Optimizing Bioremediation of β-Blockers: Cometabolic Transformation of Propranolol and Metoprolol by Raoultella terrigena BB2 and Stenotrophomonas terrae BB3

Abstract

β-blockers are among the most widely prescribed cardiovascular drugs and are increasingly recognised as emerging pollutants due to their persistence, continuous release into aquatic environments, and potential toxicological effects on aquatic organisms. Their removal in conventional wastewater treatment plants is often inefficient, highlighting the need for biological remediation strategies. This study aimed to identify bacterial strains with the highest potential for the biotransformation of β-blockers. Therefore, we isolated and characterised bacterial strains capable of transforming two commonly used β-blockers—propranolol and metoprolol. The strains BB2 and BB3, which were able to transform propranolol and metoprolol, respectively, were identified as Raoultella terrigena and Stenotrophomonas terrae, respectively. BB2 showed broad metabolic versatility, utilising a wide range of carbon sources, whereas BB3 exhibited limited substrate utilisation. Antibiotic resistance profiling further distinguished the strains, with BB2 resistant across multiple antibiotic classes and BB3 largely sensitive. Co-metabolic assays demonstrated that supplementation with specific carbon and nitrogen sources markedly enhanced β-blocker removal, increasing propranolol biotransformation from 5% to 50% and metoprolol from 4% to 36%. These findings demonstrate the bioremediation potential of newly isolated strains and emphasise the importance of aligning microbial metabolic traits with nutrient conditions to improve pharmaceutical removal in wastewater treatment systems.

1. Introduction

β-adrenergic receptor blockers (β-blockers) belong to the group of pharmaceuticals and personal care products (PPCPs) for the treatment of cardiovascular disorders, such as high blood pressure, abnormal heart rhythm, or angina pectoris [1]. They have been used broadly for over 50 years, and owing to continuous population growth and civilisational progress, their prescription rates increase yearly. For example, 3,687,323 prescriptions for metoprolol were issued only in China between 2018 and 2023 [2]. After performing their actions, β-blockers are not metabolised completely before being excreted from the mammalian body and are transferred to the environment or wastewater. Moreover, the improper disposal of PPCPs is a substantial source of these compounds in the environment. In Taiwan alone, almost 3.6 tons of pharmaceuticals are thrown away annually [3]. In a study conducted in India, sewage collected from western metropolitan areas was reported to contain 294.7 and 79.5 μg/L of atenolol and metoprolol, respectively [4]; however, metoprolol was detected at concentrations of 950 and 7.0 μg/L in industrial wastewater and a nearby lake, respectively [5]. In Europe, propranolol was detected in influent and effluent from a municipal sewage treatment plant in Spain at a concentration of approximately 0.39 and 0.37 μg/L, respectively [6]. In Norway, hospital wastewater contained propranolol at the concentration range of 10 ng/L–25 μg/L [7]. Conventional wastewater treatment plants (WWTPs) are not characterised by efficient pharmaceutical removal. It has been proven that the WWTP-mediated utilisation of β-blockers varies from 0 to 79% [8]. Overall, β-blockers are typically present in municipal wastewater at concentrations from ng/L to several µg/L, with higher values occasionally observed in industrial discharge.

Thus, all commercially available β-blockers reach aquatic environments, soils, and sediments at concentrations ranging from a few nanograms to micrograms per litre. Among them, the environmental concentrations of atenolol, metoprolol, and propranolol are 1–2 orders of magnitude higher than those of the other β-blocker drugs, owing to their popular use worldwide. When emerging contaminants like β-blockers find their way into drinking water sources, they could potentially endanger human health. Additionally, some have already surpassed the predicted no-effect levels in the environment, thus presenting hazards to organisms inhabiting freshwater and marine ecosystems [9,10,11].

Propranolol is characterised by the highest acute toxicity towards aquatic organisms [12]. This drug is a naphthalene derivative and binds both β1 and β2 adrenergic receptors and can act as a serotonin receptor antagonist [13]. In contrast, metoprolol, a β₁-selective β-blocker, is composed of one aromatic ring and an aryloxypropanolamine side chain. This drug generally exhibits low acute toxicity in aquatic organisms. In the literature, however, it was proven that chronic exposure effects were more significant [14,15,16]: Daphnia magna showed physiological and reproductive impacts at concentrations as low as 3.2–12.5 mg/L after 9 days of exposure. Notably, Oncorhynchus mykiss showed liver and gill cytopathology at only 1–20 µg/L after 21 days of exposure, suggesting that fish are particularly sensitive to prolonged exposure. These findings underline the potential ecological risks of chronic metoprolol contamination, even at environmentally relevant concentrations [17]. For reasons presented above, removing these pollutants from the environment is crucial.

