Heme Regulatory Motifs in Heme Oxygenase-2 Form a Thiol/Disulfide Redox Switch That Responds to the Cellular Redox State

Heme oxygenase (HO) catalyzes the rate-limiting step in heme catabolism to generate CO, biliverdin, and free iron. Two isoforms of HO have been identified in mammals: inducible HO-1 and constitutively expressed HO-2. HO-1 and HO-2 share similar physical and kinetic properties but have different physiological roles and tissue distributions. Unlike HO-1, which lacks cysteine residues, HO-2 contains three Cys-Pro signatures, known as heme regulatory motifs (HRMs), which are known to control processes related to iron and oxidative metabolism in organisms from bacteria to humans. In HO-2, the C-terminal HRMs constitute a thiol/disulfide redox switch that regulates affinity of the enzyme for heme (Yi, L., and Ragsdale, S. W. (2007) J. Biol. Chem. 282, 20156–21067). Here, we demonstrate that the thiol/disulfide switch in human HO-2 is physiologically relevant. Its redox potential was measured to be −200 mV, which is near the ambient intracellular redox potential. We expressed HO-2 in bacterial and human cells and measured the redox state of the C-terminal HRMs in growing cells by thiol-trapping experiments using the isotope-coded affinity tag technique. Under normal growth conditions, the HRMs are 60–70% reduced, whereas oxidative stress conditions convert most (86–89%) of the HRMs to the disulfide state. Treatment with reductants converts the HRMs largely (81–87%) to the reduced dithiol state. Thus, the thiol/disulfide switch in HO-2 responds to cellular oxidative stress and reductive conditions, representing a paradigm for how HRMs can integrate heme homeostasis with CO signaling and redox regulation of cellular metabolism.Heme oxygenase (HO³ ; EC 1.14.99.3) catalyzes the O₂- and NADPH-dependent conversion of heme to biliverdin, carbon monoxide (CO), and iron in a reaction that is coupled to cytochrome P450 reductase. Then, biliverdin reductase catalyzes the NADPH-dependent reduction of biliverdin to the antioxidant bilirubin. Several recent reviews on HO (1–5) and biliverdin reductase (6) are available. HO is present in organisms from bacteria to eukaryotes and, as the only known enzyme that can degrade heme, plays a critical role in heme and iron homeostasis.There are two major HO isoforms in mammals: inducible HO-1, which is ancient and widely distributed among organisms from bacteria to man, and constitutively expressed HO-2, which emerged 250 million years ago with the amniotes (7). HO-1 is found in most tissues and is highly expressed in spleen and liver (8). Conversely, HO-2 has a narrow tissue distribution, exhibiting high expression levels in the brain, testes, and carotid body (8, 9). Both HO-1 and HO-2 catalyze the NADPH- and cytochrome P450 reductase-dependent degradation of heme to CO, iron, and biliverdin, which is quickly reduced to bilirubin in the presence of biliverdin reductase (10). Controlling cellular heme concentrations is crucial because heme is required as a prosthetic group by regulatory and redox proteins, yet concentrations higher than 1 μm free heme are toxic (11). Thus, as the only mammalian proteins known to degrade heme, HOs play a key role in cellular heme homeostasis; furthermore, in vitro and in vivo studies of cellular and tissue injuries, such as oxidative stress and hemin-induced cytotoxicity, indicate that HO is cytoprotective (9).HO-1 and HO-2 share high sequence and three-dimensional structural homology in their core domains (12, 13); however, their sequences diverge near their C termini, in which HO-2 contains two conserved heme regulatory motifs (HRMs), involving Cys²⁶⁵ in HRM1 and Cys²⁸² in HRM2⁴ (12, 14) (Fig. 1). It was shown recently that the HRMs in HO-2 do not bind heme per se but instead form a reversible thiol/disulfide redox switch that indirectly regulates the affinity of HO-2 for heme (14). However, for this redox switch to have any physiological consequence, the midpoint redox potential of the thiol/disulfide couple must be near the ambient intracellular redox potential, estimated to range from −170 to −250 mV (15).Open in a separate windowFIGURE 1.Major structural regions in HO-1 and HO-2. His²⁵ in HO-1 or His⁴⁵ in HO-2 is the heme-binding ligand.The HRM has been proposed to constitute a heme-binding site (16, 17) that regulates key metabolic processes from bacteria to humans. The HRM consists of a conserved Cys-Pro core sequence that is usually flanked at the N terminus by basic amino acids and at the C terminus by a hydrophobic residue. HRM/heme interactions have been proposed to regulate the activity and/or stability of proteins that play central roles in respiration and oxidative damage (18, 19), coordination of protein synthesis and heme availability in reticulocytes (20, 21), and controlling iron and heme homeostasis (22–26). An important component of the last process is HO-2.Here, we demonstrate that the C-terminal HRMs, which form a thiol/disulfide redox switch between Cys²⁶⁵ and Cys²⁸², exhibit a redox potential that falls well within the ambient cellular redox potential. By expressing HO-2 in bacterial and human cells and trapping the thiols using the isotope-coded affinity tag (ICAT) technique, it was shown that the redox state of the C-terminal HRMs in growing cells responds to the cellular redox state. The disulfide state is favored under oxidative conditions, and the dithiol state is predominant under reducing conditions. Thus, the HRMs act as a molecular rheostat that responds to the ambient intracellular redox potential and, based on earlier studies (14), controls activity of HO-2 by regulating heme binding to the enzyme.     

