Journal of Biotechnology and Biosafety

Journal of Biotechnology and Biosafety

Volume 2 Issue 3 May/June 2014

An International, Open Access, Peer reviewed,

Bi-Monthly Journal

Editorial

Editor-in-Chief

Chethana G S [email protected]

[email protected]

www.jobb.co.in

Advisory Board

Dr. S.M. Gopinath, Phd HOD, Dept of Biotechnology, Acharya Institute of Technology, Bangalore, INDIA

Dr. Vedamurthy A.B. Phd Professor, P.G. Department of Studies in Biotechnology and Microbiology, Karnatak

University, Dharwad, India

Dr. Hari Venkatesh K Rajaraman MD(Ay), PGDHM Manager, R&D, Sri Sri Ayurveda Trust, Bangalore, INDIA

R. Rajamani, M.Sc.,M.Phil.,B.Ed. Co-Principle Investigator, SSIAR, Bangalore, INDIA

Dr. Pravina Koteshwar, MBBS, MD Director, Academic Programs, ICRI, India

Ghanshyam Kumar Shrivastava, M.Pharm Research Head, SSIAR, Bangalore, India

Editorial Board

Dr. Pushpinder Kaur, Phd Research Associate, CSIR-Institute of Microbial Technology Sector,

Chandigarh, INDIA

Dr. Kavita Sharma, Phd Senior Scientist, Research and Development, Pharmacology Division,

Sigma Test and Research Centre, New Delhi, INDIA

Dr. Kasim Sakran Abass, Phd Associate Professor, College of Nursing,

University of Kirkuk, Kirkuk, IRAQ

Index – JOBB, Volume 2, Issue 2 - March/April 2014

Biochemistry

BIODECOLORIZATION OF REACTIVE DYES BY USING PLEUROTUS OSTREATUS Muthukumaran P, Priya M, Divya R, Indhumathi E, Keerthika C 94-101

Animal Biotechnology

A SIMULTANEOUS METHOD DEVELOPMENT, VALIDATION AND CONFIRMATORY ANALYSIS OF

AMOZ, AOZ, AHD AND SEM IN KATLA FISH (KATLA KATLA) AND BAGDA SHRIMP (PENIOUS

MONODON) BY UPLC-MS/MS (QPXE) Md. Ashraful Alam, Talukdar Muhammad Waliullah, Akter Mst Yeasmin, Md. Serajul Islam,

Md. Manik Mia 102-112

Short Communication

ANTILIPASE ACTIVITY: CRATAEVA NURVALA AND ACACIA CATECHU (L.) Hari Venkatesh K R, Chethana G. S

113-115

Journal of Biotechnology and Biosafety Volume 2, Issue 2, May-June 2014, 94-101

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www.jobb.co.in International, Peer reviewed, Open access, Bimonthly Online Journal

Research article BIODECOLORIZATION OF REACTIVE DYES BY USING

PLEUROTUS OSTREATUS

______________________________________ Muthukumaran P1*, Priya M2, Divya R3, Indhumathi E4, Keerthika C5

1Assistant professor, Department of Biotechnology, Kumaruguru College of Technology, Coimbatore-641049, Tamil Nadu. 2Iyear M.Tech (Biotechnology) Department of Biotechnology, Kumaruguru College of Technology, Coimbatore-641049, Tamil Nadu. 3,4,5IIIyear B.Tech (Biotecnology) Department of Biotechnology, Kumaruguru College of Technology, Coimbatore-641049, Tamil Nadu. *CorrespondingAuthor: [email protected]

ABSTRACT In this study, 4 different effluent samples (2 untreated samples and 1 treated sample and 1 soil sample) were collected from Common effluent treatment plant (CETP) in State Industries Promotion Corporation of Tamil Nadu Limited (SIPCOT), Perundurai, Erode District, Tamil Nadu. About 8 different fungal colonies were obtained from the collected samples. Based on the decolorization studies, the fungal isolates were screened and then tested for their ability to decolorize three synthetic dyes such as Reactive Red 120, Reactive Black 5 and Direct Red 81. After final screening, one fungal isolate were selected for dye decoloration studies. This fungal isolate were identified as Pleurotus ostreatus. In decoloration studies Pleurotus ostreatus shows 66%, 76% and 57 % of dye removal of Reactive Red 120, Reactive Black 5 and Direct Red 81 respectively. The various physical parameters such as temperature, pH, C:N ratio, culture incubation conditions were optimized for the decolorization of the three synthetic dyes by Pleurotus ostreatus.

Key words: Reactive dyes, Decoloration, Effluent, Optimization, Pleurotus ostreatus _____________________________________________________________________________________________________

INTRODUCTION

Environmental pollution is one of the major problems of the modern world. On one hand, industrialization is necessary to satisfy the needs of the world’s overgrowing population but on the other hand, it threatens life on earth by polluting the environment. Textile dyes are one of the most prevalent chemicals in use today. With increasing usage of the wide variety of dyes in the industries pollution from the effluents has become increasingly alarming. Currently, various chemical, physical and biological treatment methods are used to remove color. Microbial decolorization and degradation is and environmentally friendly and cost – effective process. In general, Biological methods using various microbes like bacteria, fungi and algae of dye removal could be a viable option as a low-cost and eco-friendly decentralized wastewater treatment system for small- scale industries various marine derived fungal isolates were used to degrade textile dyes from raw effleluents (Ashutosh

kumar et al., 2010). Similarly, various industrial textile dyes from raw effluents were decolorized by using various filamentous fungi Penicillium simplicissimum and toxicity evaluation of industrially treated textiles effluents were evaluated after fungal treatment (Bergsten et al., 2009).

Many of the industrially used textile dyes were decolorized by using aerobic and anaerobic conditions. Reactive red 11 and 152 azo dyes were decolorized by aerobic fermentation conditions (Kodam and Gawai, 2006).apart from fungal degradation and decoloration of textile effluent dyes, many fungal based enzymes were used to decoloration of azo dyes. One of main enzymes Manganse Peroxidase from White-Rot Basidiomycete Phanerochaete Sordida were used to decolorize azo dyes (Koichi et al., 2003). Similarly, Colour removal of textile dyes were studied by using culture extracts of white rot fungi (Mehmet et al., 2009).


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Apart from white rot fungi, some filamentous fungus were used for biodecolorization and biodegradation of various industrial Reactive blue (Mohandass et al., 2007). Muhammad et al., 2009, reported that, white rot fungus Coriolus versicolor IBL-04 can decolorize dyes in various textile industry effluents.

Aim of this study focuses on the biological decolourization of textile effluents through fungal isolates obtained from contaminated sites. The fungal colonies were isolated from the effluent samples and the soil from the contaminated sites. Then the isolates selected and screened with the ability to decolorize the effluent dyes with higher efficiency.

MATERIALS AND METHODS

Sample Collection

The dye effluent samples and soil sample from the dye contaminated sites were collected from various textile industries such as CETP in SIPCOT, Perundurai, About 4 effluent samples (2 untreated samples and 1 treated sample and 1 soil sample) were collected and then isolation of fungal colonies from these samples were carried out.

