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Article

General Soil Properties Modulate Bacterial Community Tolerance to Clarithromycin in Laboratory-Spiked Agricultural Soils

by
Laura Rodríguez-González
1,2,*,
Manuel Arias-Estévez
1,2,3,
Montserrat Díaz-Raviña
3,4,
Juan José Villaverde
3,4,
David Fernández-Calviño
1,2,3 and
Vanesa Santás-Miguel
1,2,5
1
Área de Edafoloxía e Química Agrícola, Departamento de Bioloxía Vexetal e Ciencia do Solo, Facultade de Ciencias, Universidade de Vigo, Campus As Lagoas s/n, 32004 Ourense, Spain
2
Instituto de Agroecoloxía e Alimentación (IAA), Universidade de Vigo, Campus Auga, 32004 Ourense, Spain
3
Comunidades Microbianas de Suelos (id. UA 1678), MBG-CSIC/Universidad de Vigo, Associated Unit to CSIC, Avda de Vigo s/n, 15705 Santiago de Compostela, Spain
4
Departamento de Suelos, Biosistemas y Ecología Agroforestal, Misión Biológica de Galicia (MBG-CSIC), Avda de Vigo s/n, 15705 Santiago de Compostela, Spain
5
Section of Microbial Ecology, Department of Biology, Ecology Building, Lund University, SE-22362 Lund, Sweden
*
Author to whom correspondence should be addressed.
Agriculture 2026, 16(12), 1312; https://doi.org/10.3390/agriculture16121312 (registering DOI)
Submission received: 11 May 2026 / Revised: 11 June 2026 / Accepted: 12 June 2026 / Published: 13 June 2026
(This article belongs to the Section Ecosystem, Environment and Climate Change in Agriculture)
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Abstract

Clarithromycin is a widely prescribed macrolide antibiotic that can enter soils using sewage treatment plant effluents, where it is frequently detected. Because it could exert selective pressure on soil microbes, this study examined whether bacterial communities in 12 agricultural soils developed tolerance to clarithromycin after 42 days of exposure to different clarithromycin concentrations (7.8 mg kg−1–2000 mg kg−1). Results showed that tolerance increased in a clear dose-dependent manner and was significantly higher than in control soils at concentrations of 31.3 mg kg−1 and above. Soil characteristics also shaped the response. At lower clarithromycin doses, tolerance was restricted in those soils with higher values of eCEC, clay content, organic carbon, and C/N ratio. At higher doses, tolerance increased with pH, likely due to increased clarithromycin bioavailability. This study provides evidence of the impact of clarithromycin on soil microbiota and suggests that contamination by this antibiotic may promote the development of bacterial tolerance. Future studies should be carried out to further clarify the factors that influence the development of tolerance and also to determine the possible spread of this resistance in the environment.

