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Article

Microbial Diversity and Heavy Metal Resistome in Slag-Contaminated Soils from an Abandoned Smelter in Chihuahua, Mexico

by
Gustavo Montes-Montes
1,
Zilia Y. Muñoz-Ramírez
2,
Leonor Cortes-Palacios
1,
Javier Carrillo-Campos
1,
Obed Ramírez-Sánchez
3,
Ismael Ortiz-Aguirre
1,
Laila N. Muñoz-Castellanos
2 and
Román González-Escobedo
1,*
1
Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Periférico Francisco R. Almada km 1, Chihuahua 31453, Mexico
2
Facultad de Ciencias Químicas, Universidad Autónoma de Chihuahua, Campus II Circuito Universitario s/n, Chihuahua 31125, Mexico
3
Soil Genomics & Discovery Department, Solena Inc., Av. Olímpica 3020-D, Villas de San Juan, León 37295, Mexico
*
Author to whom correspondence should be addressed.
Soil Syst. 2025, 9(2), 30; https://doi.org/10.3390/soilsystems9020030
Submission received: 14 February 2025 / Revised: 22 March 2025 / Accepted: 31 March 2025 / Published: 1 April 2025
(This article belongs to the Special Issue Microbial Community Structure and Function in Soils)
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Abstract

:
Heavy metal(loid) (HM) contamination in soils from smelting activities poses significant environmental and public health risks, as well as disruptions in microbial community dynamics and HM resistance gene profiles. This study investigates the microbial diversity, resistome, and physicochemical properties of soils from the abandoned Avalos smelter in Chihuahua, Mexico. Through soil analyses, we identified elevated concentrations of certain HMs, which pose serious environmental and health hazards. The metagenomic analysis of the microbial community, composed of bacteria, archaea, and fungi, was dominated by genera such as Streptomyces, Bradyrhizobium, Halobaculum, Nitrosocosmicus, Fusarium, and Aspergillus in rhizospheric soil. Furthermore, a diverse array of metal resistance genes (MRGs) were detected, associated with copper, arsenic, iron, lead, cadmium, zinc, and other HMs. Additionally, metagenome-assembled genomes (MAGs) revealed the presence of functional genes linked to HM resistance, providing deeper insights into the ecological roles and metabolic capabilities of microbial taxa. These findings highlight the significant impact of smelting-derived contamination on microbial diversity and functional potential, offering valuable insights for the development of bioremediation strategies in HM-contaminated environments.

1. Introduction

Soil contamination by heavy metal(loid)s (HM), particularly in regions near mining and smelting facilities, poses a critical threat to human health and environmental stability. This contamination significantly disrupts soil chemistry, impacting local ecosystems, including flora, fauna, and microbial communities [1,2]. Rhizospheric soils, which are crucial for plant health due to their microbial diversity and nutrient cycling functions, can be severely affected by metals such as copper (Cu) and lead (Pb) [3]. These pollutants can reduce microbial diversity and promote the growth of resistant taxa, thereby altering the microbial community structure and enriching the resistome within the soil microbiota [4].
Microbial communities in contaminated soils have developed adaptive mechanisms to cope with HMs, including metal sequestration, efflux pumps, and metabolic modifications that enable survival in toxic conditions [5]. These mechanisms are often linked to metal resistance genes (MRGs), which tend to accumulate in contaminated environments, contributing to a more resilient resistome in affected soils [4,5]. The presence of these genes and microbial adaptations not only facilitates survival in hostile environments but also influences ecological stability and nutrient dynamics within the rhizosphere, affecting soil health and plant–microbe interactions [6,7].
Research on the effects of HMs on microbial communities and resistomes in highly contaminated rhizosphere soils is still in its early stages. Several studies have focused on agricultural soils or moderately impacted environments [8,9,10], leaving legacy contamination sites, such as abandoned smelting areas, relatively unexplored. Understanding microbial responses and the resistome in these environments can lay the groundwork for effective remediation strategies and provide insights into the long-term ecological effects of contamination. Metagenomics, which enables the comprehensive profiling of microbial communities and their associated genes, has proven to be a crucial tool in these studies. For example, metagenomics has been used to identify resistance genes and understand microbial dynamics in response to contamination in HM-contaminated soils from activated sludge [11], in contaminated sediments from e-waste sites in China [12], and in an ancient open-cast mine in North Wales, UK [13], contributing valuable information for developing targeted bioremediation techniques.
The former Avalos smelter site in Chihuahua, Mexico, operated from 1908 to 1997, producing large quantities of impure lead, silver, gold, zinc oxides, and cadmium oxides. During its years of operation, the smelter processed ores from multiple mining districts in the state, generating more than 120,000 tons of slag as a by-product of metallurgical processes. These slag deposits were disposed of on-site in large piles [14], making it a high-priority site for study due to significant HM contamination. Compared with other industrial and metallurgical sites, the Avalos site presents a unique challenge due to its proximity to populated areas and prolonged industrial activity, which has profoundly impacted soil chemistry and, consequently, microbial biodiversity. These conditions, resulting from the prolonged accumulation of heavy metals, have created a highly selective environment that has likely favored the proliferation of resistant microorganisms and the enrichment of MRGs within the soil microbiome. Based on these considerations, this study aims to characterize the diversity of microbial communities, the resistome, and metagenome-assembled genomes (MAGs), as well as the metal(loid) concentrations in soils affected by HMs at the Avalos site. This study seeks to expand insights into the ecological effects of HM contamination on soil health and microbial diversity, providing a foundation for future remediation strategies in similar areas.

