Reduction in fossil fuel consumption by using alternate sources of energy is a major challenge facing mankind in the coming decades. Bioethanol production using lignocellulosic biomass is the most viable option for addressing this challenge. Industrial bioconversion of lignocellulosic biomass, though possible now, is not economically viable due to presence of barriers that escalate the cost of production. As cellulose and hemicellulose are the major constituents of terrestrial biomass, which is available in massive quantities, hydrolysis of cellulose and hemicellulose by the microorganisms are the most prominent biochemical processes happening in the earth. Microorganisms possess different categories of proteins associated with different stages of bioethanol production and a number of them are already found and characterized. Many more of these proteins need to be identified which suit the specificities needed for the bioethanol production process. Discovery of proteins with novel specificities and application of genetic engineering technologies to harvest the synergies existing between them with the aim to develop consolidated bioprocess is the major direction of research in the future. In this review, we discuss the different categories of proteins used for bioethanol production in the context of breaking the barriers existing for the economically feasible lignocellulosic bioethanol production.
The interactions between crop plants and the endophytic bacteria colonizing them are poorly understood and experimental methods were found to be inadequate to meet the complexities associated with the interaction. Moreover, research on endophytic bacteria was focused at host plant species level and not at cultivar level which is essential for understanding the role played by them on the productivity of specific crop genotype. High throughput genomics offers valuable tools for identification, characterization of endophytic bacteria and understand their interaction with host plants. In this paper we report the use of high throughput plant genomic data for identification of endophytic bacteria colonizing rice plants. Using this novel next generation sequencing based computational method Sphingopyxis granuli and Pseudomonas aeruginosa were identified as endophytes colonizing the elite indica rice cultivar RP Bio-226 and their draft genome sequences were assembled.
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