Structural Basis of Stereospecificity in the Bacterial Enzymatic Cleavage of β-Aryl Ether Bonds in Lignin.

Lignin is a combinatorial polymer comprising monoaromatic units that are linked via covalent bonds. Although lignin is a potential source of valuable aromatic chemicals, its recalcitrance to chemical or biological digestion presents major obstacles to both the production of second-generation biofuels and the generation of valuable coproducts from lignin's monoaromatic units. Degradation of lignin has been relatively well characterized in fungi, but it is less well understood in bacteria.

RiceNet v2: an improved network prioritization server for rice genes.

Rice is the most important staple food crop and a model grass for studies of bioenergy crops. We previously published a genome-scale functional network server called RiceNet, constructed by integrating diverse genomics data and demonstrated the use of the network in genetic dissection of rice biotic stress responses and its usefulness for other grass species. Since the initial construction of the network, there has been a significant increase in the amount of publicly available rice genomics data.

Cellulosic biomass pretreatment and sugar yields as a function of biomass particle size.

Three lignocellulosic pretreatment techniques (ammonia fiber expansion, dilute acid and ionic liquid) are compared with respect to saccharification efficiency, particle size and biomass composition. In particular, the effects of switchgrass particle size (32-200) on each pretreatment regime are examined. Physical properties of untreated and pretreated samples are characterized using crystallinity, surface accessibility measurements and scanning electron microscopy (SEM) imaging.

Lab to farm: applying research on plant genetics and genomics to crop improvement.

Over the last 300 years, plant science research has provided important knowledge and technologies for advancing the sustainability of agriculture. In this Essay, I describe how basic research advances have been translated into crop improvement, explore some lessons learned, and discuss the potential for current and future contribution of plant genetic improvement technologies to continue to enhance food security and agricultural sustainability.

Glycoside hydrolases from a targeted compost metagenome, activity-screening and functional characterization.

Background: Metagenomics approaches provide access to environmental genetic diversity for biotechnology applications, enabling the discovery of new enzymes and pathways for numerous catalytic processes. Discovery of new glycoside hydrolases with improved biocatalytic properties for the efficient conversion of lignocellulosic material to biofuels is a critical challenge in the development of economically viable routes from biomass to fuels and chemicals.

Results: Twenty-two putative ORFs (open reading frames) were identified from a switchgrass-adapted compost community based on sequence homology to related gene families.

Microfluidic glycosyl hydrolase screening for biomass-to-biofuel conversion.

The hydrolysis of biomass to fermentable sugars using glycosyl hydrolases such as cellulases and hemicellulases is a limiting and costly step in the conversion of biomass to biofuels. Enhancement in hydrolysis efficiency is necessary and requires improvement in both enzymes and processing strategies. Advances in both areas in turn strongly depend on the progress in developing high-throughput assays to rapidly and quantitatively screen a large number of enzymes and processing conditions.

A rapid and inexpensive labeling method for microarray gene expression analysis.

Background: Global gene expression profiling by DNA microarrays is an invaluable tool in biological research. However, existing labeling methods are time consuming and costly and therefore often limit the scale of microarray experiments and sample throughput. Here we introduce a new, fast, inexpensive method for direct random-primed fluorescent labeling of eukaryotic cDNA for gene expression analysis and compare the results obtained on the NimbleGen microarray platform with two other widely-used labeling methods, namely the NimbleGen-recommended double-stranded cDNA protocol and the indirect (aminoallyl) method.