scholarly journals Stimulation of diesel degradation and biosurfactant production by aminoglycosides in a novel oil-degrading bacterium Pseudomonas luteola PRO23

2016 ◽  
Vol 70 (2) ◽  
pp. 143-150 ◽  
Author(s):  
Iva Atanaskovic ◽  
Jelena Jovicic-Petrovic ◽  
Marjan Biocanin ◽  
Vera Karlicic ◽  
Vera Raicevic ◽  
...  
Keyword(s):  
Crude Oil ◽  
Growth Kinetics ◽  
Microbial Growth ◽  
Biosurfactant Production ◽  
Lag Phase ◽  
Degrading Bacterium ◽  
Light Oil ◽  
Oil Concentration ◽  
Pseudomonas Luteola ◽  
Biodegradation Efficiency

Bioremediation is promising technology for dealing with oil hydrocarbons contamination. In this research growth kinetics and oil biodegradation efficiency of Pseudomonas luteola PRO23, isolated from crude oil-contaminated soil samples, were investigated under different concentrations (5, 10 and 20 g/L) of light and heavy crude oil. More efficient biodegradation and more rapid adaptation and cell growth were obtained in conditions with light oil. The 5 to 10 g/L upgrade of light oil concentration stimulated the microbial growth and the biodegradation efficiency. Further upgrade of light oil concentration and the upgrade of heavy oil concentration both inhibited the microbial growth, as well as biodegradation process. Aminoglycosides stimulated biosurfactant production in P. luteola in the range of sub-inhibitory concentrations (0.3125, 0.625 ?g/mL). Aminoglycosides also induced biofilm formation. The production of biosurfactants was the most intense during lag phase and continues until stationary phase. Aminoglycosides also induced changes in P. luteola growth kinetics. In the presence of aminoglycosides this strain degraded 82% of diesel for 96 h. These results indicated that Pseudomonas luteola PRO23 potentially can be used in bioremediation of crude oil-contaminated environments and that aminoglycosides could stimulate this process.

Assessment of Crude Oil Degradation by Mixed Culture of Bacillus subtilis and Pseudomonas aeruginosa at Different Concentrations

2020 ◽  
Vol 9 (2) ◽  
pp. 33-50
Author(s):  
A.A. Faggo ◽  
A.H. Kawo ◽  
B.H. Gulumbe ◽  
U.J.J. Ijah
Keyword(s):  
Crude Oil ◽  
Mixed Culture ◽  
Control Sample ◽  
Gas Chromatography Mass Spectrometry ◽  
Oil Degradation ◽  
Pollution Levels ◽  
Degrading Bacteria ◽  
Crude Oil Degradation ◽  
Light Oil ◽  
Oil Concentration

Petroleum hydrocarbon (PHCs) contamination of soil, freshwater and air is of global concern. The aim of this study was to assess the extent of crude oil degradation by mixed bacterial culture of different crude oil concentrations using gas chromatography-mass spectrometry (GC-MS). Seven oil samples were collected from petroleum-contaminated fields in Kano state, Nigeria, and screened for crude oil utilizing bacteria. A control sample of soil from an ecological garden (control soil) was also analyzed. Crude oil-degrading bacteria were isolated, enumerated and identified using cultural, morphological and biochemical characteristics, and screened for their ability to utilize Bonny Light Oil as a source of carbon and energy. Bacteria with the highest potential to utilize crude oil were selected and subjected to bioremediation studies at three different pollution levels (5%, 10% and 15%) for 56 days. The residual crude oil was assessed using GC-MS. The results revealed that the mixed culture completely degraded eighteen components ranging from C10 to C25 at 5% crude oil concentration while only C8 to C11 and C8 to C9 were degraded at 10 and 15% respectively. The results of this study indicated the potential of B. subtilis and P. aeruginosa in bioremediation of crude oil contaminated soil.

