PharmD Romain Pelletier
email: romain.pelletier@chu-rennes.fr

Brendan Le Daré

Pierre-Jean Ferron

Diane Le Bouedec

Angéline Kernalléguen

Isabelle Morel

Thomas Gicquel

Brendan Le Daré

Use of innovative, cross-disciplinary in vitro, in silico and in vivo approaches to characterize the metabolism of chloro-alpha-pyrrolidinovalerophenone (4-Cl-PVP)

Keywords: new psychoactive substances, 4-Cl-PVP, metabolism, molecular networking, HepaRG Cells, in silico

    Use of innovative, cross-disciplinary in vitro, in silico and in vivo approaches to characterize the metabolism of chloro-alpha-pyrrolidinovalerophenone (4-Cl-PVP)

Introduction

Drug addiction is a major public health issue and has been accentuated by the arrival of a variety of new psychoactive substances (NPS); the incidence of intoxication has increased worldwide [START_REF] Miotto | Clinical and pharmacological aspects of bath salt use: a review of the literature and case reports[END_REF][START_REF] Abuse | Synthetic Cathinones ("Bath Salts") DrugFacts[END_REF][START_REF] Maida | A Review of Synthetic Cathinone-Related Fatalities From 2017 to 2020[END_REF]. At the end of 2021, the European Monitoring Center for Drugs and Drug Addiction was monitoring 162 cathinones -the second most prevalent type of NPS, after synthetic cannabinoids (European Monitoring Centre for Drugs and Drug Addiction. 2022). Cathinones are emerging amphetamine derivatives of cathine (a compound present in the leaves of the African shrub khat) used for their euphoric and stimulating properties [START_REF] Kelly | Cathinone derivatives: a review of their chemistry, pharmacology and toxicology[END_REF][START_REF] Majchrzak | The newest cathinone derivatives as designer drugs: an analytical and toxicological review[END_REF]. In France, these drugs are commonly used during chemsex among "men who have sex with men" [START_REF] Batisse | Chemsex practice in France: An update in Addictovigilance data[END_REF]). However, the cathinones' toxic effects and metabolism have not been extensively characterized, and the absence of a cathinone consumption marker hinders the detection of cases of intoxication by toxicology laboratories. This is particularly the case for 4-chloro-alphapyrrolidinovalerophenone (4-Cl-PVP), for which no cases of intoxication have been reported in the scientific and medical literature.

In vitro, in vivo and (most recently) in silico approaches can be used to study the metabolism of NPSs.

