ReviewPlants (Basel, Switzerland)2026
Nutrient-Driven Modulation of Microbial, Plant, and Rhizosphere Processes for Heavy Metal Remediation.
Review in Plants (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
7 authors.
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Abstract
Heavy metal pollution remains a major global environmental challenge due to persistent ecological risks and potential threats to food safety. Microbial remediation and phytoremediation represent sustainable alternatives to conventional treatments; however, their effectiveness is strongly influenced by number of factors including nutrient availability. This review critically examines how nutritional regulation governs microbial metabolism, plant physiological responses, and rhizosphere interactions to enhance heavy metal transformation and removal. Metal bioavailability depends on type, concentration, soil pH, redox potential, and microbial processes. Interventions including fertilizers, chelating agents, inoculation with arbuscular mycorrhizal fungi and plant-growth-promoting rhizobacteria enhance phytoremediation processes through regulating plant nutrient and heavy metal uptake, while selection between ammonium/nitrate changes rhizosphere pH consequently affects plant metal uptake. Similarly, nutrients, i.e., phosphate, iron, zinc and manganese competitively affect metal uptake. Organic amendments enhance phytostabilization, especially for selenium and mercury, while enhancing chromium reduction. Sulfur-reducing bacteria precipitate metals as insoluble sulfides with 90% efficiency. In addition, soil amendments including plant-growth-promoting rhizobacteria, arbuscular mycorrhizal fungi, and metal-chelating agents can be strategically used to enhance the phytoextraction from metal from contaminated soils. We suggest that the future integration of modern approaches such as multi-omics and cisgenesis supported by artificial intelligence tools can help to accurately predict the efficiency of nutrient regulation strategies and their remediation outcomes, thereby supporting evidence-based soil management.
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