
==== Front
J Biol Chem
J Biol Chem
The Journal of Biological Chemistry
0021-9258
1083-351X
American Society for Biochemistry and Molecular Biology

S0021-9258(24)02095-7
10.1016/j.jbc.2024.107594
107594
Research Article
Drug metabolism of ciprofloxacin, ivacaftor, and raloxifene by Pseudomonas aeruginosa cytochrome P450 CYP107S1
Kandel Sylvie E. 1
Tooker Brian C. 2
Lampe Jed N. jed.lampe@cuanschutz.edu
1∗
1 Department of Pharmaceutical Sciences, Skaggs School of Pharmacy, University of Colorado, Aurora, Colorado, USA
2 Pulmonary Division, Department of Medicine, National Jewish Health, Denver, Colorado, USA
∗ For correspondence: Jed N. Lampe jed.lampe@cuanschutz.edu
18 7 2024
8 2024
18 7 2024
300 8 10759430 4 2024
29 6 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Drug metabolism is one of the main processes governing the pharmacokinetics and toxicity of drugs via their chemical biotransformation and elimination. In humans, the liver, enriched with cytochrome P450 (CYP) enzymes, plays a major metabolic and detoxification role. The gut microbiome and its complex community of microorganisms can also contribute to some extent to drug metabolism. However, during an infection when pathogenic microorganisms invade the host, our knowledge of the impact on drug metabolism by this pathobiome remains limited. The intrinsic resistance mechanisms and rapid metabolic adaptation to new environments often allow the human bacterial pathogens to persist, despite the many antibiotic therapies available. Here, we demonstrate that a bacterial CYP enzyme, CYP107S1, from Pseudomonas aeruginosa, a predominant bacterial pathogen in cystic fibrosis patients, can metabolize multiple drugs from different classes. CYP107S1 demonstrated high substrate promiscuity and allosteric properties much like human hepatic CYP3A4. Our findings demonstrated binding and metabolism by the recombinant CYP107S1 of fluoroquinolone antibiotics (ciprofloxacin and fleroxacin), a cystic fibrosis transmembrane conductance regulator potentiator (ivacaftor), and a selective estrogen receptor modulator antimicrobial adjuvant (raloxifene). Our in vitro metabolism data were further corroborated by molecular docking of each drug to the heme active site using a CYP107S1 homology model. Our findings raise the potential for microbial pathogens modulating drug concentrations locally at the site of infection, if not systemically, via CYP-mediated biotransformation reactions. To our knowledge, this is the first report of a CYP enzyme from a known bacterial pathogen that is capable of metabolizing clinically utilized drugs.

Keywords

Pseudomonas aeruginosa
pathogen
cytochrome P450
drug-metabolizing enzyme
fluoroquinolone antibiotics
CFTR potentiator
SERM antimicrobial adjuvant
Abbreviations

CE collision energy

CF cystic fibrosis

CFTR CF transmembrane conductance regulator

CV cone voltage

CYP cytochrome P450

DMSO dimethyl sulfoxide

FdR ferredoxin reductase

Fdx ferredoxin

LC-UV-MS liquid chromatography combined with UV and mass spectrometry detection

MRM multiple reaction monitoring

MS/MS tandem mass spectrometry

PK pharmacokinetics

Reviewed by members of the JBC Editorial Board. Edited by Joseph Jez
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pmcWhile much has been learned regarding the impact of the gut microbiota contribution to drug metabolism and disposition in humans (1, 2, 3), few studies have focused on the “pathobiome” (4, 5, 6), defined as the entire complement of pathogenic microorganisms infecting a host at any particular point in time (7, 8). When a predominant pathogenic microbial species systemically invades the human body, or a specific human tissue, how this impacts the fate of drugs during an infection has not yet been duly considered. Among the opportunistic human pathogens, Pseudomonas aeruginosa, well known for its intrinsic resistance to antibiotics (9, 10), is a common cause of nosocomial pneumonia and infections in the severely burned, immunocompromised, and cystic fibrosis (CF) patients (11, 12, 13, 14). Antibiotic treatment has generally been challenging for these patient groups due to altered drug pharmacokinetics (PK) usually triggered by the pathophysiological changes relating to their illnesses and resulting in increased risks for developing antibiotic resistance (15, 16, 17). Multiple absorption, distribution, metabolism, and excretion processes may be involved simultaneously in the modified PK profiles of these patients (17). The altered PK occurring from the increased antibiotic clearance rate often requires a higher dosage regimen to achieve therapeutic efficacy. In CF patients, the higher nonrenal clearance rate of the antibiotic may result from an increase in metabolism (18, 19, 20). For example, for the fluoroquinolone antibiotic fleroxacin, Mimeault et al. (19) reported an increase in the mean plasma concentrations and area under the curves of the N-desmethyl and N-oxide metabolites in CF patients. Drug–drug interactions from CF-related polypharmacy could to some extent contribute to induction of the cytochrome P450 (CYP) drug-metabolizing enzymes (21). Parker et al. (22) proposed a CF-related genetic component for the increase of CYP1A2 activity measured in a cohort of young children with CF, whereas Knoppert et al. in 1988 (23) considered enhanced extrahepatic metabolizing activity to be linked to the increased metabolism and pointed specifically to the lung undergoing profound pathological changes due to chronic Pseudomonas infections. Intriguingly, treatment of human A549 cells, a lung carcinoma epithelial cell line, with the P. aeruginosa virulence factors 1-hydroxyphenazine and pyocyanin resulted in the induction of CYP1A1 and CYP1B1 transcription via activation of the aryl hydrocarbon receptor (24, 25). Furthermore, P. aeruginosa is well known for its intrinsic drug-metabolizing enzymes, such as the β-lactamases, which are prominent mechanisms of resistance occasioning serious treatment challenges for β-lactam antibiotics (4, 10, 26).

Interestingly, among the bacterial enzymes that metabolize drugs, Pseudomonas CYP enzymes have never been considered as potential pathways for drug metabolism during an infection. Bacterial CYPs are important for carbon source metabolism (27, 28), detoxification (29, 30), and secondary metabolite pathways including alkaloids, terpenes, steroids, and fatty acids (31, 32, 33, 34, 35). The genome of P. aeruginosa contains at least three putative CYP genes: CYP107S1, CYP168A1, and CYP169A1. Previously, a study based on a CYP107S1 gene knockout supported involvement of that CYP in the metabolic activation of procarcinogens (36). Subsequently, the P. aeruginosa CYP168A1 gene was cloned, expressed, and identified as a subterminal fatty acid hydroxylase (35, 37). In that study, we also demonstrated that CYP168A1 can hydroxylate arachidonic acid, a precursor for eicosanoids, essential for inflammatory signaling pathways and present in abundance in the CF lung. Subsequently, CYP168A1 from the P. aeruginosa HS9 strain, a strain isolated from soil, was investigated for its propensity to biodegrade via dehalogenation the hexabromocyclododecane chemicals commonly used as flame retardants and considered as persistent organic chemicals due to their environmental accumulation (29). Taken together, these findings emphasize the role of the P. aeruginosa CYP enzymes as xenobiotic detoxifiers that allow the bacteria to adapt to different environmental settings (e.g., from soil, to water, to living plants, and animals). Given that P. aeruginosa is an opportunistic human pathogen, an important question intrigued us: could the CYP enzymes from P. aeruginosa perform a detoxification function by metabolizing drugs, much as their human CYP counterparts do?

Here, we set out to investigate the abilities of one P. aeruginosa CYP enzyme, CYP107S1, to bind and metabolize drugs, including fluoroquinolone antibiotics, a CF transmembrane conductance regulator (CFTR) potentiator drug, and the selective estrogen receptor modulator (SERM) raloxifene, which has previously demonstrated antibiotic adjuvant properties against P. aeruginosa (38, 39, 40, 41, 42, 43). After cloning and expressing the CYP107S1 gene in Escherichia coli, we focused our efforts in characterizing the major metabolites formed from each drug by the recombinant CYP107S1 using the spinach-derived redox partner electron transfer complex and then further substantiated our metabolic data through molecular docking of the drugs to a CYP107S1 homology model. To our knowledge, this is the first report of a CYP enzyme from a known bacterial pathogen that is capable of metabolizing clinically utilized drugs.

