TY - JOUR
T1 - The relationship between quorum sensing dynamics and biological performances during anaerobic membrane bioreactor treatment
AU - Shah, Syed Salman Ali
AU - Park, Hyeona
AU - Park, Hyung June
AU - Kim, Jinwoo
AU - Mameda, Naresh
AU - Choo, Kwang Ho
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/11
Y1 - 2022/11
N2 - Anaerobic membrane bioreactors (AnMBRs) enhance carbon neutrality with biomethane recovery from wastewater; however, microbial signaling, which may affect biological performances, was poorly understood. Here, we thus evaluate quorum sensing (QS) dynamics while monitoring acyl-homoserine lactones (AHLs) and autoinducer-2 (AI-2) levels during long-term AnMBR operations after sludge inoculation. Significant organic removal and methane production were achieved with the reactor startup. Signal molecule levels varied with transient organic loading rates, depending on their types. A starving condition may cause an increase in short- and medium-chain AHLs and AI-2. Biopolymers, biosolids, volatile fatty acids, and alkalinity levels had positive correlations with short- and medium-chain AHLs and AI-2, whereas methane production had positive correlations with long-chain AHLs. The principal component analysis of QS signal composition and biological performance data explains their interconnectivity. The findings of this study help to understand that QS signals regulate metabolic pathways in addition to microbial group behaviors.
AB - Anaerobic membrane bioreactors (AnMBRs) enhance carbon neutrality with biomethane recovery from wastewater; however, microbial signaling, which may affect biological performances, was poorly understood. Here, we thus evaluate quorum sensing (QS) dynamics while monitoring acyl-homoserine lactones (AHLs) and autoinducer-2 (AI-2) levels during long-term AnMBR operations after sludge inoculation. Significant organic removal and methane production were achieved with the reactor startup. Signal molecule levels varied with transient organic loading rates, depending on their types. A starving condition may cause an increase in short- and medium-chain AHLs and AI-2. Biopolymers, biosolids, volatile fatty acids, and alkalinity levels had positive correlations with short- and medium-chain AHLs and AI-2, whereas methane production had positive correlations with long-chain AHLs. The principal component analysis of QS signal composition and biological performance data explains their interconnectivity. The findings of this study help to understand that QS signals regulate metabolic pathways in addition to microbial group behaviors.
KW - Acyl-homoserine lactones
KW - Anaerobic membrane bioreactor
KW - Autoinducer-2 (AI-2)
KW - Biomethane
KW - Quorum sensing
UR - http://www.scopus.com/inward/record.url?scp=85138523053&partnerID=8YFLogxK
U2 - 10.1016/j.biortech.2022.127930
DO - 10.1016/j.biortech.2022.127930
M3 - Article
C2 - 36261999
AN - SCOPUS:85138523053
SN - 0960-8524
VL - 363
JO - Bioresource Technology
JF - Bioresource Technology
M1 - 127930
ER -