Isolation of fungal colonies from the collected effluent and samples

A fungus, Penicillium simplicissimum isolated from the sediment collected from the industrial contaminated sources decolorized three reactive dyes very effectively (Bergsten et al., 2009). The effluent dye samples and soil sample were serially diluted and 100 µl of the diluted effluent sample is added to the center of the Potato Dextrose Agar (Himedia) plates. The plates were then incubated at 30oC for 48 hrs. A mixture of fungal colonies was obtained on these plates after incubation. From these distinct colonies were chosen and are then pure cultured through streak plate method. The pure cultured fungal colonies were then maintained as slant for further studies. Decolorization studies with Synthetic dyes

A wide range of fungal isolates can decolorize various dyes (Fu and Viraraghavan, 2001 a,b).In the present decolorization studies were carried out for the selected colonies with three synthetic dyes namely Reactive Red 120, Reactive Black 5 and Direct Red 81. These dyes were prepared at a concentration of 50 mg/100mL and the decolorization assay mixture consists of 10% of dye. The decolorization studies were then carried out following the same procedure used for the decolorization of the effluent

dyes. These studies were done for the selected fungal colonies.

Dye removal (%) was calculated as Dye Removal (%) = Initial absorbance – Final absorbance x 100

Initial absorbance

Optimization of decolorization of the synthetic dyes by fungal strains

The optimization of the decolorization efficiency was then carried out for the fungal colonies. The effect of pH, Temperature, C:N ratio and culture incubation conditions were studied and these parameters are optimized to obtain maximum decolorization of the commercial dyes using the fungal colonies.

Effect of Temperature on the decolorization efficiency

The effect of temperature on the decolorization of the commercial dyes was analyzed at three different incubation temperatures 30oC, 37oC and 45oC. The decolorization % was calculated for the samples incubated at different temperatures and the optimum temperature for the decolorization was determined.

Effect of pH on the decolorization efficiency

The effect of pH on the decolorization of commercial dyes was analyzed. The decolorization media was prepared at different pH 3, 4, 5 and 6 and the decolorization % was calculated and the optimum pH for the decolorization of the textile dyes by the fungi was determined.

Effect of C:N ratio on the decolorization efficiency

The effect of the C:N ratio on the decolorization efficiency was determined by using the Bushnell and Haas media with different Carbon: Nitrogen source ratios such as 1:2, 1:1, 2:1. The optimum C:N ratio for the effective dye decolorization was determined from these studies.

Effect of culture incubation conditions on the decolorization efficiency

The effect of the culture incubation conditions on the dye decolorization was studied. The decolorization was carried out by incubating the decolorization assay mixture in the orbital shaker. Then the effect of culture incubation conditions on the decolorization efficiency compared and the optimum condition for decolorization was determined.


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RESULTS AND DISCUSSIONS

The decolorization textile dyes was carried out using a fungal isolates which was isolated from the effluent samples and soil samples from the effluent dye contaminated sites. The fungal isolates are isolated from the contaminated sites can easily adapt to the adverse environment and thus can be used for the decolorization of the dyes.

Isolation of fungal colonies from the effluent and soil samples

About 8 different fungal colonies were obtained from the samples obtained from CETP, Perundurai. The bacterial and fungal isolates were obtained from the soil and effluent samples from the small scale dyeing and printing units in Baddi (Himachal Pradesh, India) and Pali (Rajasthan, India) by this method (Prachi and Anushree, 2008).

Table 1 Name and source of the fungal colonies isolated from CETP samples

Source of the Organism Culture Name

CETPS CETPF1 CETPF2

CETPE1 CETPF3 CETPE2 CETPF4

CETPE3 CETPF5 CETPF6

CETPS

CETPF7

CETPF8

CETPE1 – CETP Effluent sample 1, CETPE2 – CETP Effluent sample 2, CETPE3 – CETP Effluent sample 3

CETPS – CETP Soil sample, CETPF – CETP sample Fungi

Fig 1 (a). Fungal isolates CETPF 1, CETPF 2 CETPF 3 and CETPF 4 from the source CETP Effluent Sample 3


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Fig 1(b). Fungal isolates CETPF 5, CETPF 6 CETPF 7 and CETPF 8 from the source CETP Effluent Sample 3

Decolorization of the synthetic dyes using the selected fungal isolates

The screened fungal isolates were then tested for their ability to decolorize the synthetic dyes. Three synthetic dyes namely Reactive Red 120, Reactive Black 5 and Direct Red 81 were used for these studies. The synthetic dye removal % of the screened with fungal isolates is used for further screening. Among 8 different fungal isolates, CETPE 1 shows maximum per cent age of dye removal

Fig. 2 Synthetic dye removal% of the fungal isolates from CETP samples

Optimization of the decolorization efficiency for the selected fungal strains The optimization of the decolorization efficiency was then carried out for the screened fungal strains. The effect of various physical parameters such as pH, Temperature, C:N ratio and shaking conditions were studied. The optimum conditions for the decolorization of the synthetic dyes were determined.


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Effect of Temperature on the decolorization efficiency The effect of temperature on the decolorization of the commercial dyes was analyzed at three different incubation temperatures

30oC, 37oC and 45oC. The decolorization % was calculated for the samples incubated at different temperatures and the following

table gives the decolorization % after 7 days for the four fungal isolates. From the study, Pleurotus ostreatus decolorize 64,77 and

62 % of three different reactive dyes at 5 at 30 oC. Similar report was showed that, Pleurotus ostreatus can able to decoloraize upto

97. 2 % of RBBR (Casieri et al., 2008).

Fig. 3 Effect of Temperature on the decolorization efficiency of synthetic dyes by Pleurotus ostreatus The maximum dye removal was found to occur at the incubation temperature of 30oC. Thus, the optimum temperature for decolorization for the three synthetic dyes by the fungal isolates was found to be 30oC.

Effect of pH on the decolorization efficiency

The effect of pH on the decolorization of synthetic dyes by the fungal strains was analyzed. The decolorization media was prepared at different pH 3, 4, 5 and 6 and the assay mixture decolorization % was calculated. The following table gives the synthetic dye removal % of the four fungal strains at different pH.

Fig. 4 Effect of pH on the decolorization efficiency of synthetic dyes by Pleurotus ostreatus


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The increase in percent decolorization with the further increase in pH (> 4.5) from the work the optimal pH is to be pH 6, it may be production enzyme by Pleurotus ostreatus. And it may be a change in pH may affect the enzyme activities (Knapp and Newby, 1995) Effect of C:N ratio on the decolorization Efficiency

The effect of the C:N ratio on the decolorization efficiency was determined by using the decoloriization media with different Carbon:Nitrogen source ratios such as 1:2, 1:1, 2:1. The following table gives the dye removal % of the fungal strains at different C:N ratios.

Fig. 5 Effect of C:N ratio on the decolorization Efficiency of synthetic dyes by Pleurotus ostreatus

Various researchers have reported an enhanced decolorization efficiency of textile dyes by using supplemental carbon sources. By using starch, glucose, glycerol and rice and wheat bran as a carbon source, decolorization Efficiency of synthetic Reactive dye 222 by Pleurotus ostreatus various from 56- 93% (Chen et al., 2002). The maximum dye removal % occurred at the C:N ratio of 1:2. Thus, the optimum C:N ratio for synthetic dye decolorization was determined to be 1:2 for the fungal strains.

Effect of incubation conditions on the Decolorization Efficiency

The effect of the shaking and stationary conditions on the dye decolorization was studied. The decolorization was carried out by incubating the decolorization assay mixture in the orbital shaker at 180 rpm at 30oC for 6 days. Then the effect of static and shaking condition on the decolorization efficiency was studied. The following table gives the dye removal% of samples incubated at shaking and static conditions. Previous report shows that, the maximum decolorazation of ractive dye 222 was 915 at 6th day of incubation (Shumaila et al., 2012). In these studies Pleurotus ostreatus can decolorize upto 77 % of reactive black, 64% of reactive red and 62% of direct red under static conditions.


