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]     

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.     

Chemokine (C-C Motif) Ligand 2 Engages CCR2+ Stromal Cells of Monocytic Origin to Promote Breast Cancer Metastasis to Lung and Bone

Metastatic spread of cancer to distant vital organs, including lung and bone, is the overwhelming cause of breast cancer mortality and morbidity. Effective treatment of systemic metastasis relies on the identification and functional characterization of metastasis mediators to multiple organs. Overexpression of the chemokine (C-C motif) ligand 2 (CCL2) is frequently associated with advanced tumor stage and metastatic relapse in breast cancer. However, the functional mechanism of CCL2 in promoting organ-specific metastasis of breast cancer has not been rigorously investigated. Here, we used organ-specific metastatic sublines of the MDA-MB-231 human breast cancer cell line to demonstrate that overexpression of CCL2 promotes breast cancer metastasis to both lung and bone. Conversely, blocking CCL2 function with a neutralizing antibody reduced lung and bone metastases. The enhancement of lung and bone metastases by CCL2 was associated with increased macrophage infiltration and osteoclast differentiation, respectively. By performing functional assays with primary cells isolated from the wild type, CCL2 and CCR2 knock-out mice, we showed that tumor cell-derived CCL2 depends on its receptor CCR2 (chemokine, CC motif, receptor 2) expressed on stromal cells to exert its function in promoting macrophage recruitment and osteoclast differentiation. Overall, these data demonstrated that CCL2-expressing breast tumor cells engage CCR2⁺ stromal cells of monocytic origin, including macrophages and preosteoclasts, to facilitate colonization in lung and bone. Therefore, CCL2 and CCR2 are promising therapeutic targets for simultaneously inhibiting lung and bone metastasis of breast cancer.Breast cancer is the most common malignancy in women in the United States, with an estimated 182,000 new cases and 40,000 deaths in 2008 (1). Late stage breast cancer patients develop metastases in bone, lung, liver, brain, and other organs, which are responsible for most breast cancer-related mortality and morbidity (2). Severe complications from bone metastasis include debilitating bone fractures, nerve compression and bone pain, and hypercalcemia (3–5), whereas lung metastasis is accompanied by cough, bloody sputum, rib cage pain, and, eventually, failure of the respiratory functions (6). Colonization of different secondary organs by breast cancer is believed to be a complex, multigenic process that depends on productive interactions between tumor cells and stromal microenvironments through concerted actions of organ-specific metastasis genes (7, 8). Functional genomic analysis of preclinical models of breast cancer to bone, lung, and brain have identified distinct sets of organ-specific metastasis genes (9–11), providing novel mechanistic insights into key rate-limiting steps of metastasis to different organs. However, as advanced breast cancer patients often suffer from metastases at several secondary organs, identifying genes that are capable of instigating metastasis to multiple sites may provide the ideal targets for therapeutic intervention of systemic metastasis.Chemokines are small (8–14 kDa) proteins classified into four conserved groups (CXC, CC, C, and CX3C) based on the position of the first two cysteines that are adjacent to the amino terminus (12). They are chemotactic cytokines that stimulate directed migration of leukocytes in response to inflammatory signals. Chemokines are also involved in the maintenance of hematopoietic homeostasis, regulation of cell proliferation, tissue morphogenesis, and angiogenesis (13). Chemokines bind to the seven-transmembrane domain receptors to elicit downstream molecular events that coordinate cell movement. Even though chemokines are unlikely to be a contributing factor for tumor initiation, they can have pleiotropic effects on tumor progression (13, 