Microbial Bioindicators for Monitoring the Impact of Emerging Contaminants on Soil Health in the European Framework

Abstract

Antibiotic resistance (AR) is recognized by the World Health Organization as a major threat to human health, and recent studies highlight the role of microplastics (MPs) in its spread. MPs in the environment may act as vectors for antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs). Bacterial communities on the plastisphere, the surface of MPs, are influenced by plastic properties, allowing ARB to colonize and form biofilms. These biofilms facilitate the transfer of ARGs within microbial communities. This study analyzed data from the LUCAS soil dataset (885 soil samples across EU countries) using the Emu tool to characterize microbial communities at the genus/species level. Functional annotation via PICRUSt2, supported by a custom tool for Emu output formatting, revealed significant correlations between the genera Solirubrobacter, Bradyrhizobium, Nocardioides, and Bacillus with pathways linked to microplastic degradation and antibiotic resistance. These genera were consistently present in various soil types (woodland, grassland, and cropland), suggesting their potential as bioindicators of soil health in relation to MP pollution. The findings underscore MPs as hotspots for ARB and ARGs, offering new insights into the identification of bioindicators for monitoring soil health and the ecological impacts related to MP contamination.

1. Introduction

Maintaining healthy soil is essential for sustaining ecosystems and promoting agricultural productivity across different types of land use. However, practices related to land management and the presence of emerging pollutants can severely degrade soil quality, hinder plant development, and disrupt the delivery of critical ecosystem functions [1]. For instance, the Food and Agriculture Organization (FAO) estimates that soil degradation affects approximately 33% of the world’s soils, resulting in annual global agricultural productivity losses worth around USD 40 billion. The document accompanying the proposed EU Soil Directive [2] estimates the impact assessment costs related to soil degradation and the consequent loss of ecosystem services to be EUR 68.8 billion per year (upper value of quantified costs), excluding contaminated sites and when sustainable management practices are not implemented, or EUR 292.4 billion per year (upper value of quantified costs). More than 60% of soils in Europe are considered to be unhealthy due to current management practices, pollution, urbanization, and the effects of climate change. Land use disturbances are mainly the result of anthropogenic pressure affecting soil microbial diversity and leading to substantial changes in microbial community composition [3,4]. These disturbances alter the composition of soil functional groups, which in turn, modify biogeochemical cycles (e.g., carbon (C) and nitrogen (N)) [5], with cultivated lands showing greater biodiversity than natural ones, like forests, possibly due to increased soil disturbance [6]. Therefore, land use intensification significantly impacts the structure of soil microbial communities to preserve optimal soil health, and agricultural practices should prioritize sustainable intensification [7].

Different land uses, particularly in agricultural soils, can result in varying levels of emerging pollutants, including microplastics (MPs) and agrochemical residues. These changes disrupt the intricate relationships between the soil and microorganisms, intensifying risks to soil health and undermining the sustainability of agricultural systems [8]. For example, the introduction and widespread use of synthetic petrol-based plastic materials have significantly impacted the world, with global plastic production hitting 360 million tons in 2018 [9]. Plastics accumulate in the environment due to low recycling rates and their persistent nature. In agricultural settings, microplastics can enter the soil through multiple pathways, including the use of plastic mulching films, the application of sludge and compost containing plastic particles, and irrigation with water contaminated by microplastics [10]. These particles then break down further into micro- (>200 µm) and nano-plastics (>20 µm), posing additional challenges for soil ecosystems [11]. Conventional MPs and nanoplastics can significantly modify the soil’s physical attributes, such as structure porosity, bulk density, and water content, as well as its chemical characteristics, including pH, organic matter, nutrient levels, and the presence of contaminants like toxic metals or organic pollutants. The accumulation of microplastic pollution in agricultural systems poses substantial risks to both ecosystems and human health [12] and has negative impacts on agricultural productivity and food security [13]. Until now, due to the lack of longer-term field trials and the unrepresentative concentrations of microplastics that may not reflect the true condition of agricultural soil [11], the impacts of microplastic pollution on agricultural productivity are largely unquantified and unreliable. A decrease in crop yields of 11–24% has been found in agricultural soils with a high concentration of microplastic residues in the soil [14].

