Speakers

Title: "Soil spectroscopy: when spectroscopy and machine learning combine to solve agricultural soil diagnostic problems"

The field of agriculture faces a significant challenge as the demand for food production continues to increase alongside decreasing arable land. Soil health is among the main factors influencing agricultural production. The traditional soil analysis methods that are used to assess the quality of soil are costly and take time and require the use of chemicals. The introduction of soil spectroscopy that combines spectroscopic analysis and machine learning tools has revolutionized the way soils are diagnosed, providing valuable insights into soil properties. Soil spectroscopy is a non-destructive method of analyzing soil properties using electromagnetic radiation. This method involves the use of sensors that measure the energy absorbed/reflected by the soil, namely, when the data is extracted by machine learning models. The obtained results from soil spectroscopy provides valuable information about soil physic-chemical, and biological properties, including soil organic matter, pH, nutrient content, and texture.

In addition to that, the use of machine learning in soil spectroscopy makes it possible to analyze data in real-time. With traditional soil analysis methods, it can take days or even weeks to receive results. However, with ML models, soil data can be analyzed instantly, allowing farmers to make decisions quickly and take action to ensure optimal crop growth and production.

References:

Barra, I., et al., 2021a. Soil spectroscopy with the use of chemometrics, machine learning and pre-processing techniques in soil diagnosis: Recent advances–A review. Trends Anal. Chem. 135, 116166. https://doi.org/10.1016/j.trac.2020.116166

Barra, I., et al., 2022. The application of statistical preprocessing on spectral data does not always guarantee the improvement of the predictive quality of multivariate models: Case of soil spectroscopy applied to Moroccan soils. Vib. Spectrosc. 121, 103409. https://doi.org/10.1016/j.vibspec.2022.103409

Title: "Thymus satureioides: Toward a One Health Approach"

Lately, there has been growing recognition of the interconnectedness among human, animal, and environmental well-being. This comprehensive perspective is defined as the 'One Health Approach.' By considering these interconnections between the three realms, this approach strives to address health issues in a thorough and lasting manner. Natural compounds can provide safe, efficacious, and multi-mechanistic agents that are beneficial for all living organisms.

Zaitra, Thymus satureioides, is an aromatic plant with a long history of use in culinary and traditional medicine. The plant contains high amounts of minerals, amino acids, and phenolic compounds, and its essential oil is rich in thymol and carvacrol, among others. Zaitra extracts and essential oils have demonstrated a wide array of biological properties, including antioxidant, hepatoprotective, antiparasitic, antifungal, antimicrobial, antibiofilm, anti-quorum sensing, antiaging, antidiabetic, renoprotective, anticancer, anti-inflammatory, and insecticidal properties. In conclusion, Zaitra is a promising source of functional phytocompounds for all living organisms.

 Titre: "Applications des méthodes de la modélisation moléculaire dans la conception des molécules d’intérêt thérapeutique "

L’utilisation de méthodes et d’outils chémoinformatiques dans l’analyse et la comparaison de chimiothèques a montré son intérêt et son efficacité récemment. En effet, avec l’émergence de la pandémie de la COVID-19 le recours à ces méthodes est devenu incontournable. Ces méthodes constituent également une interface entre différentes champs disciplinaire regroupant la chimie, la biologie et l’informatique. Elle permet, grâce aux programmes informatiques, de rassembler des données d’analyses physicochimiques, biologiques et structurales dans une unité de lieu et de temps. Les modèles moléculaires qui en découlent font la synthèse des informations de ces différentes sources et participent ainsi à la compréhension des mécanismes d’interaction entre les petites molécules bioactives et leur cible biologique. La modélisation moléculaire fournit également des outils efficaces d’aide à la conception et à la sélection de nouvelles structures par la simulation de leurs interactions et par des prévisions quantitatives d’activité biologique. Dans cette conférence, nous allons donner un aperçu général sur des techniques employées dans la conception in silico des candidats de médicaments. Puis, nous allons présenter la stratégie employée pour l’utilisation des méthodes de modélisation moléculaire, notamment les méthodes QSAR, le docking moléculaire et la dynamique moléculaire. Et enfin, nous allons présenter et discuter quelques résultats obtenus lors de l’utilisation de ces méthodes dans l’évaluation et la proposition de nouveaux composés bioactifs d’origine naturelle et synthétique susceptible de manifester une activité prometteuse contre certaines maladies émergentes.

