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沉积物微生物燃料电池中微生物群落的功能预测

Functional Prediction of Microbial Communities in Sediment Microbial Fuel Cells.

作者信息

Kuo Jimmy, Liu Daniel, Lin Chorng-Horng

机构信息

Department of Planning and Research, National Museum of Marine Biology and Aquarium, Pingtung 94450, Taiwan.

Graduate Institute of Marine Biology, National Dong Hwa University, Pingtung 94450, Taiwan.

出版信息

Bioengineering (Basel). 2023 Feb 3;10(2):199. doi: 10.3390/bioengineering10020199.

Abstract

Sediment microbial fuel cells (MFCs) were developed in which the complex substrates present in the sediment could be oxidized by microbes for electron production. In this study, the functional prediction of microbial communities of anode-associated soils in sediment MFCs was investigated based on 16S rRNA genes. Four computational approaches, including BugBase, Functional Annotation of Prokaryotic Taxa (FAPROTAX), the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2), and Tax4Fun2, were applied. A total of 67, 9, 37, and 38 functional features were statistically significant. Among these functional groups, the function related to the generation of precursor metabolites and energy was the only one included in all four computational methods, and the sum total of the proportion was 93.54%. The metabolism of cofactor, carrier, and vitamin biosynthesis was included in the three methods, and the sum total of the proportion was 29.94%. The results suggested that the microbial communities usually contribute to energy metabolism, or the metabolism of cofactor, carrier, and vitamin biosynthesis might reveal the functional status in the anode of sediment MFCs.

摘要

沉积物微生物燃料电池(MFCs)被开发出来,其中沉积物中存在的复杂底物可被微生物氧化以产生电子。在本研究中,基于16S rRNA基因对沉积物MFCs中阳极相关土壤的微生物群落进行了功能预测。应用了四种计算方法,包括BugBase、原核生物分类群功能注释(FAPROTAX)、通过重建未观察状态进行群落系统发育调查(PICRUSt2)和Tax4Fun2。共有67、9、37和38个功能特征具有统计学意义。在这些功能组中,与前体代谢物和能量生成相关的功能是所有四种计算方法中唯一都包含的,比例总和为93.54%。辅因子、载体和维生素生物合成的代谢被三种方法所包含,比例总和为29.94%。结果表明,微生物群落通常有助于能量代谢,或者辅因子、载体和维生素生物合成的代谢可能揭示沉积物MFCs阳极中的功能状态。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4044/9951962/54eb1a87b9c7/bioengineering-10-00199-g001.jpg

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