The large use of inorganic and organic fertilizers is an important contributor to microplastic concentrations in agricultural soils [13]. Moreover, microplastics in agricultural soils can become airborne through wind erosion, agricultural activities, or tillage practices, potentially contributing to air pollution and impacting respiratory health in humans and animals. Studies have indicated that airborne microplastics are now found in remote areas, highlighting their ability to travel long distances and enter the atmosphere [15]. Additionally, microplastics from agricultural soils can leach into water bodies through runoff or irrigation practices, contributing to the contamination of freshwater and marine ecosystems. Once in aquatic environments, especially oceans, microplastics can disrupt food webs, harm aquatic organisms, and serve as vectors for pollutants, such as heavy metals and persistent organic chemicals [16,17]. Studies by de Souza Machado et al. (2018) [18] and Lozano et al. (2021) [19] have clarified the complex impacts of MPs on soil properties, including bulk density, water-holding capacity, aggregation, pH, and nutrient retention. Moreover, MPs can absorb and transfer other pollutants, potentially leading to bioaccumulation and toxicity along food chains [20].

For example, microplastics can introduce both antibiotics and antibiotic-resistant bacteria into the soil, acting as carriers for these emerging pollutants [21]. This occurs because microplastics can absorb antibiotics and serve as surfaces for biofilm formation, where resistant bacteria can thrive and accumulate [22]. The hydrophobicity, surface roughness, and chemical composition of plastics further enhance bacterial adhesion and create microenvironments that promote horizontal gene transfer, facilitating the spread of antibiotic resistance genes within these biofilm communities [23]. Consequently, these particles enhance the persistence and mobility of antibiotic resistance within soil ecosystems, intensifying environmental and agricultural health risks [24]. Li et al. (2024) reported how MPs can impact the distribution and abundance of antibiotic resistance genes (ARGs) in soil–vegetable systems [25]. Moreover, MPs facilitate the propagation of ARGs through horizontal gene transfer mechanisms. Recent investigations by Caruso (2019) [26] and Yan et al. (2020) [27] have highlighted the capacity of MPs to adsorb various ARGs, potentially facilitating their movement to deeper soil layers and even groundwater.

Thus, agrochemical residues, from pesticides to fertilizers and antibiotics (ABs), can accumulate in soils, leading to adverse effects on soil microbiota and ecosystem functioning [28,29]. Indeed, research by Huang et al., (2019) [30], Fei et al., (2020) [31] and Zhou et al., (2021) [32] has highlighted the significant influence of MPs on soil bacterial communities and their associated functions, as MPs create hotspots for microbial activities.

Antibiotics (ABs), antibiotic-resistant bacteria (ARB), and antibiotic resistance genes (ARGs) have emerged as significant environmental concerns due to their widespread contamination, primarily resulting from the overuse of these substances in human and veterinary medicine [33]. When ABs are only partially metabolized in treated organisms, they are excreted in human and animal waste, continuously introducing them into aquatic and soil ecosystems through wastewater treatment facilities, biosolids, and agricultural practices [34]. As a result, ABs are considered pseudo-persistent organic pollutants (pseudo-POPs) [35], and their biocidal effects can severely disrupt the diversity of natural microbial communities, impairing critical ecosystem functions [36]. Furthermore, ABs can accelerate the spread of ARBs and ARGs in the environment. Recognized as a critical threat within the One Health framework [37,38], ARGs underscore the need for a comprehensive understanding of how various soil types, such as woodlands, grasslands, and croplands, interact with emerging pollutants. This knowledge is essential for developing sustainable agricultural practices and effective pollution mitigation strategies to protect soil health, ensure food security, and promote long-term environmental sustainability, particularly concerning the impact of microplastics (MPs) on soil systems, which are recognized as a critical threat within the One Health framework.

The interplay between MPs and soil health, particularly in the context of ARG dissemination across European soils, has gained significant attention in recent years.

The monitoring of these emerging soil contaminants is complex, costly, and time-consuming. Furthermore, there is a lack of political guidelines that regulate these pollutants, in terms of standard thresholds or methods [39,40]. The identification of indicators, especially microbial ones for a rapid assessment of soil health could be the way forward [41,42].

