Lipid Extract from Ulva ohnoi Algae: Chemical Characterization, Antibacterial Potential, and Cytotoxicity in the Search for New Agents Against MDR Infections

Antimicrobial resistance is a critical global concern. This study explored the lipid extract (LE) of Ulva ohnoi regarding its chemical composition, antibacterial activity, and cytotoxicity against multidrug-resistant (MDR) microorganisms. The LE was characterized by GC–MS, thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). Antibacterial efficacy was determined by Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) against MDR isolates: Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, and coagulase-negative Staphylococci (CoNS). Cytotoxicity was evaluated in murine fibroblast (L929) and bovine renal fibroblast (MDBK) cells using MTT, Neutral Red (NR), Lactate Dehydrogenase (LDH), and hemolytic activity (HA) assays. Lipid characterization revealed palmitic acid (63.62%) and oleic acid (21.01%) as major components. TGA indicated 88% mass loss, and DSC showed no amorphous/crystalline domains. LE showed favorable MIC values against S. aureus and CoNS (1.33 mg/mL) and against A. baumannii and E. coli (2 mg/mL), indicating moderate antibacterial activity typical of an unfractionated crude extract. MBC results indicated bacteriostatic activity (1–8 mg/mL). The extract was cytotoxic to L929 and MDBK cells at concentrations close to its MIC (IC₅₀ 0.25–1.95 mg/mL) but well tolerated by blood cells (HA IC50 4.705 mg/mL). U. ohnoi LE extends, rather than establishes, the previously reported antibacterial potential of Ulva lipids through comprehensive chemical characterization and MDR-isolate evaluation. However, low selectivity indices (SI < 10) indicate that the LE does not yet present an adequate therapeutic window, reinforcing the need for bioassay-guided purification. Nevertheless, it is a starting point for developing new antibacterial agents. Graphical Abstract