Project description:Dataset used for biochemometric analyses on the extract and fractions of Rosmarinus officinalis (Salvia rosmarinus) tested against MRSA.
Project description:The aqueous extract of yerba mate, a South American tea beverage made from Ilex paraguariensis leaves, has demonstrated bactericidal and inhibitory activity against bacterial pathogens, including methicillin-resistant Staphylococcus aureus (MRSA). The gas chromatography-mass spectrometry (GC-MS) analysis of two unique fractions of yerba mate aqueous extract revealed 8 identifiable small molecules in those fractions with antimicrobial activity. For a more comprehensive analysis, a data analysis pipeline was assembled to prioritize compounds for antimicrobial testing against both MRSA and methicillin-sensitive S. aureus using forty-two unique fractions of the tea extract that were generated in duplicate, assayed for activity, and analyzed with GC-MS. As validation of our automated analysis, we checked our predicted active compounds for activity in literature references and with used authentic standards to test for antimicrobial activity. 3,4-dihydroxybenzaldehyde showed the most antibacterial activity against MRSA at low concentrations in our bioassays. In addition, quinic acid and quercetin were identified using random forests analysis and 5-hydroxy pipecolic acid was identified using linear discriminant analysis. We additionally also generated a ranked list of unidentified compounds that may contribute to the antimicrobial activity of yerba mate against MRSA. Here we utilized GC-MS data to implement an automated analysis that resulted in a ranked list of compounds that likely contribute to the antimicrobial activity of aqueous yerba mate extract against MRSA.
Project description:A strategy for the high-throughput screening of a peptide nucleic acid (PNA) encoded peptide library to allow the identification of MRSA and MSSA selective peptides including AMPs. This novel screening approach allows simultaneous screening of cell selective peptides with different uptake mechanisms including lytic peptides and non-lytic CPPs. MRSA and MSSA were incubated with Library-18 (50 uM; corresponding to 39 nM of each library member) under short incubation times (30 min) to ensure collection of both live and apoptotic cells, which allowed selection of lytic peptides as well as non-lytic CPPs. Incubation was followed by washing and lysis and the intracellular and membrane associated library members were extracted and purified by filter centrifugation (between 3,000 and 10,000 Da). The extracted PNA tags were hybridized onto custom designed microarrays. Each microarray consisted of 4 sub-arrays of 44,000 features each with 33 replicates of each oligonucleotide complementary to each member of the library as well as 1232 non-coding negative controls. Microarray scanning and data analysis (BlueFuse, BlueGenome) was used to extract the intensity of the FAM label, thereby giving the relative amount of PNA hybridized to each spot and the identity of the peptide.
Project description:Antimicrobial resistance (AMR) is widely acknowledged as one of the most serious public health threats facing the world, yet the private sector finds it challenging to generate much-needed medicines. As an alternative discovery approach, a small array of diarylimidazoles was screened against the ESKAPE pathogens and the results made publicly available through the Open Source Antibiotics (OSA) consortium. Of the 18 compounds tested (at 32 μg/mL), 15 showed >90% growth inhibition activity against MRSA alone. In the subsequent hit-to-lead optimization of this chemotype, 147 new heterocyclic compounds containing the diarylimidazole and other core motifs were synthesized, tested against MRSA and structure-activity relationships identified. While potent, these compounds have moderate to high clearance rates and some associated toxicity. The best overall balance of parameters was found with OSA_975, a compound with good potency and solubility and slow clearance in rat hepatocytes. In this study, we used multiplexed kinase inhibitor beads/mass spectrometry (MIB/MS) to study the human molecular targets of these phenotypically active compounds.
2024-01-26 | PXD040208 | Pride
Project description:Dataset used for 3q29 Project samples (n=46) analyses
Project description:Methicillin-resistant Staphylococcus aureus (MRSA) is a major human pathogen in both community and health care settings, which causes a wide range of infections. Its resistance to β-lactam antibiotics and methicillin in particular, greatly complicates treatment options and success rate due to the limited number of antibiotics with activity against MRSA. To further the development of alternative therapeutics, the mechanisms that mediate antibiotic resistance in MRSA need to be fully understood. Cannabinoid compounds including cannabidiol (CBD), tetrahydrocannabinol (THC) and cannabinol (CBN) have shown promise as potential antibiotic adjuvants. In the present study, MRSA cells were subjected to antibiotic stress from methicillin in combination with three cannabinoid compounds, and subsequently analysed using metaproteomics to assess the metabolic response. Subjecting MRSA to methicillin made the cells more viable and increased their energy production, as well as upregulation of penicillin-binding protein 2 (PBP2). The cannabinoids all showed antimicrobial activity against MRSA, and inhibited the energy production of the cells as well as PBP2 when used in combination with methicillin. Furthermore, all three cannabinoid compounds inhibited resistance mechanisms in MRSA, resulting in a decrease in the minimum inhibitory concentration (MIC) of methicillin when used in combination.
Project description:The authors use a large dataset (>30k) to train an explainable graph-based model to identify potential antibiotics with low cytotoxicity. The model uses a substructure-based approach to explore the chemical space. Using this method, they were able to screen 283 compounds and identify a candidate active against methicillin-resistant S. aureus (MRSA) and vancomycin-resistant enterococci.
Model Type: Predictive machine learning model.
Model Relevance: The model predicts the probability of growth inhibition.
Model Encoded by: Sarima Chiorlu (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam
Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos18ie
Project description:The authors use a large dataset (>30k) to train an explainable graph-based model to identify potential antibiotics with low cytotoxicity. The model uses a substructure-based approach to explore the chemical space. Using this method, they were able to screen 283 compounds and identify a candidate active against methicillin-resistant S. aureus (MRSA) and vancomycin-resistant enterococci.
Model Type: Predictive machine learning model.
Model Relevance: Prediction of Human cytotoxicity endpoints.
Model Encoded by: Sarima Chiorlu (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam
Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos42ez
Project description:Plants have a long history of use for their medicinal properties. The complexity of botanical extracts presents unique challenges and necessitates the application of innovative approaches to correctly identify and quantify bioactive compounds. With this study, we employed untargeted metabolomics to explore the antimicrobial activity of the botanical Rumex crispus (yellow dock), a member of the Polygonaceae family that is used as an herbal remedy for bacterial infections. Ultra high-performance liquid chromatography coupled to high resolution mass-spectrometry (UPLC-MS) was used to identify and quantify the known antimicrobial compound emodin. In addition, we used biochemometric approaches to integrate data measuring antimicrobial activity from R. crispus root starting material and fractions against methicillin resistant Staphylococcus aureus (MRSA) with UPLC-MS data. Our results support the hypothesis that multiple constituents, including the anthraquinone emodin, contribute to the antimicrobial activity of R. crispus against MRSA.
Project description:S. aureus ATCC 25923 is performance standard for antimicrobial susceptibility testing. S. aureus ATCC 33591 showed resistance against erytrhromycin, penicillin, and streptomycin. We used microarray to compare RNA expression between sensitive and resistant strain of S. aureus as a preliminary research for MRSA inhibition.