Experimental analysis of the oil addition effect on mycelia and polysaccharide productions in Ganoderma lucidum submerged culture

The effect of corn oil addition on mycelium growth and polysaccharide productions in the medicinal mushroom Ganoderma lucidum was studied. The results showed that when a level of 2% corn oil was added at the beginning of culture, the biomass and polysaccharide productions reached a maximum of 12.9 and 1.038 g/L, respectively, during 13-day cultivation. The pH variation along with morphology observation in culture provided an indirect inference to the promotional effect of oil addition. Moreover, a curve fitting analysis was carried out to assay the elevated effect on biomass and exopolysaccharide productions in oil added culture. The experimental data of substrates consumption and products formation in culture with oil addition were predicted through the fitting equations obtained in single carbon source culture. The numerical results further clarified the stimulatory effects of oil addition in G. lucidum culture.     

NAD(P)H: Quinone oxidoreductase 1, glutathione S-transferase M1, environmental tobacco smoke exposure, and childhood asthma

Environmental tobacco smoke (ETS) exposure might increase the risk for childhood asthma, and we hypothesized the effect may be modified by the phase II genes NAD(P)H: quinone oxidoreductase 1 (NQO1) and glutathione S-transferase (GST) M1. To investigate the genetic and environmental associations with asthma, GSTM1 and NQO1 functional polymorphisms and ETS were analyzed in a two-staged cross-sectional study among elementary schoolchildren in Taiwan. Multiple logistic regression analysis revealed a significant association between the Ser allele of the NQO1 Pro187Ser polymorphism and asthma (OR = 1.6, 95% CI 1.3–1.8). Although GSTM1 genotype itself was not significantly associated with asthma (OR = 1.0, 95% CI 0.8–1.1), the GSTM1 genotype modified the association between the NQO1 polymorphism and asthma in children exposed to ETS (p = 0.0002). The NQO1 gene might be involved in the development of asthma, especially in children carrying the GSTM1 null genotype who are exposed to ETS.     

Rational Extension of the Ribosome Biogenesis Pathway Using Network-Guided Genetics

Biogenesis of ribosomes is an essential cellular process conserved across all eukaryotes and is known to require >170 genes for the assembly, modification, and trafficking of ribosome components through multiple cellular compartments. Despite intensive study, this pathway likely involves many additional genes. Here, we employ network-guided genetics—an approach for associating candidate genes with biological processes that capitalizes on recent advances in functional genomic and proteomic studies—to computationally identify additional ribosomal biogenesis genes. We experimentally evaluated >100 candidate yeast genes in a battery of assays, confirming involvement of at least 15 new genes, including previously uncharacterized genes (YDL063C, YIL091C, YOR287C, YOR006C/TSR3, YOL022C/TSR4). We associate the new genes with specific aspects of ribosomal subunit maturation, ribosomal particle association, and ribosomal subunit nuclear export, and we identify genes specifically required for the processing of 5S, 7S, 20S, 27S, and 35S rRNAs. These results reveal new connections between ribosome biogenesis and mRNA splicing and add >10% new genes—most with human orthologs—to the biogenesis pathway, significantly extending our understanding of a universally conserved eukaryotic process.     

Oncogenic Pathway Combinations Predict Clinical Prognosis in Gastric Cancer

Many solid cancers are known to exhibit a high degree of heterogeneity in their deregulation of different oncogenic pathways. We sought to identify major oncogenic pathways in gastric cancer (GC) with significant relationships to patient survival. Using gene expression signatures, we devised an in silico strategy to map patterns of oncogenic pathway activation in 301 primary gastric cancers, the second highest cause of global cancer mortality. We identified three oncogenic pathways (proliferation/stem cell, NF-κB, and Wnt/β-catenin) deregulated in the majority (>70%) of gastric cancers. We functionally validated these pathway predictions in a panel of gastric cancer cell lines. Patient stratification by oncogenic pathway combinations showed reproducible and significant survival differences in multiple cohorts, suggesting that pathway interactions may play an important role in influencing disease behavior. Individual GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Predicting pathway activity by expression signatures thus permits the study of multiple cancer-related pathways interacting simultaneously in primary cancers, at a scale not currently achievable by other platforms.     