14). Among more than 50 human chemokines, CCL2 is of particular importance. CCL2, also called monocyte chemoattractant protein-1 (MCP-1), is a potent chemoattractant for monocytes, memory T lymphocytes, and natural killer cells (15). It is involved in a number of inflammatory conditions associated with monocyte recruitment, including delayed hypersensitivity reactions, bacterial infection, arthritis, and renal disease (15). The importance of CCL2 in cancer was manifested by its overexpression in a variety of tumor types, including glioma, ovarian, esophagus, lung, breast, and prostate cancers (15–17). In prostate cancer, CCL2 expression levels was associated with advanced pathological stage (16). Importantly, CCL2-neutralizing antibodies inhibit bone resorption in vitro and bone metastasis in vivo (18–20). In lung cancer, serum CCL2 levels were elevated in lung cancer patients with bone metastasis compared with localized diseases. Neutralizing antibodies against CCL2 also inhibited the tumor conditioned media-induced osteoclast formation in vitro and bone metastasis in vivo (17). Taken together, these findings suggested a role of CCL2 in bone metastasis.A potential role of CCL2 in breast cancer progression and metastasis has been indicated by the analysis of CCL2 expression of tumor and serum samples from breast cancer patients. Serum CCL2 levels were significantly higher in postmenopausal breast cancer patients than in age-matched controls (21). Over 50% of breast cancer tumor samples had intense staining of CCL2 in tumor cells (22). Prognostic analysis further revealed that high expression of CCL2 was correlated with advanced tumor stage, lymph node metastasis (23), and early relapse (24). CCL2 up-regulation in breast tumors was also associated with the infiltration of tissue-associated macrophages (TAMs)³ and with increased microvessel density (22, 24). TAMs have been known to contribute to primary tumor progression and metastasis of breast cancer (25), which is supported by epidemiological evidence showing that TAM infiltration portended a poor clinical outcome (26, 27). However, whether the function of CCL2 in modulating activity of macrophages and possibly other cell types is important for breast tumor organotropic metastasis has not been rigorously investigated. CCL2 may engage organ-specific cell types derived from the same bone marrow myelomonocytic progenitors. These progenitors differentiate into osteoclast precursors in bone or into blood monocytes that eventually become mature macrophages in different tissues, like alveolar macrophages in lung (28). These stromal cell types of myelomonocytic origin may contribute to different functions in different organ-specific metastases. Another unresolved question regarding the function of CCL2 in tumor-stroma interaction is the functional involvement of CCL2 receptors. CCL2 can bind to both CCR2 and CCR4 (29, 30). Loss of function studies in mice showed CCL2 and CCR2 knock-out mice displayed similar impairments in monocyte migration (31, 32), suggesting that CCR2 is the major functional receptor for CCL2. Understanding whether CCR2 deficiency in stromal cells leads to compromised monocyte engagement by CCL2-expressing tumor cells may have important implications in designing targeting therapeutics against the CCL2/CCR2 axis.In this study, we used the recently developed organ-specific metastatic sublines of the human breast cancer cell MDA-MB-231 (9, 10, 33) and showed that overexpression of CCL2 promotes both lung and bone metastases. This function was associated with increased TAM infiltration in lung metastasis and increased osteoclast differentiation in bone metastasis, respectively. Furthermore, by using macrophages and bone marrow cells isolated from wild type, CCL2-deficient, and CCR2-deficient mice, we showed that CCR2 expression in stromal cells is essential for tumor-derived CCL2 to recruit macrophages and promote osteoclastogenesis. Targeting tumor-derived CCL2 by a neutralizing antibody significantly reduced metastasis formation in both bone and lung.     

