# Green Compost Effectiveness in Improving Quality of an Agricultural Soil Co-contaminated by Antibiotics and Copper

Chiara de Carolis, Anna Barra Caracciolo, Lisa Ciadamidaro, Michel Chalot, Alessandra Narciso, Ludovica Rolando, Paola Grenni

► To cite this version:

Chiara de Carolis, Anna Barra Caracciolo, Lisa Ciadamidaro, Michel Chalot, Alessandra Narciso, et al. Green Compost Effectiveness in Improving Quality of an Agricultural Soil Co-contaminated by Antibiotics and Copper. Journal of Soil Science and Plant Nutrition, 2026, 10.1007/s42729-026-03008-y. hal-05499883

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# Green Compost Effectiveness in Improving Quality of an Agricultural Soil Co-contaminated by Antibiotics and Copper

Chiara De Carolis<fnref n="1" />,<fnref n="2" /> ID · Anna Barra Caracciolo<fnref n="1" />,<fnref n="4" /> ID · Lisa Ciadamidaro<fnref n="3" /> ID · Michel Chalot<fnref n="3" /> ID · Alessandra Narciso<fnref n="1" /> ID · Ludovica Rolando<fnref n="1" /> ID · Paola Grenni<fnref n="1" />,<fnref n="4" /> ID

Received: 31 March 2025 / Accepted: 5 January 2026

© The Author(s) 2026

## Abstract

This work aimed at investigating the effectiveness of a vegetal waste compost (green compost) in improving the quality of a degraded agricultural soil with a low organic carbon content, low microbial activity and co-contaminated by copper and an antibiotic (AB) mixture (sulfamethoxazole, ciprofloxacin and chlortetracycline). The soil was planted with *Lactuca sativa* L. and its growth was evaluated in presence/absence of the green compost in soil microcosms. Physico-chemical (e.g. pH, temperature, organic carbon and contaminants) parameters, microbial abundance (DAPI counts) and enzymatic activities (dehydrogenase, phosphatase and β-glucosidase) were integrated in a soil quality index (SQI). Moreover, microbial biodiversity (NGS) and possible presence of antibiotic resistance genes (qPCR) were investigated in the soil microbial community. The SQI results showed the effectiveness of the green compost in increasing soil quality and fertility. In fact, the lettuce growth (total biomass, leaf area, leaf number and root elongation) was significantly improved. Although antibiotics were inhibiting growth, the soil plant-microbiome system was partially able to counteract the negative effects of these contaminants. Moreover, the soil microbial community showed shifts in some populations under treatments with compost and lettuce. Antibiotic resistance genes (ARGs) were promoted in AB and copper presence with the highest values in the bulk soil. Interestingly, the green compost promoted not only the highest plant biomass, but also the lowest ARG values. The green compost proved to be a good solution for recycling waste, increasing the organic carbon, microbial activity and fertility of the degraded soil and limiting the spread of ARGs (unlike agro-zootechnical organic amendments, e.g. manure).

<footnote>Anna Barra Caracciolo
anna.barracaracciolo@irsa.cnr.it</footnote>

<footnote n="1">¹ Water Research Institute, National Research Council (IRSA-CNR), Montelibretti (Rome), Italy</footnote>

<footnote n="2">² Department of Environmental Biology, Sapienza University of Rome, Rome, Italy</footnote>

<footnote n="3">³ Université Marie et Louis Pasteur, CNRS, Chrono-environnement (UMR 6249), Montbéliard F-25200, France</footnote>

<footnote n="4">⁴ National Biodiversity Future Center (NBFC), Palermo, Italy</footnote>
**Graphical Abstract**

**Antibiotics**

<figure><img src="image_2.png" /></figure>

**Green compost**

<figure><img src="image_3.png" /></figure>

**Soil Quality index**

<figure><img src="image_4.png" /></figure>

**Bacterial genera**

<figure><img src="image_5.png" /></figure>

Rhizosphere
microbiome
structure
shift with
ABs and
compost

**Keywords** Microbial community · Enzymatic activities · Biodiversity · Antibiotic mixture · Antibiotic resistance genes · Soil quality index

# 1 Introduction

The growth in human population over the last century, from 1.6 billion people in 1900 to around 8.2 billion people in 2024, has led to an increase in land exploitation for agricultural purposes with a high impact on natural ecosystems. Conventional agriculture requires an intensive use of synthetic fertilizers, pesticides and fungicides (including copper), which contribute to loss of soil quality both in abiotic and biotic terms. The EU Thematic Strategy for Soil Protection (EC 2006) and subsequently the Soil Strategy for 2030 (EC 2021) have recognized a series of soil degradation threats. They include erosion, decline in organic matter, local and diffuse contamination, sealing, compaction, loss in biodiversity, salinization, floods and landslides. All of these can be caused by agriculture practices. In the Green Deal the European Commission has been promoting several actions for “boosting an efficient use of resources to achieve a clean, circular economy, restoring biodiversity and reducing pollution”. In the coming years, a reduction in chemical fertilizer use and an increase in organic ones derived from agro-zootechnical waste is expected. The recycling of organic waste with a high organic matter content, such as manure, represents a key factor for improving soil and crop quality with socio-economic and environmental benefits (Eriksen et al. 1999; Hargreaves et al. 2008; Morra 2019; Panuccio et al.

2021). Although the use of organic amendments is regulated in Europe by Regulation (EU) 2018/848 and 2019/1009 (EU 2018; EU 2019) with the exclusion of pathogens and pollutants, the possible presence of emerging contaminants (e.g. antibiotics, ABs) and antibiotic resistance genes has not still been confronted.

Several works have demonstrated that ABs are diffuse agricultural soil contaminants due to their overuse for animal and human health (Grenni et al. 2018; Narciso et al. 2024; Pan and Chu 2017) and antibiotic resistance genes (ARGs) have been found in both organic fertilizers (Barra Caracciolo et al. 2022; Visca et al. 2022) and in amended soil (Grenni et al. 2024; Rauseo et al. 2019). In fact, ABs are only partially metabolized in the organisms treated and can reach soil together with antibiotic resistant bacteria (ARB) and ARGs from the application of organic fertilizers such as manure (e.g. cattle, swine and poultry). Reclaimed water and biosolids from treatment plants can also contribute to soil contamination (Barra Caracciolo et al. 2022; Grenni et al. 2018). Indeed, AB residues in organic waste can range from ng kg⁻¹ to mg kg⁻¹ (Narciso et al. 2023; Visca et al. 2021).

In agroecosystems, sulfamethoxazole, ciprofloxacin and chlortetracycline are among the most commonly found ABs (Visca et al. 2022; Zhang et al. 2022). Sulfamethoxazole is a sulphonamide used in both human and veterinary medicine for its broad-spectrum action as a bacteriostatic (Grenni et al. 2019;
Prasannamedha and Kumar 2020). Sulfamethoxazole is listed in the top 30 most frequently detected wastewater contaminants (Toyama et al. 2024) and residual concentrations of sulfamethoxazole have also been found in surface water and soil, with the highest concentrations (up 0.1 mg kg⁻¹) in agricultural soils (Narciso et al. 2023). Ciprofloxacin is a broad-spectrum AB and among the most prescribed fluoroquinolones used in human and veterinary medicine (Sodhi and Singh 2021). Ciprofloxacin tends to accumulate in solid matrices, reaching concentrations of up to 5.6 mg kg⁻¹ in agricultural soils (Pan and Chu 2017; Cycon et al. 2019; Kairigo et al. 2020). Finally, chlortetracycline, which belongs to the tetracycline group, is another broad-spectrum AB (Zhou et al. 2021) and its concentrations in soil range from ng kg⁻¹ to mg kg⁻¹. Cycon et al. (2019) reported a chlortetracycline maximum concentration of 12.9 mg kg⁻¹ in an agricultural soil.

Composting is a natural aerobic process of biotransformation of complex organic matter into simpler or more readily usable form. It reduces the volume of waste material and forms compost, a highly stable humus-like substance rich in nutrients (Barra Caracciolo et al. 2015; Lakshmipathi et al. 2019; Mathur et al. 1993). The heat generated in active compost also inactivates some microbial pathogens. Recently, some authors found that composting of cow manure mixed with straw effectively reduced ARGs vs. tetracyclines, macrolides, sulphonamides and quinolones (Bai et al. 2025). Composts can vary in their content of minerals, biochemicals, humic substances and amount of microorganisms (Lakshmipathi et al. 2019). The compost use provides environmental benefits such as increase in soil structure, density and porosity, water holding capacity and reduction in soil erosion and nutrient leaching (Vaverková et al. 2020). There is still little literature on the influence of compost on the adsorptive capacity of soil pollutants. However, Tang et al. (2021) observed that a soil amended with a compost obtained from pig manure (80%) and wood chips (20%), had an ability to adsorb antibiotics as a result of complexing actions of functional groups from humus and fulvic acids on the compost surface.

