Exploration of bacterial strains with bioremediation potential for mercury and cyanide from mine tailings in "San Carlos de las Minas, Ecuador"

1.   Introduction

As a developing country, Ecuador views metallic mining as a significant economic activity that contributes to job creation and tax revenue ^[1]. Despite its benefits, concerns arise regarding the environmental damage caused by this expansion. Water resources, soil, and air are the most affected, along with riverbank deforestation and displacement of indigenous communities ^[2]. Governmental institutions regulate this activity, mandating the creation of mine tailings for waste disposal. However, there needs to be more consistent monitoring to ensure compliance with environmental regulations. Artisanal or illegal mining exacerbates the problem, discharging sediments directly into nearby water bodies and impacting ecosystems and downstream communities ^[3].

The significant accumulation of sediments in mine tailings, laden with contaminants such as mercury (Hg), cyanide (CN^-), and other heavy metals, constitutes one of the environmental focal points responsible for a significant decline in soil biological activities ^[4]. Gold (Au) tailings contain large quantities of toxic substances such as Hg and CN^- used in mining operations. Hg is employed in the Au extraction process because pure Au and volatile Hg can be obtained by heating an Au-Hg alloy ^[5], and it is known that Hg is a hazardous and persistent environmental contaminant causing clinical conditions in humans ^[6,7]. Hg in an organism is not essential and does not play a vital role in biological processes. Although traces of heavy metals are naturally observed in soils, their excessive accumulation can deteriorate soil quality and damage surface plants ^[8]. Furthermore, the absorption of heavy metals by humans, animals, and plants negatively affects biological chains, leading to ecological safety issues ^[9]. Cyanide is also used in leaching techniques for Au extraction, posing a potential contaminant affecting plants, agricultural areas, and groundwater, representing a risk to human and animal health ^[10,11,12].

On the other hand, these sites represent a high scientific interest due to the complex microbial diversity they harbor. They consist of microorganisms that exhibit metal resistance developed through the moderate evolution of their genetic material, being considered beneficial due to their potential for natural bioremediation ^[13]. Bioremediation has shown outstanding results in removing various organic contaminants and heavy metals ^[14]. Compared with traditional physical and chemical methods, microbial remediation offers a practical and environmentally friendly approach, featuring advantages such as high efficiency, low cost, and being eco-friendly ^[15]. The importance of this research arises from the complexity of studying microorganisms inhabiting contaminated environments due to the need for adequate media and methodology ^[16]. There are reports of microorganisms found in mine tailings with metabolic capacities to reduce, eliminate, or transform contaminants' concentrations and chemical nature in the sediments ^[17]. For example, strains such as Escherichia coli, Proteus sp., Saccharomyces sp., and Desulfobacter sp. have been reported in soils contaminated with Hg ^[18,19,20]. There are reports of alkalophilic bacteria belonging to the genera Bacillus sp. and Pseudomonas sp., which biodegrade free cyanide and thiocyanate ^[21,22]. However, more information on tailings in the Zamora Chinchipe province of Ecuador must be provided. Therefore, this study reveals valuable information about interesting bacterial microorganisms with high potential for the bioremediation of Hg and CN^-. It also reveals bacterial species that have not been reported in other articles for use in bioremediation purposes.

2.   Materials and methods

2.1.   Sampling site

The soil sampling was carried out in duplicate in September 2022 at the main mine tailings of the private company "Mincampa Minera Campanillas S.A", located in the Amazon region, in the San Carlos de las Minas parish (Zamora Chinchipe, Ecuador) (Latitude: 4°3'28.55"S; Longitude: 78°47'15.55"W) at an altitude between 1705–1720 meters above sea level. A systematic grid sampling approach followed, considering that the tailings had an area of 1000 m². The number of samples with statistical significance was calculated, resulting in a total of 68-point sub-samples. Each sub-sample was taken at a depth of 10 cm using a sterile spatula. Subsequently, the sub-samples were homogenized to form a composite sample of 1 kg, which was stored in polyethylene bags and transported to the laboratory in a cooler at 4 ℃ for subsequent analysis ^[23].

2.2.   Soil characterization

The physicochemical characterization of the soil was carried out at the soil laboratory of the Polytechnic School of Chimborazo in Ecuador. In accordance with Book VI Annex 2 of the Ecuadorian Environmental Technical Standard ^[24], five parameters described in Annex 2 were considered: "Parameters for assessing the initial quality of soil according to its use, mining land use component". The parameters considered were pH, electrical conductivity, moisture content, Hg, and CN^-. pH and electrical conductivity were determined in triplicate by dilution in an aqueous medium and by direct measurement using a Jenway 3510 pH meter and COND 51+ conductivity meter based on Environmental Protection Agency (EPA) 9045D ^[25] and EPA 9050 ^[26] standards, respectively.

