Activin A Suppresses Osteoblast Mineralization Capacity by Altering Extracellular Matrix (ECM) Composition and Impairing Matrix Vesicle (MV) Production

During bone formation, osteoblasts deposit an extracellular matrix (ECM) that is mineralized via a process involving production and secretion of highly specialized matrix vesicles (MVs). Activin A, a transforming growth factor-β (TGF-β) superfamily member, was previously shown to have inhibitory effects in human bone formation models through unclear mechanisms. We investigated these mechanisms elicited by activin A during in vitro osteogenic differentiation of human mesenchymal stem cells (hMSC). Activin A inhibition of ECM mineralization coincided with a strong decline in alkaline phosphatase (ALP¹) activity in extracellular compartments, ECM and matrix vesicles. SILAC-based quantitative proteomics disclosed intricate protein composition alterations in the activin A ECM, including changed expression of collagen XII, osteonectin and several cytoskeleton-binding proteins. Moreover, in activin A osteoblasts matrix vesicle production was deficient containing very low expression of annexin proteins. ECM enhanced human mesenchymal stem cell osteogenic development and mineralization. This osteogenic enhancement was significantly decreased when human mesenchymal stem cells were cultured on ECM produced under activin A treatment. These findings demonstrate that activin A targets the ECM maturation phase of osteoblast differentiation resulting ultimately in the inhibition of mineralization. ECM proteins modulated by activin A are not only determinant for bone mineralization but also possess osteoinductive properties that are relevant for bone tissue regeneration.The quality of bone tissue is determined by the balanced action of the anabolic bone cells, the osteoblasts, and their catabolic counterparts, the osteoclasts. This process of bone remodeling occurs throughout life and can be influenced by a wide variety of molecules, having ultimately an impact on the quality of bone (1, 2). Activins and inhibins are members of the TGF-β superfamily with predominant antagonistic effects in their classically known target tissues, such as in gonadotropin producing cells in the pituitary and their role in reproduction (3, 4). Like other TGF-β member, activins elicit biological responses by binding to type I and II serine/threonine kinase receptors at the cell surface. Upon ligand binding, signaling is further transduced in the cytoplasm by phosphorylated Smad protein complexes that once in the nucleus regulate gene expression. This signaling pathway is highly complex because of crosstalk between different ligands (Activins, BMPs, TGF-β) binding to multiple serine/threonine kinase receptors that activate different Smad proteins signaling to the nucleus. Activin is known to signal using type II receptors ACVR2A or ACVR2B and the type I receptor ACVRIB (shared with BMPs) activating Smad2 and 3 proteins (shared with TGF-β). Inhibins exert their inhibitory effects on activin by competitive binding to the activin receptors in the presence of betaglycan. This signaling regulates a wide array of biological activities from cell proliferation, differentiation to tumor development and endocrine signaling (5, 6) in many cell lineages like hematopoietic (7, 8) and monocyte/macrophage (9, 10). Several consequences of these reproductive hormones, especially those of activin A, are also described in relation to bone metabolism. Activin A is present in bone tissue (11, 12) affecting both osteoclasts and osteoblasts. While having a consistent pro-osteoclastogenic effect (9, 13), the activin A impact on osteoblast differentiation is more controversial (see (14) for review) Several reports support a stimulatory effect of activin A on osteoblast differentiation and mineralization in vitro and in vivo (9, 15, 16). On the other hand, two different studies, using rat and human bone formation models, have demonstrated that activin A treatment has a coherent inhibitory influence on osteogenesis leading to significant reduction of the mineralization capacity (11, 17). These opposing effects of activin A on osteoblastogenesis may simply reflect species differences, however, it may be also driven by heterogeneity of the used cell model or the stage of osteoblast differentiation (14). Nevertheless, a negative role of activin A in bone formation is also supported by other in vivo studies in mice and primates in which blockage of activin signaling resulted in increased bone mass (18, 19). Moreover, transgenic mice overexpressing human inhibin A showed increased bone formation (20).The extracellular compartment is crucial for bone because it determines most of the bone quality properties (21, 22), including its strength, stability, and integrity. Interestingly, a mature extracellular matrix (ECM) is characterized by the capacity to mineralize even in the absence of further osteoblast activity (11, 23). This biomineralization process is complex and not fully elucidated but it is thought to be started within MVs (24). Osteoblasts in bone and other cells in mineralization competent tissues, such as cartilage (25), tendon (26), teeth (27), and calcifying vasculature (28) produce and release from their plasma membrane these vesicles with diameters ranging between 50 and 200 nm. It is inside these membrane-enclosed particles that first crystals of mineral are formed and grow, before the vesicle membrane is permeated and the mineral crystallization advances into the ECM (29, 30). In this context, proteins that can mobilize calcium and inorganic phosphate (Pi), the backbone of the hydroxyapatite crystals present in bone, are of utmost importance. P_i donor proteins found in MVs include alkaline phosphatase (ALP) and inorganic pyrophosphatases (31) whereas the annexin family of proteins is postulated to be crucial for calcium influx into the vesicles (32–34).In this study we investigated the inhibitory effect of activin A on human mesenchymal stem cells (hMSC) derived osteoblast differentiation and mineralization. We have previously shown that in human osteoblast cultures activin A influences the expression of many ECM genes altering ECM maturity (11). Thus, we focused our analysis on extracellular environment changes, namely the ECM and matrix vesicles (MVs). The characterization of these compartments was done using the state-of-the-art quantitative proteomics tools including SILAC metabolic labeling and mass spectrometry. Furthermore, the importance of ECM composition for osteoblast differentiation was also determined.     

