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通过电化学刺激和机器学习解析 Candidatus geobacter eutrophica 的共代谢电子转移机制。

Disentangling the syntrophic electron transfer mechanisms of Candidatus geobacter eutrophica through electrochemical stimulation and machine learning.

机构信息

Department of Civil and Environmental Engineering, University of Illinois, Urbana-Champaign, Urbana, IL, 61801, USA.

Department of Civil and Environmental Engineering, Temple University, Philadelphia, PA, 19122, USA.

出版信息

Sci Rep. 2021 Jul 23;11(1):15140. doi: 10.1038/s41598-021-94628-0.


DOI:10.1038/s41598-021-94628-0
PMID:34302023
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8302695/
Abstract

Interspecies hydrogen transfer (IHT) and direct interspecies electron transfer (DIET) are two syntrophy models for methanogenesis. Their relative importance in methanogenic environments is still unclear. Our recent discovery of a novel species Candidatus Geobacter eutrophica with the genetic potential of IHT and DIET may serve as a model species to address this knowledge gap. To experimentally demonstrate its DIET ability, we performed electrochemical enrichment of Ca. G. eutrophica-dominating communities under 0 and 0.4 V vs. Ag/AgCl based on the presumption that DIET and extracellular electron transfer (EET) share similar metabolic pathways. After three batches of enrichment, Geobacter OTU650, which was phylogenetically close to Ca. G. eutrophica, was outcompeted in the control but remained abundant and active under electrochemical stimulation, indicating Ca. G. eutrophica's EET ability. The high-quality draft genome further showed high phylogenomic similarity with Ca. G. eutrophica, and the genes encoding outer membrane cytochromes and enzymes for hydrogen metabolism were actively expressed. A Bayesian network was trained with the genes encoding enzymes for alcohol metabolism, hydrogen metabolism, EET, and methanogenesis from dominant fermentative bacteria, Geobacter, and Methanobacterium. Methane production could not be accurately predicted when the genes for IHT were in silico knocked out, inferring its more important role in methanogenesis. The genomics-enabled machine learning modeling approach can provide predictive insights into the importance of IHT and DIET.

摘要

种间氢转移(IHT)和直接种间电子转移(DIET)是产甲烷菌的两种共生模型。它们在产甲烷环境中的相对重要性仍不清楚。我们最近发现了一种新型的 Candidatus Geobacter eutrophica 物种,具有 IHT 和 DIET 的遗传潜力,它可能成为解决这一知识空白的模式物种。为了实验证明其 DIET 能力,我们基于 DIET 和细胞外电子转移(EET)共享相似代谢途径的假设,在 0 和 0.4 V 相对于 Ag/AgCl 对 Ca. G. eutrophica 占主导地位的群落进行了电化学富集。经过三批富集,与 Ca. G. eutrophica 系统发育上接近的 Geobacter OTU650 在对照中被淘汰,但在电化学刺激下仍然丰富且活跃,表明 Ca. G. eutrophica 具有 EET 能力。高质量的草图基因组进一步显示与 Ca. G. eutrophica 具有高度的系统发育相似性,编码外膜细胞色素和氢代谢酶的基因被积极表达。使用来自优势发酵细菌 Geobacter 和 Methanobacterium 的酒精代谢、氢代谢、EET 和产甲烷基因,训练了一个贝叶斯网络。当 IHT 的基因在计算机上被敲除时,甲烷的产生不能被准确预测,这表明它在产甲烷过程中起着更重要的作用。基于基因组的机器学习建模方法可以为 IHT 和 DIET 的重要性提供预测性见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab74/8302695/03b681316e46/41598_2021_94628_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab74/8302695/c54a4dbea29f/41598_2021_94628_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab74/8302695/caa7347c6fd0/41598_2021_94628_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab74/8302695/5444a65c32fb/41598_2021_94628_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab74/8302695/02bb394d93f9/41598_2021_94628_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab74/8302695/b619d01f9afe/41598_2021_94628_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab74/8302695/03b681316e46/41598_2021_94628_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab74/8302695/c54a4dbea29f/41598_2021_94628_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab74/8302695/caa7347c6fd0/41598_2021_94628_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab74/8302695/5444a65c32fb/41598_2021_94628_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab74/8302695/02bb394d93f9/41598_2021_94628_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab74/8302695/b619d01f9afe/41598_2021_94628_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab74/8302695/03b681316e46/41598_2021_94628_Fig6_HTML.jpg

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