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Published on: October 15, 2015
Resolving metabolic interdependencies during chlorobenzene dechlorination in a Dehalobacter-containing community
William T Scott1, Luz A Puentes Jácome2, Bart Nijsse3
1Department of Agricultural and Biological Engineering, Purdue University, 610 Purdue Mall, West Lafayette, IN, 47907, USA; Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Stippeneng 4, Wageningen, 6703 HB, The Netherlands; UNLOCK, Wageningen University & Research and Delft University of Technology, Stippeneng 2, Wageningen, 6703 HB, The Netherlands.
Abstract:
Chlorinated benzenes are persistent groundwater contaminants whose anaerobic transformation can depend on organohalide-respiring microorganisms embedded within metabolically interconnected communities. Here, we asked which microorganisms and metabolic functions characterize a Dehalobacter-containing dechlorinating community, and whether bioinformatics and genome-resolved metabolic modeling could identify candidate interactions supporting organohalide respiration. To address these questions, we integrated dechlorination data from related Dehalobacter-containing enrichment lineages with genome-resolved metagenomics and constraint-based modeling. Transformation of 1,2,4-trichlorobenzene (TCB) to dichlorobenzenes and monochlorobenzene (MCB) was observed in one enrichment lineage, whereas MCB transformation to benzene was observed in a related lineage; in the latter, benzene increased from 0 to 62.3μmol bottle-1 as MCB decreased from 88.3 to 22.0μmol bottle-1 over 120 days. These experiments comprised one observation unit per lineage rather than independent biological reactor replicates and therefore do not establish continuous TCB-to-benzene conversion within a single culture. Genome-resolved reconstruction identified two Dehalobacter populations among 12 community members selected for metabolic modeling. Following structural, phenotypic, and thermodynamic quality control, pairwise random flux sampling predicted a metabolically differentiated exchange network: Methanobacterium consumed H2 in all 11 pairwise models (median model-normalized flux, 22.36 mmol gDW-1 h-1), whereas Methanothrix consumed acetate in all 11 (10.16 mmol gDW-1 h-1) and released CH4 (9.51 mmol gDW-1 h-1), distinguishing hydrogenotrophic and acetoclastic methanogenic functions. Model-guided community reduction across 39 sensitivity scenarios produced objective-minimal candidate communities in 34 scenarios, predominantly bicultures with condition-dependent recruitment of a third member. A Dehalobacter member occurred in every candidate community and Methanothrix recurred across all evaluated scenarios, defining a compact model-predicted Dehalobacter-methanogen backbone rather than demonstrating biological indispensability. Together, these results distinguish observed dechlorination from genome-inferred metabolic potential and model-predicted interactions, providing experimentally testable hypotheses for metabolic dependencies that could inform more predictable anaerobic bioremediation strategies.
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