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天然微生物群落与基因工程微生物群落:了解公众对室内应用的态度及未来参与途径。

Natural vs. genetically engineered microbiomes: understanding public attitudes for indoor applications and pathways for future engagement.

作者信息

Cummings Christopher L, Landreville Kristen D, Kuzma Jennifer

机构信息

Genetic Engineering and Society Center, Raleigh, NC, United States.

Engineer Research and Development Center (ERDC), Vicksburg, MS, United States.

出版信息

Front Genet. 2025 Mar 26;16:1560601. doi: 10.3389/fgene.2025.1560601. eCollection 2025.

Abstract

This study examines public preferences for natural microbiomes and support for genetically engineered (GE) microbiomes in the built environment, focusing on the demographic, sociographic, and attitudinal factors that influence these preferences. Using data from a nationally representative survey of 1,000 U.S. adults, we employed hierarchical regression analyses to assess the relative contribution of these variables. While demographic and sociographic factors explained limited variance, topic-specific attitudes, including positive perceptions of microbiome engineering's potential to improve quality of life, were the most significant predictors of support. Conversely, age, distrust in science, and perceived knowledge negatively influenced support for GE microbiomes, reflecting skepticism among some audiences. The findings highlight the potential of the Responsible Research and Innovation (RRI) framework to align the development of microbiome engineering with societal values and to address diverse public perspectives. This research provides actionable insights for policymakers, researchers, and communicators seeking to navigate the complexities of public engagement with emerging biotechnologies.

摘要

本研究调查了公众对建筑环境中自然微生物群落的偏好以及对基因工程(GE)微生物群落的支持情况,重点关注影响这些偏好的人口统计学、社会统计学和态度因素。我们利用对1000名美国成年人进行的具有全国代表性的调查数据,采用分层回归分析来评估这些变量的相对贡献。虽然人口统计学和社会统计学因素解释的方差有限,但特定主题的态度,包括对微生物群落工程改善生活质量潜力的积极看法,是支持率的最重要预测因素。相反,年龄、对科学的不信任和感知知识对支持基因工程微生物群落产生了负面影响,反映出一些受众的怀疑态度。研究结果凸显了负责任研究与创新(RRI)框架在使微生物群落工程发展与社会价值观保持一致以及应对不同公众观点方面的潜力。这项研究为寻求应对公众参与新兴生物技术复杂性的政策制定者、研究人员和传播者提供了可操作的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/050a/11979166/1a0044b69214/fgene-16-1560601-g001.jpg

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