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Fig. 8 | Microbiome

Fig. 8

From: Machine learning-assisted identification of bioindicators predicts medium-chain carboxylate production performance of an anaerobic mixed culture

Fig. 8

Overview of the quantitative prediction of process performance in the anaerobic bioreactor system. a Anaerobic mixed culture fermentation of lactate and xylan for the production of n-caproate (C6) and n-caprylate (C8) by lactate-based chain elongation. Based on the recovery of metagenome-assembled genomes, the left panel shows the bioindicators capable of performing key steps of the fermentation. b Reducing the hydraulic retention time (HRT) as an operation-based strategy to optimise the process performance and to manage the reactor microbiota towards desired functions. Shortening the HRT from 8 to 2 days enhanced productivities of C4, C6 and C8. The enriched reactor microbiota comprised functional groups involved in xylan hydrolysis, xylose fermentation and chain elongation with lactate, presented by a co-occurrence network of environmental factors (controlled conditions with only reducing the HRT), ecosystem functioning (process performance) and microbial community. The full network is shown in Additional file 1: Fig. S13. c Predicting performance of ecosystem processes with random forest analysis. We developed a random forest two-step workflow to predict the HRT phases and carboxylate production quantitatively by using relative abundance data of the 16S rRNA-derived species (ASVs, amplicon sequence variants)

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