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]     

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.     

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]     

Quantitative Proteomics of the Neisseria Gonorrhoeae Cell Envelope and Membrane Vesicles for the Discovery of Potential Therapeutic Targets

Neisseria gonorrhoeae (GC) is a human-specific pathogen, and the agent of a sexually transmitted disease, gonorrhea. There is a critical need for new approaches to study and treat GC infections because of the growing threat of multidrug-resistant isolates and the lack of a vaccine. Despite the implied role of the GC cell envelope and membrane vesicles in colonization and infection of human tissues and cell lines, comprehensive studies have not been undertaken to elucidate their constituents. Accordingly, in pursuit of novel molecular therapeutic targets, we have applied isobaric tagging for absolute quantification coupled with liquid chromatography and mass spectrometry for proteome quantitative analyses. Mining the proteome of cell envelopes and native membrane vesicles revealed 533 and 168 common proteins, respectively, in analyzed GC strains FA1090, F62, MS11, and 1291. A total of 22 differentially abundant proteins were discovered including previously unknown proteins. Among those proteins that displayed similar abundance in four GC strains, 34 were found in both cell envelopes and membrane vesicles fractions. Focusing on one of them, a homolog of an outer membrane protein LptD, we demonstrated that its depletion caused loss of GC viability. In addition, we selected for initial characterization six predicted outer membrane proteins with unknown function, which were identified as ubiquitous in the cell envelopes derived from examined GC isolates. These studies entitled a construction of deletion mutants and analyses of their resistance to different chemical probes. Loss of NGO1985, in particular, resulted in dramatically decreased GC viability upon treatment with detergents, polymyxin B, and chloramphenicol, suggesting that this protein functions in the maintenance of the cell envelope permeability barrier. Together, these findings underscore the concept that the cell envelope and membrane vesicles contain crucial, yet under-explored determinants of GC physiology, which may represent promising targets for designing new therapeutic interventions.Neisseria gonorrhoeae (GC)¹ is an obligate human pathogen and the etiological agent of gonorrhea, a sexually transmitted disease. GC infection remains a significant health and economic burden worldwide (1). It is also the second most commonly reported infectious disease in the United States (2). Gonorrhea ranges from clinically asymptomatic to local genital infections to disseminated bloodstream infections. Asymptomatic infections often have devastating consequences on women''s health including pelvic inflammatory disease, ectopic pregnancy, and infertility (3). Additionally, GC infections facilitate transmission and acquisition of HIV (4). For all of these reasons it is critical to provide effective treatments against gonorrhea. Currently, a dual therapy with cephalosporin and either azithromycin or doxycycline is recommended (5). However, over the past several years treatment failures associated with GC strains displaying decreased susceptibility to extended spectrum cephalosporins have been reported from various parts of the world (6–9). This is especially concerning because no other antibiotics are clinically useful in these cases, and because no appropriate vaccine exists (10). The escalating problem of the spread of antimicrobial resistance in GC, and the importance of the development of new approaches to study, treat, and prevent GC infection, have been recognized by the World Health Organization and by the Centers for Disease Control and Prevention (11, 12).We propose that largely unexplored proteins localized to bacterial cell envelope and naturally released membrane vesicles are particularly promising as potential novel molecular targets for therapeutic interventions against gonorrhea. The small fraction of known components of the GC cell envelope (outer membrane, periplasm, cytoplasmic membrane) plays a fundamental role in establishing infection by enabling the microbes to adhere to and invade host cells, facilitating nutrient acquisition, host tissue destruction, and suppression of immune responses (3, 13–15). Further, GC, like many other Gram-negative bacteria, produces membrane vesicles (MVs), which are nano-sized bilayered proteolipids (16). Naturally produced MVs are potentially an effective way to deliver toxins, enzymes, and other effectors