Network-level analysis of metabolic regulation in the human red blood cell using random sampling and singular value decomposition

Background  

Extreme pathways (ExPas) have been shown to be valuable for studying the functions and capabilities of metabolic networks through characterization of the null space of the stoichiometric matrix (S). Singular value decomposition (SVD) of the ExPa matrix P has previously been used to characterize the metabolic regulatory problem in the human red blood cell (hRBC) from a network perspective. The calculation of ExPas is NP-hard, and for genome-scale networks the computation of ExPas has proven to be infeasible. Therefore an alternative approach is needed to reveal regulatory properties of steady state solution spaces of genome-scale stoichiometric matrices.     

Protein evolution on a human signaling network

Background  

The architectural structure of cellular networks provides a framework for innovations as well as constraints for protein evolution. This issue has previously been studied extensively by analyzing protein interaction networks. However, it is unclear how signaling networks influence and constrain protein evolution and conversely, how protein evolution modifies and shapes the functional consequences of signaling networks. In this study, we constructed a human signaling network containing more than 1,600 nodes and 5,000 links through manual curation of signaling pathways, and analyzed the d _N/d _S values of human-mouse orthologues on the network.     

New potent biphalin analogues containing p-fluoro-L-phenylalanine at the 4,4' positions and non-hydrazine linkers

We report the synthesis and the biological evaluation of two new analogues of the potent dimeric opioid peptide biphalin. The performed modification is based on the replacement of two key structural elements of the native biphalin, namely: the hydrazine bridge which joins the two palindromic moieties and the phenylalanine residues at the 4,4′ positions of the backbone. The new analogues 9 and 10 contain 1,2-phenylenediamine and piperazine, respectively, in place of the hydrazidic linker and p-fluoro-l-phenylalanine residues at 4 and 4′ positions. Binding values are: K_\texti^m = 0.51 \textnM K_{\text{i}}^{\mu } = 0.51\,{\text{nM}} and K_\texti^d = 12.8 \textnM K_{\text{i}}^{\delta } = 12.8\,{\text{nM}} for compound 9, K_\texti^m = 0.09 \textnM K_{\text{i}}^{\mu } = 0.09\,{\text{nM}} and K_\texti^d = 0.11 \textnM K_{\text{i}}^{\delta } = 0.11\,{\text{nM}} for analogue 10.     

A method for the generation of standardized qualitative dynamical systems of regulatory networks

Background  

Modeling of molecular networks is necessary to understand their dynamical properties. While a wealth of information on molecular connectivity is available, there are still relatively few data regarding the precise stoichiometry and kinetics of the biochemical reactions underlying most molecular networks. This imbalance has limited the development of dynamical models of biological networks to a small number of well-characterized systems. To overcome this problem, we wanted to develop a methodology that would systematically create dynamical models of regulatory networks where the flow of information is known but the biochemical reactions are not. There are already diverse methodologies for modeling regulatory networks, but we aimed to create a method that could be completely standardized, i.e. independent of the network under study, so as to use it systematically.     

Mining protein networks for synthetic genetic interactions

Background  

The local connectivity and global position of a protein in a protein interaction network are known to correlate with some of its functional properties, including its essentiality or dispensability. It is therefore of interest to extend this observation and examine whether network properties of two proteins considered simultaneously can determine their joint dispensability, i.e., their propensity for synthetic sick/lethal interaction. Accordingly, we examine the predictive power of protein interaction networks for synthetic genetic interaction in Saccharomyces cerevisiae, an organism in which high confidence protein interaction networks are available and synthetic sick/lethal gene pairs have been extensively identified.     

Functional classification of proteins based on projection of amino acid sequences: application for prediction of protein kinase substrates

Background  

The knowledge about proteins with specific interaction capacity to the protein partners is very important for the modeling of cell signaling networks. However, the experimentally-derived data are sufficiently not complete for the reconstruction of signaling pathways. This problem can be solved by the network enrichment with predicted protein interactions. The previously published in silico method PAAS was applied for prediction of interactions between protein kinases and their substrates.     

Regulation of phosphate starvation responses in higher plants

Background

Phosphorus (P) is often a limiting mineral nutrient for plant growth. Many soils worldwide are deficient in soluble inorganic phosphate (P_i), the form of P most readily absorbed and utilized by plants. A network of elaborate developmental and biochemical adaptations has evolved in plants to enhance P_i acquisition and avoid starvation.

Scope

Controlling the deployment of adaptations used by plants to avoid P_i starvation requires a sophisticated sensing and regulatory system that can integrate external and internal information regarding P_i availability. In this review, the current knowledge of the regulatory mechanisms that control P_i starvation responses and the local and long-distance signals that may trigger P_i starvation responses are discussed. Uncharacterized mutants that have P_i-related phenotypes and their potential to give us additional insights into regulatory pathways and P_i starvation-induced signalling are also highlighted and assessed.