For CN^- determination, the process began with solid-to-liquid extraction through basic digestion with 50% sodium hydroxide following EPA method 9013A ^[23]. This was followed by analysis using the Pyridine-Pyrazolone colorimetric method (range 0.002–0.240 mg/L CN) based on the American Public Health Association (APHA) method 4500-CN-E using Hach equipment and reagents ^[27].

The Hg concentration was measured using solid-to-liquid extraction through acid digestion with 65% nitric acid and 50% hydrogen peroxide, followed by determination via atomic absorption spectrophotometry using hydride generation and cold vapor techniques based on EPA method 7471 ^[28].

2.3.   Isolation and purification of bacterial strains

From the composite soil sample, serial dilutions were prepared on a 10-fold basis ranging from 10^-1 to 10^-10. Each dilution was spread onto nutrient agar Petri dishes, and those dishes containing a viable colony count, ranging from 30 to 300, were selected for the isolation and subsequent purification of strains. For strain isolation, colonies showing morphological differences were selected and streaked onto nutrient agar Petri dishes using the streaking procedure and then incubated for 48 hours at 37 ℃. Subsequently, subculturing was performed until pure cultures were obtained.

2.4.   Characterization of bacterial strains

Once the strains were isolated, morphological characterization of the colonies was performed through macroscopic observation, determining the color and shape characteristics of the bacterial colonies. Gram staining is a differential method used to distinguish bacteria based on their cell wall composition and to observe their shape more accurately. To perform the staining, first, a smear is prepared from a pure culture sample to be analyzed, followed by fixing the sample using heat. The staining process involves several steps. First, crystal violet is applied for one minute, and Lugol is added to fix the stain. Next, the decolorizer is added, and finally, the sample is stained with safranin for one minute. Subsequently, the sample is observed under the microscope. According to the staining principle, bacteria that appear pink are Gram-negative due to their higher lipid content in the cell wall. Conversely, bacteria that retain the purple color are Gram-positive, characterized by a higher content of peptidoglycans in their cell wall ^[29].

Each colony was inoculated by stabbing into test tubes containing 3 mL of SIM medium for motility tests. SIM medium is a multitest medium used to evaluate bacterial motility. Positive motility results are indicated by a cloudy area extending away from the inoculation line, while a negative test is characterized by growth only along the inoculation line and no further ^[30].

Eight bacterial strains were selected for molecular characterization, labeled numerically from 1 to 8. The process began with DNA extraction, followed by evaluation of its quality and integrity through microvolume spectrophotometry and visualization on agarose gel. PCR amplification of the 16S and rpoB fragments was performed using the rpoB primers: rpoB-F/rpoB-R (5'-ATC GAA ACG CCT GAA GGT CCA AAC AT-3'/ 5'-ACA CCC TTG TTA CCG TGA CGA CC-3') ^[31] for sample 3; and for the other samples, universal 16s primers were used: 27F/1492R (5'-AGAGTTTGATCCTGGCTCAG-3'/5'-GGTTACCTTGTTACGACTT-3') ^[32]. Once the DNA fragments were amplified, sequencing was performed using Sanger and high throughput methods, followed by assembly using bioinformatics tools. For species identification, DNA sequences were entered into the NCBI Blast platform, and the taxonomy of each strain was determined based on the percentage similarity with the existing database.

2.5.   Degradability tests of CN^- and Hg

Once the strains were identified at the molecular level, they were subjected to CN^- and Hg degradability tests. These tests were conducted in test tubes containing 10 mL of nutrient broth enriched with sodium cyanide and mercury chloride, respectively. The tests were performed in triplicate at three different concentrations, as shown in Table 1.

Table 1.  Contaminant concentration values for degradability tests.

Contaminant	C1	C2	C3
Cyanide (NaCN)	6.83 mg/L	8.04 mg/L	9.47 mg/L
Mercury (HgCl2)	10 mg/L	88 mg/L	100 mg/L

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According to the soil analysis conducted at the mining tailings site, no CN^- contamination was reported. Therefore, to determine the concentrations for the CN^- degradability tests, the permissible limit established in the Remediation Criteria (maximum permissible values) of Annex 2 of Book VI of the Unified Text of Secondary Legislation of the Ministry Environment of Ecuador for commercial and industrial soil, which is 8.0 mg/kg, was considered ^[24]. From this value, the concentration was increased by 15% and decreased by 15% to obtain the three concentrations mentioned earlier.

