Defining the Structural Basis of Human Plasminogen Binding by Streptococcal Surface Enolase

The flesh-eating bacterium group A Streptococcus (GAS) binds and activates human plasminogen, promoting invasive disease. Streptococcal surface enolase (SEN), a glycolytic pathway enzyme, is an identified plasminogen receptor of GAS. Here we used mass spectrometry (MS) to confirm that GAS SEN is octameric, thereby validating in silico modeling based on the crystal structure of Streptococcus pneumoniae α-enolase. Site-directed mutagenesis of surface-located lysine residues (SEN^{K252 + 255A}, SEN^K304A, SEN^K334A, SEN^K344E, SEN^K435L, and SEN^Δ434–435) was used to examine their roles in maintaining structural integrity, enzymatic function, and plasminogen binding. Structural integrity of the GAS SEN octamer was retained for all mutants except SEN^K344E, as determined by circular dichroism spectroscopy and MS. However, ion mobility MS revealed distinct differences in the stability of several mutant octamers in comparison with wild type. Enzymatic analysis indicated that SEN^K344E had lost α-enolase activity, which was also reduced in SEN^K334A and SEN^Δ434–435. Surface plasmon resonance demonstrated that the capacity to bind human plasminogen was abolished in SEN^{K252 + 255A}, SEN^K435L, and SEN^Δ434–435. The lysine residues at positions 252, 255, 434, and 435 therefore play a concerted role in plasminogen acquisition. This study demonstrates the ability of combining in silico structural modeling with ion mobility-MS validation for undertaking functional studies on complex protein structures.Streptococcus pyogenes (group A Streptococcus, GAS)⁸ is a common bacterial pathogen, causing over 700 million human disease episodes each year (1). These range from serious life-threatening invasive diseases including necrotizing fasciitis and streptococcal toxic shock-like syndrome to non-invasive infections like pharyngitis and pyoderma. Invasive disease, in combination with postinfection immune sequelae including rheumatic heart disease and acute poststreptococcal glomerulonephritis, account for over half a million deaths each year (1). Although a resurgence of GAS invasive infections has occurred in western countries since the mid-1980s, disease burden is much greater in developing countries and indigenous populations of developed nations, where GAS infections are endemic (2–4).GAS is able to bind human plasminogen and activate the captured zymogen to the serine protease plasmin (5–17). The capacity of GAS to do this plays a critical role in virulence and invasive disease initiation (3, 17–19). The plasminogen activation system in humans is an important and highly regulated process that is responsible for breakdown of extracellular matrix components, dissolution of blood clots, and cell migration (20, 21). Plasminogen is a 92-kDa zymogen that circulates in human plasma at a concentration of 2 μm (22). It consists of a binding region of five homologous triple loop kringle domains and an N-terminal serine protease domain that flank the Arg⁵⁶¹–Val⁵⁶² site (23), where it is cleaved by tissue plasminogen activator and urokinase plasminogen activator to yield the active protease plasmin (20, 23). GAS also has the ability to activate human plasminogen by secreting the virulence determinant streptokinase. Streptokinase forms stable complexes with plasminogen or plasmin, both of which exhibit plasmin activity (20, 24). Activation of plasminogen by the plasmin(ogen)-streptokinase complex circumvents regulation by the host plasminogen activation inhibitors, α₂-antiplasmin and α₂-macroglobulin (11, 20). GAS can bind the plasmin(ogen)-streptokinase complex and/or plasmin(ogen) directly via plasmin(ogen) receptors at the bacterial cell surface (6). These receptors include the plasminogen-binding group A streptococcal M-like protein (PAM) (25), the PAM-related protein (19), glyceraldehyde-3-phosphate dehydrogenase (GAPDH; also known as streptococcal plasmin receptor, Plr, or streptococcal surface dehydrogenase) (9, 26), and streptococcal surface enolase (SEN or α-enolase) (27). Interactions with these GAS receptors occurs via lysine-binding sites within the kringle domains of plasminogen (6).In addition to its ability to bind human plasminogen, SEN is primarily the glycolytic enzyme that converts 2-phosphoglycerate to phosphoenolpyruvate (27–29). SEN is abundantly expressed in the cytosol of most bacterial species but has also been identified as a surface-located protein in GAS and other bacteria including pneumococci, despite lacking classical cell surface protein motifs such as a signal sequence, membrane-spanning domain, or cell-wall anchor motif (27, 28, 30, 31). The interaction between SEN and plasminogen is reported to be facilitated by the two C-terminal lysine residues at positions 434 and 435 (27, 32). In contrast, an internal binding motif containing lysines at positions 252 and 255 in the closely related α-enolase of Streptococcus pneumoniae has been shown to play a pivotal role in the acquisition of plasminogen in this bacterial species (33). The octameric pneumococcal α-enolase structure consists of a tetramer of dimers. Hence, potential binding sites could be buried in the interface between subunits. In fact, the crystal structure of S. pneumoniae α-enolase revealed that the two C-terminal lysine residues are significantly less exposed than the internal plasminogen-binding motif (34).In this study, we constructed an in silico model of GAS SEN, based on the pneumococcal octameric α-enolase crystal structure, and validated this model using ion mobility (IM) mass spectrometry (MS). Site-directed mutagenesis followed by structural and functional analyses revealed that Lys³⁴⁴ plays a crucial role in structural integrity and enzymatic function. Furthermore, we demonstrate that the plasminogen-binding motif residues Lys²⁵² and Lys²⁵⁵ and the C-terminal Lys⁴³⁴ and Lys⁴³⁵ residues are located adjacently in the GAS SEN structure and play a concerted role in the binding of human plasminogen.     