An alternative to the physicochemical removal of pharmaceuticals is biodegradation. It does not require additional energy inputs, is significantly less expensive, and, most importantly, can result in the complete degradation of the contaminant. Unfortunately, many β-blockers are resistant to it owing to the presence of heteroaromatic rings with aryloxypropanolamine side chains [18]. Nevertheless, biodegradation of these drugs was studied mostly with nitrification sludge, activated sludge, or enriched bacterial consortia [8,19,20]. The degradation of metoprolol (10 µg/L) after 24 days of incubation with heterotrophic bacteria, nitrite-oxidising bacteria, and enriched ammonia-oxidising bacteria has been reported to be 48, 58, and 64%, respectively [19].

In this study, we performed a screening process to identify bacterial strains capable of degrading or transforming two of the most widely used β-blockers globally, propranolol and metoprolol. Our primary goal was to select the strains with the highest transformation potential under laboratory conditions. We have isolated strains capable of transforming either propranolol or metoprolol, characterised their metabolism, and assessed their potential to remove pharmaceuticals. Furthermore, we evaluated the effects of various carbon and nitrogen sources on the efficiency of the co-metabolic biotransformation of the selected β-blockers. The obtained data provide the foundation for bioaugmentation strategies that significantly improve β-blockers’ biodegradation efficiency in wastewater treatment. To our knowledge, this study represents one of the first systematic screenings of β-blocker-transforming bacteria and the first to investigate how nutrient conditions influence their co-metabolic transformation capacity, offering new insight into microbial strategies for efficient β-blocker removal.

2. Results

2.1. Isolation of Propranolol- and Metoprolol-Degrading Bacteria from Activated Sludge

Screening for bacterial strains capable of degrading selected β-blockers in the activated sludge from the Klimzowiec municipal WWTP (Chorzów, Poland) resulted in the isolation of two strains capable of degrading propranolol, marked as BB1 and BB2, and three strains capable of degrading metoprolol, named BB3, BB4, and BB5. All isolated strains were Gram-negative and coccoid-shaped, except for strains BB2 and BB3, which were rod-shaped (Figure S1).

Candidate selection for further experiments was based on 3-day drug transformation tests in liquid MSM, where β-blockers were provided as the sole carbon source. This incubation period was chosen to identify microorganisms capable of initiating biotransformation most rapidly, a trait considered highly advantageous for both bioremediation applications. Rapid onset of degradation is particularly relevant to wastewater treatment plants, where hydraulic retention times typically do not exceed 2–3 days. During this 3-day period, only the BB2 and BB3 strains started the biotransformation of propranolol and metoprolol, respectively. For this reason, these strains were selected for further experiments. Both strains were grown on tryptone-soy agar for 24 h to study their morphological characteristics. The colonies of chosen strains were smooth, creamy white, and opaque (Figure S2).

2.2. Molecular Identification of the Selected Strains

The phylogenetic tree showed that the BB2 strain belongs to the Raoultella genus and forms a clade with Raoultella terrigena (Figure S3). The 16S rRNA gene sequences of these strains showed 98.36% similarity to R. terrigena ATCC 33257. For the BB3 strain, the analysis revealed that it belonged to the genus Stenotrophomonas and formed a clade with Stenotrophomonas terrae R-32768 (Figure S4), exhibiting 99.7% similarity to the 16S rRNA gene sequence.

2.3. Phenotypic Characterisation

The selected strains, BB2 and BB3 produced dehydrogenases, catalase, and siderophores. Cytochrome oxidase activity was detected only in BB3, which also displayed motility, whereas the other strain did not (

Table 1. Biochemical characterisation of the BB2 and BB3 strains.

	Bacterial Strain
Tested Enzyme/Feature	BB2	BB3
Dehydrogenases	+	+
Cytochrome oxidase	−	+
Catalase	+	+
Nitrate reductase	+	+
Siderophores	+	+
Motility	−	+

“+”—positive result; “−”—negative result.

).

