An Integrative Systems Biology approach to define the divergent kinetic responses of S. cerevisiae and C. albicans to amino acid starvation

一种综合系统生物学方法来定义酿酒酵母和白色念珠菌对氨基酸饥饿的不同动力学反应

• 批准号: BB/F010826/1
• 负责人: Al Brown
• 金额: $ 74.08万
• 依托单位: University of Aberdeen
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2008
• 资助国家: 英国
• 起止时间: 2008 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FF010826%2F1
• 关键词: Integrative; Systems; Biology; approach; define

Microbes must adapt to rapid changes in their environment if they are to survive these changes. For example, microbes must be able to adapt their metabolism to use the available nutrients, and they must adapt to nutrient limitation as these nutrients become exhausted. We are comparing how two different yeasts adapt to a particular type of nutrient limitation (amino acid starvation). We are studying bakers' yeast (Saccharomyces cerevisiae) because it is one of the best model organisms available, and because there is already a strong platform of knowledge about the amino acid starvation response in this yeast that has allowed us to build a mathematical model of this response. We are comparing bakers' yeast to Candida albicans because this is a medically important pathogen of humans that frequently causes infections in the mouth and vagina (thrush) and causes life-threatening bloodstream infections in intensive care patients. Clearly these yeasts have evolved in very different niches. Nevertheless we have shown that the pathogenic yeast C. albicans responds in roughly the same way as bakers' yeast to amino acid starvation. However, there are significant differences in the way their responses are regulated. Hence these yeasts appear to have retained a similar solution to the problem (they both make more amino acids via metabolism to overcome the shortage of amino acids), but there are differences in the control systems that regulate their adaptive responses. Both yeasts must respond rapidly to the initial nutrient starvation, but slowly turn off this starvation response as amino acids become available through metabolism. Therefore, the responses in these two yeasts must be effectively managed over time, even though their control systems differ. Our aim is to characterise these interesting differences because they will tell us about how such control systems have evolved in these yeasts. Our approach includes the building of a mathematical model that can describe the amino acid starvation response quantitatively, and that can accurately predict responses to novel experimental conditions. We have built a preliminary model. In this project we will optimise this model for bakers' yeast, and then build an equivalent model for the pathogenic yeast. These mathematical models will be very useful because they will allow us to rapidly simulate (on the computer) large numbers of experiments that are impractical to perform in the lab. This will allow us to focus our efforts in the laboratory on those experiments that are likely to be most interesting and informative. In this way we will characterise the differences between the control systems in these two yeasts. This will generate information about how these control systems have evolved, which will provide valuable messages about the evolution of microbial control systems in general.

微生物必须适应环境的快速变化，才能在这些变化中生存下来。例如，微生物必须能够适应它们的新陈代谢以利用可用的营养素，并且它们必须适应营养素限制，因为这些营养素被耗尽。我们正在比较两种不同的酵母如何适应一种特定类型的营养限制（氨基酸饥饿）。我们正在研究面包酵母（酿酒酵母），因为它是最好的模式生物之一，因为已经有一个强大的平台，了解这种酵母中的氨基酸饥饿反应，使我们能够建立这种反应的数学模型。我们将面包酵母与白色念珠菌进行比较，因为这是一种医学上重要的人类病原体，经常导致口腔和阴道感染（鹅口疮），并在重症监护患者中导致危及生命的血流感染。很明显，这些酵母在非常不同的生态位中进化。尽管如此，我们已经表明，致病酵母C。白色念珠菌对氨基酸饥饿的反应方式与面包酵母大致相同。然而，它们的反应调节方式存在重大差异。因此，这些酵母似乎保留了解决问题的类似方法（它们都通过代谢产生更多的氨基酸，以克服氨基酸的短缺），但调节其适应性反应的控制系统存在差异。两种酵母都必须对初始的营养饥饿迅速作出反应，但随着氨基酸通过代谢变得可用，缓慢地关闭这种饥饿反应。因此，这两种酵母的反应必须随着时间的推移进行有效管理，即使它们的控制系统不同。我们的目标是阐明这些有趣的差异，因为它们将告诉我们这些控制系统是如何在这些酵母中进化的。我们的方法包括建立一个数学模型，可以定量描述氨基酸饥饿反应，并可以准确地预测新的实验条件下的反应。我们建立了一个初步的模型。在这个项目中，我们将优化这个模型的面包酵母，然后建立一个等价的模型致病酵母。这些数学模型将是非常有用的，因为它们将使我们能够（在计算机上）快速模拟大量在实验室中不切实际的实验。这将使我们能够将实验室的工作重点放在那些可能最有趣和最有信息量的实验上。通过这种方式，我们将分析这两种酵母中控制系统之间的差异。这将产生有关这些控制系统如何演变的信息，这将提供有关微生物控制系统总体演变的有价值的信息。

项目成果

Microbial signaling and systems biology.

微生物信号传导和系统生物学。

• DOI: 10.1186/gb-2010-11-5-302
• 发表时间: 2010
• 期刊: Genome biology
• 影响因子: 12.3
• 作者: Brown AJ

Drug-mediated metabolic tipping between antibiotic resistant states in a mixed-species community.

• DOI: 10.1038/s41559-018-0582-7
• 发表时间: 2018-08
• 期刊: Nature ecology & evolution
• 影响因子: 16.8
• 作者: Beardmore RE;Cook E;Nilsson S;Smith AR;Tillmann A;Esquivel BD;Haynes K;Gow NAR;Brown AJP;White TC;Gudelj I
• 通讯作者: Gudelj I

Metabolism impacts upon Candida immunogenicity and pathogenicity at multiple levels.

• DOI: 10.1016/j.tim.2014.07.001
• 发表时间: 2014-11
• 期刊: TRENDS IN MICROBIOLOGY
• 影响因子: 15.9
• 作者: Brown, Alistair J. P.;Brown, Gordon D.;Netea, Mihai G.;Gow, Neil A. R.
• 通讯作者: Gow, Neil A. R.

Impact of the transcriptional regulator, Ace2, on the Candida glabrata secretome.

转录调节因子 Ace2 对光滑念珠菌分泌组的影响。

• DOI: 10.1002/pmic.200800706
• 发表时间: 2010
• 期刊: Proteomics
• 影响因子: 3.4
• 作者: Stead DA

Stress adaptation in a pathogenic fungus.

• DOI: 10.1242/jeb.088930
• 发表时间: 2014-01-01
• 期刊: The Journal of experimental biology
• 作者: Brown AJ;Budge S;Kaloriti D;Tillmann A;Jacobsen MD;Yin Z;Ene IV;Bohovych I;Sandai D;Kastora S;Potrykus J;Ballou ER;Childers DS;Shahana S;Leach MD
• 通讯作者: Leach MD