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Article

A Preliminary Investigation into Heavy Metal Tolerance in Pseudomonas Isolates: Does the Isolation Site Have an Effect?

by
Alessandro De Santis
,
Antonio Bevilacqua
*,
Angela Racioppo
,
Barbara Speranza
,
Maria Rosaria Corbo
,
Clelia Altieri
and
Milena Sinigaglia
Department of Agriculture, Food, Natural Resources and Engineering, University of Foggia, Via Napoli 25, 71122 Foggia, Italy
*
Author to whom correspondence should be addressed.
Agriculture 2025, 15(15), 1692; https://doi.org/10.3390/agriculture15151692
Submission received: 26 June 2025 / Revised: 31 July 2025 / Accepted: 3 August 2025 / Published: 5 August 2025
(This article belongs to the Special Issue Functional Regulation of Soil Microorganisms in Agricultural Ecosystems: Impact on Agronomical Practices)
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Abstract

One hundred presumptive Pseudomonas isolates, recovered from 15 sites impacted by anthropogenic activity in the Foggia district (Italy), were screened for key adaptive and functional traits important for environmental applications. The isolates were phenotypically characterized for their ability to grow under combined pH (5.0–8.0) and temperature (15–37 °C) conditions, to produce proteolytic enzymes, pigments, and exopolysaccharides, and to tolerate SDS. Moreover, the resistance to six environmentally relevant heavy metals (Cd, Co, Cu, Ni, Zn, As) was qualitatively assessed. The results highlighted wide inter-strain variability, with distinct clusters of isolates showing unique combinations of stress tolerance, enzymatic potential, and resistance profile. PERMANOVA analysis revealed significant effects of both the isolation site and the metal type, as well as their interaction, on the observed resistance patterns. A subset of isolates showed co-tolerance to elevated temperatures and heavy metals. These findings offer an initial yet insightful overview of the adaptive diversity of soil-derived Pseudomonas, laying the groundwork for the rational selection of strains for bioaugmentation in contaminated soils.