Results

Expression and characterization of recombinant CYP107S1

CYP107S1 from the PAO1 strain was cloned (Fig. S1), expressed in E. coli, purified, and subsequently characterized for the first time as a soluble CYP recombinant isoform. The purified protein migrated as a single band just under the 50 kDa protein marker on the denatured SDS-PAGE gel (Fig. 1A). The spectral absorption patterns of CYP107S1 were characteristic to a heme-containing protein with a λmax of 417 nm for the oxidized species and 414 nm for the sodium dithionite reduced heme iron species (Fig. 1B). The difference spectrum of the sodium dithionite reduced CYP107S1 binding to carbon monoxide exhibited a shift in the Soret band to a maximum at 449 nm (Fig. 1C), consistent with the spectral signature of CYP enzyme featured by an intense 450 nm band (44). The initial recombinant protein expression experiment from 4 L of E. coli culture yielded 3 μmoles of purified and soluble (His)-tagged CYP107S1 protein.Figure 1 Expression and spectral absorption characteristics of the recombinant CYP107S1.A, SDS-PAGE for the purified CYP107S1 recombinant protein expressed with a C-terminal 4xHis-tag (lane # 1; 32 pmol in 2 μl) on a Bio-Rad 4 to 15% Mini-protean TGX precast gel with Tris/glycine/SDS buffer and stained with the Bio-safe Coomassie G-250 solution from Bio-Rad. B, oxidized (solid line) and reduced (dashed line) absorption spectra of CYP107S1. C, CO-binding difference spectrum of the dithionite reduced CYP107S1. CO, carbon monoxide.

Ligand binding to CYP107S1

Spectral titrations were first conducted with a variety of azole compounds (Fig. 2, top panel), which are notorious CYP inhibitors triggering a type II red shift of the Soret band due to the direct coordination to the heme iron of the free electron pair originating from the nitrogen on the azole ring (45, 46). Binding isotherms for the azole compounds were plotted based on the maxima and minima obtained from the calculated difference binding spectra and then fitted to the best binding model to estimate the apparent dissociation constant (Kd, app) (Fig. 3, Tables 1, and S1). As expected, the three azole drugs tested demonstrated a type II binding mode (Fig. 3), but surprisingly, all bound to CYP107S1 with submicromolar Kd, app between 0.2 and 0.6 μM and best fit to the Hill equation model with nHill coefficient between 1.3 and 2 (Tables 1 and S1), suggesting a large and flexible active site with some potential allosteric features. To explore the binding affinities of CYP107S1 for other drugs, we initially focused on antibiotics used to treat P. aeruginosa infection and in particular fluoroquinolones (Fig. 2, middle panel), which have occasionally been reported for their altered PK in CF patients (19). Interestingly, titration of ciprofloxacin into purified CYP107S1 triggered a type II shift of the Soret band analogous to the azole ligands but approximately half the amplitude (ΔAmax) and yielded a weak Kd, app of 52 μM (Fig. 4A and Table 1). Conversely, titration of the fluoroquinolone fleroxacin produced a type I shift of the Soret band to 388 nm, signaling displacement of the heme distal water as the sixth ligand to the heme iron (45), and hence, substantiating substrate binding in the CYP107S1 active site (Fig. 4B). The binding isotherm of fleroxacin showed high variability between replicates spreading farther with increasing fluoroquinolone concentrations. Effectively, fleroxacin was poorly soluble in aqueous buffer and titration of the compound was challenging. A binding affinity of 68 μM was determined for fleroxacin, which remains in the same affinity range of ciprofloxacin (Table 1). Among the fluoroquinolones tested, titration of levofloxacin led to no spectral changes of the purified CYP107S1 (data not shown). The bulkiness and rigidity of the polycyclic structure of levofloxacin may possibly restrain binding into CYP107S1 active site and not trigger perturbation of the heme spectrum. Next, our probing of CYP107S1 ligand binding extended to nonantibiotic drugs and led us to uncover two tight-binding ligands with type I binding characteristics, ivacaftor and raloxifene (Fig. 2, bottom panel; Fig. 4, C and D). Ivacaftor bound to CYP107S1 with an affinity of 1.1 μM and raloxifene with a submicromolar Kd, app of 0.40 μM (Table 1). Both fit best to the Hill equation model (Table S1), again indicating cooperativity and hinting to a possible allosteric modulation feature in the CYP107S1 active site.Figure 2 Chemical structures of drugs tested for ligand binding to CYP107S1.

Figure 3 Azole-binding isotherms for CYP107S1 with representative difference spectra. Binding isotherms of clotrimazole (A), econazole (B), and ketoconazole (C), including biological triplicate measurements and with insets containing representative calculated difference spectra obtained from 1 μM CYP107S1, were best fitted using the Hill equation model with R2 of 0.990, 0.969, and 0.963, respectively.

Figure 4 Binding isotherms of the antibiotic agents, CFTR potentiator, and SERM adjuvant for CYP107S1 with representative difference spectra. Binding isotherms of ciprofloxacin (A), fleroxacin (B), ivacaftor (C), and raloxifene (D) were best fitted to either the one binding site model or the Hill equation model with R2 of 0.963, 0.883, 0.982, and 0.989, respectively. Insets correspond to representative calculated difference spectra obtained using 4 μM CYP107S1 for the fluoroquinolones and ivacaftor and 1 μM CYP107S1 for raloxifene. Tandem cuvettes were used for spectroscopic measurements to account for the absorbance originating from the ligands. CFTR, cystic fibrosis transmembrane conductance regulator; SERM, selective estrogen receptor modulator.

Table 1 CYP107S1 binding affinities for azoles, fluoroquinolone antibiotics, a CFTR potentiator and a SERM adjuvant

Ligands	Best fit model	Kd, app (μM)	nHill	ΔAmax (AU)	
Azoles					
 Clotrimazole	Hill	0.61 (0.55–0.69)	1.3	0.075 (0.073–0.078)	
 Econazole	Hill	0.24 (0.21–0.26)	2	0.070 (0.067–0.073)	
 Ketoconazole	Hill	0.21 (0.18–0.232)	1.5	0.050 (0.048–0.052)	
Fluoroquinolone antibiotics				
 Ciprofloxacin	Hyperbolic	52 (44–62)	-	0.032 (0.030–0.035)	
 Fleroxacin	Hyperbolic	68 (41–120)	-	0.041 (0.032–0.058)	
CFTR potentiator					
 Ivacaftor	Hill	1.1 (1.0–1.3)	1.3	0.046 (0.044–0.049)	
SERM adjuvant				
 Raloxifene	Hill	0.40 (0.36–0.44)	1.2	0.033 (0.032–0.034)	
Kd, app, apparent dissociation constant. nHill, Hill coefficient as degree of cooperativity indicator.

Binding and delta absorbance values are presented with the 95% confidence intervals in parentheses.

CFTR, cystic fibrosis transmembrane conductance regulator; SERM, selective estrogen receptor modulator.