Graphical Abstract

1. Introduction

Antibiotics are widely used worldwide to treat infectious diseases. Their consumption has increased in recent decades to reach levels of 34.3 billion defined daily doses in 2023 [1]. Most of the antibiotic administered is not metabolised in the human body and 30% to 90% is excreted [2] in its original form or as secondary metabolites [3,4,5]. Excreted antibiotics from domestic and hospital use become part of the wastewater and reach wastewater treatment plants (WWTPs). The WWTPs’ processes were not designed to reduce antibiotics in their effluents, so antibiotics can be found in their water and sludge [6,7,8], being the main sources of antibiotics entering the environment [9,10,11]. Specifically, antibiotics enter the soil by applying WWTP effluents for irrigation or as amendments in crop fields [11,12,13].
Antibiotics and their metabolites entering soils affect the structure and diversity of natural bacteria and cause changes in their basic functions, such as the degradation of organic matter [14,15,16,17]. In addition, the pressure exerted by any pollutant on the microbiota of an ecosystem can lead to the development of tolerance to that pollutant [18]. The arrival of antibiotics in the soil could make soil an environmental source of antibiotic resistance [19]. Tolerance can be propagated in the environment, including through plasmid exchange between bacteria from phylogenetically distant groups [20] and even transmitted to humans [21,22]. The emergence and spread of antibiotic-resistant bacteria present significant risks to human health and have become a serious global concern [23], as the development of new antibiotics has not progressed rapidly enough to address these challenges [24].
Macrolide antibiotics are the third most prescribed antibiotic family worldwide [25] and have been classified by the World Health Organisation as critical antimicrobials of the highest priority [26]. One of the most commonly prescribed macrolide antibiotics is clarithromycin (CLA). CLA is an amphoteric molecule, as it can exist as a cation, zwitterion, and anion depending on the pH, due to its two dissociation constants of 9 and 12.5 [27]. CLA is among the top 100 most commonly used pharmaceutical compounds [28]. Its frequent use and the fact that 38–46% of CLA consumed is excreted in urine [29] have resulted in CLA being detected in sewage treatment plants around the world [30,31,32]. The frequent detection of CLA in WWTP effluent, and the fact that CLA exhibits moderate affinity for the solid phase with a Kd value ranging from 2.5 to 10.5 L kg−1 [33], indicates that CLA can either bind to WWTP sludge or remain in a mobile state in dissolved phases that reach rivers and soils used for irrigation, posing a high potential environmental risk [34,35,36].
Once in the soil, CLA can exhibit different environmental behaviours. The moderate CLA affinity for the solid phase results in intermediate environmental mobility compared to other antibiotics such as tetracyclines, fluoroquinolones, and sulphonamides [33]. Furthermore, in the upper soil layers, CLA may be degraded through photochemical and photocatalytic degradation [37]. CLA is also susceptible to oxidation and can be persistent under the anaerobic conditions found in sludge and anoxic soils [36]. Due to all these factors, the half-life of CLA in soil can vary depending on the soil type, ranging from 10 to 1000 days [38,39]. However, the transformation products of CLA, synthesis intermediates and subproducts can also be biologically active [29]. Those products are difficult to detect, so the full mass load of the antibiotic is not known [40]. Despite this detected problem, studies that have evaluated the adverse effects of CLA antibiotic in the environment are scarce and mostly limited to aquatic environments [41]. The few studies on the soil matrix have shown that CLA antibiotic is toxic to soil bacteria [42] and that it is capable of modifying microbial structure [43,44]. Once it is known that CLA perturbs bacterial communities in soils, the next logical question is whether these perturbations lead to the development of antibiotic tolerance. Some recent studies have addressed this issue by considering only one soil type or/and in mixture with other antibiotics [45,46,47].
Based on previous evidence, we hypothesised that CLA contamination would induce tolerance in soil bacterial communities, and that the extent of tolerance would depend on antibiotic concentration and key soil properties. Accordingly, this study tested whether the antibiotic CLA could lead to tolerance development in 12 agricultural soil samples showing a gradient of carbon (C) content and pH and at 6 different antibiotic concentrations (7.81–2000 mg kg−1) 42 days after application using the Pollution-Induced Community Tolerance (PICT) method. PICT method assesses tolerance at the community level without identifying the specific bacterial taxa responsible for this response. The specific objectives were as follows: (1) to evaluate whether soil contamination with CLA induces tolerance in bacteria; (2) to examine tolerance variations according to antibiotic concentration; and (3) to detect influences of physicochemical soil characteristics on antibiotic tolerance. The wide range of agricultural soils and antibiotic concentrations in this study will make the findings of this study provide critical insights into the effects of CLA antibiotics entering soil ecosystems and contribute to defining safe threshold levels of contamination.

2. Materials and Methods

2.1. Chemical Products

The antibiotic CLA with CAS 81103-11-9 and purity of 95% and talc with CAS 14807-96-6 were provided by Sigma-Aldrich (Steinheim, Germany). Dimethyl sulphoxide (C2H6OS) (DMSO) with purity ≥ 99.9% and CAS 67-68-5 was provided by Fisher ChemicalTM (Pittsburgh, PA, USA).

2.2. Soil Samples

For this study, 12 soils were selected from different cultivation areas of the northwestern Iberian Peninsula (Galicia), not previously treated with sewage sludge. Each sample was composed of 10–20 subsamples from the high 20 cm of depth collected by the Edelman probe. The number of subsamples depended on the number of probe insertions required to obtain roughly the same amount of soil. The subsamples were mixed to form a homogeneous sample, air-dried and sieved through a 2 mm mesh sieve. This sampling methodology, including the number of subsamples and the depth, was consistently applied to all 12 soils to ensure methodological comparability. They were then stored in polypropylene jars until laboratory use. The physicochemical and mineralogical characteristics of each soil were analysed according to the methods described in [42], where the results of the analyses can also be consulted, as well as in Table 1 of this study. As the study focused on the influence of soil physicochemical properties on the response to CLA, microbiological parameters were not included in the initial soil characterisation.