1. Introduction

Soil ecosystems represent one of the most diverse and functionally essential components of the terrestrial biosphere, sustaining a vast array of microbial life that mediates critical biogeochemical processes [1]. Among soil microorganisms, bacteria of the Pseudomonas genus have garnered significant attention due to their exceptional metabolic versatility, ecological plasticity, and potential applications in agro-environmental management and bioremediation [2]. However, increasing anthropogenic pressures, such as contamination by petroleum hydrocarbons, heavy metals, and phytochemical residues, are altering soil functions and imposing substantial stress on resident microbial communities [3]. These disturbances not only compromise nutrient cycling and soil fertility but also affect microbial diversity and activity at both the structural and functional levels. In this context, understanding the ecological roles and adaptive mechanisms of Pseudomonas spp. in contaminated soils is critical for developing effective microbial-based remediation strategies aligned with sustainable environmental management goals [4].
Species of the Pseudomonas genus are characterized by their broad catabolic potential, rapid growth rate, high motility, and ability to synthesize a wide array of secondary metabolites, including biosurfactants, siderophores, and degradative enzymes. These features confer a selective advantage in nutrient-limited or chemically stressed environments and support their adaptation to contaminated soils [5]. Strains belonging to P. putida and P. aeruginosa species have demonstrated the ability to degrade various environmental pollutants, including polycyclic aromatic hydrocarbons and chlorinated solvents, via specific enzymatic pathways [6,7,8].
Although metal tolerance and bioremediation are mechanistically distinct processes, they are often interrelated. Many Pseudomonas strains that exhibit high levels of resistance to heavy metals, through mechanisms such as efflux pumps (e.g., CzcCBA, CopA), sequestration by metallothioneins or polyphosphates, and binding via exopolysaccharides, also possess enhanced capabilities for biosorption and enzymatic detoxification [9,10,11,12]. These traits not only allow survival in toxic conditions but can also promote active biotransformation of contaminants.
Moreover, the ability of Pseudomonas spp. to form biofilms and adapt to fluctuating pH, temperature, and oxygen levels enhances their resilience and persistence in contaminated soils, both in situ and under engineered remediation settings [13]. The growing body of research continues to elucidate the regulatory networks and stress response systems that underpin their environmental adaptability, reinforcing the relevance of Pseudomonas as a model genus in environmental microbiology and applied biotechnology.
The implementation of effective microbial remediation strategies requires a careful selection and characterization of bacterial strains exhibiting ecological fitness, high resistance under different stress conditions and high degradation potential under site-specific environmental conditions [14]. Within the Pseudomonas genus, considerable inter-strain variability exists, highlighting the need for robust screening protocols to identify the most promising candidates [15]. Traditional approaches include phenotypic assays based on growth kinetics, pollutant tolerance, and enzymatic activity, performed under simulated soil conditions or in the presence of contaminant analogues. The success of Pseudomonas-based bioremediation depends not only on the intrinsic catabolic capacity but also on the organism’s ability to survive, persist, and interact with native microbiota and host plants in the targeted environment [16].
Abiotic factors such as the pH, temperature, moisture content, and contaminant load significantly influence microbial survival, activity, and community structure, thereby affecting the efficiency of bioremediation processes. Although Pseudomonas spp. are generally resilient, they exhibit variable physiological responses to these stressors. For example, suboptimal pH conditions may inhibit membrane transport systems and enzymatic activity, whereas nutrient imbalances, particularly carbon-to-nitrogen ratios, can shift metabolic pathways away from xenobiotic degradation [16,17].
Pollutant bioavailability is often limited by adsorption into soil particles or entrapment in micropores, reducing microbial access and metabolic uptake. This challenge is often addressed using biosurfactant-producing strains of Pseudomonas, which enhance the solubility and dispersion of hydrophobic compounds. Similarly, the presence of heavy metals can exert selective pressure on microbial communities, favoring the proliferation of metal-resistant genotypes but simultaneously suppressing the overall diversity and function. To mitigate such constraints, engineered approaches such as bioaugmentation and bioventing are frequently combined with microbial inoculation to optimize environmental conditions for target strain performance [18].
Recent advances in microbial biotechnology and systems biology have led to the development of next-generation remediation strategies that move beyond traditional single-strain applications. Increasingly, research is focusing on the design and deployment of naturally co-evolved microbial consortia, in which Pseudomonas spp. often serve as keystone degraders due to their complementary metabolic roles and ecological robustness [19]. These consortia can be tailored to site-specific contaminant profiles and environmental conditions, enhancing the degradation efficiency and functional resilience [20]. Furthermore, co-inoculation with arbuscular mycorrhizal fungi and plant growth-promoting rhizobacteria (PGPR) can synergistically improve plant health and pollutant uptake in phytoremediation systems [21], with Pseudomonas acting as both a facilitator of degradation and a root colonizer [22].
Despite the growing interest in microbial resistance to heavy metals, relatively few studies have investigated Pseudomonas isolates from unmanaged contaminated soils under real-world, multi-stressor conditions. Limited attention has been paid to how the history and typology of anthropogenic contamination may influence adaptive traits such as metal tolerance, acid–base resilience, and thermotolerance.
This study focuses on contaminated soils from the Foggia district (Apulia region, Southern Italy), a territory with many sites subjected to intense and long-standing anthropogenic pressures. The waste materials observed in these areas are largely composed of municipal solid waste (MSW), including plastics, packaging, household debris, etc., often mixed with construction rubble, obsolete electronics, and small-scale industrial discards. According to recent estimates by Legambiente [23], over 618,000 tons of such illegal waste have been deposited throughout the province of Foggia, particularly in marginal or unregulated zones. Complementary to this, the ARPA Puglia report 2022 [24] documents over 120 officially registered contaminated or potentially contaminated sites in the province of Foggia. These include former landfills, illegal dumping areas, and disused industrial zones. Environmental monitoring of these sites has revealed frequent exceedances of contamination thresholds for several key pollutants in surface soils, especially heavy metals (e.g., Pb, Zn, Cu, As, Sn), organotin compounds, hydrocarbons (C > 12), and in some cases, PCBs and PAHs.
This complex contamination scenario, shaped by the coexistence of organic and inorganic pollutants, provides a realistic context for investigating the adaptive responses of indigenous soil bacteria. In particular, the persistence of heavy metals associated with decomposing waste and electronic residues is likely to exert selective pressure on microbial communities. The absence of remediation measures further reinforces the chronic nature of this environmental stressor and its potential impact on soil microbial ecology and functionality. Therefore, this study aimed to explore the phenotypic and functional variability of Pseudomonas spp. isolates collected from contaminated areas in the Foggia district, focusing on their ability to tolerate heavy metals, pH fluctuations, and thermal stress. In addition, we investigated whether the site of origin, reflecting different types and intensities of anthropogenic disturbance, influenced the adaptive profiles of the isolates, with the broader goal of identifying potential ecological associations between environmental pressure and microbial resistance traits.

2. Materials and Methods

2.1. Isolation and Preservation of Pseudomonas spp.

A total of 100 presumptive Pseudomonas spp. isolates were obtained in Spring 2023 from 15 contaminated soil samples collected from the topsoil layer (0–15 cm depth) across the Foggia district (Apulia region, Italy). The GPS coordinates of each sample are reported in Table 1. The areas were chosen based on visible evidence of long-standing anthropogenic impact, particularly urban solid waste accumulation, and included roadside verges, abandoned peri-urban lots, and uncultivated rural zones.
Soil samples were collected under sterile conditions using clean spatulas and stored in sterile containers. Samples were transported to the laboratory under refrigerated conditions and processed within 24 h to limit the microbial community shifts during transport. Presumptive identification of the isolates as Pseudomonas spp. was based on selective cultivation on Pseudomonas Agar Base (PAB, Oxoid, Milan) supplemented with CFC (cetrimide–fucidin–cephaloridine) (Oxoid), which inhibits the growth of Gram-positive bacteria and many Gram-negative genera [25]. Colonies exhibiting typical morphology and pigmentation were further subcultured and tested for oxidase activity. Although molecular confirmation (e.g., 16S rRNA gene sequencing) was not performed in this study, it is planned for future work. The purified cultures were maintained on Nutrient Agar (Oxoid) slants at 4 °C for short-term storage and cryopreserved in Nutrient broth + 33% glycerol (J.T. Baker, Milan) at −20 °C for long-term use.
All the isolates were subsequently subjected to a series of biochemical and functional assays, including tolerance tests against heavy metals (Cu, Zn, Pb, among others), pH (acidic and alkaline), and temperature stress, in order to assess their ecological fitness under contaminated soil conditions. These assays aimed to identify phenotypic traits associated with environmental resilience and potential applicability in microbial-based bioremediation strategies.

