Ecology of food waste chain-elongating microbiome

Microbial chain elongation has emerged as a valuable bioprocess for obtaining marketable products, such as medium chain fatty acids usable in several industrial applications, from organic waste. The understanding of the microbiology and microbial ecology in these systems is crucial to apply these microbiomes in reliable production processes controlling microbial pathways to promote favourable metabolic processes, which will in turn increase product specificity and yields. In this research, the dynamics, cooperation/competition and potentialities of bacterial communities involved in the long-term lactate-based chain elongation process from food waste extract were evaluated under different operating conditions by DNA/RNA amplicon sequencing and functional profile prediction. The feeding strategies and the applied organic loading rates strongly affected the microbial community composition. The use of food waste extract promoted the selection of primary fermenters (i.e., , ) responsible for the production of electron donors (i.e., lactate). The discontinuous feeding and the organic loading rate 15 gCOD L d selected the best performing microbiome in which microbes coexist and cooperate to complete the chain elongation process. Both at DNA and RNA level, this microbiome was composed by the lactate producer , the short chain fatty acids producers Erysipelotrichaceae , and the chain elongator . This microbiome also showed the highest predicted abundance of short-chain acyl-CoA dehydrogenase, the functional enzyme responsible for the chain elongation process. The combined approach herein used allowed to study the microbial ecology of chain elongation process from food waste by identifying the main functional groups, establishing the presence of potential biotic interactions within the microbiomes, and predicting metabolic potentialities. This study provided pivotal indications for the selection of high-performance microbiome involved in caproate production from food waste that can serve as a basis for further improving system performance and engineering the process scale-up.