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.     

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]     

Quantitative Proteomics Reveals Protein–Protein Interactions with Fibroblast Growth Factor 12 as a Component of the Voltage-Gated Sodium Channel 1.2 (Nav1.2) Macromolecular Complex in Mammalian Brain

Voltage-gated sodium channels (Nav1.1–Nav1.9) are responsible for the initiation and propagation of action potentials in neurons, controlling firing patterns, synaptic transmission and plasticity of the brain circuit. Yet, it is the protein–protein interactions of the macromolecular complex that exert diverse modulatory actions on the channel, dictating its ultimate functional outcome. Despite the fundamental role of Nav channels in the brain, information on its proteome is still lacking. Here we used affinity purification from crude membrane extracts of whole brain followed by quantitative high-resolution mass spectrometry to resolve the identity of Nav1.2 protein interactors. Of the identified putative protein interactors, fibroblast growth factor 12 (FGF12), a member of the nonsecreted intracellular FGF family, exhibited 30-fold enrichment in Nav1.2 purifications compared with other identified proteins. Using confocal microscopy, we visualized native FGF12 in the brain tissue and confirmed that FGF12 forms a complex with Nav1.2 channels at the axonal initial segment, the subcellular specialized domain of neurons required for action potential initiation. Co-immunoprecipitation studies in a heterologous expression system validate Nav1.2 and FGF12 as interactors, whereas patch-clamp electrophysiology reveals that FGF12 acts synergistically with CaMKII, a known kinase regulator of Nav channels, to modulate Nav1.2-encoded currents. In the presence of CaMKII inhibitors we found that FGF12 produces a bidirectional shift in the voltage-dependence of activation (more depolarized) and the steady-state inactivation (more hyperpolarized) of Nav1.2, increasing the channel availability. Although providing the first characterization of the Nav1.2 CNS proteome, we identify FGF12 as a new functionally relevant interactor. Our studies will provide invaluable information to parse out the molecular determinant underlying neuronal excitability and plasticity, and extending the relevance of iFGFs signaling in the normal and diseased brain.Voltage-gated sodium channels (Nav)¹ are transmembrane proteins consisting of a pore-forming α subunit (Nav1.1-Nav1.9) and one or more accessory β-subunits (β₁–β₄) (1–3). Predominately clustered at the axonal initial segment (AIS), the α subunit alone is necessary and sufficient for channel assembly and the initiation and propagation of action potentials following membrane depolarization (4). Although the α subunit is functional on its own, it is the transient and stable protein–protein interactions that modulate subcellular trafficking, compartmentalization, functional expression, and fine-tune the channel biophysical properties (5–9). Thus, the Nav channel and the protein constituents that comprise the protein–protein interaction network are all part of a macromolecular complex that modulates the spatiotemporal dynamics of neuronal input and output playing a critical role in synaptic transmission, signal integration, and neuronal plasticity. Perturbations in this protein–protein interaction network can lead to deficits in neuronal excitability, and eventually neurodegeneration and cell death (10–15).Given the relevance of these interactions for the native channel activity and its overall role in controlling brain circuits, it is increasingly important to uncover these associations. Antibody-based affinity purification (AP) combined with mass spectrometry (MS) is widely used for the enrichment and analysis of target proteins and constituents of their protein–protein interactions as it can be performed at near physiological conditions and preserves post-translational modifications relevant to protein complex organization (16–19). Differential mass spectrometry provides an unbiased method for the efficient, MS-based measurement of relative protein fold changes across multiple complex biological samples. This technology has been successfully applied to a number of ion channels (20–26), but—to the best of our knowledge—not to the study of any member of the Nav channel family. Using a target-directed AP approach combined with quantitative MS, we identified proteins constituting the putative interactome of Nav1.2, one of three dominant Nav channel isoforms in the mammalian brain, from native tissue (1, 2, 4, 8). Among these putative interactors, the fibroblast growth factor 12 (FGF12), a member of the intracellular FGF family (5, 13, 14), stood out as one of the most abundant coprecipitating proteins with ∼30-fold enrichment over other interactors. With a combination of confocal microscopy in brain tissue, reconstitution of the interactor in a heterologous systems and electrophysiological assays, we provide validation for FGF12 as a bona fide relevant component of the Nav1.2 proteome and a modulator of Nav1.2-encoded currents. Altogether, the identified channel/protein interaction between FGF12 and Nav1.2 provides new insights for structural and functional interpretation of neuronal excitability, synaptic transmission, and plasticity in the normal and diseased brain.     

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]     

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.     

High-definition De Novo Sequencing of Crustacean Hyperglycemic Hormone (CHH)-family Neuropeptides