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Fig. 6 Effect of incubation conditions on the Decolorization Efficiency of synthetic dyes by Pleurotus ostreatus

The maximum dye removal % occurred at the static. Thus, the optimum condition for synthetic dye decolorization by the fungal strains was under the static condition. Thus, the various physical parameters were optimized for the decolorization of the synthetic dyes by the fungal isolates. The optimum conditions were incubation temperature of 30oC, pH 6, C:N ratio 1:2 and incubation under static condition. This was in accordance with the literature studies, the fungal isolates from the dye contaminated sites showed high decolorization of the synthetic dyes at the incubation temperature of 30oC, at pH 6 and C:N ratio of 1:2 of the decolorization media. The fungal strains secrete lignolytic enzymes extracellularly which produce high decolorization under static condition (Prachi and Anushree, 2009).

CONCLUSION

Environmental pollution caused by the release of a wide range of compounds as a consequence of industrial progress has now assumed serious proportions. Textile dyes are one of the most prevalent chemicals in use today. With increasing usage of the wide variety of dyes in the industries pollution from the effluents has become increasingly alarming. Microbial decolorization and degradation is and environmentally friendly and cost – effective process. The fungal isolates were isolated from the effluent and soil samples from the contaminated sites. These isolates were subjected to initial screening through the decolorization studies on effluent dyes. The screened strains were then tested for their ability to decolorize three synthetic dyes namely, Reactive Red 120, Reactive Black 5 and Direct Red 81 and then final screening was done based on these studies. After final screening, one fungal isolate were selected. The fungal isolate were identified as Pleurotus ostreatus.

The various physical parameters such as temperature, pH, C:N ratio, culture incubation conditions were optimized for the decolorization of the three synthetic dyes by the fungal isolate. It was concluded that the fungal isolate were isolated from the samples of the dye contaminated sites showed higher synthetic dye removal per cent age. Thus, the fungal isolate can be used for the decolorization of textile dyes efficiently.

REFERENCES

Ashutosh kumar Verma, Chandralata Raghukumar, Pankaj Verma, Yogesh S. Shouche and Chandrakant Govind Naik (2010). ‘Four marine-derived fungi for bioremediation of raw textile mill effluents’, Biodegradation.21(2):217-233.


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Bergsten-Torralba, L.R, M.M. Nishikawa, D.F Baptista, D.P Magalhães, and da. M Silva (2009). ‘Decolorization of different textile dyes by Penicillium simplicissimum and toxicity evaluation after fungal treatment’, Brazilian Journal of Microbiology. 40:808-817. Casieri, L., Varese, G.C., Anastasi, A., Prigione, V., Svobodova, K., Filippelo Marchisio, V and C. Novotny.(2008). ‘Decolorization and Detoxication of Reactive Industrial Dyes by Immobilized Fungi Trametes pubescens and Pleurotus ostreatus’. Folia Microbiol. 53(1): 44–52. Chen M, Liu H, Wang W, Wang Y (2002).’Influence of supplemental nutrient on aerobic decolorization of Acid red 14 in an inactivated sludge’. J. Int. Microb. Biotechnol. 23(1):686-692. Fu, Y., and Viraraghavan, T. (2001) a. Fungal decoloration of dye waste water ,a review. Bioresource Technology. 79(8):251- 262. Fu, Y., and Viraraghavan, T. (2001). b. ‘Removal of acid blue 29 from aqueous solution by Aspergillus niger’. Am. Assoc. Text. Chem. Color. Rev.1(1):36-40.

Kodam. K.M, K.R.Gawai (2006).‘Decolorisation of reactive red 11 and 152 azo dyes under aerobic conditions’, Indian Journal of Biotechnology. 5:422-424. Knapp JS, Newby PS (1995). ‘Decolourization of dyes by wood rotting basidiomycete fungi’. Enzyme Microb. Technol. 17:664-668.

Koichi Harazono, Yoshio Wataanabe and Kazunori Nakamura (2003).‘Decolorization of Azo Dye by the White-Rot Basidiomycete Phanerochaete Sordida by Its Manganse Peroxidase’, Journal of Bioscience And Bio Engineering. 95(5):455-459. Prachi Kaushik and Anushree Malik (2009). ‘Microbial decolourization of textile dyes through isolates obtained from contaminated sites’, Journal of Scientific & Industrial Research. 68:325-331. Prachi Kaushik and Anushree Malik (2008). ‘Fungal dye decolourization: Recent advances and future potential’: Environ. Inter. 35(1):127-141. Mehmet.A, Mazmanci,Ali Unyayar, Emarh A.Erkurt, Nilay B.Arkci,Elif Bilen and Mustafa Ozyurt (2009).‘Colour removal of textile dyes by culture extracts obtained from White rot fungi’, African Journal of Microbiology Research. 3(10):585-589. Mohandass Ramya, Bhaskar Anusha, S. Kalavathy, and S. Devilaksmi (2007). ‘Biodecolorization and biodegradation of Reactive Blue by Aspergillus sp’, African Journal of Biotechnology. 6(12):1441-1445. Muhammad Asgher, Naseema Azim and Haq Nawaz Bhatti (2009).‘Decolorization of practical textile industry effluents by white rot fungus Coriolus versicolor IBL-04’: Biochemical Engineering Journal. 47(1-3):61-65. Shumaila Kiran, Shaukat Ali, M. Asgher and Farooq Anwar (2012).‘Comparative study on decolorization of reactive dye 222 by white rot fungi Pleurotus ostreatus IBL-02 and Phanerochaete Chrysosporium IBL-03’. African Journal of Microbiology Research. 6(15):3639- 3650.

Citation of this article: Muthukumaran P, PriyaM, Divya R, Indhumathi E, Keerthika C (2014). BIODECOLORIZATION OF REACTIVE DYES BY USINGPLEUROTUS OSTREATUS. Journal of

Biotechnology and Biosafety. 2(3):94-101

Source of Support: Nil Conflict of Interest: None Declared


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Research article

A SIMULTANEOUS METHOD DEVELOPMENT, VALIDATION AND CONFIRMATORY ANALYSIS OF AMOZ, AOZ, AHD AND SEM IN KATLA FISH (KATLA KATLA) AND BAGDA SHRIMP (PENIOUS MONODON) BY UPLC-MS/MS

(QPXE).

Md. Ashraful Alam*1, Talukdar Muhammad Waliullah2, Akter Mst Yeasmin2, Md. Serajul Islam1, Md. Manik Mia 1

1FIQC Laboratory, Matshya Bhaban, Ramna, Dhaka, Bangladesh

2Molecular and Cell Biology Laboratory, Bioscience Department, GSST, Shizuoka University. 836-Oya, Suruga-ku, Shizuoka ╤ 422-8529, Japan. *Corresponding author email: [email protected]

ABSTRACT A method has been developed to analyse AMOZ (5-methyle-morpholino-3-amino-2-oxazolidinone), AOZ (3-amino-2-oxazolidinone), SEM (semicarbazide) and AHD (1-aminohydantoin) in fish and shrimp. Samples were defatted with cold methanol and derivatized with HCl and 2-nitrobenzaldehyde. After derivatization at 37 ±2°C for 16± 2 hours (overnight) samples were neutralized by adding KH2PO4 and pH were adjusted to 7.0±0.5 with NaOH solution. Finally samples were extracted with ethyl acetate and evaporated to near dryness under nitrogen gas at 50°C. Finally residue was reconstituted in 1ml of 50 % methanol and transferred to vial by filtering through syringe filter (0.2µm) for analysis with LC-MS/MS. The method was validated in shrimp and fish matrix according to the criteria defined in Commission Decision 2002/657/EC. In case of shrimp sample the decision limit (CCα) was in the range of 0.13-0.19µg/kg and the detection capability (CCβ) was in the range of 0.22- 0.32µg/kg respectively, for nitrofuran metabolites (AMOZ, AOZ, AHD and SEM). In case of fish samples CCα value was in the range of 0.15-0.22µg/kg and CCβ value was in the range of 0.28-0.36µg/kg for nitrofuran metabolites all of which are less than set MRPL (1µg/kg). The mean recoveries were in the range of 90–108% for shrimp and that of 90-105% for fish. The precision of the method, expressed as RSD values for the within-laboratory reproducibility, for AMOZ, AOZ, AHD and SEM at the three levels of fortification (0.5, 1.0 and 1.5)µg/kg, was less than 15%.

