Next Article in Journal
Development of a Real-Time Online Automatic Measurement System for Propeller Manufacturing Quality Control
Previous Article in Journal
Systematic Review: Malware Detection and Classification in Cybersecurity
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Applied Sciences
Volume 15
Issue 14
10.3390/app15147746
applsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Molecular Response of Bacteria Exposed to Wastewater-Borne Nanoparticles

by
Nina Doskocz
,
Katarzyna Affek
and
Monika Załęska-Radziwiłł
*
Department of Biology, Faculty of Environmental Engineering, Warsaw University of Technology, Nowowiejska 20, 00-653 Warsaw, Poland
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(14), 7746; https://doi.org/10.3390/app15147746
Submission received: 12 June 2025 / Revised: 4 July 2025 / Accepted: 9 July 2025 / Published: 10 July 2025
Browse Figures
Versions Notes

Abstract

The increasing release of nanoparticles into aquatic environments, particularly via wastewater, raises concerns about their biological effects on microbial communities. This study investigated the molecular response of Pseudomonas putida to aluminum oxide nanoparticles (Al2O3NPs) under controlled conditions and in synthetic wastewater, both before and after biological treatment. Acute toxicity was evaluated using growth inhibition assays, while the expression of katE, ahpC, and ctaD—genes associated with oxidative stress and energy metabolism—was quantified via RT-qPCR. Exposure to pristine Al2O3NPs induced a strong, time-dependent upregulation of all tested genes (e.g., katE and ahpC up to 4.5-fold). In untreated wastewater, this effect persisted but at a lower intensity; bulk Al2O3 caused only moderate changes. Treated wastewater samples showed markedly reduced gene expression, indicating partial detoxification. Nanoparticles elicited stronger biological responses than their bulk counterparts, confirming the material form-specific effects. Comparative analysis with Daphnia magna revealed similar patterns of oxidative stress gene activation. These findings highlight the influence of nanoparticle form and environmental matrix on microbial responses and support the use of gene expression analysis as a sensitive biomarker for nanoparticle-induced stress in environmental risk assessment.

1. Introduction

The growing presence of nanoparticles in wastewater has emerged as a significant environmental concern due to their expanding use across various industrial sectors. Engineered nanomaterials, including aluminum oxide nanoparticles (Al2O3NPs), are increasingly applied in medicine [1,2,3], cosmetics [4], textiles [5], electronics and materials science [6,7], water treatment [8,9], and environmental remediation [10]. These nanoparticles are introduced into aquatic systems through industrial discharges and consumer products, raising critical concerns regarding their long-term ecological impact, particularly in the context of wastewater treatment.
Due to their high surface reactivity, small size (<50 nm), and large specific surface area, Al2O3NPs may interact strongly with biological systems and pose risks to both environmental and human health [11]. Studies have shown varied effects on bacteria, with Escherichia coli exhibiting mild growth inhibition due to reactive oxygen species (ROS) generation, Pseudomonas stutzeri showing oxidative stress responses without significant toxicity, and Staphylococcus aureus experiencing cell wall perforation and membrane disruption [11,12,13,14]. The increasing detection of Al2O3NPs in wastewater systems underscores the need for improved regulatory frameworks and advanced methods of toxicological assessment.
A major limitation of conventional toxicity tests is their inability to elucidate the mechanisms of nanoparticle toxicity [15]. Standard assays, which typically focus on survival and reproduction, fail to detect subtle molecular effects or stress responses. Recent studies have highlighted the importance of molecular biomarkers, such as gene expression changes, as sensitive early indicators of nanoparticle-induced stress, revealing mechanisms like ROS-mediated oxidative stress and membrane damage [10,11,12,13,14,16]. These molecular responses provide insight into how nanoparticles affect cellular processes, including oxidative stress and detoxification pathways. Despite progress in the field, the specific toxicological mechanisms of many nanomaterials remain poorly understood [17].
In aquatic organisms such as Daphnia magna, exposure to metal nanoparticles (e.g., copper, silver) has been shown to induce differential expression of genes involved in oxidative stress responses, immune regulation, and energy metabolism [18,19,20]. However, similar studies on microorganisms, especially bacteria, are still limited. Although bacteria play a crucial role in aquatic ecosystems and are key to biological wastewater treatment processes, their molecular responses to nanoparticles are underexplored. Existing studies primarily focus on general community-level effects, including oxidative stress, microbial diversity shifts, and the potential for horizontal gene transfer linked to antibiotic resistance [20,21,22,23]. The specific responses of individual bacterial species to distinct types of nanomaterials, particularly metal-based or polymeric nanoparticles, remain insufficiently characterized [24,25]. Such studies are crucial, as Al2O3NPs may disrupt bacterial cell membranes, generate ROS, or alter energy metabolism, potentially affecting wastewater treatment efficiency.
The aim of this study was to evaluate the transcriptional response of Pseudomonas putida to wastewater with aluminum oxide nanoparticles and their bulk counterparts, focusing on genes involved in oxidative stress and energy metabolism. P. putida was selected as the model bacterium due to its ecological relevance in wastewater treatment systems, where it contributes to biodegradation and nutrient cycling [26,27]. Its metabolic versatility, robustness, and well-characterized genetic background make it ideal for studying nanoparticle-induced stress responses, particularly through molecular techniques like RT-qPCR [28,29]. Using RT-qPCR (Quantitative Reverse Transcription Polymerase Chain Reaction), we analyzed the expression of katE, ahpC, and ctaD, which encode catalase, alkyl hydroperoxide reductase, and a CtaD subunit of cytochrome c oxidase, respectively. The CtaD subunit is a core component of cytochrome c oxidase (Complex IV) in the electron transport chain, catalyzing the reduction of oxygen to water and contributing to proton pumping for ATP synthesis [30]. We selected ctaD as a biomarker because its expression reflects disruptions in energy metabolism and oxidative stress responses, which are sensitive to the physicochemical properties of Al2O3NPs and bulk Al2O3, such as surface reactivity and bioavailability. The bacteria were exposed to Al2O3 in both nano and bulk forms under controlled conditions (in aqueous suspensions) and in synthetic wastewater before and after treatment in a laboratory-scale sequencing batch reactor (SBR). We hypothesized that Al2O3NPs would trigger stronger and more sustained transcriptional responses than bulk material, particularly in untreated wastewater where particle bioavailability is higher.
This research contributes to the growing field of environmental nanotoxicology by providing mechanistic insight into the biological activity of aluminum oxide nanoparticles and their fate in wastewater systems. By integrating molecular and ecotoxicological approaches, the study supports the implementation of gene expression markers in environmental monitoring and highlights the limitations of conventional toxicity tests. These findings offer a scientific basis for improving risk assessment frameworks for engineered nanomaterials in complex environmental matrices.

2. Materials and Methods

2.1. Preparation of Al2O3NPs and Bulk Al2O3 Suspensions

Commercial samples of Al2O3NPs (nanopowder < 50 nm with a specific surface area > 40 m2/g) and Al2O3 (Al2O3, purity over 98%, <10 m2/g) were obtained (CAS no. 1344-28-1, Merck Life Sciences, Poznań, Poland). The high surface area of Al2O3NPs enhances their reactivity and potential for reactive oxygen species generation, facilitating interactions with bacterial cell membranes. Stock suspensions of 10 mg/L of nano and macro forms of Al2O3 were prepared in deionized and sterile water. To avoid the formation of aggregates, stock suspensions were sonicated (0.4 kW, 20 kHz) for 30 min before being diluted to the exposure concentrations.

