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Ultra-high performance liquid chromatography–high-resolution mass spectrometry (UPHLC–HRMS) is used to discover and monitor single or sets of biomarkers informing about metabolic processes of interest. The technique can detect 1000’s of molecules (i.e., metabolites) in a single instrument run and provide a measurement of the global metabolome, which could be a fingerprint of activity. Despite the power of this approach, technical challenges have hindered the effective use of metabolomics to interrogate microbial communities implicated in the removal of priority contaminants. Herein, our efforts to circumvent these challenges and apply this emerging systems biology technique to microbiomes relevant for contaminant biodegradation will be discussed. Chlorinated ethenes impact many contaminated sites, and detoxification can be achieved by organohalide-respiring bacteria, a process currently assessed by quantitative gene-centric tools (e.g., quantitative PCR). This laboratory study monitored the metabolome of the SDC-9™ bioaugmentation consortium during cis-1,2-dichloroethene (cDCE) conversion to vinyl chloride (VC) and nontoxic ethene. Untargeted metabolomics using an UHPLC-Orbitrap mass spectrometer and performed on SDC-9™ cultures at different stages of the reductive dechlorination process detected ~10,000 spectral features per sample arising from water-soluble molecules with both known and unknown structures. Multivariate statistical techniques including partial least squares-discriminate analysis (PLSDA) identified patterns of measurable spectral features (peak patterns) that correlated with dechlorination (in)activity, and ANOVA analyses identified 18 potential biomarkers for this process. Statistical clustering of samples with these 18 features identified dechlorination activity more reliably than clustering of samples based only on chlorinated ethene concentration and Dhc 16S rRNA gene abundance data, highlighting the potential value of metabolomic workflows as an innovative site assessment and bioremediation monitoring tool.

Chlorinated volatile organic compound (cVOC) degradation rate constants are crucial information for site management. Conventional approaches generate rate estimates from the monitoring and modeling of cVOC concentrations. This requires time series data collected along the flow path of the plume. The estimates of rate constants are often plagued by confounding issues, making predictions cumbersome and unreliable. Laboratory data suggest that targeted quantitative analysis of Dehalococcoides mccartyi ( Dhc ) biomarker genes (qPCR) and proteins (qProt) can be directly correlated with reductive dechlorination activity. To assess the potential of qPCR and qProt measurements to predict rates, we collected data from cVOC-contaminated aquifers. At the benchmark study site, the rate constant for degradation of cis -dichloroethene (cDCE) extracted from monitoring data was 11.0 ± 3.4 yr -1 , and the rate constant predicted from the abundance of TceA peptides was 6.9 yr -1 . The rate constant for degradation of vinyl chloride (VC) from monitoring data was 8.4 ± 5.7 yr -1 , and the rate constant predicted from the abundance of TceA peptides was 5.2 yr -1 . At the other study sites, the rate constants for cDCE degradation predicted from qPCR and qProt measurements agreed within a factor of 4. Under the right circumstances, qPCR and qProt measurements can be useful to rapidly predict rates of cDCE and VC biodegradation, providing a major advance in effective site management.