Conclusions

An impressive list of factors that regulate P_i starvation responses is now available, as is a good deal of knowledge regarding the local and long-distance signals that allow a plant to sense and respond to P_i availability. However, we are only beginning to understand how these factors and signals are integrated with one another in a regulatory web able to control the range of responses demonstrated by plants grown in low P_i environments. Much more knowledge is needed in this agronomically important area before real gains can be made in improving P_i acquisition in crop plants.     

Module detection in complex networks using integer optimisation

Background  

The detection of modules or community structure is widely used to reveal the underlying properties of complex networks in biology, as well as physical and social sciences. Since the adoption of modularity as a measure of network topological properties, several methodologies for the discovery of community structure based on modularity maximisation have been developed. However, satisfactory partitions of large graphs with modest computational resources are particularly challenging due to the NP-hard nature of the related optimisation problem. Furthermore, it has been suggested that optimising the modularity metric can reach a resolution limit whereby the algorithm fails to detect smaller communities than a specific size in large networks.     

How accurate and statistically robust are catalytic site predictions based on closeness centrality?

Background  

We examine the accuracy of enzyme catalytic residue predictions from a network representation of protein structure. In this model, amino acid α-carbons specify vertices within a graph and edges connect vertices that are proximal in structure. Closeness centrality, which has shown promise in previous investigations, is used to identify important positions within the network. Closeness centrality, a global measure of network centrality, is calculated as the reciprocal of the average distance between vertex i and all other vertices.     

Of mice and mammoths: generality and antiquity of the island rule

Aim

We assessed the generality of the island rule in a database comprising 1593 populations of insular mammals (439 species, including 63 species of fossil mammals), and tested whether observed patterns differed among taxonomic and functional groups.

Location

Islands world‐wide.

Methods

We measured museum specimens (fossil mammals) and reviewed the literature to compile a database of insular animal body size (S_i = mean mass of individuals from an insular population divided by that of individuals from an ancestral or mainland population, M). We used linear regressions to investigate the relationship between S_i and M, and ANCOVA to compare trends among taxonomic and functional groups.

Results

S_i was significantly and negatively related to the mass of the ancestral or mainland population across all mammals and within all orders of extant mammals analysed, and across palaeo‐insular (considered separately) mammals as well. Insular body size was significantly smaller for bats and insectivores than for the other orders studied here, but significantly larger for mammals that utilized aquatic prey than for those restricted to terrestrial prey.

Main conclusions

The island rule appears to be a pervasive pattern, exhibited by mammals from a broad range of orders, functional groups and time periods. There remains, however, much scatter about the general trend; this residual variation may be highly informative as it appears consistent with differences among species, islands and environmental characteristics hypothesized to influence body size evolution in general. The more pronounced gigantism and dwarfism of palaeo‐insular mammals, in particular, is consistent with a hypothesis that emphasizes the importance of ecological interactions (time in isolation from mammalian predators and competitors was 0.1 to > 1.0 Myr for palaeo‐insular mammals, but < 0.01 Myr for extant populations of insular mammals). While ecological displacement may be a major force driving diversification in body size in high‐diversity biotas, ecological release in species‐poor biotas often results in the convergence of insular mammals on the size of intermediate but absent species.     

Universal partitioning of the hierarchical fold network of 50-residue segments in proteins

Background  

Several studies have demonstrated that protein fold space is structured hierarchically and that power-law statistics are satisfied in relation between the numbers of protein families and protein folds (or superfamilies). We examined the internal structure and statistics in the fold space of 50 amino-acid residue segments taken from various protein folds. We used inter-residue contact patterns to measure the tertiary structural similarity among segments. Using this similarity measure, the segments were classified into a number (K _c) of clusters. We examined various K _c values for the clustering. The special resolution to differentiate the segment tertiary structures increases with increasing K _c. Furthermore, we constructed networks by linking structurally similar clusters.     

Exploration of biological network centralities with CentiBiN

Background  

The elucidation of whole-cell regulatory, metabolic, interaction and other biological networks generates the need for a meaningful ranking of network elements. Centrality analysis ranks network elements according to their importance within the network structure and different centrality measures focus on different importance concepts. Central elements of biological networks have been found to be, for example, essential for viability.     

Invariant properties of mycobiont-photobiont networks in Antarctic lichens

Aim

Lichens are often regarded as paradigms of mutualistic relationships. However, it is still poorly known how lichen-forming fungi and their photosynthetic partners interact at a community scale. We explored the structure of fungus-alga networks of interactions in lichen communities along a latitudinal transect in continental Antarctica. We expect these interactions to be highly specialized and, consequently, networks with low nestedness degree and high modularity.

Location

Transantarctic Mountains from 76° S to 85° S (continental Antarctica).

Time Period

Present.

Major Taxa Studied

Seventy-seven species of lichen-forming fungi and their photobionts.

Methods

DNA barcoding of photobionts using nrITS data was conducted in 756 lichen specimens from five regions along the Transantarctic Mountains. We built interaction networks for each of the five studied regions and a metaweb for the whole area. We explored the specialization of both partners using the number of partners a species interacts with and the specialization parameter d'. Network architecture parameters such as nestedness, modularity and network specialization parameter H₂' were studied in all networks and contrasted through null models. Finally, we measured interaction turnover along the latitudinal transect.