Metabolism of fluoroquinolone antibiotics by CYP107S1

Our binding data indicated differences in the binding mode to CYP107S1 between the different fluoroquinolone drugs, with ciprofloxacin binding like an azole inhibitor, fleroxacin like a substrate, and levofloxacin displaying no evidence of binding. Therefore, in order to determine if CYP107S1 could metabolize any of the fluoroquinolone drugs, metabolism studies were carried out using the spinach-derived redox partner complex consisting of the spinach ferredoxin (Fdx) and ferredoxin reductase (FdR). The spinach Fdx and FdR redox partners have been used previously as effective electron transfer surrogates for the P. aeruginosa CYP168A1 isoform (35). Incubations of ciprofloxacin at 10 and 50 μM were carried out with 1 μM CYP107S1 and up to 60 min at 37 °C and analyzed for metabolite formation using liquid chromatography combined with UV and mass spectrometry detection (LC-UV-MS). While several MS scan types were used for the initial detection of potential metabolites, multiple reaction monitoring (MRM) and product ion scans were the ultimate LC-MS scans acquired for the metabolism studies. Since UV detection provided us with only limited signal for the metabolites, no UV data will be presented here. A total of five major metabolites (C1 to C5) were detected for ciprofloxacin by mass spectrometry (Fig. 5 and Table 2). Profiling of the metabolites revealed multiple biotransformation reactions by CYP107S1 for ciprofloxacin from N-dealkylation to hydroxylation and oxidation to oxo moieties. To allow for structure elucidation, tandem mass spectrometry (MS/MS) spectra were acquired for ciprofloxacin and its metabolites and were further supplemented with proposed ion fragmentation (Fig. 6). All metabolites, except for the C1 metabolite, were fully dependent on the cofactor NADPH. The C1 metabolite showed only partial dependency for the NADPH cofactor (Fig. 5A). Detected as an ion with an m/z of 306, it was identified as the desethylene derivative of ciprofloxacin (Fig. 6B) and exactly matched the retention time and MS/MS spectrum of the desethylene standard (Fig. S2). It is noteworthy to acknowledge that the desethylene metabolite was detected as an impurity in the ciprofloxacin standard (data not shown), which to some extent may impact the interpretation of its NADPH dependency in our incubations. One oxociprofloxacin metabolite, C2, was detected at the retention time of 5.24 min (Fig. 5B). According to the MS/MS spectrum and the proposed ion fragmentation, the oxidation to the oxo is directed to the piperazine ring (Fig. 6C). However, comparison with the oxociprofloxacin standard of the human metabolite (Fig. S2) revealed unmatched metabolites. Effectively, the human oxociprofloxacin metabolite standard eluted after ciprofloxacin at the retention time of 6.58 min and showed a different ion fragmentation pattern than C2. Two hydroxylation products of ciprofloxacin, C3 and C4, eluted after the parent (Fig. 5, D and E). From the LC-MS data and proposed ion fragmentation, hydroxylation to C4 indicated attack of the piperazine ring (Fig. 6E), and interestingly, a hydroxyl metabolite eluting (6.39 min; Fig. 5E) adjacent to the oxociprofloxacin standard (Fig. S2). Under our experimental conditions, C5 emerged as the metabolite with the highest mass spectrometric signal intensity (Fig. 5F). Although differences in ionization efficiency between the metabolites may require some consideration here, formation of a potential multi-oxo derivative (Fig. 6F) representing a major metabolic pathway is remarkable because of the requisite for multiple sequential oxidations. Conversely to ciprofloxacin, metabolism studies for fleroxacin (40 μM) and levofloxacin (50 μM) with CYP107S1 led to the characterization of only one type of metabolite formed by N-demethylation of the piperazine N-methyl (Figs. S3 and S4). The N-desmethyl derivatives were detected to a small extent in the control incubations without the NADPH cofactor, presumably from impurities present hitherto in the parent standards (data not shown); however, significant increase of the N-desmethyl metabolites was observed for both fluoroquinolones in presence of the NADPH cofactor.Figure 5 Pseudomonas aeruginosa CYP107S1 metabolizes the fluoroquinolone antibiotic ciprofloxacin. Representative MRM chromatograms for the major metabolites (C1–C5) formed in the incubations of the recombinant CYP107S1 (1 μM) and the spinach redox partners with ciprofloxacin at 10 μM up to 60 min and in the presence or absence of the cofactor NADPH. The MRM chromatograms correspond to the following mass transitions: 306 > 245 for C1 (A; desethylene), 346 > 245 for C2 (B), 332 > 231 for ciprofloxacin (C), 348 > 261 for C3 (D), 348 > 245 for C4 (E), and 360 > 243 for C5 (F). MRM, multiple reaction monitoring.

Table 2 Metabolite profiling for ciprofloxacin by Pseudomonas aeruginosa CYP107S1

Component	Retention time (min)	Parent ion (m/z)	Proposed chemical formula	Mass shift from parent	Proposed biotransformation	
C1a (desethylene)	4.86	306	C15H16FN3O3	−26	N-Dealkylation	
C2	5.24	346	C17H16FN3O4	+14	Oxidation to oxo	
Ciprofloxacin	5.43	332	C17H18FN3O3	-	-	
C3	5.49	348	C17H18FN3O4	+16	Hydroxylation	
C4	6.39	348	C17H18FN3O4	+16	Hydroxylation	
C5	6.73	360	C17H14FN3O5	+28	(Oxidation to oxo) × 2	
a The desethylene metabolite was also detected in the ciprofloxacin standard and 0 min incubation.

Figure 6 MS/MS spectra for ciprofloxacin and the CYP107S1 metabolites with proposed structure fragmentation insets. MS/MS spectra for the ciprofloxacin standard (A) and the metabolites C1 (B), C2 (C), C3 (D), C4 (E), and C5 (F) formed in ciprofloxacin (50 μM) incubations with recombinant CYP107S1 (1 μM). In the insets, structure elucidation is proposed for each metabolite according to Table 2 and the MS/MS ion fragmentation. CE, collision energy; MS/MS, tandem mass spectrometry.

Metabolism of the CFTR potentiator ivacaftor by CYP107S1

Ivacaftor, typically prescribed as a monotherapy for CF patients with the G551D mutation of the CFTR gene and included in other CFTR combination drug therapies, is a primary medication for the treatment of CF (47, 48). Therefore, when a treated CF patient is experiencing a P. aeruginosa infection, nano to micromolar concentration of the drug may be present in the systemic circulation and, consequently, reaching the site of infection and the bacterial pathogen. The strong binding affinity with the type I binding mode obtained for ivacaftor with the CYP107S1 recombinant enzyme favored the drug to be a prime substrate for this Pseudomonas CYP (Fig. 4 and Table 1). In order to test the accuracy of our assumption, a metabolism study was conducted. The MS sample analysis of ivacaftor incubated at 10 μM with 1 μM of CYP107S1 produced one major metabolite, I1, detected by mass spectrometry as m/z of 409 representing an addition of 16 mass units from the parent m/z, and thus, strongly indicating hydroxylation of ivacaftor by CYP107S1 (Fig. 7 and Table 3). Comparison of retention time and MS/MS spectrum of the I1 metabolite (Fig. 7, B and E) with the hydroxymethyl ivacaftor standard (Fig. 7, C and F) revealed that they were perfectly matching analytes. The hydroxymethyl ivacaftor is also a major circulating human metabolite in adult and pediatric CF patients which is formed by metabolism of ivacaftor via the hepatic CYP3A pathway (49).Figure 7 Hydroxylation of the CFTR potentiator ivacaftor by Pseudomonas aeruginosa CYP107S1. Representative MRM chromatograms for ivacaftor (A) and the I1 metabolite (B) formed in the incubations of the recombinant CYP107S1 (1 μM) and the spinach redox partners with ivacaftor at 10 μM up to 60 min and in the presence or absence of the cofactor NADPH. C, representative MRM chromatogram for the hydroxymethyl ivacaftor standard. MS/MS spectra for the ivacaftor standard (D), the I1 metabolite (E) formed in CYP107S1 incubations, and the hydroxymethyl ivacaftor standard (F), including proposed structure fragmentation insets. CFTR, cystic fibrosis transmembrane conductance regulator; MS/MS, tandem mass spectrometry; MRM, multiple reaction monitoring.