Mcl-1 Degradation during Hepatocyte Lipoapoptosis

The mechanisms of free fatty acid-induced lipoapoptosis are incompletely understood. Here we demonstrate that Mcl-1, an anti-apoptotic member of the Bcl-2 family, was rapidly degraded in hepatocytes in response to palmitate and stearate by a proteasome-dependent pathway. Overexpression of a ubiquitin-resistant Mcl-1 mutant in Huh-7 cells attenuated palmitate-mediated Mcl-1 loss and lipoapoptosis; conversely, short hairpin RNA-targeted knockdown of Mcl-1 sensitized these cells to lipoapoptosis. Palmitate-induced Mcl-1 degradation was attenuated by the novel protein kinase C (PKC) inhibitor rottlerin. Of the two human novel PKC isozymes, PKCδ and PKCθ, only activation of PKCθ was observed by phospho-immunoblot analysis. As compared with Jurkat cells, a smaller PKCθ polypeptide and mRNA were expressed in hepatocytes consistent with an alternative splice variant. Short hairpin RNA-mediated knockdown of PKCθ reduced Mcl-1 degradation and lipoapoptosis. Likewise, genetic deletion of Pkcθ also attenuated Mcl-1 degradation and cytotoxicity by palmitate in primary hepatocytes. During treatment with palmitate, rottlerin inhibited phosphorylation of Mcl-1 at Ser¹⁵⁹, a phosphorylation site previously implicated in Mcl-1 turnover. Consistent with these results, an Mcl-1 S159A mutant was resistant to degradation and improved cell survival during palmitate treatment. Collectively, these results implicate PKCθ-dependent destabilization of Mcl-1 as a mechanism contributing to hepatocyte lipoapoptosis.Current evidence suggests that hepatic steatosis is present in up to 30% of the American population (1). A subset of these individuals develop severe hepatic lipotoxicity, a syndrome referred to as NASH² (2), which can progress to cirrhosis and its chronic sequela (3, 4). A major risk factor for hepatic lipotoxicity is insulin resistance (5–7), resulting in excessive lipolysis within peripheral adipose tissue with release of high levels of free fatty acids (FFA) to the circulation. Circulating FFA are taken up by the liver via fatty acid transporter 5 and CD36 (8–10), and the bulk of hepatic neutral fat is derived from re-esterification of circulating FFA (8). Current concepts indicate that FFA, and not their esterified product (triglyceride), mediate hepatic lipotoxicity (11, 12). Elevated serum FFA correlate with liver disease severity (13–15), and therapies that enhance insulin sensitivity ameliorate hepatic lipotoxicity, in part, by decreasing plasma FFA (16). Hepatic FFA also accumulate in experimental steatohepatitis, further supporting a role for these nutrients in hepatic lipotoxicity (17). Saturated FFA are more strongly implicated in hepatic lipotoxicity than unsaturated FFA (18, 19). Saturated FFA induce hepatocyte apoptosis (20, 21), a cardinal feature of nonalcoholic fatty liver disease (22), and serum biomarkers of apoptosis are useful for identifying hepatic lipotoxicity (23). Thus, FFA-mediated lipotoxicity occurs, in part, by apoptosis.Apoptosis is regulated by members of the Bcl-2 protein