2. Materials and Methods

2.1. Soil Sampling

Soil samples were collected from two distinct points at the abandoned smelter in Avalos, Chihuahua, Mexico (28°37′13″ N, 106°00′40″ W) (Figure 1). The first site consisted of rhizospheric soil (hereafter referred to as the RS sample) from the sparse vegetation present in an area with HM slags, dominated solely by grassland-type vegetation (28°37′32.0″ N, 106°00′16.2″ W). The second site consisted of non-rhizospheric soil (hereafter referred to as the NRS sample), located approximately 1 km away from the first sampling point (28°36′57.9″ N, 106°00′23.3″ W). Three subsamples were collected at each point to form a composite sample. For soil collection, the uppermost 20 cm of soil was removed, and approximately 500 g was placed in a sterile, resealable bag and transported at 4 °C to the laboratory, where it was immediately processed [15]. Each soil sample was divided into two portions: one half was used for metagenomic DNA extraction, and the other half was used for physicochemical soil analysis.

2.2. Soil Physicochemical Analysis

The analysis was conducted in triplicate based on the criteria established by the Mexican Official Standard NOM-147-SEMARNAT/SSA1-2004 to determine the concentrations of the following elements: As, Be, Ca, Cd, Co, Cr, Cu, Fe, Mg, Mn, Mo, Ni, Pb, Sb, Se, and Zn. The sample preparation involved acid digestion using microwave-assisted technology with an Anton Paar Multiwave Go system. The procedure utilized 14 mL of reverse aqua regia and 0.5 mL of hydrogen peroxide. Once the solution was prepared, vials were placed inside the microwave and processed for 40 min at a pressure of 20 atm, following the EPA-3051A method. After digestion, the samples were cooled for 10 min inside a fume hood and transferred into 50 mL volumetric flasks using distilled water. Subsequently, the samples were refrigerated for preservation and later analyzed for heavy metal quantification using Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) (PerkinElmer®, Optima™ 8300, Waltham, MA, USA) [18].

2.3. DNA Extraction and Sequencing

Genomic DNA was extracted from 250 mg of soil using a ZymoBIOMICSTM DNA Miniprep Kit (Zymo Research, Irvine, CA, USA) according to the manufacturer’s protocol. The quality and concentration of the DNA were assessed using a NanoDrop spectrophotometer (Thermo Scientific, Wilmington, DE, USA) and by electrophoresis on 1% agarose gel. For sequencing, the extracted DNA was sent to Illumina Inc. (San Diego, CA, USA) for library preparation and processing. A total of 100 ng of DNA was used to generate sequencing libraries with the Illumina DNA Prep (M) Tagmentation Kit (# Cat. 20018705). To enable multiplexing, unique index adapters were added to each sample using the IDT for Illumina DNA/RNA UD Indexes Set A Tagmentation (# Cat. 20027213). The concentration of the prepared libraries was measured using the Qubit dsDNA HS Assay Kit (Thermo Fisher, Waltham, MA, USA), and their quality was evaluated with the Agilent Bioanalyzer 2100 using the NGS 1-6000 Kit. Sequencing was performed on an Illumina NovaSeq 6000 system (Illumina Inc., San Diego, CA, USA) with a 2 × 150 bp paired-end run on an S4 flow cell [19].

2.4. Metagenomic Data Analysis

The quality of the received reads was assessed using FastQC v0.12.1 [20]. Reads containing artificial sequences and nucleotides with poor read quality (Phred < 34) were trimmed using TrimGalore v0.6.7 [21], followed by a second quality check with FastQC v0.12.1. The cleaned reads were then selected for further analysis. Taxonomic affiliation was assigned using Kraken v2.1.3 [22] with the prebuilt RefSeq database (prebuilt_pluspf_2024-01-12), which contains sequences for bacteria, archaea, fungi, and protozoa (https://benlangmead.github.io/aws-indexes/k2, accessed on 20 November 2024). Microbial diversity analysis was conducted in R Core Team statistical package v4.4.1 [23] using the phyloseq v1.40.0 [24] vegan v2.6-10 [25], and tidyverse v1.3.0 [26] libraries. Finally, a differential abundance analysis was performed using ALDEx2 v1.38.0 [27] in R to identify taxa with significant differences between samples, applying a Dirichlet-multinomial model to infer abundance from counts and determine effect sizes for the taxa.

2.5. Analysis of MRGs

To investigate the presence of genes conferring metal resistance in the microbiome, metagenomic reads were assembled using MetaSPAdes v3.0 [28] with k-mer lengths of 21, 33, and 55. The resulting contigs were then mapped against the Antibacterial Biocide and Metal Resistance Genes Database (BacMet) [29] using DIAMOND v2.0.15 [30] in BLASTp alignment mode. Sequences with >80% identity and an e-value ≤ 1 × 10−5 were retained. Subsequently, data filtering and grouping were performed in R v4.4.1, based on the total count of genes involved in metal resistance and their corresponding genera. Additionally, visualizations were generated using the treemap library [31].