The in vitro approaches include metabolic studies with human liver microsomes; this cell-free model contains membrane-bound drug metabolizing enzymes, such as cytochrome P450 (CYP) [START_REF] Richeval | In vitro Characterization of NPS Metabolites Produced by Human Liver Microsomes and the HepaRG Cell Line Using Liquid Chromatographyhigh Resolution Mass Spectrometry (LC-HRMS) Analysis: Application to Furanyl Fentanyl[END_REF][START_REF] Lopes | Metabolic Profile of Four Selected Cathinones in Microsome Incubations: Identification of Phase I and II Metabolites by Liquid Chromatography High Resolution Mass Spectrometry[END_REF]. In contrast, cell-based models (such as metabolically competent primary human hepatocytes (PHHs) and the differentiated HepaRG cell line) approximate physiological conditions; xenobiotics and their metabolites are thus exposed to cell barriers and intracellular components, and so the NPS' dynamics and toxicity in liver cells can be studied [START_REF] Diao | New Synthetic Cannabinoids Metabolism and Strategies to Best Identify Optimal Marker Metabolites[END_REF] Le Daré et al. 2020b). In particular, the HepaRG cell line stably expresses CYPs and uridine glucuronyl transferases (UGTs) and so metabolizes xenobiotics in much the same way as PHHs [START_REF] Aninat | Expression of cytochromes P450, conjugating enzymes and nuclear receptors in human hepatoma HepaRG cells[END_REF][START_REF] Quesnot | Production of chlorzoxazone glucuronides via cytochrome P4502E1 dependent and independent pathways in human hepatocytes[END_REF][START_REF] Hugbart | Non-oxidative ethanol metabolism in human hepatic cells in vitro: Involvement of uridine diphospho-glucuronosyltransferase 1A9 in ethylglucuronide production[END_REF]. We have previously used the HepaRG to study the metabolism of other NPSs [START_REF] Richeval | In vitro Characterization of NPS Metabolites Produced by Human Liver Microsomes and the HepaRG Cell Line Using Liquid Chromatographyhigh Resolution Mass Spectrometry (LC-HRMS) Analysis: Application to Furanyl Fentanyl[END_REF][START_REF] Allard | Application of a molecular networking approach for clinical and forensic toxicology exemplified in three cases involving 3-MeO-PCP, doxylamine, and chlormequat[END_REF]Gicquel et al. 2021a). In vivo approaches are considered to be the "gold standard" because they feature suitable consumption markers of drug intake (depending on the matrix analyzed) and take account of the pharmacokinetic properties of the metabolites' parent molecule. Thus, studies of NPS metabolism in human blood and ACCEPTED MANUSCRIPT / CLEAN COPY urine samples are still the most relevant [START_REF] Allard | Application of a molecular networking approach for clinical and forensic toxicology exemplified in three cases involving 3-MeO-PCP, doxylamine, and chlormequat[END_REF]Gicquel et al. 2021b;Ameline et al. 2019a, b;[START_REF] Allibe | Fatality involving ocfentanil documented by identification of metabolites[END_REF][START_REF] Pelletier | New psychoactive substance cocktail in an intensive care intoxication case elucidated by molecular networking[END_REF].

In order to make the best use of metabolic data obtained in vitro and in vivo, bioinformatics analyses of liquid chromatography-high resolution mass spectrometry (LC-HRMS) data are becoming increasingly valuable [START_REF] Seidl | CPExtract, a Software Tool for the Automated Tracer-Based Pathway Specific Screening of Secondary Metabolites in LC-HRMS Data[END_REF][START_REF] Klingberg | Developments in high-resolution mass spectrometric analyses of new psychoactive substances[END_REF]. For example, molecular networking facilitates the computational reprocessing of big data and is used increasingly in analytical and clinical toxicology labs [START_REF] Allard | Application of a molecular networking approach for clinical and forensic toxicology exemplified in three cases involving 3-MeO-PCP, doxylamine, and chlormequat[END_REF][START_REF] Allard | Comparative molecular networking analysis of a Rauwolfia plant powder and biological matrices in a fatal ingestion case[END_REF]Le Daré et al. 2020b). This powerful bioinformatics tool links spectrally related molecules by comparing their fragmentation spectra and analyzing mass differences between compounds that may correspond to known biotransformation reactions; it is therefore possible to identify metabolic pathways by information propagation from a known molecule (Le Daré et al. 2020a).

Lastly, in silico metabolism prediction software is the most recently developed technique. It provides access to metabolic but circumvents the drawbacks of cell culture or poor sample availability. In studies of metabolism, in silico systems incorporate models based on (i) the quantitative structure-activity relationship, which assumes that molecules with similar structures potentially exhibit similar metabolism properties, (ii) docking potential substrates into the active site of the enzyme, or (iii) quantum mechanical calculations used to predict reactivity [START_REF] Du | Recent Advances in QSAR and Their Applications in Predicting the Activities of Chemical Molecules, Peptides and Proteins for Drug Design[END_REF][START_REF] Gertrudes | Machine Learning Techniques and Drug Design[END_REF][START_REF] Kazmi | In silico approaches and tools for the prediction of drug metabolism and fate: A review[END_REF][START_REF] Tyzack | Computational methods and tools to predict cytochrome P450 metabolism for drug discovery[END_REF][START_REF] Trana | In silico prediction, LC-HRMS/MS analysis, and targeted/untargeted data-mining workflow for the profiling of phenylfentanyl in vitro metabolites[END_REF]). In addition to in vitro and in vivo approaches, the in silico approach confirms the level of evidence required for the identification of metabolites in a simple, rapid and cost-effective manner.

