Fate of influent microbial populations during medium chain carboxylic acid recovery from brewery and pre-fermented food waste streams. Issue 2 (24th December 2021)

• Record Type: Journal Article
• Authors: Shrestha, Shilva; Colcord, Brittany; Fonoll, Xavier; Raskin, Lutgarde
• Is Part Of: Environmental science. Volume 8:Issue 2(2022)
• Page Start: 257
• Page End: 269
• Publication Date: 2021-12-24
• Subjects: Water-supply -- Periodicals; Water security -- Periodicals; Water resources development -- Periodicals; Water chemistry -- Periodicals; 553.705
• DOI: 10.1039/d1ew00656h
• Languages: English
• ISSNs: 2053-1400

Abstract

Abstract : Waste streams continuously introduce active and inactive microbial populations that can influence assembly of microbial communities in chain elongation systems. Abstract : Chain elongation is an emerging biotechnology for medium chain carboxylic acid (MCCA) production from diverse waste streams. Food and brewery waste were upgraded to MCCAs using mixed-culture microbial communities in an anaerobic sequencing batch reactor. A maximum MCCA volumetric production rate of 9.1 mmole L −1 d −1 (1.1 g L −1 d −1 ) was achieved with caproate as the major MCCA. MCCA toxicity induced at acidic pH limited greater MCCA production. Microbial community dynamics were investigated using time-series 16S rRNA gene (referred to as rDNA) and 16S rRNA sequencing data. The relative activities (as determined by 16S rRNA sequencing) of microbial populations belonging to the Clostridiales order and Pseudoramibacter genus positively correlated to MCCA production. The ratio of relative activity and relative abundance (rRNA/rDNA) and a mass balance-based approach to calculate specific growth rates were used to identify influent populations that were active in the bioreactor. Some of the most abundant and active microbial populations in the influent ( e.g., Prevotella ) were less active in the bioreactor. On the other hand, chain elongating microbial groups ( Clostridiales and Pseudoramibacter ) were enriched in the bioreactor even though they were present at low relative abundances and activities in the influent, suggesting that selection dominated bioreactor community assembly. The approaches developed in this study allow identification of active and inactive microbial populations, which will improve the linkage of process performance with microbial community structure during process modeling.