Center for Microbial Ecology and Technology (CMET), Ghent University, Coupure Links 653, B-9000, Gent, Belgium; Division of Soil and Water Management, Department of Earth and Environmental sciences, KU Leuven, Kasteelpark Arenberg 20, PO box 2411, B-3001, Leuven, Belgium; Bio- and Chemical Systems Technology, Reactor Engineering and Safety (CREaS), Department of Chemical Engineering, KU Leuven, Celestijnenlaan 200F, PO box 2424, B-3001, Leuven, Belgium.
Bioprocess Engineering, Otto von Guericke University, Universitätsplatz 2, 39106, Magdeburg, Germany.
Water Res. 2021 Sep 1;202:117422. doi: 10.1016/j.watres.2021.117422. Epub 2021 Jul 10.
The anaerobic digestion microbiome has been puzzling us since the dawn of molecular methods for mixed microbial community analysis. Monitoring of the anaerobic digestion microbiome can either take place via a non-targeted holistic evaluation of the microbial community through fingerprinting or by targeted monitoring of selected taxa. Here, we compared four different microbial community fingerprinting methods, i.e., amplicon sequencing, metaproteomics, metabolomics and cytomics, in their ability to characterise the full-scale anaerobic digestion microbiome. Cytometric fingerprinting through cytomics reflects a, for anaerobic digestion, novel, single cell-based approach of direct microbial community fingerprinting by flow cytometry. Three different digester types, i.e., sludge digesters, digesters treating agro-industrial waste and dry anaerobic digesters, each reflected different operational parameters. The α-diversity analysis yielded inconsistent results, especially for richness, across the different methods. In contrast, β-diversity analysis resulted in comparable profiles, even when translated into phyla or functions, with clear separation of the three digester types. In-depth analysis of each method's features i.e., operational taxonomic units, metaproteins, metabolites, and cytometric traits, yielded certain similar features, yet, also some clear differences between the different methods, which was related to the complexity of the anaerobic digestion process. In conclusion, cytometric fingerprinting through flow cytometry is a reliable, fast method for holistic monitoring of the anaerobic digestion microbiome, and the complementary identification of key features through other methods could give rise to a direct interpretation of anaerobic digestion process performance.
自采用分子方法混合微生物群落分析以来，厌氧消化微生物组一直困扰着我们。厌氧消化微生物组的监测可以通过指纹图谱对微生物群落进行非靶向的整体评估，也可以通过对选定分类群进行靶向监测来进行。在这里，我们比较了四种不同的微生物群落指纹图谱方法，即扩增子测序、宏蛋白质组学、代谢组学和细胞组学，以评估它们对全规模厌氧消化微生物组的特征描述能力。通过细胞组学进行的细胞指纹图谱反映了一种针对厌氧消化的新型单细胞方法，即通过流式细胞术直接对微生物群落进行指纹图谱分析。三种不同的消化器类型，即污泥消化器、处理农业工业废物的消化器和干式厌氧消化器，每个消化器都反映了不同的操作参数。α多样性分析得出的结果不一致，特别是在不同方法中，丰度的结果不一致。相比之下，β多样性分析产生了可比的图谱，即使在转化为门或功能时也是如此，三种消化器类型可以清晰区分。对每种方法的特征（即操作分类单元、宏蛋白质、代谢物和细胞组学特征）进行深入分析，得出了某些相似的特征，但不同方法之间也存在一些明显的差异，这与厌氧消化过程的复杂性有关。总之，通过流式细胞术进行细胞指纹图谱是一种可靠、快速的全规模监测厌氧消化微生物组的方法，通过其他方法互补识别关键特征，可以直接解释厌氧消化过程的性能。
