Analysis, Predictive Modelling and In Vitro Validation of Gene Expression During 2-aminoethylphosphonate Metabolism in Sinorhizobium meliloti 1021.

这项研究项目是一位微生物学家和一位控制系统工程师的合作努力，他们对研究数学模型可以用来预测细菌系统中的基因表达的方法有共同的兴趣。这项建议将使申请者能够在其学科的界面上发展专门知识，从而对复杂生物系统的机制有新的见解。预计这将启动一个超越该项目的长期合作研究计划，重点是工业和医疗应用中生物系统的治疗和操纵方面的发展。在这项研究中，我们使用一个相对简单的系统，即生物降解氨基酸β-丙氨酸类似物的代谢路线，称为2-氨基乙基膦酸根。这种化合物具有共价碳-磷(C-P)键，使其非常耐酶攻击。然而，在土壤细菌Meliloti 1021中，有一条新的途径允许这种微生物利用2AEP作为生长所需的碳、氮和磷的来源。这条途径的不同寻常之处在于它会产生一种抗病毒化合物--乙酸膦，作为新陈代谢的中间产物：这是一种新的现象，到目前为止还没有在细菌中观察到，我们希望更多地了解该途径的基因是如何对不同的环境条件做出反应的。我们希望找出参与2AEP代谢的五个基因在活跃生长在2AEP上的细菌培养物中是否存在差异表达。为了做到这一点，我们将使用一种名为逆转录酶聚合酶链式反应(RT-PCR)的技术，该技术将允许我们参照已知DNA数量的标准来测量在2AEP上生长期间从培养物中取出的几个细胞样本中的基因表达水平。我们将在这项工作中产生的数据将是最高质量的，因此将在数据的可靠性和严谨性方面作为基准研究，并应引起系统生物学研究人员的极大兴趣。他工作的一个主要目标是开发建模技术，使细胞过程的真实生化途径得以揭示。因此，该项目的一个主要方面致力于研究将生物化学的知识和分析与数学分析结合起来的方法。这将使我们能够开发一个全面的系统模型，然后我们将使用该模型来预测基因表达的动态，以响应不同的2AEP底物浓度和营养限制。验证所提出的模型的可行性是极其重要的，在严格的模拟测试之后，将对喂入少量2AEP的细菌培养物进行进一步的有针对性的基因表达分析，以检验计算机预测。该模型的生物学意义将从理解土壤微生物对营养物质流入的反应、确定细胞控制机制以及系统对环境噪声的稳健性等方面进行研究。这项研究将引起对有机膦化合物新陈代谢感兴趣的科学家的兴趣，有机膦化合物广泛应用于医药、农业和工业。开发的技术也将对生化途径动力学建模领域的其他人产生更广泛的兴趣。这些技术可以用于预测类似系统中的基因表达行为，也许包括那些与某些细菌的发病有关的系统，这可能为开发新的抗菌剂提供一个起点。研究人员将从这项工作中受益匪浅，这种互惠的科学交流拓宽了他们对系统生物学实验可能被输入并用于设计新陈代谢预测模型的方式的理解。

This research project is a collaborative effort between a microbiologist and a control systems engineer who have a shared interest in examining the ways in which mathematical models can be used to predict gene expression in bacterial systems. This proposal will enable the applicants to develop expertise at the interface of their disciplines leading to new insight in the mechanisms of complex biological systems. This is expected to initiate a long-term collaborative research program beyond this project, focused on developments in the treatment and manipulation of biological systems for industrial and medical applications. For this investigation, we are using a relatively simple system, namely the metabolic route for biodegradation of an analogue of the amino acid beta-alanine, called 2-aminoethylphosphonate. This compound has a covalent carbon to phosphorus (C-P) bond that makes it very resistant to enzymatic attack. However, in the soil bacterium Sinorhizobium meliloti 1021 there is a novel pathway that allows this microorganism to use 2AEP as a source of carbon, nitrogen and phosphorus for growth. The pathway is unusual in that it generates an antiviral compound, phosphonoacetate, as an intermediate in metabolism: this is a new phenomenon, which has not been observed in bacteria until now and we wish to know more about the way in which the genes of the pathway are expressed in response to different environmental conditions. We wish to find out whether or not the five genes involved in the metabolism of 2AEP are differentially expressed in bacterial cultures that are actively growing on 2AEP. In order to do this, we will use a technique called reverse transcriptase PCR (RT-PCR) which will allow us to measure, with reference to standards of known amounts of DNA, the levels of gene expression in several samples of cells removed from cultures during growth on 2AEP. The data we will produce during this work will be of the highest quality and will therefore serve as a benchmark study in terms of both reliability and rigour of data, and should be of significant interest to systems biology researchers.A principal aim of his work is to develop modelling techniques which enable the true biochemical pathway of cellular processes to be uncovered. A major aspect of this project is therefore devoted to investigating methods for bringing together knowledge and analysis of the biochemistry with mathematical analysis. This will enable the development of a comprehensive system model, which we will then use to make predictions of the dynamics of gene expression in response to different 2AEP substrate concentrations and nutrient limitations. Validation of the feasibility of the proposed model is extremely important and following rigorous simulation tests, further targeted gene expression analysis will be carried out on bacterial cultures fed with small amounts of 2AEP in order to test the in silico predictions. The biological implications of the model will be studied in terms of understanding of the responses of soil microbes to nutrient influx; determining the cellular control mechanisms; and robustness of the system to environmental noise. The research will be of interest to scientists interested in metabolism of organophosphonate compounds, which are widely used in medicine, agriculture and industry. The techniques developed will also be of wider interest to others in the field of modelling biochemical pathways dynamics. The techniques could be of use in predicting gene expression behaviour in similar systems, including perhaps those related to pathogenesis of certain bacteria and this could provide a starting point for the development of new antimicrobials. The investigators will benefit significantly from the work, with the reciprocal scientific interchange broadening their understanding of the ways by which systems biology experiments may be fed into and used to design predictive models of metabolism.