The architecture and dynamics of microbial interaction networks in food model ecosystems

食物模型生态系统中微生物相互作用网络的结构和动态

• 批准号: RGPIN-2017-04771
• 负责人: Filteau, Marie
• 金额: $ 4.37万
• 依托单位: Université Laval
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=765363
• 关键词: architecture; dynamics; microbial; interaction; networks

Microorganisms are the most abundant and diverse form of life on earth. They form complex communities that perform essential functions in various ecosystems, which benefit the environment, agriculture and our health. Interactions between microorganisms may be crucial to these ecosystems functions, if for example a function depends on the presence of complementary species. Therefore, understanding microbial communities at the systems level, that is considering the interplay between microorganisms, is a major challenge, especially for food production where controlling microbial contamination is critical. The meat industry in particular is in dire need of new microbial control strategies as over 20 % of the 263 million tonnes of meat produced in the world each year is thrown away partly because of microbial spoilage. Taking advantage of novel technologies involving high throughput sequencing and systems biology approaches, this project aims at characterizing the interactions between members of a meat model microbial community with the ultimate goal of helping envision new microbial control strategies. The meat environment sustains a wide diversity of microorganisms and represents a tractable system of reduced complexity well suited for experimental microbial community experiments. A first output of the project will be to describe the structure of the microbial community and the contribution of each member to community assembly and functions, demonstrating the feasibility of experimentally manipulating complex microbiota in vitro. A second output will be to systematically map the relationships between members and explain their role in community properties, thus expanding our system level understanding of microbial communities. A third output will be to use our model and interaction network to predict the effects of biotic and abiotic antimicrobial treatments on meat microbial spoilage. Research efforts to decipher mechanisms underlying microbial community ecology will be welcome in coming years to establish new microbial control strategies to reduce waste of meat and eventually other food products. Thus, this program will ultimately benefit the Canadian food industry and its consumers by taking a step forward towards sustainability and by helping maintain Canada at the forefront of food science R&D.

微生物是地球上数量最多、种类最多的生命形式。它们形成复杂的群落，在各种生态系统中发挥重要作用，有利于环境、农业和我们的健康。例如，如果一种功能依赖于互补物种的存在，那么微生物之间的相互作用可能对这些生态系统功能至关重要。因此，在系统层面理解微生物群落，即考虑微生物之间的相互作用，是一项重大挑战，特别是对于控制微生物污染至关重要的食品生产。肉类行业尤其迫切需要新的微生物控制策略，因为世界上每年生产的2.63亿吨肉类中有20%以上是由于微生物腐败而被丢弃的。利用涉及高通量测序和系统生物学方法的新技术，该项目旨在描述肉类模型微生物群落成员之间的相互作用，最终目标是帮助设想新的微生物控制策略。肉类环境维持了广泛的微生物多样性，代表了一个可处理的系统，降低了复杂性，非常适合实验微生物群落实验。该项目的第一个成果将是描述微生物群落的结构和每个成员对群落组装和功能的贡献，证明在体外实验操纵复杂微生物群的可行性。第二个输出将是系统地绘制成员之间的关系并解释它们在群落属性中的作用，从而扩展我们对微生物群落的系统级理解。第三个输出将是使用我们的模型和相互作用网络来预测生物和非生物抗菌处理对肉类微生物腐败的影响。未来几年，研究微生物群落生态学机制的努力将受到欢迎，以建立新的微生物控制策略，以减少肉类和其他食品的浪费。因此，该计划将最终使加拿大食品工业及其消费者受益，向可持续发展迈出一步，并帮助加拿大保持在食品科学研发的前沿。