Systems Biology of Hydrogen Oxidising Bacteria for the Production of High Quality Feed Protein and Other Feed Ingredients

预计到2050年，世界人口将达到100亿，这就需要大幅度增加粮食生产。人均蛋白质摄入量预计也将大幅上升。因此，需要大幅度增加食物蛋白质产量以满足需求。传统的蛋白质来源与温室气体排放和对生物多样性的影响有关。因此，迫切需要大规模的创新、可持续的蛋白质生产。氢氧化细菌是一种有前途的替代品，可作为所谓的单细胞蛋白质的可持续来源。目的和方法：这项研究将与我们的工业合作伙伴Deep分支生物技术有限公司（www.deepbranchbio.com）密切合作，Deep是一家位于诺丁汉的公司，该公司正在彻底改变使用细菌将工业碳捕获到饲料成分中的方法。饲料或食品的营养价值在很大程度上取决于细胞蛋白质含量和组成。更深入地了解不同的细菌生长条件如何影响这些参数将有利于工业和进一步我们对细菌细胞代谢的科学理解。该项目将使用一套模式生物和工业菌株，通过系统地改变培养条件、对所产生的生物质进行成分分析以及对在不同条件下生长的细菌细胞进行组学分析来解决这一问题。结合预测建模，生成的数据将有助于建立所观察到的变化的分子基础和潜在的潜在机制。实验室中发现的有利条件将用工业生产的CO2进行大规模测试。作为提供培训的一部分，深分支生物技术将提供在工业现场获得经验的机会。

The world's population is predicted to reach 10 billion by 2050, requiring significant increases in food production. The intake of protein per person is also expected to rise sharply. Hence, a substantial increase in food protein production is needed to meet demands. Conventional sources of protein are linked to greenhouse gas emissions and impact on biodiversity. Hence, there is an urgent need for innovative, sustainable protein production at scale. Hydrogen oxidising bacteria are a promising alternative as a sustainable source of so-called single cell protein. These bacteria fix CO2 and generate protein-rich biomass using hydrogen as a source of energy.Aims and approach: The proposed study will be undertaken in close collaboration with our industrial partner, Deep Branch Biotechnology Ltd (www.deepbranchbio.com), a Nottingham based company that is revolutionising the use of bacteria to capture industrial carbon into feed ingredients. The nutritional value of a feed or food product strongly depends on cellular protein content and composition. A deeper understanding of how different bacterial growth conditions impact these parameters would be beneficial to industry and further our scientific understanding of bacterial cell metabolism. Using a set of model organisms and industrial strains, the project will seek to address this by systematic variation of culturing conditions, compositional analysis of the created biomass and omics analysis of bacterial cells grown under the different conditions. In combination with predictive modelling the generated data will help to establish the molecular basis of the observed changes and potential underlying mechanisms. Conditions found to be favourable in the laboratory will be tested at large scale with industrially produced CO2. As part of the offered training, Deep Branch Biotechnology will offer the opportunity to gain experience at an industrial site.