There are different types of compost depending on its origin, such as from municipal organic fraction, livestock effluents, agro-industrial waste, municipal and agro-industrial sewage sludge or green waste (e.g. crop residues, yard trimmings, olive oil pomace and chopped branches; Morra 2019; Reyes-Torres et al. 2018). Compost from green waste (termed green compost) contains organic compounds which are recalcitrant to biodegradation (e.g. lignin, which typically forms a protective layer around cellulose preventing or slowing its aerobic decomposition) or slowly/moderately degradable (e.g. hemicellulose, cellulose; Reyes-Torres et al. 2018). It therefore contains a lower nutrient content (e.g. nitrogen, phosphorous and potassium) than other types of

compost (Reyes-Torres et al. 2018). However, green compost has a low pathogen and micro-pollutant content and this can fulfil the quality standards and utilization restrictions for compost use in organic farming systems (Bustamante et al. 2016). Nevertheless, works which have investigated ABs, ARB and ARGs in green compost are quite scarce so far.

Organic farming is a rapidly growing market worldwide and because it requires organic amendments as fertilizers and copper (Cu) as a fungicide, it is necessary to investigate if these agricultural practices do not really affect the soil and plant-microbiome system. Cu is used as a wide spectrum pesticide; due to its low mobility, it tends to accumulate in soil due to repeated applications. It is generally found in pig manure because it is added to feed as a growth promoter (Panagos et al. 2018). Using manure as fertiliser can contribute to contamination of agroecosystems (Ballabio et al. 2018). Cu is an essential micronutrient, as it plays a key role in numerous morphological, physiological, and biochemical processes (Rehman et al. 2019); however, excessive concentrations can have toxic effects on biota and potential negative impacts on soil fertility (Karimi et al. 2021; La Torre et al. 2018).

The agricultural contamination scenario is quite complex because mixtures of contaminants are present and knowledge of the combined effects of ABs and Cu are quite scarce. Previous works have shown that adding livestock manure or digestate to soil can improve soil quality and plant growth; however, they introduce ARGs in different ways and this effect is more pronounced in the presence of Cu (Barra Caracciolo et al. 2022; Narciso et al. 2024). Moreover, the possibility that ABs and ARGs can be present in edible plants is not excluded (Barra Caracciolo et al. 2022). For this reason, the aim of this work was to test if the use of a green compost was effective in improving the quality and fertility of a soil co-contaminated by ABs and Cu. Moreover, the possible introduction, spread or reduction in ARGs when adding the green compost was also evaluated. For this purpose, a microcosm experiment was performed using an agricultural soil which was degraded in terms of low organic matter content (C: N ratio of 7.11) and collected from an organic farm. Soil samples were spiked in different ways with a mixture of ABs (sulfamethoxazole, ciprofloxacin and chlortetracycline) in the presence/absence of Cu. Moreover, an edible plant (*Lactuca sativa* L.) was cultivated.

# 2 Materials and Methods

## 2.1 Sampling Site and Organic Amendment

Soil samples were collected from the surface layer (0–20 cm) of an agricultural soil in an organic farm located in Central
Italy (Cesano, close to Rome, Italy). The sandy-clay-loam soil (60% sand, 22% loam, 18% clay, USDA 1987) had 1.28% organic carbon, 0.18% total N and pH of 7.12 (Table S1). The temperature of soil and its moisture prior the experimental setup were 18 °C and 10%, respectively. The soil was manually homogenized, with plant roots and any stones removed, and dried at room temperature before use.

The vegetal waste compost used as the organic amendment was supplied by the AGRIVALOR Company (Sainte-Croix-en-Plaine, France); it contained 17.6% organic carbon, 1.42% organic N, pH 8 and C: N ratio of 12.4 (additonal characteristics are in Table S1).

## 2.2 Microcosm Set-Up

Microcosms consisting of 1.4 L capacity plant pots were set up for the experiment. Each microcosm was filled with 1 kg of soil, which was spiked with either three ABs (AB mixture: sulfamethoxazole, ciprofloxacin and chlortetracycline, 7 mg kg⁻¹ each) and/or copper sulphate (CuSO₄ × 5H₂O, 30 mg kg⁻¹) and amended with the green compost (1% w/w). A one-month-old *Lactuca sativa* L. (crispa variety) seedling was added to each pot. Moreover, some microcosms spiked with the contaminant mixture did not include a plant. Finally, control microcosms consisting of only agricultural soil with a plant were also set up. Each condition was performed with six replicates (total 54 microcosms).

The nine experimental conditions performed are summarised as follows:

* Soil (Control): S.

* Soil + Antibiotic mixture + Cu: SABCu.

* Soil + L. sativa (Control with plant): S_P.

* Soil + AB mixture + L. sativa: SAB_P.

* Soil + Cu + L. sativa: SCu_P.

* Soil + AB mixture + Cu + L. sativa: SABCu_P.

* Soil + Compost + L. sativa: SCom_P.

* Soil + AB mixture + Compost + L. sativa: SABCom_P.

* Soil + AB mixture + Cu + Compost + L. sativa: SABCuCom_P.

The microcosms were placed in a growth chamber with a day/night illumination duration of 14 h/10 h, day/night temperature of 22 °C/18°C and humidity of 70%, for 42 days. The soil was regularly irrigated with distilled water to maintain a constant soil moisture (ca. 23%), corresponding to 45% of the soil water holding capacity.

Two destructive samplings were performed, one at the start (3 h after compost and contaminant addition) and the other at 42 days (a time sufficient for harvesting lettuce for its consumption). At the end of the experiment plant roots developed in all the soil of each pot, so that the soil can be

considered ‘rhizosphere soil’. For each condition, the analyses were performed in at least three replicates.

## 2.3 Cu Analyses

The total and bioavailable Cu concentrations were determined in dried (60 °C) and ground soil samples. For total Cu, 0.5 g of soil was mineralised using acid digestion in closed tubes placed in a block digestion system (DigiPREP, SCP Sciences, Courtaboeuf, France) using a mixture of 37% hydrochloric acid (5 mL) and 68% nitric acid (2 mL). Gradual heating was used to reach a final temperature of 120 °C (total run time: 260 min). At the end of this step, the sample was filtered (Whatman 1 paper filters, 11 µm porosity). Ultrapure water was then added to a final volume of 50 mL. The element concentrations were determined by an ICP-AES (Radial ICAP 6500 model, Thermo Fischer Scientific, Courtaboeuf, France), as also previously described (Assad et al. 2017). To assess the analytical quality, a standard reference soil sample (ERM®- European Reference Materials-CC141) was subjected to the same protocol.

For bioavailable Cu fraction, 5 g of soil samples was incubated with 50 mL of calcium chloride (10 mM) under agitation (40 rpm) for 2 h at room temperature. The mixture was first filtered (Whatman 1 paper filters) and acidified at 1% (v/v) with HNO₃ prior to inductively coupled plasma atomic emission spectrometry (ICP-AES, Thermo Fischer Scientific, Inc., Pittsburg, USA) analysis (Assad et al. 2017).

All samples for total and bioavailable Cu were analysed in triplicate.

## 2.4 Total Microbial Abundance and Soil Microbial Activities

The total microbial abundance (No. cells g soil⁻¹) was determined using the direct epifluorescence count method under an epifluorescence microscope (Leica Digital Microscope 4000 B, Leica Microsystems GmbH, Wetzlar, Germany) and using DAPI (4',6-Diamidino-2-phenylindole dihydrochloride) dye as the fluorescent DNA intercalant, as described in Barra Caracciolo et al. (2015).

The enzymatic activities measured were dehydrogenase, phosphatase and β-glucosidase.

Dehydrogenase activity reflects the overall microbial respiration rate and therefore biological oxidation of organic matter (Tabatabai, 1994). The method is based on an extraction and subsequent colorimetric determination of the colour intensity of the 2,3,5-triphenyl formazan (TPF) produced from the TTC reduction (Tabatabai, 1994). The colour intensity was measured with a Thermo Multiskan FC Microplate Photometer (Thermo Fisher Scientific; Waltham, MA, USA). Dehydrogenase was expressed as µg TPF g soil⁻¹.
Phosphatase and β-glucosidase activities were estimated as *p*-nitrophenol (PNP) released. These enzymatic activities were expressed as µg PNP g of dry soil⁻¹ h⁻¹. Soil samples (0.5 g each) were incubated (37 °C for 1 h) for phosphatase with a buffered solution (pH 6.5) of sodium *p*-nitrophenyl phosphate hexahydrate and toluene as described in detail in Tabatabai and Bremner (1969), and for β-glucosidase with a *p*-nitrophenyl-β-D-glucopyranoside solution as the substrate (Tabatabai 1982), respectively. In both cases, the PNP released was measured spectrophotometrically (UV/Vis spectrometry absorbance at 400 nm wavelength) as an enzymatic reaction product and it was estimated using the specific calibration curve (10–50 µg L⁻¹ of PNP, R²=0.99 for phosphatase and 5–25 µg L⁻¹, R²=0.99 for β-glucosidase, respectively).

All the microbiological analyses were performed in at least three replicates for each experimental condition and sampling.

## 2.5 Soil Quality Index

A Soil Quality Index (SQI) was applied using nine different soil parameters (microbial abundance, dehydrogenase, phosphatase, β-glucosidase, pH, organic carbon, AB content, total and bioavailable Cu) as indicators.

In accordance with Santorufo et al. (2021), for each soil parameter used, a parameter score (S) from 0 to 1 was calculated for each experimental condition, reflecting low and high quality respectively. The two criteria used were as follows:

$$ More is better : S = (x - x_{min})/(x_{max} - x_{min}) $$

$$ Less is better : S = 1 - (x - x_{min})/(x_{max} - x_{min}) $$

The *more is better* criterion was applied to microbial abundance and enzyme activities. Because copper in an acidic soil is more bioavailable and consequently shows more deleterious effects on soil biota, a relative increase in pH (slightly above 7) was considered positive for improving overall soil quality (Lebron et al. 2025).