Keyword: Nitrofuran metabolites, method development, validation, Fish and Shrimp, CCα and CCβ. __________________________________________________________________________________________


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INTRODUCTION The nitrofuran antibiotics have been widely used for the

treatment of infectious diseases in cattle, pigs, poultry and

aquaculture (M. N. Hassan et al.,. 2013). Nitrofuran parent

drugs, furazolidone, nitrofurazone, nitrofurantoin and

furaltadone and their related structures are depicted in Figure 1

(M. Vass et al.,. 2008). These parent compounds metabolise

rapidly after ingestion to form corresponding tissue bound

metabolites (Nouws and Laurensen, 1990; McCracken et al.,

1995). In vivo, these metabolites can be released by natural

stomach acids (Hoogenboom et al.., 1992); this fact is taken

into consideration in the isolation of metabolites for residue

analysis. If nitrofuran remains in food, it causes mutagenesis,

carcinogenicity and teratogenesis (Ebringer L et.al., 1982,

Czeizel AE et al.., 2001). It has been reported that

furazolidone overdose in mammals may not only cause muscle

convulsions but also can lead to nerve breakage throughout the

body (Chung-Wei Tsaia et al.., 2009). Nitrofurazone can also

inhibit sperm production in mice (Julia D. George et

al.,.1996). In both birds and mammals, nitrofurans are rapidly

metabolized following oral administration and the majority of

a dose is quickly eliminated in the urine, but metabolites bind

easily to tissues and can persist at low concentrations for

weeks following treatment (Craine & Ray, 1972, Vass et al.,

2008). The rapid metabolism of nitrofurans has made

screening for parent drugs difficult in food products, but the

development of assays that can detect nitrofuran metabolites

have been used to demonstrate the persistence of residues in

egg yolk and albumen (McCracken et al., 2001; Stachel et al.,

2006).

As a result of their rapid metabolism, nitrofuran parent

substances are not suitable for monitoring and typically their

metabolites are analyzed. For example 3-amino-2-

oxazolidinone (AOZ) is the metabolites of furazolidone,

which can be released from bound tissues under acidic

conditions and detected by reaction with 2-nitrobenzaldhyde

to produce 2-nitrophenylmethylene-3-amino-2-oxazolidinone

(NPAOZ) (M. Vass et al.., 2008), the occurring reaction is

shown in Figure 2 (Chung-Wei Tsaia et al.., 2009).

Because of the toxicity of nitrofuran, the European Union

(EU) banned the use of nitrofuran antibiotics in food-

producing animals (Commission Decision 2003/181/EC,

Cooper KM et al,. 2004) and set the minimum required

performance limit (MRPL: “minimum content of an analyte in

a sample, which at least has to be detected and confirmed”) for

the detection of nitrofuran residues (metabolites) in food of

animal origin at 1µg/kg (Commission Decision 2003/181/EC).

Thus, a sensitive and reliable method for the determination of

nitrofuran at residual levels is very important. In the past

decades, several analytical methods have been developed for

the screening and quantitation of nitrofuran metabolites in

foods and biological samples. Some methods already reported

for the determination of nitrofurans e.g. detection of AOZ

(Cooper KM et al., 2004) by enzyme immunoassay (ELISA)

has been used for the detection of AOZ (3-amino-2-

oxazolidone) in prawn tissue, quantitative determination of

four nitrofuran metabolites in chicken meat by HPLC-MSMS

(Mottier P et al., 2005), analysis of matrix-bound nitrofuran

residues in honey by HPLC-MSMS (Khong SP et al., 2004).

However, Ultra Performance LC (UPLC) and MS/MS

(Quattro Premier XE) is a more sophisticated technique

allowing a very effective isolation of analyte ions from the

noise-producing matrix. Following the EU decision

2002/657/EC the goal of present study is to optimize UPLC–

MS/MS technique for a simultaneous method development,

validation and confirmatory analysis of nitrofuran metabolites

(AMOZ, AOZ, AHD and SEM)) by assessing its derivatives

in Katla Fish (Katla katla) and Bagda shrimp (Penious

monodon) by UPLC-MS/MS(QPXE).

Journal of Biotechnology and BiosafetyVolume 2, Issue 3, May

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Parent Drug Nitrofurazone, mw: 198.14

Nitrofurantoin, mw: 238.16

Furazolidone, mw: 225.16

Furaltadone, mw: 324.29

Figure1: Structures of nitrofuranparent compounds(semicarbazide), NPSEM 3[(2-nitrophenyl)methylene]NPAHD [3-(2-nitrobenzylidenamino)-2,4-nitrobenzylidenamino)-2-oxazolidinone) NPAMOZ (5-(morpholinomethyl)-3-(2-nitrobenzylidenamino)nitrobenzylidenamino)-2-oxazolidinone-d5)

Journal of Biotechnology and Biosafety , May-June 2014, 102-112

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International, Peer reviewed, Open access, Bimonthly Online Journal

Metabolite DerivativeSEM, mw: 111.53 HCl

2-NP-SCA

AHD, mw: 151.55

2-NP-AHD

AOZ, mw: 102.09

2-NP-AOZ

AMOZ, mw: 201.22

2-NP-AMOZ

2-NP-AMOZ_D5, mw: 339.36

parent compounds metabolites and nitrophenyl derivatives. nitrophenyl)methylene]-hydrazinecarboxamide; Nitrofurantoin,

-imidazolidinedione];Furazolidone,AOZ (3-amino-oxazolidinone) and Furaltadone, AMOZ (3-amino-5-morpholinomethyl

nitrobenzylidenamino)-2-oxazolidinone), 2-NP-AMOZ_D5(5d5)



Derivative

SCA, mw: 208.17

AHD, mw: 248.19

AOZ, mw: 235.20

AMOZ, mw: 334.33

AMOZ_D5, mw: 339.36

nitrophenyl derivatives. nitrofurazone, SEM itrofurantoin, AHD (1-aminohydantoin),

-2-oxazolidinone), NPAOZ (3-(2-morpholinomethyl-1,3-oxazolidinone),

AMOZ_D5(5-(morpholinomethyl)-3-(2-


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Figure2: A. Metabolism of parent drugs (Furazolidone to tissue-bonded AOZ). B. Hydrolysis of tissue-bonded metabolites (Tissue-bonded AOZ to AOZ) and C. Derivatization with 2-NBA (2-nitrobenzaldehyde) to produce target analyte (AOZ to derivative NPAOZ)

MATERIAL AND METHODS Apparatus and Chemicals:

Micro pipette: eppendorf; Analytical balance(4 dp): Shimadzu AUY 220; Syringe filter: 4 mmPTFE 0.2µm (Waters, USA); Incubator with shaker: KullanmaKilavuzunu, ST 402; Nitrogen Evaporator (Organomation Associates Jnc.); Vortex mixer: Barnstead Thermolyne, M 16710-33; Test tubes: IWAKI TE32 Pyrex, Asahi, Indonesia; Ethylacetate and n-Hexane (HPLC grade); Acetonitrile and Methanol (HPLC and MS grade),

Sigma Aldrich, Germany; Sodium hydroxide (NaOH): Marks, Germany;

2-nitrobenzaldehyde (2-NBA): Marks, Germany; Dimethyl sulfoxide(DMSO): Merck Germany; Hydrochloric acid (HCl): 37% HCl (specific gravity

1.19), Marks, Germany; KH2PO4 (anhydrous); NaCl: RANKEM, S0160; Phosphate buffered saline(PBS); Purified Water (deionized) from Milli-Q apparatus

(Millipore, Bedford, USA); Nitrofuran standards (AMOZ, AOZ, SEM, AHD),

assay >99%, Sigma Fluka, Germany.


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General reagents: 0.5 mM ammonium acetate solution: Take 0.0192g

ammonium acetate was dissolved into 500mL deionized water.

2-NBA Solution: Weigh 151.2mg 2-nitrobenzaldehyde (Merck) into a 10mL volumetric flask, dissolve and make up to the mark with methanol. Prepare fresh every day.

HCl (0.2M): Take 8.3mL of 37% HCl (specific gravity 1.19) and dilute to 0.5 litre with water in a volumetric flask.

KH2PO4 (0.3M): Take 20.403g of anhydrous potassium dihydrogen phosphate and dissolve in 500mL water in a volumetric flask.

NaOH (1.0M): Take 20g sodium hydroxide and dissolve in 500mL water in a volumetric flask.

Stock standard AMOZ, d5-AMOZ and AOZ, 1000ppm: 10mg of each standard (AMOZ, d5-AMOZ and AOZ) was dissolved separately in three separate 10mL volumetric flask and made upto marked with methanol and stored in a refrigerator for 12 months.

Stock standard AHD (as HCl salt), 1000ppm: 13.16mg of standard was dissolved in a 10mL volumetric flask made upto the marked with methanol and stored in a refrigerator for 12 months.

Stock standard SEM (as HCl salt), 1000ppm: 14.85mg of standard was dissolved in a 10 ml volumetric flask using DMSO and made upto the marked with methanol and stored in a refrigerator stored in a refrigerator for 12 months.

Mixed standard (AMOZ, AOZ, AHD, SEM), 10ppm: Pipette 100µL of each stock standard(1000ppm) of SEM, AHD, AOZ and AMOZ into a 10mL volumetric flask and make up to the mark with methanol and stored in a refrigerator for a maximum of 03 months.

10ppm d5-AMOZ internal standard: Pipette 100µLof stock standard d5-AMOZ (1000ppm) into a 10mL volumetric flask and make up to the mark with methanol.

10ng/mL mixed working standards (AMOZ, AOZ, AHD, and SEM): freshly prepared from 10ppm mixed standard by diluting with methanol.

10ng/mL d5-AMOZ working standard: freshly prepared from 10ppm d5-AMOZ by diluting with methanol.

Solution of NP derivatives was prepared in same way. Samples: Shrimp and fish samples were pasted separately with blender after removing shell and eight samples [reagent blank, matrix blank, matrix with internal standard(IS) blank and quality control (QC)] were taken as quality check samples and another seven were taken to make calibration curve (0.25 to 5.00ppb)for each matrix. All these samples and analytes were weighed out (1.00 ± 0.01g) into 50 ml screw capped polypropylene centrifuge tube separately.

Extraction Procedure: (Method was developed by self)

Add 8mL cold methanol to each tube & vortex for 1 minute and centrifuge at 4000 rpm for 4 minutes.

Discard the methanol and repeat using 4mL methanol. Add 5mL of 0.2 M HCl and 50µL of 2-

nitrobenzaldehyde Add 200µL of 10ng/mL of d5-AMOZ to all tubes for

equivalent concentration of 2.00ppb and required volume of nitrofuran (4 mixed) standards (10ng/mL) was added to the standard curve tubes to make equivalent concentration 0.25 to 5ppb and that of QC samples 1.00ppb (the EU MRPL)except reagent blank and matrix blank.

Incubate all tubes in a water bath at 37 ±2 °C for 16± 2 hours (overnight). Avoid exposure of samples to light.

Neutralize the samples by adding 500µL of 0.3 M KH2PO4 to each tube and adjust to pH 7.0 ±0.5 with 1M NaOH solution.

Add 4mL ethyl acetate to each tube and vortex for 1 minute.

Centrifuge for 8 minutes at 4000 rpm and collect the organic layer (upper layer) into a clean tube.

Repeat the extraction using 4mL ethyl acetate, centrifuge and combine the organic layers.

Evaporate to near dryness under nitrogen gas at 50°C. Add1mL50% methanol and vortex for 1minute to reconstitute the sample. Pass the sample through a 0.2µm syringe filter and collect in a vial for subsequent LC-MS/MS analysis.


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UPLC-MS/MS Analysis:

Software: Masslynx v4.1 LC Identity: ACQUITY UPLC®

Waters, USA

Column:AQUITY UPLC BEH C18, 1.7µm, 2.1x100 mm (Waters, USA), Solvent A: 0.5 mM ammonium acetate buffer solution Solvent B: Methanol, Injection Volume (L): 10, Column temp: 350C, Sample Temp: 100C

LC Separation Method: Gradient MS Method Parameters

Instrument: Quatro Premier XE, Instrument Identifier: VAB1275,

Function type: MRM (multiple reaction monitoring), MRM method was developed by using NP derivatives of nitrofuran metabolites.

Ion Mode: ES+, Inter Channel Delay (Sec): 0.005, InterScan Time(sec): 0.005, Span (Daltons): 0.2,

Start time (Min): 0.00, End Time (Min): 08, Dwell time (Sec): 0.025,

Capillary(kV): 3.50, Cone(V): 30, Extractor(V): 3, RF Lens(V): 0.10, Source Temperature:120, Desolvation Temperature: 400,LM1 Resolution: 12.0,

HM1 Resolution: 12.0, Ion Energy 1: 0.5, Entrance voltage: 2, Exit voltage:

2, LM2 Resolution: 12.0, HM2 Resolution: 13.0, Ion

Energy 2: 1.0, Multiplier voltage: 645, Cone Gas Flow(L/Hr): 50, Desolvation Gas Flow(L/Hr): 800, Collision gas:

Argon @ 3.7 x 10-3 mbar, Collision Gas Flow(mL/Min):0.17 (As required for collision gas pressure )

Formulas (Calculation of Results) The nitrofuran metabolites quantified by means of a calibration prepared using pre-formed 2-nitrophenylderivatives curve at six calibration levels ranging from 0.25 to 5.00 µg/kg of the underivatised metabolites.

Ion Ratio, R = Peak area of primary ion (PAPI) Peak area of secondary ion (PASI) Response factor (RF)

= PAPI of interested substance x ISC Peak area of internal standard ion CAP concentration, X = (RF-b)/a

Where, ISC= Internal Standard Concentration, a=Slope of calibration curve, b= intercept of calibration curve.