Table 3 Metabolite profiling of ivacaftor by Pseudomonas aeruginosa CYP107S1

Component	Retention time (min)	Parent ion (m/z)	Proposed chemical formula	Mass shift from parent	Proposed biotransformation	
I1 (hydroxymethyl ivacaftor)	3.18	409	C24H28N2O4	+16	Hydroxylation	
Ivacaftor	4.01	393	C24H28N2O3	-	-	

Metabolism of raloxifene by CYP107S1

Our ligand binding data indicated tight binding of raloxifene to CYP107S1 and a prototypical type I spectrum of a CYP substrate ligand (Fig. 4 and Table 1). To investigate the potential for raloxifene metabolism by the P. aeruginosa CYP107S1 enzyme, an in vitro metabolism study was carried out with raloxifene at 10 μM, 0.5 μM recombinant CYP107S1, and the spinach electron redox partners. The LC-UV-MS analysis of the raloxifene samples revealed significant substrate loss and formation of three major metabolites, denoted as R1 to R3 (Fig. 8, A–F and Table 4). According to its m/z of 406 and MS/MS ion fragmentation (Fig.9B), the metabolite R1 was formed by N-dealkylation at the piperidine ring of raloxifene. From the representative UV chromatogram of the incubation sample with the cofactor NADPH (Fig. 8B), R2 was the most abundant metabolite, followed by R3. R2 derived from dehydrogenation at the piperazine ring as substantiated by the fragment ions of m/z 82 and 110 of its MS/MS spectrum (Fig. 9C). Conversely, the R3 metabolite was more challenging to identify. Detected under the same MRM transition as R2 (472 > 110) (Fig. 8F), one possibility is that it arises from dehydrogenation at a different site of the piperidine ring. Our initial attempt to elucidate the structure of the R3 metabolite based on the product ion spectrum of the precursor ion at m/z 472 (Fig. 9D) was unsuccessful. In fact, the molecular ion of m/z 581 was unexpected and led us to acquire a full scan for R3 (Fig. 8G). The full mass spectrum of R3 presented an intense ion at m/z 472 and a smaller ion at m/z 943. When examining more closely the isotopic distribution of each ion, the multicharged nature of the ion at m/z 472 was clear and allowed us to propose, at last, dimerization of a raloxifene molecule with its dehydrogenated derivative. Interestingly, raloxifene dimerization has been previously reported with human liver microsomes, human CYP3A4 recombinant enzyme, and peroxidases (50).Figure 8 Metabolism of the SERM adjuvant raloxifene by Pseudomonas aeruginosa CYP107S1. Representative UV chromatograms (280 nm) for raloxifene (10 μM) incubations with CYP107S1 (0.5 μM) and the spinach redox partners at 0 min (A), 60 min with NADPH (B) or without NADPH (C). Representative MRM chromatograms for raloxifene (D) and its metabolites (E and F) formed in the CYP107S1 incubations in the presence or absence of the cofactor NADPH. The MRM chromatograms correspond to the following mass transitions: 474 > 112 for raloxifene (D), 406 > 121 for R1 (E), 472 > 110 for R2 and R3 metabolites (F). G, mass spectrum (in continuum) for full scan between the mass range m/z 350 to 1050 for the R3 metabolite, including insets pointing to the isotopic distribution pattern of ions at m/z 472 and 943. MRM, multiple reaction monitoring; SERM, selective estrogen receptor modulator.

Table 4 Metabolite profiling of raloxifene by Pseudomonas aeruginosa CYP107S1

Component	Retention time (min)	Parent ion (m/z)	Proposed chemical formula	Mass shift from parent	Proposed biotransformation	
R1	5.31	406	C23H19NO4S	−68	N-Dealkylation	
R2	5.94	472	C28H25NO4S	−2	Dehydrogenation	
Raloxifene	6.04	474	C28H27NO4S	-	-	
R3	6.95	943 [M+H]+	C56H50N2O8S2	+469	Dehydrogenation + dimerization	
472 [M+2H]2+	

Figure 9 MS/MS spectra for raloxifene and the CYP107S1 metabolites with proposed structure fragmentation insets. MS/MS spectra for the raloxifene standard (A) and the metabolites R1 (B), R2 (C), and R3 dimer (D) formed in raloxifene incubations with recombinant CYP107S1 (0.5 μM). In the insets, structure elucidation is proposed for each metabolite according to Table 4 and the MS/MS ion fragmentation. MS/MS, tandem mass spectrometry.

CYP107S1 homology model

A homology model was built using the CYP pikromycin hydroxylase PikC from Streptomyces venezuelae as a template (51). The structure generated indicated a compact, globular enzyme with a typical CYP fold and architecture (Fig. 10A). CASTp 3.0 (52) calculated an active site volume of 1526 Å3 with an area of 1482 Å2, including several subpockets within the interior of the active site cavity (Fig. 10B). This was significantly larger than the active site volume of the other CYP enzyme that we had previously characterized from P. aeruginosa, CYP168A1 (670 Å3 with an area of 570 Å2) (35). The CYP107S1 structure includes a single cysteine residue (C347) that serves as the fifth, axial ligand to the heme iron. The proportion of aromatic residues totaled 5%, including 2% tyrosine, 2.3% phenylalanine, and 0.7% tryptophan, and was near half of the total aromatic residues in the CYP168A1 sequence (∼9%). The structure is composed of 17 alpha helical regions (52.5%; A–Q), including the I-helix that runs across the roof of the active site, above the heme iron. A shortened F/G loop substrate recognition region is present at the mouth of the active site.Figure 10 CYP107S1 homology model.A, stylized amino acid backbone of the CYP107S1 homology model (light gray) with the heme prosthetic group (red). B, CAST-p defined CYP107S1 solvent accessible active site (solvent accessible surface is colored according to hydrophobicity, with more red colored residues being more hydrophobic, blue hydrophilic, and white neutral).

Molecular docking of substrates to CYP107S1

The highest ranked docking pose for ciprofloxacin gave an energetic score of −7.6 kcal/mol (Fig. 11, A and B and Table S2). In this model, the C13 atom of the piperazine ring is located within 4.75 Å of the heme iron, which positions it well for possible oxidation by the activated iron oxime species (Fig. 11B). This conforms well to the proposed structures of the observed metabolites as they predict oxidation on this side of the piperazine ring (Fig. 6). Additionally, ciprofloxacin forms predicted interactions with A173, S236, M287, and F387, and the protoporphyrin IX ring system in the active site pocket, stabilizing it in an orientation for productive oxidation of the piperazine ring. While no hydrogen bond contacts are predicted in this binding pose, there are apparent pi–pi interactions between F387 and the quinolone ring of ciprofloxacin (Fig. 11B). In the case of ivacaftor, the two top-ranked poses were of approximately equal energy (−9.4 versus −9.3 kcal/mol) (Table S2), however the second energetically ranked pose reflected an optimal orientation with the tert-butylphenol group adjacent to the phenolic alcohol within 5.39 Å of the heme iron (Fig. 11, C and D), which agrees well with the metabolite data obtained for this drug (Fig. 7). Therefore, this pose was chosen for further analysis. In this pose, ivacaftor is predicted to form several contacts with CYP107S1 active site residues, including L89, Q172, T240, M287, and F387, as well as the protoporphyrin IX ring. In addition to hydrophobic contacts with the peptide backbone of Q172, the side chain hydroxyl is predicted to form a hydrogen bond with the amine hydrogen of the quinolone ring of ivacaftor and specific hydrophobic contacts with the catalytic threonine residue, T240. In this pose, the side chain of M287 interacts directly with the tert-butyl farthest from the phenolic alcohol, which may partially explain why oxidation is favored on the alternate tert-butyl group of the phenol ring. In contrast to ciprofloxacin and ivacaftor, which both contain an oxoquinolone core, the most energetically favorable pose of raloxifene bound to CYP107S1 resulted in an extended conformation that occupied the near entirety of the active site (Fig. 11, E and F). The calculated binding energy was determined to be −10.3 kcal/mol (Table S2). In this extended conformation, the benzothiophene moiety of the drug is oriented toward the mouth of the active site, farthest away from the heme iron, with the p-hydroxyphenol in a perpendicular orientation to the benzothiophene ring and interacting with residue Q172. The benzothiophene is anchored in this position through pi–pi interactions with the aromatic ring of H38 (Fig. 11F). The piperidine ring of raloxifene, the metabolic site of oxidation (Fig. 9), is oriented closest to the heme iron, with C3 of the piperidine ring of raloxifene calculated to be within 5.08 Å of the heme iron. Of the three drugs examined, raloxifene has the greatest number of interactions with active site amino acids, including E37, H38, L89, Q172, M287, L288, Y307, and F387, as well as the protoporphyrin IX ring, which may help explain its high affinity and rapid metabolism.Figure 11 Docking of ciprofloxacin, ivacaftor, and raloxifene to the CYP107S1 homology model.A, CYP107S1 active site cutaway (residues 62–79) (light gray) with the heme prosthetic group (red) and the docked structure of ciprofloxacin (light blue, color coded by heteroatom). B, docked ciprofloxacin-CYP107S1 active site close-up, indicating interacting residues (A173, magenta; S236, green; M287, orange; and F387, yellow). Interacting pseudo-bonds are shown in green, and distance from the nearest substrate carbon to the heme is shown in black. (The same color scheme is maintained in all subsequent panels). C, CYP107S1 active site cutaway with ivacaftor docked (ivacaftor show in steel blue, color coded by heteroatom). D, close-up of ivacaftor docked in the CYP107S1 active site, indicating interacting residues (L89, turquoise; Q172, salmon; T240, purple; and M287, orange). E, CYP107S1 active site cutaway with raloxifene docked (raloxifene shown in purple, color coded by heteroatom). F, close-up of raloxifene docked in the CYP107S1 active site. Pseudo-bonds were omitted for figure clarity, but interacting residues were included (E37, forest green; H38, teal; L89, turquoise; Q172, salmon; M287, orange; L288, olive green; Y307, lime green; and F387, yellow).

