Molecular Chaperone Hsp70/Hsp90 Prepares the Mitochondrial Outer Membrane Translocon Receptor Tom71 for Preprotein Loading

The preproteins targeted to the mitochondria are transported through the translocase of the outer membrane complex. Tom70/Tom71 is a major surface receptor of the translocase of the outer membrane complex for mitochondrial preproteins. The preproteins are escorted to Tom70/Tom71 by molecular chaperones Hsp70 and Hsp90. Here we present the high resolution crystal structures of Tom71 and the protein complexes between Tom71 and the Hsp70/Hsp90 C terminus. The crystal structures indicate that Tom70/Tom71 may exhibit two distinct states. In the closed state, the N-terminal domain of Tom70/Tom71 partially blocks the preprotein-binding pocket. In the open state, the N-terminal domain moves away, and the preprotein-binding pocket is fully exposed. The complex formation between the C-terminal EEVD motif of Hsp70/Hsp90 and Tom71 could lock Tom71 in the open state where the preprotein-binding pocket of Tom71 is ready to receive preproteins. The interactions between Hsp70/Hsp90 and Tom71 N-terminal domain generate conformational changes that may increase the volume of the preprotein-binding pocket. The complex formation of Hsp70/Hsp90 and Tom71 also generates significant domain rearrangement within Tom71, which may position the preprotein-binding pocket closer to Hsp70/Hsp90 to facilitate the preprotein transfer from the molecular chaperone to Tom71. Therefore, molecular chaperone Hsp70/Hsp90 may function to prepare the mitochondrial outer membrane receptor Tom71 for preprotein loading.The mitochondrion plays important roles in cell physiology. The mitochondrion functions as the “cellular power house” by generating most of the supply of ATP for the cell. In addition, the mitochondrion is involved in a number of critical cellular processes including the synthesis of metabolites, lipid metabolism, free radical production, and metal ion homeostasis. The mitochondrion consists of four compartments, the outer membrane, the inner membrane, the intermembrane space, and the mitochondrial matrix. The mitochondrion contains a large number of proteins (1), but only a few of these are translated within the mitochondrion (2). Therefore, the majority of the mitochondrial proteins are synthesized in the cytosol and translocated into the mitochondrion.The mitochondrial preproteins contain specific targeting signals to reach the correct compartments within the mitochondria. The mitochondrial matrix preproteins contain N-terminal targeting sequences that form the short amphipathic helices (2–6). On the other hand, some mitochondrial proteins of the inner and outer membrane contain internal targeting signals within the mature proteins (7). The mitochondrion has developed a set of delicate translocons to transport the preproteins into the mitochondrial compartments, one translocase of the outer membrane (TOM)² and two translocases of the inner membrane (TIM23 and TIM22) (4, 5, 8). The TOM complex has two surface receptors, Tom20 and Tom70 (9, 10). Tom20 recognizes the N-terminal mitochondrial targeting signals from the preproteins, whereas Tom70 binds to internal targeting sequences of preproteins such as the multi-transmembrane carrier proteins residing in the mitochondrial membranes (9–12). The crystal structure of Saccharomyces cerevisiae Tom70 revealed that Tom70 contained 11 TPR motifs, and the TPR motifs were clustered into two domains. The three TPR motifs in the N-terminal domain of Tom70p form a peptide-binding groove for the C-terminal EEVD motif of Hsp70/Hsp90, whereas the C-terminal domain of Tom70p contains a large preprotein-binding pocket (13).Molecular chaperones Hsp70 and Hsp90 play important roles in targeting the preproteins to TOM complex (14). Hsp70 and Hsp90 can protect these preproteins from aggregation in the cytosol (15). The C-terminal EEVD motifs of Hsp70/Hsp90 may interact directly with the N-terminal domain of Tom70p to target the preproteins to TOM complex (13, 14, 16). The C-terminal EEVD motif of Hsp70/Hsp90 has been indicated to bind several proteins containing TPR motifs including Hop and CHIP. The complex structures for the Hsp70/Hsp90 EEVD motif and Hop and CHIP TPR regions have been determined (17–21).Tom71 (also known as Tom72) was identified as a homologue with Tom70 with high amino acid sequence identity (>50%) (22). Tom71 shares overlapping functions with Tom70 to transfer the preproteins and maintain the mitochondrial morphology (23, 24). In this study, we have determined the crystal structures of S. cerevisiae Tom71 and the complexes of Tom71 and Hsp70/Hsp90 C-terminal EEVD motifs. These structures suggest that the Hsp70/Hsp90 binding to Tom70/Tom71 may keep Tom70/Tom71 in the open state for receiving preproteins. The Hsp70/Hsp90 interactions may also increase the volume of the preprotein-binding pocket of Tom70/Tom71 and prepare Tom70/Tom71 for preprotein loading.     