2.3. Experimental Design

The 12 study soil samples were moistened to 70% of their water-holding capacity and incubated in darkness at 22 °C for 15 days, sufficient time for the stabilisation of the microbial community [48].
After the incubation period, the PICT method was used to study the development of CLA tolerance in soils. This method evaluates whether CLA contamination induces an increase in tolerance at the bacterial community level as a collective functional response of the bacteria present in the soil, although without identifying the specific bacterial taxa involved in this response. The PICT method consists of two distinct phases. The first phase of PICT was contamination. To this end, each of the 12 soil samples was homogenised and fractionated into 24 parts of 5 g each to be dry contaminated, in triplicate, with 6 concentrations of CLA (0, 7.81, 31.25, 125, 500, and 2000 mg kg−1). The wide range of CLA concentrations used in this study, including values above those typically detected in the environment [30,49], was selected to capture the full tolerance response across soils with contrasting properties and to identify tolerance thresholds, following common approaches in ecotoxicological studies [16,42,45,50]. The CLA dilutions were prepared using talc, ensuring the same amount of dry matter was added to each microcosm (4 mg dilution per gram of dry soil). For the control (0 mg kg−1), only talc was added without CLA. Talc has been widely used as a carrier for the application of antibiotics and other compounds in soil-contamination studies [42,50,51], including studies with CLA in which no relevant interactions with this antibiotic have been reported [52,53]. The respective CLA dilution, or only the talc for control, was thoroughly mixed with the soil by hand using a spoon to ensure an even distribution throughout the soil sample. This resulted in 288 microcosms (12 soils × 8 concentrations × 3 replicates). After mixing the soil with the antibiotic, the microcosms were incubated in darkness at 22 °C for 42 days to provide sufficient time for the possible development of tolerance [54,55]. This incubation period was also based on previous findings showing that soil bacterial communities fully recovered from CLA toxicity within 42 days [42]. During the incubation period, moisture levels were monitored by weighing the samples and distilled water was added when necessary to maintain the initial moisture level.
In the second phase of the PICT, the bacterial suspension was extracted from each microcosm as explained in the study [42]. Then, the bacterial suspension obtained from each microcosm was divided into 10 aliquots (1.35 mL). Each aliquot was added 0.15 mL of a different concentration of CLA (0, 0.01, 0.03, 0.1, 0.5, 2.0, 7.8, 31.3, 125 and 500 mg L−1 final concentration in the 1.5 mL). Due to the low solubility of CLA in water, DMSO was used. First, a mother dissolution of 5000 mg L−1 was made by dissolving 0.02 g of CLA in 2.5 mL of DMSO and then adding 1.5 mL of distilled water. From that dilution, serial 1:4 dilutions were made by adding 1 mL of the previous dilution in 2.6 mL of distilled water plus 0.4 mL of DMSO.
The tritium-labelled leucine incorporation method [56,57] was used to quantify bacterial growth. Briefly, a known amount of tritium-labelled leucine was added to each sample and incubated for 2 h for the bacterial community to incorporate the leucine. After this time, bacterial growth was stopped with trichloroacetic acid. After several washing cycles, the radioisotopes incorporated in each sample were counted using a liquid scintillation analyser (Tri-Carb 2810 TR, PerkinElmer, Waltham, MA, USA). The data were obtained in disintegrations per minute (DPMs).
The sequence of ten DPM values of each microcosm (one value for each concentration of CLA added in liquid) was divided by the DPMs of its blank (sample with only water and DMSO without antibiotic). These relative values, representative of bacterial growth, were plotted against the added CLA concentration to obtain dose–response curves. For each dose–response curve, the concentration at which bacterial growth was reduced by half (Log EC50) was calculated using the following logistic model:
Y = c/[1 + eb(a−x)]
where Y represents Leu incorporation (bacterial community growth) for each antibiotic concentration; x is the logarithm of the antibiotic concentration; a is the Log EC50 value; b is a parameter related to the slope of the inhibition curve; and c is the bacterial growth rate in the control sample (without antibiotic).
Higher Log EC50 values indicate higher concentration of antibiotic required to achieve the same level of bacterial growth inhibition. This would mean increased bacterial tolerance to CLA. The three replicates performed yielded mean Log EC50 values ± SD.
The increase in tolerance from uncontaminated soils to soils with antibiotics was expressed in logarithmic value in order to plot in a more proportionate way. First, the inverse logarithm of the Loc EC50 values were made to obtain the EC50 values, then the EC50 of the uncontaminated soils was subtracted of the EC50 of the contaminated soils, lastly, the logarithm of the resulting difference was taken. Therefore, the formula was calculated as Log ΔEC50 (Log ΔEC50 = Log (EC50 contaminated − EC50 uncontaminated)). In cases where the ΔEC50 value was 0 or negative and the logarithmic value could not be calculated, a small positive value was assigned, interpreted as no tolerance development.