Discussion

The pathobiome terminology was adopted to describe dysbiosis triggered by impaired interactions between the host immune system and a subset of microorganisms, ultimately contributing to disease state in the host (7, 8, 53, 54). Analogous to the gut microbiome, the pathobiome evolves into an integral biotic environmental component of the host during infection, transforming its metabolic landscape (6, 55). The resilience of human bacterial pathogens to antibiotic therapy relies upon their intrinsic resistance mechanisms and their remarkable metabolic flexibility allowing rapid adaptation to new environments (56, 57, 58). Among the metabolic artillery featured in bacterial species, CYP enzymes have repeatedly demonstrated their ability to catalyze a variety of reactions with varied chemical substrates (e.g., cholesterol, camphor, deoxynivalenol, and hexabromocyclododecanes), either performing a detoxification function or biodegradation for sources of carbon for the bacterial cells (29, 30, 31). Therefore, it may be well conceivable for CYP enzymes from pathogenic bacteria to be able to metabolize drugs administered during an infection. To our knowledge, the closest evidence of a bacterial pathogen CYP enzyme metabolizing a drug is CYP124 from Mycobacterium tuberculosis and the lead drug candidate SQ109, a promising lead for tuberculosis treatment currently still under clinical trials (59, 60). Here, our original research work unveiled a novel and promiscuous CYP enzyme, CYP107S1 from the opportunistic human pathogen P. aeruginosa, capable of binding and metabolizing multiple clinically used drugs belonging to different drug classes.

The UV-visible spectral data of the soluble recombinant CYP107S1 (Fig. 1) were characteristic of a CYP enzyme, with no sign of P420 species. The submicromolar binding affinity measured for all three azole ligands (Fig. 3 and Table 1) denoted an active site capable of tightly accommodating a wider range of ligand sizes in comparison to the P. aeruginosa CYP168A1 isoform (35). Fluoroquinolones are among the most prescribed antibiotics for treating P. aeruginosa infections, with ciprofloxacin and levofloxacin representing the two most active fluoroquinolones inhibiting P. aeruginosa growth. However, due to their overuse, prevalence of fluoroquinolone resistance has increased in recent years (61, 62). Interestingly, the fluoroquinolone spectral titrations gave rise to contrasting shifts of the Soret band between ciprofloxacin, fleroxacin, and levofloxacin (Fig. 4, A and B; levofloxacin not shown, since no difference spectrum observed). Titrations of ciprofloxacin to CYP107S1 generated difference binding spectra analogous to the azole inhibitor drugs, suggesting the coordination of the piperazine nitrogen to the heme iron (Figs. 3 and 4A). In contrast, the presence of a methyl group on the piperazine nitrogen of fleroxacin entirely switched the binding mode, inducing a type I shift (Fig. 4B). In both cases, weak binding affinities were measured (Kd, app > 50 μM) (Table 1). Considering that a dose of 32.5 mg of ciprofloxacin dry powder administrated by inhalation in adult patients with CF resulted in a ciprofloxacin mean concentration in sputum of 100 μM (or up to 3 mM after 45 min from the oral inhalation) (63, 64) enhances the relevancy of these fluoroquinolone Kd, app values by underscoring the possibility of their direct metabolism in vivo. Subsequently, titrations of the drugs ivacaftor and raloxifene demonstrated tight type I binding for CYP107S1 with Kd, app values of 1.1 and 0.40 μM, respectively (Fig. 4, C and D and Table 1). Altogether, our binding data denoted a rather promiscuous bacterial CYP107S1 enzyme. In humans, the hepatic CYP3A4 isoform is considered the most promiscuous CYP enzyme and has been repeatedly documented for its allosteric (nonhyperbolic) binding and kinetic behaviors (65, 66, 67, 68, 69). Remarkably, for several ligands, the CYP107S1 binding isotherms best fit the Hill model, usually employed for modeling cooperativity (Table 1 and S1). Ketoconazole and econazole showed the highest degree of cooperativity to CYP107S1 with a Hill (n) coefficient of 1.5 and 2, respectively. In comparison, cooperative binding of ketoconazole to CYP3A4 was characterized by a Hill coefficient of 1.4 (70). The promiscuous and cooperative behavior of CYP107S1 reinforces the concept of a highly adaptable CYP-dependent detoxification pathway of P. aeruginosa.

Our ligand binding studies provided basic information on the interactions occurring between CYP107S1 and the different classes of drugs tested, but further understanding of the extent to which these drugs may be metabolized by CYP107S1 was ultimately needed. Our in vitro metabolism work revealed metabolism by CYP107S1 of all three fluoroquinolone drugs, ivacaftor, and raloxifene. Among the fluoroquinolone drugs, ciprofloxacin metabolism by CYP107S1 resulted in the greatest number of metabolites formed either by N-dealkylation, hydroxylation, or oxidation to oxo moieties (Table 2). This finding was somewhat unexpected from the type II binding mode observed for ciprofloxacin (Fig. 4A). While type II binding is often considered an indicator for CYP inhibition potential because of the direct coordination of the ligand to the heme iron atom, it is also known that CYP enzymes can significantly metabolize these types of ligands (46). Ketoconazole metabolism by CYP3A4 is a perfect illustration, with the major metabolic pathways involving oxidation and degradation of the imidazole and piperazine rings (71, 72). Thus, type II binding does not preclude metabolism.

To provide further insight into the structural implications of drug substrate interaction with the CYP107S1 active site, a homology model was constructed based on the pikromycin CYP hydroxylase PikC backbone. The overall fold was typical for a CYP enzyme and highly reminiscent of the P. aeruginosa CYP that we had previously characterized, CYP168A1 (Fig. 10A) (35). However, the active site volume calculated by CASTp (Fig. 10B) was significantly larger than for CYP168A1 (35). This suggests that CYP107S1 can accommodate much larger ligands than CYP168A1, or possibly even multiple ligands, as suggested by the cooperative binding response measured. Ligand docking with ciprofloxacin resulted in a thermodynamically stable structure (−7.6 kcal/mol, Table S2) with interactions with multiple active site residues, including A173, S236, M287, and F387 (Fig. 11, A and B). The distance to the heme iron (4.75 Å) from the C13 atom of the piperazine ring is optimal for substrate oxidation at this site. Together, our binding, structural elucidation, and docking data substantiated ciprofloxacin positioning in CYP107S1 active site with the piperazine ring hovering near the heme, allowing for its oxidation (Fig. 11B). NADPH-dependent formation of the desethylene ciprofloxacin (C1), a metabolite found in human plasma and urine samples (73), was observed in P. aeruginosa CYP107S1 incubations (Figs. 5 and 6 and Table 2). Multiple piperazinyl oxidation products were detected in CYP107S1 incubations of ciprofloxacin (Table 2), yet none matched the human oxociprofloxacin metabolite standard (Fig. S2), a major urinary and biliary metabolite (73, 74). On the other hand, only one metabolic pathway, via N-demethylation at the piperazine ring, was identified for fleroxacin and levofloxacin with the recombinant CYP107S1 (Figs. S3 and S4). N-demethylation is one of the two metabolic pathways described for fleroxacin and levofloxacin in humans, with the other biotransformation involving formation of an N-oxide metabolite (19, 75, 76, 77). Hence, overall, our fluoroquinolone CYP107S1 metabolism data unveiled, for the first-time, overlapping drug biotransformation reactions between the P. aeruginosa and the human CYP drug-metabolizing enzymes.

