Targeting cellular metabolism to inhibit synergistic biofilm formation of multi-species isolated from a cooling water system
Kang, D.; Liu, W.; Kakahi, F. B.; Delvigne, F.
Show abstract
Biofilm is ubiquitous in natural environments, causing biofouling in industrial water systems and leading to liquidity and heat transfer efficiency decreases. In particular, multi-species coexistence in biofilms can provide the synergy needed to boost biomass production and enhance treatment resistance. In this study, a total of 37 bacterial strains were isolated from a cooling tower where acetic acid and propionic acid were used as the primary carbon sources. These isolates mainly belonged to Proteobacteria and Firmicutes, which occupied more than 80% of the total strains according to the 16S rRNA gene amplicon sequencing. Four species (Acinetobacter sp. CTS3, Corynebacterium sp. CTS5, Providencia sp. CTS12, and Pseudomonas sp. CTS17) were observed to co-exist in the synthetic medium, showing a synergistic effect towards biofilm formation. Three metabolic inhibitors (sulfathiazole, 3-Bromopyruvic acid, and 3-Nitropropionic acid) were employed as possible treatments against biofilm formation due to their inhibition effect on c-di-GMP biosynthesis or assimilation of volatile fatty acids. All of them displayed evident inhibition profiles to biofilm formation. Notably, the combination of these three inhibitors possessed a remarkable ability to block the development of a multi-species biofilm with lower concentrations, suggesting an enhanced effect with their simultaneous use. This study demonstrates that targeting cellular metabolism is an effective way to inhibit biofilm formation derived from multi-species.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Establishing Essential Oil Stewardship Through the Case of Rosemary and Thyme Oils Against Staphylococcus aureus 96%
- SARS-CoV-2 virus in Raw Wastewater from Student Residence Halls with concomitant 16S rRNA Bacterial Community Structure changes 95%
- Isolation, identification and selection of bacteria with the proof-of-concept for bioaugmentation of whitewater from woodfree paper mills 95%
Similar papers in this journal
- L-norepinephrine Induces Community Shift, Oxidative Stress Response, Metabolic Reprogramming, and Virulence Potential in Wastewater Microbiomes 95%
- The hospital sink drain biofilm resistome is independent of the corresponding microbiota, the environment and disinfection measures 95%
- Denitrification kinetics indicates nitrous oxide uptake is unaffected by electron competition in Accumulibacter 95%
Similar papers in this journal
- Impact of operational conditions on drinking water biofilm dynamics and coliform invasion potential 95%
- The bi-directional extracellular electron transfer process aids iron cycling by Geoalkalibacter halelectricus in a highly saline-alkaline condition 95%
- Assessing the activity of different plant-derived molecules and potential biological nitrification inhibitors on a range of soil ammonia- and nitrite- oxidizing strains 95%
Similar papers in this journal
- Isolation, screening, degradation characteristics of a quinclorac-degrading bacteria D and its potential of bioremediation for rice field environment polluted by quinclorac 95%
- Field testing of an enzymatic quorum quencher coating additive to reduce biocorrosion of steel 95%
- Investigating the resistome, taxonomic composition, andmobilome of bacterial communities in hospital wastewaters ofMetro Manila using a shotgun metagenomics approach 95%
Similar papers in this journal
- Effect of chlorination and pressure flushing of drippers fed by reclaimed wastewater on biofouling 97%
- Impact of temperature on Legionella pneumophila, its protozoan host cells, and the microbial diversity of the biofilm community of a pilot cooling tower 96%
- First wastewater surveillance-based city zonation for effective COVID-19 pandemic preparedness powered by early warning: A study of Ahmedabad, India 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.