The primary objective of the present study was to elucidate the metabolism of 4-Cl-PVP by applying a combination of in vitro, in vivo and in silico techniques. This innovative approach was coupled with molecular networking, in order to thoroughly explore the metabolism of this emerging NPS and to determine the chemical structures of its likely metabolites. The secondary objective was to identify putative 4-Cl-PVP additional consumption markers for use in clinical practice.

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Material and methods

A CASE OF INTOXICATION WITH 4 -CL-PVP

A 49-year-old patient was admitted to the emergency department at Rennes University Hospital of (Rennes, France) with confusion and incoherent speech. The patient was known for drug abuse and schizoaffective disorders. The emergency services had observed a bag labelled "4-Cl-PVP", an electronic cigarette liquid and 1-propionyl-lysergic acid diethylamide (1P-LSD) pills among the patient's possessions. On admission to the intensive care unit (ICU), the patient presented with tachycardia (120 beats per minute) and arterial hypertension (140/80 mmHg). Standard laboratory assays did not reveal any cardiac, hepatic, renal, hemostatic or electrolyte disorders. Toxicological analyses of blood and urine samples were performed on admission and after 24 hours in hospital. The NPSs fluorometamphetamine (FMA), methylmethcathinone (MMC) and 4-Cl-PVP were identified in samples of the patient's biological fluids, along with methadone (prescribed for opioid use disorder), the anxiolytic diazepam and the antipsychotic clozapine and loxapine. The patient was discharged 48 hours after admission.

MATERIAL

William's E medium was purchased from Gibco (ThermoFisher Scientific, San Jose, CA, USA).

Penicillin-streptomycin was obtained from Life Technologies (Grand Island, NY, USA). Fetal bovine serum was purchased from Eurobio (Courtaboeuf, France). Glutamine was obtained from Life Technologies (Paisley, UK). Hydrocortisone hemisuccinate was purchased from SERB (Paris, France). Dimethylsulfoxide (DMSO), formic acid, ammonium acetate and insulin were obtained from Sigma-Aldrich (Saint Louis, MO, USA). LC-MS grade methanol, acetonitrile and water were obtained from Fisher Scientific UK (Loughborough, UK). The 4-Cl-PVP standard solution (1 mg/ml in methanol) was a gift from Dr Jean-Michel Gaulier (Lille University Hospital, Lille, France).

HEPARG CELL CULTURE

The HepaRG cell line (initially obtained from a liver tumor of a patient with hepatocarcinoma) was cultured as described previously [START_REF] Aninat | Expression of cytochromes P450, conjugating enzymes and nuclear receptors in human hepatoma HepaRG cells[END_REF]. Briefly, HepaRG cells were seeded at a density of 10 5 cells/well in 96-well plates and cultured for 2 weeks in William's culture medium E supplemented ACCEPTED MANUSCRIPT / CLEAN COPY with 10% fetal bovine serum, 50 U/mL penicillin, 50 μg/mL streptomycin, 5 µg/mL insulin, 2 mM glutamine, 50 μM hydrocortisone sodium hemisuccinate, and 2% DMSO. The cells were then cultured for an additional 2 weeks in the same medium supplemented with 2% DMSO, to induce cell differentiation into cholangiocyte-and hepatocyte-like cells; as described previously, these cells express liver-specific metabolic functions capable of producing phase I and II metabolites [START_REF] Richeval | In vitro Characterization of NPS Metabolites Produced by Human Liver Microsomes and the HepaRG Cell Line Using Liquid Chromatographyhigh Resolution Mass Spectrometry (LC-HRMS) Analysis: Application to Furanyl Fentanyl[END_REF]Le Daré et al. 2020b;Gicquel et al. 2021a;[START_REF] Ferron | Molecular Networking for Drug Toxicities Studies: The Case of Hydroxychloroquine in COVID-19 Patients[END_REF].

