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.     

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.     

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.     

N-Terminal-oriented Proteogenomics of the Marine Bacterium Roseobacter Denitrificans Och114 using N-Succinimidyloxycarbonylmethyl)tris(2,4,6-trimethoxyphenyl)phosphonium bromide (TMPP) Labeling and Diagonal Chromatography

Given the ease of whole genome sequencing with next-generation sequencers, structural and functional gene annotation is now purely based on automated prediction. However, errors in gene structure are frequent, the correct determination of start codons being one of the main concerns. Here, we combine protein N termini derivatization using (N-Succinimidyloxycarbonylmethyl)tris(2,4,6-trimethoxyphenyl)phosphonium bromide (TMPP Ac-OSu) as a labeling reagent with the COmbined FRActional DIagonal Chromatography (COFRADIC) sorting method to enrich labeled N-terminal peptides for mass spectrometry detection. Protein digestion was performed in parallel with three proteases to obtain a reliable automatic validation of protein N termini. The analysis of these N-terminal enriched fractions by high-resolution tandem mass spectrometry allowed the annotation refinement of 534 proteins of the model marine bacterium Roseobacter denitrificans OCh114. This study is especially efficient regarding mass spectrometry analytical time. From the 534 validated N termini, 480 confirmed existing gene annotations, 41 highlighted erroneous start codon annotations, five revealed totally new mis-annotated genes; the mass spectrometry data also suggested the existence of multiple start sites for eight different genes, a result that challenges the current view of protein translation initiation. Finally, we identified several proteins for which classical genome homology-driven annotation was inconsistent, questioning the validity of automatic annotation pipelines and emphasizing the need for complementary proteomic data. All data have been deposited to the ProteomeXchange with identifier PXD000337.Recent developments in mass spectrometry and bioinformatics have established proteomics as a common and powerful technique for identifying and quantifying proteins at a very broad scale, but also for characterizing their post-translational modifications and interaction networks (1, 2). In addition to the avalanche of proteomic data currently being reported, many genome sequences are established using next-generation sequencing, fostering proteomic investigations of new cellular models. Proteogenomics is a relatively recent field in which high-throughput proteomic data is used to verify coding regions within model genomes to refine the annotation of their sequences (2–8). Because genome annotation is now fully automated, the need for accurate annotation for model organisms with experimental data is crucial. Many projects related to genome re-annotation of microorganisms with the help of proteomics have been recently reported, such as for Mycoplasma pneumoniae (9), Rhodopseudomonas palustris (10), Shewanella oneidensis (11), Thermococcus gammatolerans (12), Deinococcus deserti (13), Salmonella thyphimurium (14), Mycobacterium tuberculosis (15, 16), Shigella flexneri (17), Ruegeria pomeroyi (18), and Candida glabrata (19), as well as for higher organisms such as Anopheles gambiae (20) and Arabidopsis thaliana (4, 5).The most frequently reported problem in automatic annotation systems is the correct identification of the translational start codon (21–23). The error rate depends on the primary annotation system, but also on the organism, as reported for Halobacterium salinarum and Natromonas pharaonis (24), Deinococcus deserti (21), and Ruegeria pomeroyi (18), where the error rate is estimated above 10%. Identification of a correct translational start site is essential for the genetic and biochemical analysis of a protein because errors can seriously impact subsequent biological studies. If the N terminus is not correctly identified, the protein will be considered in either a truncated or extended form, leading to errors in bioinformatic analyses (e.g. during the prediction of its molecular weight, isoelectric point, cellular localization) and major difficulties during its experimental characterization. For example, a truncated protein may be heterologously produced as an