Molecular Networking for Drug Toxicities Studies: The Case of Hydroxychloroquine in COVID-19 Patients

Using drugs to treat COVID-19 symptoms may induce adverse effects and modify patient outcomes. These adverse events may be further aggravated in obese patients, who often present different illnesses such as metabolic-associated fatty liver disease. In Rennes University Hospital, several drug such as hydroxychloroquine (HCQ) have been used in the clinical trial HARMONICOV to treat COVID-19 patients, including obese patients. The aim of this study is to determine whether HCQ metabolism and hepatotoxicity are worsened in obese patients using an in vivo/in vitro approach. Liquid chromatography high resolution mass spectrometry in combination with untargeted screening and molecular networking were employed to study drug metabolism in vivo (patient’s plasma) and in vitro (HepaRG cells and RPTEC cells). In addition, HepaRG cells model were used to reproduce pathophysiological features of obese patient metabolism, i.e., in the condition of hepatic steatosis. The metabolic signature of HCQ was modified in HepaRG cells cultured under a steatosis condition and a new metabolite was detected (carboxychloroquine). The RPTEC model was found to produce only one metabolite. A higher cytotoxicity of HCQ was observed in HepaRG cells exposed to exogenous fatty acids, while neutral lipid accumulation (steatosis) was further enhanced in these cells. These in vitro data were compared with the biological parameters of 17 COVID-19 patients treated with HCQ included in the HARMONICOV cohort. Overall, our data suggest that steatosis may be a risk factor for altered drug metabolism and possibly toxicity of HCQ.

Boosting annotation in nutrimetabolomics by Feature-Based Molecular Networking: analytical and computational strategies applied to human urine samples from an untargeted LC-MS/MS based bilberry-blueberry intervention study.

Urine represents a challenging metabolite mixture to decipher. Yet, it contains valuable information on dietary intake patterns as typically investigated using randomized, single-blinded, intervention studies. This research demonstrates how the use of Feature-Based Molecular Networking in combination with public spectral libraries, further expanded with an 'In-house' library of metabolite spectra, improved the non-trivial annotation of metabolites occurring in human urine samples following bilberry and blueberry intake. Following this approach, 65 berry-related and human endogenous metabolites were annotated, increasing the annotation coverage by 72% compared to conventional annotation approaches. Furthermore, the structures of 15 additional metabolites were hypothesized by spectral analysis. Then, by leveraging the MzMine quantitative information, several molecular families of phase II (e.g., glucuronidated phenolics) and phase I (e.g., phenylpropionic acid and hydroxybenzoic acid molecular scaffolds) metabolism were identified by correlation analysis of postprandial kinetics, and the dietary impact of endogenous and exogenous metabolites following bilberry-blueberry intake was estimated.

Integrated metabolomic, molecular networking and genome mining analyses uncover novel angucyclines from Streptomyces sp. RO-S4 isolated from Bejaia Bay, Algeria

Multi-omic approaches have recently made big strides towards the effective exploration of microorganisms and accelerating the discovery of new bioactive compounds. We combined metabolomic, molecular networking, and genomic-based approaches to investigate the metabolic potential of the Streptomyces sp. RO-S4 strain isolated from the polluted waters of Bejaia Bay in Algeria. Antagonistic assays against methicillin-resistant Staphylococcus aureus with RO-S4 organic extracts showed an inhibition zone of 20 mm by the agar diffusion method, and its minimum inhibitory concentration was 16 μg/mL. A molecular network was created using GNPS and annotated through the comparison of MS/MS spectra against several databases. The predominant compounds in the RO-S4 extract belonged to the angucyclines family. Three compounds were annotated as known metabolites, while all the others were putatively new to Science. Notably, all compounds had fridamycin-like aglycones, and several of them had a lactonized D ring analogous to that of urdamycin L. The whole genome of Streptomyces RO-S4 was sequenced to identify the biosynthetic gene cluster (BGC) encoding for these angucyclines, which yielded a draft genome of 7,497,846 bp with 72.4% G+C content. Subsequently, a genome mining analysis revealed 19 putative biosynthetic gene clusters, including a grincamycin-like BGC with a high similarity to that of Streptomyces sp. CZN-748 previously reported to also produce mostly open fridamycin-like aglycones. As the ring-opening process leading to these compounds is still not defined, we performed comparative analysis with other angucycline BGCs and advanced some hypotheses to explain the ring-opening and lactone formation, possibly linked to the uncoupling between the activity of GcnE and GcnM homologues in the RO-S4 strain. The combination of metabolomic and genomic approaches greatly improved the interpretation of the metabolic potential of the RO-S4 strain.