2.2. Lab-Scale Wastewater Treatment Plant (WWTP)

The wastewater samples used in this study originated from laboratory-scale sequencing batch reactors (SBRs), as described in detail in a previous publication [31]. Briefly, three reactors were operated for 63 days with synthetic influent and activated sludge obtained from a municipal wastewater treatment plant. One reactor served as a control (no additives), the second was supplemented with aluminum oxide nanoparticles (Al2O3NPs, 10 mg/L), and the third with aluminum oxide in bulk form (10 mg/L). Samples were collected weekly, stored at 4 °C, and homogenized prior to use in exposure experiments with test organisms. The list of wastewater samples used in exposure experiments is provided in Table 1.

2.3. Growth Inhibition and Toxicity Assessment in Pseudomonas putida

The bacterial growth inhibition assay was conducted using P. putida KT2440 (DSM 6125), obtained from the German Collection of Microorganisms and Cell Cultures (DSMZ) and Life Technologies GmbH (Karlsruhe, Germany). All necessary components for preparing the bacterial culture and test media were sourced from Sigma-Aldrich (Poznań, Poland). The assay followed the ISO Guideline 107122 (1994) [32]. Initially, the bacterial culture was transferred into 200 mL of sterilized culture medium. The culture was placed in sterilized Erlenmeyer flasks, sealed with cotton wool, and placed on a magnetic stirrer to ensure proper mixing and aeration throughout the experiment. The bacterial suspension was adjusted to an initial optical density (OD610) of 0.2 prior to exposure to the tested solutions. The assessment of growth inhibition was conducted on the basis of measurement of the optical density of samples with λ = 610 nm at the beginning and at the end of the 16-h test. The growth inhibition (I) was calculated using the following formula:
I = B c − B n B c − B 0 × 100 %
where Bc is the optical density of suspension in the control sample after time t; Bn is the optical density of suspension in the sample examined after time t; and B0 is the optical density of suspension in the control at time 0.
The effective concentration (EC50) values were calculated using probit analysis, a statistical method that estimates concentration–response relationships [33]. The 95% confidence intervals were also calculated to ensure precision in determining the concentration at which 50% of the organisms exhibit a specific effect. To quantify acute toxicity, toxicity units (TUₐs) were calculated from the EC50 values according to the following standard formula:
T U a = 1 E C 50 × 100
where EC50 is expressed in %. Higher TUₐ values indicate greater acute toxicity. This approach enables the direct comparison of toxicity levels across different treatments or exposure conditions [34].

2.4. Gene Expression Exposures

After completion of the toxicity assay, bacterial samples were collected at both 1 h and 16 h of exposure for further molecular analysis. From each sample, 1 mL of bacterial suspension was centrifuged at 1500× g for 10 min, and the resulting cell pellets were re-suspended in 200 μL of Phenozol reagent (A&A Biotechnology, Gdańsk, Poland) to ensure cell lysis and RNA stabilization. The samples were taken directly from the toxicity test described in Section 2.3, in which P. putida was exposed to 10 mg/L of aluminum oxide in nanoparticulate or bulk form, as well as to the untreated and treated wastewater samples listed in Table 1.

2.5. RNA Extraction, Reverse Transcription, and Real-Time Quantitative PCR

Total RNA was purified using the Total RNA Mini Plus kit (A&A Biotechnology, Poland) as per the protocol. The concentration of each sample was determined by analyzing 1.5 μL of each sample on a NanoDrop Spectrophotometer. The TranScriba Kit (A&A Biotechnology, Poland) was used to perform the reverse transcription reaction following the manufacturer’s protocols. RNA was purified from DNA using the Clean-Up RNA Concentrator Kit (A&A Biotechnology, Gdańsk, Poland) and served as a template with a mixture of oligo (dT) 18 primers and random hexamers (in a 2:1 ratio). A negative reverse transcription control (no reverse transcriptase) was performed for each template.
The prepared samples were incubated at 65 °C for 5 min and then cooled to 4 °C. Then, 4 µL of reaction buffer, 2 µL of dNTP’s mix, and 4 µL of TranScriba™ reverse transcriptase were added to each sample. After mixing the samples, they were incubated at 25 °C for 5 min and then another 30 min at 42 °C. To complete the reaction, the mixtures were heated at 70 °C for 10 min. The cDNA prepared in this way was used as a template in the Real-Time PCR reaction.
Real-Time PCR reactions were performed in a Stratagene Mx3000P thermal cycler (Agilent Technologies, Santa Clara, CA, USA), using the SYBR Green dye as a fluorochrome and the following program: 95 °C for 5 min, 40 cycles of 95 °C for 15 s, and 60 °C for 30 s. For each cDNA sample, a Real-Time PCR reaction was set up, amplifying fragments of 16S genes and the tested genes catE, ctaD, and ahpC for P. putida. Primer sequences used in qPCR are available in Table 2. PCR reactions, performed in triplicate, and the obtained Ct values were averaged. The specificity of each amplification was validated by examining its melting curve. Each run included a negative control. To create the comparative curve, cDNA solutions were prepared in a series of five-fold dilutions. The effects of pristine Al2O3NPs on gene expression are presented as relative changes in transcript levels of selected genes, normalized to the 16S rRNA reference gene and calculated using the 2−ΔΔCt method. The ΔΔCt = ΔCt″0″−ΔCt″16″ ΔCt″0″ = Ct_gen″0″−Ct_16S″0″ and ΔCt″16″ = Ct_gen″48″−Ct_16S″16″ (Ct-cycle threshold), assuming that the reaction efficiencies are close to 100% [35]. For the wastewater-borne NP effluent experiments, fold changes were calculated relative to the untreated control (water), also normalized to 16S rRNA. ΔCt values were derived from three biological replicates (n = 3), each consisting of at least three technical replicates. Technical replicates were averaged to yield a single ΔCt per sample. Outliers with Ct values deviating by more than ±2 standard deviations from the group mean were excluded. Relative expression values above 1 indicate gene upregulation, while values below 1 indicate downregulation.