Confirmation criteria: The selectivity of this method is judged by the use of two transitions for each analyte which count for 4 identification points (IPs), as defined by the EU criteria set out in Commission Decision 2002/657/EC. The nitrofurans are listed in Table II of Commission Regulation (EC) No 37/2010 (unauthorized compounds with no MRL). This means that the minimum number of IPs to consider for their identification is four. Consequently our method fulfils this requirement. Nitrofuran metabolites were considered as positively identified in the samples when the peak area ratio of the various transitions were within the tolerance set by Commission Decision 2002/657/EC. In addition, the relative retention time of the analyte must be equal to that of the calibration standard to within ± 2.5%

RESULTS AND DISCUSSION

UPLC_MS–MS detection The detector (QPXE) was firstly operated in positive ESI+ MS mode to select characteristic ions as the precursors of NP-SEM, NP-AHD, NP-AOZ and NP-AMOZ and its deuterated internal standard NP-AMOZ_D5(Figure2). The compounds were then analyzed by ESI+ MS–MS in a positive ionization product ion scan mode by selecting m/z 209.00, 249.00, 236.29, 335.41 and 340.41 ions as the precursor ion, respectively. The collision-induced dissociation (CID) experiments of these ions, giving rise to m/z 166.10 and 192.10 for NP-SEM, 104.00 and 133.90 for NP-AHD, 104.06 and 134.04 for NP-AOZ, 291.20 and 100.09 for NP-AMOZ and 296.27 for NP-AMOZ_D5 (Figure 4). The transition which showed higher response considered as a Quantifier and

Journal of Biotechnology and BiosafetyVolume 2, Issue 3, May

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other as a Qualifier. The selected transitions and their MS–MS conditions are given in Table 3separation was done by UPLC system and tgradient method is shown the Table 1. There were no peak in solvent blank, reagent blank and matrix blank,case of matrix_ISand in case of spike sample each transition showed separate peak. (Figure 4). Analytical performance Method validation was carried out according to criteria described in Decision 2002/657/EC. The parameters taken into account were: response linearity, decision limit (CCα), detection capability (CCβ), reliability and accuracy. The

Time(min) 0.00 1.00 3.25 5.50 6.70 8.00

Table 2: Decision Limit & Detection Capability (CCα & CCβ) for Analyte

CCα (µg/kg)

SEM AOZ AHD AMOZ

Figure 3: A comparative representation of CCα and CCβ

SEM

AOZ

AHD

AMOZ

Journal of Biotechnology and Biosafety , May-June 2014, 102-112

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The selected transitions and their optimal 3. The compound

separation was done by UPLC system and the developed . There were no peak in

and matrix blank, a single peak in in case of spike sample each transition

carried out according to criteria described in Decision 2002/657/EC. The parameters taken into account were: response linearity, decision limit (CCα), detection capability (CCβ), reliability and accuracy. The

calibration curve showed a good lineafrom 0.25 to 5.0ng/g with the cor0.9985. The decision limit(CCβ)were calculated using the procedure set out in ISO Guide 11843, as described in Commission Decision 2002/657/EC. The validation data were generated (3 levels and seven replicates per level) on each of three days. The value of (CCα) was in the range of 0.was in the range 0.22 to 0.3matrix (Table 2 and Figure(1ng/g). The trueness was expressed in terms of recovery rates. The results are presented in

Table 1: Gradient conditions: Pump A1 Pump B1 Flow(mL/min) 95 5 0.250 95 5 0.250 1 99 0.250 1 99 0.250 95 5 0.250 95 5 0.25

Decision Limit & Detection Capability (CCα & CCβ) for shrimp and fish matrixShrimp Fish

CCα (µg/kg) CCβ (µg/kg) CCα (µg/kg) CCβ (µg/kg)

0.19 0.32 0.15 0.280.14 0.23 0.22 0.360.13 0.22 0.18 0.320.15 0.28 0.19 0.31

A comparative representation of CCα and CCβ in Shrimp and Fish

AMOZ



calibration curve showed a good linearity in the conc. range ng/g with the correlation coefficient above

. The decision limit (CCα) and detection capability )were calculated using the procedure set out in ISO

Guide 11843, as described in Commission Decision 2002/657/EC. The validation data were generated (3 levels and seven replicates per level) on each of three days. The

was in the range of 0.13 to 0.22ng/g and CCβ to 0.36ng/g for both shrimp and fish

and Figure 3) which was less than MRPL The trueness was expressed in terms of recovery rates.

he results are presented in Table 4.

Curve 1 6 6 6 6 6

shrimp and fish matrix

CCβ (µg/kg)

0.28 0.36 0.32 0.31

in Shrimp and Fish


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Table 3: The selected transitions of nitrofuran metabolites and their optimal MS–MS conditions:

Ions monitored Quantifier /Qualifier Cone Voltage(V) Collision Energy(V)

NP-SEM transitions

m/z208.99165.78, Quantifier 24 9

m/z208.99191.83, Qualifier 24 13

NP-AOZ transitions m/z236.03133.67, Quantifier 29 13

m/z 236.03103.65, Qualifier 29 23

NP-AHD transitions m/z249.02133.67, Quantifier 29 11

m/z249.02103.65, Qualifier 29 23

NP-AMOZ transitions m/z335.25291.08, Quantifier 27 11

m/z 335.25127.62, Qualifier 27 21

NP-AMOZ-D5 transition m/z340.29 296.13, Quantifier 24 11

Figure 4: UPLC-MS/MS Chromatograms of daughter ions of nitrofuran metabolites and internal Standard (IS) AMOZ_D5


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Table 4: Validation data of AHD, AOZ, SEM and AMOZ in shrimp and Fish at 3 different concentrations

DISCUSSION

Nitrofuran metabolites were considered positively identified in the samples when the peak area ratio of the various transitions were within the tolerance set by Commission Decision 2002/657/EC The precursor and daughter ions obtained in the result have a good agreement with previous findings (Mottier P et al., 2005, Khong SP et al., 2004) which indicate the compounds were identified accurately. The gradient method for compounds separation was developed by methanol and 0.5mM ammonium acetate in water which gives a good chromatographic peak shape without any peak tailing or peak fronting. The trend analysis of the result of quality control samples of this method in quality control chart prepared by previous data explains the experiments of whole year were in good and homogeneous condition. In case of shrimp samples

the decision limit (CCα) were in the range of 0.13-0.19ng/g and detection capability (CCβ) were in the range of 0.22-0.32ng/g and in case of fish samples CCα value were in the rage of 0.15-0.22ng/g and CCβ value was in the range of 0.28-0.36ng/g all of which are less than MRPL (1ng/g) that explains that the method was good enough for analysis. As there was no peak in solvent blank, reagent blank, matrix blank(negative sample) and a single peak in case of matrix with internal standard (IS) which indicates no contamination was found in sample, solvent and in the extraction process. The performance characteristics of the method presented in this paper indicate that it may be preferably used in food analysis for nitrofuran control.