Title: ”Targeting PfGluPho as a Promising Strategy for Developing Selective Antimalarial Drugs”

Glucose-6-phosphate dehydrogenase-6-phosphogluconolactonase (PfGluPho) plays a pivotal role in the Pentose Phosphate Pathway (PPP) of Plasmodium falciparum, a crucial factor for its development inside the human body, as it serves as a major source of NADPH. Given the structural disparities between PfGluPho and its human homolog, it presents a promising role as a potential target for the development of selective antimalarial drugs against Malaria. Our research motivations have been focused on exploring various compounds described in literature that exhibit selective inhibitory effects on PfGluPho. Understanding the binding mode of these compounds is essential for identifying the molecular determinants responsible for their activity and paving the way for the design of novel antimalarial agents. Another key challenge in our research lies in the absence of an X-ray 3D structure of the Plasmodium falciparum enzyme form. To overcome this limitation, we have employed a combination of homology modeling techniques, molecular docking, and molecular dynamics simulations to generate a reliable 3D model. This 3D structure will potentially serve as a facilitator to design new and effective PfGluPho selective inhibitors. In present conference, we will summarize the diverse strategies and significant progress made by our research group in both the identification of potential inhibitors for PfGluPho and the elucidation of its 3D structure. These findings hold promise for the development of innovative and targeted antimalarial therapies, bringing us closer to combatting Malaria effectively.

Title: "In silico study of inhibitory effect of secondary metabolites against OmpA and OmpW in Klebsiella pneumoniae"

Antibiotics have undoubtedly played a crucial role in medical sciences. However, their excessive and irrational use by humans creates multidrug-resistant pathogens that cause difficult-to-treat infections. One of the virulence factors involved in antibiotic resistance is the presence of outer membrane proteins Omps. These proteins are found in Klebsiella pneumoniae,  causing nosocomial and community-acquired infections. The two proteins OmpA and OmpW, are small water-filled channels that perform various functions at the outer membrane level and play a role in antibiotic resistance. There are no known inhibitors explicitly targeting the OmpA and OmpW proteins in K. pneumoniae, and few identified inhibitors for these targets in other bacteria. The aim of this study is to identify new molecules from the SuperNatural 3.0 database exhibiting antibacterial activity, which could serve as potential inhibitors against OmpA and OmpW through an in silico approach. The selected molecules after a virtual screening against OmpA and OmpW, based on docking score, was further subjected to Lipinski’s rule of five and ADME/T properties. The six molecules selected belong to the class of aurones and can be considered potential inhibitors against OmpA and OmpW in K. pneumoniae. Molecular Dynamics and Experimental studies will validate their inhibitory effect and reveals the most potent against on K. pneumoniae.

Keywords: Klebsiella pneumoniae, OmpA, OmpW, molecular dockingVirtual screening, ADMET, Lipinski, aurones.

Title: "Title: Innovative antimicrobial strategy for the treatment of MDR bacterial infection"

The development of new approaches that adjuvant the scarcity of clinically relevant antibiotics for treatment of infections by multidrug-resistant Gram-negative bacteria is an urgent need. Previously, we showed that tamoxifen, an anti-cancer drug, presents very promising therapeutic efficacy in animal models of infection with MDR Gram negative bacteria such as Acinetobacter baumannii, Pseudomonas aeruginosa and Escherichia coli by modulating the migration of immune cells from bone marrow to blood and reducing the hyperinflammation [Miró-Canturri A, et al. Pharmaceuticals 2021], and metabolizing tamoxifen to three major metabolites (desmethyltamoxifen, hydroxytamoxifen and endoxifen) that exhibit high antibacterial activity against this A. baumannii and E. coli in vitro [Miró-Canturri A, et al. Antibiotics 2021]. However, the molecular target(s) of the tamoxifen metabolites (MET), remain to be determined.