CELL TREATMENT WITH 4-CL-PVP Differentiated HepaRG cells were incubated for 8, 24 or 48 hours in 100 µL of medium containing 4-Cl-PVP at three different concentrations (1, 10, and 20 µM). Cell culture supernatants were recovered, frozen at -20°C, and thawed immediately before extraction for analysis. 96-well plates were incubated in 5% CO2 controlled atmosphere in a thermostatic chamber at 37°C, as described elsewhere (Le Daré et al. 2020b;Gicquel et al. 2021a). All in vitro experiments were performed in triplicate.

SAMPLE EXTRACTION

Two hundred microliters of each sample (cell supernatant or biological fluid) were supplemented with 500 μL of methanol and 300 μL of a 0.1 mol/L zinc sulfate solution for extraction. After evaporation of the supernatant, the residue was taken up in 200 μL of mobile phase and transferred to chromatographic vials for analysis using LC-HRMS (Le Daré et al. 2020b).

4-CL-PVP ASSAY BY LC-MS/MS

4-Cl-PVP concentrations were measured using liquid chromatography-tandem mass spectrometry (LC-MS/MS) on a Xevo TQ-XS quadrupole mass spectrometer with an electrospray ionization (ESI) source.

The instrument was coupled to a Waters Acquity Class-H Plus equipped with a quaternary pump system (Waters, Milford MA, USA) and an Acquity HSS C18 column (150 × 2 mm, 1.8 μm, Waters) during 15 min. The column was held at 40°C, and the autosampler was set to 15°C. Ions were detected in multiple reaction monitoring mode. The transitions (collision energies) monitored were m/z 266.1 → 125.0 and 195.1 (24/16 eV) for 4-Cl-PVP and 242.0 → 129.0 (26 eV) for the internal standard (ketamine-d4) (Supplemental data 1).

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LC-HRMS/MS ANALYSIS LC-HRMS was performed with an UltiMate 3000 pump coupled to a Q Exactive mass spectrometer (Thermo Scientific, San Jose, CA, USA) with a heated ESI source. The non-targeted LC-HRMS/MS screening method used to build the molecular network has been described elsewhere (Le Daré et al. 2020b[START_REF] Daré | In vivo and in vitro α-amanitin metabolism studies using molecular networking[END_REF]Gicquel et al. 2021a;[START_REF] Ferron | Molecular Networking for Drug Toxicities Studies: The Case of Hydroxychloroquine in COVID-19 Patients[END_REF]. Briefly, LC was performed on an Accucore Phenyl Hexyl (100 × 2.1 mm, 2.6 μm) column (Thermo Scientific) at 40°C, using an injection volume of 10 µL, an elution gradient, and a flow rate of 500 µL/min for 15 minutes. The orbitrap mass spectrometer operated in positive ESI mode, with the acquisition range of 100-700 m/z. Ion precursor selection was performed in "data-dependent" mode: the five most intense ions from the previous scan were selected for fragmentation ("top N of 5") (Supplemental data 2).

GENERATION OF MOLECULAR NETWORKS

The semi-quantitative approach to molecular network generation has been described elsewhere [START_REF] Allard | Application of a molecular networking approach for clinical and forensic toxicology exemplified in three cases involving 3-MeO-PCP, doxylamine, and chlormequat[END_REF][START_REF] Allard | Comparative molecular networking analysis of a Rauwolfia plant powder and biological matrices in a fatal ingestion case[END_REF]Le Daré et al. 2020b;Gicquel et al. 2021a). Briefly, spectral raw data (.raw format) were converted into an open MS format (.mzXML) and then preprocessed (deconvolution, deisotoping, alignment, gap-filling, and filtering) with MZmine 2. 4.1 software (mzmine.github.io). The single .mgf output file was then loaded on the Global Natural Products Social networking (GNPS) web platform (gnps.ucsd.edu), to generate the molecular network. Nodes represented the molecules and were linked and grouped into clusters when they were spectrally close. Biotransformation reactions were identified from the mass difference between molecules. Links between nodes were created when the cosine score was greater than 0.7. The molecular network was visualized using Cytoscape 3.8.0 software (San Diego, CA, USA). Nodes were labelled with the exact protonated mass (m/z), and the links between nodes were labelled with the exact mass shift. A color was assigned to each concentration, and the areas of different colors in each node semi-quantitatively represented the concentrations of the corresponding compound in each condition, as described previously (Le Daré et al. 2020b;Gicquel et al. 2021a) (Supplemental data 3).

