An integrated approach to produce biodiesel and monoglycerides by enzymatic interestification of babassu oil (Orbinya sp)

Two screenings of commercial lipases were performed to find a lipase with superior performance for the integrated production of biodiesel and monoglycerides. The first screening was carried out under alcoholysis conditions using ethanol as acyl acceptor to convert triglycerides to their corresponding ethyl esters (biodiesel). The second screening was performed under glycerolysis conditions to yield monoglycerides (MG). All lipases were immobilized on silica-PVA composite by covalent immobilization. The assays were performed using babassu oil and alcohols (ethanol or glycerol) in solvent free systems. For both substrates, lipase from Burkholderia cepacia (lipase PS) was found to be the most suitable enzyme to attain satisfactory yields. To further improve the process, the Response Surface Methodology (RSM) was used to determine the optima operating conditions for each biotransformation. For biodiesel production, the highest transesterification yield (>98%) was achieved within 48 h reaction at 39 degrees C using an oil-to-ethanol molar ratio of 1:7. For MG production, optima conditions corresponded to oil-to-glycerol molar ratio of 1: 15 at 55 degrees C, yielding 25 wt.% MG in 6 h reaction. These results show the potential of B. cepacia lipase to catalyze both reactions and the feasibility to consider an integrated approach for biodiesel and MG production. (C) 2009 Elsevier Ltd. All rights reserved.

Strategies for genetic model specification in the screening of genome-wide meta-analysis signals for further replication

Background Meta-analysis is increasingly being employed as a screening procedure in large-scale association studies to select promising variants for follow-up studies. However, standard methods for meta-analysis require the assumption of an underlying genetic model, which is typically unknown a priori. This drawback can introduce model misspecifications, causing power to be suboptimal, or the evaluation of multiple genetic models, which augments the number of false-positive associations, ultimately leading to waste of resources with fruitless replication studies. We used simulated meta-analyses of large genetic association studies to investigate naive strategies of genetic model specification to optimize screenings of genome-wide meta-analysis signals for further replication. Methods Different methods, meta-analytical models and strategies were compared in terms of power and type-I error. Simulations were carried out for a binary trait in a wide range of true genetic models, genome-wide thresholds, minor allele frequencies (MAFs), odds ratios and between-study heterogeneity (tau(2)). Results Among the investigated strategies, a simple Bonferroni-corrected approach that fits both multiplicative and recessive models was found to be optimal in most examined scenarios, reducing the likelihood of false discoveries and enhancing power in scenarios with small MAFs either in the presence or in absence of heterogeneity. Nonetheless, this strategy is sensitive to tau(2) whenever the susceptibility allele is common (MAF epsilon 30%), resulting in an increased number of false-positive associations compared with an analysis that considers only the multiplicative model. Conclusion Invoking a simple Bonferroni adjustment and testing for both multiplicative and recessive models is fast and an optimal strategy in large meta-analysis-based screenings. However, care must be taken when examined variants are common, where specification of a multiplicative model alone may be preferable.

Next Generation Sequencing of Pooled Samples Reveals New SNRNP200 Mutations Associated with Retinitis Pigmentosa

The gene SNRNP200 is composed of 45 exons and encodes a protein essential for pre-mRNA splicing, the 200 kDa helicase hBrr2. Two mutations in SNRNP200 have recently been associated with autosomal dominant retinitis pigmentosa (adRP), a retinal degenerative disease, in two families from China. In this work we analyzed the entire 35-Kb SNRNP200 genomic region in a cohort of 96 unrelated North American patients with adRP. To complete this large-scale sequencing project, we performed ultra high-throughput sequencing of pooled, untagged PCR products. We then validated the detected DNA changes by Sanger sequencing of individual samples from this cohort and from an additional one of 95 patients. One of the two previously known mutations (p.S1087L) was identified in 3 patients, while 4 new missense changes (p.R681C, p.R681H, p.V683L, p.Y689C) affecting highly conserved codons were identified in 6 unrelated individuals, indicating that the prevalence of SNRNP200-associated adRP is relatively high. We also took advantage of this research to evaluate the pool-and-sequence method, especially with respect to the generation of false positive and negative results. We conclude that, although this strategy can be adopted for rapid discovery of new disease-associated variants, it still requires extensive validation to be used in routine DNA screenings. (C) 2011 Wiley-Liss, Inc.