The *less is better* criterion was applied for AB content, total and bioavailable Cu, because high concentrations can be toxic for soil organisms (Marzaoli et al. 2010).

The overall parameter score (SQI) was calculated as reported by Andrews et al. (2004) as follows:

$$ SQI = \sum_{i=1}^{n} Si/n $$

In which *S* is each parameter score obtained from each parameter; *n*: number of parameters used (in our case, *n*=9).

The SQI can have values from 0 (lowest quality) to 1 (highest quality).

## 2.6 Microbial DNA Extraction and Quantification of ARGs

Total DNA was extracted using the DNeasy PowerSoil kit (Qiagen, United States) and then used for both qPCR and NGS analyses.

X96 real-time PCR detection system (Bio-Rad, Hercules, CA, USA) to target the *sul1*, *sul2*, *intI1*, *qnrS*, *qepA*, *aac-(6')-Ib-cr*, *tetA* and *tnpA* genes. These genes are mainly associated with sulfonamide, fluoroquinolone, tetracycline and also copper resistance (Gillings et al. 2015; Manageiro et al. 2017; Pan et al. 2023, 2024; Zhang et al. 2017).

The primer list used and additional details are reported in Supplementary materials (Table S3). Results are reported as relative abundances normalised to the 16S rRNA gene.

## 2.7 Evaluation of Microbial Community Composition by Next Generation Sequencing (NGS)

Aliquots of the DNA extracted were used for NGS. The hypervariable V3–V4 region of 16 S rRNA genes were amplified by Miseq Illumina with the Pro341F and Pro805R (Takahashi et al. 2014). Further details are reported in Supplementary materials, Table S4.

The Illumina Miseq sequencing raw data are deposited in the NCBI (National Center for Biotechnology Information) database (accession number: PRJNA1153537).

## 2.8 Plant Growth Analyses

Plants were sampled and weighed fresh (g) at the end of the experiment. The leaf area (cm²) was measured by scanning the leaves of each plant and then the images were processed using a Python-based image analysis. Plant height (cm) and number of leaves (No. leaves per plant) were measured weekly to assess biomass production during the experiment.

## 2.9 Statistical Analyses

The microbiological and plant growth results are reported as average values ± standard errors of at least three replicates. All the statistical analyses were performed using R software (4.3.1 version https://www.r-project.org).

The Principal Component Analysis (PCA) of the overall data was run to graphically synthesize the complexity of the dataset by considering the ARGs at 42 d (*sul1t42*, *sul2t42*, *intI1t42* and *qepAt42*), SQI, main microbial genera, total Cu concentration and total plant biomass. The PCA was performed, using the packages “FactoMineR” and “factoextra”.
The differences among treatments in terms of microbial abundance and activities, soil quality index, plant parameters and the relative abundances of the ARGs were calculated using ANOVA (aov function of R) and subsequently Tukey's test (TukeyHSD function of R). In all cases, a significance threshold of 0.05 was considered. Moreover, the structure of the microbial community (at genus level) was mapped using heatmap modules in the "R" statistical package ("ComplexHeatmap"). The heatmap reports the most abundant prokaryotic genera (top 22 genera, net of "unclassified" ones) detected in the overall samples corresponding to >1% of total identified genera, and the dataset used for the heatmap was normalized by mean and standard deviation (z-score). Differences among conditions were evaluated using the PERMANOVA test.

# 3 Results

## 3.1 Cu in Soil

A significantly higher amount of total Cu was found in the SABCu, SCu_P, SABCu_P and SABCuCom_P conditions in line with its addition to soil. A similar trend for the bioavailable Cu content was found (Supplementary material, Table S2). Adding compost (SCom_P and SABCom_P), soil pH increased significantly (p<0.05) if compared to the other conditions with the plant (Table 1).

## 3.2 Soil Microbial Abundance and Activities

In the presence of only ABs, a significantly prompt decrease (p<0.05) in microbial abundance was observed. At the end of the experiment (42 days), the microbial numbers generally

increased in all conditions with lettuce (rhizosphere). However, the highest values (p<0.05) were in SABCom_P and SABCuComp_P (Fig. 1).

The initial dehydrogenase activity (Fig. 2a) was quite low in all soil conditions. AB and Cu alone (SAB_P and SCu_P) had a transient detrimental effect on dehydrogenase values. Although the addition of the green compost did not cause an immediate increase in microbial activity, its presence was able to counteract both AB and Cu negative effects. Interestingly, in the presence of both ABs and Cu (SABCu_P) the dehydrogenase was not affected. At 42 days, the initial detrimental effect of ABs or Cu alone was never observed and dehydrogenase was higher in the compost presence than in its absence. The highest value (p<0.05) of dehydrogenase was found in SCom_P.

The phosphatase values were very low in comparison to those of other studies (Ciadamidaro et al. 2016) and initially relatively similar for all conditions (Fig. 2b). At the end of the experiment, an overall increase in this activity was observed for all treatments. The highest values were found in the presence of the green compost, with the highest one in SCom_P.

β-glucosidase activity (Fig. 2c) was initially higher in SCom_P if compared to the other conditions. A general increase in the presence of compost and in SABCu_P condition was observed at day 42.

## 3.3 Soil Quality Index

The integration into the SQI of the different soil and microbiological indicators showed that the initial soil (S) was of a very poor quality (Fig. 3). The addition of a plant such as lettuce generally increased its quality. Adding compost resulted in short- (3 h) and long-term (42 d) improvements, with the highest value in the SCom_P condition.

## 3.4 Plant Growth

Lettuce biomass, number of leaves, leaf area and root elongation are reported in Figs. 4a, b, c and d, respectively. The highest values (p<0.05) for lettuce growth were found in the SCom_P and the lowest ones in the SAB_P and SABCu_P conditions. Adding Cu alone did not affect plant parameters if compared to the control (S_P). On the contrary, AB alone (SAB_P) and AB+Cu (SABCu_P) had detrimental effects on lettuce growth in terms of biomass, number of leaves, leaf area and root elongation. However, compost partially buffered these negative effects, with a higher biomass in the presence of compost (SABCom_P and SABCuComp_P) than without it (SAB_P and SABCu_P).

<table><caption>**Table 1** Total Cu (mg kg⁻¹) and pH values in the soil at 42 days in the various conditions. Different letters indicate significant differences among the various treatments. S: soil (Control); SABCu soil+Antibiotic mixture+Cu; S_P: soil+Plant (Control with *L. sativa*); SAB_P: soil+AB mixture+Plant; SCu_P: soil+Cu+Plant; SABCu_P: soil+AB mixture+Cu+Plant; SCom_P: soil+Compost+Plant; SABCom_P: soil+AB mixture+Compost+Plant; SABCuCom_P: soil+AB mixture+Cu+Compost+Plant</caption><thead><tr><th></th><th>Total Cu (mg kg<sup>-1</sup>)</th><th>pH</th></tr></thead><tbody><tr><td>S</td><td>29.66±0.08<sup>b</sup></td><td>7.12±0.03<sup>b</sup></td></tr><tr><td>SABCu</td><td>35.90±1.52<sup>a</sup></td><td>6.82±0.04<sup>de</sup></td></tr><tr><td>S_P</td><td>28.40±0.31<sup>b</sup></td><td>6.96±0.03<sup>c</sup></td></tr><tr><td>SAB_P</td><td>28.20±0.25<sup>b</sup></td><td>6.78±0.07<sup>e</sup></td></tr><tr><td>SCu_P</td><td>34.82±0.40<sup>a</sup></td><td>6.58±0.01<sup>f</sup></td></tr><tr><td>SABCu_P</td><td>33.95±0.83<sup>a</sup></td><td>6.90±0.01<sup>cd</sup></td></tr><tr><td>SCom_P</td><td>27.78±0.35<sup>b</sup></td><td>7.32±0.02<sup>a</sup></td></tr><tr><td>SABCom_P</td><td>26.31±0.47<sup>b</sup></td><td>7.24±0.01<sup>a</sup></td></tr><tr><td>SABCuCom_P</td><td>34.60±1.52<sup>a</sup></td><td>7.12±0.03<sup>b</sup></td></tr></tbody></table>
<figure><img src="image_6.png" /><figcaption>**Fig. 1** Microbial abundance (No. cells g soil⁻¹) in the various experimental conditions at 3 h and 42 d. The vertical bars are the standard errors. Different letters indicate significant differences among the various treatments (p value≤0.05) S: Soil (Control); SABCu: Soil+antibiotic mixture+Cu; S_P: Soil+Plant (Control with *L. sativa*); SAB_P:</figcaption></figure>

Soil+AB mixture+Plant; SCu_P: Soil+Cu+Plant; SABCu_P: Soil+AB mixture+Cu+Plant; SCom_P: Soil+Compost+Plant; SABCom_P: Soil+AB mixture+Compost+Plant; SABCuCom_P: Soil+AB mixture+Cu+Compost+Plant

## 3.5 Quantification of ARGs

Overall ARGs (No. copies 16S⁻¹) increased (3 h) due to the various treatments. In particular, the *sull*, *sul2*, *intl*1 and *qepA* genes (associated with antibiotic and copper resistance) were in significantly higher relative abundances in contaminated conditions than in the control one (S, *p*<0.05), (Fig. 5). Other ARGs (i.e. *qnrS*, and *aac-(6')-Ib-cr*, *tetA* and *tnpA*) searched for were not detected in the soil studied; in fact, their relative concentrations were lower than those of the negative control used in the qPCR.

