Multi Locus Sequence Typing scheme for Acidithiobacillus caldus strain
evaluation and differentiation
Harold Nu
~nez
a, David Loyola
b, Juan Pablo C
ardenas
a,c, David S. Holmes
a,c, D. Barrie Johnson
d,
Raquel Quatrini
a,c,*
aFundacion Ciencia & Vida, Santiago, Chile
bNational Center for Genomics, Proteomics and Bioinformatics of Chile, Santiago, Chile cFacultad de Ciencias Biologicas, Universidad Andres Bello, Santiago, Chile
dSchool of Biological Sciences, University of Wales, LL572UW Bangor, UK
Received 15 April 2014; accepted 29 July 2014 Available online 29 August 2014
Abstract
Phenotypic, metabolic and genetic properties of several Acidithiobacillus caldus strains indicate the existence of as yet undefined levels of variation within the species. Inspite of this, intraspecies genetic diversity has not yet been explored in detail.
In this study, the design and implementation of a Multi Locus Sequence Typing (MLST) scheme for At. caldus is described. This represents the first MLST-based study applied to industrial isolates of the species. Seven informative and discriminant MLST markers were selected using a sequence-driven approach and a custom-designed bioinformatic pipeline. The allelic profiles of thirteen At. caldus strains from diverse geographical origins and industrial settings were derived using this scheme.
MLST-based population structure analysis indicated only moderate amounts of genetic diversity within the set of strains, further supporting their current assignment to a single species. Also, no clear evidence for geographical isolation could be derived from this study. However, the prevalence of sequence type 1 in heap leaching industrial settings support the view that bioprocess conditions and dynamics may have a strong influence on At. caldus (microbial) microdiversity patterns.
The MLST scheme presented herein is a valuable tool for the identification and classification of strains of At. caldus for either ecological or evolutionary studies and possibly also for industrial monitoring purposes.
© 2014 The Authors. Published by Elsevier Masson SAS on behalf of Institut Pasteur. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
Keywords: Multi Locus Sequence Typing (MLST); Phylogenetics; SNPs; Sequence types; Acidithiobacillus caldus; Industrial isolates
1. Introduction
Bioleaching microbial communities harbor a moderate di-versity of acidophilic bacteria and archaea, spanning eleven known prokaryotic divisions and a wider number of classes. One of the best-studied classes is Acidithiobacillia [1]. The type genus of this class is Acidithiobacillus and consists of a
group of obligatory acidophilic, Gram-negative, rod shaped bacteria that derive energy from the oxidation of reduced sulfur compounds to support autotrophic growth [2,3]. For a number of years now, the genus included only three validly described sulfur oxidizing speciese Acidithiobacillus caldus, Acidithiobacillus thiooxidans and Acidithiobacillus alberten-sis e and one sulfur- and iron-oxidizer e Acidithiobacillus ferrooxidans, based on 16S rRNA gene sequence analysis[2]. Yet, significant intrinsic diversity judged in terms of both genetic and physiological heterogeneity has been recognized within the group in recent years. This has been considered
* Corresponding author. Fundacion Ciencia & Vida, Facultad de Ciencias Biologicas, Universidad Andres Bello, Santiago, Chile.
E-mail address:[email protected](R. Quatrini).
Research in Microbiology 165 (2014) 735e742
www.elsevier.com/locate/resmic
http://dx.doi.org/10.1016/j.resmic.2014.07.014
0923-2508/© 2014 The Authors. Published by Elsevier Masson SAS on behalf of Institut Pasteur. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
indicative of a poorly classified and highly polymorphic taxon requiring further revision[2,4e10].
Genomic variability within At. ferrooxidans has been firmly established using ribotyping methods and multi locus sequence typing (MLST) [11]. The high degree of phyloge-netic diversity has warranted recent reclassification of known strains and definition of two novel species of iron oxidizers, Acidithiobacillus ferrivorans[12]and Acidithiobacillus ferri-durans [13]. Conversely, information on the diversity of obligatory sulfur-oxidizing members of the genus, including the moderately thermophilic acidophile At. caldus, is scarce. At. caldus is ubiquitous in bioleaching operations and plays a relevant role in both stirred tanks and heap bioleaching con-sortia[14].
