Cyanide degrading microbial species using different nutritional sources under different temperature and pH conditions
Recent developments in biotechnology for agro- /agro-industrial waste utilization have identified a plethora of agricultural waste (agrowaste) that is suitable for microbial proliferation and production of a variety of high value biological products, which are useful in industrial as well as environmental applications. About 1.6 billion tons of agrowaste is reportedly generated globally per annum . Considering the environmental degeneration caused by such waste, and the fact that they are readily available, research studies have been geared toward assessing the feasibility of converting such waste into value added products. Studies into the chemical and nutritional composition of agrowaste have equally identified some of them as suitable substrates for microbial cultivation [54, 40, 63, 69, 5].
In environmental bioremediation applications, microorganisms can be supported on solid agrowaste to provide the required macro- and micro-nutrients required for biofilm formation, which usually enhances the metabolic activities of the microorganisms for solubilization and biodegradation of contaminants, some of which are known to be potential human carcinogens [18, 22]. The paradigm shift from conventional substrates such as refined glucose, to unconventional substrates such as solid agrowaste or agro-industrial waste could be due to the fact that the latter mitigates operational costs, particularly for large-scale processes. Nutrients are considered the largest expense in industrial bioprocesses whereby the fermentation medium can account for a large proportion of fermentation costs [10, 39, 60]. Suitable agrowaste such as orange peel, apple pomace, wheat bran, sugar cane bagasse, wheat bran, soybean oil cake, jatropha curcas, whey waste, and
One of the most common wastewater pollutants is cyanide. It is usually released through various anthropogenic activities in the form of industrial effluent discharged from numerous industries. Another incessant anthropogenic source of cyanide deposition into the environment is through petroleum oil processing and its derivatives. Naturally, hydrocarbon oils such as petroleum contain cyano group compounds, which react with metals during thermal cracking operations to form metal cyanide complexes that culminate in wastewater . Many of these cyanide complexes are known to be highly unstable, mainly due to thermal instability, thus releasing free cyanide into the environment under high temperature. It has been reported by Acheampong
It is common to use oxidation methods for cyanide degradation and its complexes, such as the use of metal catalyzed hydrogen peroxide, and alkaline chlorination processes, including removal by ion-exchange resin . This approach, though effective, has some drawbacks that are of major concern. The excess reagents used in the treatment tend to further pollute the environment, as well as increase operational costs. In addition, due to municipal regulations in some countries, the application of chemical methods on a large scale is not permissible. Considering that cyanide in wastewater is undesirable, if present, it must not exceed the discharge limit of 0.01 mg F-CN/L . Thus, cyanide degradation using biotechnological processes is desirable.
It has been shown that several microorganisms such as algae, bacteria, and fungi, can produce enzymes that are capable of degrading free cyanide, cyanide complexes and by-products produced [3, 24, 33, 59]. Recently, studies have established sustainable cyanide biodegradation processes using various microorganisms such as
The application of agrowaste as a substrate in cyanide biodegradation systems is particularly promising, as reported by Santos
2. Application of
sp. and Beta vulgaris in cyanide biodegradation
3. Biodegradation of cyanide by
Fusarium oxysporum grown on Beta vulgaris
A number of different studies report on the application of cyanide degrading fungi. For instance, white rot fungi,
There has been limited emphasis on the effect of carbon or nitrogen sources used in the biodegradation of cyanide. The viability of the agrowaste depends on the type of bioremediation required and the microorganism used. When the cultivating conditions are conducive, the minerals, proteins, carbohydrates and water in the agrowaste become easily accessible to the microorganisms . Monosaccharides such as mannose, glucose and fructose present in the agrowaste can effectively support and/or enhance microbial growth . Other overriding factors which directly influence cyanide degradation include exposure to direct sunlight, temperature and pH. Cyanide compounds are soluble in water, thus dissociate and evaporate easily at low pH (i.e. pH<9) while under high salinity, the solubility decreases. Also at neutral pH, weak-acid dissociable (WAD) cyanides such as copper or zinc cyanide complexes, if present in a high concentration, dissociate, releasing a cyano group. Similarly, the reduction in temperature reduces the activity of microorganisms used in bioremediation. A number of studies have proven that, at low temperature (below 10oC), growth of microorganisms is inhibited, resulting in low removal rates of contaminants such as ammonium-nitrogen, nitrates and cyanide [72, 29, 73].
