Targeting Microbial Biofouling by Controlling Biofilm Formation and Dispersal Using Rhamnolipids on RO Membrane.
null ZahidullahMuhammad Faisal SiddiquiShamas TabraizFarhana MaqboolFazal AdnanIhsan UllahMuhammad Ajmal ShahWaqar Azeem JadoonTariq MehmoodSadia QayyumZiaur RahmanPublished in: Membranes (2022)
Finding new biological ways to control biofouling of the membrane in reverse osmosis (RO) is an important substitute for synthetic chemicals in the water industry. Here, the study was focused on the antimicrobial, biofilm formation, and biofilm dispersal potential of rhamnolipids (RLs) (biosurfactants). The MTT assay was also carried out to evaluate the effect of RLs on biofilm viability. Biofilm was qualitatively and quantitatively assessed by crystal violet assay, light microscopy, fluorescence microscopy (bacterial biomass (µm 2 ), surface coverage (%)), and extracellular polymeric substances (EPSs). It was exhibited that RLs can reduce bacterial growth. The higher concentrations (≥100 mg/L) markedly reduced bacterial growth and biofilm formation, while RLs exhibited substantial dispersal effects (89.10% reduction) on preformed biofilms. Further, RLs exhibited 79.24% biomass reduction while polysaccharide was reduced to 60.55 µg/mL ( p < 0.05) and protein to 4.67 µg/mL ( p < 0.05). Light microscopy revealed biofilm reduction, which was confirmed using fluorescence microscopy. Microscopic images were processed with BioImageL software. It was revealed that biomass surface coverage was reduced to 1.1% at 1000 mg/L of RLs and that 43,245 µm 2 of biomass was present for control, while biomass was reduced to 493 µm 2 at 1000 mg/L of RLs. Thus, these data suggest that RLs have antimicrobial, biofilm control, and dispersal potential against membrane biofouling.
Keyphrases
- biofilm formation
- staphylococcus aureus
- candida albicans
- pseudomonas aeruginosa
- single molecule
- high throughput
- escherichia coli
- wastewater treatment
- high resolution
- optical coherence tomography
- anaerobic digestion
- high speed
- cystic fibrosis
- single cell
- drug delivery
- label free
- deep learning
- cancer therapy
- electronic health record
- drinking water
- small molecule
- binding protein
- protein protein