The BB2 strain presented the potential to degrade most carbon sources effectively. On the contrary, BB3 could utilise only limited carbon sources, such as acetyl-glucosamine, mannose, lactic acid, glucose, maltose, Tween 40, maltotriose, and pyruvic acid (Figure 1A).

The antibiotic resistance profile of the BB2 strain revealed that this strain was resistant to all analysed antibiotics, except for novobiocin. However, strain BB2 showed low-level resistance to antibiotics such as oxacillin, carbenicillin, vancomycin, sulfadiazine, tobramycin, sulfamethoxazole, spiramycin, and rifampicin. Additionally, strain BB2 showed sensitivity to benzethonium chloride, fluoroorotic acid, and aspartic-β-hydroxamate. The BB3 strain was sensitive to all analysed antimicrobial agents and antibiotics, except for penicillin G (Figure 1B).

2.4. Various Carbon and Nitrogen Sources Impact Culture Growth and Drug Degradation Dynamics

As shown in Figure 2, propranolol (5 mg/L) and metoprolol (10 mg/L) did not provide sufficient carbon sources for the designated strains to support culture growth in both cases. Among all additional carbon and nitrogen sources (each added at a concentration of 0.5 g/L), the BB2 strain was able to grow efficiently only in the presence of ammonium acetate and glucose (Figure 2A). However, differences in the growth dynamics were observed. Cultures that grew on the ammonium acetate showed the absence of the lag phase and a 4-day-long logarithmic growth phase. Using glucose as a carbon source for the BB2 culture resulted in a prolonged 4-day-long lag phase, followed by a logarithmic growth phase. On the contrary, the cultures of the BB3 strain grew only when glucose was present in the medium (Figure 2B). The growth was characterised by 1- and 4-day-long lag phases and a 4-day-long log phase.

Additional carbon and nitrogen sources impacted the rates of propranolol and metoprolol biotransformation compared to the degradation rates obtained without additional supplementation (Figure 3; propranolol—5 ± 0.5%; metoprolol—4 ± 0.3%). The cultures of the BB2 strain supplemented with ammonium acetate exhibited an enhanced propranolol transformation rate (Figure 3A). The highest removal rate was 50 ± 4% of the initial concentration after 7 days of incubation. Although ammonium chloride also facilitated degradation (12 ± 1%), its impact was less pronounced than that of ammonium acetate. For BB3 cultures enriched with either glucose, ammonium chloride, or sodium acetate, a significant acceleration was observed in the rate of metoprolol transformation (Figure 3B). The addition of glucose exhibited the greatest effect on drug transformation. After 10 days of incubation, it was observed that 36 ± 1%, 19 ± 2%, and 17 ± 1% of the metoprolol was removed in cultures supplemented with glucose, ammonium chloride, or sodium acetate, respectively. The observed transformation occurred only in the presence of an additional carbon source, supporting the cometabolic nature of propranolol and metoprolol transformation by BB2 and BB3.

3. Discussion

A successful bioremediation system relies on microorganisms that can efficiently transform pollutants and remain competitive in their native microbial communities. For this reason, activated sludge was selected as the source of isolates, as it naturally contains bacteria adapted to wastewater composition, pharmaceutical exposure, and fluctuating nutrient and hydraulic conditions. Such indigenous strains are strong candidates for bioaugmentation, as they are more likely to survive and function effectively in real treatment systems while minimising ecological disruption [21,22,23].

Strain BB2 was identified as Raoultella, a genus closely related to Klebsiella (separated in 2001). While generally not highly virulent, Raoultella spp. possess factors such as LPS, adhesins, siderophores, biofilm formation, and bacteriocins [23]. They are known for degrading fatty compounds [24], PAHs [25], TNT [26], and for reducing heavy metals [27], highlighting their bioremediation potential. BB2 exhibited typical genus traits (catalase-positive, non-motile, oxidase-negative, nitrate-reducing) [23,28,29]. Notably, siderophore production may support both virulence and aromatic compound degradation by facilitating iron acquisition [23,30,31]. The recovery of Raoultella from municipal activated sludge is unsurprising, as this genus is frequently detected in wastewater environments and has been associated with nutrient-rich, pollutant-exposed habitats. Its metabolic versatility and capacity to tolerate chemical stressors likely reflect adaptation to the nutrient and contaminant gradients characteristic of WWTPs.