At. caldus ATCC 51756 (type strain) belongs to a distinct Restriction Fragment Length Polymorphism (RLFP) group[7] and clusters inside a well defined global DNA homology group when compared to all other currently recognized Acid-ithiobaillus species using DNAeDNA hybridization [9,15]. Sequencing and analysis of the 16S rRNA gene has shown a low degree of variation among strains and has been taken as evidence that At. caldus constitutes a homogeneuos phyloge-netic taxon [6]. However, assessment of phenotypical and metabolic properties of several At. caldus strains indicates the existence of as yet undefined levels of variation within the species[16e19]. Recent whole genome comparison of the two fully sequenced strains of At. caldus (ATCC 51756 and SM-1) further support this argument [20e22]. Despite being 100% identical at the 16S rRNA gene level and having an average nucleotide identity (ANI) of 97.9%, these two strains differ in about 20% of their respective genomes[22]. Altogether, these inconsistencies call for revision of the taxon using more robust and resolutive approaches of phylogenetic analysis.
Genetic multi locus studies using homologous genomic regions from multiple individuals to infer gene genealogies and phylogenetic trees haven proven to be valuable alterna-tives to whole genome comparisons [23,24]. Genetic loci being profiled need to be stable, widely distributed among genomes, present in single copy and need to have high in-formation content. Thus, single copy non-recombining genes containing a series of single nucleotide polymorphisms (SNPs) are likely to be good indicators of population diversity. Bac-terial housekeeping genes (HKGs) meet all these criteria and are frequently used in strain typing, taxonomy assignment and phylogenetic analysis [25,26]. However, selecting the most suitable HKG for MLST is a cumbersome job requiring iter-ative cycles of design and validation[27].
In this work, we describe a bioinformatic and experimental pipeline that facilitates the identification and validation of the most suitable HKG marker genes for MLST profiling of strains of At. caldus. The MLST scheme developed is used to evaluate intra-specific genetic heterogeneity and phylogenetic relationships among industrial isolates of At. caldus. In addi-tion, this marker selection pipeline can be widely applied to any microbial group or species of interest to facilitate infor-mative MLST marker selection and primer design. We will soon make the pipeline available to the community through a
dedicated web server. For the moment, consultations may be done via e-mail to the authors.
2. Methods
2.1. Bacterial strains
Thirteen At. caldus strains from diverse geographical ori-gins and industrial settings were used in this study (Table 1). The tetrathionate medium was prepared from a mineral salts solution containing the following (grams per liter): (NH4)2SO4, 3.0; KCl, 0.1; K2HPO4, 0.5; MgSO47H2O, 0.5;
Ca(NO3)2. 4H2O, 0.014; Na2SO4, 1.45. The pH was adjusted
to 2.5 with H2SO4, and the mixture was autoclaved. The trace
element solution used contained the following (milligrams per liter): ZnSO4, $ 7H2O, 10.0; CuSO4 $ 5H2O, 1.0; MnSO4$
4H2O, 1.0; CoCl2 $ 6H2O, 0.5; Cr2(SO4)3, 15H2O, 0.5;
Na2B4O710H2O, 0.5; NaMoO42H2O, 0.5. After autoclaving,
1 ml of the solution was added per liter of medium. Filter-sterilized K2S4O6 was added to a final concentration of
10 mM, and the pH was adjusted to 2.5 with H2SO4. At. caldus
was grown at 37C with constant shaking. 2.2. DNA preparation, PCR amplification and sequencing
Genomic DNA was extracted by the phenol-chloroform method, as described previously [28]. Primers for the target genes were designed from the available sequence data of At. caldus strains ATCC 51756 (GenBank accession # CP005986) and SM-1 (GenBank accession # CP002573). Target genes and primers are listed inTable S1.
Amplification reactions were performed in a total volume of 50ml containing 100 ng of DNA, 0.5 ml of Herculase II Fusion DNA Polymerase (Agilent), 10ml of 5 Herculase II reaction buffer, 0.5ml of dNTP mixture (2.5 mM each) and 1.25 ml of 10 mm primers. The genes were amplified in a Maxygen Gradient Thermocycler (Axygen) using the following parameters: 95C for 2 min, followed by 30 cycles of 95C for 20 s, 60C for 20 s and 72C for 1 min, with a final extension period at 72 C for 3 min. Amplified DNAs
Table 1
Acidithiobacillus caldus strains used in this study.