Shrimp

Fish

Analyte

Fortification Level

Overall Mean

(µg/kg)

Overall Recovery

(%)

Within Day

CV

Between Day CV

Intermediate

Precision CV

Overall Mean

(µg/kg)

Overall Recovery

(%)

Within Day

CV

Between Day

CV

Intermediate

Precision CV

AHD

0.50 0.51 101 8.2 2.0 8.4 0.50 100 8.1 2.3 5..3

1.00 1.02 102 5.0 5.9 7.7 1.01 101 5.0 4..5 5..6

1.50 1.46 97 2.7 2.4 3.7 1.45 97 2.6 2.7 3.6

AOZ

0.50 0.47 94 6.9 7.2 10.0 0.46 92 6.9 5.6 8.7

1.00 0.93 93 6.1 4.6 7.6 0.92 92 6.1 5.3 7.4

1.50 1.43 95 2.7 2.3 3.6 1.41 94 2.5 2.4 3.6

SEM

0.50 0.52 104 5.2 2.4 5.4 0.51 102 5.1 2.8 5.8

1.00 1.01 101 6.3 4.3 3.4 1.01 101 6.1 4.5 4.5

1.50 1.55 103 3.2 2.6 4.5 1.50 100 3.3 2.9 4.9

AMOZ

0.50 0.45 90 7.0 2.8 7.6 0.49 98 5.6 2.9 7.6

1.00 0.93 93 2.6 8.8 9.2 0.96 96 2.7 4.7 4.6

1.50 1.44 96 2.2 5.1 5.6 1.47 98 2.3 5.2 3.6


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CONCLUSION The method was developed and validated for qualitative and qualitative measurement of nitrofuran metabolites in fish and shrimp muscles. The range of CCα (0.13-0.22 ng/g) and CCβ (0.22-0.36ng/g) values for all nitrofuran metabolites investigated suitably met the EU criteria and can be used for food control analysis.

Acknowledgement

We would like to acknowledge the Deputy Director of Fish Inspection and Quality Control Laboratory for giving us a scope of this work. We express our sincere thanks to all officers and staffs of the laboratory for helps and cooperation during work. We also acknowledge Dr. Glenn Kennedy, Chemical Surveillance Branch, Agrifood and Bioscience Institute, Northern Ireland, UK, for his sincere guidance and helping in the validation data calculation.

REFERENCES

Chung-Wei Tsaia, Chi-Hsin Hsua and Wei-Hsien Wanga (2009), Determination of Nitrofuran Residues in Tilapia Tissue by Enzyme-Linked Immunosorbent Assay and Confirmation by Liquid Chromatography Tandem Mass Spectrometric Detection, Journal of the Chinese Chemical Society, 56, 581-588

Commission Decision 2003/181/EC, http://ec.europa.eu/food/food/chemical safety/residues/third_countries _en.htm

Cooper KM, Elliott CT, Kennedy DG. (2004), Detection of 3-amino-2-oxazolidinone (AOZ), a tissue-bound metabolite of the nitrofuranfurazolidone, in prawn tissue by enzyme immunoassay.US National Library of MedicineNational Institutes of Health, Food AdditContam. Sep; 21(9):841-8.

Craine, E.M. & Ray, W.H. (1972) Metabolites of furazolidone in urine ofchickens. Journal of Pharmaceutical Sciences, 61, 1495–1497.

Czeizel AE, Rockenbauer M, Sørensen HT, Olsen J.(2001) Nitrofurantoin and congenital abnormalities. Eur J Obstet Gynecol Reprod Biol. Mar; 95(1):119-26.

Ebringer L, Subík J, Lahitová N, Trubacík S, Horváthová R, Siekel P, Krajcovic J. (1982), Mutagenic effects of two nitrofuran food preservatives. US National Library of MedicineNational Institutes of Health;29 (6):675-84.

Hoogenboom L.A.P., Berghmans M.C.J., Polman T.H.G., Parker R., Shaw I.C. (1992): Depletion of protein-bound furazolidone metabolites containing the 3-amino-2-oxazolidinone side-chain from liver, kidney and muscle tissues from pigs. Food Additives and Contaminants, 9, 623–630.

Julia D. George, Patricia A. Fail, Thomas B. Grizzle, and Jerrold J. Heindel (1996); Nitrofurazone: Reproductive Assessment by Continuous Breeding in Swiss Mice1 Fundamental and applied toxicology 34, ARTICLE NO. 0175, 56-66

Khong SP, Gremaud E, Richoz J, Delatour T, Guy PA, Stadler RH, Mottier P. (2004); Analysis of matrix-bound nitrofuran residues in worldwide-originated honeys by isotope dilution high-performance liquid chromatography-tandem mass spectrometry. US National Library of MedicineNational Institutes of Health. J Agric Food Chem. 52(17): 5309-15

McCracken R.J., Blanchflower W.J., Rowan C., Mccoy M.A., Kennedy D.G. (1995): Determination of furazolidone in porcine tissue using thermospray liquid chromatography-mass spectrometry and a study of the pharmacokinetics and stability of its residues. Analyst, 120, 2347–2351.

McCracken, R.J., Spence, D.E., Floyd, S.D. & Kennedy, D.G. (2001) Evaluation of the residues of furazolidone and its metabolite, 3-amino-2-oxazolidinone (AOZ), in eggs. Food Additives and Contaminants, 18, 954–959.

M.N. Hassan, M. Rahman, M.B. Hossain, M.M. Hossain, R. Mendes, A.A.K.M. Nowsad (2013). Monitoring the presence of chloramphenicol and nitrofuran metabolites in cultured prawn, shrimp and feed in the Southwest coastal region of Bangladesh. The Egyptian Journal of Aquatic Research. 39(1):51-58, http://dx.doi.org/10.1016/j.ejar.2013.04.004

Mottier P, Khong SP, Gremaud E, Richoz J, Delatour T, Goldmann T, Guy PA. (2005).“Quantitative determination of four nitrofuran metabolites in meat by isotope dilution liquid chromatography-electrospray ionisation-tandem mass spectrometry”. J Chromatogr A. Mar 4;1067 (1-2):85-91.


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M. Vass, K. Hruska, M. Franek (2008), Nitrofuran antibiotics: a review on the application, prohibition and residual analysis VeterinarniMedicina, 53, (9): 469–500

Nouws J.F.M., Laurensen J. (1990): Postmortal degradation of furazolidone and furaltadone in edible tissues of calves. Veterinary Quarterly, 12, 56–59.

Stachel, C., Bock, C., Hamann, F. & Gowik, P. (2006) Residues of several nitrofurans in egg. Journal of Veterinary Pharmacology and Therapeutics, 29 (Suppl. 1), 143–144.

2002/657/EC: Commission Decision of 12 August 2002 implementing Council Directive 96/23/EC concerning the performance of analytical methods and the interpretation of results (Text with EEA relevance) (notified under document number C (2002) 3044). http://ec.europa.eu/food/food/chemicalsafety/residues/ lab_analysis_en.htm

Citation of this article: Md. Ashraful Alam, Talukdar Muhammad Waliullah, Akter Mst Yeasmin, Md. Serajul Islam, Md. Manik Mia (2014). A SIMULTANEOUS METHOD DEVELOPMENT,

VALIDATION AND CONFIRMATORY ANALYSIS OF AMOZ, AOZ, AHD AND SEM IN KATLA FISH (KATLA KATLA) AND BAGDA SHRIMP (PENIOUS MONODON) BY UPLC-MS/MS

(QPXE).Journal of Biotechnology and Biosafety. 2(3):102-112

Source of Support: Nil Conflict of Interest: None Declared


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Research article ANTILIPASE ACTIVITY: CRATAEVA NURVALA AND ACACIA CATECHU (L.)

_________________________________

Hari Venkatesh K R1 Chethana G. S2* _________________________________ 1Manager, R & D, Sri Sri Ayurveda Trust, Bangalore, Karnataka, India 2 Research Associate, R & D, Sri Sri Ayurveda Trust, Bangalore, Karnataka, India *Corresponding author email id: [email protected]

ABSTRACT: antilipase activity is defined as inhibition of lipase enzyme inturn inhibiting the accumulation of cholesterol in the body. The degradation of FFA may result in increased Cholesterol & Obesity. The idea of inhibition of lipase enzyme may help in the controlled release of free fatty acids in the body thereby decreasing the cholesterol & fat content in the body. Some of the aqueous extract of the plants like Crataeva nurvala bark and Acacia catechu (L.) showed a significant in antilipase activity as 40.09% and 52.74% of inhibition.

