Comparing methods for metabolic network analysis and an application to metabolic engineering

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.     

Fruit fly behavior in response to chemosensory signals

An important question in contemporary sensory neuroscience is how animals perceive their environment and make appropriate behavioral choices based on chemical perceptions. The fruit fly Drosophila melanogaster exhibits robust tastant and odor-evoked behaviors. Understanding how the gustatory and olfactory systems support the perception of these contact and volatile chemicals and translate them into appropriate attraction or avoidance behaviors has made an unprecedented contribution to our knowledge of the organization of chemosensory systems. In this review, I begin by describing the receptors and signaling mechanisms of the Drosophila gustatory and olfactory systems and then highlight their involvement in the control of simple and complex behaviors. The topics addressed include feeding behavior, learning and memory, navigation behavior, neuropeptide modulation of chemosensory behavior, and I conclude with a discussion of recent work that provides insight into pheromone signaling pathways.     

A spatially dynamic cohort of regulatory genes in the endomesodermal gene network of the sea urchin embryo

A gene regulatory network subcircuit comprising the otx, wnt8, and blimp1 genes accounts for a moving torus of gene expression that sweeps concentrically across the vegetal domain of the sea urchin embryo. Here we confirm by mutation the inputs into the blimp1cis-regulatory module predicted by network analysis. Its essential design feature is that it includes both activation and autorepression sites. The wnt8 gene is functionally linked into the subcircuit in that cells receiving this ligand generate a β-catenin/Tcf input required for blimp1 expression, while the wnt8 gene in turn requires a Blimp1 input. Their torus-like spatial expression patterns and gene regulatory analysis indicate that the genes even-skipped and hox11/13b are also entrained by this subcircuit. We verify the cis-regulatory inputs of even-skipped predicted by network analysis. These include activation by β-catenin/Tcf and Blimp1, repression within the torus by Hox11/13b, and repression outside the torus by Tcf in the absence of Wnt8 signal input. Thus even-skipped and hox11/13b, along with blimp1 and wnt8, are members of a cohort of torus genes with similar regulatory inputs and similar, though slightly out-of-phase, expression patterns, which reflect differences in cis-regulatory design.     

NAMPT,GRN, and SERPINE1 signature as predictor of disease progression and survival in gliomas

Adipose tissue is an important source of adipokines involved in anti- and pro-inflammatory effects. Their involvement in certain cancers such as breast and colon cancer is known but in gliomas it remains unexplored till date. The aim of this study was to assess the status of adipokines as prognostic markers of gliomas (low grade gliomas [LGG] and glioblastoma mutiforme [GBM]). Expression status (messenger RNA [mRNA]), overall survival (OS) and disease-free survival (DFS) was identified using gene expression profiling interactive analysis server. Clinicopathological analysis and correlation between different adipokines was performed using Xena server. Protein expression status was analyzed using tissue sections from the Human Protein Atlas. Out of 11 adipokines studied visfatin (NAMPT), apelin (APLN), granulin (GRN), serpin peptidase inhibitor/plasminogen activator inhibitor type 1 (PAI-1) member 1 (SERPINE1), and chemokine (C-C motif) ligand 2 (CCL2) mRNA levels were significantly upregulated in both LGG and GBM. Interleukin 6 (IL6) mRNA was found be significantly upregulated only in GBM. NAMPT, GRN, SERPINE1, and IL6 showed reduced OS as well as worst DFS for patients having higher mRNA expression in LGG. Increased expression of CCL2 showed worst OS in LGG patients while resistin (RETN) and GRN showed the worst OS in GBM patients. Higher expression of RETN, GRN, IL6, SERPINE1, and CCL2 were found to be positively correlated with shorter DFS in GBM. In the clinicopathological analysis, NAMPT, GRN, IL6, SERPINE1, and CCL2 expressions were significantly associated between the neoplasm histological G2 and G3 grades. Furthermore, expression of NAMPT, GRN, tumor necrosis factor, IL6, SERPINE1, and CCL2 were significantly associated with histological type in LGG patients. NAMPT, GRN, SERPINE1, CCL2, and RETN expression were found to be correlated with each other in gliomas. Finally, NAMPT, GRN, and SERPINE1 were also found to be upregulated using immunohistochemistry in a lower grade and high grade gliomas as compared to normal cells. In conclusion, we have identified key adipokines, namely NAMPT, GRN, and SERPINE1 as potential diagnostic and prognostic markers that might be instrumental in the development and progression of gliomas.     

HSM — a hybrid system based approach for modelling intracellular networks

The paper proposes a hybrid system based approach for modelling of intracellular networks and introduces a restricted subclass of hybrid systems – HSM – with an objective of still being able to provide sufficient power for the modelling of biological systems, while imposing some restrictions that facilitate analysis of systems described by such models.     

Evolutionary bioscience as regulatory systems biology

At present several entirely different explanatory approaches compete to illuminate the mechanisms by which animal body plans have evolved. Their respective relevance is briefly considered here in the light of modern knowledge of genomes and the regulatory processes by which development is controlled. Just as development is a system property of the regulatory genome, causal explanation of evolutionary change in developmental process must be considered at a system level. Here I enumerate some mechanistic consequences that follow from the conclusion that evolution of the body plan has occurred by alteration of the structure of developmental gene regulatory networks. The hierarchy and multiple additional design features of these networks act to produce Boolean regulatory state specification functions at upstream phases of development of the body plan. These are created by the logic outputs of network subcircuits, and in modern animals these outputs are impervious to continuous adaptive variation unlike genes operating more peripherally in the network.