Lipopeptide biosurfactant production bacteria Acinetobacter sp. D3-2 and its biodegradation of crude oil

2014 ◽  
Vol 16 (4) ◽  
pp. 897-903 ◽  
Author(s):  
Mutai Bao ◽  
Yongrui Pi ◽  
Lina Wang ◽  
Peiyan Sun ◽  
Yiming Li ◽  
...  
Keyword(s):  
Crude Oil ◽  
Contaminated Soil ◽  
Potential Effect ◽  
Soil Samples ◽  
Biosurfactant Production ◽  
Degrading Bacterium ◽  
Petroleum Contaminated Soil ◽  
Lipopeptide Biosurfactant ◽  
Acinetobacter Sp

In this work, a hydrocarbon-degrading bacterium D3-2 isolated from petroleum contaminated soil samples was investigated for its potential effect in biodegradation of crude oil. The strain was identified as Acinetobacter sp.

Potential Bifunctional Rhizobacteria from Crude Oil Sludge for Hydrocarbon Degradation and Biosurfactant Production

2021 ◽  
Author(s):  
Siti Shilatul Najwa Sharuddin ◽  
Siti Rozaimah Sheikh Abdullah ◽  
Nur ‘Izzati Ismail ◽  
Ahmad Razi Othman ◽  
Hassimi Abu Hasan
Keyword(s):  
Crude Oil ◽  
Biosurfactant Production ◽  
Oil Sludge ◽  
Hydrocarbon Degradation ◽  
Crude Oil Sludge

scholarly journals Bio-Electrochemical System Depollution Capabilities and Monitoring Applications: Models, Applicability, Advanced Bio-Based Concept for Predicting Pollutant Degradation and Microbial Growth Kinetics via Gene Regulation Modelling

Processes ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 1038
Author(s):  
Argyro Tsipa ◽  
Constantina K. Varnava ◽  
Paola Grenni ◽  
Vincenzo Ferrara ◽  
Andrea Pietrelli
Keyword(s):  
Gene Regulation ◽  
Growth Kinetics ◽  
Microbial Fuel Cells ◽  
Growth Kinetic ◽  
Microbial Growth ◽  
Pollutant Removal ◽  
Enzyme Expression ◽  
Regulation Mechanisms ◽  
Microbial Growth Kinetics ◽  
Difficult Challenge

Microbial fuel cells (MFC) are an emerging technology for waste, wastewater and polluted soil treatment. In this manuscript, pollutants that can be treated using MFC systems producing energy are presented. Furthermore, the applicability of MFC in environmental monitoring is described. Common microbial species used, release of genome sequences, and gene regulation mechanisms, are discussed. However, although scaling-up is the key to improving MFC systems, it is still a difficult challenge. Mathematical models for MFCs are used for their design, control and optimization. Such models representing the system are presented here. In such comprehensive models, microbial growth kinetic approaches are essential to designing and predicting a biosystem. The empirical and unstructured Monod and Monod-type models, which are traditionally used, are also described here. Understanding and modelling of the gene regulatory network could be a solution for enhancing knowledge and designing more efficient MFC processes, useful for scaling it up. An advanced bio-based modelling concept connecting gene regulation modelling of specific metabolic pathways to microbial growth kinetic models is presented here; it enables a more accurate prediction and estimation of substrate biodegradation, microbial growth kinetics, and necessary gene and enzyme expression. The gene and enzyme expression prediction can also be used in synthetic and systems biology for process optimization. Moreover, various MFC applications as a bioreactor and bioremediator, and in soil pollutant removal and monitoring, are explored.

scholarly journals A Bayesian approach to analyzing phenotype microarray data enables estimation of microbial growth parameters

2016 ◽  
Vol 14 (03) ◽  
pp. 1650007 ◽  
Author(s):  
Matthias Gerstgrasser ◽  
Sarah Nicholls ◽  
Michael Stout ◽  
Katherine Smart ◽  
Chris Powell ◽  
...  
Keyword(s):  
High Throughput ◽  
Bayesian Approach ◽  
Microarray Data ◽  
Time Course ◽  
Microbial Growth ◽  
Mcmc Methods ◽  
Lag Phase ◽  
Maximum Output ◽  
Phenotype Microarray ◽  
Phenotype Microarrays