Binding Modes of Aromatic Ligands to Mammalian Heme Peroxidases with Associated Functional Implications: CRYSTAL STRUCTURES OF LACTOPEROXIDASE COMPLEXES WITH ACETYLSALICYLIC ACID, SALICYLHYDROXAMIC ACID, AND BENZYLHYDROXAMIC ACID*

The binding and structural studies of bovine lactoperoxidase with three aromatic ligands, acetylsalicylic acid (ASA), salicylhydoxamic acid (SHA), and benzylhydroxamic acid (BHA) show that all the three compounds bind to lactoperoxidase at the substrate binding site on the distal heme side. The binding of ASA occurs without perturbing the position of conserved heme water molecule W-1, whereas both SHA and BHA displace it by the hydroxyl group of their hydroxamic acid moieties. The acetyl group carbonyl oxygen atom of ASA forms a hydrogen bond with W-1, which in turn makes three other hydrogen-bonds, one each with heme iron, His-109 N^ϵ2, and Gln-105 N^ϵ2. In contrast, in the complexes of SHA and BHA, the OH group of hydroxamic acid moiety in both complexes interacts with heme iron directly with Fe-OH distances of 3.0 and 3.2Å respectively. The OH is also hydrogen bonded to His-109 N^ϵ2 and Gln-105N^ϵ2. The plane of benzene ring of ASA is inclined at 70.7° from the plane of heme moiety, whereas the aromatic planes of SHA and BHA are nearly parallel to the heme plane with inclinations of 15.7 and 6.2°, respectively. The mode of ASA binding provides the information about the mechanism of action of aromatic substrates, whereas the binding characteristics of SHA and BHA indicate the mode of inhibitor binding.Lactoperoxidase (LPO)⁴ (EC 1.11.1.7) is a member of the family of glycosylated mammalian heme-containing peroxidase enzymes which also includes myeloperoxidase (MPO), eosinophil peroxidase (EPO), and thyroid peroxidase. These enzymes also show functional similarities to non-homologous plant and fungal peroxidases because they follow a similar scheme of reaction (1–3), but their modes of ligand binding differ considerably. Furthermore, the association of the prosthetic heme group in mammalian peroxidases is through covalent bonds (4–9), whereas covalent linkages are absent in other peroxidases (10–14). Among the four mammalian peroxidases, the prosthetic heme group is linked through three covalent bonds in MPO, whereas in LPO, EPO, and thyroid peroxidase only two covalent linkages are formed. So far the detailed crystal structures of only two mammalian peroxidases, MPO and LPO, are known (15–20). One of the most striking differences between these two mammalian peroxidases is concerned with the basic structural organization in which MPO exists as a covalently linked dimer, whereas LPO is a monomeric protein. At present the fundamental questions pertaining to mammalian heme peroxidases are (i) what distinguishes between the aromatic ligands that one ligand acts as a substrate, whereas the other ligand works as an inhibitor and (ii) how the substrate and inhibitor specificities differ between two enzymes lactoperoxidase and myeloperoxidase.Lactoperoxidase oxidizes inorganic ions, preferentially thiocyanate (SCN⁻), and to a lesser extent, bromide (Br⁻), whereas in the case of myeloperoxidase the chloride (Cl⁻) ion is a preferred substrate (21, 22). The mammalian peroxidases including LPO are also involved in catalyzing the single electron oxidation of various physiologically important organic aromatic substrates including phenols (23, 24), catecholamines, and catechols (25–27) as well as other experimental model compounds such as aromatic amines (28), polychlorinated biphenyls (29), steroid hormones (30–32), and polycyclic aromatic hydrocarbons (33). However, the mode of binding of aromatic ligands and associated functional implications are not yet clearly understood. Surprisingly, the structural