18:0 Lyso PC Derived by Bioactivity-Based Molecular Networking from Lentil Mutant Lines and Its Effects on High-Fat Diet-Induced Obese Mice

Lentil (Lens culinaris; Fabaceae), one of the major pulse crops in the world, is an important source of proteins, prebiotics, lipids, and essential minerals as well as functional components such as flavonoids, polyphenols, and phenolic acids. To improve crop nutritional and medicinal traits, hybridization and mutation are widely used in plant breeding research. In this study, mutant lentil populations were generated by γ-irradiation for the development of new cultivars by inducing genetic diversity. Molecular networking via Global Natural Product Social Molecular Networking web platform and dipeptidyl peptide-IV inhibitor screening assay were utilized as tools for structure-based discovery of active components in active mutant lines selected among the lentil population. The bioactivity-based molecular networking analysis resulted in the annotation of the molecular class of phosphatidylcholine (PC) from the most active mutant line. Among PCs, 1-stearoyl-2-hydroxy-sn-glycero-3-phosphocholine (18:0 Lyso PC) was selected for further in vivo study of anti-obesity effect in a high-fat diet (HFD)-induced obese mouse model. The administration of 18:0 Lyso PC not only prevented body weight gain and decreased relative gonadal adipose tissue weight, but also attenuated the levels of total cholesterol, triglycerides, low-density lipoprotein cholesterol, and leptin in the sera of HFD-induced obese mice. Additionally, 18:0 Lyso PC treatment inhibited the increase of adipocyte area and crown-like structures in adipose tissue. Therefore, these results suggest that 18:0 Lyso PC is a potential compound to have protective effects against obesity, improving obese phenotype induced by HFD.

LC-QTOF-MS/MS Based Molecular Networking Approach for the Isolation of α-Glucosidase Inhibitors and Virucidal Agents from Coccinia grandis (L.) Voigt

Coccinia grandis or ivy gourd is an edible plant. Its leaves and fruits are used as vegetable in many countries. Many works on antidiabetic activity of a crude extract of C. grandis, i.e., in vitro, in vivo, and clinical trials studies, have been reported. Profiles of the antidiabetic compounds were previously proposed by using LC-MS or GC-MS. However, the compounds responsible for antidiabetic activity have rarely been isolated and characterized by analysis of 1D and 2D NMR data. In the present work, UHPLC-ESI-QTOF-MS/MS analysis and GNPS molecular networking were used to guide the isolation of α-glucosidase inhibitors from an extract of C. grandis leaves. Seven flavonoid glycosides including rutin (1), kaempferol 3-O-rutinoside (2) or nicotiflorin, kaempferol 3-O-robinobioside (3), quercetin 3-O-robinobioside (4), quercetin 3-O-β-D-apiofuranosyl-(1→2)-[α-L-rhamnopyranosyl-(1→6)]-β-D-glucopyranoside (5) or CTN-986, kaempferol 3-O-β-D-api-furanosyl-(1→2)-[α-L-rhamnopyranosyl-(1→6)]-β-D-glucopyranoside (6), and kaempferol 3-O-β-D-apiofuranosyl-(1→2)-[α-L-rhamnopyranosyl-(1→6)]-β-D-galactopyranoside (7) were isolated from C. grandis leaves. This is the first report of glycosides containing apiose sugar in the genus Coccinia. These glycosides exhibited remarkable α-glucosidase inhibitory activity, being 4.4–10.3 times more potent than acarbose. Moreover, they also displayed virucidal activity against influenza A virus H1N1, as revealed by the ASTM E1053-20 method.

Revisiting marine bioprospecting of tropical Indonesian macroalgae from West Timor

<p>Marine algae are an important and historically rich source of new marine-based natural products. This thesis describes the screening of 40 Indonesian macroalgal samples using liquid chromatography-mass spectrometry (LC-MS) based molecular networking, and the subsequent nuclear magnetic resonance (NMR)-guided isolation and structural elucidation of a 6-deoxy-6-aminoglycoglyrecolipid (60). Molecular networking was performed using LC-MS/MS data through the online Global Natural Product Social Molecular Networking (GNPS) platform directly from crude extracts. NMR spectroscopy-guided screening was also employed targeting unique peaks detected by 1H NMR to validate any hits from GNPS. Out of 40 macroalgae specimens collected from West Timor waters, six samples were prioritised by the molecular networking screening. Proton NMR revealed three specimens with significantly interesting peaks but only one specimen, Laurencia snackeyi was purified further, which yielded compound 60.</p>

Revisiting marine bioprospecting of tropical Indonesian macroalgae from West Timor

<p>Marine algae are an important and historically rich source of new marine-based natural products. This thesis describes the screening of 40 Indonesian macroalgal samples using liquid chromatography-mass spectrometry (LC-MS) based molecular networking, and the subsequent nuclear magnetic resonance (NMR)-guided isolation and structural elucidation of a 6-deoxy-6-aminoglycoglyrecolipid (60). Molecular networking was performed using LC-MS/MS data through the online Global Natural Product Social Molecular Networking (GNPS) platform directly from crude extracts. NMR spectroscopy-guided screening was also employed targeting unique peaks detected by 1H NMR to validate any hits from GNPS. Out of 40 macroalgae specimens collected from West Timor waters, six samples were prioritised by the molecular networking screening. Proton NMR revealed three specimens with significantly interesting peaks but only one specimen, Laurencia snackeyi was purified further, which yielded compound 60.</p>