In the initial soil analysis, a high Hg concentration was found, indicating a significant level of contamination that must be considered. Therefore, to establish the concentrations of Hg to be used for the degradability tests, a minimum concentration corresponding to the permissible limit established in the Remediation Criteria (maximum permissible values) of Annex 2 of Book VI of the Unified Text of Secondary Legislation of the Ministry Environment of Ecuador for commercial and industrial use, which is 10.0 mg/kg, was used ^[24]. The second concentration used was based on the mean of the values obtained in the initial physicochemical analysis of the samples, which was 87.575 mg/kg. The maximum concentration corresponds to the value increased by 15% of the annex's permissible limit of 100.7 mg/kg. The bacterial strains were then inoculated into each tube along with the previously established concentrations of CN^- and Hg. The tubes were incubated for five days at 37 ℃, and the Hg and CN^- concentrations were measured at the end of the experiment using the same protocol described in the soil characterization section, Section 2.2. Additionally, the achieved cell density was measured using spectrophotometry with an absorbance of 600 nm. The absorbance of the McFarland standards was then measured to obtain the calibration curve and the mathematical expression correlating absorbance with the number of cells to determine the value of CFU/mL.

2.6.   Statistical analysis

The experimental analysis considered the degradation percentage of two contaminants (dependent variable) by eight bacteria isolated from mining tailings soil (independent variable) to assess the ability of each type of bacteria to degrade CN^- and Hg and compare their efficacy. A statistical summary was performed with the obtained data to test for significant differences among the means of the three applied contaminant concentrations. A multiple-range test was conducted to determine if degradation rates are statistically different using STATGRAPHICS 19.0 software.

3.   Results and discussion

3.1.   Soil characterization

According to the soil characterization in Table 2, an average pH value of 6.14 was obtained, classified as slightly acidic, consistent with the findings of Gürtekin and Aydar ^[33], which indicate that mine tailings are moderately acidic due to acid drainage caused by the metamorphism and leaching of sulfide-rich minerals, such as reactive pyrite mineral. These values are a consequence of the atmospheric oxidation of exposed pyrite minerals in the tailings deposit, producing sulfuric acid (mine acid drainage) ^[34,35]. On the other hand, it is expected to find electrical conductivity (EC) values greater than 1500 µS/cm in tailings soils sampled at depths shallower than 60 cm ^[34,36]. The increase in EC and acidic pH indicate oxidative activity due to the higher presence of oxygen on the surface, microbial activity, and constant water contact ^[34,37]. It is important to note that, until the development of the present study, a detailed analysis of soil characterization in the parish of Zamora Chinchipe, Ecuador, has not been published, making it difficult to compare the pH and conductivity values observed in Table 2.

Table 2.  pH and electrical conductivity values of soil samples from the mining tailings.

Sample	pH	Electrical conductivity, EC (µS/cm)
1	6.23 ± 0.101	1788.51 ± 15.15
2	6.04 ± 0.138	2159.08 ± 4.724
Mean	6.14	1973.80

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Hg contamination in artisanal and small-scale gold mining (ASGM) communities is widespread globally. In the process of extracting residual gold after amalgamation, it is often reprocessed with CN^{- [38]}. For this reason, it was essential to determine the CN^- concentration in the mining tailings soil. The CN^- concentration obtained was 8.0 mg/kg, as shown in Table 3, which is below the permissible limits set by Ecuadorian legislation. However, the detected concentration possibly results from the geological characteristics of the sediment, as leachate waste contains CN^- residues that undergo various changes such as atmospheric dispersion, chemical transformation into other carbon and nitrogen species, and retention in solid form as cyanometallic precipitates or adsorbed species with metals such as cyanate (CNO⁻) and thiocyanate (SCN⁻) ^[21,39]. Even Hg reacts with CN^- under aerobic conditions to produce Hg(CN)₄^2- and other complexes ^[38].

Table 3.  Physicochemical parameters for initial soil quality analysis.

Sample	Cyanide (CN-) (mg/kg)	Mercury (Hg) (mg/kg)
1	0.14	75.7
2	0.14	99.45
Mean	0.14	88.75
Permissible limit value *	8.0	10.0
*Note: Annex 2: Remediation Criteria for Contaminated Soils, from the Environmental Quality Standard for Soil Resources and Remediation Criteria for Contaminated Soils in Ecuador.