The second strain, BB3, showing the highest potential for metoprolol transformation, was identified as Stenotrophomonas (Xanthomonadaceae). This genus degrades aromatic hydrocarbons and contains dioxygenases for xenobiotic breakdown (e.g., phenol derivatives, polycyclic hydrocarbons, selenium compounds) [32,33]. Although Stenotrophomonas generally lacks oxidase, some oxidase-positive strains like BB3 and its closest relative, S. terrae R-32768, were identified [34]. The members of this genus are also known to promote plant growth and development in marginal soils through the biosynthesis of antagonistic metabolites, such as siderophores, antimicrobial peptides, and biosurfactants [35]. The isolation of Stenotrophomonas from activated sludge also aligns with previous findings, as this genus is commonly enriched in wastewater systems due to its ability to utilise diverse organic compounds and tolerate fluctuating environmental stress. Interestingly, bacterial motility and chemotaxis also play a pivotal role in enhancing the biodegradation of aromatic pollutants by facilitating the directed movement of cells toward contaminant sources, thereby increasing pollutant bioavailability and cellular uptake. Chemotactic bacteria such as Pseudomonas putida F1 demonstrated accelerated degradation of aromatic compounds like toluene and naphthalene [36]. The motility observed in BB3 may further support competitive fitness in biofilm-rich activated sludge environments, where chemotaxis can enhance access to micropollutants.

The ability to utilise diverse carbon sources is essential for microbial survival across varying environments. Strain BB2 shows notable metabolic adaptability, thriving under fluctuating nutrient conditions. It efficiently metabolises a wide range of carbohydrates, including monosaccharides, disaccharides, and sugar acids, consistent with the presence of pathways for hexose and pentose metabolism, indicating a primary reliance on carbohydrate-derived energy [37]. In contrast, its inability to utilise propionic, glycolic, glyoxylic, acetoacetic, and tricarballylic acids reflects limited capacity for short-chain fatty and keto acid metabolism, suggesting reduced dependence on lipid oxidation. Similarly, lack of growth on Tween 20, Tween 40, and Tween 80 implies absence of lipase activity and minimal utilisation of surfactant-based carbon sources [38,39]. BB2 demonstrated selective amino acid catabolism, however, failure to metabolise α-ketoglutarate and α-ketobutyrate indicates restricted TCA cycle functionality and limited energy generation from amino acid intermediates [40]. As a member of Enterobacteriaceae, BB2 primarily relies on sugars and fermentative metabolism, though there are related strains such as R. planticola 232-2 [23,24]. The presence of pathways for hydroxyphenylacetic acid metabolism suggests capacity for aromatic compound degradation, a trait associated with lignin decomposition and potential bioremediation applications. Comparable metabolic versatility has been observed in Raoultella sp. SM1 from a uranium mine in Kowary, Poland, capable of iron reduction and uranium precipitation [27].

Metabolic profiling of the BB3 strain revealed a preference for simple carbohydrates, organic acids, and dipeptides, indicating versatile yet selective catabolic capabilities. BB3 efficiently utilised substrates such as N-acetyl-D-glucosamine, α-D-glucose, maltose, maltotriose, and tricarboxylic acid intermediates, including citric, acetic, pyruvic, and propionic acids, consistent with active glycolytic and oxidative pathways. Positive metabolism of Tween 40 suggests esterase or lipase activity and potential lipolytic capacity [39], in contrast to the BB2 strain. The strain also metabolised amino acids and small peptides, reflecting the ability to exploit proteinaceous substrates. However, BB3 failed to utilise many disaccharides, sugar alcohols, phosphorylated sugars, and uronic acids, indicating restricted saccharolytic range. Overall, BB3 exhibits a narrower, specialised carbon utilisation profile, favouring readily degradable low-complexity substrates, in contrast to numerous Stenotrophomonas species that typically metabolise a broader array of disaccharides and sugar alcohols [34].

Bioremediation bacteria often harbour antibiotic resistance genes (ARGs) due to co-selection in polluted environments. As noted by Colin et al. [41] and Phale et al. [42], microorganisms degrading hydrocarbons, heavy metals, and other contaminants frequently carry mobile genetic elements encoding both pollutant tolerance and antibiotic resistance. The association of resistance determinants with plasmids is especially noteworthy, since plasmids not only facilitate antimicrobial resistance but are also linked to an expanded metabolic repertoire and the potential for more complete degradation of environmental pollutants. While effective in pollution mitigation, these bacteria may act as ARG reservoirs, particularly in wastewater and contaminated soils, raising biosafety concerns and highlighting the need for ARG monitoring and safer bioremediation strategies. Although we did not determine the genetic basis of resistance in our isolates, such associations highlight the importance of monitoring antibiotic resistance when selecting strains for bioremediation.