Keywords: Triglycerols, FFA, Cholesterol, Antilipase, kadira, varuna _____________________________________________________________________________________________

INTRODUCTION: Dietary lipids represent the major source of unwanted calories; therefore, lipid metabolism is a vital and subtle balance that maintains energy homeostasis. Inhibition of pancreatic lipase is an attractive targeted approach for the treatment of obesity. (C.D. Zheng, et al, 2010). The lipases catalyze wide range of reactions, including hydrolysis, inter-esterification, alcholysis, acidolysis, esterification and aminolysis. They catalyse the hydrolysis of fatty acid ester bond in the triacylglycerol (TAG) and release free fatty acids (ffa). The reaction is reversible. (Vakhlu, J. and Kour, A. 2006). Crataeva nurvala bark contains a variety of the bioactive phytochemical constituents in medicinal plantswhich include flavonoids, phenolic compounds, tannins, anthracene derivatives, and essential oils. (Dugganaboyana Guru Kumar et al., 2012). Crataeva nurvala belong to family Capparidaceae commonly known as Varuna, is an evergreen tree indigenous to India. It is reported that C. nurvala traditionally being used in treating blood flow, waste elimination and breathing problems,

fever and metabolic disorders, joint lubrication, skin moisture, wound healing, memory loss, heart and lung weakness and weak immune system. (Atanu Bhattacharjee et al.,2012)

Acacia catechu (L.) willd, commonly known

as Khadira, is widely used in Ayurveda for the

treatment of diseases. Preliminary analysis of various

functional groups revealed the presence of alkaloids,

tannin, saponins, carbohydrate, starch, steroid and

proteins. (Dhruve K et al., 2011). It is reported that

bark of Acacia catechu contain alkaloids and many

other very potent active components which shows

anti-microbial activity so for management of wounds

and burns it also acts as a disinfectant which reduces

the chances of infections at the site of wound. Due to

presence of alkaloids and other active constituents it

is used in many dermatological disorders. A

combination of cinnamon and extract of Acacia

catechu is given to treat diarrhea. (Muhammad Anis

Hashmat, Rabia Hussain, 2013)


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MATERIALS AND METHOD: (Oben J., et al., 2010) Lipase inhibitory activity: Inhibition of lipase by the aqueous extract of selected herbs was determined using a modified assay described by Oben J., et al., 2010

1. Briefly, a suspension containing 1% (v/v) of

triolein, and 1% (v/v) Tween 40 in 0.1M phosphate buffer (pH 8) from IP was prepared and emulsified. [ 1% triolein=1mL in 100ml and 1% tween 40=1ml in 100mL]

2. Assays were then initiated by adding 800 μL of the triolein emulsion to 200 μL of porcine pancreatic lipase 0.1gm (modified from the protocol) pancreatic in 15 mL 0.1M phosphate buffer at pH 8.0) and 200 μL of extract (or 0.1M Phosphate buffer, pH 8).

3. The contents were mixed and the absorbance measured immediately at 450 nm and designated as T0.

4. The test tubes were incubated at 37°C for 30 min and at the end of the incubation; the absorbance at 450 nm was recorded and designated as T30.

5. The variation in absorbance = [A450 (T0) - A450 (T30)] was calculated for both control and the treatment and the % inhibition was calculated using the formula:

% Inhibition = ([A450Control - A450Extract] /

A450Control) × 100

Where, A = absorbance of the sample, B = absorbance of blank (no extract), and C = absorbance of control. RESULTS AND DISCUSSION: Table 1 shows the percentage inhibition of antilipase activity of the aqueous extract of the kadira and varuna. Studies have shown that the pharmacological activities of these plants are attributable to the presence of secondary metabolites such as polyphenols, saponins, tannins, terpenes, flavonoids and alkaloids that are active inhibitors of pancreatic lipase. One reason why some of the plant extracts used in the study demonstrated high anti-lipase activity could be due to higher contents of bioactive compounds in their tissues (Muhammad Abubakar Ado et al., 2013). Therefore we can conclude that the herbal extract in this study contains these secondary metabolites which is responsible for anti lipase activity. Table no. 1: The percentage of inhibition is described in the table given below. Sl.no Aqueous extract of

herbs Percentage of inhibition

1 Kadira (Acacia catechu heart wood)

52.74%

2 Varuna (Crataeva nurvala bark)

40.07%

CONCLUSION:

Aqueous extracts of the kadira and varuna shows a significant antilipase activity. These herbs could be useful in the management of some chronic diseases like hyperlipidemia & increased levels of cholesterol. This study of inhibition of lipase enzyme is one

aspect of treating cholesterol. The herbal aqueous extract of kadira and varuna showed significant effect. Much more work has to be done considering many more aspects.


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REFERENCES: Atanu Bhattacharjee, Shastry Chakrakodi Shashidhara, Aswathanarayana (2012). Phytochemical and ethno-pharmacological profile of Crataeva nurvala Buch-Hum (Varuna): A review. Asian Pacific Journal of Tropical Biomedicine.S1162-S1168. Cheng-Dong Zheng, Ya-Qing Duan, Jin-Ming Gao1, Zhi-Gang Ruan. Screening for Anti-lipase Properties of 37 Traditional Chinese Medicinal Herbs. J Chin Med Assoc.2010; 73(6):319–324. Dhruve K, Harish C R, Prajapati P K. Pharmacognostical evaluation of Acacia catechu wild, heartwood with special reference to tyloses (2011). Int J Green Pharma.5:336-341. Dugganaboyana Guru Kumar, Purandekkattil Deepa,

Muthaiyan A. Rathi, Periasamy Meenakshi and Velliyur K. Gopalakrishnan(2012). Modulatory effects of Crataeva nurvala bark against testosterone and N-methyl-N-nitrosourea-induced oxidative damage in prostate of male albino rats. Pharmacogn Mag. 2012 Oct-Dec; 8(32): 285–291.

Etoundi C.B., Kuaté D., Ngondi J.L., Oben J. Anti-amylase, anti-lipase and antioxidant effects of aqueous extracts of some Cameroonian spices. Journal of Natural Products. 3(2010):165-171 Jyoti Vakhlu, Avneet Kour (2006). Yeast lipases: enzyme purification, biochemical properties and gene cloning. Electronic Journal of Biotechnology. 9(1): 69-85 Muhammad Anis Hashmat, Rabia Hussain (2013). A review on Acacia catechu Wild. INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS. 5(1):593-600. Muhammad Abubakar Ado, Faridah Abas, Abdulkarim Sabo Mohammed and Hasanah M. Ghazali (2013). Anti- and Pro-Lipase Activity of Selected Medicinal, Herbal and Aquatic Plants, and Structure Elucidation of an Anti-Lipase Compound. Molecules. 18: 14651-14669. doi:10.3390/molecules181214651

Citation of this article: Hari Venkatesh K R, Chethana G S (2014). ANTILIPASE

ACTIVITY: CRATAEVA NURVALA AND ACACIA CATECHU (L.). Journal of

Biotechnology and Biosafety. 2(3): 113-115

Source of support: Nil Conflict of interest: None Declared .

Journal of Biotechnology and Biosafety

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