At 42 days, a general decline in *intl*1 and *qepA* genes was observed. In contrast, the *sull*1 and *sul2* genes increased over time in all treatments, regardless of the presence or not of antibiotics. In particular, *sull*1 and *sul2* increased significantly (*p*<0.05) in all treatments spiked with ABs (SAB_P, SABCu_P), except in the compost presence (SABCom_P and SABCuCom_P). However, soil spiked with ABs and amended with compost in the presence of lettuce (SABCom_P and SABCuCom_P) showed a lower abundance in *sull*1 and *sul2* than the corresponding conditions without compost (SAB_P and SABCu_P).

## 3.6 Microbial Community Composition by Next-Generation Sequencing

The prokaryotic community was characterized by sequencing the 16 S gene in the various experimental conditions at 42 days. The Shannon, Evenness and Chao1 diversity indices, based on abundance of the ASV are reported in Supplementary materials, Table S5. In plant presence (S_P), Shannon diversity was higher than in the bulk soil (S). However, the presence of ABs significantly decreased biodiversity (*p*<0.05) in the rhizosphere in both SAB_P and SABCom_P conditions. Copper (SCu_P) also reduced biodiversity. Interestingly, in the case of the microcosms amended with compost (SCom_P), although the Shannon index was lower than in the bulk soil (S), a higher Evenness was found.

Overall, the various treatments modulated the soil microbial community (Fig. 6). *Actinobacteria* (33.4%) were the dominant class in the bulk soil (S), followed by *Bacilli* (15.7%). *Alphaproteobacteria* (8.8%), *Clostridia* (3.4%) and *Gammaproteobacteria* (3.2%). The growth of lettuce plants (S_P) increased *Alphaproteobacteria*
<figure><img src="image_7.png" /><figcaption>**Fig. 2** a) Dehydrogenase activity (µg TPF g⁻¹ dry soil); b) Phosphatase activity (µg PNP g⁻¹ dry soil h⁻¹) and c) β-glucosidase activity (µg PNP g⁻¹ dry soil h⁻¹) in the various experimental conditions at 3 h and 42 d. The vertical bars are the standard errors. Different letters indicate significant differences among the various treatments (p value≤0.05). S: Soil (Control); SABCu: Soil+Antibiotic mixture+Cu; S_P: Soil+Plant (Control with *L. sativa*); SAB_P: Soil+AB mixture+Plant; SCu_P: Soil+Cu+Plant; SABCu_P: Soil+AB mixture+Cu+Plant; SCom_P: Soil+Compost+Plant; SABCom_P: Soil+AB mixture+Compost+Plant; SABCuCom_P: Soil+AB mixture+Cu+Compost+Plant</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>**Fig. 3** Soil quality index (SQI) in the various experimental conditions at 3 h and 42 d. The vertical bars are the standard errors S: Soil (Control); SABCu: Soil+Antibiotic mixture+Cu; S_P: Soil+Plant (Control with *L. sativa*); SAB_P: Soil+AB mixture+Plant; SCu_P: Soil+Cu+Plant</figcaption></figure>

SABCu_P: Soil+AB mixture+Cu+Plant; SCom_P: Soil+Compost+Plant; SABCom_P: Soil+AB mixture+Compost+Plant; SABCuCom_P: Soil+AB mixture+Cu+Compost+Plant

(14.2%), *Gammaproteobacteria* (4.9%) and decreased *Deltaproteobacteria* (1.8%). With compost (SCom_P), a lower percentage of *Actinobacteria* (27.7%), *Alphaproteobacteria* (8.3%), *Clostridia* (2.9%) and higher percentages of *Gammaproteobacteria* (5.4%), *Deltaproteobacteria* (2.3%), *Bacteroidia* (2%) and *Phycisphaerae* (1.8%) than S_P were observed. Adding ABs (SABCom_P), a sharp decrease in *Actinobacteria* (15.2%) and a reduction in *Alphaproteobacteria* (7.9%), *Bacilli* (6.7%), *Deltaproteobacteria* (1.8%), *Clostridia* (1.2%), *Phycisphaerae* (0.9%) and *Anaerolineae* (0.6%), compared to SCom_P were found. Conversely, a marked increase was observed in the relative abundance of *Gammaproteobacteria* (22.3%) and *Bacteroidia* (11.4%). In the co-presence of ABs and Cu (SABCuCom_P) the rhizosphere microbial community was affected differently to the condition with only ABs (SABCom_P). In fact, *Actinobacteria* (21.7%), *Bacilli* (14.3), *Alphaproteobacteria* (11.7%), *Deltaproteobacteria* (3.2%), *Clostridium* (2.2%), *Phycisphaerae* (1.9%) and *Anaerolineae* (1.3%) were in higher percentages and other groups in lower ones (e.g. *Gammaproteobacteria*: 6.1% and *Bacteroidia*: 2.9%).

In the antibiotic and plant condition (SAB_P), the predominant bacterial groups were *Actinobacteria* (33.3%),

*Bacilli* (18.9%) and *Clostridia* (3.5%). In comparison with the soil containing solely lettuce (S_P), a reduced percentage of *Alphaproteobacteria* and *Gammaproteobacteria* was detected in compost absence, in both SAB_P and SCu_P experimental groups.

At the genus level (Fig. 7), the bulk soil (S) was characterized by a high abundance of gram-positive bacteria such as the *Streptomyces* (*Actinobacteria*) (21.8%) and *Bacillus* (*Bacilli*) (13.1%) genera; in the presence of plants (S_P), the *Sphingomonas* (*Alphaproteobacteria*) genus was found in higher amounts (9.3%). In antibiotic and compost addition in plant presence (SABCom_P), a very high abundance of *Fulvivirga* (*Bacteroidia*) (10.4%) was identified, along with lower amounts of *Streptomyces* (8.4%) and *Bacillus* (4.4%).

Combining the relevant data at 42 days, the PCA explained 57.8% of the total variance (Fig. 8). PCA clearly distinguished data on the basis of the presence or absence of compost. The green compost (blue points) favoured a positive SQI, lettuce biomass and several gram-negative bacteria. Interestingly, in the absence of compost (pink points), several gram-positive bacteria (e.g. *Arthrobacter*, *Streptomyces*, *Paenibacillus* and *Nocardia*) were associated with ARGs and Cu.
<figure><img src="image_9.png" /><figcaption>**Fig. 4** Plant growth parameters. a) Total biomass (g); b) Number of leaves per plant; c) Leaf area (cm²) and d) Root elongation (cm) in the various experimental conditions at 42 days. The vertical bars are the standard errors. Different letters indicate significant differences among the various treatments (p value ≤0.05) S: Soil (Control); SABCu: Soil+Antibiotic mixture+Cu; S_P: Soil+Plant (Control with *L. sativa*); SAB_P: Soil+AB mixture+Plant; SCu_P: Soil+Cu+Plant; SABCu_P: Soil+AB mixture+Cu+Plant; SCom_P: Soil+Compost+Plant; SABCom_P: Soil+AB mixture+Compost+Plant; SABCuCom_P: Soil+AB mixture+Cu+Compost+Plant</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>**Fig. 5** Relative gene abundances (No. copies 16 S⁻¹) in the various experimental conditions at 3 h and 42 d. The vertical bars are the standard errors. Different letters indicate significant differences among the various treatments (p value≤0.05) S: Soil (Control); SABCu: Soil+Antibiotic mixture+Cu; S_P: Soil+Plant (Control with L. sativa); SAB_P: Soil+AB mixture+Plant; SCu_P: Soil+Cu+Plant; SABCu_P: Soil+AB mixture+Cu+Plant; SCom_P: Soil+Compost+Plant; SABCom_P: Soil+AB mixture+Compost+Plant; SABCuCom_P: Soil+AB mixture+Cu+Compost+Plant</figcaption></figure>

## 4 Discussion

The general increase in microbial abundance (42 d, Fig. 1) was ascribable to the experimental conditions (e.g. higher water content and temperature), which were more favourable to bacterial growth when compared with the initial ones of the soil (Table S1). Moreover, the presence of plants promoted a further proliferation of microorganisms in the rhizosphere, in accordance with other works (Barra Caracciolo et al. 2022; Narciso et al. 2024). Indeed, plants release root exudates, rendering the rhizosphere richer in nutrients as compared to bulk soil (Prashar et al. 2014).

