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Using systems biology approaches to study a multidrug resistance network

机译:使用系统生物学方法研究多药耐药性网络

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Multidrug resistance (MDR), a phenomenon with impact in Human Health and in Agro-Food and Environmental Biotechnology, often results from the activation of drug efflux pumps, many times controlled at the transcriptional level. The complex transcriptional control of these genes has been on the focus of our research, guided by the information gathered in the YEASTRACT database. In this paper, the approach used to elucidate the transcriptional control of FLR1, encoding a Saccharomyces cerevisiae Drug:H+ Antiporter, in response to stress induced by the fungicide mancozeb is explained. The transcription regulatory network underlying FLR1 activation was defined based on experimental data. Subsequently, a mathematical model describing this network was built and its response to mancozeb stress in different genetic backgrounds was simulated, using the Genetic Network Analyzer (GNA) software. This approach allowed the identification of essential features of the transition from unstressed to fungicide stressed cells and to make new predictions on the dynamical behavior of the system, which were validated experimentally. This work provides a good example of the successful combination of experimental and computational approaches in a systems biology perspective.
机译:多药耐药性(MDR)是一种对人体健康以及农业食品和环境生物技术产生影响的现象,通常是由药物外排泵的激活引起的,多次被控制在转录水平上。这些基因的复杂转录控制一直是我们研究的重点,并以YEASTRACT数据库中收集的信息为指导。本文解释了用于阐明FLR1的转录控制的方法,该方法可对杀菌剂mancozeb诱导的应激反应,编码啤酒酵母:H + Antiporter。基于实验数据定义了FLR1激活基础的转录调控网络。随后,使用遗传网络分析器(GNA)软件建立了描述该网络的数学模型,并模拟了其在不同遗传背景下对代森锰锌胁迫的响应。这种方法可以识别从无应力细胞向杀真菌剂胁迫的细胞过渡的基本特征,并可以对系统的动力学行为做出新的预测,并通过实验进行了验证。这项工作为从系统生物学的角度成功地结合实验和计算方法提供了一个很好的例子。

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