data on the complexes of mammalian peroxidases with aromatic ligands are conspicuously lacking. The only available structural report is on the complex of MPO with salicylhydroxamic acid (SHA) (34). Even in this case, the coordinates of this structure are not available for a detailed analysis. In the case of non-homologous plant peroxidases, a few crystal structures of their complexes with aromatic compounds are available (35–38), but their modes of binding are not very similar to those of mammalian peroxidases because the distal ligand binding sites in mammalian and plant peroxidases differ markedly. In this regard it is pertinent to note that the substrate binding site in peroxidases, in general, is observed at the δ-heme edge of the heme moiety on the distal side; in plant peroxidases an additional ligand binding site has also been observed at γ-heme edge (39–41). Unlike those in mammalian peroxidases where the heme moiety is buried deeply in the protein core, in plant peroxidases it is located close to the surface of the protein. Therefore, to characterize the mode of binding of the aromatic substrates and aromatic inhibitors and also for defining the subsites in the substrate binding site, we have determined the crystal structures of three complexes of bovine lactoperoxidase with aromatic ligands, acetylsalicylic acid (ASA), SHA, and benzylhydroxamic acid (BHA). Acetylsalicylic acid can be oxidized by lactoperoxidase to ASA free radical (42), whereas both salicylhydroxamic acid and benzylhydroxamic acid act as potent inhibitors of mammalian peroxidases (43–47). The determination of binding characteristics of these compounds having different actions has helped in establishing the relationship between the modes of binding and their potential actions as the substrates and inhibitors. To the best of our knowledge, this is the first structural report on the modes of binding of three aromatic ligands, ASA, SHA, and BHA, to LPO as well as the first structural study of the complexes of any mammalian peroxidase with ASA and BHA. These studies have shown that ASA, SHA, and BHA bind to LPO at the substrate binding site on the distal side. The SHA and BHA directly interact with the heme iron, whereas ASA interacts through the heme water molecule, which in turn is hydrogen-bonded to the heme iron. These studies have provided a greater insight into the mechanisms of substrate and inhibitor binding in the two mammalian peroxidases.     

Analysis of Free Energy Signals Arising from Nucleotide Hybridization Between rRNA and mRNA Sequences during Translation in Eubacteria

A decoding algorithm is tested that mechanistically models the progressive alignments that arise as the mRNA moves past the rRNA tail during translation elongation. Each of these alignments provides an opportunity for hybridization between the single-stranded, -terminal nucleotides of the 16S rRNA and the spatially accessible window of mRNA sequence, from which a free energy value can be calculated. Using this algorithm we show that a periodic, energetic pattern of frequency 1/3 is revealed. This periodic signal exists in the majority of coding regions of eubacterial genes, but not in the non-coding regions encoding the 16S and 23S rRNAs. Signal analysis reveals that the population of coding regions of each bacterial species has a mean phase that is correlated in a statistically significant way with species () content. These results suggest that the periodic signal could function as a synchronization signal for the maintenance of reading frame and that codon usage provides a mechanism for manipulation of signal phase.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

A Bacillus anthracis S-Layer Homology Protein That Binds Heme and Mediates Heme Delivery to IsdC