Soil microbial communities and their analyses, thanks to their plasticity, can provide a solution through the identification of so-called bioindicators [43]. Commonly, a group of microorganisms whose function, population, or status can reveal the qualitative status of an environment is considered a bio-indicator. However, the definition of soil health is still unclear [44,45].

Within this study, the LUCAS soil database, containing bacterial DNA sequences from 885 soil samples across 23 countries of the European Union and the United Kingdom with multiple vegetation covers and associated land uses [46], was analyzed with the homology alignment likelihood software Emu [47], which has a higher resolution for genus/species classification. To perform the function annotation, a custom pipeline was applied to merge the Emu output with the functional prediction of PICRUSt2 [48]. This research aimed to (i) compare the impact of different soil coverages on potential MP degradation pathways at a European scale and (ii) propose microbial genera suitable to be used as bioindicators to assess soil health in terms of MP pollution within soil characterized by different land uses. Furthermore, based on the results obtained, a systematic data mining analysis of the scientific literature was conducted to evaluate the current state of research on this topic, identify existing gaps, and emphasize the significance of considering these bacterial genera as bioindicators of soil health in relation to antibiotic and microplastic pollution.

2. Materials and Methods

2.1. The LUCAS Soil Dataset and Data Retrieval

The dataset includes 16S rRNA and ITS raw DNA sequences for 885 samples collected as part of the Land Use/Cover Area Frame Survey (LUCAS) soil in 2018 [49]. For this study, raw 16S rRNA gene DNA sequences were retrieved from the NCBI Sequence Read Archive (SRA) database under the BioProject ID PRJNA952168. Following the same scheme used in the work of Labouyrie et al. (2023) [46], the official LUCAS land cover nomenclature was used, consisting of three primary land cover types: cropland, grassland, and woodland. For more information on the soil samples, refer to Table S1.

2.2. Taxonomic Classification of Soil Microbial Communities

The raw fastq files were filtered using “cutadapt” v4.4 and classified with Emu (https://gitlab.com/treangenlab/emu; accessed on 1 December 2024), selecting the short reads options (--sr) and using the SILVA database (version 138.1).

A custom workflow was created ad hoc and used to format the Emu output for the functional annotation (Section 2.3). Briefly, the R library “tidyverse” was used to manipulate the Emu output and create an OTU-like table. A consensus sequence was created by aligning all the sequences with the same tax_id with Clustal Omega v1.2.4 and then creating a consensus sequence from the multiple alignment using EMBOSS v6.6.0.0. Both the OTU-like table and the consensus sequences were used for the functional prediction.

2.3. Microbial Communities Functional Annotation with PICRUSt2

The software Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2, Version 2.4.2; https://github.com/picrust/picrust2; accessed on 1 December 2024), which can predict the function of a bacterial community according to the proportion of marker gene sequences in the samples, was used to infer the approximate functional potential of microbial communities.

2.4. Statistical Analysis and Visualization

Network analyses were performed to visualize correlations between ARGs, MP degradation genes, and soil microbial genus relative abundances. Spearman’s rank correlations (ρ > 0.75 and p < 0.01) were used to build a correlation matrix. The network analyses were performed in the R environment using the “Hmisc” package, and the network visualization was conducted on the interactive platform of Gephi. The plots were generated using RStudio v 2023.12.1+402 with the library “ggplot2”. To identify the specific bacterial genera shared among the defined sample groups, a Venn diagram was constructed in the R environment using the “VennDiagram” package. Random forest (RF) was performed in the R environment using the “randomForest” package to determine the role of ARGs, MP degradation genes, and microbial community structure in the identification of microbial indicators. The statistical significance was set at p < 0.05.

2.5. Data Mining

A systematic search was conducted in the Scopus database using the query “microplastic* AND ((arg* OR (antibiotic AND resistance)) AND (Bacillus OR Solirubrobacter OR Roseiarcus OR Nocardioides OR Bradyrhizobium)”, yielding a total of 25 items. The Scopus .csv file containing all relevant information about the selected articles, including bibliographic details and abstracts, was imported into R Studio (version 2024.12.0+467) for further processing and analysis. The Bibliometrix package within the R Studio environment was utilized for the analysis [50]. A bigram co-occurrence network analysis was conducted to elucidate the relationships between key concepts and themes. The Walktrap clustering algorithm was employed with a maximum of 100 nodes to identify the predominant topics and their interconnections. Raw data, along with the .csv file with information about the selected articles, are provided in the Supplementary Materials section.

