Relating Chloroethene Respiration Rates in Dehalococcoides to Protein and mRNA Biomarkers

Molecular biomarkers could provide critical insight into myriad in situ microbial activities. In this study we explore correlations of both mRNA and protein biomarkers with chloroethene respiration rate in Dehalococcoides. In a series of continuously fed dechlorinating mixed-culture microcosm experi...

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Veröffentlicht in:Environmental science & technology 2012-09, Vol.46 (17), p.9388-9397
Hauptverfasser: Rowe, Annette R, Heavner, Gretchen L, Mansfeldt, Cresten B, Werner, Jeffrey J, Richardson, Ruth E
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Sprache:eng
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Zusammenfassung:Molecular biomarkers could provide critical insight into myriad in situ microbial activities. In this study we explore correlations of both mRNA and protein biomarkers with chloroethene respiration rate in Dehalococcoides. In a series of continuously fed dechlorinating mixed-culture microcosm experiments (n = 26), we varied respiratory substrates, substrate ratios and feeding rates. Transcript levels for most biomarkers were responsive down to 0.01× the culture’s maximum respiration rate. The dehalogenase TceA and the Ni–Fe hydrogenase HupL transcripts were positively correlated (Pearson’s r of 0.89 and 0.88, respectively) with respiration rates on log–log plots between 1.5 and 280 μeeq/L-hr for mRNA abundances of 107 to 1010 transcripts/mL (0.07–230 transcripts/genome). These trends were independent of the types of chloroethene or electron donors fed. Other mRNA target levels plateaued or declined at respiration rates above 5 μeeq/L-hr. Using both relative and absolute protein quantification methods, we found that per-genome protein abundances of most targeted biomarkers did not statistically change over the experimental time frames. However, quantified enzyme levels allowed us to calculate in vivo enzyme-specific rate constants (k cat) for the dehalogenases PceA and TceA: 400 and 22 substrate molecules/enzyme-sec, respectively. Overall, these data support the promise of both mRNA and protein biomarkers for estimating process rates through either empirical (mRNA-based) or kinetic (protein-based) models, but they require follow-up studies in other cultures and at active remediation sites.
ISSN:0013-936X
1520-5851
DOI:10.1021/es300996c