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. 2019 Jan 30:10:60.
doi: 10.3389/fmicb.2019.00060. eCollection 2019.

Domestication of Local Microbial Consortia for Efficient Recovery of Gold Through Top-Down Selection in Airlift Bioreactors

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Domestication of Local Microbial Consortia for Efficient Recovery of Gold Through Top-Down Selection in Airlift Bioreactors

Ricardo Ulloa et al. Front Microbiol. .

Abstract

Extreme acidophiles play central roles in the geochemical cycling of diverse elements in low pH environments. This has been harnessed in biotechnologies such as biomining, where microorganisms facilitate the recovery of economically important metals such as gold. By generating both extreme acidity and a chemical oxidant (ferric iron) many species of prokaryotes that thrive in low pH environments not only catalyze mineral dissolution but also trigger both community and individual level adaptive changes. These changes vary in extent and direction depending on the ore mineralogy, water availability and local climate. The use of indigenous versus introduced microbial consortia in biomining practices is still a matter of debate. Yet, indigenous microbial consortia colonizing sulfidic ores that have been domesticated, i.e., selected for their ability to survive under specific polyextreme conditions, are claimed to outperform un-adapted foreign consortia. Despite this, little is known on the domestication of acidic microbial communities and the changes elicited in their members. In this study, high resolution targeted metagenomic techniques were used to analyze the changes occurring in the community structure of local microbial consortia acclimated to growing under extreme acidic conditions and adapted to endure the conditions imposed by the target mineral during biooxidation of a gold concentrate in an airlift reactor over a period of 2 years. The results indicated that operative conditions evolving through biooxidation of the mineral concentrate exerted strong selective pressures that, early on, purge biodiversity in favor of a few Acidithiobacillus spp. over other iron oxidizing acidophiles. Metagenomic analysis of the domesticated consortium present at the end of the adaptation experiment enabled reconstruction of the RVS1-MAG, a novel representative of Acidithiobacillus ferrooxidans from the Andacollo gold mineral district. Comparative genomic analysis performed with this genome draft revealed a net enrichment of gene functions related to heavy metal transport and stress management that are likely to play a significant role in adaptation and survival to adverse conditions experienced by these acidophiles during growth in presence of gold concentrates.

Keywords: Acidithiobacillus; acidophiles; adaptation; consortia; domestication; metagenome derived assembly; targeted metagenomics.

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Figures

Figure 1
Figure 1
Top-down approach and experimental design utilized in the study.
Figure 2
Figure 2
Acclimatization of IMC present in the Andacollo samples to acidic conditions at 30°C. (A) Oxidation of ferrous iron in DSMZ 882 medium. (B) Production of protons in 0K-S0 medium. Sample types are color coded to differentiate slurry (gray), water (blue), biofilm (orange), milled ore (green), and sterile control (black). Symbols: BVB (formula image); BVS (formula image); BVW (formula image); SPB (formula image); SPS (formula image); RVS (formula image); PPO (formula image); SC: sterile control (-).
Figure 3
Figure 3
Biooxidation capacity of the adapted RVS consortium. (A) Biooxidation was assessed as the solubilization of Fe (A) and Zn (B) in DSMZ 882 medium at 30°C, during the Cycle 0 and Cycle 10.
Figure 4
Figure 4
Taxonomic profiles and proportions of the RVS microbial consortium during adaptation cycles to the RGC. (A) Phylum level, top 100 ASVs; (B) Class level, top 100 ASVs; (C) Order level, top 20 ASvs. (D) Absolute abundance of the ASVs ascribed to the dominant taxon (Acidithiobacillia): ASV1 (184,713 total reads); ASV2 (51,844 total reads); ASV3 (191 total reads); ASVr (3,890 total remaining reads).
Figure 5
Figure 5
Rankabundance and heatmap of known acidophilic taxa during adaptation of the RVS microbial consortium. Values in heatmap are the actual read variant abundances of the top 2,000 ASVs.
Figure 6
Figure 6
Domesticated RVS microbial consortium metagenomic analysis. (A) Per base coverage and sequencing depth coverage of different sequenced Acidithiobacillus spp. used as references (individually or concatenated). (B) Comparative analysis of shared vs. exclusive genes between the metagenome derived assembled genome (MAG) for the dominant taxon in the domesticated consortium (at Cycle 10) and sequenced A. ferrooxidans strains. (C) Genomic representation of the MAG_RVS1 showing conservation of gene products in sequenced A. ferrooxidans strains and gene islands (GIs) encoding adaptive functions.

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References

    1. Aziz R. K. K., Bartels D., Best A. A., DeJongh M., Disz T., Edwards R. A., et al. (2008). The RAST Server: rapid annotations using subsystems technology. BMC Genomics 9:75. 10.1186/1471-2164-9-75 - DOI - PMC - PubMed
    1. Barrick J. E., Lenski R. E. (2013). Genome dynamics during experimental evolution. Nat Rev. Genet. 14 827–839. 10.1038/nrg3564 - DOI - PMC - PubMed
    1. Bokulich N. A., Kaehler B. D., Rideout J. R., Dillon M., Bolyen E., Knight R., et al. (2018). Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6:90. 10.1186/s40168-018-0470-z - DOI - PMC - PubMed
    1. Bolger A. M., Lohse M., Usadel B. (2014). Trimmomatic: a flexible trimmer for illumina sequence data. Bioinformatics 30 2114–2120. 10.1093/bioinformatics/btu170 - DOI - PMC - PubMed
    1. Bolyen E., Rideout J. R., Dillon M. R., Bokulich N. A., Abnet C., Al-Ghalith G. A., et al. (2018). QIIME 2: reproducible, interactive, scalable, and extensible microbiome data science. PeerJ 6:e27295v1 10.7287/peerj.preprints.27295v1 - DOI - PMC - PubMed