Improving the phytoextraction capacity of plants to scavenge metal(loid)-contaminated sites
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».