3. Results and Discussion

Aluminum dioxide nanoparticles exhibited high acute toxicity toward P. putida, with an EC50 value of 0.5 mg/L after 16 h of exposure. In contrast, the bulk form of the tested material showed markedly lower toxicity, with EC50 values ≥ 10 mg/L. This difference may result from the higher surface reactivity and greater bioavailability of nanoparticles, which, due to their unique physicochemical properties, interact more readily with bacterial cell surfaces [36,37]. Our results support this mechanism of action—high acute toxicity observed after just 16 h of exposure correlates with a marked increase in the expression of ahpC gene, which is responsible for neutralizing reactive oxygen species (ROS). This indicates intense oxidative stress and redox imbalance in P. putida cells. In contrast, the low toxicity of the bulk form may result from its smaller specific surface area, limited dispersion, and reduced ability to interact with bacterial cells. These findings are consistent with previous reports highlighting the critical role of particle size, surface area, and ion release potential in determining nanoparticle toxicity [38,39]. Detailed toxicity data are provided in Supplementary Tables S1 and S3.
Studies on other bacteria reveal varied responses to Al2O3NPs. For instance, E. coli exhibited mild growth inhibition only at high concentrations (1000 μg/mL) [12]. Similarly, P. stutzeri showed no significant toxicity but a dramatic 8.2-fold increase in katB expression, indicating oxidative stress, while Bacillus cereus was unaffected at the tested doses [13]. In contrast, Al2O3NPs were bactericidal against multidrug-resistant S. aureus and coagulase-negative staphylococci [14].
Further supporting these observations, untreated wastewater samples stimulated bacterial growth in all tested variants, including control, nano-, and bulk-amended systems, likely due to the presence of readily bioavailable organic compounds. In the case of treated wastewater samples, no acute toxicity was observed according to ISO Guideline 10712-2 (1994) [32], as EC50 values were equal to or greater than 100%. However, moderate growth inhibition was detected, ranging from 20% to 45% across tested samples, suggesting the presence of residual inhibitory substances despite the treatment process. These sublethal effects may result from residual organic and inorganic compounds that either interact with nanoparticles or act independently. Detailed toxicity data are provided in Supplementary Tables S2 and S4.
To better understand the potential mechanisms underlying the observed toxic effects, changes in the expression of oxidative stress-related genes were also analyzed. Alterations in gene expression were observed as early as 1 and 16 h after P. putida exposure to Al2O3 nanoparticles and differed from the responses under control conditions. A significant, time-dependent increase in the expression of all three analyzed genes was observed. After 1 h, katE and ahpC expression increased approximately 2.5-fold compared to the control, while ctaD showed only a slight elevation (fold change ~1.2) (Figure 1A). After 16 h, katE expression reached nearly 4.5-fold and ahpC approximately 3.9-fold, indicating a sustained and intensified oxidative stress response. The expression of ctaD also increased to around 3.0-fold, suggesting that prolonged nanoparticle exposure may trigger broader cellular responses, including those related to energy metabolism and electron transport (Figure 1B).
In the presence of the bulk form of the material, changes in gene expression were less pronounced, although still detectable. After 1 h of exposure, moderate upregulation of katE and ahpC was observed (~1.6 and ~1.5, respectively), while ctaD expression was slightly decreased compared to the control (Figure 1A). After 16 h, katE and ahpC expression levels increased to approximately 2.0 and 1.8, respectively, reflecting a moderate activation of the stress response. The expression of ctaD also increased (~1.5), although it remained significantly lower than in the nanoparticle treatment (Figure 1B).
The expression of the stress-related genes katE, ctaD, and ahpC was also evaluated in bacterial cells exposed to untreated (I) and biologically treated (E) wastewater samples supplemented with either Al2O3NPs, bulk material, or no additives (control) (Figure 2, Figure 3 and Figure 4). In untreated wastewater containing Al2O3 nanoparticles (WW-NPs-I), all three genes showed consistently elevated expression throughout the 63-day experiment. For katE, expression levels remained above 4.0 on day 1 and gradually declined to approximately 3.3 by day 63 (Figure 2). AhpC followed a similar pattern, starting at ~3.6 and decreasing to ~3.0 (Figure 3), while ctaD expression ranged from ~2.2 on day 1 to ~1.7 by the final time point (Figure 4). These results indicate a sustained oxidative stress response triggered by the presence of nanoparticles in the raw wastewater matrix. In the untreated wastewater control samples (WW-Control-I), an initial moderate increase in gene expression was observed (e.g., katE~3.5, ctaD~2.0, ahpC~3.2), likely due to the presence of bioavailable organic matter and associated metabolic activity. However, gene expression gradually decreased over time, reaching baseline or near-baseline levels by day 63 (katE~1.4, ctaD~1.0, ahpC~1.3), indicating the transient nature of the initial response in the absence of particulate additives (Figure 2, Figure 3 and Figure 4).
In biologically treated wastewater samples containing nanoparticles (WW-NPs-E), elevated gene expression was still observed, although at consistently lower levels than in the untreated equivalents. Expression of katE decreased from ~4.1 to ~3.2 over the course of the experiment, ahpC from ~3.4 to ~2.8, and ctaD from ~2.0 to ~1.6. These data suggest that biological treatment reduced but did not eliminate the biological activity or bioavailability of nanoparticles (Figure 2, Figure 3 and Figure 4). Gene expression analysis in P. putida revealed the molecular response to stress induced by exposure to aluminum oxide nanoparticles, showing time-dependent expression patterns across all analyzed genes. Following exposure to pristine Al2O3NPs, significant upregulation of katE and ahpC—encoding catalase and alkyl hydroperoxide reductase, respectively—was observed. These enzymes are key components of the oxidative stress response, responsible for the detoxification of reactive oxygen species (ROS). The most pronounced changes occurred after 16 h, indicating sustained oxidative pressure in bacterial cells. Similar induction of these genes has been reported in other Gram-negative bacteria exposed to TiO2 NPs and ZnONPs [40,41].
The expression of ctaD, encoding a subunit of cytochrome oxidase—a central element of the respiratory chain—was also elevated. This may reflect disruptions in membrane-associated energy metabolism or increased cellular energy demand under stress conditions. However, the correlation between ctaD expression and ATP synthesis is complex, as nanoparticle-induced membrane damage or the presence of uncoupling agents in wastewater could lead to proton leakage across the bacterial membrane, dissipating the proton motive force (PMF) without driving ATP synthase activity [42]. In such scenarios, elevated ctaD expression may serve to maintain electron flow and oxygen consumption to counteract stress, rather than directly contributing to ATP production. Comparable changes were previously observed in P. putida exposed to hematite nanoparticles (Fe2O3 NPs), which reduced the expression of fumC and sodA, pointing to metabolic imbalance and oxidative stress. Downregulation of fumC, coding for fumarase C in the TCA cycle, suggests reduced NADH production and impaired electron transport, while decreased sodA expression may lead to ROS accumulation and respiratory chain dysfunction [43]. Additionally, Morales et al. (2006) [44] demonstrated that inactivation of the cyo-type ubiquinol oxidase in P. putida affects the global regulation of genes involved in electron transport and energy metabolism. While not directly related to nanoparticle exposure, this finding supports the notion that alterations in electron transport components can modulate bacterial adaptation to environmental stressors [44].
Our results show that both raw and treated wastewater containing Al2O3NPs induced changes in katE, ahpC, and ctaD expression in P. putida, with the strongest response observed in raw wastewater. The expression profiles suggest that nanoparticle exposure in a complex wastewater matrix may trigger both acute oxidative stress responses and longer-term metabolic adaptations involving electron transport. In raw wastewater samples, the marked upregulation of katE and ahpC points to strong activation of cellular defence systems for detoxifying hydrogen peroxide and organic hydroperoxides. Al2O3NPs that are present in raw wastewater in a more reactive, unmodified form may have induced excessive ROS production through direct interaction with the cell surface or dissolved organic compounds. The presence of additional organic and inorganic pollutants could have further intensified these effects, for example, by forming corrosion layers around nanoparticles or promoting their aggregation, altering their toxicity [45,46,47].
Concurrently, ctaD expression was moderately increased, suggesting disturbances in the electron transport chain and elevated energy requirements resulting from stress conditions. These effects likely promoted the activation of alternative respiratory pathways, such as those involving cytochrome o ubiquinol oxidase (cyo) or cytochrome bd oxidase, which can serve as terminal oxidases under stress conditions, bypassing the cytochrome c oxidase pathway encoded by ctaD [48,49]. These alternative oxidases, characterized by high oxygen affinity, may help maintain redox balance and support cellular respiration when cytochrome c oxidase activity is compromised, ensuring sufficient ATP production for defence and repair systems. Thus, the presence of Al2O3NPs in raw wastewater appears to elicit both immediate antioxidant responses and adaptive shifts in energy metabolism [45].
As biological treatment progressed, the transcriptional responses of katE, ahpC, and ctaD in P. putida gradually declined, reflecting environmental detoxification and reduced bioavailability of nanoparticle fractions. Physicochemical data likewise showed a decrease in dissolved Al3+ concentrations over time [31], potentially reducing cellular stress. In the control group, the observed decay in bacterial growth likely resulted from the depletion of bioavailable organic compounds and the accumulation of inhibitory metabolites in the wastewater matrix, which could limit metabolic activity and growth over time, even in the absence of nanoparticles or bulk material. These factors collectively contributed to the observed reduction in transcriptional activity and growth across all experimental conditions. Nevertheless, katE and ahpC remained upregulated relative to the control, possibly due to residual nanoparticle activity or delayed effects from prior exposure. Interestingly, ctaD expression was initially low but increased in treated wastewater at later time points, possibly indicating the compensatory upregulation of energy pathways in response to membrane dysfunction, altered electron flow, or increased ATP demand. Similar adaptive mechanisms, including upregulation of cytochrome oxidase genes and alternative respiratory pathways, have been reported in P. putida responding to redox and oxidative stress induced by environmental stressors [44].