unfolded polypeptide recalcitrant to structure determination (25). Moreover, N-terminal modifications, which are poorly documented in annotation databases, may occur (26, 27).Unfortunately, the poor polypeptide sequence coverage obtained for the numerous low abundance proteins in current shotgun MS/MS proteomic studies implies that the overall detection of N-terminal peptides obtained in proteogenomic studies is relatively low. Different methods for establishing the most extensive list of protein N termini, grouped under the so-called “N-terminomics” theme, have been proposed to selectively enrich or improve the detection of these peptides (2, 28, 29). Large N-terminome studies have recently been reported based on resin-assisted enrichment of N-terminal peptides (30) or terminal amine isotopic labeling of substrates (TAILS) coupled to depletion of internal peptides with a water-soluble aldehyde-functionalized polymer (31–35). Among the numerous N-terminal-oriented methods (2), specific labeling of the N terminus of intact proteins with N-tris(2,4,6-trimethoxyphenyl)phosphonium acetyl succinamide (TMPP-Ac-OSu)¹ has proven reliable (21, 36–39). TMPP-derivatized N-terminal peptides have interesting properties for further LC-MS/MS mass spectrometry: (1) an increase in hydrophobicity because of the trimethoxyphenyl moiety added to the peptides, increasing their retention times in reverse phase chromatography, (2) improvement of their ionization because of the introduction of a positively charged group, and (3) a much simpler fragmentation pattern in tandem mass spectrometry. Other reported approaches rely on acetylation, followed by trypsin digestion, and then biotinylation of free amino groups (40); guanidination of lysine lateral chains followed by N-biotinylation of the N termini and trypsin digestion (41); or reductive amination of all free amino groups with formaldehyde preceeding trypsin digestion (42). Recently, we applied the TMPP method to the proteome of the Deinococcus deserti bacterium isolated from upper sand layers of the Sahara desert (13). This method enabled the detection of N-terminal peptides allowing the confirmation of 278 translation initiation codons, the correction of 73 translation starts, and the identification of non-canonical translation initiation codons (21). However, most TMPP-labeled N-terminal peptides are hidden among the more abundant internal peptides generated after proteolysis of a complex proteome, precluding their detection. This results in disproportionately fewer N-terminal validations, that is, 5 and 8% of total polypeptides coded in the theoretical proteomes of Mycobacterium smegmatis (37) and Deinococcus deserti (21) with a total of 342 and 278 validations, respectively.An interesting chromatographic method to fractionate peptide mixtures for gel-free high-throughput proteome analysis has been developed over the last years and applied to various topics (43, 44). This technique, known as COmbined FRActional DIagonal Chromatography (COFRADIC), uses a double chromatographic separation with a chemical reaction in between to change the physico-chemical properties of the extraneous peptides to be resolved from the peptides of interest. Its previous applications include the separation of methionine-containing peptides (43), N-terminal peptide enrichment (45, 46), sulfur amino acid-containing peptides (47), and phosphorylated peptides (48). COFRADIC was identified as the best method for identification of N-terminal peptides of two archaea, resulting in the identification of 240 polypeptides (9% of the theoretical proteome) for Halobacterium salinarum and 220 (8%) for Natronomonas pharaonis (24).Taking advantage of both the specificity of TMPP labeling, the resolving power of COFRADIC for enrichment, and the increase in information through the use of multiple proteases, we performed the proteogenomic analysis of a marine bacterium from the Roseobacter clade, namely Roseobacter denitrificans OCh114. This novel approach allowed us to validate and correct 534 unique proteins (13% of the theoretical proteome) with TMPP-labeled N-terminal signatures obtained using high-resolution tandem mass spectrometry. We corrected 41 annotations and detected five new open reading frames in the R. denitrificans genome. We further identified eight distinct proteins showing direct evidence for multiple start sites.     