WallGen,Software to Construct Layered Cellulose-Hemicellulose Networks and Predict Their Small Deformation Mechanics

We understand few details about how the arrangement and interactions of cell wall polymers produce the mechanical properties of primary cell walls. Consequently, we cannot quantitatively assess if proposed wall structures are mechanically reasonable or assess the effectiveness of proposed mechanisms to change mechanical properties. As a step to remedying this, we developed WallGen, a Fortran program (available on request) building virtual cellulose-hemicellulose networks by stochastic self-assembly whose mechanical properties can be predicted by finite element analysis. The thousands of mechanical elements in the virtual wall are intended to have one-to-one spatial and mechanical correspondence with their real wall counterparts of cellulose microfibrils and hemicellulose chains. User-defined inputs set the properties of the two polymer types (elastic moduli, dimensions of microfibrils and hemicellulose chains, hemicellulose molecular weight) and their population properties (microfibril alignment and volume fraction, polymer weight percentages in the network). This allows exploration of the mechanical consequences of variations in nanostructure that might occur in vivo and provides estimates of how uncertainties regarding certain inputs will affect WallGen''s mechanical predictions. We summarize WallGen''s operation and the choice of values for user-defined inputs and show that predicted values for the elastic moduli of multinet walls subject to small displacements overlap measured values. “Design of experiment” methods provide systematic exploration of how changed input values affect mechanical properties and suggest that changing microfibril orientation and/or the number of hemicellulose cross-bridges could change wall mechanical anisotropy.Plant scientists have long studied how primary wall structure influences mechanical properties (Preston, 1974). In this work, we develop methods to predict the elastic modulus for layered networks of cellulose microfibrils (CMFs) cross-linked by hemicellulose (HC) chains when they are subject to small imposed displacements.Polysaccharides provide over 90% of wall mass and therefore are likely to dominate wall mechanics. Two distinct but probably interacting (Zykwinska et al., 2005) networks are recognized: a cellulose-hemicellulose (CHC) network and a pectin network. Pectins can be removed by mutations, allowing measurements of the mechanical properties of the CHC network (Ryden et al., 2003) that can be compared with predicted values. The two networks probably make roughly comparable mechanical contributions in pectin-rich dicots (Ryden et al., 2003), but the CHC network presumably dominates in monocots with pectin-poor, type II walls (Carpita and Gibeaut, 1993; Rose, 2003). Plant cells align CMFs (Baskin, 2005) but not noncellulosic polysaccharides such as pectins and HCs. CMF alignment, therefore, underlies the structural and mechanical anisotropy seen in many cell walls.In principle, wall structure can predict mechanical properties, a multiscale modeling problem of the type that materials scientists often tackle (Kwon et al., 2008). In this context, structural and mechanical inputs concern polymer chains or aggregates, and mechanical properties are predicted for pieces of material several orders of magnitude larger that contain many polymer chains. There are some structure-based quantitative predictions of the mechanics of secondary walls (Bergander and Salmén, 2002; Keckes et al., 2003; Salmén, 2004; Hofstetter et al., 2005; Altaner and Jarvis, 2008), but most discussions of primary walls only involve qualitative consideration of how factors such as CMF length and alignment might change growth anisotropy (Wasteneys, 2004; Baskin, 2005) rather than the small displacement mechanical properties with which we are concerned. Modeling plant cell walls provides several particular challenges. First, walls vary greatly in CMF alignment, with multinet, polylamellate, helicoidal, and other types recognized; second, polymer composition varies even within one wall type; and third, polymer interactions remain uncertain, with the view that HCs cross-bridge CMFs (Hayashi, 1989) challenged on various grounds by those regarding them as providing spacing or otherwise facilitating movement between CMFs (Whitney et al., 1999; Thompson, 2005). In beginning multiscale modeling of primary walls, therefore, we sought a strategy that facilitated in silico experiments in which we could vary the structure, composition, and other wall properties that contribute to the complex microstructure of cell walls and that provided the opportunity to give the polymers more complex properties in future studies.Many modeling strategies facilitate computation by simplifying (homogenizing) wall