Distribution of Organohalide-Respiring Bacteria between Solid and Aqueous Phases
Bibliographic record
Abstract
Contemporary microbial monitoring of aquifers relies on groundwater samples to enumerate nonattached cells of interest. One-dimensional column studies quantified the distribution of bacterial cells in solid and the aqueous phases as a function of microbial species, growth substrate availability and porous medium (i.e., Appling soil versus Federal Fine Ottawa sand with 0.75% and 0.01% [w/w] organic carbon, respectively). Without supplied growth substrates, effluent from columns inoculated with the tetrachloroethene- (PCE-) to-ethene-dechlorinating bacterial consortium BDI-SZ containing Dehalococcoides mccartyi (Dhc) strains and Geobacter lovleyi strain SZ (GeoSZ), or inoculated with Anaeromyxobacter dehalogenans strain W (AdehalW), captured 94-96, 81-99, and 73-84% of the Dhc, GeoSZ, and AdehalW cells, respectively. Cell retention was organism-specific and increased in the order Dhc < GeoSZ < AdehalW. When amended with 10 mM lactate and 0.11 mM PCE, aqueous samples accounted for 1.3-27 and 0.02-22% of the total Dhc and GeoSZ biomass, respectively. In Appling soil, up to three orders-of-magnitude more cells were associated with the solid phase, and attachment rate coefficients (katt) were consistently greater compared to Federal Fine sand. Cell-solid interaction energies ranged from -2.5 to 787 kT and were consistent with organism-specific deposition behavior, where GeoSZ and AdehalW exhibited greater attachment than Dhc cells. The observed disparities in microbial cell distributions between the aqueous and solid phases imply that groundwater analysis can underestimate the total cell abundance in the aquifer by orders-of-magnitude under conditions of growth and in porous media with elevated organic carbon content. The implications of these findings for monitoring chlorinated solvent sites are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".