The plant waste compost (green compost) used in this work had a significant positive effect on dehydrogenase activity (SCom_P microcosms). A positive increase in soil dehydrogenase in the case of agro-zootechnical amendments (Grenni et al. 2009; Grenni et al. 2012; Mangalassery et al. 2019), and compost produced from municipal waste

(Di Lenola et al. 2018; Garbini et al. 2023) has been found in several works. However, unlike other organic amendments such as digestate, which has been shown to also increase microbial activity in the presence of contaminants (Barra Caracciolo et al. 2015; Narciso et al. 2024), the green compost used in this work was only partially able to buffer the negative effects of ABs on dehydrogenase (Fig. 2a). Most organic waste used as amendments is rich in labile organic matter and has a chemical structure quite different from the plant waste compost used in this work. In fact, vegetal compost contains lignocellulosic matter which is characterised by a low decomposition rate and does not provide a ready carbon source and nutrients for bacteria. Indeed, green compost is reported to improve mainly soil physical structure (e.g. increase in water retention and decrease in soil compaction), making soil a more favourable habitat for microbial community development and plant growth (Bustamante et al. 2016; Mangalassery et al. 2019).
<figure><img src="image_11.png" /><figcaption>**Fig. 6** Bacterial class relative abundance (% of ASV) in the various conditions at 42 d S: Soil (Control); SABCu: Soil+Antibiotic mixture+Cu; S_P: Soil+Plant (Control with *L. sativa*); SAB_P: Soil+AB mixture+Plant; SCu_P: Soil+Cu+Plant; SABCu_P: Soil+AB mixture+Cu+Plant; SCom_P: Soil+Compost+Plant; SABCom_P: Soil+AB mixture+Compost+Plant; SABCuCom_P: Soil+AB mixture+Cu+Compost+Plant</figcaption></figure>

As regards the general increase in phosphatase activity observed at the end of the experiment, this was in accordance with the microbial abundance increase (Adetunji et al. 2017). On the contrary, β-glucosidase showed the highest values only in green compost-amended microcosms (SCom_P, SABCom_P and SABCuComp_P), since this enzyme is typically linked to the breaking of cellobiose residues, commonly found in green compost. In particular, β-glucosidase acts in the final stage of cellulose degradation by hydrolysing cellobiose residues (Adetunji et al. 2017). Finally, the unexpectedly high value in the SABCu_P condition (in the absence of green compost) may be attributable to the production of plant secondary metabolites, given the stress caused to the lettuce by the presence of contaminants such as AB and Cu, as also reported by other authors (Akula and Ravishankar 2011; Vives-Peris et al. 2020). Indeed, it is likely that these contaminants were, in turn, metabolised by microorganisms, thereby increasing the β-glucosidase levels. This possibility requires further investigation.

The SQI made it possible to integrate and summarize several indicators of soil quality (Sánchez-Navarro et al. 2024).

The initial agricultural soil (S) was of a poor quality and further decreased following the addition of the contaminants (with the lowest value in their co-presence). On the other hand, the green compost (SCom_P) was a short (3 h) and long-term (42 d) soil quality improver. The green compost also improved the soil quality at the start of the experiment where ABs and Cu were co-present (SABCuCom_P). In line with the SQI, the highest plant growth was observed in the presence of compost (SCom_P). Moreover, the presence of green compost resulted in enhanced plant growth, particularly in the presence of antibiotic mixture (SABCom_P vs. SAB_P, Fig. 4). Although the green compost improved overall plant growth (Fig. 4), the latter was influenced more negatively by the co-presence of both contaminants (ABs and Cu) or of the antibiotics alone, if compared to the rhizosphere microbiome (Figs. 1 and 2). On the contrary, Cu alone (SCu_P) had no long-term (42 days) negative effects on either the soil as a whole nor on lettuce growth, in contrast to a previous work, where, in an experiment performed with the same soil and edible plant, Cu alone affected negatively both the rhizosphere microbiome and lettuce (Narciso et al.
<figure><img src="image_12.png" /><figcaption>**Fig. 7** Heatmap of Prokaryotic relative abundances at genus level in the different conditions at 42 d. Genera and conditions were grouped in accordance with a hierarchical clustering dendrogram, at the top and on the left hand side of the heatmap. Higher genera abundances are in red, while lower abundances are in blue (Data are means of 3 independent replicates) S: Soil (Control); SABCu: Soil+Antibiotic mixture</figcaption></figure>

+Cu; S_P: Soil+Plant (Control with *L. sativa*); SAB_P: Soil+AB mixture+Plant; SCu_P: Soil+Cu+Plant; SABCu_P: Soil+AB mixture+Cu+Plant; SCom_P: Soil+Compost+Plant; SABCom_P: Soil+AB mixture+Compost+Plant; SABCuCom_P: Soil+AB mixture+Cu+Compost+Plant

2024). However, in Narciso et al. (2024), the experiment was performed in a greenhouse and subjected to increasing temperatures (up to 43 °C), which caused a further stress factor for plant growth.

The antibiotic mixture exerted a higher detrimental effect on the lettuce plant than on the rhizosphere microbiome. This phenomenon presumably occurred as a result of the high adaptability and versatility of the microbiome, which resulted in the capacity for rapid shifts in microbial structure. ABs act as a pressure, selectively affecting less sensitive populations or increasing ARG spread phenomena (Barra Caracciolo et al. 2020b). These possibilities were investigated through NGS and qPCR analysis. Specifically, the analysis of the microbial community structure showed how *Proteobacteria* group generally increased when plants were present. Within it, *Alphaproteobacteria* include the *Sphingomonas* genera, which promote plant growth (Sultana et al. 2024), and other genera, such as *Neoasaia*, able to grow in degraded soils and resistant to some contaminants (Wang et al. 2015; Yukphan et al. 2005). However, the latter genera were also

found (although in lower percentages) in the bulk soil (S); their presence, together with the high percentage of gram-positive bacteria (*Actinobacteria* + *Bacilli* + *Clostridia*), suggests that the autochthonous microbial community had adapted to antibiotic contamination. In fact, the PCA analysis (Fig. 8) demonstrated that several gram-positive bacteria, encompassing *Nocardia* (*Actinobacteria*), *Arthrobacter* (*Actinobacteria*), *Streptomyces* (*Actinobacteria*) and *Brevibacillus* (*Bacillus*), were associated with soil not amended with compost and with the presence of ARGs. Indeed, these genera comprise several ARB (Nonthakaew et al. 2025; Rammali et al. 2022; Sun et al. 2020; Zhang et al. 2021). Conversely, PCA analysis demonstrated that the green compost was predominantly associated with *Proteobacteria* and other gram-negative bacteria, such as *Fulvivirga* (*Bacteroidia*).

It is interesting to note that the green compost seemed to be able not only partially buffering the negative effects of the contaminants (see SQI values and plant growth), but also counteracting the spread of ARGs. In fact, we observed a lower abundance of sulfamethoxazole resistance genes
<figure><img src="image_13.png" /><figcaption>**Fig. 8** Principal component analysis (PCA) constructed using the following variables: ARGs at 42 d (*sul1t42*, *sul2t42*, *intl1t42* and *qepAt42*), SQL, main microbial genera, Cu_total concentration and total lettuce biomass. The length of each vector represents the contribution of the corresponding variable to the principal component (Dim1 and Dim2), while the direction of each vector indicates the correlation</figcaption></figure>

between the variable and the principal components. Data points are grouped into coloured ellipses representing a 95% confidence interval, showing samples' segregation by presence or absence of compost. Enlarged points within ellipses represent the centroids of the sample distributions

in soil spiked with ABs and amended with compost in the presence of lettuce (Fig. 5). This effect could be ascribable to AB adsorption on the green compost (García-Delgado et al. 2023), which in turn may have limited both contaminant availability and ARGs spread. This may also explain the relative increase in AB-spiked conditions of gram-positive bacteria in the absence of compost (SAB_P and SABCu_P) and of gram-negative ones in its presence (SABCom_P and SABCuCom_P). Indeed, the gram-negative/gram-positive bacteria ratio was 0.28 in antibiotic and plant presence (SAB_P) vs. 1.94 in antibiotic and plant presence with compost addition (SABCom_P) and 0.54 in antibiotic and Cu

addition with plant (SABCu_P) vs. 0.71 in the same condition with compost (SABCuCom_P, Fig. S1 and Table S5). Gram-positive bacteria comprise a plethora of resistant and, in many cases, multidrug resistant bacteria (Nandi et al. 2004; Jubeh et al. 2020). Gram-negative bacteria, and in particular *Proteobacteria*, tend to increase in abundance in good quality soils (Barra Caracciolo et al. 2015, 2020a) and in the presence of higher organic carbon availability (Mhete et al. 2020), and our results confirm this. In fact, *Proteobacteria* comprise a wide range of species involved in key soil functions such as nutrient cycling and organic matter decomposition.
The presence of ARGs in the control soil at the start and at the end of the experiment suggests that the soil had been previously in contact with ABs and the values were in the range (4.0 × 10⁻⁰⁴ – 2.82 × 10⁻⁰⁴ copies 16 S⁻¹) of those found in the same soil in a previous work (Narciso et al. 2024). In any case, antibiotic resistance is a natural phenomenon of the environment, which results in the complexity of establishing a “baseline concentration” of ARGs in agricultural soils. This concentration of ARGs depends on biotic (e.g. microbial abundance and presence of ARB) and abiotic factors (e.g. temperature and water stress) in addition to any previous treatments with organic amendments. For example, a higher microbial abundance may increase horizontal transfer of ARGs due to higher encounter rates (Sun et al. 2024).

