Data Driven Hypothesis Modelling Of Dehalococcoides Mccartyi: Predicted Biology And Biomarkers Of Stress In Two Mixed Microbial Communities
| dc.contributor.author | Mansfeldt, Cresten | en_US |
| dc.contributor.chair | Richardson, Ruth E. | en_US |
| dc.contributor.committeeMember | Zinder, Stephen H | en_US |
| dc.contributor.committeeMember | Gossett, James Michael | en_US |
| dc.date.accessioned | 2013-09-05T15:25:49Z | |
| dc.date.available | 2018-01-29T07:00:36Z | |
| dc.date.issued | 2013-01-28 | en_US |
| dc.description.abstract | Transcriptomic and proteomic expression levels were examined in two Dehalococcoides mccartyi (DMC)-containing mixed community cultures (D2 and the commercially available KB1®). These reductively organodehalorespiring communities were subjected to a wide range of feeding conditions in regards to electron acceptor type, electron donor type, feeding rate, and additions of known stressors. The electron acceptors included chloroethenes, chlorophenols, and chlorobenzenes. D2- specific and genus-wide (pangenome) microarrays monitored the transcriptional response. Clustering of D2's transcriptome formed distinct groupings of genes responding either positively, negatively, or indifferently to increased chloroethene respiration rate. The transcripts responding positively to respiration potentially participate in DMC's incompletely described electron transport chain. Correlation analysis inferred putative relationships in the regulation of reductive dehalogenases (RDases) and small electron carriers such as glutaredoxin and thioredoxin. Differential expression comparisons across electron acceptor types also highlighted the potential role of the RDases DET1559 and pceA (DET0318) in chloro-aromatic respiration. To comprehend more fully the transcriptomic data, the Reverse Engineering/Forward SimulationTM Bayesian network inference platform predicted a sparse set of confident gene-to- gene and gene-to-condition relationships. Conditions included metabolite levels, phenotypic respiration rates, or the existence of stressors. Strong interactions were noted across the D2 and KB-1® mixed communities for a positive relationship between the S-Layer cell wall protein and a major RDase (tceA in D2 and vcrA in KB-1®) as well as a positive interaction between the hydrogenase hup and the formate dehydrogenase. Applying a network inference algorithm to the D2 and KB-1® communities' transcriptome behavior created a data-driven predictive tool. This tool allows for hypothesis generation for hundreds of genes in the inferred network. . Combining the transcriptomic with proteomic data for stress conditions allowed a targeted detection of diagnostic biomarkers. Across the stressful conditions investigated for DMC (electron donor limitation as well as solvent, oxygen, and pH stress) DnaJ and HspR (DET1411-1412) appeared up-regulated. Due to their centrality in the cell and high background noise, they may prove to be difficult in situ biomarkers. Instead, the linking of a methylglyoxal synthase (DET0146) to solvent and the superoxide dismutase operon (DET0954-0965) to oxidative stress should be pursued as potential diagnostic field site indicators. | en_US |
| dc.identifier.other | bibid: 8267023 | |
| dc.identifier.uri | https://hdl.handle.net/1813/33825 | |
| dc.language.iso | en_US | en_US |
| dc.subject | Dehalococcoides mccartyi | en_US |
| dc.subject | transcriptomics and proteomics | en_US |
| dc.subject | network inference modelling | en_US |
| dc.title | Data Driven Hypothesis Modelling Of Dehalococcoides Mccartyi: Predicted Biology And Biomarkers Of Stress In Two Mixed Microbial Communities | en_US |
| dc.type | dissertation or thesis | en_US |
| thesis.degree.discipline | Civil and Environmental Engineering | |
| thesis.degree.grantor | Cornell University | en_US |
| thesis.degree.level | Doctor of Philosophy | |
| thesis.degree.name | Ph. D., Civil and Environmental Engineering |
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