Implications for Microbial Metallomics
Iron speciation and coordination defined here map directly onto canonical metal–protein chemistry relevant to microbial physiology and ecology.
| Concept | Implication |
|---|---|
| CHED residues (Cys/His/Glu/Asp) dominate ligation | Prioritize these residues in microbial metalloprotein motif searches and mutational probes. |
| Dual Fe²⁺/Fe³⁺ binding is common | Incorporate both oxidation states in microbial iron-site predictions and redox-cycling assays. |
| Fe-S cluster proteins identified | Target Fe-S proteome modules when profiling microbial electron transfer and redox sensing. |
| Octahedral/tetrahedral/square-planar motifs observed | Use geometry-aware scoring for microbial metalloprotein annotation and docking. |
| Cytoplasm/nucleus-biased localization (plant) | For microbes, emphasize cytosolic nucleic-acid–binding and catalytic iron proteins in exposure studies. |
| Ferritin-like and transferrin-receptor-like domains cataloged | Extend searches for microbial storage/uptake analogs in diagnostics or nutrient-immunity models. |
Limitations
All evidence is in silico; no experimental metalloproteomics, speciation analytics, or concentration data were reported. Metal identity is limited to Fe²⁺/Fe³⁺ predictions without direct verification; many sites showed “free” or non-ideal coordination. Findings derive from one species and depend on homology templates, modeling quality thresholds, and prediction cutoffs.
Future perspectives
Validate priority candidates experimentally using complementary structural and metallomic assays to confirm oxidation state, stoichiometry, and geometry. Test whether predicted CHED-centered motifs and Fe-S proteins exhibit the inferred activities and localizations. Translate the pipeline to microbial genomes, retaining the same thresholds and geometry checks, to benchmark cross-kingdom conservation of iron-site chemotypes. Expand to time- or condition-specific expression datasets to relate iron-site prevalence to physiological states.
Key takeaways for Researchers and Clinicians
A proteome-wide, model-based screen in bread wheat identified 117–130 high-confidence iron-binding proteins across cytosolic and nuclear compartments. The most informative chemistries were CHED-mediated ligation, frequent dual Fe²⁺/Fe³⁺ binding, and diverse but often non-ideal coordination geometries. The clearest quantitative outputs are counts of oxidation-state affinity and geometry classes plus localization proportions. Methodologically, a stringent cascade (sequence → structure → site prediction → geometry check) is feasible and portable. For microbial metallomics, this offers a geometry- and residue-aware blueprint to annotate iron sites that affect redox metabolism, nutrient acquisition, and potential diagnostic targets.
Citation
Verma SK, Sharma A, Sandhu P, Choudhary N, Sharma S, Acharya V, Akhter Y. Proteome scale identification, classification and structural analysis of iron-binding proteins in bread wheat. Journal of Inorganic Biochemistry. 2017;170:63-74. doi:10.1016/j.jinorgbio.2017.02.012