2.2. Phenotyping

The ability of isolates to produce fluorescent pigments was assessed by streaking on Nutrient Agar (NA; Oxoid). Plates were incubated at 25 °C for 48–72 h and examined under visible light and ultraviolet (UV) illumination at 365 nm using a Wood’s lamp [26]. Pigment production was recorded qualitatively as the presence or absence of fluorescence. To further evaluate the synthesis of blue pigments (e.g., pyocyanin), isolates were also streaked on Mascarpone Agar (prepared as per Chierici et al. [27]) and incubated at 25 °C for 24–48 h. Blue pigment expression was recorded qualitatively, based on the presence or absence of visible pigmentation in the agar.
EPS production was evaluated by two Congo Red Agar (CRA) protocols. The first was the original method reported by Freeman et al. [28], slightly modified by using NA supplemented with 5% (w/v) sucrose as the carbon source. The second followed the protocol reported by Maalej et al. [29], which uses 1% (w/v) glucose in NA. In both cases, Congo Red was added at a final concentration of 0.8 g/L after autoclaving.
Plates were incubated at 25 °C for 72 h, and EPS production was assessed qualitatively, based on the colony morphology, dye absorption, and mucoid consistency. Colonies were classified as positive when they appeared black, shiny, and viscous, and as negative when they were red, dry, and flat.
Protease activity was assessed using Skim Milk Agar (SMA) prepared according to the method of Pailin et al. [30], with modifications. A 10% (w/v) skim milk powder solution was reconstituted in distilled water and autoclaved at 121 °C for 5 min. After cooling, it was added to sterile Nutrient Agar (Oxoid) to obtain final skim milk concentrations of 5% and 10% (v/v).
Each Pseudomonas isolate was spot-inoculated with 10 μL of a 24 h culture onto both SMA formulations and incubated at 25 °C for 48 h. Proteolytic activity was assessed qualitatively by the presence or absence of clear halos surrounding colonies, indicating casein hydrolysis. Negative control plates (uninoculated) were used to exclude spontaneous clearing.
Resistance to sodium dodecyl sulfate (SDS) was evaluated following the protocol described by Furmanczyk et al. [31]. The test medium was M9 minimal agar. After autoclaving, the medium was cooled to 50 °C and supplemented with cold, filtrated SDS at a final concentration of 2% (w/v).
Each Pseudomonas isolate was spot-inoculated (20 μL) and incubated at 25 °C for 48 h. Growth was assessed qualitatively, based on the presence or absence of a visible halo.
The antagonistic potential of Pseudomonas isolates was evaluated using the method of Fernández-Fernández et al. [32] modified as follows. The test was conducted against Bacillus subtilis DSM 10, obtained from the bacterial collection of the University of Foggia. A fresh overnight culture of B. subtilis was streaked onto NA plate (9 cm diameter) and incubated at 37 °C for a few hours (no more than 4 h). After incubation, each Pseudomonas isolate was spot-inoculated (20 μL) in the middle of a plate and incubated at 25 °C for 48 h under aerobic conditions. Antibacterial activity was evaluated qualitatively, based on the presence or absence of visible inhibition halos surrounding the Pseudomonas spot. Isolates were classified as positive (inhibition zone present) or negative (no inhibition). Each assay was performed in duplicate, and control plates without Pseudomonas inoculation were included (negative control).

2.3. Growth as a Function of the pH, Temperature and Heavy Metal Presence

To assess the physiological adaptability of the Pseudomonas isolates to environmental stress, each isolate was tested for its ability to grow on solid media under varying pH and temperature conditions, applying an internal protocol.
Bacterial suspensions were prepared from overnight cultures grown on Nutrient Agar, and 10 μL aliquots were streaked onto Nutrient Agar plates adjusted to pH 5.0, 6.0, and 8.0 using sterile HCl or NaOH, as appropriate. The pH of each batch of medium was confirmed using a calibrated pH meter (Hanna Instruments, Woonsocket, RI, USA). Following inoculation, the plates were incubated under aerobic conditions at three distinct temperatures: 15 °C, 25 °C, and 37 °C. Growth was recorded after 48 and 72 h and 1 week of incubation by visual inspection, with colony development indicating tolerance/growth (coded by “1”) or absence of growth (coded by “0”) according to the specific environmental condition.
The resistance of Pseudomonas isolates to selected heavy metals was assessed on solid Nutrient Agar supplemented with individual metal salts [33]. The following compounds were used as metal sources: cadmium chloride 2.5-hydrate (CdCl2·2.5H2O), copper(II) chloride dihydrate (CuCl2·2H2O), nickel(II) chloride hexahydrate (NiCl2·6H2O), zinc sulfate heptahydrate (ZnSO4·7H2O), sodium arsenite (NaAsO2), and cobalt(II) chloride hexahydrate (CoCl2·6H2O). Heavy metals were obtained from Sigma Aldrich (St. Louis, MO, USA).
Sterile stock solutions of each metal salt were added to the autoclaved molten Nutrient Agar to obtain final concentrations of 200 mg/L. Subsequently, the plate was streak-inoculated with overnight culture and incubated at 25 °C for 48 h under aerobic conditions. Bacterial growth was visually assessed and categorized as no growth (0) or growth (1). The heavy metals concentration was chosen as a standardized high threshold to qualitatively assess the tolerance potential under strong selective pressure. While environmental concentrations may vary significantly among metals, this level was adopted to facilitate statistical comparative screening across isolates, and it is consistent with previous studies on the phenotypic resistance profiling of soil bacteria [34,35].

