Metalloproteomics: High-Throughput Structural and Functional Annotation of Proteins in Structural Genomics

Modern proteomes contain putative imprints of ancient shifts in trace metal geochemistry

Because of the rise in atmospheric oxygen 2.3 billion years ago (Gya) and the subsequent changes in oceanic redox state over the last 2.3-1 Gya, trace metal bioavailability in marine environments has changed dramatically. Although theorized to have influenced the biological usage of metals leaving discernable genomic signals, a thorough and quantitative test of this hypothesis has been lacking. Using structural bioinformatics and whole-genome sequences, the Fe-, Zn-, Mn-, and Co-binding metallomes of 23 Archaea, 233 Bacteria, and 57 Eukarya were constructed. These metallomes reveal that the overall abundances of these metal-binding structures scale to proteome size as power laws with a unique set of slopes for each Superkingdom of Life. The differences in the power describing the abundances of Fe-, Mn-, Zn-, and Co-binding proteins in the proteomes of Prokaryotes and Eukaryotes are similar to the theorized changes in the abundances of these metals after the oxygenation of oceanic deep waters. This phenomenon suggests that Prokarya and Eukarya evolved in anoxic and oxic environments, respectively, a hypothesis further supported by structures and functions of Fe-binding proteins in each Superkingdom. Also observed is a proliferation in the diversity of Zn-binding protein structures involved in protein-DNA and protein-protein interactions within Eukarya, an event unlikely to occur in either an anoxic or euxinic environment where Zn concentrations would be vanishingly low. We hypothesize that these conserved trends are proteomic imprints of changes in trace metal bioavailability in the ancient ocean that highlight a major evolutionary shift in biological trace metal usage.

Fortuitous structure determination of 'as-isolated' Escherichia coli bacterioferritin in a novel crystal form

Escherichia coli bacterioferritin was serendipitously crystallized in a novel cubic crystal form and its structure could be determined to 2.5 A resolution despite a high degree of merohedral twinning. This is the first report of crystallographic data on 'as-isolated' E. coli bacterioferritin. The ferroxidase active site contains positive difference density consistent with two metal ions that had co-purified with the protein. X-ray fluorescence studies suggest that the metal composition is different from that of previous structures and is a mix of zinc and native iron ions. The ferroxidase-centre configuration displays a similar flexibility as previously noted for other bacterioferritins.

Identification of a novel nonstructural protein, VP9, from white spot syndrome virus: its structure reveals a ferredoxin fold with specific metal binding sites

White spot syndrome virus (WSSV) is a major pathogen in shrimp aquaculture. VP9, a full-length protein of WSSV, encoded by open reading frame wsv230, was identified for the first time in the infected Penaeus monodon shrimp tissues, gill, and stomach as a novel, nonstructural protein by Western blotting, mass spectrometry, and immunoelectron microscopy. Real-time reverse transcription-PCR demonstrated that the transcription of VP9 started from the early to the late stage of WSSV infection as a major mRNA species. The structure of full-length VP9 was determined by both X-ray and nuclear magnetic resonance (NMR) techniques. It is the first structure to be reported for WSSV proteins. The crystal structure of VP9 revealed a ferredoxin fold with divalent metal ion binding sites. Cadmium sulfate was found to be essential for crystallization. The Cd2+ ions were bound between the monomer interfaces of the homodimer. Various divalent metal ions have been titrated against VP9, and their interactions were analyzed using NMR spectroscopy. The titration data indicated that VP9 binds with both Zn2+ and Cd2+. VP9 adopts a similar fold as the DNA binding domain of the papillomavirus E2 protein. Based on our present investigations, we hypothesize that VP9 might be involved in the transcriptional regulation of WSSV, a function similar to that of the E2 protein during papillomavirus infection of the host cells.

Identifying cysteines and histidines in transition-metal-binding sites using support vector machines and neural networks

Accurate predictions of metal-binding sites in proteins by using sequence as the only source of information can significantly help in the prediction of protein structure and function, genome annotation, and in the experimental determination of protein structure. Here, we introduce a method for identifying histidines and cysteines that participate in binding of several transition metals and iron complexes. The method predicts histidines as being in either of two states (free or metal bound) and cysteines in either of three states (free, metal bound, or in disulfide bridges). The method uses only sequence information by utilizing position-specific evolutionary profiles as well as more global descriptors such as protein length and amino acid composition. Our solution is based on a two-stage machine-learning approach. The first stage consists of a support vector machine trained to locally classify the binding state of single histidines and cysteines. The second stage consists of a bidirectional recurrent neural network trained to refine local predictions by taking into account dependencies among residues within the same protein. A simple finite state automaton is employed as a postprocessing in the second stage in order to enforce an even number of disulfide-bonded cysteines. We predict histidines and cysteines in transition-metal-binding sites at 73% precision and 61% recall. We observe significant differences in performance depending on the ligand (histidine or cysteine) and on the metal bound. We also predict cysteines participating in disulfide bridges at 86% precision and 87% recall. Results are compared to those that would be obtained by using expert information as represented by PROSITE motifs and, for disulfide bonds, to state-of-the-art methods.

Understanding the cell in terms of structure and function: insights from structural genomics

Structural genomics programs are only now moving into the large-scale production phase, yet have already produced around 2000 protein structures. Through a widespread if not exclusive emphasis on structural novelty, our knowledge of the protein fold universe is improving rapidly. With this information comes the challenge of structure-based function annotation for the many target proteins about which little or nothing is known. Recent years have therefore seen the emergence of impressively diverse bioinformatics approaches to predict the function of a protein structure. Attention is now turning to means of combining these predictions with information from various other sources.