In this work, spiking the agricultural soil with ABs and Cu (SABCu), the *sul1* gene, which can confer resistance to both antibiotics and copper (Pan et al. 2024), showed the highest relative abundance at 42 days. Cross resistance phenomena have been found in other works (Congilosi et al. 2022; Glibota et al. 2019; Mazhar et al. 2021; Narciso et al. 2024). However, a significantly lower value for this resistance gene was observed in plant presence (SABCu_P), which in turn was lower in compost presence (SABCuComp_P). In a similar way, both *sul1* and *sul2* were in lower abundances where antibiotics were spiked in presence of compost (SABCom_P) compared to its absence (SAB_P), showing how the green compost did not introduce ARGs to the soil. These results emphasize that composted plant material does not introduce ARGs into the soil, unlike agrozootechnical waste (Barra Caracciolo et al. 2022; Narciso et al. 2024; Rauseo et al. 2019; Visca et al. 2022). This aspect is an added value for this organic amendment. Finally, the lowest SQI found for the condition without compost and with the addition of both ABs and Cu (SABCu), confirms that this condition was the most affected by the antibiotic mixture and Cu owing to the compost and plant absence, suggesting how a quality index (using physico-chemical and microbiological indicators) can give an overview of soil fertility and a capacity to respond to contamination.

This experiment was conducted on a microcosm scale under realistic, but fixed conditions; however, it would be useful to test our results in the real world and for a longer time, under fluctuating temperature and water availability and in an open system. Consequently, further studies at field scale, testing different edible plant species, are desirable in order to assess the overall potential of green compost as a sustainable way of managing vegetal waste and a suitable soil improver, in line with the circular economy.

## 5 Conclusion

The application of the plant-based green compost was efficient in improving the quality and fertility of the degraded agricultural soil studied, as highlighted by the increase in the soil quality index values. Although the green compost did not enrich soil in promptly available nutrients, it proved to be an appropriate soil improver and promoted lettuce growth. The green compost partially buffered not only the detrimental contaminant effects, but also the spread of antibiotic resistance genes. The latter aspect gives it a benefit in comparison with other organic fertilizers such as cattle-manure, which introduce ARGs to soil. Finally, the overall results showed how microbial and soil parameters can be relevant indicators for evaluating soil quality and its variations under different conditions.

**Supplementary Information** The online version contains supplementary material available at https://doi.org/10.1007/s42729-026-03008-y.

**Acknowledgements** A particular thank to Vladimiro Dore of the Orto di Fabiana Company (Rome, Italy) for providing support in the experiments. We also thank Gian Luigi Garbini from the Computational Biology Group of the Department of Biology (University of Florence, Italy) for its valuable help in the bioinformatic analysis.

**Author Contributions** Chiara De Carolis: Conceptualization, Methodology, Data curation, Writing – original draft, Investigation, Validation, Writing – review & editing. Anna Barra Caracciolo: Conceptualization, Methodology, Data curation, Writing – original draft, Writing – review & editing, supervision. Lisa Ciadamidaro: Conceptualization, Methodology, Data curation, Investigation, Writing – review & editing. Michel Chalot: Conceptualization, Methodology, Investigation, Writing – review & editing. Alessandra Narciso: Methodology, Data curation, Investigation, Validation, Writing – review & editing. Ludovica Rolando: Methodology, Data curation, Investigation, Validation, Writing – review & editing. Paola Grenni: Methodology, Validation, Writing – review & editing.

**Funding** Open access funding provided by Consiglio Nazionale Delle Ricerche (CNR) within the CRUI-CARE Agreement. This research was mainly funded by the Italian Ministry of University and Research, PON "Ricerca e Innovazione" 2014-2020 DM 1061/2021 risorse FSE REACT-EU Azione IV.4 "Dottorati e contratti di ricerca su tematiche dell'innovazione" e Azione IV.5 "Dottorati su tematiche Green" (PhD scholarship awarded by Sapienza University of Rome to Chiara De Carolis). Moreover, it was partially funded by the NextGenerationEU- "National Biodiversity Future Center-NBFC-Microbial diversity and functioning of freshwater and terrestrial ecosystems" Project (Piano Nazionale Resistenza e Resilienza (PNRR)-Missione 4 Componente 2 Investimento 1.4-Avviso N. 3138 del 16 dicembre 2021 rettificato con D.D. n.3175 del 18 dicembre 2021 del Ministero dell'Università e della Ricerca, Award Number: CN_00000033, Decreto Direttoriale MUR n. 1034 del 17giugno 2022 di concessione del finanziamento, CUP B83C22002930006).

**Data Availability** Data will be made available on request.
## Declarations

**Conflict of interest** The authors declare that they have no competing financial interests or personal relationships that could have influenced the work reported in this paper.

**Open Access** This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

## References

Adetunji AT, Lewu FB, Mulidzi R, Ncube B (2017) The biological activities of β-glucosidase, phosphatase and urease as soil quality indicators: a review. J Soil Sci Plant Nutr 17:794-807. https://doi.org/10.4067/S0718-95162017000300018

Akula R, Ravishankar GA (2011) Influence of abiotic stress signals on secondary metabolites in plants. Plant Signal Behav 6:1720-1731. https://doi.org/10.4161/psb.6.11.17613

Andrews SS, Karlen DL, Cambardella CA (2004) The Soil Management Assessment Framework. Soil Sci Soc Am J 68:1945-1962. https://doi.org/10.2136/sssaj2004.1945

Assad M, Tatin-Froux F, Blaudez D, Chalot M, Parelle J (2017) Accumulation of trace elements in edible crops and Poplar grown on a titanium ore landfill. Environ Sci Pollut Res 24:5019-5031. https://doi.org/10.1007/s11356-016-8242-4

Bai B, Wang L, Guan F, Pi H, Wang A, Zhai L (2025) Maturity phase is crucial for removing antibiotic resistance genes during composting: novel insights into dissolved organic matter-microbial symbiosis system. Bioresour Technol 431:132607. https://doi.org/10.1016/j.biortech.2025.132607

Ballabio C, Panagos P, Lugato E, Huang J-H, Orgiazzi A, Jones A, Fernández-Ugalde O, Borrelli P, Montanarella L (2018) Cop- per distribution in European topsoils: an assessment based on LUCAS soil survey. Sci Total Environ 636:282-298. https://doi.org/10.1016/j.scitotenv.2018.04.268

Barra Caracciolo A, Bustamante MA, Nogues I, Di Lenola M, Luprano ML, Grenni P (2015) Changes in microbial community structure and functioning of a semiarid soil due to the use of anaerobic digestate derived composts and rosemary plants. Geoderma 245:89-97. https://doi.org/10.1016/j.geoderma.2015.01.021

Barra Caracciolo A, Grenni P, Garbini GL, Rolando L, Campanale C, Aimola G, Fernandez-Lopez M, Fernandez-Gonzalez AJ, Villadas PJ, Ancona V (2020a) Characterization of the belowground microbial community in a Poplar-Phytoremediation Strategy of a Multi-Contaminated Soil. Front Microbiol 11:2073. https://doi.org/10.3389/fmicb.2020.02073

Barra Caracciolo A, Visca A, Massini G, Patrolecco L, Miritana VM, Grenni P (2020b) Environmental fate of antibiotics and resistance genes in livestock waste and digestate from biogas plants. Environ Sci Poll Res Manag ESPRM. https://doi.org/10.37722/ESPR AM.20201.102

Barra Caracciolo A, Visca A, Rauseo J, Spataro F, Garbini GL, Grenni P, Mariani L, Mazzurco Miritana V, Massini G, Patrolecco L (2022) Bioaccumulation of antibiotics and resistance genes in let-tuce following cattle manure and digestate fertilization and their effects on soil and phyllosphere microbial communities. Environ Pollut 315:120413. https://doi.org/10.1016/j.envpol.2022.120413

Bustamante MA, Ceglie FG, Aly A, Mihreteab HT, Ciaccia C, Titarelli F (2016) Phosphorus availability from rock phosphate: combined effect of green waste composting and sulfur addition. J Environ Manage 182:557-563. https://doi.org/10.1016/j.jenvm.an.2016.08.016

Ciadamidaro L, Madejón P, Camacho F, Fernández Boy E, Madejón E (2016) Organic compost to improve contaminated soil quality and plant fertility. Soil Sci 181(11/12):487-493. https://doi.org/10.1097/SS.0000000000000186

Congilosil JL, Wallace JS, Neher TP, Howe A, Soupir ML, Aga DS (2022) Co-occurrence of antimicrobials and metals as potential drivers of antimicrobial resistance in swine farms. Front Environ Sci 10:1018739. https://doi.org/10.3389/fenvs.2022.1018739

Cycón M, Mrozik A, Piotrowska-Seget Z (2019) Antibiotics in the soil environment—degradation and their impact on microbial activity and diversity. Front Microbiol 10:338. https://doi.org/10.3389/fmicb.2019.00338

Di Lenola M, Barra Caracciolo A, Grenni P, Ancona V, Rauseo J, Laudicina VA, Uricchio VF, Massacci A (2018) Effects of Apriolio addition and Alfalfa and compost treatments on the natural microbial community of a historically PCB-contaminated soil. Water Air Soil Pollut 229:143. https://doi.org/10.1007/s11270-018-3803-4

Eriksen GN, Coale FJ, Bollero GA (1999) Soil nitrogen dynamics and maize production in municipal solid waste amended soil. Agron J 91:1009-1016. https://doi.org/10.2134/agronj.1999.9161009x