Strain Geographical origin Reference KU Kingsbury, UK [15,42]
ATCC 51756 Kingsbury, UK [15,42]
DSMZ8485 Kingsbury, UK [15,42]
BC13 Warwickshire, U.K [15,42]
MEL1 Antofagasta, Chile This work MEL2 Antofagasta, Chile This work CBAR-5 Antofagasta, Chile This work LB1 Santiago, Chile This work MNG Cape Town, RSA [39]
#6 Barberton, RSA [39]
F RSA [39]
CSH-12 Brisbane, Australia [43]
were visualized on 1.5% agarose gels after electrophoresis at a 100 V in TAE buffer for approximately 40 min, using SYBR® Green I nucleic acid gel stain (Invitrogen) and UV illumina-tion. PCR products were purified using a QIAquick PCR Pu-rification Kit (Qiagen). DNA sequencing of purified PCR products was carried out at Macrogen Inc., Korea. To mini-mize the sequencing artifacts by PCR, amplicons were sequenced using forward and reverse primers.
2.3. MLST and phylogenetic data analysis
MLST was performed as described by Maiden et al.[29]. PCR amplicons obtained were sequenced and analyzed. DNA sequences were aligned with the CLUSTALW2 tool [30] available at the European Bioinformatics Institute (http://www.ebi.ac.uk/Tools/msa/clustalw2/). Based on the alignments and the chromatograms the sequences were inspected and manually curated, when appropriate. Phylo-genetic trees were constructed using Neighbor-joining (NJ), Maximum-likelihood (ML) and Maximum-parsimony (MP) analysis. Bootstrap resampling were performed using 1000 replications for NJ, ML and MP to estimate the confidence of tree topologies. Optimal models of nucleotide substitution, DNA polymorphism data, the mean Gþ C content, Tajimas D and dN/dS ratios value were calculated using MEGA 5 [31].
3. Results
3.1. Comparative genomics-based MLST marker selection pipeline implementation
To facilitate and improve the MLST marker selection process, a bioinformatic pipeline was implemented that iden-tifies single copy HKG genes and automatically profiles the number of SNPs and conserved regions for primer design (Fig. 1). First, any given pair of closely related micro-organsims (ideally strains of the same species) was selected from public databases or local repositories for sequence comparison. Their full protein complements were retrieved in FASTA format and used as entry files for the pipeline. Next, both datasets were cross-compared using a bidirectional BLASTp implemented in Bioperl with an E-value cutoff of 104, as proof of robust sequence similarity. Conserved and genome-specific gene products were identified and pooled in different datasets. Conserved gene products were further evaluated to assess their occurrence in each dataset in single or multiple copies. For this purpose intragenomic comparisons were carried out using BLASTp with a more stringent E-value cutoff of 1010. All proteins that had one or more hits within this dataset sharing at least 90% identity and more than 80% coverage were removed and only presumably single copy genes were further evaluated. These were classified in cate-gories based on their amino acid identity levels as assessed by BLASTp in order to identify informative gene markers among the conserved genes. Next, a biopython script profiled the number of SNPs for each selected pair of conserved single
copy genes sequences using a flexible sliding window ranging in size from 250 to 650 bp and established the putative forward and reverse PCR primer amplification target sites on each marker setting a restriction for sequence variability to the first and last 20 bp. Only windows with 10 or more SNPs were retained for further analysis. To increase the likelihood of selecting informative and non-recombining genes, predicted proteins were classified from a functional perspective using COG categories and candidate HKGs were pinpointed. The final output of the pipeline was a list of candidate markers ranked by information content and linked with predicted amplicon sizes and primer sequences which the end user has to curate and evaluate.
3.2. Development of an MLST scheme for At. caldus
Using the above pipeline At. caldus type strain ATCC 51756 and At. caldus SM-1 were cross-compared and candi-date MLST markers pinpointed (Fig. 2). Using an E value of 104as cutoff, a total of 2307 conserved genes were selected among which 2259 were single copy and 2174 were more than 95% identical at the amino acid level. Within this group a total of 178 conserved genes with more than 10 SNPs were iden-tified. Seventeen HKG that met the amplicon size re-quirements of the pipeline were selected for experimental validation and further nucleotide sequence diversity analysis. Size requirement was set below 650 bp to warrant full sequencing of the amplicons in a single sequencing reaction and to allow full overlap of the forward and reverse sequences for proofreading purposes.
