Analysis of Proteins That Rapidly Change Upon Mechanistic/Mammalian Target of Rapamycin Complex 1 (mTORC1) Repression Identifies Parkinson Protein 7 (PARK7) as a Novel Protein Aberrantly Expressed in Tuberous Sclerosis Complex (TSC)

Many biological processes involve the mechanistic/mammalian target of rapamycin complex 1 (mTORC1). Thus, the challenge of deciphering mTORC1-mediated functions during normal and pathological states in the central nervous system is challenging. Because mTORC1 is at the core of translation, we have investigated mTORC1 function in global and regional protein expression. Activation of mTORC1 has been generally regarded to promote translation. Few but recent works have shown that suppression of mTORC1 can also promote local protein synthesis. Moreover, excessive mTORC1 activation during diseased states represses basal and activity-induced protein synthesis. To determine the role of mTORC1 activation in protein expression, we have used an unbiased, large-scale proteomic approach. We provide evidence that a brief repression of mTORC1 activity in vivo by rapamycin has little effect globally, yet leads to a significant remodeling of synaptic proteins, in particular those proteins that reside in the postsynaptic density. We have also found that curtailing the activity of mTORC1 bidirectionally alters the expression of proteins associated with epilepsy, Alzheimer''s disease, and autism spectrum disorder—neurological disorders that exhibit elevated mTORC1 activity. Through a protein–protein interaction network analysis, we have identified common proteins shared among these mTORC1-related diseases. One such protein is Parkinson protein 7, which has been implicated in Parkinson''s disease, yet not associated with epilepsy, Alzheimers disease, or autism spectrum disorder. To verify our finding, we provide evidence that the protein expression of Parkinson protein 7, including new protein synthesis, is sensitive to mTORC1 inhibition. Using a mouse model of tuberous sclerosis complex, a disease that displays both epilepsy and autism spectrum disorder phenotypes and has overactive mTORC1 signaling, we show that Parkinson protein 7 protein is elevated in the dendrites and colocalizes with the postsynaptic marker postsynaptic density-95. Our work offers a comprehensive view of mTORC1 and its role in regulating regional protein expression in normal and diseased states.The mechanistic/mammalian target of rapamycin complex 1 (mTORC1)¹ is a serine/threonine protein kinase that is highly expressed in many cell types (1). In the brain, mTORC1 tightly coordinates different synaptic plasticities — long-term potentiation (LTP) and long-term depression (LTD) — the molecular correlates of learning and memory (2–5). Because mTORC1 is at the core of many synaptic signaling pathways downstream of glutamate and neurotrophin receptors, many hypothesize that dysregulated mTORC1 signaling underlies cognitive deficits observed in several neurodegenerative diseases (3, 6–17). For example, mTORC1 and its downstream targets are hyperactive in human brains diagnosed with Alzheimer''s disease (AD) (18–20). Additionally in animal models of autism spectrum disorder (ASD), altered mTORC1 signaling contributes to the observed synaptic dysfunction and aberrant network connectivity (13, 15, 21–27). Furthermore, epilepsy, which is common in AD and ASD, has enhanced mTORC1 activity (28–32).Phosphorylation of mTORC1, considered the active form, is generally regarded to promote protein synthesis (33). Thus, many theorize that diseases with overactive mTORC1 arise from excessive protein synthesis (14). Emerging data, however, show that suppressing mTORC1 activation can trigger local translation in neurons (34, 35). Pharmacological antagonism of N-methyl-d-aspartate (NMDA) receptors, a subtype of glutamate receptors that lies upstream of mTOR activation, promotes the synthesis of the voltage-gated potassium channel, Kv1.1, in dendrites (34, 35). Consistent with these results, in models of temporal lobe epilepsy there is a reduction in the expression of voltage-gated ion channels including Kv1.1 (30, 31, 36). Interestingly in a model of focal neocortical epilepsy, overexpression of Kv1.1 blocked seizure activity (37). Because both active and inactive mTORC1 permit protein synthesis, we sought to determine the proteins whose expression is altered when mTORC1 phosphorylation is reduced in vivo.Rapamycin is an FDA-approved, immunosuppressive drug that inhibits mTORC1 activity (38). We capitalized on the ability of rapamycin to reduce mTORC1 activity in vivo and the unbiased approach of mass spectrometry to identify changes in protein expression. Herein, we provide evidence that mTORC1 activation bidirectionally regulates protein expression, especially in the PSD where roughly an equal distribution of proteins dynamically appear and disappear. Remarkably, using protein–protein interaction networks facilitated the novel discovery that PARK7, a protein thus far only implicated in Parkinson''s disease, (1) is up-regulated by increased mTORC1 activity, (2) resides in the PSD only when mTORC1 is active, and (3) is aberrantly expressed in a rodent model of TSC, an mTORC1-related disease that has symptoms of epilepsy and autism. Collectively, these data provide the first comprehensive list of proteins whose abundance or subcellular distributions are altered with acute changes in mTORC1 activity in vivo.     