EU (2018) Regulation (EU) 2018/848: the new EU organic food law: war in the villages or a new kind of coexistence. Eur Food Feed L Rev 14:15

EU (2006) Communication from the Commission to the Council, the European Parliament, the European Economic and Social Committee and the Committee of Regions. Brussels. European Commission, COM(2006) 231 final

EU (2021) Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions EU Soil Strategy for 2030 Reaping the benefits of healthy soils for people, food, nature and climate. Brussels, European Commission, COM/2021/699 final

EU, the Council (2019) European Parliament and (2019) Regulation (EU) 2019/1009 of the European Parliament and of the Council of 5 June 2019 Laying Down Rules on the Making Available on the Market of EU Fertilising Products and Amending Regulations (EC) No 1069/2009 and (EC) No 1107/2009 and Repealing Regulation (EC) No 2003/2003

Garbini GL, Barra Caracciolo A, Rolando L, Visca A, Borello D, Cosentini C, Gagliardi G, Ieropoulos I, Grenni P (2023) Effects of municipal waste compost on microbial biodiversity and energy production in terrestrial microbial fuel cells. N Biotechnol 78:131-140. https://doi.org/10.1016/j.nbt.2023.10.009

García-Delgado C, Delgado-Moreno L, Toro M, Puñal M, Martín-Trueba M, Eymar E, Ruiz AI (2023) The role of biochar and green compost amendments in the adsorption, leaching, and degradation of sulfamethoxazole in basic soil. Chemosphere 344:140364. https://doi.org/10.1016/j.chemosphere.2023.140364

Gillings MR, Gaze WH, Pruden A, Smalla K, Tiedje JM, Zhu Y-G (2015) Using the class 1 integron-integrase gene as a proxy for anthropogenic pollution. ISME J 9:1269-1279. https://doi.org/10.1038/ismej.2014.226
Glibota N, Grande Burgos MJ, Gálvez A, Ortega E (2019) Copper tolerance and antibiotic resistance in soil bacteria from Olive tree agricultural fields routinely treated with copper compounds. J Sci Food Agric 99:4677-4685. https://doi.org/10.1002/jsfa.9708

Grenni P, Barra Caracciolo A, Rodríguez-Cruz MS, Sánchez-Martín MJ (2009) Changes in the microbial activity in a soil amended with oak and pine residues and treated with linuron herbicide. Appl Soil Ecol 41:2-7. https://doi.org/10.1016/j.apsoil.2008.07.006

Grenni P, Rodríguez-Cruz MS, Herrero-Hernández E, Marín-Benito JM, Sánchez-Martín MJ, Barra Caracciolo A (2012) Effects of wood amendments on the degradation of terbuthylazine and on soil microbial community activity in a clay loam soil. Water Air Soil Pollut 223:5401-5412. https://doi.org/10.1007/s11270-012-1289-z

Grenni P, Ancona V, Barra Caracciolo A (2018) Ecological effects of antibiotics on natural ecosystems: a review. Microchem J 136:25-39. https://doi.org/10.1016/j.microc.2017.02.006

Grenni P, Patrolecco L, Rauseo J, Spataro F, Di Lenola M, Aimola G, Zacchini M, Pietrini F, Di Baccio D, Stanton IC, Gaze WH, Barra Caracciolo A (2019) Sulfamethoxazole persistence in a river water ecosystem and its effects on the natural microbial community and *Lemna minor* plant. Microchem J 149:103999. https://doi.org/10.1016/j.microc.2019.103999

Grenni P, Visca A, Barra Caracciolo A (2024) Antibiotics as emerging pollutants of soil ecosystems. In: Núñez-Delgado A (ed) Frontier studies in soil science. Frontier studies in soil science. Springer, Cham, pp 21-41. https://doi.org/10.1007/978-3-031-50503-4_2

Hargreaves JC, Adl MS, Warman PR (2008) A review of the use of composted municipal solid waste in agriculture. Agric Ecosyst Environ 123:1-14. https://doi.org/10.1016/j.agee.2007.07.004

Jubeh B, Breijyeh Z, Karaman R (2020) Resistance of Gram-Positive bacteria to current antibacterial agents and overcoming approaches. Molecules 25:2888. https://doi.org/10.3390/molecu les25122888

Kairigo P, Ngumba E, Sundberg L-R, Gachanja A, Tuhkanen T (2020) Occurrence of antibiotics and risk of antibiotic resistance evolution in selected Kenyan wastewaters, surface waters and sediments. Sci Total Environ 720:137580. https://doi.org/10.1016/j.s citotenv.2020.137580

Karimi B, Masson V, Guilland C, Leroy E, Pellegrinelli S, Giboulot E, Maron P-A, Ranjard L (2021) Ecotoxicity of copper input and accumulation for soil biodiversity in vineyards. Environ Chem Lett 19:2013-2030. https://doi.org/10.1007/s10311-020-01155-x

La Torre A, Iovino V, Caradonia F (2018) Copper in plant protection: current situation and prospects. Phytopathol Mediterr 57:201-236

Lakshmipathi RN, Subramanyam B, Narotham Prasad BD (2019) Microorganisms, Organic Matter Recycling and Plant Health. In: Plant health under biotic stress. In: Ansari R, Mahmood I (eds) Plant health under biotic stress. Springer, Singapore, pp 187-212. https://doi.org/10.1007/978-981-13-6043-5_10

Lebron I, Feeney CJ, Reinsch S, Shokri N, Afshar MH, Lofts S, Griffiths R, Fidler D, Jones B, Panagos P, Sawicka K, Keith AM, Seaton F, Robinson DA (2025) Patterns and thresholds for soil pH across Europe in relation to soil health and degradation. CATENA 260:109454. https://doi.org/10.1016/j.catena.2025.109454

Manageiro V, Félix D, Jones-Dias D, Sampaio DA, Vieira L, Sancho L, Ferreira E, Caniça M (2017) Genetic background and expression of the new qepA4 gene variant recovered in clinical TEM-1- and CMY-2-producing *Escherichia coli*. Front Microbiol 8:1899. https://doi.org/10.3389/fmicb.2017.01899

Mangalassery S, Kalaivanan D, Philip PS (2019) Effect of inorganic fertilisers and organic amendments on soil aggregation and biochemical characteristics in a weathered tropical soil. Soil Tillage Res 187:144-151. https://doi.org/10.1016/j.still.2018.12.008

Marzaioli R, D'Ascoli R, De Pascale RA, Rutigliano FA (2010) Soil quality in a Mediterranean area of Southern Italy as related to different land use types. Appl Soil Ecol 44:205-212. https://doi.org/10.1016/j.apsoil.2009.12.007

Mathur SP, Owen G, Dinel H, Schnitzer M (1993) Determination of compost biomaturity. I. Literature review. Biol Agric Hortic 10:65-85. https://doi.org/10.1080/01448765.1993.9754655

Mazhar SH, Li X, Rashid A, Su J, Xu J, Brejnrod AD, Su J-Q, Wu Y, Zhu Y-G, Zhou SG, Feng R, Rensing C (2021) Co-selection of antibiotic resistance genes, and mobile genetic elements in the presence of heavy metals in poultry farm environments. Sci Total Environ 755:142702. https://doi.org/10.1016/j.scitotenv.2020.142702

Mhete M, Eze PN, Rahube TO, Akinyemi FO (2020) Soil properties influence bacterial abundance and diversity under different land-use regimes in semi-arid environments. Sci Afr 7:e00246. https://doi.org/10.1016/j.sciaf.2019.e00246

Morra L (2019) Role of compost in the organic amendment of vegetable crops. Ital Hortus 27. https://doi.org/10.26353/j.itahort/2019.2.2739

Nandi S, Maurer JJ, Hofacre C, Summers AO (2004) Gram-positive bacteria are a major reservoir of class 1 antibiotic resistance integrons in poultry litter. PNAS 101:7118-7122. https://doi.org/10.1073/pnas.0306466101

Narciso A, Barra Caracciolo A, De Carolis C (2023) Overview of direct and indirect effects of antibiotics on terrestrial organisms. Antibiotics 12:1471. https://doi.org/10.3390/antibiotics12091471

Narciso A, Grenni P, Spataro F, De Carolis C, Rauseo J, Patrolecco L, Garbini GL, Rolando L, Iannelli MA, Bustamante MA, Alvarez-Alonso C, Barra Caracciolo A (2024) Effects of sulfamethoxazole and copper on the natural microbial community from a fertilized soil. Appl Microbiol Biotechnol 108:516. https://doi.org/10.1007/s00253-024-13324-x

Nonthakaew N, Sharkey LKR, Pidot SJ (2025) The genus *Nocardia* as a source of new antimicrobials. NPJ Antimicrob Resist 3:5. https://doi.org/10.1038/s44259-025-00075-6

Pan M, Chu LM (2017) Fate of antibiotics in soil and their uptake by edible crops. Sci Total Environ 599-600:500-512. https://doi.org/10.1016/j.scitotenv.2017.04.214

Pan J, Zheng N, An Q, Li Y, Sun S, Zhang W, Song X (2023) Effects of cadmium and copper mixtures on antibiotic resistance genes in rhizosphere soil. Ecotoxicol Environ Saf 259:115008. https://doi.org/10.1016/j.ecoenv.2023.115008