2.4. Statistics

Data were preliminary converted into a binary code (1, growth/enzymatic activity present; 0, no growth/no activity), used to build frequency histograms for each assay (that is, the number of isolates showing growth in the tested condition), and preliminarily treated through a Chi-square test to point out possible differences. In cases where multiple comparisons were conducted across conditions, a Bonferroni correction was applied to adjust the significance threshold accordingly.
The growth in the presence of heavy metals was further analyzed and categorized as a function of the isolation site and heavy metal (that is, the number of positive strains for each site) and analyzed through PERMANOVA, using the site and the heavy metals as categorical predictors (independent variables) and the number of positive strains for each condition as the dependent variable. A graphical representation of this categorization was achieved through a heatmap, showing the number of strains able to growth in the presence of a specific heavy metal for each site.
The correlations among the different assayed parameters (growth at different pH and temperature, growth in the presence of heavy metal) were assessed through the Spearman coefficients.
Finally, cluster analysis and k-means were performed with the number of clusters ranging from 2 to 6; the optimal number of clusters was evaluated through silhouette coefficients; cluster quality was further assessed through purity. The k-means used the Euclidean distance as the amalgamation method; data were preliminarily standardized through the z-score.
The PERMANOVA and correlations were performed using PAST software, ver. 5.2.2. (https://www.nhm.uio.no/english/research/resources/past/, accessed on 30 July 2025). The Chi-square test and Bonferroni correction were performed using Statistica for windows, ver. 12.0 (StatSoft, Tulsa, OK, USA), while the clustering and k-means was conducted using Phyton, v1.3.0.

3. Results and Discussion

A total of 100 presumptive Pseudomonas isolates obtained from contaminated soils were evaluated for multiple traits related to the bioremediation potential. The strains were subjected to various metabolic and environmental stress conditions to assess their ability to survive and function in harsh environments, as typically encountered during soil bioremediation. The characterization included the evaluation of some metabolic traits connected to protein metabolism, resistance to SDS, pigment production and antimicrobial activity toward bacilli. In the second phase, growth as a function of the pH, temperature or heavy metal presence was assessed as a prodromal step toward characterization of biological tools for bioremediation.

3.1. Phenotypical and Technological Characterization of Presumptive Pseudomonas spp.

The isolates were evaluated for their ability to utilize different carbon sources, including complex and unconventional substrates, such as dairy proteins. Proteolytic activity was assessed on Skim Milk Agar, an uncommon protein substrate for soil bacteria but an interesting matrix for lab experiments to assess the proteolytic potential of bacteria. Here, 65% of isolates showed clear hydrolysis at 5%, while 58% were positive at 10% (Figure 1), suggesting a substantial proportion of strains possess enzymatic machinery capable of protein hydrolysis under nutrient-limited conditions. Pseudomonas generally has a complex proteolytic system, as also suggested by several authors for foodborne bacteria [36,37]; however, to best of the authors’ knowledge this aspect has not been fully explored in soil bacteria. Nevertheless, the presence of this enzymatic activity is indirect evidence of the catabolic potential of the studied isolates.
Pigment production was observed in only 4% of the isolates (Figure 1). This characteristic is typically associated with specific niches of P. aeruginosa and P. fluorescens [38]; a pigment is often produced in response to stress conditions [39] or is a tool to protect bacteria from oxidative stress and UV radiation [40]. In addition, pigment production is probably linked to iron acquisition, virulence, competition with other microorganisms, and quorum sensing [41,42]. However, the low frequency of this trait, at least for the isolates studied in the present research, suggests the need for confirmatory experiments, also including evaluation of the effects of environmental variables on pigment production.
An important experiment, as least for the present research, involved the degradation of SDS (sodium dodecyl sulfate), which is a common soil pollutant due to its widespread use in detergents and industrial applications; this characteristic was detected in 20% of the isolates (Figure 1), highlighting a subset of strains with potential relevance for bioremediation of surfactant-contaminated environments because of their ability to use such a harmful carbon source in harsh conditions [43].
In a complex matrix, microorganisms, including bioremediation tools, should interact with a huge microbiota, thus expressing negative or positive interactions. Aerobic spore-formers represent an important part of the bacterial microbiota of soil. Therefore, the antagonistic activity was tested by evaluating the inhibition of B. subtilis growth, as representative of soil spore-forming bacteria. This bioactivity, indicative of antimicrobial compound production or competitive traits important for survival in low-nutrients conditions [44], was observed in 19% of the isolates. Such antagonistic potential is commonly reported in Pseudomonas spp., as confirmed by Lyng et al. [45], reflecting the frequent competitive interactions between Bacillus and Pseudomonas genera [46].
Exopolysaccharide (EPS) production was assessed using two established protocols. The method described by Freeman et al. [28] yielded positive results in 17% of the strains, while the modified protocol reported by Maalej et al. [29] detected EPS production in 33% of the isolates (Figure 1). EPS could enhance surface adhesion, biofilm formation, and resilience under fluctuating environmental conditions [47]. In addition, EPS is involved in the interaction of rhizosphere bacteria with plants, along with nutrient delivery and availability [48]. Therefore, the selection of EPS-producing microorganisms is an added value for the correct role of bacteria in soil and for a potential use of wild microorganisms for a biological application.