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These analyses are consistent with the study by Zhang et al., which mentions that gold mine tailings have caused severe contamination by heavy metals in soil and water, emphasizing the importance of studying soil quality and its potential impact ^[40]. However, in Ecuador, there have been no reports of studies on CN^- and Hg mining contamination in the San Carlos parish, but CN^- contamination has been studied in a river in the Portovelo-Zaruma area, with CN^- contamination found even 50 km away from the mines ^[41,42].

In small-scale hard rock gold mines, some of the particles forming the amalgam with Hg are recovered with gold, while others remain with Hg in the tailings, causing soil contamination ^[43]. The type of soil clay has impermeable properties where the surface layer retains water until saturated, causing Hg to concentrate and become trapped in the surface layer ^[44]. Therefore, we were interested in determining the Hg concentration in soil samples, resulting in an average of 88.75 mg/kg, which is lower compared to other soils considered contaminated by Hg, for example, where values of up to 383.21 mg/kg are recorded in Kulon Progo ^[45]. Studies in Ecuador are scarce, but in 2003, Ramírez et al. studied the Hg concentration in mining soils in Nambija and its surroundings (an area close to our study), showing Hg values of 0.6 to 0.8 mg/kg in soil samples from San Carlos, indicating a significant increase in contamination nine years later ^[46]. Additionally, this value is eight times higher than the permissible limit under Ecuadorian standards ^[24]. It deserves attention to seek alternatives to mitigate contamination, as indicated by Romero et al., regarding the importance of developing contamination mitigation strategies and preventing it from reaching crops and continuing to affect human health and the ecosystem in general ^[47].

3.2.   Isolation of bacterial strains

Several physicochemical methods have been employed to decontaminate and recover environments contaminated with heavy metals, such as adsorption, chemical precipitation, nanomaterials, and osmosis. However, their application is limited from both environmental and economic perspectives. For this reason, biotechnology has been explored to develop cost-effective and environmentally friendly processes, such as microbial cells ^[48] and biosurfactants. These biosurfactants possess a high affinity for heavy metals. Importantly, various microorganisms, including Pseudomonas sp., Bacillus subtilis, and Bacillus sp., have been isolated for this purpose, and their success in bioremediation is a testament to the effectiveness of these methods ^[49].

Once dilutions from 10^-1 to 10^-4 were prepared and plated on Petri dishes with nutrient agar, Petri dishes showing viable growth between 30 and 300 colonies were selected. These dishes underwent four cycles of isolation, restreaking, and purification. Ultimately, 15 bacterial strains were obtained, labeled, and morphologically characterized, as described in Table 4.

Table 4.  Macroscopic characterization of bacterial strains isolated from soil.

Label	Color	Shape	Edge	Elevation	Texture	Shine
3, –1, 1°, 1*	White	Irregular	Lobed	Flat	Rough	Dull
3, –1, 8°, 2	Yellow	Circular	Entire	Raised	Smooth	Shiny
3, –2, 3°, 1*	Yellow	Circular	Entire	Convex	Smooth	Shiny
3, –9, 1°, 1*	White	Irregular	Lobed	Flat	Rough	Dull
4, –1, 6°, 1, 1*	White	Irregular	Lobed	Flat	Smooth	Shiny
4, –1, 6°, 1, 2	Yellow	Circular	Entire	Raised	Smooth	Shiny
4, –1, 6°, 1, 3	White	Irregular	Irregular	Flat	Smooth	Dull
4, –1, 6°, 2, 1	Yellow	Circular	Entire	Raised	Smooth	Shiny
4, –1, 6°, 2, 2	Dark yellow	Circular	Entire	Raised	Smooth	Dull
4, –1, 6°, 2, 3*	Yellow	Circular	Entire	Raised	Smooth	Shiny
4, –1, 7°, 1, 1*	Dark yellow	Circular	Entire	Convex	Smooth	Dull
4, –2, 1°, 2, 1*	White	Filamentous	Filamentous	Flat	Rough	Dull
4, –2, 1°, 2, 2*	Yellow	Circular	Entire	Raised	Smooth	Shiny
4, –2, 4°, 1, 1	Yellow	Irregular	Rhizoid	Flat	Rough	Shiny
4, –4, 1°, 1, 1	White	Rhizoid	Rhizoid	Flat	Smooth	Shiny
*Note: Strains chosen for molecular-level identification.

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3.3.   Characterization of bacterial strains

Eight strains were selected based on their macroscopic characteristics and subjected to Gram staining and mobility tests. Five strains were identified as Gram-positive species, and three strains were identified as Gram-negative, as observed in Table 5. Regarding shape, both cocci and bacilli types were found. In the mobility tests, five strains yielded positive results, while three strains showed no mobility.