In this study, the biodegradation of cyanide in the presence of heavy metals (arsenic, copper, lead, iron and zinc), using
4. Materials and methods
The experiments were carried out in batch cultures.
||Fructose, glucose, mannose||KCN||30||10|||
||Sugarcane molasses, glucose||[Cu(CN)4]2-, [Zn(CN)4]2-||35||7.5|||
||Glucose||KCN||35, 28||5.3-5.7, 7.0|||
||Alginate and cellulose triacetate||KCN||30||7|||
|Mixed culture of bacteria||Glucose||CN- WAD||22||7.0|||
|Mixed culture of bacteria immobilised on ultrafiltration membranes||Phenol||Cyanides||25||-|||
||NaCN, sodium alginate||NaCN, Cyanates and thiocyanates||25||7.5|||
The response surface methodology was used for the statistical design of the experiments to assess the influence of temperature and pH for optimal degradation of cyanide. A central composite design was used for the determination of optimal operating conditions with a minimum residual ammonium-nitrogen as one of the objectives. Design Expert software® version 6.0.8 (Stat-Ease Inc., USA) was used to generate the experimental runs.
The results (Table 3) indicated a variation in responses measured. There was appreciable degradation of cyanide in Runs 9, 4, 1, 3, 6, 8, 13, and 14, with the highest cyanide degraded being 263 mg F-CN/L (Run 9) and the lowest (83 mg F-CN/L) being observed for Run 11. However, both cases had a high residual ammonium-nitrogen of 210 mg NH4+-N/L and 120 mg NH4+-N/L, respectively. Both Runs 9 and 11 were axial points. Run 9 with an extremely high pH resulted in high residual ammonium-nitrogen while Run 11 with an extremely low temperature was observed to have minimal microbial activity despite the presence of a suitable quantity of
5. Statistical model analysis
The statistical model summary clarifies the fitness of the mean and quadratic models for the two responses based on the Sequential Model Sum of Squares and Lack of Fit Test. The responses were analysed using ANOVA to assess the significance of the variables in the model. A quadratic model was found to give the best fit for the experimental results.
The predicted response (Y) for the biodegradation of free cyanide in terms of the coded values was:
A model reduction was appropriate since there were many insignificant model terms. Excluding these terms improved the model. The Model F-value of 11.41 for the cyanide biodegradation was significant; therefore, there was only a 0.29% chance that a "Model F-Value" this large could occur due to noise for the quadratic model. Statistically, an adequate ratio greater than 4 is desireable for measuring a signal to noise ratio; therefore, the adequate precision of 10.341 observed in this study indicates a passable signal that can be used to further navigate the design space. Figure 3 further justifies the fitness of the model with normality in the error term.
6. Representation of the response surface model
The interaction between independent variables can be studied by plotting three dimensional (3-D) curves of the response against the variables. It allows for the interpretation of experimental results and determination of optimal conditions. Elliptical contour shows the interaction between the independent variables is perfect while a circular contour indicates the variables are non-interactive [44, 47].
7. Cyanide biodegradation optimisation
The optimisation was done using the Design-Expert software® numerical optimisation option where input factors were selected to achieve a desired perfomance. The numerical optimisation can maximise, minimise or achieve a targeted value: a single response; a single response subjected to upper and/or lower boundaries on other responses; and combinations of two or more responses. The desired goal for each variable and response is selected and the weight is chosen to show the degree of importance of individual goals. In this analysis, temperature and pH were set within range, cyanide degradation response was set at maximum while ammonium-nitrogen formation response was set at a minimum. The software gave three different solutions for this criteria with different desirability. The optimum point with the highest desirability was selected as shown in Fig.6 and 7. The optimal point with the maximum cyanide degradation of 250.436 mg F-CN/L and minimum ammonium-nitrogen formation of 74.285 mg NH4+-N /L was found to be at temperature of 30oC and pH of 11.
The response surface plot identified temperature as a more significant factor affecting both the cyanide degradation and ammonium-nitrogen formation. The ammonium-nitrogen produced can be used as a nitrogen source by the fungus.
The optimum condition for maximum cyanide degradation and minimum ammonium-nitrogen formation was found at temperature 30oC and pH of 11 where cyanide of 250.436 mg F-CN/L was degraded and ammonium-nitrogen of 74.285 mg NH4+-N/L was formed.
The authors acknowledge the CPUT University Research Fund RK 16 for funding this research.
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