Recent advances in the molecular biology of Leifsonia xyli subsp xyli, causal organism of ratoon stunting disease

Twelve years ago our understanding of ratoon stunting disease (RSD) was confined almost exclusively to diagnosis of the disease and control via farm hygiene, with little understanding of the biology of the interaction between the causal agent (Leifsonia xyli subsp. xyli) and the host plant sugarcane (Saccharum spp. hybrids). Since then, research has focused on developing the molecular tools to dissect L. xyli subsp. xyli, so that better control strategies can be developed to prevent losses from RSD. Within this review, we give a brief overview of the progression in research on L. xyli subsp. xyli and highlight future challenges. After a brief historical background on RSD, we discuss the development of molecular tools such as transformation and transposon mutagenesis and discuss the apparent lack of genetic diversity within the L. xyli subsp. xyli world population. We go on to discuss the sequencing of the genome of L. xyli subsp. xyli, describe the key findings and suggest some future research based on known deficiencies that will capitalise on this tremendous knowledge base to which we now have access.

Recent advances in alcohol-induced adduct formation

This article presents the proceedings of a symposium presented at the ISBRA 12th World Congress on Biomedical Alcohol Research, held in Heidelberg/Mannheim, Germany, September 29 through October 2, 2004. The organizers of the symposium were Simon Worrall and Victor Preedy, and the symposium was chaired by Onni Niemelä and Geoffrey Thiele. The presentations scheduled for this symposium were (1) Adduct chemistry and mechanisms of adduct formation, by Thomas L. Freeman; (2) Malondialdehyde- acetaldehyde adducts: the 2004 update, by Geoffrey Thiele; (3) Adduct formation in the liver, by Simon Worrall; (4) Protein adducts in alcoholic cardiomyopathy, by Onni Niemelä; and (5) Alcoholic skeletal muscle myopathy: a role for protein adducts, by Victor R. Preedy.

Recent advances in catalysts for methanol synthesis via hydrogenation of CO and CO2

Since the start of last century, methanol synthesis has attracted great interests because of its importance in chemical industries and its potential as an environmentally friendly energy carrier. The catalyst for the methanol synthesis has been a key area of research in order to optimize the reaction process. In the literature, the nature of the active site and the effects of the promoter and support have been extensively investigated. In this updated review, the recent progresses in the catalyst innovation, optimization of the reaction conditions, reaction mechanism, and catalyst performance in methanol synthesis are comprehensively discussed. Key issues of catalyst improvement are highlighted, and areas of priority in R&D are identified in the conclusions.

Recent advances in understanding the eutectic solidification in Al-Si foundry alloys

The formation of the Al-Si eutectic is generally the final stage of the solidification process of Al-Si foundry alloys. This means that it can be expected to have a significant impact on the feeding of a casting, and consequently the formation of casting defects, in particular porosity. Understanding and controlling the eutectic solidification process are therefore very important. This paper reviews the recent advances and unique techniques used in improving our understanding of both eutectic nucleation and growth. The role of different modifiers in controlling the eutectic solidification mechanisms is presented and the relationship between eutectic solidification mechanisms and porosity formation is outlined. This new approach to aluminium foundry alloy metallurgy is likely to form the basis for further optimisation of alloy performance and master alloys for the future.

Physical enhancement of transdermal drug application: is delivery technology keeping up with pharmaceutical development?

Advances in molecular biology have given us a wide range of protein and peptide-based drugs that are unsuitable for oral delivery because of their high degree of first-pass metabolism. Though parenteral delivery is the obvious answer, for the successful development of commercial chronic and self-administration usage formulations it is not the ideal choice. Transdermal delivery is emerging as the biggest application target for these agents, however, the skin is extremely efficient at keeping out such large molecular weight compounds and therapeutic levels are never going to be realistically achieved by passive absorption. Physical enhancement mechanisms including: iontophoresis, electroporation, ultrasound, photomechanical waves, microneedles and jet-propelled particles are emerging as solutions to this topical delivery dilemma. Adding proteins and peptides to the list of other large molecular weight drugs with insufficient passive transdermal fluxes to be therapeutically useful, we have a collection of pharmacological agents waiting for efficient delivery methods to be introduced. This article reviews the current state of physical transdermal delivery technology, assesses the pros and cons of each technique and summarises the evidence-base of their drug delivery capabilities.

Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding for complex traits because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. In this study, we explored whether physiological dissection and integrative modelling of complex traits could link phenotype complexity to underlying genetic systems in a way that enhanced the power of molecular breeding strategies. A crop and breeding system simulation study on sorghum, which involved variation in 4 key adaptive traits-phenology, osmotic adjustment, transpiration efficiency, stay-green-and a broad range of production environments in north-eastern Australia, was used. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages assuming gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies in the data. Based on the analyses of gene effects, a range of marker-assisted selection breeding strategies was simulated. It was shown that the inclusion of knowledge resulting from trait physiology and modelling generated an enhanced rate of yield advance over cycles of selection. This occurred because the knowledge associated with component trait physiology and extrapolation to the target population of environments by modelling removed confounding effects associated with environment and gene context dependencies for the markers used. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate genetic regions.

Trait physiology and crop modelling to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. We explore whether a crop growth and development modelling framework can link phenotype complexity to underlying genetic systems in a way that strengthens molecular breeding strategies. We use gene-to-phenotype simulation studies on sorghum to consider the value to marker-assisted selection of intrinsically stable QTLs that might be generated by physiological dissection of complex traits. The consequences on grain yield of genetic variation in four key adaptive traits – phenology, osmotic adjustment, transpiration efficiency, and staygreen – were simulated for a diverse set of environments by placing the known extent of genetic variation in the context of the physiological determinants framework of a crop growth and development model. It was assumed that the three to five genes associated with each trait, had two alleles per locus acting in an additive manner. The effects on average simulated yield, generated by differing combinations of positive alleles for the traits incorporated, varied with environment type. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages with gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies. We simulated a marker-assisted selection (MAS) breeding strategy based on the analyses of gene effects. When marker scores were allocated based on the contribution of gene effects to yield in a single environment, there was a wide divergence in rate of yield gain over all environments with breeding cycle depending on the environment chosen for the QTL analysis. It was suggested that knowledge resulting from trait physiology and modelling would overcome this dependency by identifying stable QTLs. The improved predictive power would increase the utility of the QTLs in MAS. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate QTLs.

Structure and dynamics of a gene network model incorporating small RNAs

As advances in molecular biology continue to reveal additional layers of complexity in gene regulation, computational models need to incorporate additional features to explore the implications of new theories and hypotheses. It has recently been suggested that eukaryotic organisms owe their phenotypic complexity and diversity to the exploitation of small RNAs as signalling molecules. Previous models of genetic systems are, for several reasons, inadequate to investigate this theory. In this study, we present an artificial genome model of genetic regulatory networks based upon previous work by Torsten Reil, and demonstrate how this model generates networks with biologically plausible structural and dynamic properties. We also extend the model to explore the implications of incorporating regulation by small RNA molecules in a gene network. We demonstrate how, using these signals, highly connected networks can display dynamics that are more stable than expected given their level of connectivity.