NRT: Quantitative & Evolutionary STEM Training (QUEST): An Integrative Training Program for Versatile STEM Professionals to Solve Environmental and Global Health Problems

NRT：定量

• 批准号: 1735316
• 负责人: Melissa Pespeni
• 金额: $ 300万
• 依托单位: University of Vermont & State Agricultural College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1735316&HistoricalAwards=false
• 关键词: NRT; Quantitative; & Evolutionary; STEM

Major environmental and global health problems, such as emerging infectious diseases, antibiotic and pesticide resistance, reduced crop yields, and the loss of biodiversity, can be addressed through the integration of evolutionary principles with the massive amounts of available climate, genomic, and public health data. For example, pathogens, pests, and invasive species often quickly evolve resistance to control measures, while important crops and wild populations have limited or variable capacity to adapt to rapidly changing global conditions. Important insights into the mechanisms of pathogen/pest resistance and resilience will require collaborative efforts that apply evolutionary principles to big data analyses and visualization. However, few opportunities exist for trainees to develop the unique combination of relevant evolutionary, quantitative, and teamwork skills. This National Science Foundation Research Traineeship (NRT) award to the University of Vermont will meet this demand with an interdisciplinary PhD training program called QUantitative & Evolutionary STEM Training (QUEST). The project anticipates training 36 PhD students as core trainees, 18 of whom will receive NRT-funded stipends, from a range of disciplines including biology, mathematics and statistics, engineering, agricultural sciences, environmental studies, and health sciences. The QUEST program is unique in its emphasis on evolutionary training, modeling for prediction, and culturally sensitive teamwork. Major research efforts will focus on three areas: (i) emerging infectious diseases and modeling for prediction, (ii) rapid evolution in response to antibiotics, pesticides, and global change conditions, and (iii) pathogen interactions that affect food security and ecosystem health. A supportive and collaborative training environment will be cultivated by cohort building via a shared, physical space, a set of core courses in which trainees work in teams to solve real-world problems, and a seminar that includes invited speakers and professional development activities. In addition, QUEST trainees will complete an applied internship, selected from government, non-profit, industry, and international partners. Through cultural sensitivity and inclusion training for faculty, staff and trainees, and innovative recruitment efforts, the traineeship aims to increase underrepresented groups in STEM. Project outcomes will be (1) trainees that are experts in the application of deep evolutionary and quantitative knowledge to develop solutions for resilience in environmental and global health systems, (2) trainees that can work creatively and collaboratively to translate their skills to practical solutions in non-academic sectors, and (3) a scalable, transferable graduate training program that increases diversity in STEM fields. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The Traineeship Track is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas, through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.

主要的环境和全球健康问题，如新出现的传染病，抗生素和杀虫剂耐药性，作物产量下降，生物多样性的丧失，可以通过将进化原理与大量可用的气候，基因组和公共卫生数据相结合来解决。 例如，病原体、害虫和入侵物种往往很快对控制措施产生抗药性，而重要作物和野生种群适应迅速变化的全球条件的能力有限或可变。 对病原体/害虫抗性和复原力机制的重要见解将需要将进化原理应用于大数据分析和可视化的合作努力。然而，学员很少有机会发展相关的进化，定量和团队合作技能的独特组合。这个国家科学基金会研究培训（NRT）奖给佛蒙特大学将满足这一需求与一个跨学科的博士培训计划，称为定量进化干培训（QUEST）。该项目预计将培训36名博士生作为核心学员，其中18人将获得NRT资助的津贴，来自生物学，数学和统计学，工程学，农业科学，环境研究和健康科学等一系列学科。 QUEST计划的独特之处在于它强调进化训练，预测建模和文化敏感的团队合作。主要研究工作将集中在三个领域：（i）新出现的传染病和预测建模，（ii）应对抗生素，农药和全球变化条件的快速进化，以及（iii）影响粮食安全和生态系统健康的病原体相互作用。一个支持性和协作性的培训环境将通过一个共享的物理空间，一套核心课程，学员在团队中解决现实世界的问题，以及一个研讨会，其中包括特邀演讲者和专业发展活动的队列建设培养。此外，QUEST学员将完成从政府，非营利组织，行业和国际合作伙伴中选择的应用实习。通过对教职员工和学员的文化敏感性和包容性培训，以及创新的招聘工作，该培训旨在增加STEM中代表性不足的群体。项目成果将是（1）学员是应用深层进化和定量知识开发环境和全球卫生系统复原力解决方案的专家，（2）学员可以创造性地合作，将他们的技能转化为非学术部门的实际解决方案，以及（3）可扩展，可转移的研究生培训计划，增加STEM领域的多样性。 NSF研究培训（NRT）计划旨在鼓励为STEM研究生教育培训开发和实施大胆的，新的潜在变革模式。培训课程致力于在高优先级的跨学科研究领域对STEM研究生进行有效培训，通过全面的培训模式，这些模式具有创新性，以证据为基础，并与不断变化的劳动力和研究需求保持一致。

项目成果

Genotypic variation and plasticity in climate-adaptive traits after range expansion and fragmentation of red spruce ( Picea rubens Sarg.)

红云杉（Picea rubens Sarg.）范围扩大和破碎后气候适应性状的基因型变异和可塑性

• DOI: 10.1098/rstb.2021.0008
• 发表时间: 2022
• 期刊: Philosophical Transactions of the Royal Society B: Biological Sciences
• 作者: Prakash, Anoob;DeYoung, Sonia;Lachmuth, Susanne;Adams, Jacquelyne L.;Johnsen, Kurt;Butnor, John R.;Nelson, David M.;Fitzpatrick, Matthew C.;Keller, Stephen R.
• 通讯作者: Keller, Stephen R.

Immunization strategies in networks with missing data

• DOI: 10.1371/journal.pcbi.1007897
• 发表时间: 2020-05
• 期刊: PLoS Computational Biology
• 影响因子: 4.3
• 作者: Samuel F. Rosenblatt;Jeffrey A. Smith;Robin Gauthier;Laurent Hébert-Dufresne

Integrating GWAS and Transcriptomics to Identify the Molecular Underpinnings of Thermal Stress Responses in Drosophila melanogaster

整合 GWAS 和转录组学来识别果蝇热应激反应的分子基础

• DOI: 10.3389/fgene.2020.00658
• 发表时间: 2020
• 期刊: Frontiers in Genetics
• 影响因子: 3.7
• 作者: Lecheta, Melise C.;Awde, David N.;O’Leary, Thomas S.;Unfried, Laura N.;Jacobs, Nicholas A.;Whitlock, Miles H.;McCabe, Eleanor;Powers, Beck;Bora, Katie;Waters, James S.
• 通讯作者: Waters, James S.

Defining and improving the rotational and intercropping value of a crop using a plant–soil feedbacks approach

• DOI: 10.1002/csc2.20200
• 发表时间: 2020-09
• 期刊: Crop Science
• 影响因子: 2.3
• 作者: Edward Marques;A. Kur;E. Bueno;E. Wettberg

Small mammal community composition varies among Ozark glades

奥扎克空地的小型哺乳动物群落组成各不相同

• DOI: 10.1093/jmammal/gyz102
• 发表时间: 2019
• 期刊: Journal of Mammalogy
• 影响因子: 1.7
• 作者: Beasley, Emily M;Maher, Sean P
• 通讯作者: Maher, Sean P