3. Results

3.1. Microplastic Degradation Genes Occurrence in the European Framework

The identification of the potential genes involved in microplastic degradation was conducted by inferring the data obtained from the analysis with the one stored in the PlasticDB [51], which contains 753 species of microorganisms that were reported in the scientific literature to have plastic-degrading capabilities and 219 genes coding for proteins described to break down plastics. It is updated bimonthly, finding the presence of 47 different genes (Figure S1). The most abundant gene of MP degradation pathways was the faaH-5 gene (involved in styrene degradation), followed by HDG (involved in styrene degradation), nthA (involved in styrene and benzoate degradation), and catE (involved in styrene, benzene, and xylene degradation). Among these four genes, the catE gene is the most central to microplastic degradation, as it encodes an essential protein for the breakdown of xylene, styrene, and benzene, while the other three genes are only involved in secondary processes in styrene degradation. Interestingly, the presence of the catE gene was significantly different (p < 0.05; Table S2) among the three categories of soil considered in this work (Figure 1), in particular between Forest-Grassland and Forest-Cropland. Indeed, the significantly higher presence of the catE gene in Cropland and Grassland compared to Forest suggests that there is a higher presence of pollution in terms of microplastics.

3.2. Identification of Potential Microbial Indicators

The identification of potential microbial indicators requires selecting bacterial genera that not only respond to key environmental pressures, such as microplastic degradation and antibiotic resistance, but also persist across diverse soil types. Venn diagrams provide a clear visualization of genera that are unique to specific samples (Crop, Grassland, and Forest) or shared across multiple environments, revealing a notable overlap of genera between different land uses (Figure 2). This overlap is crucial, as it highlights genera that are consistently present in all examined soil types, indicating their potential as reliable indicators of soil health. Interestingly, the analysis conducted in this study showed that six bacterial genera (Acidothermus, Bacillus, Bradyrhizobium, Candidatus Udaeobacter, Massilia, and Solirubrobacter) are common in all soil samples. These genera, persisting across crop, grassland, and forest soils, represent a foundational set of bacteria with the potential to serve as consistent indicators of soil health under varying environmental conditions.

The network analysis (Figure 3) showed the co-occurrence of MP degradation genes, ARGs, and microbial genera found in the different soils, highlighting taxa based on strong correlations (−0.75 < r > 0.75, p < 0.01) with other community members or functions. The network showed a modularity index of 0.9, suggesting that nodes were closely related to the ones belonging to the same cluster. Indeed, a high modularity index indicates that there are clusters or groups of nodes (i.e., ARGs, MPs, or microbial genera) that tend to co-occur in specific environments or conditions, potentially reflecting distinct micro-habitats or specific functionalities. Moreover, it may suggest that there are well-defined ecological niches within the system under analysis, where groups of microorganisms fulfill specific roles and interact more closely with each other than with other groups. Interestingly, four main modules were identified in the co-occurrence network: module 1 (modularity class: 9.67%, orange); module 2 (modularity class: 5.06%, light blue); module 3 (modularity class: 3.77%, light pink); and module 4 (modularity class: 3.35%, pink).

Module 1 (Figure 3, orange) showed the presence of Solirubrobacter and Nocardiodes genera that have a positive correlation with both some ARGs (vanSAc, vanRAc, oleC4, feaB, tetV, etc.) and some genes involved in MP degradation (dmpD, feaB, gtcA, gtcB, and catE). Module 2 (Figure 3, light blue) showed the presence of Gaiella, Acidothermus, and Bryobacter related to ARGs (especially multidrug/efflux pumps, such as tolC and oprM). Module 3 (Figure 3, light pink) showed the genus Bradyrhizobium with a positive correlation with some ARGs (bpeF, bpeE, hydr, adeA, and adeB) and some genes involved in microplastic degradation (pht5, pct, brl3397). Finally, Module 4 (Figure 3, pink) showed the presence of Bacillus with a positive correlation with ARGs (tetB, tet35, mph, and abcA) and the gene pht4, which is involved in phthalate degradation.