The sequestration of iron by mammalian hosts represents a significant obstacle to the establishment of a bacterial infection. In response, pathogenic bacteria have evolved mechanisms to acquire iron from host heme. Bacillus anthracis, the causative agent of anthrax, utilizes secreted hemophores to scavenge heme from host hemoglobin, thereby facilitating iron acquisition from extracellular heme pools and delivery to iron-regulated surface determinant (Isd) proteins covalently attached to the cell wall. However, several Gram-positive pathogens, including B. anthracis, contain genes that encode near iron transporter (NEAT) proteins that are genomically distant from the genetically linked Isd locus. NEAT domains are protein modules that partake in several functions related to heme transport, including binding heme and hemoglobin. This finding raises interesting questions concerning the relative role of these NEAT proteins, relative to hemophores and the Isd system, in iron uptake. Here, we present evidence that a B. anthracis S-layer homology (SLH) protein harboring a NEAT domain binds and directionally transfers heme to the Isd system via the cell wall protein IsdC. This finding suggests that the Isd system can receive heme from multiple inputs and may reflect an adaptation of B. anthracis to changing iron reservoirs during an infection. Understanding the mechanism of heme uptake in pathogenic bacteria is important for the development of novel therapeutics to prevent and treat bacterial infections.Pathogenic bacteria need to acquire iron to survive in mammalian hosts (12). However, the host sequesters most iron in the porphyrin heme, and heme itself is often bound to proteins such as hemoglobin (14, 28, 85). Circulating hemoglobin can serve as a source of heme-iron for replicating bacteria in infected hosts, but the precise mechanisms of heme extraction, transport, and assimilation remain unclear (25, 46, 79, 86). An understanding of how bacterial pathogens import heme will lead to the development of new anti-infectives that inhibit heme uptake, thereby preventing or treating infections caused by these bacteria (47, 68).The mechanisms of transport of biological molecules into a bacterial cell are influenced by the compositional, structural, and topological makeup of the cell envelope. Gram-negative bacteria utilize specific proteins to transport heme through the outer membrane, periplasm, and inner membrane (83, 84). Instead of an outer membrane and periplasm, Gram-positive bacteria contain a thick cell wall (59, 60). Proteins covalently anchored to the cell wall provide a functional link between extracellular heme reservoirs and intracellular iron utilization pathways (46). In addition, several Gram-positive and Gram-negative bacterial genera also contain an outermost structure termed the S (surface)-layer (75). The S-layer is a crystalline array of protein that surrounds the bacterial cell and may serve a multitude of functions, including maintenance of cell architecture and protection from host immune components (6, 7, 18, 19, 56). In bacterial pathogens that manifest an S-layer, the “force field” function of this structure raises questions concerning how small molecules such as heme can be successfully passed from the extracellular milieu to cell wall proteins for delivery into the cell cytoplasm.Bacillus anthracis is a Gram-positive, spore-forming bacterium that is the etiological agent of anthrax disease (30, 33). The life cycle of B. anthracis begins after a phagocytosed spore germinates into a vegetative cell inside a mammalian host (2, 40, 69, 78). Virulence determinants produced by the vegetative cells facilitate bacterial growth, dissemination to major organ systems, and eventually host death (76-78). The release of aerosolized spores into areas with large concentrations of people is a serious public health concern (30).Heme acquisition in B. anthracis is mediated by the action of IsdX1 and IsdX2, two extracellular hemophores that extract heme from host hemoglobin and deliver the iron-porphyrin to cell wall-localized IsdC (21, 45). Both IsdX1 and IsdX2 harbor near iron transporter domains (NEATs), a conserved protein module found in Gram-positive bacteria that mediates heme uptake from hemoglobin and contributes to bacterial pathogenesis upon infection (3, 8, 21, 31, 44, 46, 49, 50, 67, 81, 86). Hypothesizing that B. anthracis may contain additional mechanisms for heme transport, we provide evidence that B. anthracis S-layer protein K (BslK), an S-layer homology (SLH) and NEAT protein (32, 43), is surface localized and binds and transfers heme to IsdC in a rapid, contact-dependent manner. These results suggest that the Isd system is not a self-contained conduit for heme trafficking and imply that there is functional cross talk between differentially localized NEAT proteins to promote heme uptake during infection.     

