scholarly journals An integrated network analysis identifies how ArcAB enables metabolic oscillations in the nitric oxide detoxification network ofEscherichia coli

2017 ◽  
Vol 12 (8) ◽  
pp. 1600570 ◽  
Author(s):  
Sarah A. Sacco ◽  
Kristin J. Adolfsen ◽  
Mark P. Brynildsen
2017 ◽  
Vol 41 ◽  
pp. 67-81 ◽  
Author(s):  
Jonathan L. Robinson ◽  
Jacob M. Jaslove ◽  
Allison M. Murawski ◽  
Christopher H. Fazen ◽  
Mark P. Brynildsen

2006 ◽  
Vol 34 (1) ◽  
pp. 195-196 ◽  
Author(s):  
G.E. Meakin ◽  
B.J.N. Jepson ◽  
D.J. Richardson ◽  
E.J. Bedmar ◽  
M.J. Delgado

The identification of nitric oxide-bound leghaemoglobin within soya bean nodules has led to the question of how Bradyrhizobium japonicum bacteroids overcome the toxicity of this nitric oxide. It has previously been shown that one candidate for nitric oxide detoxification, the respiratory nitric oxide reductase, is expressed in soya bean nodules from plants supplied with nitrate [Mesa, de Dios Alché, Bedmar and Delgado (2004) Physiol. Plant. 120, 205–211]. In this paper, the role of this enzyme in nitric oxide detoxification is assessed and discussion is provided on other possible B. japonicum nitric oxide detoxification systems.


2019 ◽  
Vol 116 (16) ◽  
pp. 8018-8027 ◽  
Author(s):  
Joel D. Hahn ◽  
Olaf Sporns ◽  
Alan G. Watts ◽  
Larry W. Swanson

Control of multiple life-critical physiological and behavioral functions requires the hypothalamus. Here, we provide a comprehensive description and rigorous analysis of mammalian intrahypothalamic network architecture. To achieve this at the gray matter region (macroscale) level, macroscale connection (macroconnection) data for the rat hypothalamus were extracted from the primary literature. The dataset indicated the existence of 7,982 (of 16,770 possible) intrahypothalamic macroconnections. Network analysis revealed that the intrahypothalamic macroconnection network (its macroscale subconnectome) is divided into two identical top-level subsystems (or subnetworks), each composed of two nested second-level subsystems. At the top-level, this suggests a deeply integrated network; however, regional grouping of the two second-level subsystems suggested a partial separation between control of physiological functions and behavioral functions. Furthermore, inclusion of four candidate hubs (dominant network nodes) in the second-level subsystem that is associated prominently with physiological control suggests network primacy with respect to this function. In addition, comparison of network analysis with expression of gene markers associated with inhibitory (GAD65) and excitatory (VGLUT2) neurotransmission revealed a significant positive correlation between measures of network centrality (dominance) and the inhibitory marker. We discuss these results in relation to previous understandings of hypothalamic organization and provide, and selectively interrogate, an updated hypothalamus structure–function network model to encourage future hypothesis-driven investigations of identified hypothalamic subsystems.


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