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]     

Phosphoproteome Analysis of Functional Mitochondria Isolated from Resting Human Muscle Reveals Extensive Phosphorylation of Inner Membrane Protein Complexes and Enzymes

Mitochondria play a central role in energy metabolism and cellular survival, and consequently mitochondrial dysfunction is associated with a number of human pathologies. Reversible protein phosphorylation emerges as a central mechanism in the regulation of several mitochondrial processes. In skeletal muscle, mitochondrial dysfunction is linked to insulin resistance in humans with obesity and type 2 diabetes. We performed a phosphoproteomics study of functional mitochondria isolated from human muscle biopsies with the aim to obtain a comprehensive overview of mitochondrial phosphoproteins. Combining an efficient mitochondrial isolation protocol with several different phosphopeptide enrichment techniques and LC-MS/MS, we identified 155 distinct phosphorylation sites in 77 mitochondrial phosphoproteins, including 116 phosphoserine, 23 phosphothreonine, and 16 phosphotyrosine residues. The relatively high number of phosphotyrosine residues suggests an important role for tyrosine phosphorylation in mitochondrial signaling. Many of the mitochondrial phosphoproteins are involved in oxidative phosphorylation, tricarboxylic acid cycle, and lipid metabolism, i.e. processes proposed to be involved in insulin resistance. We also assigned phosphorylation sites in mitochondrial proteins involved in amino acid degradation, importers and transporters, calcium homeostasis, and apoptosis. Bioinformatics analysis of kinase motifs revealed that many of these mitochondrial phosphoproteins are substrates for protein kinase A, protein kinase C, casein kinase II, and DNA-dependent protein kinase. Our results demonstrate the feasibility of performing phosphoproteome analysis of organelles isolated from human tissue and provide novel targets for functional studies of reversible phosphorylation in mitochondria. Future comparative phosphoproteome analysis of mitochondria from healthy and diseased individuals will provide insights into the role of abnormal phosphorylation in pathologies, such as type 2 diabetes.Mitochondria are the primary energy-generating systems in eukaryotes. They play a crucial role in oxidative metabolism, including carbohydrate metabolism, fatty acid oxidation, and urea cycle, as well as in calcium signaling and apoptosis (1, 2). Mitochondrial dysfunction is centrally involved in a number of human pathologies, such as type 2 diabetes, Parkinson disease, and cancer (3). The most prevalent form of cellular protein post-translational modifications (PTMs),1 reversible phosphorylation (4–6), is emerging as a central mechanism in the regulation of mitochondrial functions (7, 8). The steadily increasing numbers of reported mitochondrial kinases, phosphatases, and phosphoproteins imply an important role of protein phosphorylation in different mitochondrial processes (9–11).Mass spectrometry (MS)-based proteome analysis is a powerful tool for global profiling of proteins and their PTMs, including protein