Further reinforcing this concept was our work on the in vitro metabolism of ivacaftor by CYP107S1. Ivacaftor is a small molecule potentiator drug for CF, a genetic disorder resulting from mutations of the CFTR gene and causing buildup of thick mucus in organs, especially the lungs (47, 78). The CF lung environment threatens the pulmonary microbiota balance and conduces to the prevalence of P. aeruginosa infection (14). Targeting the G551D gating mutation of the CFTR gene, ivacaftor is often prescribed with antibiotic medications (48). An interesting finding by Cho et al. (79) reported how ivacaftor enhanced ciprofloxacin antimicrobial activity against P. aeruginosa PAO1 strain, significantly reducing planktonic growth and biofilm formation compared to ciprofloxacin alone. Unfortunately, under clinical settings combination of ivacaftor with intensive antibiotic treatment, including oral ciprofloxacin and inhaled colistin, only transiently reduced density of the P. aeruginosa pathogen ultimately with perdurance of the lung infections (80). Binding to CYP107S1 with a low micromolar affinity, ivacaftor was metabolized to one major hydroxyl product, I1 (Fig. 7 and Table 3). The I1 hydroxyl metabolite matched the retention time and MS fragmentation of the hydroxymethyl ivacaftor standard, one of the two major human metabolites (49, 81). Ivacaftor is extensively metabolized in humans, primarily through the CYP3A pathway, with 22% of the dose eliminated as the hydroxymethyl metabolite (with one-sixth potency remaining) and 43% as an inactive carboxylic acid derivative formed from sequential methyl oxidation. Mean plasma concentration of ivacaftor in CF adults is about 4 μM, well above the EC90 of 0.7 μM and in the binding affinity range of the P. aeruginosa CYP107S1 (82). In our docking study, ivacaftor was found with the tert-butylphenol group adjacent to the phenolic alcohol with the C11 of ivacaftor within 5.39 Å of the heme iron (Fig. 11D). In addition to a number of van der Waals contacts formed with individual active site residues, including M287 and F387, the amine hydrogen of the quinolone ring of ivacaftor also forms a hydrogen bond with the alcohol of Q172, which may help explain the increased stability of this drug substrate in the CYP107S1 active site. For both ciprofloxacin and ivacaftor, the oxoquinolone core seems to form pi–pi stacking interactions with F387, suggesting that F387 may act as a gating residue in the CYP107S1 active site.

Drug repurposing has been a strategy taken by scientists to accelerate the discovery process (83, 84), the SERM drug class, originally developed as hormone therapies for the treatment of breast cancer, osteoporosis, or postmenopausal symptoms (85), has demonstrated broad spectrum antimicrobial activity in vitro and in vivo (38, 40, 41). To the best of our knowledge, clinical trials combining the SERM adjuvant with antibiotic treatment have yet to be proposed, probably because of the risk for estrogenic side effects, though our assessment of raloxifene binding and metabolism with P. aeruginosa CYP107S1 underscored its likelihood to be rapidly metabolized (Fig. 8). The major metabolite, R2, was formed by dehydrogenation at the piperidine ring (Fig. 9C). Like with the human CYP3A4 isoform (50, 86), metabolism of raloxifene led to formation of a dimer with an m/z of 943 and proposed chemical formula of C56H50N2O8S2 (Table 4 and Fig. 8G). From the m/z and our proposed structural elucidation (Fig. 9D), the R3 dimer metabolite would originate from reaction with the dehydrogenated raloxifene derivative and carbon-carbon coupling, and the piperidine ring would be the dimerization site according to the fragment ions of m/z 170 and 291. Interestingly, the dimerization site of raloxifene with CYP3A4 is on the opposite side of the molecule toward the aromatic phenol rings (50, 86), suggesting a completely different orientation of raloxifene in the active site compared to CYP107S1. Indeed, this observation is buttressed by the docking orientation of raloxifene in the CYP107S1 active site (Fig. 11, E and F). Raloxifene, a somewhat larger molecule than either ciprofloxacin or ivacaftor, is bound in an elongated conformation that extends from the heme iron all the way to F/G loop, near the mouth of the active site (Fig. 11, E and F). This positions C3 of the piperidine ring of raloxifene, the metabolic site of oxidation (Fig. 9), to be within 5.08 Å of the heme iron. Due to the extended conformation, raloxifene was found to form the largest number of interactions with active site residues (eight in total) and these likely contribute to its highly stable binding energy of −10.3 kcal/mol (Table S2). Interestingly, all three docked ligands were observed to form multiple interactions with M287 and F387, indicating the importance of these residues in general stabilization of ligands in the active site.

Our investigation into the propensity of the P. aeruginosa CYP107S1 enzyme to metabolize drugs revealed novel metabolic pathways of this human opportunistic pathogen. The promiscuity of CYP107S1, demonstrated with the metabolism of fluoroquinolone antibiotics, ivacaftor, and raloxifene, resembles that of the human hepatic CYP–metabolizing enzymes, particularly CYP3A4. In fact, this raises important questions about the potential for change in the “local” concentration of drugs at the site of infection and the ability to achieve drug efficacy in the presence of a pathogen. Yet much remains unknown about the Pseudomonas CYP enzymes and their role during infection, including their expression patterns and their endogenous functions in different stages of infection, and ultimately their role in biofilms. Arguably, our novel findings prompt for better understanding of the drug metabolism capability of the bacterial pathogenic CYP enzymes and of the rethinking of the pathobiome clinical impact on PK, and therefore, efficacy, of not only antibiotics, but all drugs prescribed during an active infection, especially those with targets near the site of that infection.

Experimental procedures

Materials

Clotrimazole and raloxifene hydrochloride were purchased from Sigma-Aldrich. Econazole was obtained from VWR International. Ketoconazole and the hydroxymethyl ivacaftor were from Toronto Research Chemicals. Ciprofloxacin hydrochloride hydrate was purchased from Thermo Fisher Scientific and the oxociprofloxacin metabolite standard from Santa Cruz Biotechnology. Levofloxacin, N-desmethyl levofloxacin, ivacaftor, and the desethylene ciprofloxacin metabolite standard were all obtained from Cayman Chemical. Fleroxacin was purchased from MedChemExpress. IPTG, PMSF, D-glucose-6-phosphate, and NADP+ were obtained from Alfa Aesar. Imidazole, the glucose-6-phosphate dehydrogenase, and the spinach Fdx and FdR were purchased from Sigma-Aldrich. All other chemicals were obtained from standard suppliers and were of reagent or analytical grade.

Construction of CYP107S1 expression vector and expression of the recombinant CYP107S1 protein

The NP_252021 protein is referenced by the National Center for Biotechnology Information as a putative CYP enzyme of 418 amino acids from P. aeruginosa PAO1 strain and is identified to the locus tag PA3331 in the Pseudomonas Genome Database (87). According to the CYP nomenclature, this CYP isoform is designated as CYP107S1 (88). Its amino acid sequence, starting with a valine, was first reverse translated to DNA employing the Sequence Manipulation Suite website (89). Then, using the GenScript GenSmart Codon Optimization tool (https://www.genscript.com/gensmart-free-gene-codon-optimization.html), CYP107S1 complementary DNA sequence was codon optimized for expression in E. coli. Finally, the codon-optimized DNA sequence was engineered with an ATG start codon at the 5′end and four histidine residues at the 3′end prior to the stop codon and inserted into a pUC57 vector using NdeI and HindIII restriction site sequences at the 5′ and 3′ ends of the CYP107S1 DNA coding sequence, respectively. After amplification of the pUC57-CYP107S1 plasmid, the CYP107S1-optimized complementary DNA insert was digested using the NdeI and HindIII restriction enzymes to allow its ligation into the pCWori+ CYP expression vector (90). The pCWori-CYP107S1 plasmid was used to transform E. coli-DH5α cells (Thermo Fisher Scientific) in preparation for the expression of the CYP107S1 protein.

