The organomercurial lyase Merb possesses unique metal-binding properties
Bibliographic record
Abstract
Select bacterial strains survive in mercury-contaminated environments due to acquisition of a transferable genetic element known as the mer operon. The mer operon typically encodes for a series of proteins that includes two enzymes, MerA and MerB. The organomercurial lyase (MerB) cleaves carbon-mercury bonds of organomercurial compounds yielding ionic mercury Hg (II) and a reduced-carbon compound. The Hg (II) ion product remains bounds until it is shuttled directly to the mercuric ion reductase (MerA) to be reduced. Based on NMR spectroscopy and X-ray crystallography studies1, we have determined that Cys96, Asp99 and Cys159 of E. Coli MerB form a catalytic triad required for cleavage of the carbon-Hg bond and binding of the Hg (II) ion product. The three catalytic residues are conserved in 61 of 65 known variants of MerB and the four remaining variants retain both cysteine residues, but contain a serine in place of Asp99. Given its unique activity, we have examined the role of serine as a catalytic residue and the ability of MerB to cleave other organometals such as organotin (known substrates or inhibitors) and organolead compounds. Soaking MerB crystals with either dimethyltindibromide or trimethylleadchloride compound indicates that MerB crystals have the capacity to cleave both carbon-Sn and carbon-Pb bonds, and we have determined crystal structures of a MerB-Sn and a MerB-Pb complex. Furthermore, substitution of Ser for Asp99 (MerB D99S) in E. coli MerB alters the metal-binding specificity, as MerB D99S chelated an unknown metal during its purification. X-ray crystallography, ICP-MS and electron paramagnetic resonance (EPR) studies were performed to identify the unknown metal and the results of these studies will be presented. Given that mercury contaminated sites are often contaminated with other heavy metals, these studies indicate that other heavy metals may have important implications when using MerA and MerB in bioremediation of organomercurial compounds.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".