In silico study of lignocellulosic biofuel processes

理论上，基因组序列提供了定义感兴趣的生物系统结构所需的所有信息。例如，知道细胞中的所有酶和每种酶接受的底物以及每种酶可以产生的所有产物，就可以制定一个生物反应主全局网络，该网络代表该细胞内可能的生化反应系统的完整库。在这项研究中，我们计划使用一个“基因组规模”的代谢网络（gsmn），从生物燃料生产中应用的一些物种的序列数据重建。GSMNS已经发表了许多医学和工业上重要的物种，包括天蓝色链霉菌和结核分枝杆菌（我们的这两个），分别促进了抗生素靶标的工艺设计和鉴定的新方法。我们计划使用基因组规模建模来证明计算机实验对生物精炼的效用。该方法将把能够进行木质纤维素降解的基因组与能够生产生物燃料的基因组联系起来，以期预测将构成体内研究基础的过程。据我们所知，这将是第一个以这种方式连接基因组规模模型的项目，因此除了提供实用信息外，还将代表科学进步。这两个阶段（生物质降解，然后是单独的生物乙醇生产阶段）可能比单个微生物处理步骤更有效。生物质降解两种“模式生物”（真菌里氏木霉和细菌热纤梭菌）的基因组最近已被测序，因此，这些物种将被纳入研究。然而，考虑到目前木质纤维素降解对酸和热预处理的依赖性，在低pH值和高温下稳定且有活性的酶具有特别的价值。因此，来源于已知降解木质纤维素的嗜热和嗜酸生物的酶对于工业过程具有重要的前景，并且由于这个原因，解糖热纤维素菌和解纤维素酸热菌（两者都已测序）将被包括在生物质降解阶段中。生物燃料生产一个重要的产量限制因素是乙醇对发酵宿主的毒性。大多数发酵生物如S.酿酒酵母不能耐受高乙醇浓度，导致产物必须通过昂贵且耗能的蒸馏步骤浓缩。树干毕赤酵母代表了一种基于其天然发酵木糖的能力而与生物燃料研究相关的酵母物种。其最近测序的基因组揭示了对负责这一过程的代谢途径的见解，该物种将被包括在我们的第二阶段建模运动发酵单胞菌中，运动发酵单胞菌被描述为具有相当大的生物燃料生产潜力，最近也被测序，并将被包括在内。大肠杆菌，它已被改造为生产异丁醇和其他醇，使用非发酵途径，将包括在内。生物质降解的原料将包括木质纤维素（有和没有化学预处理）和共基质，这可能会提高代谢的生物能源效率。四个物种中的每一个都将有gsmns构建。在每种情况下，将准备一个“草案”gsmn（使用序列注释），将通过添加进一步的反应来细化，以“关闭"模型。每个gsmn都包括许多（通常是数百个）“输入门”，即潜在的底物，由基因序列预测，但从未在实验室中尝试过。使用计算机模型，我们将能够检查需要多年体内实验的底物组合的效果。

In theory, a genome sequence provides all of the information necessary to define the structure of the biological system of interest. For example, knowing all of the enzymes in a cell and the substrates that each one accepts and all of the products that each one can make, it is possible to formulate a bioreaction master global network that represents the complete repertoire of possible biochemical reaction systems within that cell. In this study, we plan to use a 'genome-scale' metabolic network (gsmn), reconstructed from the sequence data for a number of species with applications in biofuel production. Gsmns have already been published for a number of medically- and industrially-important species, including Streptomyces coelicolor and Mycobacterium tuberculosis (these 2 by us) facilitating novel approaches to process design and identification of antibiotic targets, respectively. We plan to use genome scale modelling to demonstrate the utility of in silico experimentation to Biorefining. The approach will link genomes, capable of carrying out lignocellulose degradation to genomes able to produce biofuels, with a view to predicting processes that will form the basis for an in vivo study. As far as we are aware, this will be the first project to link genome scale models in this way, and will therefore represent a scientific advance in addition to providing pragmatic information. This 2-stage (biomass degradation followed by a separate bioethanol production stage) is potentially more efficient than a single microbial processing step. Biomass Degradation The genomes of two 'model organisms' (the fungus Trichoderma reesei and the bacterium Clostridium thermocellum) have recently been sequenced and these species will, therefore, be included in the study. However, considering the current dependence on acid and heat pre-treatment in lignocellulose degradation, enzymes that are stable and active at low pH values and at high temperatures are of particular value. Thus, enzymes derived from thermophilic and acidophilic organisms known to degrade lignocellulose hold significant promise for industrial processes, and, for this reason Caldicellulosiruptor saccharolyticus and Acidothermus cellulolyticus (both of which have been sequenced) will be included in the biomass degradation stage. Biofuel production A significant yield limiting factor is the toxicity of ethanol to the fermenting host. Most fermenting organisms such as S. cerevisiae cannot tolerate high ethanol concentrations resulting in a product that must then be concentrated through an expensive and energy-intensive distillation step. Pichia stipitis represents one yeast species of relevance to biofuel research based on its natural ability to ferment xylose. Its recently sequenced genome revealed insights into the metabolic pathways responsible for this process and this species will be included in our second stage modelling Zymomonas mobilis, which has been described as having considerable potential for biofuel production has also been sequenced recently and will be included Finally, the use of E. coli, which has been engineered to produce isobutanol and other alcohols, using non-fermentative pathways, will be included. The feed-stocks to be examined for biomass degradation will include lignocellulose (with and without chemical pre-treatment) and co-substrates, which may enhance bioenergetic efficiency of metabolism. Each of the four species will have gsmns constructed. In each case, a 'draft' gsmn will be prepared (using the sequence annotations) which will be refined by the addition of further reactions in order to 'close' the model. Each gsmn includes numerous (often hundreds of) 'input gates', ie potential substrates, predicted by the gene sequence but never tried in the laboratory. Using in silico models, we will be able to examine the effect of combinations of substrates that would require many years of experimentation in vivo.