Pan J, Zheng N, An Q, Li Y, Sun S, Wang S, Ji Y, Li N (2024) The effects of cadmium-copper stress on the accumulation of antibiotic-resistance genes in soil and pakchoi leaves. Soil Biol Biochem 191:109362. https://doi.org/10.1016/j.soilbio.2024.109362

Panagos P, Ballabio C, Lugato E, Jones A, Borrelli P, Scarpa S, Orgiazzi A, Montanarella L (2018) Potential sources of anthropogenic copper inputs to European agricultural soils. Sustainability 10:2380. https://doi.org/10.3390/su10072380

Panuccio MR, Mallamaci C, Attinà E, Muscolo A (2021) Using digestate as fertilizer for a sustainable tomato cultivation. Sustainability 13:1574. https://doi.org/10.3390/su13031574

Prasannamedha G, Kumar PS (2020) A review on contamination and removal of sulfamethoxazole from aqueous solution using cleaner techniques: present and future perspective. J Clean Prod 250:119553. https://doi.org/10.1016/j.jclepro.2019.119553

Prashar P, Kapoor N, Sachdeva S (2014) Rhizosphere: its structure, bacterial diversity and significance. Rev Environ Sci Biotechnol 13:63-77. https://doi.org/10.1007/s11157-013-9317-z

Rammali S, Hilali L, Dari K, Bencharki B, Rahim A, Timinouni M, Gaboune F, El Alaoui M, khattabi A (2022) Antimicrobial and antioxidant activities of Streptomyces species from soils of three different cold sites in the Fez-Meknes region Morocco. Sci Rep 12:17233. https://doi.org/10.1038/s41598-022-21644-z
Rauseo J, Barra Caracciolo A, Ademollo N, Cardoni M, Di Lenola M, Gaze W, Stanton I, Grenni P, Pescatore T, Spataro F, Patrolecco L (2019) Dissipation of the antibiotic sulfamethoxazole in a soil amended with anaerobically digested cattle manure. *J Hazard Mater* 378:120769. https://doi.org/10.1016/j.jhazmat.2019.120769

Rehman M, Liu L, Wang Q, Saleem MH, Bashir S, Ullah S, Peng D (2019) Copper environmental toxicology, recent advances, and future outlook: a review. *Environ Sci Pollut Res* 26:18003–18016. https://doi.org/10.1007/s11356-019-05073-6

Reyes-Torres M, Oviedo-Ocaña ER, Dominguez I, Komilis D, Sánchez A (2018) A systematic review on the composting of green waste: feedstock quality and optimization strategies. *Waste Manag* 77:486–499. https://doi.org/10.1016/j.wasman.2018.04.037

Santorufo L, Memoli V, Panico SC, Esposito F, Vitale L, Di Natale G, Trifuoggi M, Barile R, De Marco A, Maisto G (2021) Impact of anthropic activities on soil quality under different land uses. *Int J Environ Res Public Health* 18:8423. https://doi.org/10.3390/ije rph18168423

Sánchez-Navarro V, Peñalver A, Zornoza R, Fernández-Calviño D (2024) In Best Soil Handbook for soil sampling procedures and methodologies for the measurement of soil health indicators

Sodhi KK, Singh DK (2021) Insight into the fluoroquinolone resistance, sources, ecotoxicity, and degradation with special emphasis on ciprofloxacin. *J Water Process Eng* 43:102218. https://doi.org/10.1016/j.jwpe.2021.102218

Sultana R, Islam SMN, Shuvo SB, Ehsan GMdA, Saha P, Khan MdMR, Rumman N (2024) Endophytic bacterium *Sphingomonas panaciterrae* NB5 influences soil properties and improves growth, nutrient contents, and yield of red amaranth (*Amaranthus tricolor* L.). *Curr Plant Biol* 39:100372. https://doi.org/10.1016/j.cpb.2024.100372

Sun H, Bjerketorp J, Levenfors JJ, Schnürer A (2020) Isolation of anti-biotic-resistant bacteria in biogas digestate and their susceptibility to antibiotics. *Environ Pollut* 266:115265. https://doi.org/10.1016/j.envpol.2020.115265

Sun B, Bai Z, Li R, Song M, Zhang J, Wang J, Zhuang X (2024) Efficient elimination of antibiotic resistome in livestock manure by semi-permeable membrane covered hyperthermophilic composting. *Bioresour Technol* 407:131134. https://doi.org/10.1016/j.bio rtech.2024.131134

Tabatabai MA (1982) Soil Enzymes. In: Page AL (ed) Chemical and Microbiological Properties, vol 9. Wiley Online Library, pp 903–947. https://doi.org/10.2134/agronmonogr9.2.2ed.c43

Tabatabai MA (1994) Soil enzymes. Methods Soil Analysis: Part 2 Microbiol Biochem Prop 5:775–833. https://doi.org/10.2136/sss abookser5.2.c37

Tabatabai MA, Bremner JM (1969) Use of p-nitrophenyl phosphate for assay of soil phosphatase activity. *Soil Biol Biochem* 1:301–307. https://doi.org/10.1016/0038-0717(69)90012-1

Takahashi S, Tomita J, Nishioka K, Hisada T, Nishijima M (2014) Development of a prokaryotic universal primer for simultaneous analysis of bacteria and archaea using next-generation sequencing. *PLoS One* 9:e105592. https://doi.org/10.1371/journal.pone.0105592

Tang S, Liang J, Gong J, Song B, Yang Z, Fang S, Zhang P, Cao W, Li J, Luo Y (2021) The effects of biochar/compost for adsorption behaviors of sulfamethoxazole in amended wetland soil. *Environ Sci Pollut Res* 28:49289–49301. https://doi.org/10.1007/s11356-021-13959-7

Toyama T, Kobayashi M, Rubiyatno, Morikawa M, Mori K (2024) Sulfamethoxazole removal and fuel-feedstock biomass production from wastewater in a phyto-Fenton process using duckweed culture. *Chemosphere* 361:142592. https://doi.org/10.1016/j.che mosphere.2024.142592

USDA (1987) Soil Textural Classification Study Guide. United States Department of Agriculture- Soil Conservation Service, Washington DC

Vaverková MD, Adamcová D, Winkler J, Koda E, Petrželová L, Maxianová A (2020) Alternative method of composting on a reclaimed municipal waste landfill in accordance with the circular economy: benefits and risks. *Sci Total Environ* 723:137971. https://doi.org/10.1016/j.scitotenv.2020.137971

Visca A, Barra Caracciolo A, Grenni P, Patrolecco L, Rauseo J, Massini G, Mazzurco Miritana V, Spataro F (2021) Anaerobic digestion and removal of Sulfamethoxazole, Enrofloxacin, Ciprofloxacin and their antibiotic resistance genes in a full-scale biogas plant. *Antibiotics* 10:502. https://doi.org/10.3390/antibiotics10050502

Visca A, Rauseo J, Spataro F, Patrolecco L, Grenni P, Massini G, Mazzurco Miritana V, Barra Caracciolo A (2022) Antibiotics and antibiotic resistance genes in anaerobic digesters and predicted concentrations in agroecosystems. *J Environ Manage* 301:113891. https://doi.org/10.1016/j.jenvman.2021.113891

Vives-Peris V, de Ollas C, Gómez-Cadenas A, Pérez-Clemente RM (2020) Root exudates: from plant to rhizosphere and beyond. *Plant Cell Rep* 39:3–17. https://doi.org/10.1007/s00299-019-02447-5

Wang B, Shao Y, Chen F (2015) Overview on mechanisms of acetic acid resistance in acetic acid bacteria. *World J Microbiol Biotechnol* 31:255–263. https://doi.org/10.1007/s11274-015-1799-0

Yukphan P, Malimas T, Potacharoen W, Tanasupawat S, Tanticharoen M, Yamada Y (2005) *Neoasaia chiangmaiensis* gen. nov., sp. nov., a novel osmotolerant acetic acid bacterium in the *α*-Proteobacteria. *J Gen Appl Microbiol* 51:301–311. https://doi.org/10.2323/jgam.51.301

Zhang R, Gu J, Wang X, Qian X, Duan M, Sun W, Zhang Y, Li H, Li Y (2017) Relationships between Sulfachloropyridazine sodium, zinc, and sulfonamide resistance genes during the anaerobic digestion of swine manure. *Bioresour Technol* 225:343–348. http://doi.org/10.1016/j.biortech.2016.10.057

Zhang X, Zhu R, Li W, Ma J, Lin H (2021) Genomic insights into the antibiotic resistance pattern of the tetracycline-degrading bacterium, *Arthrobacter nicotianae* OTC-16. *Sci Rep* 11:15638. https://doi.org/10.1038/s41598-021-94840-y

Zhang Y, Cheng D, Xie J, Zhang Y, Wan Y, Zhang Y, Shi X (2022) Impacts of farmland application of antibiotic-contaminated manures on the occurrence of antibiotic residues and antibiotic resistance genes in soil: a meta-analysis study. *Chemosphere* 300:134529. https://doi.org/10.1016/j.chemosphere.2022.134529

Zhou T, Cao L, Zhang Q, Liu Y, Xiang S, Liu T, Ruan R (2021) Effect of chlortetracycline on the growth and intracellular components of *Spirulina platensis* and its biodegradation pathway. *J Hazard Mater* 413:125310. https://doi.org/10.1016/j.jhazmat.2021.125310

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