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]     

Neurabin: A Novel Neural Tissue–specific Actin Filament–binding Protein Involved in Neurite Formation

We purified from rat brain a novel actin filament (F-actin)–binding protein of ∼180 kD (p180), which was specifically expressed in neural tissue. We named p180 neurabin (neural tissue–specific F-actin– binding protein). We moreover cloned the cDNA of neurabin from a rat brain cDNA library and characterized native and recombinant proteins. Neurabin was a protein of 1,095 amino acids with a calculated molecular mass of 122,729. Neurabin had one F-actin–binding domain at the NH₂-terminal region, one PSD-95, DlgA, ZO-1–like domain at the middle region, a domain known to interact with transmembrane proteins, and domains predicted to form coiled-coil structures at the COOH-terminal region. Neurabin bound along the sides of F-actin and showed F-actin–cross-linking activity. Immunofluorescence microscopic analysis revealed that neurabin was highly concentrated in the synapse of the developed neurons. Neurabin was also concentrated in the lamellipodia of the growth cone during the development of neurons. Moreover, a study on suppression of endogenous neurabin in primary cultured rat hippocampal neurons by treatment with an antisense oligonucleotide showed that neurabin was involved in the neurite formation. Neurabin is a candidate for key molecules in the synapse formation and function.During the development of the nervous system, the distal tip of the elongating axon—the growth cone—actively migrates toward its target cell in response to the combined actions of attractive and repulsive guidance molecules in the extracellular environment (Garrity and Zipursky, 1995; Keynes and Cook, 1995; Chiba and Keshishian, 1996; Culotti and Kolodkin, 1996; Friedman and O''Leary, 1996; Tessier-Lavigne and Goodman, 1996). When the growth cone contacts with the target cell, it is transformed into the functional presynaptic terminal (Garrity and Zipursky, 1995; Chiba and Kishishian, 1996). The actin cytoskeleton has been shown to play crucial roles in these processes of the synapse formation (Mitchison and Kirschner, 1988; Smith, 1988; Bentley and O''Connor, 1994; Lin et al., 1994; Mackay et al., 1995; Tanaka and Sabry, 1995).In the developing nervous system, the actin cytoskeleton is prominent in two structural domains of the growth cone, filopodia and lamellipodia (Mitchison and Kirschner, 1988; Smith, 1988; Bentley and O''Connor, 1994; Lin et al., 1994; Mackay et al., 1995; Tanaka and Sabry, 1995). In these domains, actin filament (F-actin)¹ assembled at the leading edge are transported into the center of the growth cone and disassembled there. It has been suggested that this retrograde flow of F-actin is crucial for the growth cone motility. Drugs that disrupt F-actin have also been shown to cause the lamellipodial and filopodial collapse and block the ability of neurons to extend the growth cone in the correct direction (Marsh and Letourneau, 1984; Forscher and Smith, 1988; Bentley and Toroian-Raymond, 1986; Chien et al., 1993). These results suggest that the actin cytoskeleton regulates not only the growth cone motility but also the growth cone directionality. Recently, a variety of guidance molecules and their receptors have been identified (Garrity and Zipursky, 1995; Keynes and Cook, 1995; Chiba and Keshishian, 1996; Culotti and Kolodkin, 1996; Friedman and O''Leary, 1996; Tessier-Lavigne and Goodman, 1996). However, which molecules of the actin cytoskeleton are essential for the growth cone motility and directionality is not well understood.When the growth cone contacts with the target cell, the target cell regulates the development of the presynaptic nerve terminal and the formation of the functional synapse (Bowe and Fallon, 1995; Chiba and Keshishian, 1996). In the established nervous system, the presynaptic and postsynaptic membranes get aligned in space and constitute the synaptic junction (Burns and Augustine, 1995; Garner and Kindler, 1996). Electron microscopic studies have revealed the ultrastructural features of the synaptic junction (Burns and Augustine, 1995; Garner and Kindler, 1996). The presynaptic cytoplasm is characterized by synaptic vesicles (SVs). SVs are not distributed uniformly; SVs cluster together in the vicinity of the presynaptic plasma membrane, where F-actin forms a network and is associated with the presynaptic plasma membrane (Hirokawa et al., 1989). Most SVs within the cluster are linked through thin strands to each other, to F-actin, or to both (Hirokawa et al., 1989). A subset of SVs within the cluster are attached by fine filamentous threads to neurotransmitter release zone at the presynaptic plasma membrane (Hirokawa et al., 1989). The presynaptic submembranous cytoskeleton is assumed to be involved in recruiting Ca²⁺ channels and the components of the SV fusion complex, delivering SVs to the neurotransmitter release zone, and keeping them in place (Burns and Augustine, 1995; Garner and Kindler, 1996). At the inner surface of the post-synaptic plasma membrane, there is an electron dense thickening, called postsynaptic density. The postsynaptic density is assumed to be involved in the selective targeting and accumulation of ion channels and receptors (Burns and Augustine, 1995; Garner and Kindler, 1996). It is also assumed that the presynaptic and postsynaptic submembranous cytoskeleton elements are linked to cell adhesion molecules to regulate the synaptic stabilization and plasticity (Fields and Itoh, 1996; Garner and Kindler, 1996). The presynaptic and postsynaptic submembranous cytoskeleton elements are thought to be composed of spectrin/fodrin, ankyrin, α-adducin, and protein 4.1 isoforms and to be linked to F-actin through these cytoskeleton proteins (Garner and Kindler, 1996). However, little is known about which molecules of the submembranous cytoskeleton are essential for the synaptic transmission and/or the synaptic stabilization.To understand the regulation of the actin cytoskeleton during and after the development of the nervous system, it is of crucial importance to identify F-actin–binding proteins implicated in the synapse formation and function. Therefore, we attempted here to isolate neural tissue–specific F-actin–binding proteins. We isolated a novel neural tissue–specific F-actin–binding protein from rat brain, which may be involved in neurite formation, and named it neurabin (neural tissue–specific F-actin–binding protein).     

Septin 11 Is Present in GABAergic Synapses and Plays a Functional Role in the Cytoarchitecture of Neurons and GABAergic Synaptic Connectivity