3.2. Growth Response Under Combined pH and Temperature Conditions

After analyzing the metabolic potential of the soil isolates, the second step concerned the growth profile as a function of the pH, temperature, and heavy metal presence. Growth over a wide range of conditions is a main prerequisite for technological robustness of the assayed microorganisms.
To assess the physiological resistance of the Pseudomonas isolates, a combinatorial analysis of the pH and temperature effects on bacterial growth was conducted. Cultures were inoculated on Petri plates adjusted to three pH levels (5.0, 6.0, and 8.0) and incubated at three distinct temperatures (15 °C, 25 °C, and 37 °C). Observations were recorded at three points: 48 h, 72 h, and one week. The experiments, as for the assays in the presence of heavy metals, were performed in a complex laboratory medium, that is, Nutrient Agar. Although for ecophysiological assays minimal media should be used to avoid a masking effect due to the medium, preliminary experiments performed on the isolates tested in this study revealed that a minimal medium could exert an additive or synergistic effect with other stresses, thus masking effective resistance/sensitivity.
For each condition, the number of isolates exhibiting visible growth (presence of colonies) was quantified and expressed as the number of positive observations. The use of a solid medium, while exerting the benefit of a matrix similar to soil, at least for its macrostructure, does not consent to the “building” of a kinetic; therefore, the results were reported at different time intervals, as it is well known that some factors (mainly pH and temperature) could exert transient stress on bacteria.
After 48 h (Figure 2), 100% of isolates grew at 25 °C/pH 8.0, and 98% at 25 °C/pH 6.0 (98%), while a slightly lower proportion showed growth at 25 °C/pH 5.0 (86%) (p < 0.05). At 15 °C, the growth ranged from 85–90%, whereas at 37 °C, the growth was significantly reduced (54% at pH 5.0, p < 0.05). These results indicate an optimal growth range around 25 °C and near neutral to slightly alkaline pH.
These results suggest that Pseudomonas isolates exhibit optimal metabolic activity in mesophilic and near-neutral environments, a characteristic widely observed in the genus. In fact, previous studies have demonstrated that mesophilic temperatures (20–30 °C) and pH values between 6.5 and 8.0 support robust aerobic growth and membrane functionality in several Pseudomonas species [49]. The poor performance observed at 37 °C, especially under acidic stress, aligns with the known sensitivity to thermophilic conditions of Pseudomonas strains, which generally prefer a lower temperature and a neutral pH.
By 72 h (Figure 3), the growth had improved under most conditions. At 15 °C, the growth increased significantly (p < 0.05), suggesting cold adaptation in a portion of the population. The growth at 37 °C also improved modestly at pH 6.0 and 8.0 (67–77%, p < 0.05), indicating partial thermotolerance.
Similar delayed-growth patterns at low temperatures have been reported by Chahuan et al. [2], who highlighted cold-induced metabolic adjustments as keys elements of Pseudomonas adaptability under suboptimal conditions.
At 1 week (Figure 4), nearly all the isolates grew at 15 °C and 25 °C across all the pH levels, with 100% positivity at pH 6.0 and 8.0. Although the growth at 37 °C remained limited, a progressive increase in the number of positive isolates was observed, especially at pH 6.0 (77%) and pH 8.0 (67%) (p < 0.05).
These results suggest that Pseudomonas isolates exhibit significant ecological plasticity in response to combined abiotic stresses. The growth was robust at a near neutral to slightly alkaline pH and at mesophilic temperatures, with delayed but substantial adaptation to colder environments and moderate resilience to thermal stress when the pH was not acidic. The observed patterns are strongly supported by the current literature on Pseudomonas physiology and stress tolerance, which highlights the genus’ capacity to modulate key metabolic and structural features across variable environmental conditions [50,51].

3.3. Growth in Presence of Heavy Metals

The technological robustness was also assessed against six environmentally relevant heavy metals: sodium arsenite, cobalt (II) chloride hexahydrate, zinc sulphate heptahydrate, nickel (II) chloride hexahydrate, copper (II) chloride dihydrate, and cadmium chloride dihydrate. The concentration of 200 mg/L, although not environmentally representative, was deliberately chosen as a high-threshold screening level to identify strongly resistant isolates. Similar concentrations have been used in previous qualitative tolerance studies [34,35]. The results were converted into a binary code and used as the input for a PERMANOVA analysis, with the kind of heavy metal and isolation site as categorical predictors. However, sodium arsenite was not further used, as more than 90% of strains were positive in the assay, and these results could mask or cause statistical artifacts in the multivariate approaches.
To perform this analysis, the dataset was preliminary categorized by reporting for each site the number of positive strains for each heavy metal (that is, the number of strains growing in the assayed conditions). Categorization was performed through a heatmap showing the effective interaction site vs. the heavy metal tolerance (Figure 5); this picture shows the actual values in terms of the percentages of strains positive for growth in the presence of heavy metals for each site. This output revealed that most isolates from many sites showed a negative outcome (no growth in the presence of heavy metal), with some exceptions. The heatmap visually summarizes the distribution of resistance traits across sites. A darker cell indicates a higher proportion of tolerant isolates at that site for a given metal. Mainly, the isolates were tolerant (83 and 67%) if recovered from sites C and N, while at least 50% of isolates from sites A, C and H were tolerant of Zn (respectively, 62.5, 50 and 67%). Another interesting result was that the isolates from C were also tolerant of Co (at least 50% of them).
Then, a PERMANOVA was run. The outputs are in Table 2. Both predictors, as well as their interaction, were statistically significant.
Since the table provides no quantitative output, the results were also reported as the decomposition of the statistical hypothesis, that is, a “graphical portioning” of the effect of each predictor on the dataset; in accordance with the results reported in Section 3.2, these test data were also expressed as absolute frequencies. Regarding the site influence (Figure 6), the mean recovery of tolerant isolates varied considerably: site C showed the highest tolerance rate (37%), followed by sites A, D, E, and H (from 17 to 22%). Conversely, sites I, L, M, O, and Q showed the lowest tolerance (3–5%). This pattern may reflect site-specific environmental histories, such as prior exposure to industrial runoff or waste discharge, which select for resistant genotypes. Previous studies have reported similar geospatial clustering of resistance traits in Pseudomonas spp., often correlated with the localized anthropogenic impact [52] and heavy metal burden in soils [53,54,55].
Concerning the metal-specific tolerance (Figure 7), positive outcomes were observed as follows: 21% for zinc, 17% for cadmium, 14% for copper, 9% for nickel, and 6% for cobalt. These differences likely reflect variations in metal toxicity and bioavailability. Zinc is an essential micronutrient and is often tolerated, whereas cadmium and cobalt are non-essential and highly toxic even at low concentrations [56]. The relatively high cadmium tolerance may suggest an adaptive co-resistance mechanism, involving stress response pathways, as also demonstrated in other studies [57,58,59].