2.6. Metagenome-Assembled Genomes (MAGs)

To generate MAGs, assembled contigs were separated into bins using MetaWRAP v1.3 [32]. Quality assessment of the resulting MAGs was performed using CheckM v1.2.3 [33], with MAGs categorized based on completeness and contamination thresholds. Two quality categories were defined: high-quality MAGs (completeness > 90%, contamination < 5%) and medium-quality MAGs (completeness > 70%, contamination < 10%). These classifications align with the Minimum Information for Metagenome-Assembled Genomes (MIMAG) standards. The taxonomic classification of the assembled genomes was determined using GTDB-Tk v2.0.0 [34]. Subsequently, MAGs were annotated using Prokka v1.14.5 [35] and compared against the BacMet database (http://bacmet.biomedicine.gu.se/, accessed on 27 November 2024 [29]) to determine the presence or absence of genes related to metal resistance within the MAGs.

3. Results

3.1. Soil Major Characteristics

The major soil characteristics are shown in Table 1. The soil texture of RS was classified as sandy loam, while that of NRS was silty. Electrical conductivity (EC) was higher in RS (1.78 mS·cm−1) than in NRS (1.18 mS·cm−1). Regarding organic matter (OM) content, NRS had a higher percentage (3.03%) compared with RS (1.3%). In terms of metal concentrations, differences were observed between the soils. RS contained higher levels of Cu (1994.65 mg·kg−1), Fe (54,817.13 mg·kg−1), Mn (5171.52 mg·kg−1), and Zn (19,563.67 mg·kg−1) compared with NRS. Conversely, NRS exhibited elevated concentrations of As (314.61 mg·kg−1), Cd (341.95 mg·kg−1), Pb (7355.86 mg·kg−1), and Se (86.98 mg·kg−1). Among the macronutrients, magnesium (Mg) levels were higher in NRS (2440.36 mg·kg−1) than in RS (1900.13 mg·kg−1). However, calcium (Ca) followed the opposite trend, being higher in RS (14,716.06 mg·kg−1) compared with NRS (2299.2 mg·kg−1).

3.2. Composition, Abundance, and α-Diversity of Microbial Communities

A total of 49,572,402 raw sequences were obtained from the RS sample. After a quality control process, 45,744,460 sequences were retained for further analysis. In the case of bacterial community, a total of 56 phyla, 567 families, and 2008 bacterial genera were identified. Taxonomic classification revealed the most abundant genera (Figure 2a), with Streptomyces showing the highest relative abundance (10.15%), followed by Bradyrhizobium (3.69%), Sphingomonas (3.62%), Nocardioides (2.80%), Pseudomonas (2.01%), Microbacterium (1.53%), Micromonospora (1.50%), Mycolicibacterium (1.33%), Blastococcus (1.31%), and Geodermatophilus (1.19%), along with 1998 other genera at relative abundances below 1.1%. In the case of archaeal community, a total of 12 phyla, 45 families, and 147 archaeal genera were identified. Among the 148 genera classified (Figure 2b), the most abundant was Halobaculum (8.08%), followed by Nitrosocosmicus (6.55%), Halorubrum (6.38%), Natrinema (4.86%), Halorussus (4.17%), Halomicroarcula (3.68%), Nitrososphaera (3.33%), Halosimplex (3.25%), Halobacterium (3.13%), Haloplanus (2.91%), and 137 additional genera displaying relative abundances below 2.9%. On the other hand, the fungal community comprised 14 phyla, 34 families, and 54 genera (Figure 2c). The most abundant genera were Fusarium (15.36%), Aspergillus (11.86%), Colletotrichum (7.28%), Pyricularia (6.34%), Thermothielavioides (5.57%), Purpureocillium (5.56%), Malassezia (4.01%), Thermothelomyces (3.91%), Drechmeria (3.82%), and Akanthomyces (3.18%), followed by 44 additional genera with relative abundances below 3.1%.
In the case of the NRS sample, a total of 4,160,235 raw sequences were obtained, and 3,939,758 high-quality sequences were retained after quality processing. In the bacterial community, a total of 48 phyla, 471 families, and 1551 genera were identified. The most abundant genus was Streptomyces (13.25%), followed by Nocardioides (5.80%), Rubrobacter (3.67%), Sphingomonas (2.52%), Pseudonocardia (2.26%), Conexibacter (2.08%), Amycolatopsis (1.69%), Micromonospora (1.62%), Bradyrhizobium (1.60%), and Pseudomonas (1.59%), along with 1541 additional genera with relative abundances below 1.5% (Figure 2d). For the archaeal community, 9 phyla, 35 families, and 99 genera were identified. The most abundant genus was Nitrososphaera (12.09%), followed by Halorubrum (8.10%), Halobaculum (6.37%), Candidatus Nitrosocosmicus (6.25%), Halobacterium (5.26%), Natrinema (4.46%), Haloterrigena (3.49%), Halosimplex (3.33%), Natronomonas (2.55%), and Haloplanus (2.53%), with 89 additional genera exhibiting relative abundances below 2.5% (Figure 2e). Furthermore, the fungal community comprised 13 phyla, 25 families, and 41 genera, primarily dominated by Aspergillus (14.51%), Pyricularia (10.68%), Fusarium (10.36%), Thermothielavioides (9.65%), Colletotrichum (8.50%), Thermothelomyces (7.80%), Drechmeria (6.27%), Ustilaginoidea (5.24%), Neurospora (3.01%), and Sporisorium (2.75%), followed by 31 additional genera with relative abundances below 2.7% (Figure 2f).
The α-diversity indices for bacterial, archaeal, and fungal communities in RS and NRS soils are summarized in Table 2. Bacterial communities in RS exhibited higher richness, with a Chao1 value of 2022.0, compared with 1697.6 in NRS. Similarly, the Shannon index indicated greater diversity in RS (5.45) than in NRS (5.01), while the Simpson index remained comparable between both soils (0.98 in RS and 0.97 in NRS). Archaeal communities followed a similar trend, with higher richness in RS (Chao1 = 148.0) relative to NRS (Chao1 = 129.7). The Shannon index was also slightly higher in RS (3.87) compared with NRS (3.63), while the Simpson index was marginally greater in RS (0.97) than in NRS (0.96), indicating a consistently more diverse archaeal community in rhizospheric soils. In contrast, fungal communities exhibited a different pattern. While Chao1 richness was higher in RS (52) than in NRS (44), the Shannon and Simpson indices revealed lower diversity and evenness in RS. Specifically, the Shannon index was lower in RS (1.16) compared with NRS (2.91), and the Simpson index was also reduced in RS (0.52) relative to NRS (0.92).

3.3. ALDEx2 Analysis

The ALDEx2 analysis identified significant differences in taxa between RS and NRS samples. In the bacterial community, taxa such as Bradyrhizobium, Sphingomonas, Lentzea, Roseomonas, and Pseudomonas were among the most enriched in RS, while Rubrobacter, Pseudonocardia, Conexibacter, Nocardioides, and Massilia were more enriched in NRS (Figure 3a). In archaea, RS exhibited a higher enrichment of Halorussus, Salinigranum, Halobaculum, Halobellus, and Natrinema, whereas Nitrososphaera, Candidatus Nitrosocosmicus, Haloterrigena, Haloarcula, and Halosiccatus were more enriched in NRS (Figure 3b). In the fungal community, RS was characterized by the enrichment of Malassezia, Fusarium, Purpureocillium, Akanthomyces, and Ascochyta, while NRS exhibited higher enrichment of Thermothelomyces, Thermothielavioides, Ustilaginoidea, Pyricularia, and Drechmeria (Figure 3c).

3.4. Identification and Abundance of MRGs

The analysis of MRGs in RS and NRS samples revealed a diverse array of genes involved in resistance to various HMs (Figure 4). Among Cu-resistance genes, copA (5.99% in RS, 9.37% in NRS), actP (7.45% in RS, 7.43% in NRS), ctpV (2.97% in RS, 7.24% in NRS), ctpG (6.01% in RS, 4.92% in NRS), copF (3.28% in RS), and golT (1.99% in RS), which encode for metal ion transporters and resistance mechanisms, were the most abundant genes. Among As-resistance genes, arsM (2.25% in RS, 3.57% in NRS), aioA/aoxB (1.84% in RS, 0.77% in NRS), arsB (1.20% in RS, 1.54% in NRS), and arsH (1.66% in RS) were the most abundant, encoding proteins responsible for arsenic methylation, oxidation, detoxification, and efflux systems. In addition, other important genes detected include copA (4.41% in RS, 9.37% in NRS), silA (1.18% in RS, 1.06% in NRS), cueA (1.00% in RS, 1.25% in NRS), and silP (1.54% in RS) as Ag-resistance genes; ctpD (0.35% in RS, 1.44% in NRS) and cnrA (1.98% in RS) as co-resistance genes; merA (2.13% in RS, 2.12% in NRS), merR1 (0.98% in RS), and merT (0.83% in RS) as Hg-resistance genes; and czrA (1.56% in RS, 2.41% in NRS), actR (0.59% in RS), and czcA (0.53% in RS) as Cd-resistance genes, which encode for metal ion transporters, efflux pumps, and regulatory proteins involved in metal detoxification processes, representing the most abundant resistance mechanisms for each metal.
In addition to identifying the relative abundance of MRGs, the relationship between metal concentration and the most abundant bacterial genera harboring these MRGs was analyzed (Figure 5). In both RS and NRS samples, Mycobacterium exhibited the highest proportion of MRGs, with a dominant association with Fe (18.57% in RS, 22.30% in NRS) and Cu (17.93% in RS, 15.42% in NRS). Pseudomonas, another prominent genus, demonstrated broad resistance to multiple metals. In RS, it displayed significant resistance genes for Cu (8.0%), Zn (5.42%), Cd (5.39%), Ag (5.29%), and Hg (1.25%), while in NRS, it was linked to Cu (5.94%), Ag (5.94%), Cd (4.46%), and Zn (4.46%).
Other genera exhibited specific associations with certain metals. In RS, Bradyrhizobium was primarily linked to Co (6.74%) and As (0.69%), while in NRS, Rhodococcus was associated with Fe (5.76%) and Cu (2.04%). Rhizobium was present in both RS and NRS samples, with resistance genes to Cu (4.38% in RS, 2.27% in NRS), Cd (1.28% in RS), and Zn (1.22% in RS). In contrast, Cupriavidus was linked to Co (1.31% in RS), Zn (1.17% in RS), and Cd (1.17% in RS). Meanwhile, Lysobacter was associated with Cu (3.15%) and Ag (3.15%) in NRS. Additionally, genera such as Mesorhizobium and Escherichia were connected to Cu, Ag, and Cd resistance genes at proportions < 3.35% in both RS and NRS samples.

3.5. Characteristics of the Recovered MAGs and Identification of MRGs

A total of 4,499,776 contigs were recovered from RS samples, while 411,096 contigs were obtained from NRS samples. In the NRS sample, 8337 contigs were grouped into two MAGs; however, neither met the MIMAG standards, which require at least 50% completeness with <10% contamination, and they were therefore discarded. In contrast, in RS, 11,007 contigs were grouped into 20 MAGs, all of which successfully met MIMAG standards. Among these, 9 MAGs were classified as high quality (>90% completeness, <5% contamination), while 11 MAGs were categorized as medium quality (>70% completeness, <10% contamination) (Supplementary Table S1).
A total of 18 of the 20 recovered genomes were affiliated with the bacterial domain, while the remaining two belonged to the archaeal domain, with Actinobacteriota being the most dominant phylum. A total of 3 MAGs were classified at the order level, 7 at the family level, and 10 at the genus level (Figure 6). Among the identified MRGs, Cu had the highest number of associated genes, with a total of 74, followed by As (47 genes), Zn (29 genes), and Cd, Co, and Zn, each with 25 genes. The most abundant gene found across all bins was recG, with 18 occurrences, followed by fieF (13 occurrences), pstA (11 occurrences), galE (11 occurrences), and czcD (10 occurrences).
Furthermore, the bin with the highest abundance of MRGs was identified as bin_5 (Caldovatus), containing a total of 57 resistance-related genes, including arsC, pstA, pstB, pstC, pstS, and pgpA for arsenic resistance; zntA (Pb/Cd/Zn) for lead resistance; and merR1, merA, and merB for mercury resistance. This was followed by bin_8 (SCGC-AG-212-J23), with 55 resistance-related genes, including arsenic resistance genes (aioB, arsC, pstA, pstB, and pgpA) and multi-resistance genes (czcA, czcC, and czcS) conferring resistance to Cd, Zn, and Co. Bin_21 (Bradyrhizobium) contained 44 resistance-related genes, including arsenic resistance genes (aioA, aioB, arsM, and pstA), as well as zntA (Pb/Cd/Zn) and mntH (Mn/Fe/Cd/Co/Zn), indicating robust multi-metal resistance potential. Lastly, bin_2 (Longimicrobium) contained a total of 42 resistance-related genes, including zraS (a Pb resistance gene) and 5 arsenic resistance genes (arsR, pstA, pstB, pstC, and pstS).

4. Discussion

This study presents the first characterization of microbial communities in heavy metal-contaminated soils from the abandoned Avalos smelter site, where pollutants have remained exposed to the environment in Chihuahua City. The results revealed bacterial, archaeal, and fungal genera with potential roles in heavy metal tolerance, which are crucial for survival under extreme environmental stress. While these microorganisms exhibit traits associated with metal resistance, their bioremediation potential warrants further functional validation.
Distinct heavy metal (HM) concentrations were observed between RS and NRS samples. RS exhibited higher concentrations of Cu, Fe, Mn, and Zn compared with NRS. These findings reflect the proximity of RS to smelting activities, which have been shown to deposit metal particulates directly onto nearby soils, consistent with their role as primary smelting by-products in industrial sites [13]. Conversely, NRS contained higher concentrations of As, Cd, Pb, and Se. These elements are likely transported via wind or water erosion, accumulating at greater distances from the smelter [6]. According to NOM-147-SEMARNAT/SSA1-2004, which establishes remediation thresholds for contaminated soils in Mexico, several metals analyzed in this study exceeded permissible levels for agricultural, residential, or industrial uses. In RS, As (172.92 mg·kg−1) and Cd (57.77 mg·kg−1) exceeded the limits for agricultural and residential use (22 mg·kg−1 and 37 mg·kg−1, respectively). In NRS, As (314.61 mg·kg−1) exceeded even the industrial threshold (260 mg·kg−1), while Pb concentrations in both RS (1495.04 mg·kg−1) and NRS (7355.86 mg·kg−1) were very high, surpassing all limits established by the regulation. These findings indicate a significant risk to both environmental and human health, necessitating targeted remediation efforts [36].
On the other hand, the microbial community structure of the Avalos smelter site soils revealed differences between RS and NRS samples in terms of sequencing depth, taxonomic composition, and diversity metrics. Overall, rhizospheric soil exhibited a slightly higher diversity of bacteria, archaea, and fungi compared with non-rhizospheric soil. Although the RS sample had more than ten times the sequencing depth of the NRS sample, the alpha diversity indices remained relatively similar. An enriched microbial diversity has been reported in rhizospheric soil, as observed in contaminated soils affected by e-waste [37], since a greater number of species increase the likelihood that an ecosystem will retain its functions even if some species are eliminated or suppressed by environmental stressors [38]. Additionally, microbial community–plant interactions involve the secretion of a variety of metabolites by plant roots, including organic acids, sugars, amino acids, and secondary metabolites, which selectively recruit and support the establishment of microorganisms in the rhizosphere [39]. Furthermore, site-specific characteristics may have also contributed to the observed differences, as the RS sample was collected from an area dominated by smelting slag with sparse vegetation, whereas the NRS site was located in a zone without plant cover and free of slag deposits.
In agreement with these findings, RS soil exhibited a microbial composition dominated by genera known for their metal tolerance and bioremediation potential. In RS, the dominance of genera such as Streptomyces and Bradyrhizobium suggests a significant microbial contribution to metal tolerance and degradation processes. Studies have shown that Streptomyces spp. can thrive in metal-polluted environments due to their ability to employ a wide range of resistance mechanisms, including biosorption, reduction, biomineralization, extracellular binding by chelators, efflux through transport systems, and intracellular metal binding [40]. Additionally, Streptomyces has been documented to tolerate HM such as Cr, As, Zn, Cu, and Pb [41], as well as Cd [42], among others, making this genus highly effective in bioremediation efforts [43]. Similarly, Bradyrhizobium plays a key role in maintaining soil health under metal stress conditions. In addition to its symbiotic nitrogen fixation in plants, it has been documented to utilize biosorption and exopolysaccharide production mechanisms [44], which can immobilize and reduce the toxicity of metals such as Zn, Pb, and Hg, thereby enhancing plant resilience in contaminated soils [45].
Among the archaeal genera identified, Halobaculum, Halorubrum, Halorussus, and Halobacterium, among others, have been documented to exhibit remarkable adaptations to extreme environments, including soils with high salinity and HM contamination [46,47,48]. Furthermore, Nitrosocosmicus and Nitrososphaera, key nitrifying archaea associated with the plant rhizosphere [49], contribute significantly to nitrogen cycling by oxidizing ammonia to nitrite, even under high salinity and metal stress, making them crucial players in biogeochemical cycles [50,51]. Similarly, dominant fungal genera such as Fusarium and Aspergillus have been identified as key contributors to the stability of HM-contaminated soils, demonstrating distinct yet complementary mechanisms of adaptation and remediation. Fusarium sp. has demonstrated significant biosorption and biotransformation abilities, particularly in Zn sequestration, through mechanisms such as organic acid production, intracellular compartmentalization, and enzymatic detoxification [52]. Likewise, Aspergillus species, including A. flavus and A. niger, exhibit remarkable resistance to Cr and Pb, utilizing processes such as bioaccumulation and extracellular enzyme production to mitigate metal toxicity, making them valuable candidates for bioremediation strategies [53].
The ALDEx2 analysis revealed significant differences in the abundance of taxa between RS and NRS, highlighting the impact of environmental pressures and plant–microbe interactions in shaping microbial communities. Despite the high concentrations of HM in both samples, the rhizospheric microbial community exhibited a distinct association with specific taxa. Genera such as Bradyrhizobium, Sphingomonas, Lentzea, Roseomonas, and Pseudomonas were enriched in RS, likely due to their roles in nutrient cycling, stress tolerance, and plant–microbe interactions. Notably, Bradyrhizobium and Sphingomonas are well known for their ability to detoxify HM and promote plant growth, with Sphingomonas producing bioactive compounds and siderophores to mitigate metal stress [54]. Among archaeal taxa, RS exhibited a higher abundance of halophilic genera, including Halorussus, Salinigranum, Halobaculum, and Halobellus, which are adapted to high-salinity environments and play critical roles in osmotic balance and sulfur and nitrogen cycling [46]. Similarly, the fungal community displayed notable differentiation, with Malassezia, Fusarium, Purpureocillium, Akanthomyces, and Ascochyta enriched in RS. Fusarium and Purpureocillium are particularly recognized for their capacity to tolerate and remediate HM contamination through biosorption and bioaccumulation mechanisms [52]. The presence of Malassezia in the soil samples is particularly intriguing, as this fungal genus is typically recognized as an opportunistic pathogen in humans and other animals [55]. However, some studies have reported Malassezia in unexpected habitats, including nematodes in soil [56] and marine environments [57], suggesting that this genus may possess greater ecological plasticity than previously thought. These findings highlight the importance of expanding our understanding of the ecology of these fungi, as their presence in soil may reflect unknown survival strategies or symbiotic relationships with other soil microbiota. Additionally, they may contribute to nutrient cycling or soil microbial dynamics, underscoring the need for further studies to elucidate their roles in terrestrial ecosystems.
The analysis of MRGs revealed a diverse set of genes associated with the high concentrations of heavy metals quantified, suggesting a correlation between contamination and microbial genetic diversity. This could lead to a high selective pressure due to constant exposure to these contaminants at a site that was a leading center of the metallurgical industry in the 20th century. The results obtained are consistent with the genera previously described and align with prior studies documenting the presence and abundance of MRGs in HM-contaminated soils [5,58]. The higher abundance of copA in NRS samples (9.37%) compared with RS samples (5.99%) may indicate greater selective pressure from Cu in non-rhizospheric soils, potentially due to the absence of plant-mediated exclusion mechanisms [59]. For As-resistance genes, such as arsM, aioA/aoxB, and arsB, their presence in both samples suggests microbial adaptation to environments with high concentrations of this metalloid. The arsM gene, which encodes ArsM homologue proteins necessary for As biomethylation, may be linked to the ability of certain microorganisms to transform As into less toxic forms in soils [60]. In this context, the analysis of the relationship between bacterial genera and MRGs revealed that Mycobacterium was the dominant genus in both samples, with a strong association with Fe and Cu resistance. This finding is consistent with studies identifying Mycobacterium as a genus highly resistant to HMs, attributed to its capacity to accumulate and detoxify metals through mechanisms such as biosorption and siderophore production [61]. The presence of Pseudomonas, a genus known for its broad resistance to multiple metals, was also notable in both samples, exhibiting resistance genes for Cd, Cu, Ag, Fe, Hg, and Zn. This genus has been extensively studied for its ability to thrive in HM-contaminated environments, largely due to the presence of efflux systems and detoxifying enzymes [62,63].
The recovery and characterization of MAGs from RS provided key insights into the microbial potential for metal resistance. Among the 20 MAGs identified, the bacterial domain predominated, with Actinobacteriota being the most dominant phylum. This phylum is well documented for its resilience in extreme environments and its involvement in the production of secondary metabolites, including siderophores and metal-binding compounds [64]. The identification of archaeal MAGs further highlights the functional diversity of rhizospheric communities, particularly in extreme and metal-contaminated environments. In fact, the analysis of MRGs in the MAGs revealed that Cu had the highest number of associated genes, followed by As, Zn, Cd, and Co. These results are consistent with previous studies demonstrating that Cu and As are among the most common metals in contaminated soils, exerting strong selective pressure on microbial communities to develop resistance mechanisms [65,66]. The high abundance of MRGs suggests that many of these genes are part of the functional genetic repertoire that enables microorganisms to play a fundamental role in resistance to multiple metals, possibly through mechanisms of transport, detoxification, and regulation of metal homeostasis [67].
Notably, MAG bin_5 (Caldovatus) exhibited the highest number of resistance-related genes, revealing bioremediation potential, which is underscored by its comprehensive array of genes involved in detoxification and metal transport, including arsC and zntA, suggesting robust arsenic and multi-metal resistance capabilities. However, studies on this genus are currently limited to its localization in hot springs [68,69]. MAG bin_21 (Bradyrhizobium) also displayed a multi-metal resistance profile, with genes such as aioA, aioB, arsM, pstA, zntA, and mntH, indicating this genus’s notable capacity to withstand the toxicity of As, Pb, Cd, Zn, Co, and Mn [45]. This finding is particularly relevant, as Bradyrhizobium is known for its ability to establish symbiosis with leguminous plants, which could confer additional advantages in the rhizosphere for metal detoxification. Finally, MAG bin_2 (Longimicrobium) exhibited a high abundance of resistance genes for Pb (zraS) and As (arsR, pstA, pstB, pstC, and pstS), which has been documented to enhance plant tolerance to HMs, reduce the metal enrichment capacity of plants, and improve the nitrogen fixation capacity of the soil [70]. Therefore, the study of MRGs and MAGs highlights the diversity of resistance strategies in rhizospheric microorganisms, resulting in a greater potential for the natural attenuation of HM contamination, improved microbial-driven soil restoration, and the promotion of plant–microbe interactions that contribute to ecosystem resilience.

5. Conclusions

This study highlights the unique microbial diversity and functional potential of rhizospheric soils at the Avalos smelter site, which is characterized by high concentrations of HMs, including Cu, As, Zn, and Cd. Despite these extreme conditions, key taxa such as Streptomyces, Bradyrhizobium, Halobaculum, Nitrosocosmicus, and Halorubrum were identified, harboring diverse metal resistance genes that enable mechanisms such as metal sequestration, efflux, and detoxification. The recovery of high-quality MAGs revealed robust multi-metal resistance pathways, particularly in genera such as Caldovatus, Bradyrhizobium, and Longimicrobium, underscoring their adaptability to toxic environments. These findings demonstrate the ecological resilience of rhizospheric microbial communities and their crucial role in tolerating and mitigating HM stress. This work provides a baseline for the development of bioremediation strategies that harness the genetic and metabolic capabilities of these microbes to restore ecosystems contaminated by high levels of HMs.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/soilsystems9020030/s1. Supplementary Table S1: Quality metrics and taxonomic classification of MAGs.

Author Contributions

Conceptualization, R.G.-E. and Z.Y.M.-R.; methodology, G.M.-M., L.C.-P., J.C.-C., O.R.-S., I.O.-A., L.N.M.-C. and Z.Y.M.-R.; validation, R.G.-E. and Z.Y.M.-R.; formal analysis, G.M.-M., R.G.-E. and Z.Y.M.-R.; investigation, R.G.-E. and Z.Y.M.-R.; resources, R.G.-E. and L.N.M.-C.; data curation, G.M.-M.; writing—original draft preparation, G.M.-M., R.G.-E. and Z.Y.M.-R.; writing—review and editing, G.M.-M., L.C.-P., R.G.-E., J.C.-C., O.R.-S., I.O.-A., L.N.M.-C. and Z.Y.M.-R.; visualization, G.M.-M.; supervision, Z.Y.M.-R. and R.G.-E.; project administration, R.G.-E. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The datasets generated and/or analyzed during the current study are available in the NCBI Bioproject database under accession number PRJNA1223431.

Acknowledgments

The authors would like to thank the Secretaría de Desarrollo Urbano y Ecología (SEDUE) for their logistical support and for providing access to the smelter facilities. We thank the Secretaría de Ciencia, Humanidades, Tecnología e Innovación (SECIHTI-Mexico) for the financial support provided to G.M.-M. through a master’s fellowship and to Z.Y.M.-R. through a postdoctoral fellowship. The authors gratefully acknowledge the computing time granted by LANCAD and CONACYT on the supercomputer Yoltla at LSVP UAM-Iztapalapa. We also extend our gratitude to Rafael Escobedo and Frida Caraveo for their valuable contributions in conducting the physicochemical analyses of the soil samples. Finally, we thank the four anonymous reviewers for their comments, which helped improve the quality of the manuscript.

Conflicts of Interest

Author O.R.-S. has been involved as a consultant and expert in bioinformatics for Solena Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

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Figure 1. Distribution of soil sampling sites. The map was created using Leaflet [16] and Mapbox [17] to visualize the spatial distribution of the sampling locations.
Figure 1. Distribution of soil sampling sites. The map was created using Leaflet [16] and Mapbox [17] to visualize the spatial distribution of the sampling locations.
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Figure 2. Relative microbial abundance in soil samples from the Avalos smelter site, Chihuahua. RS: (a) bacteria, (b) archaea, (c) fungi; NRS: (d) bacteria, (e) archaea, (f) fungi.
Figure 2. Relative microbial abundance in soil samples from the Avalos smelter site, Chihuahua. RS: (a) bacteria, (b) archaea, (c) fungi; NRS: (d) bacteria, (e) archaea, (f) fungi.
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Figure 3. ALDEx2-based differential abundance analysis of taxa between RS and NRS soils: (a) bacteria, (b) archaea, and (c) fungi.
Figure 3. ALDEx2-based differential abundance analysis of taxa between RS and NRS soils: (a) bacteria, (b) archaea, and (c) fungi.
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Figure 4. Relative abundance of metal resistance genes (MRGs) in (a) RS and (b) NRS samples, identified using the BacMet database.
Figure 4. Relative abundance of metal resistance genes (MRGs) in (a) RS and (b) NRS samples, identified using the BacMet database.
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Figure 5. Relationships between bacterial genera and their associated MRGs for heavy metal(loid)s in (a) RS and (b) NRS samples.
Figure 5. Relationships between bacterial genera and their associated MRGs for heavy metal(loid)s in (a) RS and (b) NRS samples.
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Figure 6. Metal resistance genes (MRGs) in metagenome-assembled genomes (MAGs) obtained from RS samples. Gene presence and absence are indicated by red and black squares, respectively.
Figure 6. Metal resistance genes (MRGs) in metagenome-assembled genomes (MAGs) obtained from RS samples. Gene presence and absence are indicated by red and black squares, respectively.
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Table 1. Physicochemical properties and metal concentrations of soil samples.
Table 1. Physicochemical properties and metal concentrations of soil samples.
PropertiesRSNRS
TextureSandy loam Silty
EC (mS·cm−1)1.781.18
OM (%)1.33.03
pH7.147.32
Cu1994.65702.78
Zn19,563.672179.42
Fe54,817.1315,233.6
As172.92314.61 *
Mg1900.132440.36
Cd57.77341.95
Co37.2931.81
Cr67.9249.2
Pb 1495.04 *7355.86 *
Ca14,716.062299.2
Mn5171.52605.86
Ni16.9229.32
Mo118.4104.87
Be12.9625.84
Sb59137.18
Se16.0686.98
Metal concentrations are expressed in mg·kg−1 Elements exceeding the industrial limits established by NOM-147-SEMARNAT/SSA1-2004 are marked with *.
Table 2. α-Diversity indices of microbial communities in RS and NRS samples.
Table 2. α-Diversity indices of microbial communities in RS and NRS samples.
SampleCommunityChao1ShannonSimpson
RSBacteria2022.05.450.98
Archaea148.03.870.97
Fungi521.160.52
NRSBacteria1697.65.010.97
Archaea129.73.630.96
Fungi442.910.92
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Montes-Montes, G.; Muñoz-Ramírez, Z.Y.; Cortes-Palacios, L.; Carrillo-Campos, J.; Ramírez-Sánchez, O.; Ortiz-Aguirre, I.; Muñoz-Castellanos, L.N.; González-Escobedo, R. Microbial Diversity and Heavy Metal Resistome in Slag-Contaminated Soils from an Abandoned Smelter in Chihuahua, Mexico. Soil Syst. 2025, 9, 30. https://doi.org/10.3390/soilsystems9020030

AMA Style

Montes-Montes G, Muñoz-Ramírez ZY, Cortes-Palacios L, Carrillo-Campos J, Ramírez-Sánchez O, Ortiz-Aguirre I, Muñoz-Castellanos LN, González-Escobedo R. Microbial Diversity and Heavy Metal Resistome in Slag-Contaminated Soils from an Abandoned Smelter in Chihuahua, Mexico. Soil Systems. 2025; 9(2):30. https://doi.org/10.3390/soilsystems9020030

Chicago/Turabian Style

Montes-Montes, Gustavo, Zilia Y. Muñoz-Ramírez, Leonor Cortes-Palacios, Javier Carrillo-Campos, Obed Ramírez-Sánchez, Ismael Ortiz-Aguirre, Laila N. Muñoz-Castellanos, and Román González-Escobedo. 2025. "Microbial Diversity and Heavy Metal Resistome in Slag-Contaminated Soils from an Abandoned Smelter in Chihuahua, Mexico" Soil Systems 9, no. 2: 30. https://doi.org/10.3390/soilsystems9020030

APA Style

Montes-Montes, G., Muñoz-Ramírez, Z. Y., Cortes-Palacios, L., Carrillo-Campos, J., Ramírez-Sánchez, O., Ortiz-Aguirre, I., Muñoz-Castellanos, L. N., & González-Escobedo, R. (2025). Microbial Diversity and Heavy Metal Resistome in Slag-Contaminated Soils from an Abandoned Smelter in Chihuahua, Mexico. Soil Systems, 9(2), 30. https://doi.org/10.3390/soilsystems9020030

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