Computational Applications: Beauvericin from a Mycotoxin into a Humanized Drug.

Drug discovery was initially attributed to coincidence or experimental research. Historically, the traditional approaches were complex, lengthy, and expensive, entailing costly random screening of synthesized compounds or natural products coupled with in vivo validation largely depending on the availability of appropriate animal models. Currently, in silico modeling has become a vital tool for drug discovery and repurposing. Molecular docking and dynamic simulations are being used to find the best match between a ligand and a molecule, an approach that could help predict the biomolecular interactions between the drug and the target host. Beauvericin (BEA) is an emerging mycotoxin produced by the entomopathogenic fungus Beauveria bassiana, being originally studied for its potential use as a pesticide. BEA is now considered a molecule of interest for its possible use in diverse biotechnological applications in the pharmaceutical industry and medicine. In this manuscript, we provide an overview of the repurposing of BEA as a potential therapeutic agent for multiple diseases. Furthermore, considerable emphasis is given to the fundamental role of in silico techniques to (i) further investigate the activity spectrum of BEA, a secondary metabolite, and (ii) elucidate its mode of action.

ABC transporter inhibition by beauvericin partially overcomes drug resistance in Leishmania tropica.

Leishmaniasis is a neglected tropical disease infecting the world's poorest populations. Miltefosine (ML) remains the primary oral drug against the cutaneous form of leishmaniasis. The ATP-binding cassette (ABC) transporters are key players in the xenobiotic efflux, and their inhibition could enhance the therapeutic index. In this study, the ability of beauvericin (BEA) to overcome ABC transporter-mediated resistance of Leishmania tropica to ML was assessed. In addition, the transcription profile of genes involved in resistance acquisition to ML was inspected. Finally, we explored the efflux mechanism of the drug and inhibitor. The efficacy of ML against all developmental stages of L. tropica in the presence or absence of BEA was evaluated using an absolute quantification assay. The expression of resistance genes was evaluated, comparing susceptible and resistant strains. Finally, the mechanisms governing the interaction between the ABC transporter and its ligands were elucidated using molecular docking and dynamic simulation. Relative quantification showed that the expression of the ABCG sub-family is mostly modulated by ML. In this study, we used BEA to impede resistance of Leishmania tropica. The IC50 values, following BEA treatment, were significantly reduced from 30.83, 48.17, and 16.83 µM using ML to 8.14, 11.1, and 7.18 µM when using a combinatorial treatment (ML + BEA) against promastigotes, axenic amastigotes, and intracellular amastigotes, respectively. We also demonstrated a favorable BEA-binding enthalpy to L. tropica ABC transporter compared to ML. Our study revealed that BEA partially reverses the resistance development of L. tropica to ML by blocking the alternate ATP hydrolysis cycle.

Phenotypic and molecular characterization of multi-drug resistant Klebsiella spp. isolates recovered from clinical settings.

Klebsiella pneumoniae is a Gram-negative bacterium that colonizes the gastrointestinal tract and nasopharynx with many being linked to nosocomial infections. Extended-spectrum ß-lactamases (ESBL)-producing and carbapenem-resistant K. pneumoniae is recognized by the World Health Organization (WHO) as a critical public health concern. In this study, whole-genome sequencing (WGS) - based analysis was performed to understand the molecular epidemiology of multi-drug resistant Klebsiella spp. clinical isolates. Genome comparison, multi-locus sequence typing (MLST), pulsed-field gel electrophoresis (PFGE), and whole-genome-SNP-based phylogenetic analysis (wg-SNP) were used for in-depth molecular characterization. in silico typing was used to determine the resistance genes, virulence factors, Inc. groups, and capsular types. All except one isolate were non-susceptible to meropenem and 89% were non-susceptible to ertapenem and imipenem. blaNDM, blaOXA-48, and blaKPC were the detected carbapenemases with blaNDM-1 found in half of the sequenced genomes. Resistance to colistin was detected in one isolate and was linked to several genetic alterations in crrB, pmrB, and pmrC genes. The most common plasmid type was IncFIB followed by IncR, and the Type 3 fimbriae, encoded by the mrkABCDF operon, was conserved among all isolates. The most common sequence- (ST) and K-type detected were ST147 and K64. The prevelance and the genomic relatedness of ST147 isolates, as shown by the data from SNP-based phylogenetic analysis, PFGE, and genomic clustering, may be an outbreak marker. However, this can only be validated through a more comprehensive study encompassing a wider sampling scheme and over an extended timeframe.

Tracking SARS-CoV-2 variants during the 2023 flu season and beyond in Lebanon.

BACKGROUND: Early SARS-CoV-2 variant detection relies on testing and genomic surveillance. The Omicron variant (B.1.1.529) has quickly become the dominant type among the previous circulating variants worldwide. Several subvariants have emerged exhibiting greater infectivity and immune evasion. In this study we aimed at studying the prevalence of the Omicron subvariants during the flu season and beyond in Lebanon through genomic screening and at determining the overall standing and trajectory of the pandemic in the country. METHODS: A total of 155 SARS-CoV-2 RNA samples were sequenced, using Nanopore sequencing technology. RESULTS: Nanopore sequencing of 155 genomes revealed their distribution over 39 Omicron variants. XBB.1.5 (23.29 %) was the most common, followed by XBB.1.9.1 (10.96 %) and XBB.1.42 (7.5 %). The first batch collected between September and November 2022, included the BA.2.75.2, BA.5.2, BA.5.2.20, BA.5.2.25 and BQ.1.1.5 lineages. Between December 2022 and January 2023, those lineages were replaced by BA.2.75.5, BN.1, BN.1.4, BQ.1, BQ.1.1, BQ.1.1.23, CH.1.1, CM.4 and XBK. Starting February 2023, we observed a gradual emergence and dominance of the recombinant XBB and its sub-lineages (XBB.1, XBB.1.5, XBB.1.5.2, XBB.1.5.3, XBB.1.9, XBB.1.9.1, XBB.1.9.2, XBB.1.16, XBB.1.22 and XBB.1.42). CONCLUSIONS: The timely detection and characterization of SARS-CoV-2 variants is important to reduce transmission through established disease control measures and to avoid introductions into animal populations that could lead to serious public health implications.