Table 5.  Gram staining and bacterial mobility tests.

Bacterial strain	Gram staining	Morphology	Mobility
E1	–	Bacilli	+
E2	–	Cocci	+
E3	+	Bacilli	+
E4	+	Bacilli	–
E5	+	Staphylococci	–
E6	+	Cocci	–
E7	+	Bacilli	+
E8	–	Coccobacilli	+
*Note: +: Gram positive; –: Gram negative; +: Positive mobility; –: Negative mobility.

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The DNA obtained from sample E1 was sent for high-throughput sequencing after amplicon library preparation, while the other DNA samples (E2 to E8) were sequenced using the Sanger method. Subsequently, molecular identification was performed by comparing the DNA sequences obtained with the GenBank nucleotide database from NCBI for bacterial identification, and the results are shown in Table 6.

Table 6.  Molecular identification.

Original code	Fragment length (bp)	% Fragment quality	Organism	Fragment	% Species identity	Accession Number
E1	1459	…	Pseudomonas chengduensis	16S	100	NR 125523.1
E2	168	89.8	Pseudomonas alcaliphila	16S	98.8	NR 114072.1
E3	1035	99.8	Bacillus subtilis	rpoB	100	CP053102.1
E4	147	94.6	Bacillus altitudinis	16S	99.32	MT569984.1
E5	762	100	Staphylococcus saprophyticus	16S	100	CP035294.1
E6	768	99.7	Micrococcus aloeverae	16S	100	NR 134088.1
E7	683	99.9	Bacillus subtilis	16S	99.71	OP986262.1
E8	749	99.7	Hydrogenophaga laconesensis	16S	99.6	NR 149183.1

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3.4.   CN^- and mercury Hg degradability tests

The McFarland scale standards were used; their absorbance at 600 nm was measured, and this variable was correlated with the number of cells measured in CFU/mL representing each standard. An equation was obtained to express this relationship. The equation is described as: $y = \mathrm{17,394}x-\mathrm{0,966}$; where y is the number of cells and x is the absorbance measured in each sample shown in Table 7.

Table 7.  McFarland scale.

McFarland Standard Number	Volume BaCl2 1% (mL)	Volume H2SO4 1% (mL)	Number of cells (1x108 CFU/mL)	Absorbance at 600nm
0.5	0.05	9.95	1.5	0.097
1	0.1	9.90	3	0.236
2	0.2	9.80	6	0.422
3	0.3	9.70	9	0.584
4	0.4	9.60	12	0.745
5	0.5	9.50	15	0.934
6	0.6	9.40	18	1.106
7	0.7	9.30	21	1.272
8	0.8	9.20	24	1.424
9	0.9	9.10	27	1.588
10	1.0	9.00	30	1.775

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In the cyanide medium, a maximum cell density of 2.41x10⁸ CFU/mL was recorded, reached by the species Hydrogenophaga laconesensis. Following this, Bacillus altitudinis and Pseudomonas alcaliphila exhibited average densities of 1.84x10⁸ CFU/mL and 1.65x10⁸ CFU/mL, respectively. For Micrococcus aloeverae and Staphylococcus saprophyticus, cell densities of up to 1.5x10⁸ CFU/mL and 1.37x10⁸ CFU/mL were reached, respectively. The species with the most minor cell development were Pseudomonas chengduensis and Bacillus subtilis, with averages of 1.06x10⁸ CFU/mL and 0.72x10⁸ CFU/mL, respectively. It is worth noting that the species E7 (Bacillus subtilis) achieved superior development, with 1.46x10⁸ CFU/mL, compared to E3 (Bacillus subtilis), despite being the same species. The averages reached by each species at their three concentrations are detailed in Table 8 below:

Table 8.  Cell density in the cyanide and mercury medium.