2.4. Statistical Analysis

KaleidaGraph software 4.0 (Synergy Software, Reading, PA, USA) was used to plot the dose–response curves and obtain the Log EC50 values according to the model explained above. Log EC50 values were analysed using linear mixed-effects models (LMM), considering CLA concentration as a fixed effect and soil as a random effect to account for variability among soils. Pairwise comparisons among concentration levels were performed using Bonferroni-adjusted post hoc tests to control for multiple comparisons. In addition, Pearson’s correlation coefficient was used to detect correlations of Log ΔEC50 values with soil characteristics. Statistical analyses were performed using SPSS Statistics 25 software (IBM, Armonk, NY, USA).

3. Results and Discussion

Dose–response curves were obtained for all soils and the CLA doses at which they were contaminated (Figure 1). Along the curve, bacterial growth decreased as the amount of CLA added increased, creating sigmoidal-shaped curves. These curves fitted well with the logistic model (R2 ≥ 0.9), allowing for the calculation of the Log EC50 value of each curve (Table S1, Supplementary Material).

3.1. Bacterial Tolerance to CLA in CLA-Contaminated Soils

The Log EC50 values of the control soils from the 12 soil samples ranged from 1.17 ± 0.11 to 2.14 ± 0.10 (mean Log EC50 = 1.75). Relative to the control curves, most of the curves of the CLA-contaminated soils shifted to the right in most soils and appeared to shift further to the right the more they were contaminated with CLA (Figure 1). The rightward shift of the curves resulted in higher Log EC50 values (Table S1, Supplementary Material). The higher the Log EC50 value, the higher the concentration of antibiotic required to achieve the same level of bacterial growth inhibition. This would mean increased bacterial tolerance to CLA. Specifically, Log EC50 values of soils contaminated with 7.8 mg kg−1 ranged between 2.28 ± 0.23 and 1.46 ± 0.07 (mean Log EC50 = 1.84), with 31.3 mg kg−1 between 2.28 ± 0.07 and 1.55 ± 0.12 (mean Log EC50 = 1.94), with 125 mg kg−1 between 2.28 ± 0.07 and 1.55 ± 0.12 (mean Log EC50 = 1. 94), with 125 mg kg−1 between 2.43 ± 0.06 and 1.63 ± 0.06 (mean Log EC50 = 2.00), with 500 mg kg−1 between 2.65 ± 0.08 and 1.86 ± 0.05 (mean Log EC50 = 2.26) and with 2000 mg kg−1 between 2.82 ± 0.18 and 1.93 ± 0.03 (mean Log EC50 = 2.43).
According to the linear mixed-effects model (LMM), no statistically significant differences were detected between control soils and those contaminated with 7.8 mg kg−1 (p = 1.00) (Table S2). Nevertheless, at the other CLA concentrations (≥31.3 mg kg−1), Log EC50 values were statistically higher than the control Log EC50 values. Specifically, it was statistically higher at 31.3 mg kg−1 (p < 0.05), 125 mg kg−1 (p < 0.05), 500 mg kg−1 (p < 0.01) and at 2000 mg kg−1 (p < 0.01).
These results reveal a clear dose-dependent increase in bacterial tolerance to CLA, indicating that increasing antibiotic concentrations progressively select for more tolerant microbial communities. This pattern suggests that CLA acts as a selective pressure in soil environments, promoting shifts in bacterial responses even at sub-inhibitory concentrations. In a previous study on CLA toxicity in the same soils [42], the 10% inhibition concentration for the bacterial community exceeded 7.8 mg kg−1 in half of the soils. Therefore, although in this study no statistically significant differences were observed at the lowest concentration tested (7.8 mg kg−1), the observed trend towards increased tolerance suggests that a shift towards a more CLA-tolerant bacterial community could occur below the toxic effect threshold.
Previous studies have evaluated the effect of antibiotic concentration on the development of resistance. Ref. [58] found higher abundance of tetracycline antibiotic resistance genes at higher tetracycline concentrations in feedlot lagoon water. A higher abundance of tetracycline resistance genes at higher concentrations was also found in soils adjacent to feedlots in the study of [59], in which tetracycline concentrations ranged from 1.3 to 95.3 µg kg−1. However, the antibiotic ciprofloxacin in soils caused a higher abundance of resistance genes at doses of 0.04 and 0.4 mg kg−1 than at doses of 4 mg kg−1 [60]. Concerning our study antibiotic, dose-dependent CLA tolerance was also found by [45,47] who observed higher resistance genes to antibiotics after the application of CLA to the soil in conjunction with two other macrolide antibiotics at 10 mg kg−1, a dose close to the lowest concentration of CLA tested in our study (7.8 mg kg−1). However, other studies that irrigated soils with CLA (0–1 mg kg−1) did not detect alterations in microbiota or resistance genes, possibly because the microbial communities were already adapted or the concentrations were not sufficient to generate changes.
Importantly, the variability observed in this study among soils at each concentration level suggests that factors beyond antibiotic dose contribute to tolerance development. This highlights the potential role of soil properties in modulating CLA bioavailability and microbial responses, which is further explored in the following section.

