One of the challenges to implementing the modeling of the biological reductive dechlorination (RD) process is the evaluation of biological parameters that represent the abundance/activity levels of the microorganisms involved in the biodegradation of chloroethenes. Here we report a combined analysis of kinetic and specific biomass parameters conducted on three dechlorinating consortia enriched on PCE, TCE and cis-1,2-DCE. In these consortia, Dehalococcoides mccartyi (Dhc) represented >=70% of the bacterial population identified via 16S rRNA gene amplicon sequencing. Quantitative biomolecular methods were used to generate specific biomass parameters targeting either the Dhc population (16S rRNA genes or cells) or specific genes encoding RD process-involved reductive dehalogenases. The correlation factor between the abundance of active Dhc cells or tceA gene copies and maximum RD rates allowed to predict an increment of 7E+09 of active Dhc cells or 5E+09 tceA gene copies/L under controlled conditions. Diversely, the utilization of gene transcripts as biomass parameters for RD modeling did not provide reliable correlations with kinetic performances. This study provides valuable insights for further modeling of the RD process through the utilization of specific biomass parameters.
Correlations between maximum reductive dechlorination rates and specific biomass parameters in Dehalococcoides mccartyi consortia enriched on chloroethenes PCE, TCE and cis-1,2-DCE
Matturro Bruna;Aulenta Federico;Rossetti Simona
2021
Abstract
One of the challenges to implementing the modeling of the biological reductive dechlorination (RD) process is the evaluation of biological parameters that represent the abundance/activity levels of the microorganisms involved in the biodegradation of chloroethenes. Here we report a combined analysis of kinetic and specific biomass parameters conducted on three dechlorinating consortia enriched on PCE, TCE and cis-1,2-DCE. In these consortia, Dehalococcoides mccartyi (Dhc) represented >=70% of the bacterial population identified via 16S rRNA gene amplicon sequencing. Quantitative biomolecular methods were used to generate specific biomass parameters targeting either the Dhc population (16S rRNA genes or cells) or specific genes encoding RD process-involved reductive dehalogenases. The correlation factor between the abundance of active Dhc cells or tceA gene copies and maximum RD rates allowed to predict an increment of 7E+09 of active Dhc cells or 5E+09 tceA gene copies/L under controlled conditions. Diversely, the utilization of gene transcripts as biomass parameters for RD modeling did not provide reliable correlations with kinetic performances. This study provides valuable insights for further modeling of the RD process through the utilization of specific biomass parameters.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.