Bacterial strain	Concentration	Cyanide medium		Mercury medium
		Absorbance	Number of cells (1x108 CFU/mL)	Absorbance	Number of cells (1x108 CFU/mL)
E1	C1	0.062	0.954	0.181	2.182
	C2	0.065	1.010	0.162	1.846
	C3	0.079	1.216	0.188	2.304
E2	C1	0.100	1.552	0.259	3.533
	C2	0.133	2.057	0.180	2.159
	C3	0.087	1.340	0.153	1.689
E3	C1	0.044	0.675	0.073	1.124
	C2	0.044	0.680	0.079	1.227
	C3	0.051	0.794	0.080	1.232
E4	C1	0.122	1.881	0.128	1.255
	C2	0.103	1.588	0.162	1.858
	C3	0.133	2.052	0.157	1.771
E5	C1	0.096	1.485	0.070	1.077
	C2	0.091	1.402	0.130	1.289
	C3	0.079	1.216	0.116	1.046
E6	C1	0.072	1.108	0.190	2.345
	C2	0.101	1.557	0.203	2.571
	C3	0.119	1.835	0.142	1.504
E7	C1	0.107	1.655	0.104	0.837
	C2	0.083	1.278	0.115	1.034
	C3	0.093	1.443	0.100	0.779
E8	C1	0.136	2.108	0.140	1.475
	C2	0.154	2.387	0.161	1.834
	C3	0.146	2.253	0.187	2.281

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On the other hand, in the medium with Hg, bacterial strains exhibited higher cell growth, reaching maximum values of 3.53x10⁸ CFU/mL, with species such as Pseudomonas alcaliphila, Micrococcus aloeverae, and Hydrogenophaga laconesensis showing the highest cell densities. Species with lower growth were E3 and E7, corresponding to Bacillus subtilis and Staphylococcus saprophyticus, with cell densities between 0.78x10⁸ CFU/mL and 1.29x10⁸ CFU/mL. These obtained values may indicate more excellent resistance to Hg compared to cyanide CN^-. These results could be attributed to bacteria adapting to high Hg concentrations and naturally developing resistance even to higher contaminant levels. It is essential to mention that the bacterial genera, Bacillus and Pseudomonas, have been extensively reported in investigations to reduce other contaminants, such as Cr (VI). These studies have documented reductions from 80 to 30 mg/L, highlighting the significance of these genera in bioremediation processes of environments contaminated with heavy metals ^[50].

Despite the toxicity of CN^-, it is a compound that can be synthesized by various organisms, including bacteria, fungi, plants, or animals, employing cyanogenesis as a survival mechanism in contaminated environments ^[51]. Several organisms have developed metabolic pathways for CN^- degradation, transformation, assimilation, or tolerance and can even use it as the sole nitrogen source for growth ^[52]. Microorganisms utilize degradative pathways involving enzymes in hydrolytic, oxidative, reductive, and substitution-transfer reactions for CN^- degradation ^[22,53,54].

The CN^- degradability tests generally determined that bacterial strains achieved degradation percentages between 7.94% and 66.24%. It was noted that this percentage was lower at concentration C1, reaching a maximum value of 36.51%, and significantly increased for concentrations C2 and C3, with the latter registering the highest CN^- degradation values, as shown in Figure 1.

Figure 1.  Percentage of cyanide (CN^-) degradation for bacterial strains labeled from E1 to E8. Initial contaminant concentrations: C1 (6.83 mg/L), C2 (8.04 mg/L), C3 (9.47 mg/L). Bacterial species corresponding to the label: E1 (Pseudomonas chengduensis), E2 (Pseudomonas alcaliphila), E3 (Bacillus subtilis), E4 (Bacillus altitudinis), E5 (Staphylococcus saprophyticus), E6 (Micrococcus aloeverae), E7 (Bacillus subtilis), E8 (Hydrogenophaga laconesensis). Error bars indicate a standard deviation from the mean activities of triplicate assays.

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Some interesting results were also found due to the action of Micrococcus aloeverae, reaching the highest degradation value (66.24%). This bacterium has been reported in studies on wastewater treatment ^[55] and pesticide degradation ^[56] but not specifically in CN^- removal. The species Pseudomonas alcaliphila recorded a maximum degradation percentage of 64.76%. While this bacterium has been reported in processes such as biodegradation of Ni-citrate complexes, Ni (Nickel) recovery ^[57], and copper bioremediation ^[58], its activity against CN^- or Hg has not been reported. However, these activities suggest that Pseudomonas sp. may have the potential for cyanide or mercury degradation ^[22]. Finally, the species Bacillus subtilis reported a degradation percentage of 60.30%, which is consistent with previous findings ^[59]. These degradation percentages were achieved at the maximum concentration of C3, as shown in Figure 1.

When analyzing the degradability of CN^- at three different initial concentrations, we focused on the coefficient of variation shown in Table 9. The experiment showed that bacteria exposed to concentration C1 exhibited more significant variability in degradation data compared to concentrations C2 and C3, where the bacteria demonstrated more consistent degradation.

Table 9.  Summary statistics of cyanide (CN^-) degradation analysis.

