Bacterial glycerol tetraethers as a potential tool to trace marine methane cycling

IF 3.8 1区 地球科学 Q1 LIMNOLOGY Limnology and Oceanography Pub Date : 2023-11-20 DOI:10.1002/lno.12462
Zhe-Xuan Zhang, Jiwei Li, Hongxuan Lu, Huan Yang, Yige Zhang, Yongjie Tang, Meiyan Fu, Xiaotong Peng
{"title":"Bacterial glycerol tetraethers as a potential tool to trace marine methane cycling","authors":"Zhe-Xuan Zhang,&nbsp;Jiwei Li,&nbsp;Hongxuan Lu,&nbsp;Huan Yang,&nbsp;Yige Zhang,&nbsp;Yongjie Tang,&nbsp;Meiyan Fu,&nbsp;Xiaotong Peng","doi":"10.1002/lno.12462","DOIUrl":null,"url":null,"abstract":"<p>Branched glycerol dialkyl glycerol tetraethers (brGDGTs) are bacterial lipids that can be preserved in sedimentary archives for tens of millions of years and are ubiquitous in diverse environments, including cold seep systems. Their potential implications for detecting methane activity in deep time are, however, hampered by the multiple sources of brGDGTs in cold seeps and the lack of evidence of their stable carbon isotopes. Here, we show that brGDGTs in cold seeps are characterized by depleted stable carbon isotopic compositions of the alkyl moieties (δ<sup>13</sup>C = −32.9‰ to −82.7‰), indicating a methane metabolizing community origin, which is supported by the association between 16S rRNA genes and brGDGTs. We further identify unique seep-derived brGDGT signals from the global published dataset by a tree-based machine-learning algorithm. This trained model, named light gradient-boosting machine classification for paleoSEEP (GBM_SEEP), is further applied on a paleorecord across the Paleocene–Eocene Thermal Maximum (PETM), which suggests potential methane emission events during the PETM recovery phase. Collectively, our study links brGDGT production in cold seeps with methane metabolizing communities and provides a potential strategy to capture significant methane emission events using the machine-learning model, which warrants further investigation.</p>","PeriodicalId":18143,"journal":{"name":"Limnology and Oceanography","volume":"69 1","pages":"104-120"},"PeriodicalIF":3.8000,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Limnology and Oceanography","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/lno.12462","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"LIMNOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Branched glycerol dialkyl glycerol tetraethers (brGDGTs) are bacterial lipids that can be preserved in sedimentary archives for tens of millions of years and are ubiquitous in diverse environments, including cold seep systems. Their potential implications for detecting methane activity in deep time are, however, hampered by the multiple sources of brGDGTs in cold seeps and the lack of evidence of their stable carbon isotopes. Here, we show that brGDGTs in cold seeps are characterized by depleted stable carbon isotopic compositions of the alkyl moieties (δ13C = −32.9‰ to −82.7‰), indicating a methane metabolizing community origin, which is supported by the association between 16S rRNA genes and brGDGTs. We further identify unique seep-derived brGDGT signals from the global published dataset by a tree-based machine-learning algorithm. This trained model, named light gradient-boosting machine classification for paleoSEEP (GBM_SEEP), is further applied on a paleorecord across the Paleocene–Eocene Thermal Maximum (PETM), which suggests potential methane emission events during the PETM recovery phase. Collectively, our study links brGDGT production in cold seeps with methane metabolizing communities and provides a potential strategy to capture significant methane emission events using the machine-learning model, which warrants further investigation.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
细菌甘油四醚作为追踪海洋甲烷循环的潜在工具
支化甘油二烷基甘油四醚(brGDGTs)是一种细菌脂质,可以在沉积档案中保存数千万年,在各种环境中普遍存在,包括冷渗系统。然而,由于冷渗漏中brGDGTs的多种来源以及缺乏其稳定碳同位素的证据,它们对探测深层甲烷活动的潜在意义受到了阻碍。研究结果表明,冷渗中brGDGTs的烃基稳定碳同位素组成(δ13C = - 32.9‰~ - 82.7‰)明显减少,表明brGDGTs具有甲烷代谢群落起源,16S rRNA基因与brGDGTs存在关联。我们进一步通过基于树的机器学习算法从全球发布的数据集中识别唯一的渗出衍生的brGDGT信号。该模型命名为GBM_SEEP,并将其应用于古新世-始新世极热期(PETM)的古记录,揭示了在PETM恢复阶段可能发生的甲烷排放事件。总的来说,我们的研究将冷渗漏中的brGDGT产生与甲烷代谢群落联系起来,并提供了使用机器学习模型捕获重要甲烷排放事件的潜在策略,这值得进一步研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Limnology and Oceanography
Limnology and Oceanography 地学-海洋学
CiteScore
8.80
自引率
6.70%
发文量
254
审稿时长
3 months
期刊介绍: Limnology and Oceanography (L&O; print ISSN 0024-3590, online ISSN 1939-5590) publishes original articles, including scholarly reviews, about all aspects of limnology and oceanography. The journal''s unifying theme is the understanding of aquatic systems. Submissions are judged on the originality of their data, interpretations, and ideas, and on the degree to which they can be generalized beyond the particular aquatic system examined. Laboratory and modeling studies must demonstrate relevance to field environments; typically this means that they are bolstered by substantial "real-world" data. Few purely theoretical or purely empirical papers are accepted for review.
期刊最新文献
Advancing an integrated understanding of land–ocean connections in shaping the marine ecosystems of coastal temperate rainforest ecoregions Life in turbulent waters: unsteady biota–flow interactions across scales Genes involved in carbon, nitrogen, and sulfur cycling in an important estuarine ecosystem show coherent shifts in response to changes in environmental conditions Diel dissolved organic matter patterns reflect spatiotemporally varying sources and transformations along an intermittent stream Differential impacts of temperature increase on prokaryotes across temperature regimes in subtropical coastal waters: insights from field experiments
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1