STRUCTURAL IDENTIFICATION ON THE BASIS OF THE LC-HRMS/MS DATA

The LC-HRMS/MS technique enabled mass determination to four digits after the decimal point. The main fragments provided structural information about the corresponding parent molecule. Nodes were ACCEPTED MANUSCRIPT / CLEAN COPY annotated by spectral matching using SIRIUS 4.0 software (bio.informatik.uni-jena.de/Sirius) and information propagation (identified nodes were used as starting points to identify other nodes in the same cluster), as described previously [START_REF] Dührkop | SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information[END_REF].

IN

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Results

IN VITRO METABOLIC ANALYSES USING MOLECULAR NETWORKS

To understand the kinetics of 4-Cl-PVP's metabolism, we incubated the drug (1, 10 or 20 µM) with differentiated HepaRG cells for 0, 8, 24 or 48 hours. No cytotoxicity effects were observed under these conditions (Supplemental data 4). To increase the number of metabolites produced, the highest concentration (20 µM) was therefore chosen for in vitro metabolism study. Analysis of the culture supernatant at different time points provided a multimatrix molecular network that displayed the acquired MS/MS data (Figure 1). As the nodes were clustered together according to their MS/MS spectral similarities, we found a cluster in which 4-Cl-PVP was linked to structurally related compounds (Figure 1). The mass differences between nodes (shown on the links between nodes) were found to correspond 1). between isomers (such as hydroxylated compounds) in particular (Figure 2A-B). We used this approach to determine whether or not phase II biotransformation reactions (exemplified by glucuronidation) had taken place (Figure 2D).

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Taken as a whole, these results (i) provided a good level of understanding of the kinetics of 4-Cl-PVP metabolism in vitro, (ii) suggested that compounds structurally related to 4-Cl-PVP were indeed metabolites, and (iii) confirmed that differentiated HepaRG cells constitute a relevant model for studying cathinone metabolism in vitro [START_REF] Wagmann | How to Study the Metabolism of New Psychoactive Substances for the Purpose of Toxicological Screenings-A Follow-Up Study Comparing Pooled Human Liver S9, HepaRG Cells, and Zebrafish Larvae[END_REF].

ACCEPTED MANUSCRIPT / CLEAN COPY AN IN VIVO METABOLIC STUDY OF HUMAN BIOLOGICAL SAMPLES

We studied the in vivo metabolism 4-Cl-PVP in human blood and urine samples in a context of intoxication. The urine and plasma 4-Cl-PVP concentrations were respectively 34.4 and 1018.6 µg/L on admission and 7.4 and 213.1 µg/L 24 hours after admission. Using molecular networking, we found 13 compounds structurally related to 4-Cl-PVP and with mass shifts that might correspond to biotransformations -making them putative metabolites (Figure 4, Table 1). This approach enabled the semiquantitative visualization of how the molecules were distributed in the two matrices. All the potential metabolites were present at higher concentrations in urine samples than in blood samples. 4).

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ACCEPTED MANUSCRIPT / CLEAN COPY SUMMARY OF THE IN VITRO, IN VIVO AND IN SILICO DATA

Our present in vitro, in vivo and in silico data and the literature data on 4-Cl-PVP metabolism are summarized in Table 1 [START_REF] Lopes | Metabolic Profile of Four Selected Cathinones in Microsome Incubations: Identification of Phase I and II Metabolites by Liquid Chromatography High Resolution Mass Spectrometry[END_REF]. Isomers such as hydroxylated-4-Cl-PVP-derivatives were separated and labelled by letters, as a function of the RT. As observed previously, we found that (i) in vitro and human sample analyses gave similar results, and (ii) the metabolites identified in vitro were found much more frequently in the patient's urine samples than in the patient's blood samples (Gicquel et al. 2021a). This comparison highlighted interesting 4-Cl-PVP consumption markers because the molecules were found in the various models and had a high intensity in HRMS (ions with m/z 282.1254 and m/z 298.1204). We also summarize these putative metabolites within possible metabolism pathways within Figure 5.

