An integrative analysis of four CESA isoforms specific for fiber cellulose production between Gossypium hirsutum and Gossypium barbadense

Cotton fiber is an excellent model system of cellulose biosynthesis; however, it has not been widely studied due to the lack of information about the cellulose synthase (CESA) family of genes in cotton. In this study, we initially identified six full-length CESA genes designated as GhCESA5–GhCESA10. Phylogenetic analysis and gene co-expression profiling revealed that CESA1, CESA2, CESA7, and CESA8 were the major isoforms for secondary cell wall biosynthesis, whereas CESA3, CESA5, CESA6, CESA9, and CESA10 should involve in primary cell wall formation for cotton fiber initiation and elongation. Using integrative analysis of gene expression patterns, CESA protein levels, and cellulose biosynthesis in vivo, we detected that CESA8 could play an enhancing role for rapid and massive cellulose accumulation in Gossypium hirsutum and Gossypium barbadense. We found that CESA2 displayed a major expression in non-fiber tissues and that CESA1, a housekeeping gene like, was predominantly expressed in all tissues. Further, a dynamic alteration was observed in cell wall composition and a significant discrepancy was observed between the cotton species during fiber elongation, suggesting that pectin accumulation and xyloglucan reduction might contribute to cell wall transition. In addition, we discussed that callose synthesis might be regulated in vivo for massive cellulose production during active secondary cell wall biosynthesis in cotton fibers.     

Predicting candidate genes based on combined network topological features: a case study in coronary artery disease

Predicting candidate genes using gene expression profiles and unbiased protein-protein interactions (PPI) contributes a lot in deciphering the pathogenesis of complex diseases. Recent studies showed that there are significant disparities in network topological features between non-disease and disease genes in protein-protein interaction settings. Integrated methods could consider their characteristics comprehensively in a biological network. In this study, we introduce a novel computational method, based on combined network topological features, to construct a combined classifier and then use it to predict candidate genes for coronary artery diseases (CAD). As a result, 276 novel candidate genes were predicted and were found to share similar functions to known disease genes. The majority of the candidate genes were cross-validated by other three methods. Our method will be useful in the search for candidate genes of other diseases.     

The Minor Wall-Networks between Monolignols and Interlinked-Phenolics Predominantly Affect Biomass Enzymatic Digestibility in Miscanthus

Plant lignin is one of the major wall components that greatly contribute to biomass recalcitrance for biofuel production. In this study, total 79 representative Miscanthus germplasms were determined with wide biomass digestibility and diverse monolignol composition. Integrative analyses indicated that three major monolignols (S, G, H) and S/G ratio could account for lignin negative influence on biomass digestibility upon NaOH and H₂SO₄ pretreatments. Notably, the biomass enzymatic digestions were predominately affected by the non-KOH-extractable lignin and interlinked-phenolics, other than the KOH-extractable ones that cover 80% of total lignin. Furthermore, a positive correlation was found between the monolignols and phenolics at p<0.05 level in the non-KOH-extractable only, suggesting their tight association to form the minor wall-networks against cellulases accessibility. The results indicated that the non-KOH-extractable lignin-complex should be the target either for cost-effective biomass pretreatments or for relatively simply genetic modification of plant cell walls in Miscanthus.     

The Experimental Herbicide CGA 325′615 Inhibits Synthesis of Crystalline Cellulose and Causes Accumulation of Non-Crystalline β-1,4-Glucan Associated with CesA Protein