phosphorylation (12, 13). A variety of proteomics techniques have been developed for specific enrichment of phosphorylated proteins and peptides and for phosphopeptide-specific data acquisition techniques at the MS level (14). Enrichment methods based on affinity chromatography, such as titanium dioxide (TiO₂) (15–17), zwitterionic hydrophilic interaction chromatography (ZIC-HILIC) (18), immobilized metal affinity chromatography (IMAC) (19, 20), and ion exchange chromatography (strong anion exchange and strong cation exchange) (21, 22), have shown high efficiencies for enrichment of phosphopeptides (14). Recently, we demonstrated that calcium phosphate precipitation (CPP) is highly effective for enriching phosphopeptides (23). It is now generally accepted that no single method is comprehensive, but combinations of different enrichment methods produce distinct overlapping phosphopeptide data sets to enhance the overall results in phosphoproteome analysis (24, 25). Phosphopeptide sequencing by mass spectrometry has seen tremendous advances during the last decade (26). For example, MS/MS product ion scanning, multistage activation, and precursor ion scanning are effective methods for identifying serine (Ser), threonine (Thr), and tyrosine (Tyr) phosphorylated peptides (14, 26).A “complete” mammalian mitochondrial proteome was reported by Mootha and co-workers (27) and included 1098 proteins. The mitochondrial phosphoproteome has been characterized in a series of studies, including yeast, mouse and rat liver, porcine heart, and plants (19, 28–31). To date, the largest data set by Deng et al. (30) identified 228 different phosphoproteins and 447 phosphorylation sites in rat liver mitochondria. However, the in vivo phosphoproteome of human mitochondria has not been determined. A comprehensive mitochondrial phosphoproteome is warranted for further elucidation of the largely unknown mechanisms by which protein phosphorylation modulates diverse mitochondrial functions.The percutaneous muscle biopsy technique is an important tool in the diagnosis and management of human muscle disorders and has been widely used to investigate metabolism and various cellular and molecular processes in normal and abnormal human muscle, in particular the molecular mechanism underlying insulin resistance in obesity and type 2 diabetes (32). Skeletal muscle is rich in mitochondria and hence a good source for a comprehensive proteomics and functional analysis of mitochondria (32, 33).The major aim of the present study was to obtain a comprehensive overview of site-specific phosphorylation of mitochondrial proteins in functionally intact mitochondria isolated from human skeletal muscle. Combining an efficient protocol for isolation of skeletal muscle mitochondria with several different state-of-the-art phosphopeptide enrichment methods and high performance LC-MS/MS, we identified 155 distinct phosphorylation sites in 77 mitochondrial phosphoproteins, many of which have not been reported before. We characterized this mitochondrial phosphoproteome by using bioinformatics tools to classify functional groups and functions, including kinase substrate motifs.     