Results

We recovered a total of 842 interactions. Differences in specialization between partners were not statistically significant. Fungus-alga interaction networks showed high specialization and modularity, as well as low connectance and nestedness. Despite the large turnover in interactions occurring among regions, network parameters were not correlated with latitude.

Main Conclusions

The interaction networks established between fungi and algae in saxicolous lichen communities in continental Antarctica showed invariant properties along the latitudinal transect. Rewiring is an important driver of interaction turnover along the transect studied. Future work should answer whether the patterns observed in our study are prevalent in other regions with milder climates and in lichen communities on different substrates.     

A mechanobiological investigation of platelets

Understanding mechanotransduction pathways leading to thrombosis will require progressive steps, including determination of the mechanical behavior of the platelet membrane in response to applied loads. The platelet membrane deformation capacity, as quantified by membrane progression into a borosilicate glass micropipette of defined internal diameter, was probed in murine platelets using a controlled range of negative pressure (0–7 cm H₂O). Based on our observations that the platelet portion outside the micropipette was mostly spherical and that the platelet volume did not change upon aspiration, a novel continuum mechanics-based model of the platelet micropipette aspiration experiment was created, and a new hyperelastic isotropic material model including membrane residual tension was proposed for the platelet membrane. Murine platelet membranes maintained an average linear deformation behavior: L _p/R _p = 146,100p _i × R _p + 19.923, where L _p is the platelet length aspirated in the micropipette (m), R _p is micropipette radius (m) and p _i is the aspiration pressure (Pa). The theoretical model was used to generate material constants for the murine platelet membrane that allowed for an accurate simulation of the micropipette aspiration experiments. From published results, another set of material constants was established for the human platelet membrane. Limited cases of platelet lysis upon aspiration were analyzed using the theoretical model to determine preliminary membrane tension strength values.     

Synthesis of novel sulfonamides under mild conditions with effective inhibitory activity against the carbonic anhydrase isoforms I and II

Novel sulfonamide derivatives 6a–i, as new carbonic anhydrase inhibitors which candidate for glaucoma treatment, were synthesized from the reactions of 4-amino-N-(4-sulfamoylphenyl) benzamide 4 and sulfonyl chloride derivatives 5a–i with high yield (71–90%). The structures of these compounds were confirmed by using spectral analysis (FT-IR, ¹H NMR, ¹³C NMR, LC/MS and HRMS). The inhibition effects of 6a–i on the hydratase and esterase activities of human carbonic anhydrase isoenzymes, hCA I and II, which were purified from human erythrocytes with Sepharose®4B-l-tyrosine-p-aminobenzene sulfonamide affinity chromatography, were studied as in vitro, and IC₅₀ and K_i values were determined. The results show that newly synthesized compounds have quite powerful inhibitory properties.     

Evolutionary conservation and over-representation of functionally enriched network patterns in the yeast regulatory network

Background  

Localized network patterns are assumed to represent an optimal design principle in different biological networks. A widely used method for identifying functional components in biological networks is looking for network motifs – over-represented network patterns. A number of recent studies have undermined the claim that these over-represented patterns are indicative of optimal design principles and question whether localized network patterns are indeed of functional significance. This paper examines the functional significance of regulatory network patterns via their biological annotation and evolutionary conservation.     

cAMP controls cytosolic Ca<Superscript>2+</Superscript> levels in <Emphasis Type="Italic">Dictyostelium discoideum</Emphasis>

Background  

Differentiating Dictyostelium discoideum amoebae respond upon cAMP-stimulation with an increase in the cytosolic free Ca²⁺ concentration ([Ca²⁺]_i) that is composed of liberation of stored Ca²⁺ and extracellular Ca²⁺-influx. In this study we investigated whether intracellular cAMP is involved in the control of [Ca²⁺]_i.     

Evolutionary constraints permeate large metabolic networks

Background  

Metabolic networks show great evolutionary plasticity, because they can differ substantially even among closely related prokaryotes. Any one metabolic network can also effectively compensate for the blockage of individual reactions by rerouting metabolic flux through other pathways. These observations, together with the continual discovery of new microbial metabolic pathways and enzymes, raise the possibility that metabolic networks are only weakly constrained in changing their complement of enzymatic reactions.     

Gene and pathway identification with <Emphasis Type="Italic">L</Emphasis><Subscript><Emphasis Type="Italic">p</Emphasis></Subscript>penalized Bayesian logistic regression

Background  

Identifying genes and pathways associated with diseases such as cancer has been a subject of considerable research in recent years in the area of bioinformatics and computational biology. It has been demonstrated that the magnitude of differential expression does not necessarily indicate biological significance. Even a very small change in the expression of particular gene may have dramatic physiological consequences if the protein encoded by this gene plays a catalytic role in a specific cell function. Moreover, highly correlated genes may function together on the same pathway biologically. Finally, in sparse logistic regression withL _p (p< 1) penalty, the degree of the sparsity obtained is determined by the value of the regularization parameter. Usually this parameter must be carefully tuned through cross-validation, which is time consuming.