Biodegradation of Para Amino Acetanilide by Halomonas sp. TBZ3.

BACKGROUND: Aromatic compounds are known as a group of highly persistent environmental pollutants. Halomonas sp. TBZ3 was isolated from the highly salty Urmia Lake of Iran. In this study, characterization of a new Halomonas isolate called Halomonas sp. TBZ3 and its employment for biodegradation of para-amino acetanilide (PAA), as an aromatic environmental pollutant, is described. OBJECTIVES: This study aimed to characterize the TBZ3 isolate and to elucidate its ability as a biodegradative agent that decomposes PAA. MATERIALS AND METHODS: Primarily, DNA-DNA hybridization between TBZ3, Halomonas denitrificans DSM18045T and Halomonas saccharevitans LMG 23976T was carried out. Para-amino acetanilide biodegradation was assessed using spectrophotometry and confirmed by gas chromatography-mass spectroscopy (GC-MS). Parameters effective on biodegradation of PAA were optimized by the Response Surface Methodology (RSM). RESULTS: The DNA-DNA hybridization experiments between isolate TBZ3, H. denitrificans and H. saccharevitans revealed relatedness levels of 57% and 65%, respectively. According to GC-MS results, TBZ3 degrades PAA to benzene, hexyl butanoate, 3-methyl-1-heptanol and hexyl hexanoate. Temperature 32.92°C, pH 6.76, and salinity 14% are the optimum conditions for biodegradation with a confidence level of 95% (at level α = 0.05). CONCLUSIONS: According to our results, Halomonas sp. TBZ3 could be considered as a biological agent for bioremediation of PAA and possibly other similar aromatic compounds.

Generalized net analyte signal standard addition as a novel method for simultaneous determination: application in spectrophotometric determination of some pesticides.

Simultaneous spectrophotometric determination of three neonicotinoid insecticides (acetamiprid, imidacloprid, and thiamethoxam) by a novel method named generalized net analyte signal standard addition method (GNASSAM) in some binary and ternary synthetic mixtures was investigated. For this purpose, standard addition was performed using a single standard solution consisting of a mixture of standards of all analytes. Savings in time and amount of used materials are some of the advantages of this method. All determinations showed appropriate applicability of this method with less than 5% error. This method may be applied for linearly dependent data in the presence of known interferents. The GNASSAM combines the advantages of both the generalized standard addition method and net analyte signal; therefore, it may be a proper alternative for some other multivariate methods.

QSBR study of bitter taste of peptides: application of GA-PLS in combination with MLR, SVM, and ANN approaches.

Detailed information about the relationships between structures and properties/activities of peptides as drugs and nutrients is useful in the development of drugs and functional foods containing peptides as active compounds. The bitterness of the peptides is an undesirable property which should be reduced during drug/nutrient production, and quantitative structure bitter taste relationship (QSBR) studies can help researchers to design less bitter peptides with higher target efficiency. Calculated structural parameters were used to develop three different QSBR models (i.e., multiple linear regression, support vector machine, and artificial neural network) to predict the bitterness of 229 peptides (containing 2-12 amino acids, obtained from the literature). The developed models were validated using internal and external validation methods, and the prediction errors were checked using mean percentage deviation and absolute average error values. All developed models predicted the activities successfully (with prediction errors less than experimental error values), whereas the prediction errors for nonlinear methods were less than those for linear methods. The selected structural descriptors successfully differentiated between bitter and nonbitter peptides.

A new multi-wavelength model-based method for determination of enzyme kinetic parameters.

Lineweaver-Burk plot analysis is the most widely used method to determine enzyme kinetic parameters. In the spectrophotometric determination of enzyme activity using the Lineweaver-Burk plot, it is necessary to find a wavelength at which only the substrate or the product has absorbance without any spectroscopic interference of the other reaction components. Moreover, in this method, different initial concentrations of the substrate should be used to obtain the initial velocities required for Lineweaver-Burk plot analysis. In the present work, a multi-wavelength model-based method has been developed and validated to determine Michaelis-Menten constants for some enzyme reactions. In this method, a selective wavelength region and several experiments with different initial concentrations of the substrate are not required. The absorbance data of the kinetic assays are fitted by non-linear regression coupled to the numeric integration of the related differential equation. To indicate the applicability of the proposed method, the Michaelis-Menten constants for the oxidation of phenanthridine, 6-deoxypenciclovir and xanthine by molybdenum hydroxylases were determined using only a single initial concentration of the substrate, regardless of any spectral overlap.

Simultaneous spectrophotometric determination of benzoic acid, sorbic acid, and ascorbic acid using a net analyte signal-based method.

The net analyte preprocessing/classical least-squares (NAP/CLS) method is a simple chemometric method that has been used for the simultaneous spectrophotometric determination of benzoic acid, sorbic acid, and ascorbic acid. The obtained results indicated that the performances of the NAP/CLS and partial least-squares methods were almost identical. The net analyte signal (NAS) concept was also used to calculate multivariate analytical figures of merit, such as LOD, selectivity, and sensitivity. Wavelength selection was applied based on the concept of NAS regression, and improved the method performance in samples containing nonmodeled interferences. The method afforded recoveries in the range of 98-105%. The proposed method was successfully applied to determination of the analytes in an Iranian soft drink.