3.3. MLST-based profiling of At. caldus strains
In order to test the MLST marker selection scheme and identify the best performing markers for At. caldus 13 strains were profiled, including the type strain ATCC 51756, the SM-1 strain (sequence only) and several industrial isolates of diverse geographical origins (Table 1). Internal gene se-quences of the 17 candidate markers were amplified from genomic DNA obtained from the At. caldus strains by PCR using a high fidelity polymerase. Amplicons were sequenced and analyzed bioinformatically. The 16S rRNA gene was included for comparison.
All 18 primer pairs (targeting the 17 MLST marker genes and the 16S rRNA genes) produced positive amplicons in the expected size range in all evaluated strains. Details on the information content for the discriminant markers derived from sequence analyses, is summarized in Table 2. Markers were ranked on the basis of the number of variable sites in decreasing order and strains based on geographic origin. Comparison of the full set of sequences showed that 3 of the candidate markers (dnaE, atpD and alaS ) had fewer infor-mative sites than suggested by the pairwise comparison of the At. caldus type strain and the SM-1 strain.
Seven markers were retained for further phylogenetic analysis (Table 2). Among the selected markers, the GTP-binding protein coding gene era and a serine protease
encoding gene htrA have been used in MSLT schemes in other model bacteria [32,33]. Compared to the 16S rRNA marker, which has a high gene similarity value (99.7%), all other markers retained were significantly more variable (2.6%e
9.7% variation). Parsimony informative sites of the selected markers, that are positions in the sequence set under com-parison that contain at least two types of nucleotides in at least two different sequences, varied form a maximum of 34 ( pilC )
Fig. 1. Rational behind the bioinformatic pipeline designed to select highly informative MLST marker genes. Filters used in eah step are indicated in the left margin of the figure. A) A pair of closely related microorgansims is selected from public databases or local repositories for sequence comparison (Genome 1 and 2); B) Both datasets are cross-compared using a bidirectional BLASTp and conserved genes are identified; C) Conserved genes are filtered by copy number and single copy genes are retained; D) Genes are further categorized by amino acid identity levels; E) Remaining markers are profiled for SNP content and F) classified by COG categories to extract housekeeping genes. Housekeeping genes containing more than 10 SNPs are retrieved and validated experimentally.
Fig. 2. Selected MLST markers for At. caldus strain identification and classification. A) Whole-genome comparison of At. caldus ATCC 51756 (Aca1) and At. caldus SM-2 (Aca2) represented using ACT[44]. Conserved open reading frames between Aca1 and Aca2, representing the core genome, are linked by gray bars across genomes. The relative position of the selected MLST markers and their location with respect to core genome of each strain are indicated in the corre-sponding genomic map as numbered lines (1e7). B) Selected gene names, percent identity between Aca1 and Aca2 and their respective amplicon sizes are displayed in the order defined in A (1e7). The two identical copies of the 16S rRNA gene are prepresented only once in the gene scheme.
to a minimum of 11 (era). The alr, pilC and lnT were the most informative gene sequences in the set.
The SNPs distribution observed when using this set of markers is only partially congruent with biogeographical structure suggesting that geographical isolation underlies dif-ferentiation between certain strain groups (Table 3). European
strains (KU, BC-13) and derivatives (ATCC 51756, DSM8584) share an almost identical SNPs pattern. This is consistent with isolation and culturing history of this group of strains and supports low levels of variation occurring over short times scales. Isolates from South Africa, although not identical regarding their SNPs distribution, have a high degree of similarity. In turn, strains isolated from Chile exhibit a mixed pattern that can be placed somewhere between the Chinese strain SM-1 and the European type strain.
Sequenced gene amplicons were further analyzed and Tajimas D value calculated to seek evidence for selection (Table 2). Tajimas D value reflects when a DNA sequence is evolving under selection and deviating from the random populational frequencies of neutral mutations. Large negative Tajima's D values indicate that purifying selection is in oper-ation, while significant positive values suggest that populations are experiencing diversifying selection [34]. Half of the markers displayed positive values, indicating either a decrease in population size and/or balancing selection acting on those genes. The other half displayed negative values, implying either population size expansion and/or purifying selection on those genes. However, because of lack of statistical signifi-cance for this test, neutral selection fits better the observed patterns of variability. Synonymous versus non-synonymous nucleotide polymorphism patterns were also analyzed (Table 2). By comparing the number of synonymous changes per synonymous site (dS ), which are presumed neutral, to the number of non-synonymous changes per non-synonymous site (dN ), which possibly experience selection, selection pressures at the sequence level may be assessed. If natural selection promotes changes in the protein sequence, the ratio dN/dS is expected to be> 1 [35]. For the At. caldus strain population under study, all dN/dS values were<1, indicating that most of the sequence variability identified can be explained by pur-ifying (stabilizing) selection.
