Improving the phytoextraction capacity of plants to scavenge metal(loid)-contaminated sites
Bibliographic record
Abstract
Plants are able to extract metal(loid) contaminants from the soil or water through their roots and translocate them to harvestable aerial shoots. Of late, this plant potential has been used as a phytotechnology, termed as phytoextraction, for cleaning contaminated sites, and this process has successfully removed elements like As, Cd, Cu, Ni, and Pb, among others. Exploring plants with high metal-accumulation capacity, as well as engineering new hyperaccumulators, is a need of the hour. It is assumed that hyperaccumulators have a >1 shoot:root metal-accumulation ratio, which they achieve by way of (i) overexpression of transport systems for improved sequestration, (ii) tissue-specific protein expression, and (iii) high concentration of metal chelators. Unlike nonhyperaccumulators, the hyperaccumulating species normally bind metal ions to weak oxygen ligands and use strong ligands only for transient binding during transport to storage sites. Adequate understanding of genetics, biochemistry, and molecular biology of metal accumulation is a prelude to developing transgenics with improved phytoremediation capacity. Current research in plant breeding, genomics, and proteomics suggest promising leads to the creation of “remediation” cultivars. Several transporter genes associated with metal uptake, transport, and accumulation have been identified. Efforts are underway to enhance the phytoextraction capacity of relevant species, not only by using chelating agents but also by attempting hybridization, protoplast fusion, as well as genetic engineering through novel gene transfer, overexpression of genes, and (or) reverse gene insertion, to enhance (i) transpiration rate; (ii) uptake, translocation, and metabolism of metals; (iii) activity of enzymes related to rate-limiting steps; and (iv) transformation of accumulated metal to volatile forms, and (or) silencing gene(s) that encode proteases. Genome evolution in hyperaccumulators needs to be understood through a systematic study of ecological and molecular genomics. Sequencing of a complete genome of hyperaccumulators can help in identifying the promising functional noncoding regions in the genome, thus making the experimental analysis more accurate. In addition to the constitutive overexpression of a single gene, simultaneous expression of several genes in specific cellular components has to be focused. Other areas that require expert attention include identification of metal-transporter proteins and the introduction of genes encoding the metal transporters, overexpression of metallothioneins and phytochelatin synthase, and overproduction of nicotianamine and histidine in plants. A comprehensive study of transgenic gene frequency, covering several plant generations growing on polluted as well as nonpolluted soils, may assess the possibility of gene escape into the environment and its transfer to the microorganisms present in the surroundings. This review attempts not only to collect and collate information available on mechanisms of metal accumulation and detoxification in plants and on the factors affecting the tolerance and phytoextraction capacity of plants but also the strategies that have been or can be devised for raising novel plant genotypes with elevated capacity of metal accumulation and toxicity tolerance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".