A complete understanding of the biological functions of large signaling peptides (>4 kDa) requires comprehensive characterization of their amino acid sequences and post-translational modifications, which presents significant analytical challenges. In the past decade, there has been great success with mass spectrometry-based de novo sequencing of small neuropeptides. However, these approaches are less applicable to larger neuropeptides because of the inefficient fragmentation of peptides larger than 4 kDa and their lower endogenous abundance. The conventional proteomics approach focuses on large-scale determination of protein identities via database searching, lacking the ability for in-depth elucidation of individual amino acid residues. Here, we present a multifaceted MS approach for identification and characterization of large crustacean hyperglycemic hormone (CHH)-family neuropeptides, a class of peptide hormones that play central roles in the regulation of many important physiological processes of crustaceans. Six crustacean CHH-family neuropeptides (8–9.5 kDa), including two novel peptides with extensive disulfide linkages and PTMs, were fully sequenced without reference to genomic databases. High-definition de novo sequencing was achieved by a combination of bottom-up, off-line top-down, and on-line top-down tandem MS methods. Statistical evaluation indicated that these methods provided complementary information for sequence interpretation and increased the local identification confidence of each amino acid. Further investigations by MALDI imaging MS mapped the spatial distribution and colocalization patterns of various CHH-family neuropeptides in the neuroendocrine organs, revealing that two CHH-subfamilies are involved in distinct signaling pathways.Neuropeptides and hormones comprise a diverse class of signaling molecules involved in numerous essential physiological processes, including analgesia, reward, food intake, learning and memory (1). Disorders of the neurosecretory and neuroendocrine systems influence many pathological processes. For example, obesity results from failure of energy homeostasis in association with endocrine alterations (2, 3). Previous work from our lab used crustaceans as model organisms found that multiple neuropeptides were implicated in control of food intake, including RFamides, tachykinin related peptides, RYamides, and pyrokinins (4–6).Crustacean hyperglycemic hormone (CHH)¹ family neuropeptides play a central role in energy homeostasis of crustaceans (7–17). Hyperglycemic response of the CHHs was first reported after injection of crude eyestalk extract in crustaceans. Based on their preprohormone organization, the CHH family can be grouped into two sub-families: subfamily-I containing CHH, and subfamily-II containing molt-inhibiting hormone (MIH) and mandibular organ-inhibiting hormone (MOIH). The preprohormones of the subfamily-I have a CHH precursor related peptide (CPRP) that is cleaved off during processing; and preprohormones of the subfamily-II lack the CPRP (9). Uncovering their physiological functions will provide new insights into neuroendocrine regulation of energy homeostasis.Characterization of CHH-family neuropeptides is challenging. They are comprised of more than 70 amino acids and often contain multiple post-translational modifications (PTMs) and complex disulfide bridge connections (7). In addition, physiological concentrations of these peptide hormones are typically below picomolar level, and most crustacean species do not have available genome and proteome databases to assist MS-based sequencing.MS-based neuropeptidomics provides a powerful tool for rapid discovery and analysis of a large number of endogenous peptides from the brain and the central nervous system. Our group and others have greatly expanded the peptidomes of many model organisms (3, 18–33). For example, we have discovered more than 200 neuropeptides with several neuropeptide families consisting of as many as 20–40 members in a simple crustacean model system (5, 6, 25–31, 34). However, a majority of these neuropeptides are small peptides with 5–15 amino acid residues long, leaving a gap of identifying larger signaling peptides from organisms without sequenced genome. The observed lack of larger size peptide hormones can be attributed to the lack of effective de novo sequencing strategies for neuropeptides larger than 4 kDa, which are inherently more difficult to fragment using conventional techniques (34–37). Although classical proteomics studies examine larger proteins, these tools are limited to identification based on database searching with one or more peptides matching without complete amino acid sequence coverage (36, 38).Large populations of neuropeptides from 4–10 kDa exist in the nervous systems of both vertebrates and invertebrates (9, 39, 40). Understanding their functional roles requires sufficient molecular knowledge and a unique analytical approach. Therefore, developing effective and reliable methods for de novo sequencing of large neuropeptides at the individual amino acid residue level is an urgent gap to fill in neurobiology. In this study, we present a multifaceted MS strategy aimed at high-definition de novo sequencing and comprehensive characterization of the CHH-family neuropeptides in crustacean central nervous system. The high-definition de novo sequencing was achieved by a combination of three methods: (1) enzymatic digestion and LC-tandem mass spectrometry (MS/MS) bottom-up analysis to generate detailed sequences of proteolytic peptides; (2) off-line LC fractionation and subsequent top-down MS/MS to obtain high-quality fragmentation maps of intact peptides; and (3) on-line LC coupled to top-down MS/MS to allow rapid sequence analysis of low abundance peptides. Combining the three methods overcomes the limitations of each, and thus offers complementary and high-confidence determination of amino acid residues. We report the complete sequence analysis of six CHH-family neuropeptides including the discovery of two novel peptides. With the accurate molecular information, MALDI imaging and ion mobility MS were conducted for the first time to explore their anatomical distribution and biochemical properties.     