Algorithms for Finding Small Attractors in Boolean Networks

A Boolean network is a model used to study the interactions between different genes in genetic regulatory networks. In this paper, we present several algorithms using gene ordering and feedback vertex sets to identify singleton attractors and small attractors in Boolean networks. We analyze the average case time complexities of some of the proposed algorithms. For instance, it is shown that the outdegree-based ordering algorithm for finding singleton attractors works in time for , which is much faster than the naive time algorithm, where is the number of genes and is the maximum indegree. We performed extensive computational experiments on these algorithms, which resulted in good agreement with theoretical results. In contrast, we give a simple and complete proof for showing that finding an attractor with the shortest period is NP-hard.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

The Wavelet-Based Cluster Analysis for Temporal Gene Expression Data

A variety of high-throughput methods have made it possible to generate detailed temporal expression data for a single gene or large numbers of genes. Common methods for analysis of these large data sets can be problematic. One challenge is the comparison of temporal expression data obtained from different growth conditions where the patterns of expression may be shifted in time. We propose the use of wavelet analysis to transform the data obtained under different growth conditions to permit comparison of expression patterns from experiments that have time shifts or delays. We demonstrate this approach using detailed temporal data for a single bacterial gene obtained under 72 different growth conditions. This general strategy can be applied in the analysis of data sets of thousands of genes under different conditions.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]     

Splitting the BLOSUM Score into Numbers of Biological Significance

Mathematical tools developed in the context of Shannon information theory were used to analyze the meaning of the BLOSUM score, which was split into three components termed as the BLOSUM spectrum (or BLOSpectrum). These relate respectively to the sequence convergence (the stochastic similarity of the two protein sequences), to the background frequency divergence (typicality of the amino acid probability distribution in each sequence), and to the target frequency divergence (compliance of the amino acid variations between the two sequences to the protein model implicit in the BLOCKS database). This treatment sharpens the protein sequence comparison, providing a rationale for the biological significance of the obtained score, and helps to identify weakly related sequences. Moreover, the BLOSpectrum can guide the choice of the most appropriate scoring matrix, tailoring it to the evolutionary divergence associated with the two sequences, or indicate if a compositionally adjusted matrix could perform better.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]     

Multipattern Consensus Regions in Multiple Aligned Protein Sequences and Their Segmentation

Decomposing a biological sequence into its functional regions is an important prerequisite to understand the molecule. Using the multiple alignments of the sequences, we evaluate a segmentation based on the type of statistical variation pattern from each of the aligned sites. To describe such a more general pattern, we introduce multipattern consensus regions as segmented regions based on conserved as well as interdependent patterns. Thus the proposed consensus region considers patterns that are statistically significant and extends a local neighborhood. To show its relevance in protein sequence analysis, a cancer suppressor gene called p53 is examined. The results show significant associations between the detected regions and tendency of mutations, location on the 3D structure, and cancer hereditable factors that can be inferred from human twin studies.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27]     