For the CYP107S1 protein expression, a starter culture of the pCWori-CYP107S1 E. coli-DH5α cell in Luria-Bertani medium (containing 200 μg/ml ampicillin) was used to inoculate 4 × 1 l of Terrific broth medium in 2.8 l Fernbach flasks also supplemented with 200 μg/ml ampicillin. The bacterial cultures were incubated at 37 °C with agitation (250 rpm) until the absorbance reached 0.5 to 0.8 at 600 nm. Then, IPTG and 5-aminolevulinic acid were added at 0.5 mM final concentration each. The expression cultures were incubated for another 26 h at 25 °C using low agitation (180 rpm). The bacterial cells were collected by centrifugation at 3,400g and 4 °C for 40 min and processed for purification of the expressed CYP107S1 enzyme.

Purification of the (His)-tagged CYP107S1

The collected bacterial cell pellets were resuspended in 4 ml buffer A (50 mM Tris–HCl pH 7.5, 500 mM NaCl, 0.1 mM EDTA, and 1 mM PMSF) for each gram of bacterial cells. The bacterial cell suspension was then stirred for 30 min on ice in presence of lysozyme (0.4 mg/ml) and DNase I (0.025 mg/ml). Cell lysis was achieved on ice with a Branson sonicator set at 50% power and three 2-min bursts with 2 min resting time between each burst. Whole cells and cell debris were separated from the soluble CYP107S1 protein by ultracentrifugation at 100,000g and 4 °C for 60 min. The recombinant CYP107S1 protein in the supernatant fractions was then purified using fast protein liquid chromatography with a HisTrap-HP affinity column (5 ml) (Cytiva Life Sciences) previously equilibrated with buffer A. CYP107S1 was eluted with an imidazole gradient using the elution buffer B (50 mM Tris–HCl pH 7.5, 0.1 mM EDTA, 200 mM imidazole). Red-colored fractions, containing the bulk of the recombinant CYP107S1 protein, were pooled, and then dialyzed at 4 °C in 50 mM Tris–HCl pH 7.5, 0.1 mM EDTA and 0.1 mM DTT. The purity of the protein was analyzed by SDS-PAGE gel electrophoresis on a four to 15% Mini-Protean TGX precast gel in a Tris/glycine/SDS buffer (Bio-Rad). The gel was stained with the Bio-safe Coomassie G-250 solution from Bio-Rad, rinsed, and then captured with the iBright 1500 CL from Thermo Fisher Scientific. The concentration of the recombinant P450 was determined by UV-visible spectroscopy of the carbon monoxide-ferrous protein, with an extinction coefficient of ε = 91 mM−1 cm−1 at the wavelength of 450 nm (44). The spectral absorption characteristics of the CYP107S1 protein were obtained by UV-visible spectroscopy on a Varian Cary 60 UV-visible scanning spectrophotometer (Agilent).

Ligand Kd determination by optical difference spectroscopy

The binding selectivity of CYP107S1 for the antifungal azole agents, fluoroquinolones, ivacaftor, and raloxifene was determined using UV-visible spectroscopy. The spectra were acquired on a Varian Cary 50 Bio UV-visible scanning spectrophotometer (Agilent) between 350 and 500 nm. All ligand stock and working solutions were prepared in dimethyl sulfoxide (DMSO). Titrations of the antifungal azole compounds were carried out as previously described in Tooker et al. (35) using 1 μM CYP107S1 sample prepared in 100 mM potassium phosphate, pH 7.4 and DMSO as vehicle solvent for the reference cuvette. To account for the inherent absorbance properties of the fluoroquinolones, ivacaftor, and raloxifene, ligand titration was carried out using two (sample and reference) tandem cuvettes and by aliquoting at the minimum 1.3 ml of CYP107S1 sample in 100 mM potassium phosphate buffer, pH 7.4 in the first chamber and 1.3 ml buffer in the second chamber. The concentration of CYP107S1 in the tandem cuvettes was 4 μM for the fluoroquinolones and ivacaftor and 1 μM for raloxifene. Prior to the titration initiation, a baseline was recorded. Ligand working solutions were added incrementally to the first chamber of the sample cuvette containing CYP107S1 and to the second chamber of the reference cuvette containing only the buffer. The same volume of DMSO was added into the alternate chambers to correct for vehicle solvent effects. Spectra were recorded at varying ligand concentrations and calculated difference spectra were obtained by subtracting the reference spectrum to the corresponding ligand-bound protein spectrum. The absolute changes in absorbance deriving from a minimum of triplicate titrations were plotted as a function of ligand concentration and fitted via nonlinear regression to the best binding model (hyperbolic, quadratic, or Hill equation) using the GraphPad Prism software (version 10.0.3, GraphPad software, https://www.graphpad.com/). Statistical analysis for the best fit was done based on the Akaike information criterion method in GraphPad Prism (Table S1).

Recombinant CYP107S1 in vitro metabolism assays

In order to assess the potential for CYP107S1 to metabolize drugs, in vitro metabolism studies with the recombinant CYP107S1 were conducted in duplicate for the ciprofloxacin, fleroxacin, and levofloxacin antibiotics, the CFTR potentiator ivacaftor, and the SERM adjuvant raloxifene. These metabolism studies characterizing formation of potential metabolites are only qualitative assessment with often limited access for metabolite standards. Drugs were either dissolved in DMSO or acetonitrile with a maximum of 0.5% (v/v) solvent in the final incubation reactions, except for fleroxacin were 1% (v/v) acetonitrile was required due to its limited solubility. For ciprofloxacin (at 10 and 50 μM), fleroxacin (at 40 μM), levofloxacin (at 50 μM), and ivacaftor (at 10 μM), 1 μM CYP107S1 reactions in 100 mM potassium phosphate buffer (pH 7.4) and 3 mM MgCl2 were incubated with the spinach redox partners Fdx (10 μM) and FdR (0.1 U/ml). For raloxifene (at 10 μM), only 0.5 μM CYP107S1 with the spinach Fdx (5 μM) and FdR (0.05 U/ml) were employed. After an equilibration at 37 °C for 3 min, all reactions (200 μl) were initiated by the addition of a NADPH-regeneration system mix consisting of NADP+ (1 mM), D-glucose-6-phosphate (10 mM), and glucose-6-phosphate dehydrogenase (2 IU/ml). The reactions were incubated for up to 60 min at 37 °C under agitation and stopped by the addition of ice-cold methanol or acetonitrile. Incubations without the NADPH-regenerating system mix served as negative controls. Precipitated proteins were collected by centrifugation of the stopped samples for 20 min at 2,500g and 4 °C. Supernatants were transferred to HPLC vials for metabolite profiling and identification by LC-UV-MS analysis.