family (24). These proteins can be categorized into three subsets as follows: the guardians or anti-apoptotic members of this family, which include Bcl-2, A1, Mcl-1, Bcl-x_L, and Bcl-w; the multidomain executioners or proapoptotic members of this family, which include Bax and Bak; and the messengers or biosensors of cell death, which share only the third Bcl-2 homology domain and are referred to as BH3-only proteins. This last group of proteins includes Bid, Bim, Bmf, Puma, Noxa, Hrk, Bad, and Bik. We have previously reported that cytotoxic FFA induce Bim expression by a FoxO3a-dependent mechanism that contributes, in part, to lipoapoptosis by activating Bax (20, 21). However, Bax activation can be held in check by anti-apoptotic members of the Bcl-2 family suggesting their function may also be dysregulated during FFA-mediated cytotoxicity.Bcl-2 is not expressed in hepatocytes at the protein level (25), whereas Bcl-w and Bfl-1/A1 knock-out mice have no liver phenotype (26–28). However, both potent anti-apoptotic proteins Bcl-x_L and Mcl-1 are expressed by hepatocytes and exhibit a liver phenotype in knock-out mice (29, 30), whereas up-regulation of Mcl-1 renders hepatocytes resistant to apoptosis (31–33). It has also been posited that cellular elimination of Mcl-1 is a critical step in certain proapoptotic cascades (34, 35). Mcl-1 is unique among Bcl-2 proteins in that it has a short half-life, 30–120 min in most cell types, due to the presence of two sequences rich in proline, glutamic acid, serine, and threonine, which target the protein for rapid degradation by the proteasome (36). Proteasomal degradation of Mcl-1 is promoted by ubiquitination, which in turn is regulated by various kinase cascades (36). Despite its potential importance, a role for Mcl-1 in regulating hepatocyte FFA-mediated lipoapoptosis remains unexplored.Given that FFA induce insulin resistance (37), the kinases potentially regulating lipoapoptosis are likely those also identified in insulin resistance syndromes, especially the novel PKC isoforms PKCδ and PKCθ (38). The novel PKC isoforms are activated by diacylglycerol, which rises in the presence of FFA (39–41), and diacylglycerol levels are significantly increased in NASH (42). A role for PKCδ in apoptosis has not been described. PKCθ has recently been shown to be activated by endoplasmic reticulum stress in liver cells (43) and lipids in vivo (44, 45). Furthermore, PKCθ has also been implicated in apoptosis of Jurkat cells, neuroblastoma cells, and myeloid leukemia cells (46, 47). However, neither its role in mediating lipoapoptosis nor modulating levels/activity of Bcl-2 proteins has been examined.This study addresses the role of Mcl-1 and PKCθ in FFA-induced lipoapoptosis. We identify a pathway that involves PKCθ-dependent proteasomal degradation of Mcl-1. Using inhibitors of various steps along this pathway, along with Mcl-1 mutants that are resistant to proteasomal degradation or Ser¹⁵⁹ phosphorylation, our studies implicate Mcl-1 degradation via a PKCθ-dependent process as a critical step in lipoapoptosis.     