3.2. CLA Tolerance by Soil Characteristics

The results of the linear mixed-effects model indicated that, in addition to the concentration of CLA contamination, soil properties also influenced CLA tolerance (σ2 > 0). Accordingly, the increment of CLA tolerance (Log ΔEC50) was calculated for each soil and contamination concentration (Table S3, Supplementary Material) to explore possible correlations of tolerance increase and soil characteristics. The Log ΔEC50 values confirmed the high variability in tolerance development between soils. While in some soils the tolerance increase (Log ΔEC50) (Figure 2) was not noticeable up to the CLA concentration of 500 mg kg−1, in other soils the tolerance increase was more than 1.5 log units at the lowest CLA concentration (7.8 mg kg−1). It should be noted that the increase in Log ΔEC50 did not follow a strictly linear trend in all soils, particularly in soils 6 and 12. The Log ΔEC50 values were calculated as Log (EC50 contaminated − EC50 uncontaminated). In cases where the EC50 of the contaminated soil was equal to or lower than that of the uncontaminated control, the ΔEC50 value was zero or negative and the logarithm could not be computed. Under such conditions, a small positive value was assigned, interpreted as no tolerance development. This substitution likely contributed to the deviations from linearity observed at intermediate CLA concentrations in soils 6 and 12. Furthermore, since Log ΔEC50 values are derived from fitted dose–response curves and subsequent logarithmic transformation, small methodological variations in EC50 estimation may be amplified in the final values. Therefore, the observed soil-specific deviations most likely reflect the combined effect of the ΔEC50 substitution procedure and analytical variability rather than biologically distinct responses.
The soil characteristics that conditioned the development of CLA tolerance varied according to the concentration of contamination (Table S4, Supplementary Material). At lower CLA concentrations in the soils (≤31.3 mg kg−1), tolerance to CLA (Log ΔEC50) decreased with higher content of eCEC (R2 = 0.57; p < 0.05), clay (R2 = 0.42; p < 0.05), C (R2 = 0.63; p < 0.05) and with C/N ratio (R2 = 0.42; p < 0.05). A high eCEC value increases the amount of adsorption sites available for ionic compounds in soil colloids [61]. The eCEC influences the mobility and retention of various contaminants in soil, such as heavy metals, pesticides and drugs [62,63,64]. For antibiotics, this phenomenon has been observed in multiple studies, including ciprofloxacin and other fluoroquinolones [65,66]. The main soil colloids such as organic matter and clays play a fundamental role in the adsorption of antibiotics in soils [67,68]. In this sense, the CLA present in the soil could be adsorbed on the soil organic matter since the deprotonated sites of the organic matter can facilitate the retention of the positively charged antibiotic [69,70]. CLA retention in the soil could also be higher the higher the clay content as clay has a large specific surface area [71], which means a larger area available for interaction with CLA. Therefore, lower C and Clay contents in soils generate greater CLA bioavailability in soil dissolution, which will result in greater toxicity in soil bacteria [42] and could favour the selection of CLA-tolerant bacteria. The tolerance of bacterial communities to CLA can also be influenced by C/N ratio since this factor is one of the most influential in the structure and activity of the soil microbial community [72]. The high C/N ratio, and therefore bioavailable N limitation in the soil, could favour the presence of some types of microorganisms that extract the N typically locked in the organic matter such as ammonia-decomposing and -oxidising micro-organisms [73,74]. Such nitrifying and denitrifying bacteria are often more resistant to antibiotics such as the bacterial genera Truepera and Micropruina [75].