structure by aggregating the properties of many polymers. Procedures are well established but do not obviate the necessity to understand the underlying polymer properties and impose an additional requirement to deduce the properties of the population being homogenized. Cell walls are often compared with fiber composites, for which several approaches to the prediction of the elastic properties have been reported (Chamis and Sendeckyj, 1968). Most such micromechanical approaches, however, are based on simplifying assumptions about the geometry of the microstructure or special relations between the phase properties. Moreover, although cell walls are often described as fiber composites, this obscures important distinctions, notably the difference between the continuous interfiber matrix typical of most manufactured fiber composites and the discrete HC cross-links present in the cell wall. The mechanical properties of the continuous matrix are relatively easily measured for manufactured fiber composites, but replacing HC cross-bridges with a continuous matrix requires defining its mechanical properties. Various micromechanical models of secondary walls assume that a homogenous HC matrix surrounds CMFs (Bergander and Salmén, 2002; Salmén, 2004; Hofstetter et al., 2005); for example, Hofstetter et al. (2005) gave this phase a bulk modulus taken from testing an isotropic HC powder. Increased computing power now provides the option to avoid such homogenization with at least three advantages accruing. First, homogenization often limits the ease with which different structures can be investigated (a high priority issue for us), since homogenization assumptions may need to be reexamined and recalibrated as microstructure changes. Without homogenization, a wide range of structures can be analyzed, given that a flexible system is available for generating microstructure. Second, accumulating knowledge of the mechanics of individual polymer chains coming from techniques such as atomic force microscopy can be directly applied to the individual HCs and CMFs in a nonhomogenized model. If homogenization is applied, that relationship is lost and new assumptions must be made about the properties of the population. Third, once the basic model is established, the properties of the polymers, particularly those of the HCs, can be varied to more accurately capture the nonlinear and other properties seen on extension.We avoided homogenization by using the WallGen program to build a fragment of virtual wall whose components have one-to-one spatial and mechanical correspondence with the CMFs and HCs of a primary wall CHC network. We chose finite element analysis (FEA) to predict the mechanical properties of the entire fragment containing thousands of CMFs and HCs. In effect, then, WallGen averages by setting up the most realistic spatial arrangement, using mechanical data for individual chains and leaving FEA to predict the collective properties. The well-established engineering technique of FEA has been used to predict wall mechanics at cellular and subcellular scales. Examples include predicting cell response to microindentation (Bolduc et al., 2006) or compression between flat plates (Smith et al., 1998) and predicting the mechanics of pulped fiber networks in paper (Hansson and Rasmuson, 2004). These applications have not involved mechanical representation of individual wall polymers, but FEA has been used at this scale to model individual microtubules and F-actin polymers pulling on membranes (Allen et al., 2009) and at even finer scales to model tubulin lattice deformation within single microtubules (Schaap et al., 2006). Modern FEA programs have features of potential value for developing more sophisticated models of wall mechanics: components can have nonlinear force-extension properties and viscoelastic properties, and conditions can be specified to break links between components of the microstructure. This should allow exploration of the more complex mechanical behavior that CHC networks show when subject to larger displacements and incorporation of additional mechanical elements providing the properties generated by pectins.In this article, we describe how WallGen operates, review the choice of values for several important inputs, predict the elastic moduli of multinet walls in which HCs cross-link CMFs, compare those values with experimental values, and quantify the mechanical effects of varying several inputs to the virtual wall. We restrict consideration to polymers given linear elastic properties and, because small strains are sufficient to predict the elastic modulus, restrict experiments to small displacements to minimize inaccuracies from this simplification. A previous publication considered issues relating to representative volume elements and analyzed some simpler CHC networks (Kha et al., 2008).     