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Discussion

The objectives of the study were (i) to elucidate the metabolism of 4-Cl-PVP by applying a combination of in vitro, in vivo and in silico techniques, and (ii) to was to identify putative 4-Cl-PVP additional consumption markers for use in clinical practice.

Using a combination of in vitro, in vivo and in silico approaches, we identified 15 potential metabolites of 4-Cl-PVP, 10 of which had not been described previously. Our study of the kinetics of metabolism in vitro provided valuable insights into the nodes linked to 4-Cl-PVP. The concomitant metabolism of 4-Cl-PVP and the appearance of structurally related molecules suggests strongly that the latter were metabolites -none of which were detected in the culture medium in the absence of 4-Cl-PVP.

Furthermore, the putative intermediate and final metabolites provide a better understanding of the steps in the metabolism of 4-Cl-PVP. Nevertheless, in the absence of commercial standards for each metabolite, the fragments analysis with SIRIUS 4.0 software yielded putative structures rather than proven chemical structures [START_REF] Schymanski | Identifying small molecules via high resolution mass spectrometry: communicating confidence[END_REF].

The comparison of in vitro data with in vivo data was of particular interest. Indeed, several in vivo metabolites were found in vitro, suggesting that our cellular model is relevant and that we can have a high degree of confidence in these putative metabolites. Moreover, the good ionization response of the ions m/z 282.1254 and m/z 298.1204 (evidenced by the large nodes obtained in the molecular networks in vitro and in vivo) suggests that mass spectrometry detection is sensitive. These elements prompt us to suggest that both compounds are 4-Cl-PVP additional consumption markers. We also identified many isomers (especially hydroxylated derivatives) on the basis of differences in the fragmentation spectrum and RT. However, further studies of additional biological samples would be needed to discriminate between the metabolites found in cell models but not in our patient.

In vivo, the analysis of urine samples allowed us to identify a number of glucuronoconjugated 4-Cl-PVP derivatives (m/z 456.1418, m/z 458.1574, m/z 472.1366, m/z 474.1524 and m/z 490.1472); these derivatives appeared later than the phase I metabolites and thus extended the detection time window for this NPS. This hypothesis is also supported by the fact that a greater number of phase II metabolites ACCEPTED MANUSCRIPT / CLEAN COPY are detected in in vivo samples than in in vitro samples. Hence, these experiments provided valuable pharmacokinetic data on 4-Cl-PVP and its metabolites and showed that urine is the matrix of choice when seeking to diagnose 4-Cl-PVP intoxication. In this context, the analysis of a serial urine samples would provide precise data on the detection time windows for these compounds. In addition to identifying these consumption markers, we quantified 4-Cl-PVP in human blood and urine samples at two different timepoints (upon admission to the ICU and 24 hours after) for the first time and thus were able to estimate toxic concentrations of 4-Cl-PVP in these matrices.