Online Peptide Fractionation Using a Multiphasic Microfluidic Liquid Chromatography Chip Improves Reproducibility and Detection Limits for Quantitation in Discovery and Targeted Proteomics

Comprehensive proteomic profiling of biological specimens usually requires multidimensional chromatographic peptide fractionation prior to mass spectrometry. However, this approach can suffer from poor reproducibility because of the lack of standardization and automation of the entire workflow, thus compromising performance of quantitative proteomic investigations. To address these variables we developed an online peptide fractionation system comprising a multiphasic liquid chromatography (LC) chip that integrates reversed phase and strong cation exchange chromatography upstream of the mass spectrometer (MS). We showed superiority of this system for standardizing discovery and targeted proteomic workflows using cancer cell lysates and nondepleted human plasma. Five-step multiphase chip LC MS/MS acquisition showed clear advantages over analyses of unfractionated samples by identifying more peptides, consuming less sample and often improving the lower limits of quantitation, all in highly reproducible, automated, online configuration. We further showed that multiphase chip LC fractionation provided a facile means to detect many N- and C-terminal peptides (including acetylated N terminus) that are challenging to identify in complex tryptic peptide matrices because of less favorable ionization characteristics. Given as much as 95% of peptides were detected in only a single salt fraction from cell lysates we exploited this high reproducibility and coupled it with multiple reaction monitoring on a high-resolution MS instrument (MRM-HR). This approach increased target analyte peak area and improved lower limits of quantitation without negatively influencing variance or bias. Further, we showed a strategy to use multiphase LC chip fractionation LC-MS/MS for ion library generation to integrate with SWATH^TM data-independent acquisition quantitative workflows. All MS data are available via ProteomeXchange with identifier PXD001464.Mass spectrometry based proteomic quantitation is an essential technique used for contemporary, integrative biological studies. Whether used in discovery experiments or for targeted biomarker applications, quantitative proteomic studies require high reproducibility at many levels. It requires reproducible run-to-run peptide detection, reproducible peptide quantitation, reproducible depth of proteome coverage, and ideally, a high degree of cross-laboratory analytical reproducibility. Mass spectrometry centered proteomics has evolved steadily over the past decade, now mature enough to derive extensive draft maps of the human proteome (1, 2). Nonetheless, a key requirement yet to be realized is to ensure that quantitative proteomics can be carried out in a timely manner while satisfying the aforementioned challenges associated with reproducibility. This is especially important for recent developments using data independent MS quantitation and multiple reaction monitoring on high-resolution MS (MRM-HR)¹ as they are both highly dependent on LC peptide retention time reproducibility and precursor detectability, while attempting to maximize proteome coverage (3). Strategies usually employed to increase the depth of proteome coverage utilize various sample fractionation methods including gel-based separation, affinity enrichment or depletion, protein or peptide chemical modification-based enrichment, and various peptide chromatography methods, particularly ion exchange chromatography (4–10). In comparison to an unfractionated “naive” sample, the trade-off in using these enrichments/fractionation approaches are higher risk of sample losses, introduction of undesired chemical modifications (e.g. oxidation, deamidation, N-terminal lactam formation), and the potential for result skewing and bias, as well as numerous time and human resources required to perform the sample preparation tasks. Online-coupled approaches aim to minimize those risks and address resource constraints. A widely practiced example of the benefits of online sample fractionation has been the decade long use of combining strong cation exchange chromatography (SCX) with C18 reversed-phase (RP) for peptide fractionation (known as MudPIT – multidimensional protein identification technology), where SCX and RP is performed under the same buffer conditions and the SCX elution performed with volatile organic cations compatible with reversed phase separation (11). This approach greatly increases analyte detection while avoiding sample handling losses. The MudPIT approach has been widely used for discovery proteomics (12–14), and we have previously shown that multiphasic separations also have utility for targeted proteomics when configured for selected reaction monitoring MS (SRM-MS). We showed substantial advantages of MudPIT-SRM-MS with reduced ion suppression, increased peak areas and lower limits of detection (LLOD) compared with conventional RP-SRM-MS (15).To improve the reproducibility of proteomic workflows, increase throughput and minimize sample loss, numerous microfluidic devices have been developed and integrated for proteomic applications (16, 17). These devices can broadly be classified into two groups: (1) microfluidic chips for peptide separation (18–25) and; (2) proteome reactors that combine enzymatic processing with peptide based fractionation (26–30). Because of the small dimension of these devices, they are readily able to integrate into nanoLC workflows. Various applications have been described including increasing proteome coverage (22, 27, 28) and targeting of phosphopeptides (24, 31, 32), glycopeptides and released glycans (29, 33, 34).In this work, we set out to take advantage of the benefits of multiphasic peptide separations and address the reproducibility needs required for high-throughput comparative proteomics using a variety of workflows. We integrated a multiphasic SCX and RP column in a “plug-and-play” microfluidic chip format for online fractionation, eliminating the need for users to make minimal dead volume connections between traps and columns. We show the flexibility of this format to provide robust peptide separation and reproducibility using conventional and topical mass spectrometry workflows. This was undertaken by coupling the multiphase liquid chromatography (LC) chip to a fast scanning Q-ToF mass spectrometer for data dependent MS/MS, data independent MS (SWATH) and for targeted proteomics using MRM-HR, showing clear advantages for repeatable analyses compared with conventional proteomic workflows.     