Lipopolysaccharide directly stimulates aldosterone production via toll‐like receptor 2 and toll‐like receptor 4 related PI3K/Akt pathway in rat adrenal zona glomerulosa cells

The level of circulating endotoxin is related to the severity of cardiovascular disease. One of the indexes for the prognosis of cardiovascular disease is the plasma aldosterone level. Recently, the Toll‐like receptors (TLRs), lipopolysaccharide (LPS)‐regulated receptors, were found not only to mediate the inflammatory response but also to be important in the adrenal stress response. Whether LPS via TLRs induced aldosterone production in adrenal zona glomerulosa (ZG) cells was not clear. Our results suggest that LPS‐induced aldosterone secretion in a time‐ and dose‐dependent manner and via TLR2 and TLR4 signaling pathway. Administration of LPS can enhance steroidogenesis enzyme expression such as scavenger receptor‐B1 (SR‐B1), steroidogenic acute regulatory protein (StAR) and P450 side chain cleavage (P450scc) enzyme. LPS‐induced SR‐B1 and StAR protein expression are abolished by TLR2 blocker. Furthermore, we demonstrated that phosphorylation of Akt was elevated by LPS treatment and reduced by TLR2 blockers, TLR4 blockers, and LY294002 (PI₃K inhibitor). Those inhibitors of PI₃K/Akt pathways also abolish LPS‐induced aldosterone secretion and SR‐B1 protein level. In conclusion, LPS‐induced aldosterone production and SR‐B1 proteins expression are through the TLR2 and TLR4 related PI₃K/Akt pathways in adrenal ZG cells. J. Cell. Biochem. 111: 872–880, 2010. © 2010 Wiley‐Liss, Inc.     

Bradykinin enhances cell migration in human chondrosarcoma cells through BK receptor signaling pathways

Bradykinin (BK) is an inflammatory mediator, and shows elevated levels in regions of severe injury and inflammatory diseases. BK has recently been shown to be involved in carcinogenesis and cancer progression. In this study, we found that BK increased the migration and the expression of α2β1 integrin in human chondrosarcoma cells. We also found that human chondrosarcoma tissues had significantly higher expression of the B1 and B2 receptors comparing to normal cartilage. BK‐mediated migration and integrin up‐regulation was attenuated by B1 and B2 BK receptor siRNA or antagonist. Activations of phospholipase C (PLC), protein kinase Cδ (PKCδ), and NF‐κB pathways after BK treatment was demonstrated, and BK‐induced integrin expression and migration activity was inhibited by the specific inhibitor of PLC, PKCδ, and NF‐κB cascades. Taken together, our results indicated that BK enhances the migration of chondrosarcoma cells by increasing α2β1 integrin expression through the BK receptors/PLC/PKCδ/NF‐κB signal transduction pathway. J. Cell. Biochem. 109: 82–92, 2010. © 2009 Wiley‐Liss, Inc.     

Integrin‐linked kinase is involved in TNF‐α‐induced inducible nitric‐oxide synthase expression in myoblasts

Tumor necrosis factor‐α (TNF‐α) is a pleiotropic cytokine produced by activated macrophages. Nitric oxide (NO) is a highly reactive nitrogen radical implicated in inflammatory responses. We investigated the signaling pathway involved in inducible nitric oxide synthase (iNOS) expression and NO production stimulated by TNF‐α in cultured myoblasts. TNF‐α stimulation caused iNOS expression and NO production in myoblasts (G7 cells). TNF‐α‐mediated iNOS expression was attenuated by integrin‐linked kinase (ILK) inhibitor (KP392) and siRNA. Pretreatment with Akt inhibitor, mammalian target of rapamycin (mTOR) inhibitor (rapamycin), NF‐κB inhibitor (PDTC), and IκB protease inhibitor (TPCK) also inhibited the potentiating action of TNF‐α. Stimulation of cells with TNF‐α increased ILK kinase activity. TNF‐α also increased the Akt and mTOR phosphorylation. TNF‐α mediated an increase of NF‐κB‐specific DNA–protein complex formation, p65 translocation into nucleus, NF‐κB‐luciferase activity was inhibited by KP392, Akt inhibitor, and rapamycin. Our results suggest that TNF‐α increased iNOS expression and NO production in myoblasts via the ILK/Akt/mTOR and NF‐κB signaling pathway. J. Cell. Biochem. 109: 1244–1253, 2010. © 2010 Wiley‐Liss, Inc.