The genus Raoultella is known to exhibit intrinsic resistance to several antibiotics [30,43,44]. Consistent with this, strain BB2 displayed a multidrug-resistant phenotype, including resistance to β-lactams, aminoglycosides, polymyxins, and sulfonamides. This resistance pattern aligns with reports for related Raoultella and Klebsiella species [45,46,47].

In contrast, S. terrae BB3 showed low overall tolerance to antibiotics, consistent with non-clinical environmental Stenotrophomonas isolates [48,49]. The relatively narrow resistance pattern suggests a predominantly intrinsic resistance background, with no indication of extensive antimicrobial resistance acquisition. Nevertheless, genomic screening in future work would help confirm whether resistance traits and biotransformation capacity are chromosomal or plasmid-associated.

Microbial degradation is being increasingly examined as a more sustainable strategy than the physicochemical treatments to mitigate β-blocker pollution [9]. Nevertheless, these compounds remain recalcitrant in environmental and engineered systems due to both chemical stability and limited microbial accessibility [4,5]. Their structures, comprising aromatic rings, ether bonds, and secondary alcohol or amine groups, impede enzymatic attack, contributing to poor biodegradability. Metoprolol (log P ≈ 1.8) [50] and propranolol (log P ≈ 3.1) [51] exemplify this challenge: despite differing hydrophobicity and adsorption behaviour, neither is effectively mineralised in conventional wastewater treatment processes [52]. Efficient degradation generally requires specialised oxidative enzymes, such as cytochrome P450 monooxygenases or fungal laccases, which are not abundant in typical activated-sludge microbiomes [53]. Thus, the intrinsic chemical resilience and limited metabolic accessibility of β-blockers underpin their persistence across both aerobic and anaerobic treatment environments, highlighting the need to identify or engineer microbial systems capable of overcoming these constraints.

The β-blocker concentrations used in this study (5 mg/L propranolol and 10 mg/L metoprolol) were higher than the ng/L–µg/L levels typically detected in municipal wastewater [6,7], and do not fall within the upper range reported in industrial effluents and hospital discharge. Such elevated concentrations are commonly applied in laboratory screening studies to ensure clear observation of degradation trends and enzyme induction behaviour.

The study demonstrated that neither strain could grow with β-blockers as the sole carbon source, confirming that these compounds are not directly metabolisable and supporting their known co-metabolic nature. In such systems, xenobiotics are transformed only in the presence of an easily utilisable substrate that induces the necessary enzymatic machinery [54]. This metabolic strategy is typical for activated-sludge bacteria exposed to low-concentration pharmaceuticals and other recalcitrant pollutants.

Carbon and nitrogen supplementation markedly influenced strain performance. BB2 exhibited substrate-dependent growth dynamics: ammonium acetate enabled immediate growth without a lag phase, whereas glucose induced a four-day lag, suggesting slower metabolic activation or regulatory constraints. BB3 was less metabolically versatile, growing efficiently only with glucose, yet it showed faster adaptation to this substrate than BB2. Ammonium acetate proved to be the most effective co-substrate for BB2, enhancing the biotransformation of propranolol. Notably, propranolol transformation by BB2 proceeded at a nearly constant rate, independent of growth phase, indicating that cometabolic activity was driven by metabolic flux rather than biomass increase. In contrast, glucose and ammonium chloride supported much lower transformation rates. This likely reflects metabolic routing: acetate directly enters the TCA cycle via acetyl-CoA, promoting respiration and generating reducing equivalents (e.g., NADH) necessary for oxidative cometabolic enzymes. In many bacteria, including E. coli, glucose can trigger carbon catabolite repression, reducing expression of secondary oxidative pathways required for xenobiotic degradation [55].

Although Stenotrophomonas spp., including S. maltophilia, are capable of degrading aromatic compounds [56,57,58], glucose can either enhance or suppress these pathways depending on concentration and regulatory context. Thus, the nutrient-driven variability observed here mirrors the fluctuating substrate landscape of activated sludge, where cometabolic capacity depends strongly on co-substrate availability.