3.4. Correlation and Multivariate Analyses

The last step in this research employed multivariate approaches to address two main questions, that is, the existence of possible correlations among some phenotypic properties and the growth in the presence of heavy metals and the possibility of strain grouping into homogeneous classes. To address the first question, a multiple correlation was assessed through the Spearman coefficient. The output of this approach is a table showing a coefficient ranging from −1 (100% negative correlation) to +1 (100% positive correlation)
In Figure 8, a blue circle highlights a significant positive correlation; the most interesting result was the partial positive correlation of growth in the presence of cobalt (C8) with growth at 37 °C (C5 and C6) (coefficient of 0.22–0.24) or the growth in the presence of cobalt with cadmium (C7 and C8; coefficient at 0.22), while the use of SDS and casein (C12 and C13) were negatively related to some growth conditions (respectively, 25 °C/pH 8-C4, and 37 °C/pH 5, C5).
No direct causal relationship between cobalt resistance and thermotolerance has been reported in the literature to date; in addition, it is worth mentioning that a correlation does not imply a causation, also due to the low correlations. Further experiments at a molecular level are required to investigate the mechanisms beyond this trend and to demonstrate effective correlations, which might imply the upregulation of efflux pumps (e.g., CzcCBA, CopA) and molecular chaperones such as GroEL and GroES under both heavy metal exposure (e.g., Co2+, Cd2+, Cu2+) and elevated temperature [60,61].
The second question was about a possible isolate grouping, based on their response to phenotyping. Grouping was performed through cluster analysis and k-means, with the number of clusters ranging from two to six. However, the silhouette coefficient was the maximum for four clusters, with a value of 0.08, which was not high but was retained for further analysis, as this approach could be useful to point out possible subgroups among isolates. The cluster purity was 0.42, which highlights a degree of similarity among the groups; however, the analysis of the discriminant variables per each cluster revealed some key differences. The isolate attribution to each cluster is shown in the Supplementary Materials, while the key features of each cluster are shown in Table 3.
The four clusters were labeled as 0, 1, 2, and 3. Cluster 0 was composed of 26 isolates, which showed growth at 15 °C and pH 5 (coefficient at 0.69), and copper resistance (0.69). On the other hand, cluster 1 was characterized by resistance to cadmium and copper (respectively, for 72 and 80% of isolates).
In cluster 2, including 25 isolates, the key features were growth at pH 8/37 °C (0.92), SDS degradation (0.64) and casein hydrolysis (0.64). Finally, cluster 3 showed the highest resistance to cadmium and nickel (0.92, and 0.75), and growth at pH 5, both at 15 and 25 °C (0.79 and 0.88), suggesting adaptation to acidic and intermediate temperature conditions.
Although further experiments are required to confirm this at molecular levels, these results could suggest possible different ecological strategies among the isolates, which might reflect niche specialization in response to temperature, pH, and heavy metals.

4. Conclusions

This preliminary investigation explicates the phenotypic and functional variability of Pseudomonas spp. isolated from soils subjected to high anthropogenic pressure. The isolates demonstrated differential tolerance to abiotic stresses, particularly pH, temperature, and heavy metal exposure, underscoring their adaptive plasticity. Optimal growth was observed at 25 °C and neutral-to-slightly alkaline pH, whereas growth at 37 °C, especially under acidic conditions, was markedly reduced, indicating the general mesophilic nature of the tested strains. Heavy metal tolerance, at least for the thresholds tested in this research (200 mg/L), varied by both the compound and isolation site level, with zinc and cadmium being the most tolerated, and cobalt and nickel exerting stronger inhibitory effects. PERMANOVA analysis confirmed the statistical significance of site- and metal-specific effects, suggesting local selective pressures as key drivers in shaping resistance phenotypes. The phenotypic hierarchical clustering of the isolates provided an additional layer of insight, revealing partially distinct subgroups with divergent stress response capacities. Collectively, the data support the hypothesis that Pseudomonas spp. from contaminated environments constitute a valuable reservoir of traits exploitable for bioremediation under variable environmental conditions. In conclusion, this research represents a valuable step toward selecting and characterizing Pseudomonas isolates resistant to heavy metals, a first for a biological bioremediation approach. Further experiments are required to validate these preliminary results, including experiments at a molecular level, and to test the isolates on a wide range of concentrations of heavy metals.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/agriculture15151692/s1, Table S1: Dataset. Table S2: Isolate assignment to the phenotypic clusters.

