Suppr超能文献

揭示泥炭地中固碳微生物的多样性和丰度模式。

Uncovering diversity and abundance patterns of CO-fixing microorganisms in peatlands.

作者信息

Le Geay Marie, Mayers Kyle, Sytiuk Anna, Dorrepaal Ellen, Küttim Martin, Lamentowicz Mariusz, Tuittila Eeva-Stiina, Lauga Béatrice, Jassey Vincent E J

机构信息

Université de Toulouse, Toulouse INP, CNRS, IRD, CRBE, Toulouse, France.

Molecular Ecology and Paleogenomics - MEP, NORCE Research, Bergen, Norway.

出版信息

NPJ Biodivers. 2025 Aug 4;4(1):30. doi: 10.1038/s44185-025-00099-1.

Abstract

Microorganisms play a crucial role in the carbon (C) dynamics of peatlands - a major terrestrial C reservoir. Because of their role in C emissions, heterotrophic microorganisms have attracted much attention over the past decades. CO-fixing microorganisms (CFMs) remained largely overlooked, while they could attenuate C emissions. Here, we use metabarcoding and digital droplet PCR to survey microorganisms that potentially fix CO in different peatlands. We demonstrate that CFMs are abundant and diverse in peatlands, with on average 1021 CFMs contributing up to 40% of the total bacterial abundance. Using a joint-species distribution model, we identified a core and a specific CFM microbiome, the latter being influenced by temperature and nutrients. Our findings highlight that ASV richness and community structure were direct drivers of CFM abundance, while environmental parameters were indirect drivers. These results provide the basis for a better understanding of the role of CFMs in peatland C cycle inputs.

摘要

微生物在泥炭地(一种主要的陆地碳库)的碳(C)动态中起着至关重要的作用。由于其在碳排放中的作用,异养微生物在过去几十年中备受关注。而能够固定碳的微生物(CFMs)虽然可以减少碳排放,但在很大程度上仍被忽视。在此,我们使用宏条形码和数字液滴PCR技术来调查不同泥炭地中潜在固定碳的微生物。我们证明,CFMs在泥炭地中种类丰富且多样,平均每1021个CFMs贡献的细菌总数高达40%。通过联合物种分布模型,我们确定了一个核心CFM微生物群落和一个特定的CFM微生物群落,后者受温度和养分的影响。我们的研究结果表明,扩增子序列变体(ASV)丰富度和群落结构是CFM丰度的直接驱动因素,而环境参数是间接驱动因素。这些结果为更好地理解CFMs在泥炭地碳循环输入中的作用提供了依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e605/12322008/fe1d50b49fbb/44185_2025_99_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验