Of the 31 metabolites predicted in silico, only hydroxylated (m/z 282.1254) and glucuronoderivated metabolites (m/z 458.1575) were found in the in vitro and in vivo models. However, the BT3 software predicts sulfoconjugate derivatives not found in humans and in vitro, while these derivatives have already been detected for other molecules by the molecular network [START_REF] Allard | Comparative molecular networking analysis of a Rauwolfia plant powder and biological matrices in a fatal ingestion case[END_REF]. Also, the prediction of cytochrome by the BT3 software seems to us sometimes erroneous, it is in particular the case for the predicted metabolite m/z 268.1468 probably reduced by an alcohol dehydrogenase rather than the CYP2C9. Thus, metabolism prediction software appears to have little relevance for cathinone derivatives, as previously described by [START_REF] Carlier | 3F-α-pyrrolydinovalerophenone (3F-α-PVP) in vitro human metabolism: Multiple in silico predictions to assist in LC-HRMS/MS analysis and targeted/untargeted data mining[END_REF] for 3-fluoro-alpha-pyrrolidinovalerophenone (3-F-αPVP) [START_REF] Carlier | 3F-α-pyrrolydinovalerophenone (3F-α-PVP) in vitro human metabolism: Multiple in silico predictions to assist in LC-HRMS/MS analysis and targeted/untargeted data mining[END_REF]. More broadly, these observations call for caution in the interpretation of metabolic data generated by these software tools. Given that these software tools feature machine learning, one can assume that the limited amount of data on the metabolism of these drugs prevents the accurate prediction of biotransformation reactions from quantitative structure-activity relationships.

Thanks to the use of cross-disciplinary approaches, better knowledge of the metabolism of these molecules might help to refine the in silico predictions.

Lastly, a comparison of our metabolic results for 4-Cl-PVP with the literature data confirmed the presence of four metabolites previously described by Lopez et al. (namely M3 (m/z 268.1462), M5d (m/z 282.1254), M6 (m/z 284.1411) and M12a (m/z 458.1574); Table 1) [START_REF] Lopes | Metabolic Profile of Four Selected Cathinones in Microsome Incubations: Identification of Phase I and II Metabolites by Liquid Chromatography High Resolution Mass Spectrometry[END_REF]. Interestingly, the 4-Cl-PVP biotransformation reactions identified in our study (dehydrogenation, oxidation, oxidation + dehydrogenation, hydrolysis, carboxylation, and glucuronoconjugation) were similar to those reported for other PVP derivatives [START_REF] Manier | Different in vitro and in vivo tools for elucidating the human metabolism of alpha-cathinone-derived drugs of abuse[END_REF][START_REF] Carlier | Pyrrolidinyl Synthetic Cathinones α-PHP and 4F-α-PVP Metabolite Profiling Using Human Hepatocyte Incubations[END_REF][START_REF] Carlier | 3F-α-pyrrolydinovalerophenone (3F-α-PVP) in vitro human metabolism: Multiple in silico predictions to assist in LC-HRMS/MS analysis and targeted/untargeted data mining[END_REF].

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Conclusion

By using in vitro, in silico and in vivo models and a molecular networking approach, we identified 15 putative 4-Cl-PVP metabolites -10 of which had not been described previously. These metabolites might be 4-Cl-PVP additional consumption markers with value for hospital toxicology labs. The high intensity of the hydroxy-4-Cl-PVP (m/z 282.1254) and dihydroxy-4-Cl-PVP (m/z 298.1204) metabolites in in vivo and in vitro matrices suggests that these two compounds are particularly relevant markers of this NPS. Their inclusion in mass spectrometry identification databases might allow the specific, sensitive detection of 4-Cl-PVP intoxications over a broader time window than for the parent molecule alone.

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Figure 1 :

 1 Figure 1: Visualization of in vitro 4-Cl-PVP metabolism in differentiated HepaRG cells, using molecular networking. HepaRG cells were incubated with 4-Cl-PVP (20 μM) for 0 (control), 8, 24 and 48 h: the corresponding results are depicted in white, pink, orange, and red, respectively. Nodes are labeled with the exact protonated mass (m/z), and the links are labeled with the exact mass shift. Candidate 4-Cl-PVP metabolites are linked to the corresponding nodes. RT: retention time (in minutes).

Figure 2 .

 2 Figure 2. Structure elucidation of 4-Cl-PVP (A), Hydroxy-4-Cl-PVP (B), Dihydroxy-4-Cl-PVP (C) and Hydroxy-4-Cl-PVP glucuronide (D) using fragmentation spectrum.