Vascular Endothelial Growth Factor (VEGF) and Platelet (PF-4) Factor 4 Inputs Modulate Human Microvascular Endothelial Signaling in a Three-Dimensional Matrix Migration Context

The process of angiogenesis is under complex regulation in adult organisms, particularly as it often occurs in an inflammatory post-wound environment. As such, there are many impacting factors that will regulate the generation of new blood vessels which include not only pro-angiogenic growth factors such as vascular endothelial growth factor, but also angiostatic factors. During initial postwound hemostasis, a large initial bolus of platelet factor 4 is released into localized areas of damage before progression of wound healing toward tissue homeostasis. Because of its early presence and high concentration, the angiostatic chemokine platelet factor 4, which can induce endothelial anoikis, can strongly affect angiogenesis. In our work, we explored signaling crosstalk interactions between vascular endothelial growth factor and platelet factor 4 using phosphotyrosine-enriched mass spectrometry methods on human dermal microvascular endothelial cells cultured under conditions facilitating migratory sprouting into collagen gel matrices. We developed new methods to enable mass spectrometry-based phosphorylation analysis of primary cells cultured on collagen gels, and quantified signaling pathways over the first 48 h of treatment with vascular endothelial growth factor in the presence or absence of platelet factor 4. By observing early and late signaling dynamics in tandem with correlation network modeling, we found that platelet factor 4 has significant crosstalk with vascular endothelial growth factor by modulating cell migration and polarization pathways, centered around P38α MAPK, Src family kinases Fyn and Lyn, along with FAK. Interestingly, we found EphA2 correlational topology to strongly involve key migration-related signaling nodes after introduction of platelet factor 4, indicating an influence of the angiostatic factor on this ambiguous but generally angiogenic signal in this complex environment.Angiogenesis, the formation of blood vessels from pre-existing blood vessels, is a complex process essential for repairing injured tissue or supporting tissue growth. A great deal of work has been done to focus on understanding this phenomenon as it occurs in vivo, in particular with regard to its roles in embryonic development (1–5). In contrast to embryonic development, adult angiogenesis and inflammation are closely related phenomena that occur in vivo in a number of physiologically relevant processes. Inflammation lies at the crux of multiple physiological events in biological systems that precede the induction of angiogenesis: wound healing (6–8), chronic wounds (8), inflammatory disorders (9, 10), and cancer (9, 11, 12).Inflammatory reactions also confound tissue engineered implantable three-dimensional constructs that provide innovative clinical treatments of various diseases and injuries (13–17). As complex tissues become developed for applications in clinical trials, tissue vascularization for constructs of considerable size and volume is required for their survival (18, 19). Once implanted, these constructs will also experience significant inflammatory responses within their host''s local milieu (20, 21). These circumstances demonstrate the necessity for understanding the interactions between inflammation and angiogenesis, such as the development of predictive models (22). Elucidating specific intracellular mechanisms can provide insight for novel approaches in treatment of diseases as well as predicting responses to artificially engineered tissues.Recently, studies have shown that chemokines, which play a central role in inflammation, can influence the outcomes of angiogenesis (23–26) by promoting new blood vessel growth (e.g. CXCL1–3, CXCL5–8, CXCL12) or inhibiting its formation altogether (e.g. CXCL4, CXCL9–11, CXCL13) (26). In particular, a large body of information is available on platelet factor 4 (PF-4/CXCL4) and its ability to inhibit and even induce regression of angiogenesis. PF-4 is found throughout the adult body, at roughly 0.25–1.25 nm (2–10 ng/ml) in blood plasma, but as high as 25 μm in localized areas during wound healing (27, 28). Its ubiquitous presence, implication in cancer and vascular diseases, and use as a potential drug therapy have made PF-4 a key point of interest in influencing angiogenesis in vivo (27–30). In addition to inducing angiostasis, PF-4 can inhibit cell proliferation by halting S phase progression and reducing endothelial cell migration (25, 28, 30–32). Despite the wealth of information on PF-4 and its mechanistic effects on immune cells, scarce literature exists on the nature of the molecular signaling with endothelial cells to inhibit angiogenesis. Furthermore, the complexity of PF-4 mediated signaling and its potential to interact through multiple binding mechanisms makes it difficult to determine how PF-4 can interfere with angiogenesis (28, 29, 33, 34). Possible angiogenic signaling network interference mechanisms for PF-4 include the sequestration of growth factors and proteoglycans, antagonism of integrin-mediated signaling, or direct signaling through its chemokine receptor CXCR3, all of which have supporting evidence in previous literature (28). Along with the multiple mechanisms PF-4 may utilize for signaling, only limited studies on direct signaling elicited by PF-4 on endothelial cells have been reported; one of interest found that P38 MAPK can be activated via CXCR3 on endothelial cells cultured on plastic (35), whereas another, more definitive study showed PF-4 acting similarly to other CXCR3 ligands in activating PKA to prevent m-calpain-mediated rear de-adhesion of moving cells (36, 37). Furthermore, PF-4 could have variable sensitivities in different endothelial cell types because of heterogeneous expression of CXCR3 (38).In our study, we sought to develop an approach to assess network-level signaling interactions between PF-4 and the major angiogenic inducer vascular endothelial growth factor (VEGF)¹ within a contextually relevant 3-D angiogenesis platform, in a controlled environment to understand what role these two factors may play. We developed methods to reduce extracellular matrix contamination in our samples and were able to successfully use a two-step lysis method with a MS compatible detergent-based lysis buffer. By taking advantage of iTRAQ-based multiplexed quantitation, we were able to collect quantitative phosphoprotein signaling data from our system with early and late temporal resolution. Using correlation network methods to observe differences in our system, we found that simultaneous treatment with PF-4 and VEGF induced changes in migrational pathway topology when compared with VEGF treatment alone. Most often, these changes appeared as losses in correlations between different migrational signaling proteins. We found that several different signaling pathways involved with migration were affected, including central proteins P38α MAPK, focal adhesion kinase (FAK), and Src family kinases. Furthermore, we found statistically significant differences in tyrosine phosphorylation when HDMVECs were stimulated with VEGF and PF-4, as opposed to only VEGF. In addition, we were able to recapitulate previously reported findings on how PF-4 infers its angiostatic effects on endothelial cells. Surprisingly, our data set revealed EphA2 receptor as a central node for PF-4 signaling, indicating that it may possess a complementary role in the balance of angiogenic and angiostatic effects.To our knowledge, this is the first attempt at performing MS-based analysis of phosphotyrosine signaling networks within the context of an environment that is amenable to angiogenesis. Our work provides a step forward in applying high throughput and systems-level phosphoproteomics data collection to more physiologically relevant experimental conditions.     

