ADVANCING ECOTOXICOLOGY, FOOD SCIENCE, WILDLIFE ECOLOGY, SOIL BIOGEOCHEMISTRY, AND MICROBIAL ECOLOGY USING COMPOUND-SPECIFIC CARBON AND NITROGEN ISOTOPES ANALYSIS

利用化合物特异性碳和氮同位素分析推进生态毒理学、食品科学、野生动物生态学、土壤生物化学和微生物生态学

• 批准号: RTI-2020-00703
• 负责人: Mckinney, Melissa
• 金额: $ 10.93万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Research Tools and Instruments
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=693707
• 关键词: ADVANCING; ECOTOXICOLOGY; FOOD; SCIENCE; WILDLIFE

Our research team aims to understand the movement and fate of energy, nutrients, and contaminants through natural ecosystems and human-managed food systems, from microbes to top predators, using chemical tracers. A major recent advance in this approach is compound-specific isotopes analysis (CSIA), e.g., amino acid isotopes analysis and fatty acid isotopes analysis. We are seeking RTI funds for the equipment needed for CSIA: a gas-chromatograph interfaced to an isotope ratio mass spectrometer (GC-IRMS). This system will provide crucial new high-resolution tracer data accelerating the research programs of Melissa McKinney, Nil Basu, Stephane Bayen, Jessica Head, Kyle Elliott, Cynthia Kallenbach, Denis Roy, and Lyle Whyte. ******The CSIA approach shows potential to be a valuable tool in tracer applications, which have traditionally relied on bulk isotopes analysis. For example, as nitrogen isotope ratios of certain amino acids are conserved through the food web, while others show trophic enrichment, amino acid isotopes analysis has been shown to provide a better indication of trophic position than bulk nitrogen isotopes. With the GC-IRMS, our research groups will lead the development and application of cutting-edge CSIA techniques to identify and quantify pathways and changes in agricultural and natural ecosystems across multiple taxonomic, spatial, and temporal scales.******The GC-IRMS represents a key component of multiple research groups within the Faculty of Agricultural and Environmental Sciences at McGill University. McKinney, Basu, and Head will use the GC-IRMS to generate new high-resolution data fostering critical advances in understanding intra-specific, inter-specific, spatial, and temporal variation in contaminant exposures. Bayen will use the GC-IRMS to assess food origin fraud. Elliott will use the system to examine food web structures and their associations with contaminants. Kallenbach will use it to understand how global change factors, e.g., warming, flooding, agricultural management, influence soil nitrogen dynamics. Roy proposes to use it to assess diet differences in Arctic marine fish species adapted to different marine habitats across Canadian Arctic basins. Whyte will use the GC-IMRS to identify and track shifts in amino acid and fatty acid isotopes in polar microbial strains growing at different temperatures and salinities to determine microbial adaptations of microorganisms living in cryoenvironments.******Our 20 or more students will have a clear competitive advantage with hands-on skills in this state-of-the-science system, including its use, maintenance, quality assurance/quality control, and in isotope data processing. More broadly, various scientific fields in Canada employ GC and MS as analytical tools; thus, such hands-on training provides marketable skills for students to succeed in future academic, government, industry, and non-profit careers across the agricultural and environmental sciences.*****

我们的研究团队旨在利用化学示踪剂，了解从微生物到顶级捕食者的自然生态系统和人类管理的食物系统中能量、营养物质和污染物的运动和命运。该方法的最新主要进展是化合物特异性同位素分析（CSIA），例如氨基酸同位素分析和脂肪酸同位素分析。我们正在为 CSIA 所需的设备寻求 RTI 资金：与同位素比质谱仪 (GC-IRMS) 连接的气相色谱仪。该系统将提供重要的新型高分辨率示踪数据，加速 Melissa McKinney、Nil Basu、Stephane Bayen、Jessica Head、Kyle Elliott、Cynthia Kallenbach、Denis Roy 和 Lyle Whyte 的研究项目。 ******CSIA 方法显示出成为示踪剂应用中有价值的工具的潜力，示踪剂应用传统上依赖于批量同位素分析。例如，由于某些氨基酸的氮同位素比率在食物网中是保守的，而其他氨基酸则显示出营养富集，因此氨基酸同位素分析已被证明可以比大量氮同位素更好地指示营养位置。通过 GC-IRMS，我们的研究小组将领导尖端 CSIA 技术的开发和应用，以识别和量化跨多个分类、空间和时间尺度的农业和自然生态系统的路径和变化。******GC-IRMS 代表了麦吉尔大学农业与环境科学学院多个研究小组的关键组成部分。 McKinney、Basu 和 Head 将使用 GC-IRMS 生成新的高分辨率数据，促进在理解污染物暴露的种内、种间、空间和时间变化方面取得关键进展。 Bayen 将使用 GC-IRMS 来评估食品原产地欺诈。埃利奥特将使用该系统来检查食物网结构及其与污染物的关联。卡伦巴赫将利用它来了解全球变化因素（例如变暖、洪水、农业管理）如何影响土壤氮动态。罗伊建议用它来评估适应加拿大北极盆地不同海洋栖息地的北极海洋鱼类的饮食差异。 Whyte 将使用 GC-IMRS 来识别和跟踪在不同温度和盐度下生长的极地微生物菌株中氨基酸和脂肪酸同位素的变化，以确定生活在低温环境中的微生物的微生物适应性。******我们的 20 名或更多学生将在这个最先进的系统中拥有实践技能，包括其使用、维护、质量保证/质量控制和 同位素数据处理。更广泛地说，加拿大的各个科学领域都使用 GC 和 MS 作为分析工具；因此，这种实践培训为学生提供了适销对路的技能，使他们能够在未来的农业和环境科学领域的学术、政府、工业和非营利职业中取得成功。*****