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]     

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]     

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]     

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]     

Proinsulin and the Genetics of Diabetes Mellitus

Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.     

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]     

Printor, a Novel TorsinA-interacting Protein Implicated in Dystonia Pathogenesis

Early onset generalized dystonia (DYT1) is an autosomal dominant neurological disorder caused by deletion of a single glutamate residue (torsinA ΔE) in the C-terminal region of the AAA⁺ (ATPases associated with a variety of cellular activities) protein torsinA. The pathogenic mechanism by which torsinA ΔE mutation leads to dystonia remains unknown. Here we report the identification and characterization of a 628-amino acid novel protein, printor, that interacts with torsinA. Printor co-distributes with torsinA in multiple brain regions and co-localizes with torsinA in the endoplasmic reticulum. Interestingly, printor selectively binds to the ATP-free form but not to the ATP-bound form of torsinA, supporting a role for printor as a cofactor rather than a substrate of torsinA. The interaction of printor with torsinA is completely abolished by the dystonia-associated torsinA ΔE mutation. Our findings suggest that printor is a new component of the DYT1 pathogenic pathway and provide a potential molecular target for therapeutic intervention in dystonia.Early onset generalized torsion dystonia (DYT1) is the most common and severe form of hereditary dystonia, a movement disorder characterized by involuntary movements and sustained muscle spasms (1). This autosomal dominant disease has childhood onset and its dystonic symptoms are thought to result from neuronal dysfunction rather than neurodegeneration (2, 3). Most DYT1 cases are caused by deletion of a single glutamate residue at positions 302 or 303 (torsinA ΔE) of the 332-amino acid protein torsinA (4). In addition, a different torsinA mutation that deletes amino acids Phe³²³–Tyr³²⁸ (torsinA Δ323–328) was identified in a single family with dystonia (5), although the pathogenic significance of this torsinA mutation is unclear because these patients contain a concomitant mutation in another dystonia-related protein, ϵ-sarcoglycan (6). Recently, genetic association studies have implicated polymorphisms in the torsinA gene as a genetic risk factor in the development of adult-onset idiopathic dystonia (7, 8).TorsinA contains an N-terminal endoplasmic reticulum (ER)³ signal sequence and a 20-amino acid hydrophobic region followed by a conserved AAA⁺ (ATPases associated with a variety of cellular activities) domain (9, 10). Because members of the AAA⁺ family are known to facilitate conformational changes in target proteins (11, 12), it has been proposed that torsinA may function as a molecular chaperone (13, 14). TorsinA is widely expressed in brain and multiple other tissues (15) and is primarily associated with the ER and nuclear envelope (NE) compartments in cells (16–20). TorsinA is believed to mainly reside in the lumen of the ER and NE (17–19) and has been shown to bind lamina-associated polypeptide 1 (LAP1) (21), lumenal domain-like LAP1 (LULL1) (21), and nesprins (22). In addition, recent evidence indicates that a significant pool of torsinA exhibits a topology in which the AAA⁺ domain faces the cytoplasm (20). In support of this topology, torsinA is found in the cytoplasm, neuronal processes, and synaptic terminals (2, 3, 15, 23–26) and has been shown to bind cytosolic proteins snapin (27) and kinesin light chain 1 (20). TorsinA has been proposed to play a role in several cellular processes, including dopaminergic neurotransmission (28–31), NE organization and dynamics (17, 22, 32), and protein trafficking (27, 33). However, the precise biological function of torsinA and its regulation remain unknown.To gain insights into torsinA function, we performed yeast two-hybrid screens to search for torsinA-interacting proteins in the brain. We report here the isolation and characterization of a novel protein named printor (protein interactor of torsinA) that interacts selectively with wild-type (WT) torsinA but not the dystonia-associated torsinA ΔE mutant. Our data suggest that printor may serve as a cofactor of torsinA and provide a new molecular target for understanding and treating dystonia.     

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]