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]     

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]     

The Effect of Proteasome Inhibition on the Generation of the Human Leukocyte Antigen (HLA) Peptidome

The Major histocompatibility complex (MHC) class I peptidome is thought to be generated mostly through proteasomal degradation of cellular proteins, a notion that is based on the alterations in presentation of selected peptides following proteasome inhibition. We evaluated the effects of proteasome inhibitors, epoxomicin and bortezomib, on human cultured cancer cells. Because the inhibitors did not reduce the level of presentation of the cell surface human leukocyte antigen (HLA) molecules, we followed their effects on the rates of synthesis of both HLA peptidome and proteome of the cells, using dynamic stable isotope labeling in tissue culture (dynamic-SILAC). The inhibitors reduced the rates of synthesis of most cellular proteins and HLA peptides, yet the synthesis rates of some of the proteins and HLA peptides was not decreased by the inhibitors and of some even increased. Therefore, we concluded that the inhibitors affected the production of the HLA peptidome in a complex manner, including modulation of the synthesis rates of the source proteins of the HLA peptides, in addition to their effect on their degradation. The collected data may suggest that the current reliance on proteasome inhibition may overestimate the centrality of the proteasome in the generation of the MHC peptidome. It is therefore suggested that the relative contribution of the proteasomal and nonproteasomal pathways to the production of the MHC peptidome should be revaluated in accordance with the inhibitors effects on the synthesis rates of the source proteins of the MHC peptides.The repertoires and levels of peptides, presented by the major histocompatibility complex (MHC)¹ class I molecules at the cells'' surface, are modulated by multiple factors. These include the rates of synthesis and degradation of their source proteins, the transport efficacy of the peptides through the transporter associated with antigen processing (TAP) into the endoplasmic reticulum (ER), their subsequent processing and loading onto the MHC molecules within the ER, and the rates of transport of the MHC molecules with their peptide cargo to the cell surface. The off-rates of the presented peptides, the residence time of the MHC complexes at the cell surface, and their retrograde transport back into the cytoplasm, influence, as well, the presented peptidomes (reviewed in (1)). Even though significant portions of the MHC class I peptidomes are thought to be derived from newly synthesized proteins, including misfolded proteins, defective ribosome products (DRiPs), and short lived proteins (SLiPs), most of the MHC peptidome is assumed to originate from long-lived proteins, which completed their functional cellular roles or became defective (retirees), (reviewed in (2)).The main protease, supplying the MHC peptidome production pipeline, is thought to be the proteasome (3). It is also responsible for generation of the final carboxyl termini of the MHC peptides (4), (reviewed in (5)). The final trimming of the n-termini of the peptides, within the endoplasmic reticulum (ER), is thought to be performed by amino peptidases, such as ERAP1/ERAAP, which fit the peptides into their binding groove on the MHC molecules (6) (reviewed in (7)). Nonproteasomal proteolytic pathways were also suggested as possible contributors to the MHC peptidome, including proteolysis by the ER resident Signal peptide peptidase (8, 9), the cytoplasmic proteases Insulin degrading enzyme (10), Tripeptidyl peptidase (11–13), and a number of proteases within the endolysosome pathway (reviewed recently in (14–17)). In contrast to the mostly cytoplasmic and ER production of the MHC class I peptidome, the class II peptidome is produced in a special compartment, associated with the endolysosome pathway (18–20). This pathway is also thought to participate in the