At higher CLA concentrations in the soil, the adsorption of the antibiotic decreases, indicating lower retention in soil colloids and greater bioavailability in the soil solution [70]. This suggests that, at these high concentrations, adsorption sites could become saturated, reducing their capacity to retain CLA [67]. At elevated CLA concentrations in this study (>125 mg kg−1), other factors could significantly influence the behaviour and fate of this antibiotic, shaping its effects on soil microbial communities. In particular, bacterial tolerance to CLA increased with higher soil pH, especially at concentrations of 500 mg kg−1 (R2 = 0.43, p < 0.05) and 2000 mg kg−1 (R2 = 0.68, p < 0.001). CLA is a weakly basic molecule [76] and is more soluble in acidic conditions [76,77]. However, higher soil pH could reduce the adsorption of CLA onto soil colloids and organic matter, thereby increasing the concentration of bioavailable CLA in the soil solution. At higher pH values, soil colloids generally exhibit more negative charges, which could decrease the retention of CLA in soils [78]. Consequently, bacteria could be exposed to higher concentrations of bioavailable CLA, increasing the selective pressure exerted by the antibiotic and favouring the selection of CLA-tolerant microorganisms [79]. In addition, higher soil pH has also been associated with an increased abundance of antibiotic resistance genes in soils [80], which could further enhance the persistence and spread of resistant bacteria in these environments. Therefore, both soil characteristics and CLA dose are key factors influencing the development of tolerance in soil bacterial communities.
These findings highlight the importance of soil characteristics and CLA dose in shaping bacterial tolerance but also raise questions about the specific mechanisms by which soil bacteria adapt to CLA exposure. The mechanisms that may be involved in bacterial adaptation to CLA exposure in the studied soils are likely diverse and could vary according to the intensity of antibiotic selective pressure. At relatively low CLA concentrations, mechanisms requiring lower physiological cost for bacteria, such as antibiotic efflux, are likely to be sufficient to tolerate antibiotic exposure, whereas higher CLA concentrations could contribute to favouring additional resistance mechanisms associated with reduced antibiotic susceptibility [81,82]. In particular, at low concentrations of CLA contamination (≤125 mg kg−1), mechanisms associated with antibiotic efflux may contribute to bacterial tolerance, as efflux pumps are commonly involved in macrolide resistance [83,84]. The association of antibiotic efflux with macrolide resistance occurs particularly when encoded by the acquired mefA gene [83]. The mef subfamily of efflux pumps confers resistance primarily to 14- and 15-membered macrolides, including CLA [85]. Ref. [46] detected an increase in the abundance of efflux-related resistance genes at low CLA concentrations, although these concentrations were lower than the lowest concentration used in the present study (7.8 mg kg−1). At the higher contamination concentrations (≥500 mg kg−1), other resistance mechanisms previously associated with macrolide resistance, such as antibiotic inactivation by hydrolysis of macrocyclic lactones by esterases [86], or target-site modification mediated by erm genes [85,87,88], could also contribute to bacterial tolerance. These findings suggest that CLA contamination of soil could contribute to the selection of bacterial populations carrying different resistance mechanisms, not only to CLA but also to other macrolide antibiotics and even to other classes of antibiotics at high contamination concentrations. This would alter the structure of soil microbial communities and ecosystem functions. In addition, the association of erm genes with mobile genetic elements raises the possibility of horizontal dissemination of macrolide resistance among soil bacteria [87,89].

