Effect of heavy metal-induced stress on two extremophilic microbial communities from Caviahue-Copahue, Argentina
2021
Massello, Francisco L. | Donati, Edgardo
Metal pollution is a great concern worldwide and the development of new technologies for more sustainable extraction methods as well as for the remediation of polluted sites is essential. Extremophilic microorganisms are attractive for this purpose since they have poly-resistance mechanisms which make them versatile. In this work, we sampled an acidic river and a hot spring of Caviahue-Copahue volcanic environment. The indigenous microbial communities were exposed to five heavy metals (Cd, Co, Cu, Ni and Zn) in batch-cultures favouring different metabolisms of biotechnological interest. Remarkably, high tolerance values were reached in all the cultures, even though most of the metals studied were not present in the environmental sample. Particularly, outstanding tolerances were exhibited by acidophiles, which grew at concentrations as high as 400 mM of Zn and Ni. High-throughput amplicon sequencing of 16S rRNA gene was used to study the indigenous communities and the resistant consortia. We took three approaches for the analysis: phylotypes, OTUs and amplicon sequence variants (ASVs). Interestingly, similar conclusions were drawn in all three cases. Analysing the phylogenetic structure and functional potential of the adapted consortia, we found that the strongest selection was exerted by the culture media. Notably, there was a poor correlation between alpha diversity and metal stress; furthermore, metal stress did not seem to harm the functional potential of the consortia. All these results reveal a great adaptability and versatility. At the end, 25 metal-resistant extremophilic consortia with potential uses in bioremediation, bioleaching or biomonitoring processes were obtained.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par National Agricultural Library
Découvrez la collection de ce fournisseur de données dans AGRIS