cross presentation of class I peptides, derived from proteins up-taken by professional antigen presenting cells (21), (reviewed in (15–17, 22)).The centrality of the proteasomes in the generation of the MHC peptidome was deduced mostly from the observed change in presentation levels of small numbers of selected peptides, following proteasome inhibition (3, 23). Even the location of some of the genes encoding the catalytic subunits of the immunoproteasome (LMP2 and LMP7) (24) within the MHC class II genomic locus, was suggested to support the involvement of the proteasome in the generation of the MHC class I peptidome (25). Similar conclusions were deduced from alterations in peptide presentation, following expression of the catalytic subunits of the immunoproteasome (26), (reviewed in (5)). Yet, although most of the reports indicated reductions in presentation of selected peptides by proteasome inhibition (3, 27–29), others have observed only limited, and sometimes even opposite effects (23, 30–32).The matter is further complicated by the indirect effects of proteasome inhibition used for such studies on the arrest of protein synthesis by the cells (33–35), on the transport rates of the MHC molecules to the cell surface, and on their retrograde transport back to the vesicular system (36) (reviewed in (37)). Proteasome inhibition likely causes shortage of free ubiquitin, reduced supply of free amino acids, and induces an ER unfolded protein response (UPR), which signals the cells to block most (but not all) cellular protein synthesis (reviewed in (38)). Because a significant portion of the MHC peptidome originates from degradation of DRiPs and SLiPs (reviewed in (2)), arrest of new protein synthesis should influence the presentation of their derived MHC peptides. Taken together, these arguments may suggest that merely following the changes in the presentation levels of the MHC molecules, or even of specific MHC peptides, after proteasome inhibition, does not provide the full picture for deducing the relative contribution of the proteasomal pathway to the production of the MHC peptidome (reviewed in (7)).MHC peptidome analysis can be performed relatively easily by modern capillary chromatography combined with mass spectrometry (reviewed in (39)). The peptides are recovered from immunoaffinity purified MHC molecules after detergent solubilization of the cells (40, 41), from soluble MHC molecules secreted to the cells'' growth medium (42, 43) or from patients'' plasma (44). The purified peptides pools are resolved by capillary chromatography and the individual peptides are identified and quantified by tandem mass spectrometry (40), (reviewed in (45–47)). In cultured cells, quantitative analysis can also be followed by metabolic incorporation of stable isotope labeled amino acids (SILAC) (48). Furthermore, the rates of de novo synthesis of both MHC peptides and their proteins of origin can be followed using the dynamic-SILAC proteomics approach (49) with its further adaptation to HLA peptidomics (50–52).This study attempts to define the relative contribution of the proteasomes to the production of HLA class I peptidome by simultaneously following the effects of proteasome inhibitors, epoxomicin and bortezomib (Velcade), on the rates of de novo synthesis of both the HLA class I peptidome and the cellular proteome of the same MCF-7 human breast cancer cultured cells. The proteasome inhibitors did not reduce the levels of HLA presentations, yet affected the rates of production of both the HLA peptidome and cellular proteome, mostly decreasing, but also increasing some of the synthesis rates of the HLA peptides and cellular proteins. Thus, we suggest that the degree of contribution of the proteasomal pathway to the production of the HLA-I peptidome should be re-evaluated in accordance with their effects on the entire HLA class-I peptidome, while taking into consideration the inhibitors'' effects on the synthesis (and degradation) rates of the source proteins of each of the studied HLA peptides.     