Using a transposon library of a collection of 9504 random transposon mutants of A. baumannii ATCC 17978 strain, we select two mutants resistant to MET. To further determine whether MET affects their membrane structure, permeability and OMPs profile, we perform analysis by transmission electron microscopy, fluorescence assays, SDS-PAGE and qRT-PCR, respectively. We show that both mutant strains treated with MET presented lower membrane permeabilization and suffered morphological changes and reduction in OmpW expression. In order to confirm that OmpW is the target of MET, molecular docking of these metabolites against OmpW was performed. We find that MET binding to OmpW presented higher score. This data has been confirmed by the MET susceptibility profile of the mutant of A. baumannii deficient in OmpW which has presented MIC value 8-folds higher than the isogenic wt strain. In addition, we perform chequerboard and time-kill curve analyses to determine whether MET can synergize with clinically used antibiotic such as colistin. We find that MET is more synergistic with colistin against colistin-resistant A, baumannii during. Finally, and using mice, we determine the toxicity and pharmacokinetic parameters of MET.

Overall, our data showed that ompW might be involved in the mechanism of action of MET against A. baumannii and advanced our knowledge on the antimicrobial activity of MET as new therapeutic indication.

Title: "A Tale of Two 5-Lipoxygenase Activating Protein (FLAP) Inhibitors"

FLAP is responsible for regulating leukotriene (LT) biosynthesis. It is an integral membrane protein and acts as an anchor to activate 5-lipoxygenase (5-LO) and transfer arachidonic acid (AA) to 5-LO. Through this activation, AA is metabolized, and LT metabolites are produced. Inhibition of LT biosynthesis is a promising strategy for treating various types of inflammatory diseases. In this work, we will present the development story of quinazoline-4(3H)-one-7-carboxamides and 1,2,4-triazoles as FLAP antagonists which were discovered through a virtual screening (VS) study (IC50 values were identified as 0.87 and 2.18 μM) [1]. By further development studies, quinazolinone derivatives were designed to dually inhibit FLAP and soluble epoxide hydrolase (sEH) [2] and triazole derivatives were designed to block 5-LO product formation through binding to FLAP [3]. The structural modifications on the most potent quinazolinone derivative reached 0.70 μM for sEH and 2.70 μM for FLAP, and the most potent triazole derivative reached 1.15 μM for FLAP. These structures can become a more potent FLAP-antagonist via further developments by following the hints derived from structure-activity relationship data and computational analysis.

References:

[1] Olgac, A., et al., Discovery of Novel 5-Lipoxygenase-Activating Protein (FLAP) Inhibitors by Exploiting a Multistep Virtual Screening Protocol. Journal of Chemical Information and Modeling, 2020. 60(3): p. 1737-1748.

[2] Turanli, S., et al., Quinazoline-4(3H)-one-7-carboxamide Derivatives as Human Soluble Epoxide Hydrolase Inhibitors with Developable 5-Lipoxygenase Activating Protein Inhibition. ACS Omega, 2022. 8(41): p. 36354-36365.

[3] Olgac, A., Capan I., Dahlke P., et al., Substituted 1,2,4-triazoles as novel and selective inhibitors of leukotriene biosynthesis targeting 5-lipoxygenase-activating protein (FLAP). ACS Omega, 2023. (Just accepted)

Title: "Microbial catabolism of sterols: Processes to obtain the steroid tetracyclic nucleus"

The perhydrocyclopentanophenathrene nucleus is consisted of 17 carbon atoms, in three-hexa rings and one penta-ring: A, B, C and D. According to the junction of A/B, this chemical structure allows the occurrence of two steroid series, Trans and Cis configurations. In most of the natural steroid hormones and sterols, the A/B junction is in trans-configuration, resulting in a coplanar spatial structure of the four rings. In bile acids, the A/B junction is in cis configuration allowing the formation of two coplans. Due to intensive experimental researches, carried out worldwide, during the years 1960-1970, microbial cleavage of the lateral chain of naturally occurring sterols and functionalization of the steroid nucleus had become satisfactorily understood. Since that time, two major biotechnologies in the bioconversion domain of steroids have been established: (i) Selective cleavage of the side chain of sterols for obtaining industrially useful intermediates; (ii) Specific biotransformation functionalizing intermediate or increasing activity of a physiologically active molecule. The sterol side chain cleavage process is of great interest. It is selective, based on either: (i) Sterol nucleus chemical modification; (ii): Use of microbial mutant, deficient in at least one of the key enzymes of the nucleus rupture, Δ1-dehydrogenase and/or 9α-hydroxylase; (iii): Inhibition of at least one of these key enzymes. The intermediates thus obtained are industrially used for final production of pharmaceuticals, including hormones, contraceptive products, anti-cancers and fatting steroid molecules.

