Effect of iron and silver nanoparticles on coenzyme Q10 production by Gluconobacter japonicus FM10

Abstract

Background and Objectives: Coenzyme Q10 is an anti-aging agent whose demand is increasing progressively. There are various strategies used for increasing coenzyme Q10 production by microorganisms. In this study, for the first time, we investigated the effect of iron oxide and silver nanoparticles on coenzyme Q10 production by Gluconobacter japonicus FM10.
 Materials and Methods: In the first step, a preliminary experiment was set and carried out to obtain the minimum inhibitory concentrations of the nanoparticles on the strain FM10. Then the sub-MIC concentrations were used to investigate their effect on coenzyme Q10 production in the stationary and exponential phases of the growth, separately.
 Results: The results showed that coenzyme Q10 production increased in the presence of the iron oxide and silver nanoparticles. The silver nanoparticles induced 1.9 times higher coenzyme Q10 production. The highest level of coenzyme Q10 was induced when the silver nanoparticles were added to the culture medium at the stationary phase.
 Conclusion: This should be noticed that so far nanoparticles have been considered as antibacterial agents, rather than being considered to cause probable beneficial effects on the induction of useful products in the microbial world. In this regard, their potential for increasing coenzyme Q10 production has received no attention. However, our present results showed that the nanoparticles can be used to increase the production efficiency of coenzyme Q10 in Gluconobacter.

Development of a thin layer chromatographic method for the determination of coenzyme Q10produced byAgrobacterium tumefaciens

“…Therefore, rapid detection of CoQ 10 is necessary for its analysis at each step during its industrial production. For the identification and quantification of CoQ 10 , various techniques such as the spectrophotometric method, HPLC, HPLC with electrochemical detection, LC-MS, and so forth are widely used due to high selectivity and sensitivity [16][17][18][19][20]. Despite this, all these methods are time taking, labor-intensive, highly complicated, and expensive.…”