Article
Details
Citation
Mohammed IU, Deeni Y, Hapca SM, McLaughlin K & Spiers AJ (2015) Predicting the minimum liquid surface tension activity of pseudomonads expressing biosurfactants. Letters in Applied Microbiology, 60 (1), pp. 37-43. https://doi.org/10.1111/lam.12331
Abstract
Bacteria produce a variety of biosurfactants capable of significantly reducing liquid (aqueous) surface tension (γ) with a range of biological roles and biotechnological uses. To determine the lowest achievable surface tension (γMin), we tested a diverse collection of Pseudomonas‐like isolates from contaminated soil and activated sludge and identified those expressing biosurfactants by drop‐collapse assay. Liquid surface tension‐reducing ability was quantitatively determined by tensiometry, with 57 isolates found to significantly lower culture supernatant surface tensions to 24·5–49·1 mN m?1. Differences in biosurfactant behaviour determined by foaming, emulsion and oil‐displacement assays were also observed amongst isolates producing surface tensions of 25–27 mN m?1, suggesting that a range of structurally diverse biosurfactants were being expressed. Individual distribution identification (IDI) analysis was used to identify the theoretical probability distribution that best fitted the surface tension data, which predicted a γMin of 24·24 mN m?1. This was in agreement with predictions based on earlier work of published mixed bacterial spp. data, suggesting a fundamental limit to the ability of bacterial biosurfactants to reduce surface tensions in aqueous systems. This implies a biological restriction on the synthesis and export of these agents or a physical–chemical restriction on their functioning once produced.
Keywords
biosurfactant; liquid surface tension; Pseudomonas; statistical prediction; surfactant
Journal
Letters in Applied Microbiology: Volume 60, Issue 1
Status | Published |
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Funders | |
Publication date | 31/01/2015 |
Publication date online | 29/10/2014 |
Date accepted by journal | 19/09/2014 |
URL | |
Publisher | Wiley |
ISSN | 0266-8254 |
eISSN | 1472-765X |
People (1)
Lecturer, Computing Science