Mass spectrometry and immunoblot analysis of a rat brain fraction enriched in type-II postsynaptic densities and postsynaptic GABAergic markers showed enrichment in the protein septin 11. Septin 11 is expressed throughout the brain, being particularly high in the spiny branchlets of the Purkinje cells in the molecular layer of cerebellum and in the olfactory bulb. Immunofluorescence of cultured hippocampal neurons showed that 54 ± 4% of the GABAergic synapses and 25 ± 2% of the glutamatergic synapses had colocalizing septin 11 clusters. Similar colocalization numbers were found in the molecular layer of cerebellar sections. In cultured hippocampal neurons, septin 11 clusters were frequently present at the base of dendritic protrusions and at the bifurcation points of the dendritic branches. Electron microscopy immunocytochemistry of the rat brain cerebellum revealed the accumulation of septin 11 at the neck of dendritic spines, at the bifurcation of dendritic branches, and at some GABAergic synapses. Knocking down septin 11 in cultured hippocampal neurons with septin 11 small hairpin RNAs showed (i) reduced dendritic arborization; (ii) decreased density and increased length of dendritic protrusions; and (iii) decreased GABAergic synaptic contacts that these neurons receive. The results indicate that septin 11 plays important roles in the cytoarchitecture of neurons, including dendritic arborization and dendritic spines, and that septin 11 also plays a role in GABAergic synaptic connectivity.We have recently developed a method for the preparation of a brain fraction enriched in GABAergic postsynaptic complex (1). This fraction, insoluble in Triton X-100, was enriched in Gray''s type-II postsynaptic densities (type-II PSDs)² and in the postsynaptic GABAergic markers GABA_A receptors (GABA_ARs) and gephyrin. Here we report that septin 11 is a major component of the type-II PSD fraction.Septins are a family of proteins with GTPase activity that form heterooligomeric filaments and ringlike structures that act as diffusion barriers and scaffolds. Septins are involved in cytokinesis, positioning of the mitotic spindle, cellular morphology, vesicle trafficking, apoptosis, neurodegeneration, and neoplasia (2–5). In mammals, 14 septin genes have been identified. Each septin gene is expressed in several spliced forms. Although most septins are highly expressed in the brain (6), only recently is their role in neuronal function (7–9) and in neuropathology (10–14) is beginning to be addressed for some septins.Septin 11 is expressed in various tissues, including the brain (15), but little is known about the role of septin 11 in the brain. Septins 3, 5, 6, and 7 are localized in the presynaptic terminals, frequently associated with synaptic vesicles (6, 16, 17). In neurons, septin 11 forms heterooligomeric complexes with septin 7 and septin 5 (9, 18). Nevertheless, the regional and developmental distribution of septin 11 in the brain and in hippocampal cultures is not identical to that of septin 7 or septin 5 (8). These results and other heterooligomerization studies show that septin 11 is not always associated with septin 7 and septin 5 (7, 15, 19). Thus, septin 11 is expected to have functional properties both similar to and different from those of septin 7 and other septins that heterooligomerize with septin 11. In the present paper, we show that septin 11 is associated with the GABAergic synapses, particularly with the postsynapse, and concentrates at the neck of dendritic spines in the intact brain. Others have recently shown that another septin (septin 7) accumulates at the base of dendritic protrusions of cultured neurons (8, 9). However, it is not known whether septins also accumulate at the base of the dendritic spines in the brain. To the best of our knowledge, this is the first time that (i) a septin has been shown to be associated with GABAergic synapses and (ii) a septin has been shown to concentrate at the neck of dendritic spines and dendritic branching points in the intact brain.     

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]     

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.     

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]     

The Novel Caspase-3 Substrate Gap43 is Involved in AMPA Receptor Endocytosis and Long-Term Depression