Biolog phenotype microarrays (PMs) enable simultaneous, high throughput analysis of cell cultures in different environments. The output is high-density time-course data showing redox curves (approximating growth) for each experimental condition. The software provided with the Omnilog incubator/reader summarizes each time-course as a single datum, so most of the information is not used. However, the time courses can be extremely varied and often contain detailed qualitative (shape of curve) and quantitative (values of parameters) information. We present a novel, Bayesian approach to estimating parameters from Phenotype Microarray data, fitting growth models using Markov Chain Monte Carlo (MCMC) methods to enable high throughput estimation of important information, including length of lag phase, maximal “growth” rate and maximum output. We find that the Baranyi model for microbial growth is useful for fitting Biolog data. Moreover, we introduce a new growth model that allows for diauxic growth with a lag phase, which is particularly useful where Phenotype Microarrays have been applied to cells grown in complex mixtures of substrates, for example in industrial or biotechnological applications, such as worts in brewing. Our approach provides more useful information from Biolog data than existing, competing methods, and allows for valuable comparisons between data series and across different models.

scholarly journals Biotreatability of Crude Oil Polluted Aquatic Environment Using Indigenous Hydrocarbon Utilizing Bacteria

2020 ◽  
pp. 52-62
Author(s):  
Tudararo-Aherobo Laurelta ◽  
Okotie Sylvester ◽  
Ataikiru Tega ◽  
Stephen Avwerosuoghene
Keyword(s):  
Crude Oil ◽  
Contaminated Soils ◽  
Aquatic Environment ◽  
Bacterial Counts ◽  
A Value ◽  
Degrading Bacteria ◽  
Petroleum Resources ◽  
Oil Concentration ◽  
American Society ◽  
Hydrocarbon Utilizing Bacteria

Aim: The research aims to assess the biodegradability of crude oil polluted aquatic environment using indigenous hydrocarbon degrading bacteria. Place and Duration of Study: The research was conducted in the Environmental Management and Toxicology Laboratory, Federal University of Petroleum Resources, Effurun, Delta State. Methodology: Hydrocarbon degrading bacteria species were isolated from hydrocarbon contaminated soils, screened and used for the degradation of crude oil. 5% and 10% crude oil were used to spike the test microcosm. Physicochemical parameters such as, pH, turbidity, total petroleum hydrocarbon (TPH) and bacterial counts of the bioremediated crude oil contaminated water were monitored on Day 0, 7 and 14. The biodegradation of the crude oil was done with the various bacteria isolates singly and as a consortium. Standard methods of American Public Health Association (APHA) and American Society for Testing and Materials (ASTM) were used for the analysis. Results: The isolates identified and used for the biodegradation process were, Azomonas sp., Enterococcus sp., Klebsiella sp. and Rhizobactersp. On day 14, in the microcosms with 5% crude oil contamination, Azomonas sp. recorded the highest turbidity reading of 328 ± 2.0 NTU, while Rhizobacter sp. recorded the least with 57.67 ± 0.58 NTU. The bacterial countswere between 7.68 ± 0.002 CFU/ml and 8.05 ± 0.10x 107 CFU/ml for Rhizobacter sp. and Azomonas sp. respectively.The crude oil was also degraded most in the microcosm treated with Azomonas sp. with a residual TPH concentration of 0.0013± 0.005 mg/l.For the 10% crude oil contaminated microcosms, TPH was also biodegraded most by Azomonas sp. with a value of 0.0026 ± 0.002mg/l. Turbidity readings were between 82 ± 1.0 NTU and 375.33 ± 0.57 NTU for Rhizobacter sp. and Azomonas sp. respectively. Bacterial counts were between (7.71± 0.012)x 107CFU/ml – (8.13± 0.001) x 107CFU/ml for Rhizobacter sp. and Azomonassp. respectively. Conclusion:There wasincreased microbial countsand decrease of residual crude oil concentration, indicating degradation of the crude oil by all the isolates.However, Azomonas sp. recorded the highest TPH degradation for both the 5% and 10% crude oil contaminated microcosms.Thus, findings from the research indicate that hydrocarbon degrading bacteria exist in our environment and can be used in the remediation of aquatic polluted environment.

Solid-State Fermentation, Microbial Growth Kinetics

2014 ◽  
pp. 1-23
Author(s):  
David A. Mitchell ◽  
Deidre M. Stuart ◽  
Sibel Uludag-Demirer ◽  
Robert D. Tanner
Keyword(s):  
Solid State ◽  
Growth Kinetics ◽  
Solid State Fermentation ◽  
Microbial Growth ◽  
Microbial Growth Kinetics
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