Matricellular Protein CCN3 (NOV) Regulates Actin Cytoskeleton Reorganization

CCN3 (NOV), a putative ligand for integrin receptors, is tightly associated with the extracellular matrix and mediates diverse cellular functions, including cell adhesion and proliferation. CCN3 has been shown to negatively regulate growth although it promotes migration in a cell type-specific manner. In this study, overexpression of CCN3 reduces growth and increases intercellular adhesion of breast cancer cells. Interestingly, CCN3 overexpression also led to the formation of multiple pseudopodia that are enriched in actin, CCN3, and vinculin. Breast cancer cells preincubated with exogenous CCN3 protein also induced the same phenotype, indicating that secreted CCN3 is sufficient to induce changes in cell morphology. Surprisingly, extracellular CCN3 is internalized to the early endosomes but not to the membrane protrusions, suggesting pseudopodia-enriched CCN3 may derive from a different source. The presence of an intracellular variant of CCN3 will be consistent with our finding that the cytoplasmic tail of the gap junction protein connexin43 (Cx43) associates with CCN3. Cx43 is a channel protein permitting intercellular communication to occur. However, neither the channel properties nor the protein levels of Cx43 are affected by the CCN3 protein. In contrast, CCN3 proteins are down-regulated in the absence of Cx43. Finally, we showed that overexpression of CCN3 increases the activity of the small GTPase Rac1, thereby revealing a pathway that links Cx43 directly to actin reorganization.The CCN (CYR61/Connective Tissue Growth Factor/Nephroblastoma Overexpressed) family of multimodular proteins mediates diverse cellular functions, including cell adhesion, migration, and proliferation (1–3). Overexpression of CCN3, one of the founding members of the family, inhibits proliferation in most types of tumors such as glioblastoma and Ewing sarcoma (4, 5). Similarly, down-regulation of CCN3 has been suggested to promote melanoma progression (6). On the other hand, CCN3 can also promote migration in sarcoma and glioblastoma (4, 7), although a separate study shows that it decreases the invasion of melanoma (6). Therefore, in contrast to its role in growth suppression, the role of CCN3 signaling in cell motility is less clear.Most evidence suggests CCN3 mediates its effects by binding to the integrin proteins, such as the αVβ3 receptors (8, 9), and that CCN3 alters cell adhesion in an integrin-dependent fashion (4, 10). In melanocytes, the discoidin domain receptor 1 mediates CCN3-dependent adhesion (11). CCN3 has also been observed to associate with Notch1 (12), fibulin 1C (13), S100A4 (14), and the gap junction protein Cx43³ (15, 16), suggesting that CCN3 may also modulate cell growth via non-integrin signaling pathways.Gap junction proteins are best known for forming channels between cells, contributing to intercellular communication by allowing the exchange of small ions and molecules (17, 18). Consequently, attenuated intercellular communication has been implicated in promoting carcinogenesis (19, 20). Recent evidence has indicated that connexins can mediate channel-independent growth control through interaction of their C-terminal cytoplasmic tail with various intracellular signaling molecules (21–23). In addition, many Cx43-interacting proteins, including ZO-1 (zonula occludens-1) (24), Drebrin (25), and N-cadherin (26) associate with F-actin, thus placing Cx43 in close proximity to the actin cytoskeleton.In this study, we show for the first time that CCN3 reorganizes the actin cytoskeleton of the breast cancer cells MDA-MB-231 with the formation of multiple cell protrusions, possibly by activating the small GTPase Rac1. Our results also suggest an alternative route by which Cx43 may be functionally linked to actin cytoskeletal signaling via CCN3.     

A Ca2+ Release-activated Ca2+ (CRAC) Modulatory Domain (CMD) within STIM1 Mediates Fast Ca2+-dependent Inactivation of ORAI1 Channels