The cysteine protease caspase-3, best known as an executioner of cell death in apoptosis, also plays a non-apoptotic role in N-methyl-d-aspartate receptor-dependent long-term depression of synaptic transmission (NMDAR-LTD) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor endocytosis in neurons. The mechanism by which caspase-3 regulates LTD and AMPA receptor endocytosis, however, remains unclear. Here, we addressed this question by using an enzymatic N-terminal peptide enrichment method and mass spectrometry to identify caspase-3 substrates in neurons. Of the many candidates revealed by this proteomic study, we have confirmed BASP1, Dbn1, and Gap43 as true caspase-3 substrates. Moreover, in hippocampal neurons, Gap43 mutants deficient in caspase-3 cleavage inhibit AMPA receptor endocytosis and LTD. We further demonstrated that Gap43, a protein well-known for its functions in axons, is also localized at postsynaptic sites. Our study has identified Gap43 as a key caspase-3 substrate involved in LTD and AMPA receptor endocytosis, uncovered a novel postsynaptic function for Gap43 and provided new insights into how long-term synaptic depression is induced.Synaptic plasticity (the ability of synapses to change in strength) plays an important role in brain development and cognitive function, including learning and memory. N-methyl-d-aspartate receptor (NMDAR)¹-dependent long-term depression of synaptic transmission (LTD) is a major form of synaptic plasticity that leads to long-lasting decreases in synaptic strength. In NMDAR-LTD, synaptic depression is mainly mediated by removal of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors from the postsynaptic membrane through endocytosis (1–3).Caspases are cysteine-dependent proteases that cleave after an aspartate residue (4–6). Primary specificity for aspartate at the cleavage site is so rare in mammalian proteases that only granzyme B, a serine protease derived from lymphocytes, is known to also have such a property (7, 8). Caspases are best known for their pro-apoptotic function in programmed cell death, or apoptosis (9). Caspases activated at the end of a caspase cascade are “effector” caspases, and among them caspase-3 is the dominant one (10). In addition to apoptosis, caspases also play non-apoptotic roles such as in cell differentiation, dendritic development, and memory consolidation (11–14). For instance, our earlier studies show that NMDAR-LTD requires moderate and transient caspase-3 activation, which does not induce cell death (15, 16).In LTD, caspase-3 is activated by the mitochondrial pathway (15, 16). With the opening of NMDA receptors, calcineurin and protein phosphatase 1 are activated to dephosphorylate the Bcl-2 family protein BAD. Dephosphorylated BAD then translocates to the mitochondria, activating BAX, which is also a member of the Bcl-2 family protein. The subsequent release of cytochrome-c from mitochondria leads to the sequential activation of caspase-9 and caspase-3. Active caspase-3 induces AMPA receptor endocytosis, and therefore depression of synaptic strength. The mechanism by which caspase-3 promotes AMPA receptor endocytosis, however, remains to be determined.Caspases'' cellular functions are primarily mediated by the proteolysis of caspase substrates, resulting in change of their functions. Identification of specific proteins cleaved by caspases is therefore key to understanding the mechanisms mediating their biological functions. Several proteomic approaches, developed specifically for this purpose, have led to the identification of more than 2000 caspase cleavage sites (17–22). In particular, the recently developed subtiligase-based method for isolating proteolytic products has led to the identification of >1,000 putative caspase substrates in human samples (21, 23, 24). Subtiligase is an engineered peptide ligase that ligates esterified peptides onto the N termini of proteins or peptides through free α-amines (25). Because the majority of eukaryotic proteins are N-terminally acetylated—and therefore blocked from subtiligase labeling (26)—subtiligase can couple synthetic tagged peptides selectively to the free N-terminal α-amines of proteins derived from proteolysis. These peptide-conjugated proteolytic products can then be affinity-purified, digested with trypsin and sequenced by mass spectrometry. Identification of peptides ligated to the tagged peptide by subtiligase allows researchers to determine cleavage sites within the substrates.In this study, the subtiligase-based proteomic method was used to find capase-3 substrates in rat neurons, resulting in the identification of 81 putative aspartate cleavage sites in 56 proteins. Of these, 37 proteins (human and a single rat orthologs) were not previously reported in the CASBAH database (20), and 13 (human orthologs) are not included in the DegraBase data set compiled using the subtiligase methodology in non-neuronal tissue (21). Using complimentary methods, we further confirmed that, both in vivo and in vitro, caspase-3 cleaves three of these candidate substrates: growth associated protein 43 (Gap43), drebrin (Dbn1), and brain acid soluble protein 1 (BASP1). Surprisingly, we also found that AMPA receptor endocytosis and LTD induction both require caspase-3 to cleave Gap43, a protein well known for its presynaptic functions, at the sites identified by our study.     

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.     

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]     

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]