Sip1, a Novel RS Domain-Containing Protein Essential for Pre-mRNA Splicing

Previous studies have shown that protein-protein interactions among splicing factors may play an important role in pre-mRNA splicing. We report here identification and functional characterization of a new splicing factor, Sip1 (SC35-interacting protein 1). Sip1 was initially identified by virtue of its interaction with SC35, a splicing factor of the SR family. Sip1 interacts with not only several SR proteins but also with U1-70K and U2AF65, proteins associated with 5′ and 3′ splice sites, respectively. The predicted Sip1 sequence contains an arginine-serine-rich (RS) domain but does not have any known RNA-binding motifs, indicating that it is not a member of the SR family. Sip1 also contains a region with weak sequence similarity to the Drosophila splicing regulator suppressor of white apricot (SWAP). An essential role for Sip1 in pre-mRNA splicing was suggested by the observation that anti-Sip1 antibodies depleted splicing activity from HeLa nuclear extract. Purified recombinant Sip1 protein, but not other RS domain-containing proteins such as SC35, ASF/SF2, and U2AF65, restored the splicing activity of the Sip1-immunodepleted extract. Addition of U2AF65 protein further enhanced the splicing reconstitution by the Sip1 protein. Deficiency in the formation of both A and B splicing complexes in the Sip1-depleted nuclear extract indicates an important role of Sip1 in spliceosome assembly. Together, these results demonstrate that Sip1 is a novel RS domain-containing protein required for pre-mRNA splicing and that the functional role of Sip1 in splicing is distinct from those of known RS domain-containing splicing factors.Pre-mRNA splicing takes place in spliceosomes, the large RNA-protein complexes containing pre-mRNA, U1, U2, U4/6, and U5 small nuclear ribonucleoprotein particles (snRNPs), and a large number of accessory protein factors (for reviews, see references 21, 22, 37, 44, and 48). It is increasingly clear that the protein factors are important for pre-mRNA splicing and that studies of these factors are essential for further understanding of molecular mechanisms of pre-mRNA splicing.Most mammalian splicing factors have been identified by biochemical fractionation and purification (3, 15, 19, 31–36, 45, 69–71, 73), by using antibodies recognizing splicing factors (8, 9, 16, 17, 61, 66, 67, 74), and by sequence homology (25, 52, 74).Splicing factors containing arginine-serine-rich (RS) domains have emerged as important players in pre-mRNA splicing. These include members of the SR family, both subunits of U2 auxiliary factor (U2AF), and the U1 snRNP protein U1-70K (for reviews, see references 18, 41, and 59). Drosophila alternative splicing regulators transformer (Tra), transformer 2 (Tra2), and suppressor of white apricot (SWAP) also contain RS domains (20, 40, 42). RS domains in these proteins play important roles in pre-mRNA splicing (7, 71, 75), in nuclear localization of these splicing proteins (23, 40), and in protein-RNA interactions (56, 60, 64). Previous studies by us and others have demonstrated that one mechanism whereby SR proteins function in splicing is to mediate specific protein-protein interactions among spliceosomal components and between general splicing factors and alternative splicing regulators (1, 1a, 6, 10, 27, 63, 74, 77). Such protein-protein interactions may play critical roles in splice site recognition and association (for reviews, see references 4, 18, 37, 41, 47 and 59). Specific interactions among the splicing factors also suggest that it is possible to identify new splicing factors by their interactions with known splicing factors.Here we report identification of a new splicing factor, Sip1, by its interaction with the essential splicing factor SC35. The predicted Sip1 protein sequence contains an RS domain and a region with sequence similarity to the Drosophila splicing regulator, SWAP. We have expressed and purified recombinant Sip1 protein and raised polyclonal antibodies against the recombinant Sip1 protein. The anti-Sip1 antibodies specifically recognize a protein migrating at a molecular mass of approximately 210 kDa in HeLa nuclear extract. The anti-Sip1 antibodies sufficiently deplete Sip1 protein from the nuclear extract, and the Sip1-depleted extract is inactive in pre-mRNA splicing. Addition of recombinant Sip1 protein can partially restore splicing activity to the Sip1-depleted nuclear extract, indicating an essential role of Sip1 in pre-mRNA splicing. Other RS domain-containing proteins, including SC35, ASF/SF2, and U2AF65, cannot substitute for Sip1 in reconstituting splicing activity of the Sip1-depleted nuclear extract. However, addition of U2AF65 further increases splicing activity of Sip1-reconstituted nuclear extract, suggesting that there may be a functional interaction between Sip1 and U2AF65 in nuclear extract.     

Question Processing and Clustering in INDOC: A Biomedical Question Answering System

The exponential growth in the volume of publications in the biomedical domain has made it impossible for an individual to keep pace with the advances. Even though evidence-based medicine has gained wide acceptance, the physicians are unable to access the relevant information in the required time, leaving most of the questions unanswered. This accentuates the need for fast and accurate biomedical question answering systems. In this paper we introduce INDOC—a biomedical question answering system based on novel ideas of indexing and extracting the answer to the questions posed. INDOC displays the results in clusters to help the user arrive the most relevant set of documents quickly. Evaluation was done against the standard OHSUMED test collection. Our system achieves high accuracy and minimizes user effort.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24]