3.4. At. caldus population structure analysis using MLST To investigate relatedness between At. caldus strains and gain deeper insight into the genetic structure of the species Neighbor-joining, Maximum-likelihood and Maximum-parsimony based phylogenetic trees were constructed. Trees were built using individual genes and contrasted to a sequence concatenate of the seven markers. The concatenate comprised 3229 nucleotides and consisted of 3026 invariable sites and 132 variable sites, 128 of which were parsimony-informative sites. Topology of the concatenate (Fig. 3) was congruent with topology of single gene trees generated with most informative markers, suggesting that none of these was object of active gene flow (Fig. S1).
Sequence types (STs) were identified from the sequence alignment of the concatenate and At. caldus strains relation-ships resolved. For this purpose, variations in each marker gene sequence (allele) were assessed and combined to generate the profiles of the strains under analysis (Table 3). Overall, strain profiling using concatenated sequences resulted in 8 different STs. Seven STs were represented by a single
Fig. 3. Maximum-likelihood tree inferred from the concatenate of the seven selected MLST markers. The pilC, gdp, alr, lnt, htrA, dhal and era gene se-quences (3229 bp) from 13 At. caldus strains were concatenated and analyzed using MEGA 5. Numbers at nodes indicate the percentage bootstrap values of 1000 replicates. The bar represents expected nucleotide substitutions per site.
Table 2
Sequence analysis of the MLST selected markers and the 16S rRNA gene. Marker Length Gþ Ca IS %b Vc Pd Se Df ug rrs 636 56.4 99.7 2 0 2 1.40 ND pilCi 472 54.9 90.3 46 34 12 1.24 0.07 gdpi 461 61.7 90.9 43 14 29 1.63 0.12 alri 472 67.1 91.5 40 35 5 0.52 0.31 top3 558 62.8 94.6 30 22 8 0.53 0.04 lnti 456 60.6 93.6 27 26 1 0.61 0.04 mutL 493 64.3 95.3 23 23 0 2.70 0.21 gpi 553 63.8 96.2 21 13 8 0.76 0.07 lepA 459 63.7 95.6 20 19 1 2.17 0.04 cpaB 528 65.7 96.4 19 0 19 2.03 0.41 htrAi 459 61.0 96.1 18 18 0 2.84h 0 gfpT 507 62.9 96.6 17 17 0 0.02 0.08 top1 593 64.1 97.3 16 0 16 2.08 0.11 dhaLi 444 64.5 96.4 16 16 0 1.94 0.10 erai 465 67.6 97.4 12 11 1 0.54 0.03 dnaEj 552 67.5 98.4 9 0 9 1.90 0.11 atpDj 513 61.8 99.0 5 1 4 1.29 0.06 alaSj 497 63.3 99.6 2 0 2 1.45 0.36 a Percentage of GC content.
b Percentage of identical site. c Number of variable sites. d
Number of parsimonious-informative sites.
e
Number of singleton sites.
f
Tajimas D Test value.
g
dN/dS, ratio of the number of nonsynonymous substitutions per non-synonymous site. h Statistically significant, p< 0.01. i Selected MLST markers. j
isolate (ST-2 to ST-8), while the ST-1 included 6 isolates. ST-1 was the most frequent STs, grouping isolates from Europe and Chile. South African isolates, despite belonging to different STs, showed considerable sequence similarity. Remarkably, all ST1 strains were obtained from coal/copper leaching heaps with relatively long mineral residence times. Subtle genomic differences between ST-1 strains and other sequence type strains may explain this preference. In turn, strains isolated from reactors and oxidation tanks proved to be genetically more divergent from one another, regardless of their geographical origin. It is hypothesized that this difference could result from the higher duplication rates and therefore the possibly higher rates of mutation associated with shorter mineral residence times and more favorable growth conditions imposed by tanks and reactors versus heaps and dumps. Support for these correlations awaits future investigations. 4. Discussion
Even if a range of molecular typing techniques have been used as a surrogate measure of the genetic similarity between Acidihiobacillus spp. strains to help clarify the taxonomy of this group, studies have been heavily biased towards the At. ferrooxidans species complex [5e7,9,11,36e38]. This asser-tion can be extended to MLST based approaches that have recently helped to uncover at least two new species of iron oxidizers, albeit using different markers [11e13].