Analytical methods for the fluoroquinolone antibiotic metabolism studies

Analysis of the metabolism samples was performed on a Waters Acquity ultra-performance liquid chromatography system interfaced by a Waters Acquity diode array detector tailed to electrospray ionization with a Waters Xevo TQ-S micro tandem quadrupole mass spectrometer (Waters Corp). The diode array detector covered the range between 190 and 500 nm. The MS source parameters were as follows: 0.5 kV for capillary voltage, 150 °C for source temperature, 500 °C for desolvation temperature, and 900 l/h for desolvation gas flow. Positive ionization was employed for MRM and product ion scan modes. For ciprofloxacin and its metabolites, the following mass transitions (including collision energy, CE) were used for the MRM scan mode with a cone voltage (CV) of 40 V: 332 > 231 (CE = 36 V) for ciprofloxacin, 306 > 245 (CE = 20 V) for C1 or desethylene derivative, 346 > 245 (CE = 36 V) for C2, 348 > 261 (CE = 22 V) for C3, 348 > 245 (CE = 22 V) for C4, and 360 > 243 (CE = 36 V) for C5. The analytes were separated on a Waters Acquity BEH Phenyl column (1.7 μm, 2.1 mm × 100 mm) by flowing water and acetonitrile with 0.1% formic acid at 0.3 ml/min and using the following gradient: 2% organic held for 1 min, increased to 20% over 4 min, then increased to 98% over 2 min, and held at 98% for 1 min. For fleroxacin and the N-desmethyl metabolite, the following mass transitions were used for the MRM scan mode with a CV of 35 V: 370 > 269 (CE = 25 V) for fleroxacin and 356 > 312 (CE = 16 V) for N-desmethyl fleroxacin. Elution of fleroxacin and its N-desmethyl was performed on a Phenomenex Kinetex F5 column (1.7 μm, 2.1 mm × 100 mm) (Phenomenex) by flowing water and acetonitrile with 0.1% formic acid at 0.3 ml/min and using the following gradient: 2% organic held for 1 min, increased to 10% over 1.5 min, then increased to 30% over 3 min, increased at last to 98% over 1.5 min, and held at 98% for 1 min. For levofloxacin and the N-desmethyl levofloxacin, the following mass transitions were used for the MRM scan mode with a CV of 28 V and a CE of 17 V: 362 > 318 for levofloxacin and 348 > 304 for N-desmethyl levofloxacin. The analytes were eluted on a Waters Acquity BEH C18 column (1.7 μm, 2.1 mm × 100 mm) by flowing water and acetonitrile with 0.1% formic acid at 0.3 ml/min and using the following gradient: 2% organic held for 1 min, increased to 15% over 2 min, increased to 20% over 3 min and then 98% over 1 min, and finally held at 98% for 1 min. For product ion scans, CE was optimized to maximize ion fragmentation allowing structural elucidation.

Analytical method for ivacaftor metabolism study

The same Waters LC-MS instrumentation and MS source conditions described above were used for the study of ivacaftor metabolism, except for the capillary voltage set at 1 kV. Positive ionization was applied in all MS scan modes. The following mass transitions were used for the MRM scan mode with a CV of 30 V and a CE of 28 V: 393 > 172 for ivacaftor and 409 > 172 for I1 or hydroxymethyl ivacaftor. The analytes were separated on a Waters Acquity BEH C18 column (1.7 μm, 2.1 mm × 50 mm) by flowing water and acetonitrile with 0.1% formic acid at 0.4 ml/min and using the following gradient: 10% organic held for 0.5 min, increased to 98% over 4.5 min, and held at 98% for 1 min.

Analytical method for raloxifene metabolism study

The same Waters LC-UV-MS instrumentation and MS source conditions described for the fluoroquinolone analytical method was employed for raloxifene metabolism sample analysis. Multiple positive ionization scan types (MRM, product ion and full scan) were used to detect and characterize raloxifene and its metabolites. For the MRM scan mode, the following mass transitions were used with a CV of 40 V: 474 > 112 (CE = 30 V) for raloxifene, 406 > 121 (CE = 28 V) for R1 and 472 > 110 (CE = 28 V) for R2 and R3 metabolites. The analytes were separated on a Waters Acquity BEH C18 column (1.7 μm, 2.1 mm × 100 mm) by flowing water and acetonitrile with 0.1% formic acid at 0.4 ml/min and using the following gradient: 5% organic held for 0.5 min, increased to 55% over 7.5 min, then increased to 98% over 1 min, and held at 98% for 1.25 min.

CYP107S1 homology model construction

To explore the structural basis of CYP107S1’s interaction with ciprofloxacin, ivacaftor, and raloxifene, a homology model was constructed using UCSF MODELLER v 9.25 (91). In order to determine potential templates to use in the modelling process, a protein-PDB (https://www.rcsb.org/) BLAST search was conducted. Based on the BLAST search results, it was determined that bacterial CYP PikC protein (RCSB PDB accession code: 2WHW) was the closest match (42.1% identity), with a score of 299 bits (699) using the compositional matrix adjustment method. This resulted in 167/393 identities (42.1%), with 49% positives and 2% gaps (Fig. S5). Residues 398 (threonine) through 418 (glutamine) were deleted from the C terminus due to high threshold C-alpha RMSD (>5.0 Å) and limited overlap with the PikC sequence. The deletion of these residues did not affect the core fold of the CYP107S1 model. This adjustment resulted in a 43.6% sequence identity between the two sequences. The two sequences were then aligned using the Needleman––Wunsch global alignment algorithm in the UCSF Chimera v.15.1 multiline viewer (92). DTT, water, and other extraneous ligands were deleted from the PikC pdb structure file. The heme was retained for the homology model. Modeling was conducted by invoking a locally installed version of UCSF MODELLER v.9.25 (91) through the UCSF Chimera shell, with the number of output models set to 5, water molecules excluded, and the heme prosthetic group retained. Model #1.3 was selected for further study due to its optimal GA314 and zDOPE scores of 1.0 and −0.71, respectively. Additionally, the estimated RMSD (2.545 Å) and estimated overlap (3.5 Å) were superior to the other models produced.

Molecular docking of substrates to the heme active site of CYP107S1

Our structural understanding of the molecular interactions of CYP107S1 with drug substrate ligands was aided by molecular docking studies conducted using the CYP107S1 homology model and drug substrates in AutoDock Vina, v.1.1.2 (93). Ligands were obtained for docking by directly downloading the corresponding 3D structure in Structure Data Format file from the PubMed database (https://pubchem.ncbi.nlm.nih.gov/). Ciprofloxacin (CID 2764), ivacaftor (CID 16220172), and raloxifene (CID 5035) were all used for individual docking studies. For initial parameterization, ligand. Structure Data Format files were invoked in UCSF Chimera v. 15.1 and saved as PDB files. For ciprofloxacin, using AutoDock Tools v. 1.5.7, Gasteiger charges were added, 16 nonpolar hydrogens were merged, 12 aromatic carbons, and 4 rotatable bonds were detected and the TORSDOF function was set to 4. Subsequently, the file was saved in the PDBQT format. For the CYP107S1 homology model, polar hydrogens were added using AutoDock Tools v. 1.5.7, and the file was saved with a PDBQT extension. For ivacaftor, Gasteiger charges were added, 25 nonpolar hydrogens were merged, 15 aromatic carbons and 6 rotatable bonds were detected, and the TORSDOF function was set to 5. In the case of raloxifene, Gasteiger charges were added, 25 nonpolar hydrogens were merged, 20 aromatic carbons and 8 rotatable bonds were detected, and the TORSDOF function was set to 8 using AutoDock Tools v. 1.5.7.

For each ligand docking study, AutoDock Vina v.1.1.2 was invoked by using a script config file with the following docking grid parameters: center x-position = 19.797, center y-position = 9.312, center z-position = 40.09; size of x = 40, size of y = 46, size of z = 40, and exhaustiveness = 24. Files were designated “AD-output” and saved in the AutoDock Vina format (.pdbqt file extension). Docking results were visualized by using the ViewDockX function on the UCSF ChimeraX v. 1.7.1 interface. Hydrogen bonds were identified using the “Add H-bonds” function from the pull-down menu. van der Waals interactions were identified by using the “Find Contacts” function of the structure analysis submenu under the tools pull-down menu with the default constraints. Similarly, distances from the heme iron to the nearest substrate carbon were identified by using the “Distances” function of the structure analysis submenu.

Data availability

All data is made publicly available through the Journal of Biological Chemistry repository or may be obtained by contacting the corresponding author directly (jed.lampe@cuanschutz.edu).

Supporting information

This article contains Supporting information.

Conflict of interest

The authors declare that they have no conflicts of interest with the contents of this article.

Supporting information

Supporting infromation

CYP107S1-homology-model.pdb

Author contributions

S. E. K., B. C. T., and J. N. L. writing–review and editing; S. E. K. and J. N. L. writing–original draft; S. E. K. and J. N. L. visualization; S. E. K. and J. N. L. validation; S. E. K. methodology; S. E. K. and B. C. T. investigation; S. E. K. and J. N. L. formal analysis; S. E. K. and J. N. L. data curation; J. N. L. supervision; J. N. L. resources; J. N. L. project administration; J. N. L. funding acquisition; J. N. L. conceptualization.

Funding and additional information

This research work was generously funded by the 10.13039/100010174 University of Colorado , 10.13039/100009508 Skaggs School of Pharmacy and Pharmaceutical Sciences Start-up funds and 10.13039/100000060 NIAID grant R01 AI176245 (to J. N. L.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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