AI Article Synopsis
- Bacteria play a vital role in composting microbiomes, yet their communities and interactions are not fully understood.
- A massive analysis of 577 global compost datasets revealed over 15 million distinct bacterial sequences and identified 30 key biomarker taxa that can differentiate compost types (food, sludge, manure) with over 98% accuracy.
- These biomarkers are linked to important carbon and nitrogen processes, serve as keystone species to maintain network stability, and could inform strategies to improve composting effectiveness for various organic materials.
Article Abstract
Bacteria are an influential component of diverse composting microbiomes, but their structure and underlying dynamics are poorly understood. This study analyzed the bacterial communities of 577 compost datasets globally and constructed a substrate-dependent catalog with more than 15 million non-redundant 16S rRNA gene sequences. Using a random-forest machine-learning model, 30 biomarker taxa were identified that accurately distinguish between the food, sludge and manure waste composting microbiomes (accuracy >98 %). These biomarker taxa were closely associated with carbon and nitrogen metabolic processes, during which they contributed to the predominant stochastic process and are influenced by different factors in the substrate-specific composts. This is corroborated by the community topological characteristics, which feature the biomarkers as keystone taxa maintaining the bacterial network stability. These findings provide a theoretical basis to identify and enhance the biomarker-functional bacteria for optimizing the composting performance of different organic wastes.
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| http://dx.doi.org/10.1016/j.biortech.2023.130118 | DOI Listing |
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