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Araya G.,Catolica del Norte University | Acosta M.,Catolica del Norte University | Demergasso C.S.,Catolica del Norte University | Demergasso C.S.,Research Center Cientifica y Tecnologica Para la Mineria
Advanced Materials Research

Acidithiobacillus ferrooxidans is a chemiolithoautotrophic Gram-negative bacterium widely spread in ambient temperature bioleaching processes. Several strains of At. ferrooxidans were isolated and studied and, some time later, questions arise about whether it was a species with a wide metabolic variation or a group of closely related species. Advances in molecular biology, phylogeny and genomics have shed some light on At. ferrooxidans strains and allows their grouping according to their relations. However, significant challenges remains to be met, such as understanding how a particular strain faces environmental challenges and how a particular kind of adaptive response affects the growth and activity of the strain. The purpose of this study was to identify differential expression signals between At. ferrooxidans strains-with different abundances and dynamics-present in the bioleaching system at Escondida mine. Culture characterization and DNA macroarrays techniques provided some answers. Analysis of growth curves showed that IESL 32 had the highest anaerobic growth rate, while aerobic growth was similar for all strains. It was shown that though the phylogenetic analysis based on 16S rRNA sequences suggested a close relation between IESL 32 and the type strain ATCC 23270, the growth curves and the expression profile showed that the type strain and strain D2 had the closest similarity. Growth experiments under different conditions, together with the comparative analysis of gene expressions in At. ferrooxidans, could be a springboard for future investigations of strain characterization to broaden our knowledge about adaptation, metabolic strategies, regulation and microbial diversity in industrial processes. © (2013) Trans Tech Publications, Switzerland. Source

Soto P.,Catolica del Norte University | Soto P.,Research Center Cientifica y Tecnologica Para la Mineria | Demcrgasso C.,Catolica del Norte University | Demcrgasso C.,Research Center Cientifica y Tecnologica Para la Mineria | And 2 more authors.
WMSCI 2010 - The 14th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings

In the context of a bacterial assisted leaching system, understanding the kinetics of microbial oxidation is essential to explore alternatives for process optimization. On a laboratory scale, there are empirical-analytic models that fit well to the dynamic of bacterial populations. However, at industrial level, the bioleaching process complexity together with the limited understanding of the relationship among biological, physicochemical and operational variables, have made their modeling elusive. In this paper we present the results of the characterization of the oxidizing activity of a microbial community in an industrial bioleaching operation. Based on an ad-hoc data mining process defined for this problem, decision trees are firstly constructed and then a set of rules are selected to characterize the oxidizing activity of a subset of strips in a bioleaching system. Following the same process of decision tree generation and then rule selection, a second subset of strips are characterized and results are compared between both subsets of bioleaching strips. Source

Salazar C.N.,Catolica del Norte University | Acosta M.,Catolica del Norte University | Galleguillos P.A.,Catolica del Norte University | Galleguillos P.A.,Research Center Cientifica y Tecnologica Para la Mineria | And 3 more authors.
Advanced Materials Research

Acidithiobacillus ferrooxidans strain D2 was isolated from a copper bioleaching operation in Atacama Desert, Chile. Copper is widely used as cofactor in proteins but high concentrations of copper are toxic. Cells require certain mechanisms to maintain the copper homeostasis and avoid toxic effects of high intracellular concentration. The molecular response of A. ferrooxidans strain D2 grown in the presence/absence of copper was examined using a A. ferrooxidans whole-genome DNA microarrays. Roughly 23% of 3,147 genes represented on the microarray were differentially expressed; about 9% of them were upregulated in the presence of copper. Among the upregulated genes, those encoding for the copper efflux protein (CusA) and for the copper-translocating P-type ATPase (CopA) were upregulated. The expression of genes encoding proteins related to iron transport was repressed. Similarly, genes related with assimilative metabolism of sulfur (L-cysteine biosynthesis) cysB, cysJ, cysI, CysD-2 and cysN were upregulated. Our results show that when A. ferrooxidans strain D2 was challenged with high copper concentrations, genes related to copper stress response were upregulated as well as others that have not been reported to be related to that mechanism. In addition, some genes related to other metabolic pathways were repressed, probably because of the energy cost of the stress response. © (2013) Trans Tech Publications, Switzerland. Source

Ghorbani Y.,University of Exeter | Ghorbani Y.,Research Center Cientifica y Tecnologica Para la Mineria | Montenegro M.R.,Research Center Cientifica y Tecnologica Para la Mineria

Although heap leaching using sulfuric acid was introduced to the uranium industry in the 1950s, sodium carbonate-bicarbonate (alkaline) heap leaching of low-grade Ca-carbonate-rich uranium ores has recently gained popularity. This study presents the results of two column tests on a calcrete-type uranium-vanadium (carnotite) ore using a mixture of sodium carbonate and bicarbonate (Na2CO3/NaHCO3) as the leach solution. This data was kindly supplied by Toro Energy Ltd. The experimental data comprised physical-chemical leach information and two different irrigation rates (10 and 20 L/h·m2). The experimental data indicated that the carnotite ore with high calcium carbonate (CaCO3) can be leached effectively using the alkaline leach solution. The increase in the irrigation rate increased the uranium and vanadium extraction and decreased their concentration in the effluent. The column leach data was therefore fitted to a simplified first-order kinetic model using two approaches, a general form and a second based on the reagent consumption per unit mass of the initial valuable species (U and V). As reagent consumption is a key economic factor in the heap leaching process, having a kinetic leaching model incorporating reagent consumption would provide useful techno-economic information. In this regards a new leaching index of (β) is also introduced. Both approaches of the first order kinetic model provide a good agreement with the column testing data. © 2016 Elsevier B.V. All rights reserved. Source

Susana S.R.,University of Adelaide | Susana S.R.,Catolica del Norte University | Glonek G.,University of Adelaide | Soto P.,Catolica del Norte University | And 3 more authors.
Advanced Materials Research

A descriptive mathematical model is a valuable tool that can help understand the relationship between the bioheap leaching process at the Escondida mine in Chile, the microbial community that participates in the process, and the physical characteristics of the heap, such as the arrangement and the mineral composition of the individual leaching strips. However, the bioleaching process at Escondida is a system, which presents many challenges to modelling. The main challenges relate to the heap's design and mineral characteristics, the complex interactions between biological and physicochemical parameters, and the unexpected changes in the heap's operational conditions. The heap is sampled periodically, and more than 20 variables, including 16S rRNA gene copy number for 16 different microorganisms, are recorded. The data exhibit complex behaviour, including variable dynamics between strips, systematic differences between lifts of the heap, and spatial and temporal correlations. In this work, we develop a non-linear descriptive model for the microbial population trajectory along the leaching cycle and across the different strips. The parameterisation of the model considers the different dynamics between lifts, and strip specific parameters characterise the behaviour of data from individual strips. The parameterisation also allows for spatial correlation by incorporating the effect of adjacent strips on the microbial population trajectory. The model is found to provide a good fit to the data and captures its behaviour across strips. Residuals showed no systematic patterns of departure between the observed and modelled response. The R2 values ranged from 0.53 to 0.71, indicating a reasonable level of predictive power. © (2013) Trans Tech Publications, Switzerland. Source

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