Developing cotton (Gossypium hirsutum) fibers, cultured in vitro with their associated ovules, were used to compare the effects of two herbicides that inhibit cellulose synthesis: 2,6-dichlorobenzonitrile (DCB) and an experimental thiatriazine-based herbicide, CGA 325'615. CGA 325'615 in nanomolar concentrations or DCB in micromolar concentrations causes inhibition of synthesis of crystalline cellulose. Unlike DCB, CGA 325'615 also causes concomitant accumulation of non-crystalline beta-1,4-glucan that can be at least partially solubilized from fiber walls with ammonium oxalate. The unusual solubility of this accumulated glucan may be explained by its strong association with protein. Treatment of the glucan fraction with protease changes its size distribution and leads to precipitation of the glucan. Treatment of the glucan fraction with cellulase digests the glucan and also releases protein that has been characterized as GhCesA-1 and GhCesA-2--proteins that are believed to represent the catalytic subunit of cellulose synthase. The fact that cellulase treatment is required to release this protein indicates an extremely tight association of the glucan with the CesA proteins. In addition, CGA 325'615, but not DCB, also causes accumulation of CesA protein and a membrane-associated cellulase in the membrane fraction of fibers. In addition to the effects of CGA 325'615 on levels of both of these proteins, the level of both also shows coordinate regulation during fiber development, further suggesting they are both important for cellulose synthesis. The accumulation of non-crystalline glucan caused by CGA 325'615 mimics the phenotype of the cellulose-deficient rsw1 mutant of Arabidopsis that also accumulates an apparently similar glucan (T. Arioli, L. Peng, A.S. Betzner, J. Burn, W. Wittke, W. Herth, C. Camilleri, H. Hofte, J. Plazinski, R. Birch et al. [1998] Science 279: 717).     

Disease gene interaction pathways: a potential framework for how disease genes associate by disease-risk modules

Background

Disease genes that interact cooperatively play crucial roles in the process of complex diseases, yet how to analyze and represent their associations is still an open problem. Traditional methods have failed to represent direct biological evidences that disease genes associate with each other in the pathogenesis of complex diseases. Molecular networks, assumed as ‘a form of biological systems’, consist of a set of interacting biological modules (functional modules or pathways) and this notion could provide a promising insight into deciphering this topic.

Methodology/Principal Findings

In this paper, we hypothesized that disease genes might associate by virtue of the associations between biological modules in molecular networks. Then we introduced a novel disease gene interaction pathway representation and analysis paradigm, and managed to identify the disease gene interaction pathway for 61 known disease genes of coronary artery disease (CAD), which contained 46 disease-risk modules and 182 interaction relationships. As demonstrated, disease genes associate through prescribed communication protocols of common biological functions and pathways.

Conclusions/Significance

Our analysis was proved to be coincident with our primary hypothesis that disease genes of complex diseases interact with their neighbors in a cooperative manner, associate with each other through shared biological functions and pathways of disease-risk modules, and finally cause dysfunctions of a series of biological processes in molecular networks. We hope our paradigm could be a promising method to identify disease gene interaction pathways for other types of complex diseases, affording additional clues in the pathogenesis of complex diseases.     

Leaky Wave Antenna Based on Periodically Truncated SSPP Waveguide

Plasmonics - The guided waveguide structures based on surface plasmons can be used to miniaturize microwave devices. By simply introducing a series of periodic truncation slits in the SSPP (spoof...     

Structure and activity of DmmA, a marine haloalkane dehalogenase

DmmA is a haloalkane dehalogenase (HLD) identified and characterized from the metagenomic DNA of a marine microbial consortium. Dehalogenase activity was detected with 1,3-dibromopropane as substrate, with steady-state kinetic parameters typical of HLDs (K_m = 0.24 ± 0.05 mM, k_cat = 2.4 ± 0.1 s⁻¹). The 2.2-Å crystal structure of DmmA revealed a fold and active site similar to other HLDs, but with a substantially larger active site binding pocket, suggestive of an ability to act on bulky substrates. This enhanced cavity was shown to accept a range of linear and cyclic substrates, suggesting that DmmA will contribute to the expanding industrial applications of HLDs.     

Hemicellulose modification promotes cadmium hyperaccumulation by decreasing its retention on roots in Sedum alfredii

Plant and Soil - Plant growth in the Arctic is often nutrient limited due to temperature constraints on decomposition and low atmospheric input of nitrogen (N). Local hotspots of nutrient...