3.3. Random Forest

The RF analysis made it possible to identify the top potential contributors (e.g., microbial indicators) related to microplastic degradation and ARGs in soil communities. The objective was to determine which bacterial genera play key roles in these processes and could be considered reliable indicators of soil pollution linked to ARGs and microplastics. The RF model showed a remarkable fit between the predicted and observed values, indicating a strong linearity in the model’s predictions (Figure S2). This strong correlation between the predicted and actual values suggested that the model was highly effective in capturing the relationship between microbial community structure and functional gene abundance. This high predictive accuracy is crucial in determining reliable bioindicators, as it ensures that the taxa identified by the model have a strong, consistent association with the functional traits of interest, namely the presence of ARGs and the potential to degrade microplastics. The most important microbial genera in explaining the variation in ARG and microplastic degradation functions were identified based on their increase in node purity (IncNodePurity) values, as shown in Figure 4. The IncNodePurity metric measures the reduction in node impurity each time a variable is used to split a decision tree, and higher values indicate greater importance in predicting the outcome. Three genera stood out prominently in their contributions to the model: Roseiarcus, Solirubrobacter, and Nocardiodes. Roseiarcus genus emerged as the most important predictor in the RF model.

3.4. Data Mining

The results obtained from the microbial community structure analysis, the functional predictions, and the RF model were used as input for a data-mining analysis. This analysis aimed to assess the actual presence of the key genera highlighted by these studies (e.g., Roseiarcus, Solirubrobacter, Nocardiodes, Bacillus, and Bradyrhizobium) as potential microbial indicators for soil quality, specifically in relation to microplastic pollution and ARG presence.

Interestingly, Roseiarcus does not appear in the literature to be associated with key terms related to pollution (e.g., ARGs and microplastics). This challenges its potential use as a bio-indicator for these pollutants. Thus, the bigram co-occurrence network (Figure 5) refers to Bacillus, Bradyrhizobium, Nocardioides, and Solirubrobacter only. The bigram co-occurrence network highlighted the interconnection between two words and grouped them in clusters according to the pertinence of the topic. Moreover, the co-occurrence network further supports the potential of Bacillus, Nocardioides, Bradyrhizobium, and Solirubrobacter as soil microbial indicators for microplastic and ARG pollution, since different keywords found in the green cluster refer to soil environments.

4. Discussion

The results presented in this work were in line with other works. For example, the results followed the same trend as the work of Dulya et al. (2024), which characterized the occurrence of ARGs in European soils, reporting an increase in ARG abundance (30–43%) in croplands compared to other land cover types, and in grasslands compared to coniferous forests [52]. These contaminants not only provide surfaces for bacterial adhesion but also facilitate horizontal gene transfer among microorganisms, enabling the rapid spread of ARGs. Additionally, microplastics can enhance bacterial mobility by acting as vehicles that transport resistant strains across different environments. As a result, microplastics contribute to the widespread dissemination of ARB, posing significant challenges to public health and environmental management. Their persistence and accumulation in ecosystems further exacerbate the risks associated with the transfer of resistance traits to other microbial communities.

Despite the European community’s efforts to introduce regulations to mitigate the spread of antibiotics in agroecosystems, the use of organic fertilizers as amendments and the excessive use of antibiotics in veterinary practices for livestock still result in a continuous introduction of these contaminants into the soil [53,54]. The presence of microplastics in the soil can exacerbate the issue of antibiotic resistance, which is also challenging to monitor and to establish threshold values that can be measured and reported in the soil [55]. Identifying potential microbial indicators that are sensitive to the presence of microplastics in soil (and indirectly to ARGs) could, thus, provide more reliable and measurable tools to assess soil health. Indeed, the results shown in Figure 3 (e.g., the network analysis) identify some potential microbial indicators, such as the microbial genera Nocardioides, Solirubrobacter, Gaiella, Bryobacter, Bradyrhizobium, and Bacillus.

