Formatted Title
Integrating Genomics, Metagenomics, and Kinetics for Biokinetic Correlations in D. (ital)mccartyi Enriched Consortia: Implications for Field-Scale Biodegradation Modeling
Background/Objectives
Establishing stable reductive dechlorination cultures is essential in bioremediation research, especially for understanding biological processes at a large scale. While dechlorinating consortia are available, their metagenomic characterization is often incomplete, limiting our insight into their metabolic properties. Furthermore, a comprehensive understanding of the relationship between reaction kinetics and biological parameters remains unclear. Various kinetic models describe the reductive dechlorination (RD) process in the literature, but data on the kinetics and biomass often rely on broad indicators, not representing the specific dechlorinating population. Consequently, there exists a gap in understanding the dynamics and activity of specialized dechlorinating biomass, including D. mccartyi (Dhc) and reductive dehalogenase genes, and their correlation with kinetic performance. These parameters are intricately linked to the rate of dechlorination, underscoring the need to accurately define the biodiversity and functional properties of a dechlorinating community, quantify the biomarkers involved in the biological RD process, and evaluate kinetic parameters for the establishment of bio-kinetic correlations. This study presents an integrated approach that combines genomics, metagenomics, and kinetics (GMK) to establish precise bio-kinetic correlations. This approach has been primarily applied to a Dhc-enriched consortium, thereby facilitating the extrapolation of critical kinetic parameters essential for modeling RD biodegradation processes. This enhanced understanding offers promise for applications in both engineered systems and field-scale scenarios.
Approach/Activities
The GMK approach was applied to an active dechlorinating consortium known as the TRM culture, which has been stable for a decade and was originally derived from a wastewater treatment plant. The TRM culture was maintained at 30°C in a 2-L anaerobic bottle. It operated as a fed-batch system in a sequential manner with a cell retention time of 30 days. The culture was fed with 0.5 mM of PCE and 5 mM of lactate as a fermentable electron donor. Additionally, other electron donors, such as H2, as well as bio-based materials like polyhydroxybutyrate (PHB) and biochar, were tested. PCE degradation kinetics have been monitored by quantifying the concentration of chloroethenes and ethene from the headspace using gas-chromatography with a flame ionizing detector (GC-FID). Known dechlorinating biomarkers (16S rRNA Dhc, tceA, bvcA, vcrA genes) were quantified by Digital Droplet PCR (ddPCR) during the PCE degradation kinetics. The TRM metagenome has been defined by MiSeq Illumina Short Reads sequencing and compared with Nanopore Oxford short reads sequencing technology.
Results/Lessons Learned
The TRM culture is notably Dhc-enriched, with Dhc comprising 80% of the total Amplicon Sequence Variants (ASVs). Metagenomic analysis of the Dhc-extracted genome, obtained from the assembled metagenome of the consortium, revealed the presence of a catalytically active dehalogenase enzyme (RdhA) and nine distinct genes predicted to be reductive dehalogenases. Additionally, the Dhc-extracted genome contains gene arrays associated with the CRISPR-Cas system, recently recognized for its role in mobilizing reductive dehalogenase genes. We also explored the metabolic and functional interactions of other microbial components, including species like Clostridium and Petrimonas, within the TRM enrichment, which will be thoroughly detailed during the presentation, also considering various conditions applied to the TRM consortium. Furthermore, we will discuss the results obtained from Illumina and Nanopore Sequencing platforms. We have also established correlations between the abundances of RD biomarker genes and the maximum reductive dechlorination rates (RDmax, mmol Cl−/L/day). Per-cell respiration rates (Kmax, mmol Cl−/Dhc/day) were defined, enabling the extrapolation of these bio-kinetic parameters for modeling the RD process under various conditions. The implications for biokinetic modeling and field-scale applications will be comprehensively discussed during the presentation.