According to data from the literature, biological wastewater treatment generally reduces the intensity of transcriptional responses, aligning with environmental detoxification and a decline in nanoparticle bioavailability [20]. However, persistent gene upregulation may result from residual nanoparticle activity, secondary stress effects, or the presence of other micropollutants. Even in treated effluents, trace levels of heavy metals, nanoparticles, and pharmaceutical residues may remain [20,31,50,51,52]. Chronic exposure to such compounds can disrupt membrane potential, induce oxidative stress, and damage lipid structures. These effects increase the energy demand of cells, potentially activating ctaD and other respiratory genes. Furthermore, under conditions of limited oxygen availability—common in sludge environments—bacteria often upregulate high-affinity cytochrome oxidases such as cytochrome c oxidase to optimize oxygen usage [53,54]. Organic (e.g., humic acids) and inorganic substances present in wastewater can also influence nanoparticle transformation and behavior. The formation of corrosion layers or particle aggregation alters metal bioavailability and interactions with bacterial cells 45], thereby modulating nanoparticle toxicity. These complex environmental factors can lead to persistent low-level stress, driving restructuring of bacterial metabolism, including enhanced ATP production pathways and the adaptation of electron transport systems [20,31,36,55,56]. The literature highlights that most studies on nanoparticle effects on bacteria have been conducted in simplified model systems using pure cultures and defined media. Research based on real wastewater samples remains limited. One notable exception is the study by Meli et al. (2016), which showed that ZnONPs reduced microbial diversity and disrupted functional processes in activated sludge [57]. Similarly, Phan et al. (2020) found that ZnONPs modulated the expression of nitrification genes (amoA, hao, nirK) in wastewater systems depending on oxygen levels and nanoparticle aggregation [58]. These findings emphasize the importance of considering both the physical form of the material (nano vs. bulk) and environmental context (raw vs. treated wastewater), as nanoparticle effects on microorganisms are strongly matrix-dependent. In summary, our data suggest that katE and ahpC are sensitive biomarkers of acute oxidative stress induced by Al2O3NPs in wastewater, while ctaD reflects later-stage metabolic adaptations related to energy management in stressed bacterial cells.
In untreated wastewater containing bulk Al2O3 (WW-Bulk-I), gene expression levels were also elevated relative to controls but lower than those observed in the nanoparticle treatments. The expression of katE ranged between 3.0 and 3.5 (Figure 2), ahpC between 3.1 and 3.4 (Figure 3), and ctaD between 1.5 and 1.8 (Figure 4). While a slight downward trend was observed over time, the response remained detectable across all time points. In the treated wastewater supplemented with bulk material (WW-Bulk-E), a further reduction in gene expression was observed. KatE expression declined from ~3.0 to ~2.5 (Figure 2), ahpC from ~3.1 to ~2.2 (Figure 3), and ctaD from ~1.7 to ~1.2 (Figure 4). Compared to untreated bulk samples, these findings reflect a diminished cellular response, likely due to the physical or chemical transformation of the material during wastewater treatment. In light of these observations, it is worth emphasizing that both in wastewater and in pristine suspensions, Al2O3 nanoparticles induced stronger transcriptional responses in P. putida cells compared to their bulk counterparts. Under pristine conditions, the nanoparticles triggered significantly higher expression levels of genes associated with oxidative stress and energy metabolism (katE, ahpC, ctaD), consistent with their enhanced reactivity, solubility, and bioavailability [39,40]. In contrast, the bulk form elicited only a moderate gene expression response, which aligns with previous studies indicating its limited cellular penetration and weaker surface interactions [37]. Qiu, in turn, showed that the exposure of Shewanella oneidensis to functionalized gold nanoparticles induced sodB expression, while the ligand alone had no such effect, highlighting the critical role of surface properties in stress induction. Stronger biological responses to nanoparticles have also been demonstrated in environmental studies [17]. Meli et al. (2016) found that ZnO NPs significantly reduced bacterial taxonomic diversity in activated sludge, whereas bulk ZnO had no such effect, indicating lower interaction with microbial cells [57]. Similarly, Luche et al. (2018) reported that Bacillus subtilis exposed to ZnONPs exhibited a stringent response and significant changes in gene expression related to the TCA cycle and pentose phosphate pathway—key metabolic and redox processes [59]. These molecular effects were absent in the bulk treatment. The observed differences are primarily attributed to higher surface reactivity and ion release potential of nanoparticles, which can generate oxidative stress and facilitate stronger interaction with cell membranes [37]. Our results support this mechanism, showing more pronounced Al3+ ion release from both pristine and wastewater-associated nanoparticles than from the bulk form [20,31]. Moreover, the larger specific surface area of nanoparticles promotes adsorption to bacterial membranes and potential internalization, which may further amplify cellular responses [36]. Together, these findings indicate that nanoform Al2O3 represents a distinct environmental risk compared to bulk material, and this distinction should be considered in risk assessment, particularly in complex systems such as wastewater.
In this study, we conducted an interspecies comparative analysis to explore whether genes involved in similar cellular functions exhibit comparable transcriptional patterns in response to Al2O3NPs. Specifically, we examined the expression of homologous genes related to oxidative stress (katE/cat, ahpC/gst) and energy metabolism (ctaD/nadh) in two taxonomically distant organisms: the bacterium P. putida and the crustacean D. magna (Figure 5). These species represent different biological domains—prokaryotic and eukaryotic—and occupy distinct ecological roles, with P. putida being a model organism for microbial communities in wastewater treatment systems and D. magna serving as a widely accepted indicator species in aquatic ecotoxicology. This comparative approach was intended to better understand nanoparticle-induced toxicity mechanisms and to assess the potential for identifying universal molecular stress markers. Gene expression data for D. magna were obtained from our previously published study using the same exposure conditions and target genes (https://doi.org/10.1016/j.dwt.2025.101000) [20].
A comparison of genes with homologous function expression in P. putida and D. magna revealed consistent transcriptional response patterns across three functional groups: xenobiotic detoxification (katE/cat), oxidative stress response (ahpC/gst), and energy metabolism (ctaD/nadh) (Figure 5). In response to pristine Al2O3 nanoparticles, both organisms showed strong upregulation of detoxification (katE, cat) and oxidative stress genes (ahpC, gst), with peak expression occurring at different time points. For energy metabolism genes, contrasting responses were observed: ctaD expression increased in P. putida, while nadh expression decreased in D. magna (Figure 5). Under exposure to untreated wastewater containing Al2O3NPs, expression profiles became more aligned between species. The genes katE/cat and ahpC/gst remained moderately upregulated throughout the exposure period, while ctaD and nadh both showed a gradual decrease (Figure 5). A similar pattern was observed in treated wastewater: transcriptional activity of detoxification and oxidative stress genes was sustained, whereas energy metabolism-related genes remained downregulated in both organisms (Figure 5). The comparison of genes with homologous function expression in P. putida and D. magna revealed consistent transcriptional response patterns across three functional groups: xenobiotic detoxification (katE/cat), oxidative stress response (ahpC/gst), and energy metabolism (ctaD/nadh) (Figure 5). In response to pristine Al2O3 nanoparticles, both organisms showed strong upregulation of detoxification (katE, cat) and oxidative stress genes (ahpC, gst), with peak expression occurring at different time points. For energy metabolism genes, contrasting responses were observed: ctaD expression increased in P. putida, while nadh expression decreased in D. magna (Figure 5). Under exposure to untreated wastewater containing Al2O3NPs, expression profiles became more aligned between species. The genes katE/cat and ahpC/gst remained moderately upregulated throughout the exposure period, while ctaD and nadh both showed a gradual decrease (Figure 5). A similar pattern was observed in treated wastewater: transcriptional activity of detoxification and oxidative stress genes was sustained, whereas energy metabolism-related genes remained downregulated in both organisms (Figure 5).
In light of the existing literature, our findings support the notion that certain molecular pathways may serve as cross-species indicators of nanoparticle bioactivity [17]. Monitoring gene expression in both bacterial and eukaryotic model organisms thus offers a valuable approach for the early detection of sublethal effects and potential environmental risks associated with engineered nanomaterials. This is particularly important given the discrepancy observed between classical toxicity testing results and the actual biological activity of nanoparticles, both in pristine suspensions and in treated wastewater samples. Standard endpoints such as survival or growth inhibition may fail to detect cellular stress responses that, while sublethal, can disrupt homeostasis and affect microbial function. In our study, molecular analyses revealed clear transcriptional responses despite the absence of overt toxic effects, suggesting activation of defense mechanisms and physiological stress. Such effects, often missed by conventional assays, may nonetheless alter ecosystem-level processes. The literature further emphasizes that transcriptomic tools, such as RT-qPCR, are sensitive and effective in detecting early stress markers and predicting long-term impacts [15,16,17]. Our results, therefore, underscore the necessity of incorporating molecular biomarkers into environmental risk assessments of nanomaterials, especially in complex matrices like municipal wastewater, where traditional assays may underestimate the true biological impact.