The genus Nocardioides is already well-known for its ability to degrade various compounds, including microplastics, particularly in soils that are more affected by anthropogenic impact. Indeed, research on Nocardioides [56] has demonstrated its capability to degrade various pollutants across four distinct categories: aromatic compounds, hydrocarbons and haloalkanes, nitrogen heterocycles, and polyester pollutants like nitrophenol, cotinine, ritalinic, and polylactic acid. For instance, Nocardioides sp. KP7 harbors benzene-ring degradation genes, including phdA, phdB, phdC, and phdD, encoding enzymes facilitating degradation to phthalates using phenanthrene as a carbon source. The Solirubrobacter genus has been identified in diverse environments, such as soils, biocrust, rhizosphere habitats of various crops, and medicinal plants [57]. It is suggested that Solirubrobacter species could serve as pioneering organisms that facilitate microbiome development in plant rhizospheres, thereby contributing significantly to maintaining the health of host plants in environmentally challenging conditions. However, it has been demonstrated that Solibrubacter can also act as a carrier of ARG [58]. Furthermore, in the study by Zhang et al. [59], it is shown that the presence of MPs positively selects for this genus, making it a key bacterium in terms of indicators for both antibiotic resistance and the presence of microplastics in the soil.

Interestingly, the Gaiella genus was found to be negatively correlated to ARGs in the network, which is probably due to its association with antibiotic degradation [60]. On the other hand, Bryobacter was identified as a biomarker for microplastics by Li et al., [61]. As a biomarker for microplastics, Bryobacter was shown to be exclusive to soils exposed to low doses of microplastics, highlighting its potential as an indicator of microplastic contamination. As a type of reducing bacterium, Bryobacter plays a crucial role in various soil processes, including the reduction of pollutants like the polyethylene (PE) plastic additive Benzophenone-3, which can affect soil nutrient cycling. Its presence in microplastic-exposed soils suggests that it may also be involved in mitigating or modifying the impacts of microplastics on nitrogen cycling. [62]. However, although Wan et al. [63] found Bryobacter to be associated with antibiotic resistance genes (ARGs), few studies have reported a link between Bryobacter and ARGs.

Bradyrhizobium is known as one of the main nitrogen-fixing genera capable of forming symbiotic nodules in legumes. The study by Meng et al. [64] suggested that Bradyrhizobium could serve as an indicator of microplastic presence, but limited studies have investigated the effects of microplastics on the relative abundance of the Rhizobiaceae family (e.g., Bradyrhizobium), making it challenging to draw clear conclusions regarding rhizosphere nitrogen fixation bacteria and common bean root nodulation under microplastic pollution. Furthermore, in the study by Zhu et al., 2022 [65], certain actinobacterial and proteobacterial members, including Sinomonas, Amycolatopsis, Nocardia, Bradyrhizobium, and Burkholderia–Caballeronia–Paraburkholderia, were significantly enriched after exposure to PVC. Specifically, Nocardia, Burkholderia, and Bradyrhizobium have been associated with the degradation of phthalates or linked to phthalate degradation.

The genus Bacillus has long been recognized as one of the primary carriers of antibiotic resistance genes, often encompassing various classes of antibiotics, and is also associated with multidrug resistance phenomena, being capable of harboring plasmids with different associated resistance genes [66,67,68]. In fact, the correlation found in the network with the mph gene (associated with macrolide resistance), tet genes (associated with tetracycline resistance), and the abcA gene (linked to multidrug resistance) is well documented in the literature [69,70]. Moreover, the presence of correlation with the pht4 gene, responsible for microplastic degradation, also suggests some association between the Bacillus genus and the so-called plastisphere. Indeed, in the work of Yi et al. [71], the ability of Bacillus cereus to colonize plastic particles was shown, providing extra surfaces for the adhesion of the bacteria and thereby promoting the growth of Bacillus cereus cells. Moreover, other works [72,73] reported the ability of Bacillus sp. to use polymers as the only carbon source to survive and degrade plastics. In summary, the structural and functional potential analysis of soil communities has highlighted different key potential bioindicators of soil quality in relation to microplastic pollution and ARG.