	Count	Average	Coeff. of variation
C1 (mg/L)	8	19.742	51.387%
C2 (mg/L)	8	37.161	29.808%
C3 (mg/L)	8	52.415	21.741%
Total	24	36.439	47.063%

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A statistical, multiple-range test was conducted to determine if CN^- degradation rates differed statistically, analyzing each concentration separately. This method discriminated among the means using Fisher's least significant difference (LSD) procedure. With this method, there is a 5.0% risk of considering each pair of means as significantly different when the actual difference is equal to 0. According to the results from Table 10, CN^- degradation rates achieved for all bacterial strains used at the initial CN^- concentrations C1 (6.83 mg/L), C2 (8.04 mg/L), and C3 (9.47 mg/L) show no significant differences. This study indicates that bacteria degrade CN^- similarly, regardless of the initial concentration of the contaminant.

Table 10.  Multiple-range test. Method: 95.0 percent LSD for the cyanide (CN^-) contaminant.

	Count	Mean	Homogeneous Groups
C1 (mg/L)	8	1.427	A
C1 (mg/L)	8	1.427	A
C2 (mg/L)	8	1.494	A
C3 (mg/L)	8	1.518	A
Contrast	Sig.	Difference	+/– Limits
C1–C2		–0.067	0.512
C1–C3		–0.091	0.512
C1–C1		0	0.512
C2–C3		–0.023	0.512
C2–C1		0.067	0.512
C3–C1		0.091	0.512

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The preceding analysis corresponds to Figure 2, which depicts the range in which the maximum cyanide degradation data are concentrated. The data with the least variability are the values with the C3 concentration of the contaminant, which range between 34.39% and 66.2%; however, variability is observed for all three concentrations of the contaminant.

Figure 2.  Box plot of CN^- degradability by the eight bacterial strains concerning three different contaminant concentrations: C1 (6.83 mg/L), C2 (8.04 mg/L), C3 (9.47 mg/L).

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Studies conducted to date, where the potential of microorganisms for heavy metal degradation, in this case Hg, has been determined, have also allowed the establishment of the characteristics that confer this capacity. Like CN^-, enzymatic pathways that transform, reduce, and/or assimilate mercury have been identified. There is chromosomal level identification data on the genes encoding these functions. An important mechanism of microbial resistance to mercury is its reduction to elemental mercury (facilitated by the merA gene) ^[60,61]. Other studies establish mercury degradation pathways, primarily mediated by the regulation of the mer gene by merR in Gram-negatives and by merR2 in Gram-positives. These are transcription regulatory proteins of the mer operon, which have a high affinity for Hg²⁺, and the merA and merB genes are also mentioned ^{[61,62,63,64]}.

For degradability tests in the mercury medium, percentages greater than 85% were obtained for all species and concentrations evaluated. The species Hydrogenophaga laconesensis achieved the highest percentages, ranging from 99.44% to 99.80%, for all three concentrations. This species has been reported for potential use in oil bioremediation ^[65], but based on these findings, it can also be used in Hg removal. Additionally, Pseudomonas alcaliphila and Micrococcus aloeverae showed degradation rates of 98.97% and 98.78%, respectively. There are not many studies on Micrococcus aloeverae in the area of heavy metal bioremediation, but it is clear that it is a potential candidate for these processes as indicated by the study of Pandit et al. ^[66].

The three species showed similar degradation percentages across the three concentrations, while the remaining species did not exceed 89% at concentration C1. This result is likely due to lower cell densities at this concentration, resulting in decreased contaminant degradation due to the reduced number of cells present. On the other hand, for concentrations C2 and C3, percentages between 96.28% and 99.07% were achieved. Finally, the species with the lowest performance was strain E5, which degraded 66.91% of the Hg in the sample at its initial concentration but achieved good degradation values (96.72% and 96.41%) for concentrations C2 and C3. Figure 3 provides detailed descriptions of the degradation percentages in the mercury medium achieved by each species at their three test concentrations. These findings underscore the crucial component of the remediation process: Studying the microbial population in a contaminated environment. Advanced technical approaches are needed to understand the dynamic aspects of microbial activity and survival in a stressed environment ^[67].

Figure 3.  Percentage of mercury (Hg) degradation for bacterial strains labeled from E1 to E8. Initial contaminant concentrations: C1 (10 mg/L), C2 (88 mg/L), C3 (100 mg/L). Bacterial species corresponding to the label: E1 (Pseudomonas chengduensis), E2 (Pseudomonas alcaliphila), E3 (Bacillus subtilis), E4 (Bacillus altitudinis), E5 (Staphylococcus saprophyticus), E6 (Micrococcus aloeverae), E7 (Bacillus subtilis), E8 (Hydrogenophaga laconesensis).

