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NSF Postdoctoral Fellowship in Biology FY 2022: The role of genomic preadaptation and physiological state in modulating bacterial invasion success

NSF Postdoctoral Fellowship in Biology FY 2022: The role of genomic preadaptation and physiological state in modulating bacterial invasion success
2022 财年 NSF 生物学博士后奖学金:基因组预适应和生理状态在调节细菌入侵成功中的作用
批准号:
2209151
负责人:
Elijah Mehlferber
金额:
$13.8万
依托单位:
依托单位国家:
美国
项目类别:
Fellowship Award
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-09-01 至 2024-08-31

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中文摘要
翻译
这一行动为NSF 2022财年生物学博士后研究奖学金提供了资金,综合研究调查了基因组、环境和表型之间相互作用的生命规则。该奖学金支持研究员的研究和培训,这些研究员将以创新的方式为生活规则领域做出贡献。在这项工作中,这位研究员将研究让细菌物种成功入侵新环境的基因和环境之间的复杂相互作用。细菌通常不会入侵宿主并导致疾病,但有时它们会成功,当它们入侵时可能会导致严重感染。这些细菌所具有的特征以及帮助它们实现这种入侵的条件还没有被很好地了解,特别是因为研究通常只关注成功的入侵,而不是比较失败的入侵。这位研究员将对从不同环境中分离出来的不同细菌的入侵成功进行量化,确定生长条件的影响,并开发一种机器学习方法,将入侵结果与遗传学联系起来。该项目旨在预测未测试菌株的入侵成功。该研究员还将通过招募和培训本科生来扩大对科学的参与,特别是为了提供公平的研究机会。这个项目试图通过研究不同系统发育的机会致病菌铜绿假单胞菌菌株在入侵成功方面的差异,更好地了解向致病性转变的遗传和环境相互作用。这位研究员将首先通过量化细菌在包含竞争物种的新环境中建立的能力来确定入侵结果的这种变化,并将评估系统发育相关和基因组因素在预测成功中的作用。接下来,他们将量化不同的生理状态,在引入他们的新环境之前,由细菌的生长条件诱导的不同生理状态对入侵结果的影响。最后,研究员将整合这些数据,以比较一般和特定的预测模型,以量化在未测试的菌株中未来入侵成功的可能性。在整个项目中,这位研究员将获得细菌遗传学方面的技能,量化细菌特征,并将学习开发机器学习模型,以根据基因组信息预测表型结果。除了指导本科生,该研究员还将参与旨在促进对科学的理解和欣赏的科学推广活动,特别关注历史上服务不足的机构。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This action funds an NSF Postdoctoral Research Fellowship in Biology for FY 2022, Integrative Research Investigating the Rules of Life Governing Interactions Between Genomes, Environment and Phenotypes. The fellowship supports research and training of the fellow that will contribute to the area of Rules of Life in innovative ways. In this work, the Fellow will investigate the complex interactions between genetics and the environment that allow a bacterial species to successfully invade a new environment. Bacteria usually fail to invade a host and cause disease, but sometimes they succeed and can cause severe infections when they do. The traits these bacteria have, and conditions which help them achieve this invasion are not well-understood, especially because studies usually only focus on successful invasion without comparing to failed invasions. The Fellow will quantify invasion success across a diverse set of bacteria isolated from different environments, determine the influence of growth conditions, and develop a machine-learning approaches to link invasion outcomes to genetics. The project aims to predict invasion success in un-tested strains. The Fellow will also broaden participation in science through the recruitment and training of undergraduate students, specifically targeted towards providing equitable access to research opportunities.This project seeks to better understand the genetic and environmental interactions underlying transitions to pathogenicity by studying the variation in invasion success across strains of the phylogenetically diverse opportunistic pathogen Pseudomonas aeruginosa. The Fellow will first determine this variation in invasion outcomes by quantifying the bacteria’s ability to establish in a novel environment containing a competitor species and will assess the role of phylogenetic relatedness and genomic factors in predicting that success. Next, they will quantify the impact of different physiological states, induced by the bacteria’s growth conditions before introduction to their novel environment, on invasion outcomes. Finally, the Fellow will integrate these data to compare general and specific predictive models to quantify the potential for future invasion success in un-tested strains. Throughout the project, the Fellow will gain skills in bacterial genetics, quantifying bacterial traits, and will learn to develop machine learning models to predict phenotypic outcomes from genomic information. In addition to mentoring undergraduate students, the Fellow will engage in scientific outreach aimed at fostering understanding and appreciation for science, with a specific focus on historically underserved institutions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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