Production, characterization, and kinetic modeling of biosurfactant synthesis by Pseudomonas aeruginosa gi |KP 163922| : a mechanism perspective

© 2023. The Author(s), under exclusive licence to Springer Nature B.V..

Kinetic studies and modeling of production parameters are essential for developing economical biosurfactant production processes. This study will provide a perspective on mechanistic reaction pathways to metabolize Waste Engine Oil (WEO). The results will provide relevant information on (i) WEO concentration above which growth inhibition occurs, (ii) chemical changes in WEO during biodegradation, and (iii) understanding of growth kinetics for the strain utilizing complex substrates. Laboratory scale experiments were conducted to study the kinetics and biodegradation potential of the strain Pseudomonas aeruginosa gi |KP 163922| over a range (0.5-8% (v/v)) of initial WEO concentration for 168 h. The kinetic models, such as Monod, Powell, Edward, Luong, and Haldane, were evaluated by fitting the experimental results in respective model equations. An unprecedented characterization of the substrate before and after degradation is presented, along with biosurfactant characterization. The secretion of biosurfactant during the growth, validated by surface tension reduction (72.07 ± 1.14 to 29.32 ± 1.08 mN/m), facilitated the biodegradation of WEO to less harmful components. The strain showed an increase in maximum specific growth rate (µmax) from 0.0185 to 0.1415 h-1 upto 49.92 mg/L WEO concentration. Maximum WEO degradation was found to be ~ 94% gravimetrically. The Luong model (adj. R2 = 0.97) adapted the experimental data using a non-linear regression method. Biochemical, 1H NMR, and FTIR analysis of the produced biosurfactant revealed a mixture of mono- and di- rhamnolipid. The degradation compounds in WEO were identified using FTIR, 1H NMR, and GC-MS analysis to deduce the mechanism.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:39

Enthalten in:

World journal of microbiology & biotechnology - 39(2023), 7 vom: 02. Mai, Seite 178

Sprache:

Englisch

Beteiligte Personen:

Gaur, Shailee [VerfasserIn]
Gupta, Suresh [VerfasserIn]
Jain, Amit [VerfasserIn]

Links:

Volltext

Themen:

β-oxidation
Glycolipids
Journal Article
Luong model
Non-linear regression
Rhamnolipid
Specific growth rate
Substrate inhibition
Surface-Active Agents
Waste engine oil

Anmerkungen:

Date Completed 04.05.2023

Date Revised 04.05.2023

published: Electronic

Citation Status MEDLINE

doi:

10.1007/s11274-023-03623-2

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM356329771