In this study, both isolates required co-substrates to transform β-blockers. R. terrigena BB2 initiated propranolol degradation rapidly and more efficiently, whereas S. terrae BB3 co-metabolised metoprolol with slower activation, consistent with metoprolol’s higher hydrophilicity and lower biomass affinity. These strain- and pollutant-specific responses align with previous findings on β-blocker persistence and cometabolic removal in wastewater systems. Collectively, the traits of BB2 and BB3, like rapid cometabolic activation, co-substrate dependence, and metabolic adaptability, reflect selective pressures of wastewater environments and highlight their potential for bioaugmentation in pharmaceutical removal systems (Table S1).

4. Materials and Methods

4.1. Chemicals and Reagents

Propranolol hydrochloride, metoprolol tartrate, tetramethyl-p-phenylenediamine dihydrochloride, hydrogen peroxide, N,N-dimethyl-α-naphthylamine, tetrazolium chloride, sulfanilic acid, and HPLC-grade reagents used for chromatographic analyses (acetic acid, methanol, acetonitrile) were obtained from Sigma-Aldrich (St. Louis, MO, USA). All chemicals used for genomic identification (DreamTaq Buffer, MgCl₂, bovine serum albumin, dNTPs, DreamTaq DNA polymerase, starters, agarose, Midori Green, GeneRuler DNA Ladder 100 bp Plus) were from Thermo-Fisher Scientific (Waltham, MA, USA). Medium ingredients were obtained from VWR (Radnor, PA, USA).

4.2. Screening for Propranolol- and Metoprolol-Degrading Bacteria

Isolation of propranolol- or metoprolol-degrading bacteria was performed by the direct method from the activated sludge from the aerobic chamber of the Klimzowiec WWTP (Chorzów, Poland). The activated sludge samples (500 µL) were directly planted on a solid mineral salt medium (MSM) [59] supplemented with 10 mg/L propranolol or 5 mg/L metoprolol as the only carbon source. The inoculated plates were incubated at 25 °C for 48 h and observed daily. Obtained colonies were transferred to fresh solid MSM supplemented with 10 mg/L propranolol or 5.0 mg/L metoprolol and incubated under the same conditions. After the third transfer, the gained colonies were used for further studies.

4.3. Cultivation of the Isolated Bacterial Strains

Isolated strains were cultivated in the liquid nutrient broth at 25 °C on a rotary shaker at 130 rpm. After 24 h, the cultures were centrifuged at 5000 rpm for 15 min, washed twice with MSM, and resuspended in the same medium. Prepared bacterial suspensions were used as an inoculum for further studies.

4.4. DNA Isolation and Phylogenetic Identification of the Isolated Strains

The genomic DNA of the isolated strains was extracted using the Genomic Mini AX Bacteria Spin Kit (A&A Biotechnology, Gdańsk, Poland) following the manufacturer’s instructions. The isolated DNA yield and quality were checked spectrophotometrically. For strain identification, the 16S rRNA gene was amplified using polymerase chain reaction (PCR). The total reaction mix (50 μL) included the following: 5.0 μL of DreamTaq Buffer (10×; ThermoFisher Scientific, Waltham, Massachusetts, USA), 4.0 μL of MgCl₂ (25 mM), 1.0 μL of bovine serum albumin (BSA; 20 μg/μL), 5.0 μL of deoxyribonucleoside triphosphate mix (dNTPs; 2.0 mM each), 0.25 μL of each primer (100 μM each), 0.25 μL of DreamTaq DNA polymerase (5.0 U/μL; ThermoFisher Scientific, Waltham, MA, USA), 4.0 μL of strain genomic DNA added as a template, and 30.25 μL of PCR-grade H₂O. The standard primers used for the reaction were 27F (5′-AGAGTTTGATCMTGGCTCAG-3′) and 1492R (5′-GGTTACCTTGTTACGACTT-3′), which amplify almost the whole 16S rRNA gene (approx. 1500 bp). The touch-down PCR programme was as follows: 94 °C for 5 min, 3 cycles of 94 °C for 45 s, 57–55 °C for 30 s (−1 °C/cycle), 72 °C for 2 min, 40 cycles of 94 °C for 45 s, 53 °C for 30 s, 72 °C for 2 min, followed by final elongation at 72 °C for 5 min. The same reaction mix prepared with PCR-grade H₂O instead of a DNA template was used as the negative control. The PCR results were verified by agarose gel electrophoresis using 10 μL of the reaction. Electrophoresis was conducted in 1% agarose gel supplemented with Midori Green for DNA detection. The GeneRuler DNA Ladder 100 bp Plus was used as a size marker. Next, the PCR product was purified using the GeneJet PCR Purification Kit (Thermo-Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s instructions, and sent for sequencing to Genomed S.A (Warsaw, Poland).