Moreover, some of these genera were also found to contribute to microplastic degradation functions from the random forest analysis, in particular, Roseiarcus, Solirubrobacter, and Nocardioides. The Roseiarcus genus emerged as the most important predictor in the RF model. Although less well-studied compared to the other two genera, Roseiarcus is related to the alphaproteobacterial methanotrophs but differs due to its unique metabolic pathways and environmental adaptations and could play a significant role in microbial community dynamics in polluted environments [74,75]. Its strong association with both ARGs and microplastic degradation functions in our model makes it a promising candidate for further investigation as a bioindicator. Consistently highlighted across different types of soil, Solirubrobacter has been shown to have broad ecological versatility. Its strong association with the functional genes related to ARGs and microplastic degradation indicates that this genus is highly responsive to environmental stressors, making it a robust indicator of soil quality. Its presence in diverse soil environments [76] reinforces its potential as a reliable bioindicator across different land uses. Nocardioides was also identified as one of the key genera associated with pollution-related functions, as it is already well-known for its role in degrading recalcitrant compounds, including microplastics. This genus is particularly notable for its presence in soils impacted by anthropogenic activity, and its involvement in breaking down complex pollutants aligns well with the focus of this study on identifying taxa linked to microplastic degradation [56,77].

The RF model highlighted their functional importance and potential to serve as indicators of soil health and pollution levels. Specifically, their ability to degrade microplastics and their association with ARGs suggest that they could be valuable for future monitoring programs aimed at assessing the effects of anthropogenic activities on soil ecosystems.

The consistency of these genera across different soil types—croplands, grasslands, and forests—further supports their utility as broad-spectrum bioindicators. Their presence in diverse environments, coupled with strong correlations with relevant functional genes, makes them ideal candidates for long-term soil health monitoring, particularly in areas facing increasing pollution pressure.

Finally, data mining has allowed for the assessment of the status of these potential microbial indicators in the literature, helping to identify the most “robust” ones as potential indicators, as they may already be well-known, and uncover hidden connections with specific keywords.

Interestingly, both microplastics and ARGs were in the center of the bigram network (Figure 5) and strongly connected and coordinated two different clusters. This is in line with what was discussed above, as microplastics are increasingly recognized as hotspots for bacterial colonization and biofilm formation, which can significantly contribute to the spread of ARGs [78]. Their large surface area and hydrophobic properties create an ideal environment for microbial attachment, enabling bacteria to form dense biofilms [79,80]. Within these biofilms, horizontal gene transfer is facilitated, allowing for the rapid exchange and accumulation of ARGs among bacterial communities.

The connection between the identified clusters and the violet cluster (Figure 5), representing the incidence of bacterial biofilms on microplastic particles, reinforces the idea that microplastics act as vectors for ARG proliferation [81]. Once bacteria adhere to microplastics, the particles can easily be transported across different environments, potentially spreading ARGs to new locations, including soils and aquatic systems [82,83]. This highlights the critical role that microplastic contamination plays in exacerbating the global issue of antibiotic resistance, making it a priority for both environmental monitoring and remediation efforts. Interestingly, the “aged microplastics” keywords seemed to connect the violet cluster with the green one, suggesting that the persistence of microplastics in the environment could increase the incidence of ARGs. Indeed, it has been shown that microplastics’ aging process remarkably altered their surface properties, including increasing specific surface areas, causing the formation of oxygen-containing groups and changing the surface morphology, which further increased the probability of microbial colonization [84,85]. Thus, the co-occurrence network further supports the potentials of Bacillus, Nocardioides, Bradyrhizobium, and Solirubrobacter as soil microbial indicators for microplastic and ARGs pollution, since different keywords found in the green cluster refer to soil environments.

5. Conclusions

The results presented in this work aim to collect and summarize the metagenomic data on European soils gathered during the 2018 LUCAS soil campaign. The reported analyses allowed for the identification and definition of potential microbiological indicators to monitor soil health concerning contaminants still classified as emerging, specifically microplastics and antibiotic resistance. Indeed, the genera Bacillus, Nocardioides, Bradyrhizobium, and Solirubrobacter are candidates to be potential microbiological indicators due to their ubiquitous presence in all types of soils and their co-occurrence to MP-degrading genes and antibiotic resistance genes. This study seeks to contribute additional data in alignment with European initiatives like the Soil Mission, the proposed Soil Health Directive, and the Soil Monitoring and Resilience Act. The aim is to provide policymakers with innovative tools to advance the regulation and monitoring of soil health, particularly for contaminants that are not yet formally regulated by the European Union. Finally, the combined analysis of microplastic concentration and particle size obtained for different soil samples, along with metagenomic data, will permit evaluation of the impact of microplastics on soil microorganisms and their functions under different soil types and agro-climatic conditions, as well as to develop sustainable microbiome-based solutions to microplastic soil pollution and soil, plant, and human health.