School of Ocean and Earth Science, University of Southampton, National Oceanography Centre, Southampton, UK; Centre for Environment, Fisheries and Aquaculture Science (CEFAS), Weymouth, UK.
School of Ocean and Earth Science, University of Southampton, National Oceanography Centre, Southampton, UK.
Curr Opin Biotechnol. 2023 Apr;80:102898. doi: 10.1016/j.copbio.2023.102898. Epub 2023 Feb 3.
It is critical to gain insight into how climate change impacts evolutionary responses within climate-sensitive pathogen populations, such as increased resilience, opportunistic responses and the emergence of dominant variants from highly variable genomic backgrounds and subsequent global dispersal. This review proposes a framework to support such analysis, by combining genomic evolutionary analysis with climate time-series data in a novel spatiotemporal dataframe for use within machine learning applications, to understand past and future evolutionary pathogen responses to climate change. Recommendations are presented to increase the feasibility of interdisciplinary applications, including the importance of robust spatiotemporal metadata accompanying genome submission to databases. Such workflows will inform accessible public health tools and early-warning systems, to aid decision-making and mitigate future human health threats.
深入了解气候变化如何影响气候敏感病原体种群的进化反应至关重要，例如增加弹性、机会主义反应以及高度可变基因组背景下优势变体的出现和随后的全球传播。本综述提出了一个框架，通过将基因组进化分析与气候时间序列数据相结合，在一个新的时空数据框中用于机器学习应用，以了解过去和未来气候变化对病原体进化的反应。提出了一些建议来提高跨学科应用的可行性，包括在向数据库提交基因组时伴随稳健的时空元数据的重要性。这种工作流程将为可访问的公共卫生工具和预警系统提供信息，以帮助决策并减轻未来对人类健康的威胁。
