Red Clover: a feedstock for sustainable integrated biorefining

Lead Research Organisation: Aberystwyth University
Department Name: IBERS


To achieve truly sustainable integrated biorefining the entire value chain of the process from feedstock to production to material disposal has to be designed, evaluated and optimised. Red clover, a legume, has the potential to play a significant role in supporting truly sustainable integrated biorefining. The commercial partner, Verzyme (UK) Ltd, has considerable interest in developing the application of red clover as both a feed stock for integrated biorefining but also a host for heterologous protein production i.e. industrial enzymes in a red clover leaves post harvest under controlled conditions. The proposal has two principal goals: 1. develop clover as a potential feedstock to support integrated biorefining, where clover proteins can be used for the production of bio-plastics; 2. Identify clover lines which support enhanced production of heterologous protein production in clover leaves under post harvest conditions; A common feature of the two goals is to develop an understanding of the biochemistry and physiological response of red clover under post harvest conditions. This will involve developing an understanding at the molecular and biochemical level of the processes which are initiated when clover leaves are detached, with the goal of preserving the integrated of the leaf /cell until down stream processing is applied. The project has three broad objectives: (i)Inter-cropping strategies between red clover (Trifolium pratense) and oats (Avena sativa ) will be evaluated and optimised, with a view to obtaining a cereal harvest and a red clover harvest during a single season thereby maximise the benefits of reduced inputs. To achieve this, cropping strategies, seeding densities, and establishment strategies will be defined which support the growth of red clover as an intercrop with oats. The optimal configuration will allow a cereal being sown into an establish crop of red clover, in the spring after an early cut of clover. The cereal establishes, and is harvested late summer, allowing the red clover to recover and a second cut taken. (ii)To improve post harvest stability of red clover to enhance its utility as a feedstock to support sustainable integrated biorefining. An extensive range of red clover germplasm including populations, breeding lines and varieties held at IBERS will be screened to evaluate the biochemical, molecular and physiological response under post harvest conditions, identifying lines with reduced rates of senescence. There is already a considerable body of work on gene expression and proteomics during natural senescence and post harvest response within red and white clovers this data will be mined to identify potential candidate genes. The selected genes will then be used as potential marker/indicators of the leaves response when detached. It is important to stress that while we refer to the process as senescence, detaching a leaf and following the response post harvest is not natural senescence, therefore it is likely that additional genes may be involved. To address this affy chip microarray will be used screen RNA populations from lines selected from the biochemical and physiological studies. Using the company's proprietary transient expression technology the expression of candidate genes will be modulated using a combination of RNAi and over expression strategies, with a view to verifying the gene functional role in post harvest stability (iii)The goal is to build on the identification of red clover lines with improved post harvest stability and performance. We will identify red clover lines which support enhanced levels of transient transcription and translation under post harvest conditions. To achieve this goal the company will provide proprietary expression technology which will support transient expression within a clover leaf/cell background. A range of molecular expression techniques such as Real time PCR and run off experiments coupled to protein quantification will be applied.


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