4. Conclusions

In summary, our study demonstrates that pristine Al2O3 nanoparticles exhibit strong toxicity toward P. putida, with an EC50 of 0.5 mg/L, while bulk Al2O3 shows negligible toxicity (EC50 ≥ 10 mg/L), confirming the markedly higher biological activity of the nanoparticulate form. Exposure to pristine Al2O3NPs consistently upregulates oxidative stress-related genes (katE, ahpC) and the energy metabolism gene ctaD in P. putida, indicating a sustained molecular stress response. Gene expression changes in P. putida vary over time, with acute effects observed within 48 h and prolonged responses suggesting no full transcriptional recovery during chronic exposure. In wastewater matrices, Al2O3NPs trigger more moderate but persistent gene expression changes, particularly in oxidative stress markers, indicating sustained biological activity even after treatment. Responses to wastewater-associated Al2O3NPs differ between raw and treated matrices, reflecting variable bioavailability and the transformation of particles during wastewater treatment. In contrast, bulk Al2O3, whether in pristine suspensions or wastewater, induces only moderate or negligible gene expression changes in P. putida, underscoring its lower biological activity compared to the nanoform. Comparative analysis with D. magna suggests that genes such as katE and ahpC may serve as robust cross-species biomarkers of nanoparticle-induced effects.
These findings confirm that wastewater-borne Al2O3 in nanoparticulate form elicits specific biological responses in bacteria, unlike its bulk counterpart, and that gene expression analyses can offer early insight into sublethal exposure effects. Further integration of molecular data with classical endpoints will enhance predictive capacity in the environmental risk assessment of engineered nanomaterials.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/app15147746/s1. Table S1. Acute toxicity of Al2O3 (nanoparticles and bulk form) towards Pseudomonas putida (16 h exposure). Table S2. Acute toxicity of untreated and treated wastewater samples towards Pseudomonas putida after 16 h exposure. Table S3. Ecotoxicity categories of chemical compounds/wastewater for aquatic organisms by EPA (U.S. Environmental Protection Agency). Table S4. Ecotoxicity criteria for wastewater samples developed by Persoone et al. (2003) [34].

Author Contributions

Conceptualization, N.D.; methodology, N.D.; validation, K.A. and M.Z.-R.; formal analysis, N.D.; investigation, N.D. and K.A.; resources, N.D. and K.A.; data curation, N.D.; writing—original draft preparation, N.D.; writing—review and editing, K.A. and M.Z.-R.; visualization, N.D.; supervision, M.Z.-R.; project administration, N.D.; funding acquisition, N.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Science Center through the Miniatura 5 Program (021/05/X/ST10/00884) and was co-financed by the Warsaw University of Technology within the Excellence Initiative: Research University (IDUB) program (1820/106/Z01/2023).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All raw data that are fundamental to the results presented in this study can be provided by the corresponding author on request.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
Al2O3NPsAluminum oxide nanoparticles
TUaAcute Toxicity Unit
EC50Effective Concentration for 50% of the population
qPCRQuantitative Polymerase Chain Reaction
RT-qPCRQuantitative Reverse Transcription Polymerase Chain Reaction
ROSReactive Oxygen Species
WWTPWastewater Treatment Plant
SBRSequencing Batch Reactor
CtCycle threshold (in qPCR)
RNARibonucleic Acid
DNADeoxyribonucleic Acid
rRNARibosomal RNA
ISOInternational Organization for Standardization
NPNanoparticle
CASChemical Abstracts Service (Registry Number)
PCRPolymerase Chain Reaction
ODOptical Density
DSMZDeutsche Sammlung von Mikroorganismen und Zellkulturen