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]     

Phosphoproteome Analysis Reveals Regulatory Sites in Major Pathways of Cardiac Mitochondria

Mitochondrial functions are dynamically regulated in the heart. In particular, protein phosphorylation has been shown to be a key mechanism modulating mitochondrial function in diverse cardiovascular phenotypes. However, site-specific phosphorylation information remains scarce for this organ. Accordingly, we performed a comprehensive characterization of murine cardiac mitochondrial phosphoproteome in the context of mitochondrial functional pathways. A platform using the complementary fragmentation technologies of collision-induced dissociation (CID) and electron transfer dissociation (ETD) demonstrated successful identification of a total of 236 phosphorylation sites in the murine heart; 210 of these sites were novel. These 236 sites were mapped to 181 phosphoproteins and 203 phosphopeptides. Among those identified, 45 phosphorylation sites were captured only by CID, whereas 185 phosphorylation sites, including a novel modification on ubiquinol-cytochrome c reductase protein 1 (Ser-212), were identified only by ETD, underscoring the advantage of a combined CID and ETD approach. The biological significance of the cardiac mitochondrial phosphoproteome was evaluated. Our investigations illustrated key regulatory sites in murine cardiac mitochondrial pathways as targets of phosphorylation regulation, including components of the electron transport chain (ETC) complexes and enzymes involved in metabolic pathways (e.g. tricarboxylic acid cycle). Furthermore, calcium overload injured cardiac mitochondrial ETC function, whereas enhanced phosphorylation of ETC via application of phosphatase inhibitors restored calcium-attenuated ETC complex I and complex III activities, demonstrating positive regulation of ETC function by phosphorylation. Moreover, in silico analyses of the identified phosphopeptide motifs illuminated the molecular nature of participating kinases, which included several known mitochondrial kinases (e.g. pyruvate dehydrogenase kinase) as well as kinases whose mitochondrial location was not previously appreciated (e.g. Src). In conclusion, the phosphorylation events defined herein advance our understanding of cardiac mitochondrial biology, facilitating the integration of the still fragmentary knowledge about mitochondrial signaling networks, metabolic pathways, and intrinsic mechanisms of functional regulation in the heart.Mitochondria are the source of energy to sustain life. In addition to their evolutionary origin as an energy-producing organelle, their functionality has integrated into every aspect of life, including the cell cycle, ROS¹ production, apoptosis, and ion balance (1, 2). Our understanding of mitochondrial biology is still growing. Several systems biology approaches have been dedicated to exploring the molecular infrastructure and dynamics of the functional versatility associated with this organelle (3–5).To meet tissue-specific functional demands, mitochondria acquire heterogeneous properties in individual organs, a first statement of their plasticity in function and proteome composition (1, 6). The heterogeneity is evident even in an individual cardiomyocyte (7). A catalogue of the cardiac mitochondrial proteome is emerging via a joint effort (3–5). The dynamics of the mitochondrial proteome manifest at multiple levels, including post-translational modifications, such as phosphorylation. Our investigative goal is to decode this organellar proteome and its post-translational modification in a biological and functional context. In cardiomyocytes, mitochondria are also constantly exposed to fluctuation in energy demands and in ionic conditions. The capacity of mitochondria to cope with such a dynamic environment is essential for the functional role of mitochondria in normal and disease phenotypes (8–10). Unique protein features enabling the mitochondrial proteome to adapt to these biological changes can be interrogated by proteomics tools (10–12). Protein phosphorylation as a rapid and reversible chemical event is an integral component of these protein features (12–14).It has been estimated that one-third of cellular proteins exist in a phosphorylated state at least one time in their lifetime (15). However, only a handful of phosphorylation events have been identified to tune mitochondrial functionality (13, 14, 16) despite the fact that the first demonstration of phosphorylation was reported on a mitochondrial protein more than 5 decades ago (17). Kinases and phosphatases comprise nearly 3% of the human genome (18, 19). In mitochondria, ∼30 kinases and phosphatases have been identified thus far within the expected organellar proteome of a few thousand (3–5, 16). The number of identified mitochondrial phosphoproteins is far below one-third of its proteome size (20). Thus, it appears that the current pool of reported phosphoproteins represents only a small fraction of the anticipated mitochondrial phosphoproteome. The seminal studies from several groups (12–14, 16) demonstrated the prevalence as well as the dynamic nature of phosphorylation in cardiac mitochondria, suggesting that obtaining a comprehensive map of the mitochondrial phosphoproteome is feasible.In this study, we took a systematic approach to tackle the phosphorylation of murine cardiac mitochondrial pathways. We applied the unique strengths of both electron transfer dissociation (ETD) and collision-induced dissociation (CID) LC-MS/MS to screen phosphorylation events in a site-specific fashion. A total of 236 phosphorylation sites in 203 unique phosphopeptides were identified and mapped to 181 phosphoproteins. Novel phosphorylation modifications were discovered in diverse pathways of mitochondrial biology, including ion balance, proteolysis, and apoptosis. Consistent with the role of mitochondria as the major source of energy production under delicate control, metabolic pathways claimed one-third of phosphorylation sites captured in this analysis. To study molecular players steering mitochondrial phosphorylation, we probed the effects of calcium loading on phosphorylation. In addition, a number of kinases with previously unappreciated mitochondrial residence are suggested as potential players modulating mitochondrial pathways. Taken together, the cohort of novel phosphorylation events discovered in this study constitutes an essential step toward the full delineation of the cardiac mitochondrial phosphoproteome.     

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]     

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]