to host tissues. Additionally, evidence from various studies support that MVs participate in intercellular communication and horizontal gene transfer (16–21). In GC, MVs are necessary for biofilm formation, which is thought to play an important role in asymptomatic infection in women, resistance to antimicrobial agents, and suppression of host immune defenses (22–24). MVs may also contribute to the serum resistance by providing an enhanced ability to bind and eliminate bactericidal factors (17).Although the potential importance of proteins localized to the GC cell envelope and MVs has been reported previously (25, 26), only two proteomic studies have been published addressing GC membrane composition (27, 28). Most studies have focused on extensive characterization of factors involved in direct host cell interaction: protruding surface proteins (pili), outer membrane adhesins Opa, porins P.IA and P.IB, lipooligosaccharide, and several iron utilization proteins (3, 4, 15, 29–32). Many of these vital virulence factors undergo phase and/or antigenic variation, making them poor drug or vaccine targets. Therefore, the pursuit for novel and constitutively expressed proteins—therapeutic targets in GC—is of utmost importance.Accordingly, in this study we applied global and unbiased proteomics to compare the composition of both the cell envelopes and MVs isolated from four GC strains: FA1090, F62, MS11, and 1291. Specifically, we used isotope tagging for relative and absolute quantification (iTRAQ) coupled with multidimensional liquid chromatography and tandem mass spectrometry (2D-LC/MS/MS). This approach allowed us to determine a uniformly and differentially expressed repertoire of proteins. Focusing on a homolog of LPS transport protein, LptD (OstA, Imp), which was identified in both the cell envelopes and MVs fractions, and ubiquitously expressed among analyzed strains, we showed that its depletion led to loss of GC viability. Finally, we selected for initial characterization six predicted outer membrane proteins, which were present at similar levels in the GC cell envelopes. We generated Δngo1344, Δngo1955, Δngo1985, Δngo2111, Δngo2121, and Δngo2139 mutant strains and examined their sensitivity toward different cell envelope-perturbing agents as well as chloramphenicol. These studies showed that the lack of NGO1985 resulted in dramatically decreased GC viability, suggesting that this protein functions in the maintenance of the cell envelope permeability barrier. Overall, these findings further support our hypothesis that the conserved proteins may represent promising targets for designing new therapeutic interventions.     

Multipattern Consensus Regions in Multiple Aligned Protein Sequences and Their Segmentation

Decomposing a biological sequence into its functional regions is an important prerequisite to understand the molecule. Using the multiple alignments of the sequences, we evaluate a segmentation based on the type of statistical variation pattern from each of the aligned sites. To describe such a more general pattern, we introduce multipattern consensus regions as segmented regions based on conserved as well as interdependent patterns. Thus the proposed consensus region considers patterns that are statistically significant and extends a local neighborhood. To show its relevance in protein sequence analysis, a cancer suppressor gene called p53 is examined. The results show significant associations between the detected regions and tendency of mutations, location on the 3D structure, and cancer hereditable factors that can be inferred from human twin studies.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27]     

The Wavelet-Based Cluster Analysis for Temporal Gene Expression Data

A variety of high-throughput methods have made it possible to generate detailed temporal expression data for a single gene or large numbers of genes. Common methods for analysis of these large data sets can be problematic. One challenge is the comparison of temporal expression data obtained from different growth conditions where the patterns of expression may be shifted in time. We propose the use of wavelet analysis to transform the data obtained under different growth conditions to permit comparison of expression patterns from experiments that have time shifts or delays. We demonstrate this approach using detailed temporal data for a single bacterial gene obtained under 72 different growth conditions. This general strategy can be applied in the analysis of data sets of thousands of genes under different conditions.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]     

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]