Author Contributions

Conceptualization, A.B. and A.D.S.; methodology, A.B., M.S. and M.R.C.; investigation, A.D.S., B.S., C.A. and A.R.; data curation, A.B. and A.D.S.; software, A.B.; writing—original draft preparation, A.D.S. and A.B.; writing—review and editing, all authors; supervision, A.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

All data generated during this research are available in the Supplementary Materials without restrictions.

Conflicts of Interest

The authors declare no conflicts of interest.

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Agriculture 15 01692 g001
Figure 1. Phenotypic characterization of soil-derived Pseudomonas isolates. Bar plots indicate the percentage of strains positive for selected traits, including extracellular protease activity (5% and 10% skim milk), EPS production (Freeman and Maalej methods), pigment production, SDS degradation, and antagonism against B. subtilis (relative frequency).
Figure 1. Phenotypic characterization of soil-derived Pseudomonas isolates. Bar plots indicate the percentage of strains positive for selected traits, including extracellular protease activity (5% and 10% skim milk), EPS production (Freeman and Maalej methods), pigment production, SDS degradation, and antagonism against B. subtilis (relative frequency).
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Agriculture 15 01692 g002
Figure 2. Bar charts represent the number of isolates showing growth (presence of visible colonies) after 48 h on Nutrient Agar adjusted to pH 5.0, 6.0, and 8.0, and incubated at 15 °C (blue), 25 °C (orange), or 37 °C (gray) (absolute frequency). For each pH, the symbol “*” indicates a significant difference (Chi-square test, p < 0.05).
Figure 2. Bar charts represent the number of isolates showing growth (presence of visible colonies) after 48 h on Nutrient Agar adjusted to pH 5.0, 6.0, and 8.0, and incubated at 15 °C (blue), 25 °C (orange), or 37 °C (gray) (absolute frequency). For each pH, the symbol “*” indicates a significant difference (Chi-square test, p < 0.05).
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Agriculture 15 01692 g003
Figure 3. Bar charts represent the number of isolates showing growth (presence of visible colonies) after 72 h on Nutrient Agar adjusted to pH 5.0, 6.0, and 8.0, and incubated at 15 °C (blue), 25 °C (orange), or 37 °C (gray) (absolute frequency). For each pH, the symbol “*” indicates a significant difference (Chi-square test, p < 0.05).
Figure 3. Bar charts represent the number of isolates showing growth (presence of visible colonies) after 72 h on Nutrient Agar adjusted to pH 5.0, 6.0, and 8.0, and incubated at 15 °C (blue), 25 °C (orange), or 37 °C (gray) (absolute frequency). For each pH, the symbol “*” indicates a significant difference (Chi-square test, p < 0.05).
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Agriculture 15 01692 g004
Figure 4. Bar charts represent the number of isolates showing growth (presence of visible colonies) after 1 week on Nutrient Agar adjusted to pH 5.0, 6.0, and 8.0, and incubated at 15 °C (blue), 25 °C (orange), or 37 °C (gray) (absolute frequency). For each pH, the symbol “*” indicates a significant difference (Chi-square test, p < 0.05).
Figure 4. Bar charts represent the number of isolates showing growth (presence of visible colonies) after 1 week on Nutrient Agar adjusted to pH 5.0, 6.0, and 8.0, and incubated at 15 °C (blue), 25 °C (orange), or 37 °C (gray) (absolute frequency). For each pH, the symbol “*” indicates a significant difference (Chi-square test, p < 0.05).
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Agriculture 15 01692 g005
Figure 5. Heatmap showing the frequency (%) of isolates tolerant of each heavy metal across the 15 sampling sites. Rows represent heavy metals (Cr, Ni, Co, Zn, Cu, Pb), and columns represent sampling sites (A–Q). The color scale indicates the percentage of tolerant isolates, with darker shades corresponding to higher frequencies. Data were derived from presence/absence growth tests at 200 mg/L.
Figure 5. Heatmap showing the frequency (%) of isolates tolerant of each heavy metal across the 15 sampling sites. Rows represent heavy metals (Cr, Ni, Co, Zn, Cu, Pb), and columns represent sampling sites (A–Q). The color scale indicates the percentage of tolerant isolates, with darker shades corresponding to higher frequencies. Data were derived from presence/absence growth tests at 200 mg/L.
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Figure 6. Decomposition of the statistical hypothesis, via two-way PERMANOVA analysis, about the sampling sites, showing the distribution of samples across the 15 sampling sites (A–Q). Absolute frequency. Small letters indicate significant differences (p < 0.05).
Figure 6. Decomposition of the statistical hypothesis, via two-way PERMANOVA analysis, about the sampling sites, showing the distribution of samples across the 15 sampling sites (A–Q). Absolute frequency. Small letters indicate significant differences (p < 0.05).
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Agriculture 15 01692 g007
Figure 7. Decomposition of the statistical hypothesis, via two-way PERMANOVA analysis, about the effect of heavy metals (Cd, Co, Cu, Ni, Zn) on the microbial population. Absolute frequency. Small letters indicate significant differences (p < 0.05).
Figure 7. Decomposition of the statistical hypothesis, via two-way PERMANOVA analysis, about the effect of heavy metals (Cd, Co, Cu, Ni, Zn) on the microbial population. Absolute frequency. Small letters indicate significant differences (p < 0.05).
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Figure 8. Correlation matrix among 13 experimental variables. The codes from C1 to C13 include growth at different temperatures and pH levels: C1 = T15 and pH5, C2 = T15 and pH8, C3 = T25 and pH5, C4 = T25 and pH8, C5 = T37 and pH5, and C6 = T37 and pH8; tolerance to heavy metals: C7 = cadmium, C8 = cobalt, C9 = copper, C10 = nickel, and C11 = zinc; uncommon carbon source: C12 = SDS and C13 = skim milk 10%. The correlation coefficients range from –1 to +1 and are color-coded from red (red circle = negative correlation) to blue (blue circle = positive correlation). Gray cells highlight significant correlations.
Figure 8. Correlation matrix among 13 experimental variables. The codes from C1 to C13 include growth at different temperatures and pH levels: C1 = T15 and pH5, C2 = T15 and pH8, C3 = T25 and pH5, C4 = T25 and pH8, C5 = T37 and pH5, and C6 = T37 and pH8; tolerance to heavy metals: C7 = cadmium, C8 = cobalt, C9 = copper, C10 = nickel, and C11 = zinc; uncommon carbon source: C12 = SDS and C13 = skim milk 10%. The correlation coefficients range from –1 to +1 and are color-coded from red (red circle = negative correlation) to blue (blue circle = positive correlation). Gray cells highlight significant correlations.
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Table 1. Geographic coordinates and classification of the 15 soil sampling sites located in the Foggia district. All sites correspond to areas subject to long-term anthropogenic pressure. Coordinates were recorded using the Google Maps application during fieldwork.
Table 1. Geographic coordinates and classification of the 15 soil sampling sites located in the Foggia district. All sites correspond to areas subject to long-term anthropogenic pressure. Coordinates were recorded using the Google Maps application during fieldwork.
SiteLongitude (°E)Latitude (°N)
A15.58584941.422099
B15.59704041.4334645
C15.60823241.44483
D15.60409041.466206
E15.58430741.477667
F15.56480541.4775115
G15.54530441.477356
H15.52897741.482316
I15.51051741.4781885
L15.49205841.474061
M15.49665141.452132
N15.50541541.433294
O15.50834841.413625
P15.53568541.421741
Q15.56076741.42192
Table 2. Results of a two-way PERMANOVA performed on the dataset derived from the microbiological profiles. The analysis tested the effects of the sampling site, heavy metal type, and their interaction. Significant effects with a p < 0.05. df, degrees of freedom; SS, sum of squares; MS, mean square; F, Fisher’s test.
Table 2. Results of a two-way PERMANOVA performed on the dataset derived from the microbiological profiles. The analysis tested the effects of the sampling site, heavy metal type, and their interaction. Significant effects with a p < 0.05. df, degrees of freedom; SS, sum of squares; MS, mean square; F, Fisher’s test.
Permutation N: 9999
SourceSSdfMSFpExplained Variance (%)
Sampling site4.039140.2893.0030.00076.96
Heavy metal1.45240.3633.7790.00592.50
Interaction11.703560.2092.1750.000220.17
Residual40.8284250.096
Total58.022499
Table 3. Key features of each phenotypic cluster, based on the k-means.
Table 3. Key features of each phenotypic cluster, based on the k-means.
Cluster0123
15 °C/pH 50.690.320.20.79
15 °C/pH 80.190.640.680.71
25 °C/pH 50.150.560.160.88
25 °C/pH 80.270.800.640.46
37 °C/pH 50.540.560.160.58
37 °C/pH 80.270.680.920.25
Cd0.080.720.480.92
Co0.460.440.440.42
Cu0.690.800.160.25
Ni0.460.160.640.75
Zn0.50.440.520.54
SDS0.420.320.640.71
SM 10%0.420.160.640.67
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MDPI and ACS Style