References

  1. Rodríguez, J.A.; Fernández-García, M. Synthesis, Properties, and Applications of Oxide Nanomaterials; Wiley: Hoboken, NJ, USA, 2006. [Google Scholar] [CrossRef]
  2. Raczyński, P.; Górny, K.; Bełdowski, P.; Marciniak, B.; Pöschel, T.; Dendzik, Z. Influence of silicon nanocone on cell membrane self-sealing capabilities for targeted drug delivery—Computer simulation study. Arch. Biochem. Biophys. 2023, 749, 109802. [Google Scholar] [CrossRef] [PubMed]
  3. Lammers, T.; Hennink, W.E.; Storm, G. Tumour-targeted nanomedicines: Principles and practice. Br. J. Cancer 2008, 99, 392–397. [Google Scholar] [CrossRef] [PubMed]
  4. Gupta, V.; Mohapatra, S.; Mishra, H.; Farooq, U.; Kumar, K.; Ansari, M.J.; Aldawsari, M.F.; Alalaiwe, A.S.; Mirza, M.A.; Iqbal, Z. Nanotechnology in cosmetics and cosmeceuticals—A review of latest advancements. Gels 2022, 8, 173. [Google Scholar] [CrossRef] [PubMed]
  5. Oikonomou, E.K.; Golemanov, K.; Dufils, P.-E.; Wilson, J.; Ahuja, R.; Heux, L.; Berret, J.-F. Nanorods of natural polysaccharides: Formation mechanisms and rheology. ACS Appl. Polym. Mater. 2021, 3, 3009–3018. [Google Scholar] [CrossRef]
  6. Zajkowska-Pietrzak, W.; Turczyński, J.; Kurowska, B.; Teisseyre, H.; Fronc, K.; Dąbrowski, J.; Kret, S. ZnO nanowires grown on Al2O3–ZnAl2O4 nanostructure using solid–vapor mechanism. Arch. Metall. Mater. 2023, 68, 1177–1182. [Google Scholar] [CrossRef]
  7. Som, C.; Wick, P.; Krug, H.; Nowack, B. Environmental and health effects of nanomaterials in nanotextiles and facade coatings. Environ. Int. 2011, 37, 1131–1142. [Google Scholar] [CrossRef]
  8. Mushtaq, F.; Asani, A.; Hoop, M.; Chen, X.-Z.; Ahmed, D.; Nelson, B.J.; Pané, S. Highly efficient coaxial TiO2–PtPd tubular nanomachines for photocatalytic water purification with multiple locomotion strategies. Adv. Funct. Mater. 2016, 26, 6995. [Google Scholar] [CrossRef]
  9. Bottero, J.Y.; Rose, J.; Wiesner, M.R. Nanotechnologies: Tools for sustainability in a new wave of water treatment processes. Integr. Environ. Assess. Manag. 2006, 2, 391–395. [Google Scholar] [CrossRef]
  10. Pak, T.; Luz, L.F.L., Jr.; Tosco, T.; Costa, G.S.R.; Rosa, P.R.R.; Archilha, N.L. Pore-scale investigation of the use of reactive nanoparticles for in situ remediation of contaminated groundwater source. Proc. Natl. Acad. Sci. USA 2020, 117, 13366–13373. [Google Scholar] [CrossRef]
  11. Kumah, E.A.; Fopa, R.D.; Harati, S.; Boadu, P.; Zohoori, F.V.; Pak, T. Human and environmental impacts of nanoparticles: A scoping review of the current literature. BMC Public Health 2023, 23, 1059. [Google Scholar] [CrossRef]
  12. Sadiq, I.M.; Chowdhury, B.; Chandrasekaran, N.; Mukherjee, A. Antimicrobial sensitivity of Escherichia coli to alumina nanoparticles. Nanomedicine 2009, 5, 282–286. [Google Scholar] [CrossRef] [PubMed]
  13. Fajardo, C.; Saccà, M.L.; Costa, G.; Nande, M.; Martin, M. Impact of Ag and Al2O3 nanoparticles on soil organisms: In vitro and soil experiments. Sci. Total Environ. 2014, 473–474, 254–261. [Google Scholar] [CrossRef] [PubMed]
  14. Ansari, M.A.; Khan, H.M.; Khan, A.A.; Pal, R.; Cameotra, S.S. Antibacterial potential of Al2O3 nanoparticles against multidrug resistance strains of Staphylococcus aureus isolated from skin exudates. J. Nanoparticle Res. 2013, 15, 1970. [Google Scholar] [CrossRef]
  15. Bakand, S.; Hayes, A. Toxicological considerations, toxicity assessment, and risk management of inhaled nanoparticles. Int. J. Mol. Sci. 2016, 17, 929. [Google Scholar] [CrossRef]
  16. Chain, J.J.F.; Finlayson, S.; Crease, T.; Cristescu, M. Variation in transcriptional responses to copper exposure across Daphnia pulex lineages. Aquat. Toxicol. 2019, 210, 85–97. [Google Scholar] [CrossRef]
  17. Qiu, T.A.; Bozich, J.S.; Lohse, S.E.; Vartanian, A.M.; Jacob, L.M.; Meyer, B.M.; Gunsolus, I.L.; Niemuth, N.J.; Murphy, C.J.; Haynes, C.L.; et al. Gene expression as an indicator of the molecular response and toxicity in the bacterium Shewanella oneidensis and the water flea Daphnia magna exposed to functionalized gold nanoparticles. Environ. Sci. Nano 2015, 2, 615–629. [Google Scholar] [CrossRef]
  18. Poynton, H.C.; Loguinov, A.V.; Varshavsky, J.R.; Chan, S.; Perkins, E.J.; Vulpe, C.D. Gene expression profiling in Daphnia magna Part I: Concentration-dependent profiles provide support for the no observed transcriptional effect level. Environ. Sci. Technol. 2008, 42, 6250–6256. [Google Scholar] [CrossRef]
  19. Poynton, H.C.; Lazorchak, J.M.; Impellitteri, C.A.; Smith, M.E.; Rogers, K.; Patra, M.; Hammer, K.A.; Allen, H.J.; Vulpe, C.D. Differential gene expression in Daphnia magna suggests distinct modes of action and bioavailability for ZnO nanoparticles and Zn ions. Environ. Sci. Technol. 2011, 45, 762–768. [Google Scholar] [CrossRef]
  20. Doskocz, N.; Affek, K.; Matczuk, M.; Załęska-Radziwiłł, M. Effect of Al2O3NPs on gene expression in Daphnia magna: Implications for environmental risk assessment. Desalin. Water Treat. 2025, 321, 101000. [Google Scholar] [CrossRef]
  21. Yamini, V.; Shanmugam, V.; Rameshpathy, M.; Venkatraman, G.; Ramanathan, G.; Al Garalleh, H.; Hashmi, A.; Brindhadevi, K.; Devi Rajeswari, V. Environmental effects and interaction of nanoparticles on beneficial soil and aquatic microorganisms. Environ. Res. 2023, 236, 116776. [Google Scholar] [CrossRef]
  22. Das, P.; Xenopoulos, M.A.; Williams, C.J.; Hoque, M.E.; Metcalfe, C.D. Effects of silver nanoparticles on bacterial activity in natural waters. Environ. Toxicol. Chem. 2012, 31, 122–130. [Google Scholar] [CrossRef] [PubMed]
  23. Ameen, F.; Alsamhary, K.; Alabdullatif, J.A.; AlNadhari, S. A review on metal-based nanoparticles and their toxicity to beneficial soil bacteria and fungi. Ecotoxicol. Environ. Saf. 2021, 213, 112027. [Google Scholar] [CrossRef] [PubMed]
  24. Bharti, S.; Mukherji, S.; Mukherji, S. Enhanced antibacterial activity of decahedral silver nanoparticles. J. Nanopart. Res. 2021, 23, 36. [Google Scholar] [CrossRef]
  25. Venkatasubbu, G.D.; Baskar, R.; Anusuya, T.; Seshan, C.A.; Chelliah, R. Toxicity mechanism of titanium dioxide and zinc oxide nanoparticles against food pathogens. Colloids Surf. B Biointerfaces 2016, 148, 600–606. [Google Scholar] [CrossRef]
  26. González, G.; Herrera, G.; García, M.T.; Peña, M. Biodegradation of phenolic industrial wastewater in a fluidized bed bioreactor with immobilized cells of Pseudomonas putida. Bioresour. Technol. 2001, 80, 137–142. [Google Scholar] [CrossRef]
  27. Weimer, A.; Kohlstedt, M.; Volke, D.C.; Nikel, P.I.; Wittmann, C. Industrial biotechnology of Pseudomonas putida: Advances and prospects. Appl. Microbiol. Biotechnol. 2020, 104, 7745–7766. [Google Scholar] [CrossRef]
  28. Peng, J.; Miao, L.; Chen, X.; Liu, P. Comparative transcriptome analysis of Pseudomonas putida KT2440 revealed its response mechanisms to elevated levels of zinc stress. Front. Microbiol. 2018, 9, 1669. [Google Scholar] [CrossRef]