In this study, we describe the design and implementation of a MLST scheme for At. caldus, representing the first MLST-based molecular typing study applied to industrial isolates of the species. Seven informative and discriminant MLST markers were selected using a sequence-driven approach and a custom-designed bioinformatic pipeline. The scheme is based on the allelic profile variation of seven protein-encoding housekeeping genes pilC, lnt, alt, dhaL, era, htrA and gdp and was applied to a collection of 13 At. caldus strains from diverse geographical origins and ore mining industrial settings. All seven markers proved suitable to investigate genetic di-versity of this biotechnologically relevant bacterial species.
The dN/dS ratios for the seven loci were all less than 1, which is consistent with most of the variations being selectively neutral. Such is the case for most HKGs that are subject to purifying selection and slow evolution[39,40].
Nucleotide sequence variation in the strain population was analyzed and 8 different allelic profiles or STs were distin-guished. These STs group together strains that are known to share certain genotypic and/or phenotypic traits, such as patterns of occurrence of specific mobile genetic elements[22], sero-types[40]and/or trans-alternating field electrophoresis migra-tion profiles[41]. The percentage of polymorphic sites of the selected genes ranged between 2.6% and 9.7%, indicating only moderate amounts of genetic diversity within At. caldus. Such levels of variation are lower than those reported between At. ferrooxidans and At. ferrivorans, and are in agreement with the current assignment of this set of strains to a single species.
Despite this fact, our study provides relevant information on the prevalence of certain STs and their geographical/industrial distribution. Almost invariably, ST-1 was found to occur in heap leaching industrial settings. However, due to the modest number of At. caldus isolates in public repositories and available private collections, further work is required to evaluate whether this association holds up when additional strains of At. caldus become available. Strong differences in the residence time of the mineral, temperature variations, exposure to toxic metals and several other operational parameters between tank and heap leaching could indeed explain the observed patterns of genetic variation. Further work in this direction is underway, that will help understand aspects of the microbial dynamics and genomic divergence in different industrial settings. Overall, these results are in agreement with previous reports indicating that leaching heaps, dumps, oxidations tanks and bioreactors create condi-tions that favor different mineral-oxidizing microflora and different dynamics of species evolution.
It is conceivable that the MLST scheme presented herein may be applied, with monitoring purposes, in the biomining industry to follow changes in diversity and relative abundance of the At. caldus populations in continuous feed stirred tanks, irrigated bioleaching dumps and/or heaps.
Table 3
Allele profiles and sequence types of At. caldus strains.
Strain Origin Ore Setting STa Allele profiles
htrA era pilC dhaL alr gdp lnT
KU UK Coal Heap 1 A C F J M Q V
ATCC 51756 UK Coal Heap 1 A C F J M Q V
DSMZ8485 UK Coal Heap 1 A C F J M Q V
BC-13 UK Coal Heap 1 A C F J M Q V
MEL1 Chile Copper Heap 1 A C F J M Q V
MEL2 Chile Copper Heap 1 A C F J M Q V
CBAR5 Chile Copper Heap 2 B D G K N R W
#6 RSA Gold Tank 4 B D H L ~N Q X
MNG RSA Gold Tank 3 B C H L ~N Q X
F RSA Nickel Tank 5 B C H L ~N S X
CSH-12 Australia Gold Bioreactor 6 B E F J O T Z
SM-1 China Gold Bioreactor 7 B C I K P U W
LB1 Chile Copper Dump 8 A C H LL M S Y
Conflict of interest
The authors declare no conflict of interests. Acknowledgments
We thank Dr. C. Demergasso (Universidad Catolica del Norte, Antofagasta, Chile) and Dr. D. Rawlings (University of Stellenbosch, Matieland. South Africa) who kindly provided several of the At. caldus strains used in this study.
This work was supported by the Fondo Nacional de Desarrollo Cientıífico y Tecnologico FONDECYT (http://
www.conicyt.cl/fondecyt/) [grant numbers 3130376,
1140048, 1130683], and the Programa de Financiamiento Basal de la Comision Nacional de Investigacion Científica y Tecnologica CONICYT (http://www.conicyt.cl/pia/category/ lineas-del-programa/creacion-consolidacion-centros/[grant number PFB16]. J.P.C. is the recipient of a graduate studies fellowship from CONICYT.
Appendix A. Supplementary data
Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.resmic.2014.07.014.
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