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When analyzing the degradability of mercury at three different initial concentrations, we focused on the coefficient of variation shown in Table 11. The coefficient of variation allows us to assess the relative variability of the data. In the experiment, it was observed that bacteria exposed to concentration C1 of the contaminant exhibited more significant variability in degradation data compared to concentrations C2 and C3, which showed lower variability. This study demonstrates that bacteria exposed to higher Hg contaminant concentrations generate more consistent degradation.

Table 11.  Summary statistics of Hg degradation analysis.

	Count	Average	Coeff. of variation
C1 (mg/L)	8	88.77	12.09%
C2 (mg/L)	8	97.99	1.36%
C3 (mg/L)	8	98.02	1.18%
Total	24	94.93	7.87%

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Based on the previous statistical results in Table 11, a multiple-range test was conducted to determine if the degradation rates of the contaminant Hg were statistically different. According to the results in Table 12, the mercury degradation rates achieved for all bacterial strains used at an initial mercury concentration of 88 mg/L (C2) and 100 mg/L (C3) were similar. However, both significantly differ from the mercury concentration of 10 mg/L (C1). As observed, it is confirmed that bacteria degrade more effectively when exposed to a culture medium with high mercury concentrations (C2 and C3), and their degradation level decreases when they grow in a culture medium with low mercury concentrations. This information is essential for determining the optimal starting concentration of the contaminant at which these bacteria can work in bioremediation processes.

Table 12.  Multiple-range test. Method: 95.0 percent LSD for the mercury (Hg) contaminant.

	Count	Mean	Homogeneous Groups
C1 (mg/L)	8	88.7713	A
C2 (mg/L)	8	97.9975	B
C3 (mg/L)	8	98.02	B
Contrast	Sig.	Difference	+/– Limits
C1–C2	*	–9.2262	6.52756
C1–C3	*	–9.24875	6.52756
C2–C3		–0.0225	6.52756

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This analysis corresponds to Figure 4, which displays the range where the maximum Hg degradation data concentrate for concentrations C2 and C3. These values range between 96.28% and 99.56%, unlike concentration C1, where most of the degradation concentrates within the 86% to 98% range, with an outlier value of 66.91% degradation. Therefore, it is concluded that, regardless of the contaminant (Hg or CN^-), bacteria respond better to degradation when grown in media with higher contaminant concentrations.

Figure 4.  Box plot of Hg degradability by the eight bacterial strains concerning three different contaminant concentrations: 10 mg/L (C1), 88 mg/L (C2), and 100 mg/L (C3).

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5.   Conclusions

This study focused on isolating 15 bacterial strains from soil samples from mining tailings in the San Carlos area of Ecuador. Molecular identification revealed 5 genera, including Pseudomonas, Bacillus, Staphylococcus, Micrococcus, and Hydrogenophaga. The degrading potential of these strains against three different concentrations of CN^- and Hg was evaluated in the laboratory. For CN^-, concentrations of 6.8 mg/L, 8 mg/L, and 9.2 mg/L were used, while for Hg, concentrations of 10 mg/L, 88 mg/L, and 100 mg/L were employed. It was observed that bacteria exhibit superior degradation performance when grown in media with higher contaminant concentrations compared to lower concentrations.

CN^- degradation ranged from 7.94% to 66.24%, with Micrococcus aloeverae and Pseudomonas alcaliphila showing the highest rates. These strains, not previously mentioned in cyanide degradation studies, are promising for CN^- removal processes. Bacillus subtilis also showed satisfactory results, reaffirming its known effectiveness. For Hg degradation, bacterial strains achieved over 85% efficacy at the lowest concentration (10 mg/L). Higher concentrations led to even better removal rates, reaching 96.31% to 98.80% at 88 mg/L and 100 mg/L, respectively. Notable Hg degraders included Hydrogenophaga laconesensis and Micrococcus aloeverae, which were previously unidentified. Pseudomonas alcaliphila effectively degraded both Hg and CN^-. The study suggests further exploration and application of these bacteria from contaminated mining tailings in forming bacterial consortia, highlighting their significant potential in bioremediation processes to mitigate environmental pollution.

Use of AI tools declaration

The authors declare that artificial intelligence (AI) tools were not used in any stage of research in the studies carried out and presented in this article.

Acknowledgments

The authors would like to express their utmost gratitude to all parties who have contributed to the successful implementation of this research.

Conflicts of interest

The authors declare no conflict of interest.