The amplicon sequencing was performed in both forward and reverse directions using the Sanger sequencing method and the same primers as for the PCR. The poor-quality nucleotides in the obtained sequences were manually trimmed, and the 16S rRNA gene was reconstructed by overlapping the forward and reverse fragments of the gene, resulting in a 1283 bp sequence for BB2 and a 1293 bp sequence for BB3. The sequences were deposited in the GenBank database of the National Center for Biotechnology Information (NCBI) under the accession numbers PP972776 and PP972778.

The sequences were searched against the NCBI 16S rRNA/ITS database using the blast tool [60]. Based on the database search results, 16S rRNA sequences belonging to related bacterial species were downloaded and used for phylogenetic tree calculation. For that, the sequences were aligned using the MAFFT algorithm with default settings [61]. The resulting aligned sequences were trimmed on their 5′ and 3′ ends ensure the same flanking sequences for the whole dataset and were re-aligned using the same algorithm. The phylogenetic trees were calculated using IQ-TREE software (version 2.4.0) [62] with automatic substitution model selection [63] and validated using a 1000 ultrafast bootstrap [64]. The trees were visualised using the Interactive Tree Of Life server [65]. All sequence processing, including trimming, gene reconstruction, and multisequence alignment, was performed using Unipro Ugene software (version 51.1) [66].

4.5. Propranolol and Metoprolol Degradation Assays

The isolated strains were tested for propranolol or metoprolol degradation abilities in a 250 mL Erlenmeyer flask containing 100 mL of MSM (pH 7.2). Each flask was supplemented with propranolol or metoprolol to obtain a final concentration of 5.0 mg/L or 10 mg/L, respectively, and every 3 days with different carbon or nitrogen sources (0.5 g/L) when the experiment was longer than 3 days. Incubation was conducted with shaking (130 rpm) at 30 °C. The control cultures supplemented only with propranolol or metoprolol were also prepared. To determine the concentrations of β-blockers, bacterial culture samples from each flask were collected every 24 or 48 h, centrifuged at 14,000 rpm for 20 min, and analysed by reverse-phase high-performance liquid chromatography (RP-HPLC).

Propranolol and metoprolol concentrations were measured using the RP-HPLC (Merck HITACHI, Darmstadt, Germany) equipped with an Ascentis Express^® C18 HPLC Column (100 × 4.6 mm; Sigma-Aldrich, Burlington, MA, USA), pre-column Opti-Solw^® EXP (Sigma-Aldrich, Burlington, Massachusetts, USA), and a DAD detector (Merck HITACHI, Darmstadt, Germany). The mobile phase for propranolol separation consisted of 99.8% methanol and 1% acetic acid (45:55 v/v) with a flow rate of 1.0 mL/min. For metoprolol separation, the mobile phase consisted of acetonitrile, 99.8% methanol, and 1% acetic acid (10:15:75 v/v/v) with a flow rate of 1.0 mL/min. The column temperature was set at 23 °C. The detection wavelength was 285 nm for propranolol [67] and 272 nm for metoprolol [68]. Propranolol and metoprolol were identified by comparison of HPLC retention time and UV-VIS spectra with those from the external standards. Uninoculated controls were also prepared to determine abiotic degradation of the drugs.

4.6. Metabolic Characterisation of the Isolated Strains

To examine the metabolic characteristics of the isolated strains, the production of the dehydrogenase, cytochrome oxidase, catalase, starch hydrolase, and gelatinase enzymes was determined. Additionally, strains were tested for biosurfactant and siderophore production, and their motility abilities were evaluated.