In-depth Characterization of the Cerebrospinal Fluid (CSF) Proteome Displayed Through the CSF Proteome Resource (CSF-PR)

In this study, the human cerebrospinal fluid (CSF) proteome was mapped using three different strategies prior to Orbitrap LC-MS/MS analysis: SDS-PAGE and mixed mode reversed phase-anion exchange for mapping the global CSF proteome, and hydrazide-based glycopeptide capture for mapping glycopeptides. A maximal protein set of 3081 proteins (28,811 peptide sequences) was identified, of which 520 were identified as glycoproteins from the glycopeptide enrichment strategy, including 1121 glycopeptides and their glycosylation sites. To our knowledge, this is the largest number of identified proteins and glycopeptides reported for CSF, including 417 glycosylation sites not previously reported. From parallel plasma samples, we identified 1050 proteins (9739 peptide sequences). An overlap of 877 proteins was found between the two body fluids, whereas 2204 proteins were identified only in CSF and 173 only in plasma. All mapping results are freely available via the new CSF Proteome Resource (http://probe.uib.no/csf-pr), which can be used to navigate the CSF proteome and help guide the selection of signature peptides in targeted quantitative proteomics.Cerebrospinal fluid (CSF)¹ surrounds and supports the central nervous system (CNS), including the ventricles and subarachnoid space (1). About 80% of the total protein amount in CSF derives from size-dependent filtration of blood across the blood-brain barrier (BBB), and the rest originate from drainage of interstitial fluid from the CNS (2–4). Because CSF is in direct contact with the CNS, it should be a promising source for finding biomarkers for diseases in the CNS (5).Mapping studies characterizing the human CSF proteome and peptidome has previously been carried out using various experimental designs, including both healthy and disease-affected individuals (5–16). A total of 2630 proteins were detected in normal CSF by immunoaffinity depletion of high abundant proteins followed by strong cation exchange fractionation and LC-MS (5), whereas proteome and peptidome analyses of human CSF (collected for diagnostic purposes and turned out normal) by gel separation and trypsin digestion followed by LC-MS analysis have shown 798 proteins and 563 peptide products (derived from 91 precursor proteins) (6). In another publication, Pan et al. combined several proteomics studies in CSF from both normal subjects and subjects with neurological diseases and created a dataset of 2594 identified proteins (16). But in general, the availability and usefulness of published data from proteome mapping experiments is scarce, and the format of the data often makes searching and comparison across datasets difficult. Thus, organizing the data in online databases would greatly benefit the scientific community by making the data more accessible and easier to query. Current online databases containing MS data for CSF include the Sys-BodyFluid, with a total of 1286 CSF proteins from six studies (17). The proteome identifications database (PRIDE) (18) includes 19 studies on human CSF, but none reporting more than 103 identified proteins.Glycosylation is one of the most common post-translational modifications (PTMs), and many known clinical biomarkers as well as therapeutic targets are glycoproteins (19–25). Furthermore, glycosylation plays important roles in cell communication, signaling, aging, and cell adhesion (26, 27). Nevertheless, there are few studies on glycoprotein identification in CSF. One study identified 216 glycoproteins in CSF using both lectin affinity and hydrazide chemistry (8), and another reported 36 N-linked and 44 O-linked glycosylation sites, from 23 and 22 glycoproteins respectively, by enriching for sialic-acid containing glycopeptides (28).Considering the sparse information about the CSF proteome available in public repositories, we have combined several proteomics approaches to create a map of the global CSF proteome, the CSF glycoproteome, and the respective plasma proteome from a pool of 21 (20 for the plasma pool) neurologically healthy individuals. The large amount of data generated through these four datasets (with linked and complementary information) would not easily be accessible through existing repositories. We therefore developed the open access CSF Proteome Resource (CSF-PR, www.probe.uib.no/csf-pr), an online database including the detailed data from the four different proteomics experiments described in this study. CSF-PR will be particularly useful in guiding the selection of appropriate signature peptides for the development of targeted CSF protein assays.