Figure 3 :

 3 Figure 3: In silico prediction of 4-Cl-PVP metabolites by GLORYx and BT3 programs, showing the molecular mass [M+H]+, the confidence score (GLORYx), and the cytochromes most likely to be involved in biotransformation reactions (BT3 suggested 29 metabolites, while GLORYx suggested only 5).

Figure 4 :

 4 Figure 4: Molecular network of metabolites of 4-Cl-PVP in vivo in urine (yellow) and peripheral blood (red) on admission. Nodes are labeled with the exact protonated mass (m/z), and the links are labeled with the exact mass shift. Candidate 4-Cl-PVP metabolites are linked to the corresponding nodes. RT: retention time (in minutes). Isomers with different retention times are labelled with letters (a and b) to distinguish them.

Figure 5

 5 Figure 5 Proposed metabolites of 4-Cl-PVP structures and postulated biotransformation combining both human and in vitro studies

  /nerdd.univie.ac.at/gloryx/) freeware were used to compare the metabolites identified in vivo and in vitro. These programs predict the phase I and II metabolites of molecules in a .sdf file on the basis of their site of metabolism, CYP activity, and phase II metabolism rules (de Bruyn[START_REF] De Bruyn Kops | GLORYx: Prediction of the Metabolites Resulting from Phase 1 and Phase 2 Biotransformations of Xenobiotics[END_REF][START_REF] Wishart | BioTransformer 3.0-a web server for accurately predicting metabolic transformation products[END_REF]. Metabolism studies with BT3 were designed with the modules for phase I transformations

	SILICO METABOLIC ANALYSES
	Open-access	Biotransformer	3.0	(BT3)	(https://biotransformer.ca)	and	GLORYx
	(https:/

(CYP 1A, 2A, 2B, 2C, 2D, 2E, and 3A4) and Phase II transformations (glucuronidation and sulfation) using « Custom Human Multi-Step Transformation (Multibio)" module. This approach also enables the prediction of the cytochrome involved in biotransformations. The GLORYx program simultaneously predicts phase I and phase II metabolites and gives a predictive score ranging from 0 to 1. Only metabolites with a predictive score greater than or equal to 0.3 were taken into consideration in the present study

[START_REF] Carlier | 3F-α-pyrrolydinovalerophenone (3F-α-PVP) in vitro human metabolism: Multiple in silico predictions to assist in LC-HRMS/MS analysis and targeted/untargeted data mining[END_REF]

).

  The most intensely detected putative metabolites were the ions m/z 282.1254 (monohydroxylated derivatives) and m/z 298.1204 (dihydroxylated derivatives). We confirmed the presence of five putative

metabolites predicted by our in vitro or in silico models: m/z 280.1097 (RT: 8.4 min), m/z 282.1254 (RT: 7.0 min), m/z 282.125 (RT: 7.8 min), m/z 314.1153 (RT: 6.0 min), and m/z 298.1204 (RT: 6.2 min). We also identified glucuronoconjugated phase II metabolites, as highlighted by a mass shift of 176.033. Using information propagation, we suggest that the ions m/z 456.1418, m/z 458.1574, m/z 472.1366, m/z 474.1524 and m/z 490.1472 are glucuronoconjugated derivatives of the ions found in vitro with m/z 280.1097, m/z 282.1254, m/z 296.1047, m/z 298.1204, m/z 300.1367 and m/z 314.1153, respectively (Figure

Table 1 .

 1 Putative metabolites of 4-Cl-PVP found here in vitro, in vivo, and in silico, and in the literature. NA: not applicable; x = presence of the molecule. Metabolite isomers with different retention times are labeled with letters to distinguish them.

	In vitro	In vivo	In silico	Reference

Acknowledgments

This project was support by financial allowance "Défi Scientifique" Université Rennes 1.

The authors thank David Fraser PhD (Biotech Communication SARL, Ploudalmezeau, France) for copyediting assistance and Bernard Fromenty (NuMeCan Institute) for his helpful contribution.

Declarations Competing interests

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Ethical standards

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of University Hospital of Rennes.

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