  29. Ouyang, K.; Mortimer, M.; Holden, P.A.; Cai, P.; Wu, Y.; Gao, C.; Huang, Q. Towards a better understanding of Pseudomonas putida biofilm formation in the presence of ZnO nanoparticles (NPs): Role of NP concentration. Environ. Int. 2020, 137, 105485. [Google Scholar] [CrossRef]
  30. Li, Y.; Park, J.S.; Deng, J.H.; Bai, Y. Cytochrome c oxidase subunit IV is essential for assembly and respiratory function of the enzyme complex. J. Bioenerg. Biomembr. 2006, 38, 283–291. [Google Scholar] [CrossRef]
  31. Doskocz, N.; Affek, K.; Matczuk, M.; Drozd, M.; Załęska-Radziwiłł, M. Nanoparticles in wastewater: A comprehensive approach to understanding their ecotoxicity and genotoxicity. Desalin. Water Treat. 2025, 321, 100988. [Google Scholar] [CrossRef]
  32. ISO 107122-1994; Water quality–Pseudomonas putida growth inhibition test (Pseudomonas cell multiplication test). ISO: Geneva, Switzerland, 1994.
  33. Weber, E. Grundriss der Biologischen Statistik für Naturwissenschaftler, Landwirte und Mediziner; VEB Fischer: Jena, Germany, 1972. [Google Scholar]
  34. Persoone, G.; Marsalek, B.; Blinova, I.; Törökne, A.; Zarina, D.; Manusadzianas, L.; Nałęcz-Jawecki, G.; Tofan, L.; Stepanova, N.; Tothova, L.; et al. A practical and user-friendly toxicity classification system with microbiotests for natural waters and wastewaters. Environ. Toxicol. 2003, 18, 395–402. [Google Scholar] [CrossRef] [PubMed]
  35. Livak, K.J.; Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCt method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef] [PubMed]
  36. Slavin, Y.N.; Asnis, J.; Häfeli, U.O.; Bach, H. Metal nanoparticles: Understanding the mechanisms behind antibacterial activity. J. Nanobiotechnol. 2017, 15, 65. [Google Scholar] [CrossRef] [PubMed]
  37. Abdal Dayem, A.; Hossain, M.K.; Lee, S.B.; Kim, K.; Saha, S.K.; Yang, G.-M.; Choi, H.Y.; Cho, S.-G. The Role of Reactive Oxygen Species (ROS) in the Biological Activities of Metallic Nanoparticles. Int. J. Mol. Sci. 2017, 18, 120. [Google Scholar] [CrossRef]
  38. Zielińska, A.; Costa, B.; Ferreira, M.V.; Miguéis, D.; Louros, J.M.S.; Durazzo, A.; Lucarini, M.; Eder, P.; Chaud, M.V.; Morsink, M.; et al. Nanotoxicology and nanosafety: Safety-by-design and testing at a glance. Int. J. Environ. Res. Public Health 2020, 17, 4657. [Google Scholar] [CrossRef]
  39. Joudeh, N.; Linke, D. Nanoparticle classification, physicochemical properties, characterization, and applications: A comprehensive review for biologists. J. Nanobiotechnol. 2022, 20, 262. [Google Scholar] [CrossRef]
  40. Xie, Y.; He, Y.; Irwin, P.L.; Jin, T.; Shi, X. Antibacterial activity and mechanism of action of zinc oxide nanoparticles against Campylobacter jejuni. Appl. Environ. Microbiol. 2011, 77, 2325–2331. [Google Scholar] [CrossRef]
  41. Metryka, O.; Wasilkowski, D.; Mrozik, A. Evaluation of the Effects of Ag, Cu, ZnO and TiO2 Nanoparticles on the Expression Level of Oxidative Stress-Related Genes and the Activity of Antioxidant Enzymes in Escherichia coli, Bacillus cereus and Staphylococcus epidermidis. Int. J. Mol. Sci. 2022, 23, 4966. [Google Scholar] [CrossRef]
  42. Cadenas, S. Mitochondrial uncoupling, ROS generation and cardioprotection. Biochim. Biophys. Acta–Bioenerg. 2018, 1859, 940–950. [Google Scholar] [CrossRef]
  43. Ouyang, K.; Walker, S.L.; Yu, X.; Gao, C.; Huang, Q.; Cai, P. Metabolism, Survival, and Gene Expression of Pseudomonas putida to Hematite Nanoparticles Mediated by Surface-Bound Humic Acid. Environ. Sci. Nano 2018, 5, 682–695. [Google Scholar] [CrossRef]
  44. Morales, G.; Ugidos, A.; Rojo, F. Inactivation of the Pseudomonas putida Cytochrome o Ubiquinol Oxidase Leads to a Significant Change in the Transcriptome and to Increased Expression of the CIO and cbb3-1 Terminal Oxidases. Environ. Microbiol. 2006, 8, 1764–1774. [Google Scholar] [CrossRef] [PubMed]
  45. Levard, C.; Hotze, E.M.; Lowry, G.V.; Brown, G.E., Jr. Environmental Transformations of Silver Nanoparticles: Impact on Stability and Toxicity. Environ. Sci. Technol. 2012, 46, 6900–6914. [Google Scholar] [CrossRef] [PubMed]
  46. Adeleye, A.S.; Conway, J.R.; Garner, K.; Huang, Y.; Su, Y.; Keller, A.A. Engineered Nanomaterials for Water Treatment and Remediation: Costs, Benefits, and Applicability. Chem. Eng. J. 2016, 286, 640–662. [Google Scholar] [CrossRef]
  47. Abbas, Q.; Yousaf, B.; Ullah, H.; Ali, M.U.; Ok, Y.S.; Rinklebe, J. Environmental Transformation and Nano-Toxicity of Engineered Nanoparticles (ENPs) in Aquatic and Terrestrial Organisms. Crit. Rev. Environ. Sci. Technol. 2020, 50, 2523–2581. [Google Scholar] [CrossRef]
  48. Borisov, V.B.; Siletsky, S.A.; Paiardini, A.; Hoogewijs, D.; Forte, E.; Giuffrè, A.; Poole, R.K. Bacterial oxidases of the cytochrome bd family: Redox enzymes of unique structure, function, and utility as drug targets. Antioxid. Redox Signal. 2021, 34, 1280–1318. [Google Scholar] [CrossRef]
  49. Dinamarca, M.A.; Ruiz-Manzano, A.; Rojo, F. Inactivation of cytochrome o ubiquinol oxidase relieves catabolic repression of the Pseudomonas putida GPo1 alkane degradation pathway. J. Bacteriol. 2002, 184, 3785–3793. [Google Scholar] [CrossRef]
  50. Joseph, T.M.; Al-Hazmi, H.E.; Śniatała, B.; Esmaeili, A.; Habibzadeh, S. Nanoparticles and Nanofiltration for Wastewater Treatment: From Polluted to Fresh Water. Environ. Res. 2023, 238, 117114. [Google Scholar] [CrossRef]
  51. Akdemir, T. Trace Element Concentrations in Effluent of Municipal Wastewater Treatment Plants Along the Turkish Coasts and Assessment of Human Health Risk. Front. Mar. Sci. 2024, 11, 1521449. [Google Scholar] [CrossRef]
  52. Solanki, S.; Sinha, S.; Tyagi, S.; Singh, R. Nanomaterials for Efficient Removal of Heavy Metals. In Advances in Chemical Pollution, Environmental Management and Protection; Kumar, A., Bilal, M., Ferreira, L.F.R., Eds.; Elsevier BV: Amsterdam, Netherlands, 2024; Volume 10, pp. 117–136. [Google Scholar] [CrossRef]
  53. Richardson, D.J. Structural and Functional Flexibility of Bacterial Respiromes. In Bacterial Physiology: A Molecular Approach; El-Sharoud, W., Ed.; Springer: Heidelberg, Berlin, 2008; pp. 97–128. [Google Scholar] [CrossRef]
  54. Molina-Henares, M.A.; Ramos-González, M.I.; Rinaldo, S.; Espinosa-Urgel, M. Gene Expression Reprogramming of Pseudomonas alloputida in Response to Arginine through the Transcriptional Regulator ArgR. Microbiology 2024, 170, 001449. [Google Scholar] [CrossRef]
  55. Planchon, M.; Léger, T.; Spalla, O.; Huber, G.; Ferrari, R. Metabolomic and Proteomic Investigations of Impacts of Titanium Dioxide Nanoparticles on Escherichia coli. PLoS ONE 2017, 12, e0178437. [Google Scholar] [CrossRef]