STIM1 and ORAI1, the two limiting components in the Ca²⁺ release-activated Ca²⁺ (CRAC) signaling cascade, have been reported to interact upon store depletion, culminating in CRAC current activation. We have recently identified a modulatory domain between amino acids 474 and 485 in the cytosolic part of STIM1 that comprises 7 negatively charged residues. A STIM1 C-terminal fragment lacking this domain exhibits enhanced interaction with ORAI1 and 2–3-fold higher ORAI1/CRAC current densities. Here we focused on the role of this CRAC modulatory domain (CMD) in the fast inactivation of ORAI1/CRAC channels, utilizing the whole-cell patch clamp technique. STIM1 mutants either with C-terminal deletions including CMD or with 7 alanines replacing the negative amino acids within CMD gave rise to ORAI1 currents that displayed significantly reduced or even abolished inactivation when compared with STIM1 mutants with preserved CMD. Consistent results were obtained with cytosolic C-terminal fragments of STIM1, both in ORAI1-expressing HEK 293 cells and in RBL-2H3 mast cells containing endogenous CRAC channels. Inactivation of the latter, however, was much more pronounced than that of ORAI1. The extent of inactivation of ORAI3 channels, which is also considerably more prominent than that of ORAI1, was also substantially reduced by co-expression of STIM1 constructs missing CMD. Regarding the dependence of inactivation on Ca²⁺, a decrease in intracellular Ca²⁺ chelator concentrations promoted ORAI1 current fast inactivation, whereas Ba²⁺ substitution for extracellular Ca²⁺ completely abrogated it. In summary, CMD within the STIM1 cytosolic part provides a negative feedback signal to Ca²⁺ entry by triggering fast Ca²⁺-dependent inactivation of ORAI/CRAC channels.The Ca²⁺ release-activated Ca²⁺ (CRAC)⁵ channel is one of the best characterized store-operated entry pathways (1–7). Substantial efforts have led to identification of two key components of the CRAC channel machinery: the stromal interaction molecule 1 (STIM1), which is located in the endoplasmic reticulum and acts as a Ca²⁺ sensor (8–10), and ORAI1/CRACM1, the pore-forming subunit of the CRAC channel (11–13). Besides ORAI1, two further homologues named ORAI2 and ORAI3 belong to the ORAI channel family (12, 14).STIM1 senses endoplasmic reticulum store depletion primarily by its luminal EF-hand in its N terminus (8, 15), redistributes close to the plasma membrane, where it forms puncta-like structures, and co-clusters with ORAI1, leading to inward Ca²⁺ currents (12, 16–19). The STIM1 C terminus, located in the cytosol, contains two coiled-coil regions overlapping with an ezrin-radixin-moesin (ERM)-like domain followed by a serine/proline- and a lysine-rich region (2, 8, 20–22). Three recent studies have described the essential ORAI-activating region within the ERM domain, termed SOAR (Stim ORAI-activating region) (23), OASF (ORAI-activating small fragment) (24), and CAD (CRAC-activating domain) (25), including the second coiled coil domain and the following ∼55 amino acids. We and others have provided evidence that store depletion leads to a dynamic coupling of STIM1 to ORAI1 (26–28) that is mediated by a direct interaction of the STIM1 C terminus with ORAI1 C terminus probably involving the putative coiled-coil domain in the latter (27).Furthermore, different groups have proven that the C terminus of STIM1 is sufficient to activate CRAC as well as ORAI1 channels independent of store depletion (22–25, 27, 29). We have identified that OASF-(233–474) or shorter fragments exhibit further enhanced coupling to ORAI1 resulting in 3-fold increased constitutive Ca²⁺ currents. A STIM1 fragment containing an additional cluster of anionic amino acids C-terminal to position 474 displays weaker interaction with ORAI1 as well as reduced Ca²⁺ current comparable with that mediated by wild-type STIM1 C terminus. Hence, we have suggested that these 11 amino acids (474–485) act in a modulatory manner onto ORAI1; however, their detailed mechanistic impact within the STIM1/ORAI1 signaling machinery has remained so far unclear.In this study, we focused on the impact of this negative cluster on fast inactivation of STIM1-mediated ORAI Ca²⁺ currents. Lis et al. (30) have shown that all three ORAI homologues display distinct inactivation profiles, where ORAI2 and ORAI3 show a much more pronounced fast inactivation than ORAI1. Moreover, it has been reported (31) that different expression levels of STIM1 to ORAI1 affect the properties of CRAC current inactivation. Yamashita et al. (32) have demonstrated a linkage between the selectivity filter of ORAI1 and its Ca²⁺-dependent fast inactivation. Here we provide evidence that a cluster of acidic residues within the C terminus of STIM1 is involved in the fast inactivation of ORAI1 and further promotes that of ORAI3 and native CRAC currents.