De Santis, A.; Bevilacqua, A.; Racioppo, A.; Speranza, B.; Corbo, M.R.; Altieri, C.; Sinigaglia, M. A Preliminary Investigation into Heavy Metal Tolerance in Pseudomonas Isolates: Does the Isolation Site Have an Effect? Agriculture 2025, 15, 1692. https://doi.org/10.3390/agriculture15151692

AMA Style

De Santis A, Bevilacqua A, Racioppo A, Speranza B, Corbo MR, Altieri C, Sinigaglia M. A Preliminary Investigation into Heavy Metal Tolerance in Pseudomonas Isolates: Does the Isolation Site Have an Effect? Agriculture. 2025; 15(15):1692. https://doi.org/10.3390/agriculture15151692

Chicago/Turabian Style

De Santis, Alessandro, Antonio Bevilacqua, Angela Racioppo, Barbara Speranza, Maria Rosaria Corbo, Clelia Altieri, and Milena Sinigaglia. 2025. "A Preliminary Investigation into Heavy Metal Tolerance in Pseudomonas Isolates: Does the Isolation Site Have an Effect?" Agriculture 15, no. 15: 1692. https://doi.org/10.3390/agriculture15151692

APA Style

De Santis, A., Bevilacqua, A., Racioppo, A., Speranza, B., Corbo, M. R., Altieri, C., & Sinigaglia, M. (2025). A Preliminary Investigation into Heavy Metal Tolerance in Pseudomonas Isolates: Does the Isolation Site Have an Effect? Agriculture, 15(15), 1692. https://doi.org/10.3390/agriculture15151692

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