4. Conclusions

The results of this study evidence that CLA contamination in soil can induce antibiotic tolerance, which represents an ecological and health risk. Tolerance occurs at doses as low as 7.8 mg kg−1 in some soils. When all soils are considered together, the dose from which the Induced Tolerance Level was observed was 31.3 mg kg−1. These findings demonstrate that the PICT approach can effectively detect community-level tolerance thresholds relevant for environmental risk assessment. Having established that CLA exposure triggers a measurable increase in tolerance, future research should focus on identifying the microbial taxa and resistance mechanisms underlying this response, for which amplicon or metagenomic sequencing would be necessary.
The results of this study show a large variation in the development of CLA tolerance between the different soils, suggesting that soil characteristics may influence the bacterial response to the antibiotic. Especially, at CLA addition concentrations ≤ 125 mg kg−1, tolerance to CLA decreased with increasing factors associated with its retention in soil (eCEC, clay, C and C/N ratio), suggesting that CLA may be less bioavailable when interacting with soil colloids. Under these conditions, low-level resistance mechanisms (such as antibiotic efflux) would be sufficient to confer resistance, explaining the lack of differences observed. At CLA contamination concentrations > 125 mg kg−1, saturation of soil adsorption sites increased the amount of CLA in the solution, making CLA tolerance statistically higher than in the control soils. At these concentrations, higher soil pH correlated with higher bacterial tolerance, possibly due to lower CLA retention in higher pH soils. In addition, at these high concentrations, tolerance mechanisms that generate a high level of resistance, such as CLA inactivation or modification of binding sites, are likely to have predominated, which could lead to cross-resistance to other antibiotics.
From an environmental risk assessment perspective, these findings indicate that the potential of CLA to induce tolerance at environmentally relevant concentrations (low µg kg−1 range) is limited under most scenarios. However, in cases of localised high contamination (e.g., spills or repeated sludge application), tolerance development and potential cross-resistance to other macrolides cannot be ruled out. The strong influence of soil-specific properties on tolerance development further suggests that risk assessments for antibiotic contamination in soils should be site-specific rather than based solely on threshold concentrations.
Given the large variation in the effects of CLA on soil microbiota depending on soil characteristics and contamination concentration, further studies assessing the environmental impact are required to establish a better understanding of the possible determinants of these effects and to establish critical contamination thresholds.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agriculture16121312/s1, Table S1: Log EC50, error, and R2 values determined using the Pollution-Induced Community Tolerance (PICT) approach to assess bacterial toxicity to clarithromycin in 12 soils polluted with varying concentrations of the antibiotic (0, 7.8, 31.3, 125, 500, and 2000 mg kg−1), Table S2: Statistical results of the comparison between Log EC50 of soils contaminated with different concentrations of clarithromycin in mg per kg of soil, Table S3: Increase in Log EC50 values (Log Δ EC50 = Log EC50 contaminated soil − Log EC50 control soil) as a function of clarithromycin antibiotic concentration added (7.8, 31.3, 125, 500 and 2000 mg kg−1) in 12 agricultural soils after 42 days of antibiotic addition, Table S4: R2 values of correlation of the increase in clarithromycin antibiotic tolerance indices (Log Δ EC50 = Log EC50 contaminated soil − Log EC50 control soil) with soil characteristics in 12 agricultural soils after 42 days of the addition of different concentrations of clarithromycin (7.8 mg kg−1–2000 mg kg−1) and correlation significance according to Pearson’s correlation test.

Author Contributions

Conceptualization, M.A.-E., M.D.-R. and D.F.-C.; methodology, L.R.-G., J.J.V. and V.S.-M.; formal analysis, D.F.-C. and M.D.-R.; investigation, L.R.-G. and V.S.-M.; resources, M.A.-E.; data curation, L.R.-G. and V.S.-M.; writing—original draft preparation, L.R.-G. and V.S.-M.; supervision, D.F.-C., M.A.-E. and M.D.-R.; project administration, M.A.-E.; funding acquisition, M.A.-E. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the Spanish Ministry of Science, Innovation, and Universities through projects RTI2018-099574-B-C21 and RTI2018-099574-B-C22 (FEDER Funds). Vanesa Santás Miguel holds a postdoctoral fellowship (ED481D-2025/012) funded by the Xunta de Galicia. Laura Rodríguez González was supported by a pre-doctoral fellowship (FPU21/04206) from the Spanish Ministry of Universities. The authors would like to recognise the financial support of the Consellería de Cultura, Educación e Universidade (Xunta de Galicia) through the contract ED431C 2025/43-GRC granted to the research group BV1 of the University of Vigo.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviation

The following abbreviation is used in this manuscript:
CLAClarithromycin

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Agriculture 16 01312 g001
Figure 1. Dose–response graphs of the bacterial growth in 12 soils polluted with 6 different concentrations (0, 7.8, 31.3, 125, 500 and 2000 mg kg−1) of the antibiotic clarithromycin (CLA).
Figure 1. Dose–response graphs of the bacterial growth in 12 soils polluted with 6 different concentrations (0, 7.8, 31.3, 125, 500 and 2000 mg kg−1) of the antibiotic clarithromycin (CLA).
Agriculture 16 01312 g001
Agriculture 16 01312 g002
Figure 2. Increase in Log ΔEC50 values (Log EC50 = Log (EC50 contaminated soil − EC50 uncontaminated) as a function of clarithromycin (CLA) antibiotic concentration added (7.8, 31.3, 125, 500 and 2000 mg kg−1) in 12 agricultural soils after 42 days of antibiotic addition.
Figure 2. Increase in Log ΔEC50 values (Log EC50 = Log (EC50 contaminated soil − EC50 uncontaminated) as a function of clarithromycin (CLA) antibiotic concentration added (7.8, 31.3, 125, 500 and 2000 mg kg−1) in 12 agricultural soils after 42 days of antibiotic addition.
Agriculture 16 01312 g002
Table 1. Mean values (n = 3) of the general characteristics of the soils analysed.
Table 1. Mean values (n = 3) of the general characteristics of the soils analysed.
SoilCroppHWpHKClC (%)N (%)eCEC
(cmolc kg−1)		DOC
(mg kg−1)		Sand (%)Silt (%)Clay (%)USDA ClasificationWRB ClasificationFeo (g kg−1)Alo (g kg−1)
1Vineyard5.64.20.60.065.9120612513Sandy loamRegosol1.30.7
2Vineyard5.64.93.60.2619.5263691714Sandy loamUmbrisol3.55.8
3Vineyard5.64.81.60.186.02243443423LoamUmbrisol2.21.0
4Vineyard6.15.32.80.2337.2265612118Sandy loamUmbrisol3.64.4
5Vineyard5.74.94.80.4017.3332582021Sandy clay loamsUmbrisol2.85.3
6Vineyard5.54.26.50.4910.5350661321Sandy clay loamsUmbrisol5.53.1
7Corn4.84.43.10.375.2633701812Sandy loamUmbrisol1.82.1
8Corn4.64.22.40.283.233677149Loamy sandsUmbrisol1.62.2
9Corn4.13.73.30.344.359981109Loamy sandsUmbrisol2.31.8
10Corn5.24.73.20.414.1327552817Sandy loamUmbrisol8.93.1
11Corn5.65.13.40.4411.2356453322LoamUmbrisol8.13.8
12Corn5.14.56.80.595.5318343828Clay loamUmbrisol8.98.7
pHW is pH measured in water; pHKCl is pH measured in 0.1 M KCl; C is total carbon; N is total nitrogen; eCEC is Cationic Exchange Capacity; DOC is dissolved organic carbon; WRB is World Reference Base; Alo, Feo: extracted with ammonium oxalate (mg kg−1).
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Rodríguez-González, L.; Arias-Estévez, M.; Díaz-Raviña, M.; Villaverde, J.J.; Fernández-Calviño, D.; Santás-Miguel, V. General Soil Properties Modulate Bacterial Community Tolerance to Clarithromycin in Laboratory-Spiked Agricultural Soils. Agriculture 2026, 16, 1312. https://doi.org/10.3390/agriculture16121312

AMA Style

Rodríguez-González L, Arias-Estévez M, Díaz-Raviña M, Villaverde JJ, Fernández-Calviño D, Santás-Miguel V. General Soil Properties Modulate Bacterial Community Tolerance to Clarithromycin in Laboratory-Spiked Agricultural Soils. Agriculture. 2026; 16(12):1312. https://doi.org/10.3390/agriculture16121312

Chicago/Turabian Style

Rodríguez-González, Laura, Manuel Arias-Estévez, Montserrat Díaz-Raviña, Juan José Villaverde, David Fernández-Calviño, and Vanesa Santás-Miguel. 2026. "General Soil Properties Modulate Bacterial Community Tolerance to Clarithromycin in Laboratory-Spiked Agricultural Soils" Agriculture 16, no. 12: 1312. https://doi.org/10.3390/agriculture16121312

APA Style

Rodríguez-González, L., Arias-Estévez, M., Díaz-Raviña, M., Villaverde, J. J., Fernández-Calviño, D., & Santás-Miguel, V. (2026). General Soil Properties Modulate Bacterial Community Tolerance to Clarithromycin in Laboratory-Spiked Agricultural Soils. Agriculture, 16(12), 1312. https://doi.org/10.3390/agriculture16121312

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