  56. Rihacek, M.; Kosaristanova, L.; Fialova, T.; Rypar, T.; Sterbova, D.S.; Adam, V.; Zurek, L.; Cihalova, K. Metabolic Adaptations of Escherichia coli to Extended Zinc Exposure: Insights into Tricarboxylic Acid Cycle and Trehalose Synthesis. BMC Microbiol. 2024, 24, 384. [Google Scholar] [CrossRef] [PubMed]
  57. Meli, K.; Kamika, I.; Keshri, J.; Momba, M.N.B. The Impact of Zinc Oxide Nanoparticles on the Bacterial Microbiome of Activated Sludge Systems. Sci. Rep. 2016, 6, 39176. [Google Scholar] [CrossRef]
  58. Phan, D.; Pasha, A.B.M.T.; Carwile, N.; Kapoor, V. Effect of Zinc Oxide Nanoparticles on Physiological Activities and Gene Expression of Wastewater Nitrifying Bacteria. Environ. Eng. Sci. 2020, 37, 328–336. [Google Scholar] [CrossRef]
  59. Luche, S.; Steunou, A.L.; Mounier, S.; Chaspoul, F.; Walcarius, A.; Rols, J.L. ZnO Nanoparticles Induce Stringent Response and Metabolic Pathway Alterations in Bacillus subtilis. Nanotoxicology 2018, 12, 392–408. [Google Scholar] [CrossRef]
Applsci 15 07746 g001aApplsci 15 07746 g001b
Figure 1. Relative expression levels of katE, ctaD, and ahpC genes in Pseudomonas putida exposed to aluminum oxide nanoparticles (Al2O3NPs), bulk Al2O3, and control conditions. (A) Gene expression after 1 h of exposure. (B) Gene expression after 16 h of exposure. The results indicate time-dependent transcriptional responses associated with oxidative stress and energy metabolism pathways, with distinct differences between nanoparticulate and bulk forms of Al2O3.
Figure 1. Relative expression levels of katE, ctaD, and ahpC genes in Pseudomonas putida exposed to aluminum oxide nanoparticles (Al2O3NPs), bulk Al2O3, and control conditions. (A) Gene expression after 1 h of exposure. (B) Gene expression after 16 h of exposure. The results indicate time-dependent transcriptional responses associated with oxidative stress and energy metabolism pathways, with distinct differences between nanoparticulate and bulk forms of Al2O3.
Applsci 15 07746 g001aApplsci 15 07746 g001b
Applsci 15 07746 g002
Figure 2. Effects of influents and effluents on the expression of katE in P. putida following 16 h exposure. Data are expressed as fold induction relative to the untreated control (artificial water) and were normalized to the 16r RNA gene. Dotted lines indicate expression differences between treatments.
Figure 2. Effects of influents and effluents on the expression of katE in P. putida following 16 h exposure. Data are expressed as fold induction relative to the untreated control (artificial water) and were normalized to the 16r RNA gene. Dotted lines indicate expression differences between treatments.
Applsci 15 07746 g002
Applsci 15 07746 g003
Figure 3. Effects of influents and effluents on the expression of ahpC in P. putida following 16 h exposure. Data are expressed as fold induction relative to the untreated control (artificial water) and were normalized to the 16r RNA gene. Dotted lines indicate expression differences between treatments.
Figure 3. Effects of influents and effluents on the expression of ahpC in P. putida following 16 h exposure. Data are expressed as fold induction relative to the untreated control (artificial water) and were normalized to the 16r RNA gene. Dotted lines indicate expression differences between treatments.
Applsci 15 07746 g003
Applsci 15 07746 g004
Figure 4. Effects of influents and effluents on the expression of ctaD in P. putida following 16 h exposure. Data are expressed as fold induction relative to the untreated control (artificial water) and were normalized to the 16r RNA gene. Dotted lines indicate expression differences between treatments.
Figure 4. Effects of influents and effluents on the expression of ctaD in P. putida following 16 h exposure. Data are expressed as fold induction relative to the untreated control (artificial water) and were normalized to the 16r RNA gene. Dotted lines indicate expression differences between treatments.
Applsci 15 07746 g004
Applsci 15 07746 g005
Figure 5. Time-course expression of genes with homologous function involved in oxidative stress (katE/cat, ahpC/gst) and energy metabolism (ctaD/nadh) in P. putida and D. magna following exposure to Al2O3 nanoparticles.
Figure 5. Time-course expression of genes with homologous function involved in oxidative stress (katE/cat, ahpC/gst) and energy metabolism (ctaD/nadh) in P. putida and D. magna following exposure to Al2O3 nanoparticles.
Applsci 15 07746 g005
Table 1. Samples used in the exposure experiments with P. putida.
Table 1. Samples used in the exposure experiments with P. putida.
No.Samples Collected for AnalysisSample Name
1Al2O3NPs (10 mg/L)NPs
2Bulk Al2O3 (10 mg/L)Bulk
3Control (water)Control
4Synthetic domestic wastewater-borne 10 mg/L Al2O3NPs, fed into the SBR reactor (Influent)WW-NPs-I
5Synthetic domestic wastewater-borne bulk Al2O3 (10mg/L), fed into the SBR reactor (Influent)WW-Bulk-I
6Synthetic domestic wastewater (control), fed into the
SBR reactor (Influent)		WW-Control-I
7Synthetic domestic wastewater-borne 10 mg/L Al2O3NPs, treated by activated sludge method in SBR reactor (Effluent)WW-NPs-E
8Synthetic domestic wastewater-borne bulk Al2O3 (10mg/L), treated by activated sludge method in SBR reactor (Effluent)WW-Bulk-E
9Synthetic domestic wastewater (control), treated by
activated sludge method in SBR reactor (Effluent)		WW-Control-E
Table 2. Target genes, RT-qPCR primers, and corresponding functions.
Table 2. Target genes, RT-qPCR primers, and corresponding functions.
GenesReverse Starter (5′–3′)Forward Starter (5′–3′)Function
catECTT GAT ACC CAC CGA ACC TGCTC GCC AAC ATC GAC CTG AAGXenobiotic detoxification
ctaDGCA GGT TGA GGA TGG TGG CCCA GCC AGC GTC ACC TTC TElectron transport and energy
production
ahpCGGC AGC CTT GAC CTT ACG CATC AAG ATT GTC GAG CTG AAC GOxidative stress
16S ribosomal RNA (16S)GAA ATT CCA CCA CCC TCT ACCTAC CTT GCT GTT TTG ACG TTA CCComponent of prokaryotic ribosomes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Doskocz, N.; Affek, K.; Załęska-Radziwiłł, M. Molecular Response of Bacteria Exposed to Wastewater-Borne Nanoparticles. Appl. Sci. 2025, 15, 7746. https://doi.org/10.3390/app15147746

AMA Style

Doskocz N, Affek K, Załęska-Radziwiłł M. Molecular Response of Bacteria Exposed to Wastewater-Borne Nanoparticles. Applied Sciences. 2025; 15(14):7746. https://doi.org/10.3390/app15147746

Chicago/Turabian Style

Doskocz, Nina, Katarzyna Affek, and Monika Załęska-Radziwiłł. 2025. "Molecular Response of Bacteria Exposed to Wastewater-Borne Nanoparticles" Applied Sciences 15, no. 14: 7746. https://doi.org/10.3390/app15147746

APA Style

Doskocz, N., Affek, K., & Załęska-Radziwiłł, M. (2025). Molecular Response of Bacteria Exposed to Wastewater-Borne Nanoparticles. Applied Sciences, 15(14), 7746. https://doi.org/10.3390/app15147746

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop