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Article

Chromium-Driven Changes in Heavy Metal Resistance Genes During Pig Manure Composting

by
Guoqiang Zhao
1,2,
Peng Li
1,2,
Yao Feng
3 and
Yuanwang Liu
4,*
1
Ankang Branch of Shaanxi Agricultural Development Group Co., Ltd., Xi’an 725000, China
2
Shaanxi Agricultural Development Group Co., Ltd., Xi’an 725000, China
3
Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China
4
Hebei Key Laboratory of Heavy Metal Deep-Remediation in Water and Resource Reuse, School of Environmental and Chemical Engineering, Yanshan University, Qinhuangdao 066004, China
*
Author to whom correspondence should be addressed.
Fermentation 2025, 11(8), 472; https://doi.org/10.3390/fermentation11080472
Submission received: 25 July 2025 / Revised: 11 August 2025 / Accepted: 16 August 2025 / Published: 18 August 2025
(This article belongs to the Special Issue Turning Organic Solid Waste into Soil Nutrients Using Biological Technology)
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Abstract

Composting is an effective method for stabilizing and valorizing pig manure, which is rich in nutrients but also contains heavy metals such as chromium (Cr). These heavy metals can promote the development of heavy metal resistance genes (MRGs) during composting, posing environmental and health risks. In this study, pig manure composting supplemented with pyridine carboxylate chromium was applied to investigate its effects on heavy metal speciation and MRG abundance and explore the influence factors of the dynamics of MRGs during composting. The results showed that the addition of Cr significantly influenced the composting process, including temperature fluctuations and nutrient dynamics. Specifically, the addition of Cr weakened the impact of water addition on temperature, as evidenced by the failure of the Cr-amended treatment to re-enter the thermophilic phase after water addition. The speciation of Cr changed during composting, with a significant reduction in high-bioavailable Cr forms (e.g., a 54.56% reduction in high-bioavailable Cr in the Cr-amended treatment) and an increase in low-bioavailable forms. The abundance of MRGs, particularly copper resistance genes, increased over time, with more pronounced fluctuations in the Cr-amended treatment. The primary factors influencing the dynamics of these MRGs during composting were identified as heavy metal speciation, microbial community structure, and specific physicochemical properties such as pH, electrical conductivity, and dissolved organic carbon. The present study offers valuable insights into the complex interactions between heavy metals and microbial communities during composting and provides inspiration for managing heavy metals to minimize the spread of MRGs.

1. Introduction

Composting has long been recognized as an effective method for the stabilization and valorization of organic waste, particularly in agricultural and livestock industries. Pig manure, a nutrient-rich byproduct of pig farming, is widely used as a feedstock for composting due to its high organic matter content and potential to improve soil fertility [1]. However, the presence of heavy metals in pig manure poses significant environmental and health risks. Heavy metals, such as chromium (Cr), copper (Cu), zinc (Zn), and cadmium (Cd), are often introduced into pig manure through feed additives and veterinary practices [2]. These metals can persist in the environment and promote the development of heavy metal resistance genes (MRGs) during the composting process [3]. MRGs can significantly disrupt microbial community structures, leading to ecological imbalances that reduce biodiversity, alter nutrient cycling, and compromise soil health [4]. This disruption may also enhance the resilience of pathogenic bacteria, exacerbating ecological and health risks through environmental contamination [5]. Therefore, understanding the dynamics of MRGs during composting is essential for developing sustainable waste management practices that minimize the environmental impact of heavy metals.
Cr is a heavy metal of particular concern due to its widespread use in animal feed and its potential toxicity. Cr exists in multiple oxidation states, with Cr(III) being less toxic and more stable than Cr(VI). The speciation and bioavailability of Cr in composting systems can influence microbial community structure and the fate of other heavy metals [6]. Recent studies have shown that Cr can alter the bioavailability of heavy metals, potentially affecting the abundance and distribution of MRGs during composting [7]. The valence state of Cr is also influenced by the presence of other heavy metals [8]. Additionally, Cr can interact with microbial communities, either by directly influencing microbial metabolism or by altering the physicochemical properties of the composting environment [9]. These interactions can lead to changes in the abundance and diversity of MRGs, as well as shifts in microbial community composition. However, a critical knowledge gap remains: the specific mechanisms by which Cr influences MRG dynamics—particularly in the context of real-world pig manure composting systems where antibiotic residues coexist—are still poorly understood. Moreover, despite growing evidence of co-selection between antibiotic resistance genes (ARGs) and MRGs, no study has systematically investigated how the interaction between Cr and antibiotics modulates MRG abundance and microbial community assembly during composting. Previous work has largely focused on single stressors (e.g., either Cr or antibiotics), overlooking the synergistic or antagonistic effects of their co-occurrence [10]. This limitation hinders our ability to assess the true environmental risk of MRG proliferation in livestock waste treatment. To address this gap, this study presents the first integrated investigation into the combined effects of chromium (as pyridine carboxylate Cr) and antibiotic residues on MRG dynamics during pig manure composting. Our work uniquely combines Cr speciation analysis, longitudinal monitoring of MRG abundance, microbial community profiling, and correlation analysis to elucidate the drivers of MRG enrichment under dual stressors.
In this study, it was hypothesized that the addition of Cr would significantly influence the dynamics of MRGs during the composting process. Furthermore, considering the co-presence of antibiotics in pig manure, we aimed to investigate potential synergistic or antagonistic interactions between Cr and antibiotic residues in shaping MRG abundance and microbial community structures. To test these hypotheses, we conducted a controlled composting experiment using pig manure and sawdust as feedstocks, with and without the addition of pyridine carboxylate chromium. The physicochemical properties of the composts, the speciation of Cr, and the abundance of MRGs over a 45-day period were detected. This study will provide valuable insights into the complex interactions between heavy metals and microbial communities during composting and contribute to the development of strategies for optimizing composting practices to minimize the environmental risks associated with heavy metal resistance genes.

2. Materials and Methods

2.1. Experimental Materials

Pig manure and sawdust were used as composting materials. Pig manure was collected from a pig farm in Xi’an City, Shaanxi Province, and the pigs were fed with gentamicin in the process of breeding. Sawdust was purchased online. The basic physicochemical properties of these materials are shown in Table 1. The composting was conducted in foam boxes with an outer dimension of 820 mm × 590 mm × 440 mm and an inner dimension of 680 mm × 450 mm × 350 mm. The seed germination index (GI) of the compost product was tested using wheat variety Zhongmai 174.

2.2. Experimental Setup and Implementation

Two treatments were set up: (1) PS: pig manure and sawdust in a dry weight ratio of 6:1; (2) PSC: pig manure and sawdust in a dry weight ratio of 6:1 with the addition of 100 mg/kg of Cr (pyridine carboxylate chromium, Cr(C6H4NO2)3, CAS 14639-25-9). The final C/N ratio for both treatments was approximately 25:1. Each treatment had three replicates, with each compost pile weighing 50 kg. This study did not impose artificial control on Cr speciation, as the objective was to simulate the natural transformation of pyridine carboxylate chromium from dietary supplements during practical composting.
After the pig manure and sawdust were mixed with a total mass of 300 kg and a moisture content of approximately 60%, the mixture was homogenized, and 150 kg was treated with pyridine carboxylate chromium. The treated and untreated mixtures were divided into three portions and placed into foam boxes. Temperature was measured using a thermometer inserted into the pile (approximately 20 cm deep). The pile was turned daily when the temperature exceeded 50 °C and every two days when it was below 50 °C. Water was added to a moisture content of 60% when the temperature dropped below 50 °C and 40 °C for the first time, respectively. Samples were collected on days 1, 3, 5, 7, 10, 18, 28, 35, and 45. Sampling involved selecting three random points in the pile, removing the surface layer, and collecting approximately 50 g of material from three different vertical positions. The samples were divided into four portions using the quartering method. One portion was stored at −80 °C for DNA extraction, while the others were stored at 4 °C, freeze-dried, and air-dried for heavy metal and other physicochemical property analyses.

2.3. Determination of Physicochemical Properties and Cr

Physicochemical properties, including moisture content, organic matter (OM), total nitrogen (TN), ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3−-N), dissolved organic carbon (DOC), pH, electrical conductivity (EC), and GI were determined using methods described in a previous study [11].
Heavy metal fractionation for Cr, Cu, Zn, Ni, and Cd was assessed using a sequential extraction procedure adapted from Shehata et al. with slight modifications [6]. Specifically, 0.5 g of air-dried samples were initially extracted with 25 mL of deionized water (shaken for 2 h, repeated three times) and subsequently with 25 mL of 0.5 M KNO3 (shaken for 16 h) to determine the highly bioavailable fraction (HB-HM), which includes adsorbed and exchangeable forms. The remaining residues were further extracted with 25 mL of 0.5 M NaOH (shaken for 16 h) and 25 mL of 0.05 M Na2EDTA (shaken for 16 h) to quantify the medium bioavailable fraction (MB-HM), encompassing organically bound and carbonate-precipitated forms. The low bioavailable fraction (LB-HM), comprising sulfide forms, was extracted using 25 mL of 4 M HNO3. The total metal content was extracted using a mixture of HNO3-HClO4-H2SO4 (4:1:1). After each extraction, the liquid supernatant was filtered through filter paper, and the metal concentrations in the filtrate were measured using inductively coupled plasma atomic emission spectrometry (ICP-AES, PE Optima 5300DV, Waltham, MA, USA). Hexavalent chromium was extracted and detected using Alkaline digestion—flame atomic absorption spectrophotometry.” The total trivalent chromium content was calculated by subtracting the hexavalent chromium content from the total chromium content.

2.4. DNA Extraction and High-Throughput qPCR

To investigate the microbial community structure in compost samples, DNA was extracted from approximately 0.5 g of each sample using the MPBIO FastDNA® SPIN Kit for Soil, following the manufacturer’s protocol. The DNA purity was assessed using NanoDrop, while Qubit fluorometry was employed to quantify the DNA concentration. The integrity of the extracted DNA was verified through agarose gel electrophoresis. Only high-quality DNA samples were used for subsequent high-throughput qPCR. The Wafergen Smartchip high-throughput qPCR system was then employed to detect MRGs. A total of 21 primer pairs were utilized to amplify 8 Cu resistance genes, 3 Cd resistance genes, 1 Cr resistance gene, 7 Zn resistance genes, 1 Ni resistance gene, and 1 16S rRNA gene. The specific primers are listed in Table S1. The PCR reaction mixture was prepared using a nanoliter-scale multi-sample dispenser (MSND) to dispense the mixture into the microchip wells, followed by qPCR amplification on the cycler. The 100 nL reaction mixture consisted of 50 nL of 2× Light Cycler 480 SYBR Green I Master Mix, 5 nL of each 10 mM primer, 20 nL of DNA template at 10 ng/μL, and 25 nL of water. The PCR amplification protocol included an initial denaturation at 95 °C for 10 min, followed by 40 cycles of denaturation at 95 °C for 30 s and annealing/extension at 60 °C for 30 s. The qPCR results were automatically analyzed using the instrument’s software. A Ct value of 31 was set as the detection threshold, and amplifications with efficiencies between 80% and 120% were considered positive. Additionally, a standard plasmid containing a 16S rRNA gene fragment (1.79 × 1010 copies/L) was serially diluted tenfold to create a six-point standard curve for quantifying target MGEs. Each concentration was replicated three times, and negative and positive controls were included. The absolute abundances of MRGs were calculated using the following formulas: relative copy number of MRGs = 10(31-Ct(MRGs)/(10/3)/10(31-Ct(16S)/(10/3); absolute copy number of MRGs = relative copy number × absolute copy number of 16S rRNA gene per gram of dry sample.

2.5. Bioinformatics Analysis and Data Processing

The raw sequencing data generated by the Illumina platform underwent stringent quality control and preprocessing. Specifically, primers were removed from the reads. Reads with an average quality score lower than 10 within a 23 bp window were eliminated. Additionally, reads exhibiting an average quality score below 15 and a length shorter than 150 bp were discarded. Subsequently, the remaining reads were merged into tags utilizing the Flash algorithm, allowing for an overlap length ranging from 10 to 200 bp and tolerating a mismatch rate of 0.05. Tags containing more than 3 ambiguous nucleotide bases (N) were excluded to ensure the generation of clean tags. These clean tags were then dereplicated and sorted according to their abundance using Usearch_v11. To mitigate noise and enhance computational efficiency, sequences with an abundance of fewer than 8 were removed. Operational taxonomic units (OTUs) were subsequently clustered at a 97% similarity threshold. Chimeric sequences were identified and removed using the de novo method. The representative sequences of the OTUs were aligned against a reference database via the RDP algorithm, employing a confidence threshold of 0.8 to annotate species information. The abundance of OTUs was subsequently mapped back to the clean tags to construct an OTU abundance table.
A partial least squares path model (PLS-PM) elucidating the influence of microbial composition, heavy metals, environmental factors, and gentamicin on the patterns of MRGs was developed in Excel 2020 (Microsoft Corporation, Washington, DC, USA), adhering to the methodology outlined by Henseler and Sarstedt [12]. The constructed model was subsequently visualized using PowerPoint 2020 (Microsoft Corporation, USA). Other statistical analyses and significance tests were performed using SPSS V.19 (IBM, Armonk, NY, USA), and graphs were plotted using OriginPro 8.5 (OriginLab, Northampton, MA, USA) and Excel 2019 (Microsoft, USA).

3. Results and Discussion

3.1. Changes in Physicochemical Properties During Composting

3.1.1. Temperature

Figure 1A shows the changes in pile and ambient temperatures during composting. The pile temperatures of both treatments, PS and PSC, exceeded 50 °C on the second day of composting, entering the thermophilic phase, which lasted for 10 days. The temperature of treatment PS reached 61 °C on the fourth day and peaked at 63 °C on the fifth day. For treatment of PSC, the temperature was 55 °C on the fourth day and peaked at 59 °C on the fifth day. When the pile temperatures of both treatments dropped below 50 °C on the 13th day, water was added to restore the moisture content to approximately 60%. Subsequently, the pile temperatures of both treatments increased again, with treatment PS exceeding 50 °C on the 15th day and maintaining this temperature for 6 days. Treatment PSC did not re-enter the thermophilic phase, with a peak temperature of 49 °C on the 18th day. These results indicate that the addition of Cr affected the composting process of pig manure and sawdust. On the 33rd day of composting, when the pile temperatures of both treatments dropped below 40 °C, water was added again to restore the moisture content to approximately 60%. The pile temperatures increased slightly thereafter, but the temperature fluctuations were small, with both treatments maintaining temperatures below 35 °C. By the 45th day, the pile temperatures of both treatments were below 30 °C. The results indicate that water addition is a crucial factor influencing temperature fluctuations during composting [13]. Specifically, the re-entry of treatment PS into the thermophilic phase after water addition highlights the significance of moisture management in maintaining optimal composting conditions. However, the addition of Cr significantly weakened the impact of water addition on temperature, as evidenced by the failure of treatment PSC to re-enter the thermophilic phase after water addition. This finding is consistent with previous studies suggesting that heavy metals can inhibit microbial activity, thereby affecting the heat generation during composting [14].

3.1.2. pH and EC

Figure 1B illustrates the changes in pile pH during composting. From the start of composting to the seventh day, the pH of both treatments PS and PSC significantly decreased, likely due to the production of organic acids during the initial stages of decomposition. Subsequently, the pH increased significantly on the tenth day and then gradually decreased, fluctuating around 8.2. This pattern suggests that the initial acidification was followed by a buffering effect as the composting process progressed, stabilizing the pH at a slightly alkaline level [13]. Figure 1C shows the changes in EC during composting. The EC of treatment PSC reached a peak of 0.84 ms/cm on the third day and then gradually decreased and stabilized. Treatment PS reached a peak of 0.98 ms/cm on the seventh day and then gradually decreased and stabilized. The addition of Cr in treatment PSC had a noticeable impact on EC, indicating that Cr may influence the ionic strength of the composting material, potentially affecting nutrient availability and microbial activity. This finding aligns with previous research demonstrating that heavy metals can alter the EC of composting substrates, which in turn affects the overall composting process and the quality of the final product [15].

3.1.3. Organic Matter and Total Nitrogen

Figure 1D shows the changes in OM content during composting. Initially, both treatments PS and PSC had high OM content. By day 3, OM content decreased significantly due to rapid aerobic fermentation during the high-temperature phase. As composting continued, OM content decreased more slowly, with a final reduction of 7.97% and 7.02% for PS and PSC, respectively. The addition of Cr had no significant effect on OM content, indicating that Cr primarily influences other aspects of composting rather than organic matter degradation. Figure 1E presents the changes in TN content. In the early stages, TN content decreased significantly in both treatments, likely due to ammonia volatilization and degradation of nitrogenous compounds [16]. However, Cr addition did not significantly affect TN content initially. In later stages, Cr increased TN content in the composted material, suggesting that Cr enhances nitrogen retention, possibly by stabilizing nitrogenous compounds or reducing nitrogen loss. This finding is supported by a meta-analysis study, which showed that additives, including heavy metals, can increase nutrient levels such as TN in the final compost products [17]. This highlights the potential role of Cr in improving compost quality by increasing nitrogen content. These findings suggest that while Cr does not significantly impact the degradation of OM, it can influence nitrogen dynamics, particularly in the later stages of composting.

3.1.4. Dissolved Organic Carbon

Figure 1F illustrates the changes in DOC content during composting. The DOC content in both treatments PS and PSC increased in the first 5 days, likely due to the initial breakdown of organic matter and the release of soluble carbon compounds. Subsequently, the DOC content decreased and then increased again on the 35th day before decreasing. In the early stages of composting, the DOC content differed significantly between the two treatments, with treatment PSC showing higher DOC content. This difference may be attributed to the significant impact of Cr addition on the microbial community structure, which influenced the consumption and generation of DOC [14]. As the composting process progressed and the microorganisms adapted to the composting environment, the differences in DOC content between the treatments decreased [18].

3.1.5. NH4+-N and NO3−-N

Figure 1G illustrates the changes in NH4+-N content during composting. In both treatments PS and PSC, the NH4+-N content increased significantly in the first 3 days, likely due to the rapid decomposition of organic nitrogen compounds and their subsequent mineralization to NH4+-N. On the seventh day, NH4+-N content decreased significantly, possibly due to nitrification processes converting NH4+-N to NO3−-N. NH4+-N content then increased again on the tenth day [19]. During this period, the addition of Cr had a significant impact on NH4+-N content in the compost, suggesting that Cr may influence microbial processes involved in nitrogen transformation. From the 18th day onwards, differences in NH4+-N content between the two treatments were not significant, with final values of 1.1 and 1.2 g/kg for PS and PSC, respectively. Figure 1H shows the changes in NO3−-N content during composting. By the end of composting, NO3−-N content in both treatments decreased significantly compared to initial values, with no significant differences between treatments, both around 55 mg/kg. In treatment PS, NO3−-N content decreased rapidly from an initial value of 84.2 mg/kg to 41.1 mg/kg on the seventh day, significantly lower than in treatment PSC. This indicates that the addition of Cr had a certain impact on NO3−-N content in the early stages of composting, possibly by affecting the rate of nitrification or denitrification processes [20].

3.2. Germination Index

Figure 1I illustrates the changes in the GI during composting. Throughout the composting process, the GI values for both treatments PS and PSC remained relatively high, ranging from 90% to 130%. This high GI indicates that the pig manure used was highly harmless and suitable for composting, reflecting effective detoxification processes. Initially, the GI of treatment PSC was higher than that of PS, likely due to the addition of pyridine carboxylate chromium, which may have positively influenced seed germination. This suggests that the presence of Cr in its initial form could enhance the biological safety of the composting material. However, after the 10th day, the GI of PS surpassed that of PSC, possibly due to changes in the valence state of Cr in the compost pile, which could have altered its toxicity to seeds [21]. This highlights the dynamic nature of heavy metals during composting, where their impact on plant growth can change over time, potentially due to shifts in their chemical forms. By the end of composting, the GI of PSC was higher than that of PS, with values of approximately 129% and 119%, respectively. This indicates that despite the initial influence of Cr, the final compost quality was comparable between treatments, emphasizing the importance of considering the long-term effects of amendments on compost maturity and safety.

3.3. Changes in Cr During Composting

Figure 2A–C show the changes in different forms of Cr during composting. Throughout the composting process, the concentration of different bioavailable forms of Cr in all treatments followed the order: medium bioavailable Cr (M-Cr) > low bioavailable Cr (L-Cr) > high bioavailable Cr (B-Cr). The B-Cr content in treatment PS did not change significantly before and after composting. In contrast, treatment PSC showed a significant reduction in B-Cr content, decreasing from 12.39 mg/kg to 5.63 mg/kg, a reduction of 54.56%. This reduction suggests that the addition of Cr can enhance the transformation of B-Cr to less bioavailable forms during composting [22]. For M-Cr, different trends were observed in different treatments. In treatment PS, the M-Cr content reached a peak on the fifth day, increasing by 222.24% compared to the initial value, and increased by 11.39% by the end of composting. In treatment PSC, the M-Cr content peaked on the 18th day and then decreased, with a final increase of 65.74% compared to the initial value. This indicates that the addition of Cr can significantly influence the dynamics of M-Cr, potentially through interactions with microbial communities or changes in the chemical environment of the compost pile [22]. For L-Cr, the content in treatment PS fluctuated during composting but did not change significantly by the end. In treatment PSC, the L-Cr content increased from 33.31 mg/kg to 69.52 mg/kg, an increase of 108.70%. This significant increase in L-Cr in treatment PSC suggests that the addition of Cr may promote the transformation of other Cr forms into L-Cr, which is less bioavailable and thus less likely to pose environmental risks.
Regarding different valence states, the Cr6+ concentration in treatment PS did not change significantly before and after composting, with a final value of 2.01 mg/kg. In treatment PSC, the Cr6+ concentration increased significantly after composting, reaching 46.05 mg/kg, an increase of 46.30%. This increase in Cr6+ in treatment PSC indicates that the addition of Cr can influence the oxidation state of Cr, potentially through redox reactions facilitated by microbial activity or changes in the composting environment [23]. The Cr3+ concentration increased significantly in both treatments after composting, with treatment PS increasing from an initial concentration of 7.03 mg/kg to 30.43 mg/kg (an increase of 331.02%) and treatment PSC increasing from 122.12 mg/kg to 202.31 mg/kg (an increase of 65.66%). This suggests that composting conditions favor the formation of Cr3+, which is generally less toxic and more stable than Cr6+.
For total Cr, the content increased significantly in all treatments after composting. Treatment PS increased from 8.23 mg/kg to 31.77 mg/kg (an increase of 286.03%), and treatment PSC increased from 153.59 mg/kg to 248.36 mg/kg (an increase of 61.70%). This increase in total Cr content is likely due to the concentration effect of composting materials, where the loss of water and volatile organic compounds leads to an increase in the concentration of heavy metals. This highlights the importance of monitoring total heavy metal content in compost products to ensure they meet environmental and agricultural standards.

3.4. Changes in Heavy Metal Resistance Genes During Composting

Figure 3A presents the abundance of MRGs during composting for various treatments. Notably, only Cu, Cd, and Zn resistance genes were detected, with Cu resistance genes being the most prevalent across all treatments. The abundance of MRGs in the fresh PM was particularly high, primarily due to Cu resistance genes with an absolute abundance of 3.6 × 108 copies g/dry weight. Among the Cu resistance genes, especially copA and cusA were observed, with values of 3.8 × 107 and 3.2 × 108 copies g−1 dry weight, respectively. This initial high load of these MRGs in PM could be attributed to the initial concentrations of Cu in the compost materials, as suggested by previous studies that have linked the abundance of MRGs to the availability of corresponding heavy metals [9]. The load of specific Cu resistance genes in PM suggests a baseline level of resistance that could influence subsequent changes during composting.
In the PS treatment, the abundance of MRGs generally increased over time, with a notable peak at day 35 for genes like copA and pcoB. This increase could be attributed to the selective pressure imposed by the composting environment, which may favor microbial populations harboring these resistance genes [24]. The PSC treatment, which included the addition of Cr, exhibited a more pronounced fluctuation in MRG abundance, particularly for Cu resistance genes, which rose significantly on the 45th day. This indicates that the addition of Cr can increase the selection pressure for Cu resistance, likely as a result of Cr’s impact on altering the microbial community structure and promoting the proliferation of Cu-resistant microbial populations. Similar to the effects of Cu addition on copper resistance, Cr seems to play a crucial role in shifting microbial ecosystems toward higher Cu tolerance [25].
According to the detailed examination of individual MRGs shown in Figure 3B, the abundance of copA in PS treatment increased from 1.3 × 106 copies g−1 dry weight on day 1 to 1.0 × 108 copies g−1 dry weight on day 35, before declining to 2.8 × 107 copies g−1 dry weight on day 45. But copA in PSC treatment showed a lower abundance than that in PS treatment, and it disappeared at the end of composting. This proved that the addition of Cr influenced the growth and survival of microbial communities harboring the copA gene. Conversely, the cusA gene, which was the most prevalent among the MRGs throughout the composting process, displayed a higher initial abundance in the PS treatment on day 1 compared to the PSC treatment. Nevertheless, by the end of the composting, the abundance of cusA in PSC had become higher. Similarly, the genes pcoB, pcoC, CDF, zosA, and zntA were also found to exhibit comparable patterns of change. This observation suggests that although the initial microbial community in PS appeared to be more pre-adapted to heavy metal resistance, the Cr amendment in PSC might have conferred a selective advantage to certain microbial populations carrying these genes [24]. This selective pressure could have favored the proliferation of these populations, resulting in their increased abundance in the final compost product. The cusC gene showed high abundance in both treatments on day 1, but was not detected after the thermophilic phase. This suggests that the initial conditions supported microbial populations with cusC, but the high temperatures of the thermophilic phase likely reduced these populations [25]. This finding highlights the potential of composting to reduce certain MRGs, mitigating ecological risks.