Title: "Early-life and health behaviour influences on lung function in early adulthood"

Rationale: Early-life exposures may influence lung function at different stages of the life course. However, the relative importance of characteristics at different stages of infancy and childhood are unclear.

Objectives: To examine the associations and relative importance of early-life events on lung function at age 24 years.

Methods: We followed 7545 children from the Avon Longitudinal Study of Parents and Children from birth to 24 years. Using previous knowledge, we classified an extensive list of putative risk factors for low lung function, covering sociodemographic, environmental, lifestyle and physiological characteristics, according to timing of exposure: 1) demographic, maternal and child; 2) perinatal; 3) postnatal; 4) early childhood; and 5) adolescence characteristics. Lung function measurements (forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), FEV1/FVC and forced expiratory flow at 25-75% of FVC) were standardised for sex, age and height. The proportion of the remaining variance explained by each characteristic was calculated. The association and relative importance (RI) of each characteristic for each lung function measure was estimated using linear regression, adjusted for other characteristics in the same and previous categories.

Results: Lower maternal perinatal body mass index (BMI), lower birthweight, lower lean mass and higher fat mass in childhood had the largest RI (0.5-7.7%) for decreased FVC. Having no siblings, lower birthweight, lower lean mass and higher fat mass were associated with decreased FEV1 (RI 0.5-4.6%). Higher lean mass and childhood asthma were associated with decreased FEV1/FVC (RI 0.6-0.8%).

Conclusions: Maternal perinatal BMI, birthweight, childhood lean and fat mass and early-onset asthma are the factors in infancy and childhood that have the greatest influence on early-adult lung function.

Title: "Metabolomics and Microbiome Profiling: The Key to Unlocking Precision Medicine for Breast Cancer and Hematopoietic Stem Cell Transplantation"

The intricate relationship between the human gut microbiota (GM) and our overall health cannot be ignored. Disruption of this delicate balance can lead to the onset and progression of various diseases, including breast cancer (BC)  and hematologic malignancies treated with allogeneic hematopoietic stem cell transplantation (allo-HSCT). Indeed, investigating gut microbiota composition and metabolite profiles can offer deep insights into the interaction between gut microbiota-host, response to treatment in BC and the developpment of graft versus host-disease (GvHD) following HSCT. Metagenomics and gut metabolomics have arisen as fascinating microbiome-targeted strategies that are considered to be  powerful tools for early diagnosis and treatment of different diseases. The present study was performed in order to investigate the cross-talk between the GM-host and BC or HSCT. First, we investigated changes in GM composition by NGS and fecal metabolic signature by NMR of 8 patients undergoing neoadjuvant chemotherapy. Then, we investigate changes in GM composition by NGS and fecal metabolic signature by untargeted GC-MS between allo-HSCT patients (n = 15) and healthy controls (n = 18). For the BC, we found lower relative abundances of Firmicutes, Proteobacteria, Roseburia, Faecalibacterium, Clostridium et Ruminococcus and a higher abundance of Bacteroidetes after chemotherapy treatment compared to patients before chemotherapy and metabolic profiles of feces showed upregulated amino acids, downregulated lactate and fumaric acid in patients under the second and third cycles compared with patients before treatment. While the GM of the HSCT patients was characterized by lower relative abundances of Actinobacteria, Firmicutes, Bacteroidetes and short-chain fatty acid-producing bacteria and a higher abundance of Proteobacteria phylum after allo-HSCT. Furthermore, the most notable altered metabolic pathways in the allo-HSCT patients vs controls included the TCA cycle; butanoate, propanoate, and pyruvate metabolisms; steroid biosynthesis; and glycolysis/gluconeogenesis. Overall, these data provide valuable insights into the interplay between the gut microbiota-host and breast cancer or allo-HSCT. The information obtained can be used to complement and improve clinical tools for disease monitoring, ultimately leading to enhanced precision medicine. By understanding the host-microbe associations on a deeper level, we can reveal individualized host-microbiome phenotypes that can be integrated with other ‘omics’ data sets to enhance precision medicine even further.