Dehydrogenase activity was measured by a modified method with methylene blue [69]. Bacteria were cultured in tubes with the liquid broth (peptone 5 g/L; meat extract 3 g/L) for 48 h at 30 °C. Subsequently, two drops of methylene blue solution (1% v/v) were added to the culture. The discolouration of the medium after 30 min was considered a positive result for dehydrogenase production. The production of the cytochrome oxidase enzyme was checked by the oxidase test [70]. Cultures grown for 48 h on broth agar (peptone 5.0 g/L, meat extract 3.0 g/L, and agar 20 g/L) at 30 °C were collected using a steel loop and placed on a filter paper previously wetted by 1% tetramethyl-p-phenylenediamine dihydrochloride. The formation of the purple-blue spot indicated positive results after 10 s of incubation. A catalase test was performed using the plate method [71]. A few millilitres of 3% H₂O₂ were directly poured onto a 24 h heavily grown pure culture on a tryptic soy agar plate. The formation of bubbles was considered a positive result, indicating the production of the catalase enzyme by the analysed strains. The presence of nitrate reductase was examined using the Griess method based on the diazotisation reaction. The isolated strains were inoculated into a nitrate reduction medium (peptone 5.0 g/L, beef extract 3.0 g/L, and potassium nitrate 1.0 g/L) and incubated at 30 °C with shaking (120 rpm) for 24 h. Subsequently, two drops of N,N-dimethyl-α-naphthylamine in acetic acid (5 N) were mixed with two drops of sulfanilic acid in acetic acid (5 N) and 1.0 mL of the cultivated culture in a separate test tube. When the tested organism was able to reduce nitrate to nitrite, a red colour developed within 2 min, signalling the presence of nitrite in the tube [72].

The siderophore production was obtained using a blue agar chrome azurol S (CAS) assay. The preparation of the plates with CAS was performed according to Louden et al. [73]. The isolated strains were inoculated on the plates, and after 48 h, the medium was observed for any changes in its colour. A yellow halo around the colonies indicated the production of the siderophore. To evaluate the motility of the isolated strains, they were streaked on the medium plates for the motility test (beef extract 3.0 g/L; pancreatic digest of casein 10 g/L; NaCl 5.0 g/L, tetrazolium chloride 0.05 g/L; and agar 4.0 g/L). After 24 h of incubation, a red turbid area extending away from the inoculation line was treated as a positive result. A negative result was indicated when the red area was only in the place of inoculation [74].

The isolated strains were additionally characterised for their extended metabolic competencies using the Phenotype MicroArray system (PM; Biolog, Hayward, CA, USA) following the manufacturer’s instructions with some modifications. Briefly, cells grown on the tryptic soy agar plates for 24 h were removed by sterile swab and transferred into the IF-0 buffer. The final transmittance of the cell suspension was determined as 42% T. The prepared suspension was diluted 5 times using the IF-0 buffer with dye (Dye mix A) and used as inoculum for the following plates. The PM1 plate with various carbon sources was directly inoculated with the prepared cell suspension (100 µL/well). The PM12B plate with different antibiotics was inoculated (100 µL/well) with the cell suspension diluted 200 times using the IF-0 buffer with dye (Dye mix A). All plates were incubated in the dark for 24 h at 30 °C to develop a purple colour sufficient for growth specification. The spectroscopic determination of growth was performed using a Spark Multimode Microplate Reader (Tecan, Männedorf, Switzerland) at 590 nm before and after the incubation of the plates. The bacteria were considered resistant or insensitive to an antibiotic when there was a 100% increase in growth in at least two of these four concentrations.

4.7. Statistical Analyses

All experiments were performed in at least three replicates. The values of the propranolol and metoprolol degradation rates were expressed as a mean ± standard deviation. The values of the optical density at 600 nm and propranolol or metoprolol concentration measured on the last day of incubation were analysed by STATISTICA 13 PL software package (version 13.3). Statistically significant differences and similarities have been demonstrated by the Tukey test (p ≥ 0.05).

5. Conclusions

This study demonstrates that the effective bioremediation of β-blockers such as propranolol and metoprolol relies not only on the selection of competent microbial strains but also on understanding their distinct metabolic and co-metabolic strategies. Raoultella terrigena BB2 and Stenotrophomonas terrae BB3 exhibited complementary traits: BB2’s broad carbohydrate utilisation and preference for ammonium acetate facilitated efficient propranolol transformation, while BB3’s selective glucose metabolism enhanced metoprolol transformation. These results highlight the relevance of strain-specific metabolic traits and co-substrate availability in optimising pharmaceutical biodegradation. In addition, antibiotic resistance profiling revealed important differences between the isolates, suggesting that strain selection should also consider potential ecological and biosafety risks when designing microbial remediation strategies. Future work should explore the performance of these strains in mixed cultures and real wastewater environments, and investigate whether combining complementary metabolic profiles can enhance β-blocker removal at larger scales.