3.5. Influencing Factors of the Dynamics of Heavy Metal Resistance Genes During Composting

Figure 4 illustrates the relationships among latent variables within the internal model using a PLS-PM approach, focusing on the direct and indirect effects of different latent variables (gentamicin, environmental properties, microbial composition, heavy metals) on the explained variable (MRGs). The results indicate that the model has a good fit, with a model fit index of 0.583 and a coefficient of determination R2 of 0.801, suggesting a high level of model trustworthiness. The selected latent variables effectively account for the variations in MRGs during composting. Notably, environmental properties, microbial composition, and heavy metals have a significant impact on MRGs variations during composting (p < 0.05). Heavy metals, in particular, show the most pronounced direct effect, with a path coefficient of 0.829, contributing to a total influence of about 1.074. This underscores the potential for heavy metal management strategies to mitigate MRG dissemination. The direct effect of environmental properties on the distribution of MRGs is also substantial, with a coefficient of 0.649 and an overall effect of 1.160. This significant impact is largely mediated through its effects on heavy metals, microbial gentamicin, and microbial composition, with respective path coefficients of 0.898, 0.748, and 0.833. These findings indicate that changes in environmental conditions can significantly alter the bioavailability of heavy metals, thereby affecting microbial community structure and function [3,26]. This, in turn, can lead to changes in the abundance and distribution of MRGs. Notably, while antibiotic residues are known to co-select for MRGs during composting [10], gentamicin did not significantly impact MRG levels in this study, possibly due to the specific antibiotic and MRG types present.
Considering the significant impact of microbial composition, environmental properties, and heavy metals on MRGs, a further analysis was conducted to examine the relationships between individual MRGs and specific influencing factors. Figure 5A reveals that among copper resistance genes, copA, cusA, and cusB exhibit a significant negative correlation with Firmicutes (p < 0.05), and a positive correlation with Proteobacteria and Acidobacteria, suggesting that these MRGs are predominantly hosted by mesophilic bacteria. The higher abundance of these genes at the end of composting indicates that their microbial hosts are more likely to proliferate during the later stages of composting. However, reports have also documented the presence of these resistance genes in Firmicutes, indicating that composting conditions can influence the hosts of MRGs [27]. The initial high abundance of the cadmium resistance gene CDF is positively correlated with Firmicutes (p < 0.05). Similar findings have been reported by Yu et al. [28] and Parsons et al. [29], who also identified this gene in Firmicutes. CDF typically facilitates the transmembrane transport of Cd, moving it from the cytoplasm to vesicles or other cellular compartments, thereby reducing its toxicity to essential cellular biomolecules. The unique cell wall composition of Firmicutes, rich in peptidoglycan layers and teichoic acid walls, may partly explain its predominant role in intracellular transmembrane transport. For zinc resistance genes, zntA and zosA, which are more abundant, show a negative correlation with Firmicutes (p < 0.05). The gene zosA also shows a positive correlation with Proteobacteria. This is likely due to the significant increase in abundance of these resistance genes during the later stages of composting. The gene czcD was not detected during the thermophilic phase of composting and shows a significant negative correlation with Firmicutes and Acidobacteria (p < 0.05), while it is positively correlated with Proteobacteria and Plantomycetes, indicating that this gene is primarily hosted by mesophilic bacterial phyla.
It has been reported that the emergence of MRGs in the environment is related to the presence of heavy metals, although the types and abundance of MRGs are less associated with heavy metals and more closely related to microbial community structure and abundance [30]. However, as shown in Figure 5B, the Cu resistance genes in this study are significantly influenced by the composting properties, exhibiting a strong positive correlation with different bioavailable forms of Cu, Zn, and L-Ni, and a significant negative correlation with EC, TN, DOC, NH4+-N, and NO3−-N. The Zn and Cd resistance genes are also associated with pH and the presence of heavy metals, indicating that Cu-resistant bacteria are more susceptible to external environmental factors. Wang et al. [7] also found in pig manure compost that Cu and Zn resistance genes were significantly correlated with different forms of Cu, Zn, and pH, but not significantly related to temperature. However, in this experiment, Cu and Zn resistance genes showed a significant negative correlation with temperature, suggesting that the hosts of these resistance genes are more mesophilic bacteria. The thermophilic phase affected the growth of Cu and Zn-resistant bacteria, but after entering the cooling and maturation phases, both types of resistant bacteria proliferated extensively. This could have implications for the management of composting processes to minimize the spread of MRGs.

4. Conclusions

The present investigation elucidates the impacts of Cr on the composting process of pig manure, with particular emphasis on the interplay between MRGs, microbial composition, and physicochemical attributes. The findings show that Cr significantly affects the temperature and biochemical processes of composting. It also changes the availability of heavy metals, which in turn influences the abundance of MRGs. Notably, the transformation of Cr speciation throughout composting, marked by a decline in bioavailable forms, implies the capacity of composting to sequester and immobilize heavy metals, thus mitigating their ecotoxicological potential. The observed changes in MRG profiles, particularly the significant temporal fluctuations in copper resistance genes in the presence of Cr, highlight the complex interplay between heavy metal exposure and microbial adaptive responses. Our analysis goes beyond mere correlations to identify key factors influencing MRG. Key factors, including Cr speciation, microbial composition, pH, EC, and DOC, collectively shaped MRG dynamics. These findings provide practical guidance for managing resistance risks in composting: monitoring Cr transformation and key microbial indicators, along with optimizing operational parameters (e.g., via biochar amendment or aeration control), could help minimize the proliferation of resistance genes and enhance the environmental safety of compost products.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/fermentation11080472/s1, Table S1: Details of the qPCR primers for MRGs.

Author Contributions

Funding acquisition, G.Z., and Y.L.; project administration, G.Z.; supervision, Y.L.; writing—original draft, G.Z. and P.L.; writing—review and editing, Y.F. and Y.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Shaanxi Provincial Key Research and Development Program in 2025 (2025NC-YBXM-244), Internal Projects of Shaanxi Land Engineering Construction Group (DJNY2024-58) and the National Natural Science Foundation of China (No. 52400188). And The APC was funded by Ankang Branch of Shaanxi Agricultural Development Group Co., Ltd.

Conflicts of Interest

Author Guoqiang Zhao and Peng Li were employed by the Ankang Branch of Shaanxi Agricultural Development Group Co., Ltd. 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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Fermentation 11 00472 g001
Figure 1. Changes in physicochemical properties and GI during composting. (A) Temperature; (B) pH; (C) EC; (D) OM; (E) TN; (F) DOC; (G) NH4+; (H) NO3−; (I) GI. Key to acronyms: EC, electrical conductivity; OM, organic matter; TN, total nitrogen; DOC, dissolved organic carbon; NH4+-N, ammonium nitrogen; NO3−-N, nitrate nitrogen; GI, germination index.
Figure 1. Changes in physicochemical properties and GI during composting. (A) Temperature; (B) pH; (C) EC; (D) OM; (E) TN; (F) DOC; (G) NH4+; (H) NO3−; (I) GI. Key to acronyms: EC, electrical conductivity; OM, organic matter; TN, total nitrogen; DOC, dissolved organic carbon; NH4+-N, ammonium nitrogen; NO3−-N, nitrate nitrogen; GI, germination index.
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Figure 2. Changes in Cr in different forms during composting. (A) B-Cr; (B) M-Cr; (C) L-Cr; (D) Cr6+; (E) Cr3+; (F) total Cr. Different lowercase letters (a, b, c, d) indicate significant differences between treatments at p < 0.05.
Figure 2. Changes in Cr in different forms during composting. (A) B-Cr; (B) M-Cr; (C) L-Cr; (D) Cr6+; (E) Cr3+; (F) total Cr. Different lowercase letters (a, b, c, d) indicate significant differences between treatments at p < 0.05.
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Figure 3. The dynamics of MRGs during composting. (A) Abundance of different types of MRGs. (B) Abundance of different individual MRGs; the logarithm-transformed values of absolute abundance of MRGs are plotted.
Figure 3. The dynamics of MRGs during composting. (A) Abundance of different types of MRGs. (B) Abundance of different individual MRGs; the logarithm-transformed values of absolute abundance of MRGs are plotted.
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Figure 4. Partial least squares path models (PLS-PM) reflecting the direct, indirect, and total effects of different factors on MRGs patterns during composting. (A) PLS-PM; (B) The direct, indirect and total effects of different factors on MRGs. Significant and insignificant relationships between latent variables were presented by continuous and dashed arrows. The thicknesses of the arrows were proportional to the path coefficients (R2), which were indicated by * (p < 0.05), ** (p < 0.01). MRG, metal resistance genes; MICRO, microbial composition; HM, heavy metals; ENV, physicochemical properties.
Figure 4. Partial least squares path models (PLS-PM) reflecting the direct, indirect, and total effects of different factors on MRGs patterns during composting. (A) PLS-PM; (B) The direct, indirect and total effects of different factors on MRGs. Significant and insignificant relationships between latent variables were presented by continuous and dashed arrows. The thicknesses of the arrows were proportional to the path coefficients (R2), which were indicated by * (p < 0.05), ** (p < 0.01). MRG, metal resistance genes; MICRO, microbial composition; HM, heavy metals; ENV, physicochemical properties.
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Figure 5. Correlation analysis between individual MRGs and other influence factors. (A) relationship between MRGs and bacterial phyla. (B) relationship between MRGs and physicochemical properties. Continuous annotation variables show the relationship, with a darker color representing a greater correlation; *, p < 0.05; +/**, p < 0.01.
Figure 5. Correlation analysis between individual MRGs and other influence factors. (A) relationship between MRGs and bacterial phyla. (B) relationship between MRGs and physicochemical properties. Continuous annotation variables show the relationship, with a darker color representing a greater correlation; *, p < 0.05; +/**, p < 0.01.
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Table 1. Physicochemical properties of composting materials.
Table 1. Physicochemical properties of composting materials.
PropertyPig ManureSawdust
Moisture Content (%)43.04 ± 0.63-
pH8.51 ± 0.01-
EC (ms/cm)0.62 ± 0.02-
OM (%)70.21 ± 1.4783.35 ± 0.98
TN (%)1.76 ± 0.100.11 ± 0.01
DOC (%)1.65 ± 0.17-
NH4+-N (g/kg)2.72 ± 0.01-
NO3−-N (mg/kg)70.43 ± 0.15-
GI (%)98.58 ± 7.80-
Gentamicin Content (mg/kg)556.35 ± 2.61-
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MDPI and ACS Style

Zhao, G.; Li, P.; Feng, Y.; Liu, Y. Chromium-Driven Changes in Heavy Metal Resistance Genes During Pig Manure Composting. Fermentation 2025, 11, 472. https://doi.org/10.3390/fermentation11080472

AMA Style

Zhao G, Li P, Feng Y, Liu Y. Chromium-Driven Changes in Heavy Metal Resistance Genes During Pig Manure Composting. Fermentation. 2025; 11(8):472. https://doi.org/10.3390/fermentation11080472

Chicago/Turabian Style

Zhao, Guoqiang, Peng Li, Yao Feng, and Yuanwang Liu. 2025. "Chromium-Driven Changes in Heavy Metal Resistance Genes During Pig Manure Composting" Fermentation 11, no. 8: 472. https://doi.org/10.3390/fermentation11080472

APA Style

Zhao, G., Li, P., Feng, Y., & Liu, Y. (2025). Chromium-Driven Changes in Heavy Metal Resistance Genes During Pig Manure Composting. Fermentation, 11(8), 472. https://doi.org/10.3390/fermentation11080472

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