African Journal of Biotechnology Volume 16 Number 4, 25 January 2017 ISSN 1684-5315
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African Journal of Biotechnology
Table of Content: Volume 16 Number 4 25 January, 2017
ARTICLES
Microbial production of carotenoids – A review 139 Ligia Alves da Costa Cardoso, Karen Yuri Feitosa Kanno and Susan Grace Karp
Relationship analysis between gene expression profiles and rat liver cirrhosis occurrence 147 Gaiping Wang, Congcong Zhao, Meng Chen, Shasha Chen, Cuifang Chang and Cunshuan Xu
Molecular identification, micronutrient content, antifungal and hemolytic activity of starfish Asterias amurensis collected from Kobe coast, Japan 163 Farhana Sharmin, Shoichiro Ishizaki and Yuji Nagashima
Genetic diversity among Sawakni, Berberi and Najdi sheep breeds in Saudi Arabia using microsatellites markers 171
Ahmed Hossam Mahmoud, Ayman swelum, Mohammad Abul Farah, Khalid. Alanazi, Ahmed Rady, Mahmoud Salah, Nabil Amor and Osam Mohammed
Vol. 16(4), pp. 139-146, 25 January 2017 DOI: 10.5897/AJB2016.15763 Article Number: EB8DD9A62533 ISSN 1684-5315 African Journal of Biotechnology Copyright © 2017 Author(s) retain the copyright of this article http://www.academicjournals.org/AJB
Review
Microbial production of carotenoids – A review
Ligia Alves da Costa Cardoso1*, Karen Yuri Feitosa Kanno1 and Susan Grace Karp2
1Mestrado Profissional em Biotecnologia; Universidade Positivo; Curitiba – PR, Brasil. 2Programa de Pós Graduação em Engenharia de Bioprocessos e Biotecnologia; Universidade Federal do Paraná; Curitiba – PR, Brasil.
Received 1 November, 2016; Accepted 12 January, 2017
Carotenoids are natural pigments that can be synthesized by various microorganisms, including bacteria, yeasts, filamentous fungi and microalgae. These pigments comprise around 700 different structures with peculiar colors and biological properties that are beneficial to health. Advantages of biotechnological production of carotenoids include the ability of microorganisms to use low cost substrates, the optimized control of cultivation, minimized production time and the natural origin of the synthesized pigments. Techniques for separation and purification of carotenoids are well established at laboratory scale, however the development of processes that can be economically scaled-up is essential for industrial production.
Key words: Carotenoids, microorganisms, biotechnology, natural pigments.
CAROTENOIDS PRODUCED BY MICROORGANISMS
Carotenoids are natural pigments that can be oxidation and isomerisation, and also to light, heat, acids synthesized by various microorganisms, including and oxygen (Amorim-Carrilho et al., 2014; Mata-Goméz bacteria, yeasts, filamentous fungi (Berman et al., 2015) et al., 2014). and microalgae (Henríquez et al., 2016). Carotenoids are The production of carotenoids from microorganisms yellow, orange or red in color and because of their proven arose to compete with the production of carotenoids by activity as pro-vitamin A and antioxidant, they are used in chemical processes, as an alternative to synthetic food, cosmetics and feed industries (Johnson and additives (Bhosale, 2004). Due to the ability of various Schroeder, 1995a). These pigments comprise around microorganisms to synthesize carotenoids, biotechnology 700 different chemical structures with peculiar colors and has been considered the best alternative for the market biological properties (Stafsnes et al., 2010). The of natural pigments, which is evident from the increase of carotenoids are lipophilic isoprenoid molecules (Christaki studies about microbiological dyes (Sandmann, 2001). et al., 2013) containing double bonds that form a light Advantages of biotechnological production include the absorbing chromophore, which gives their staining ability of microorganisms to use low cost substrates, the characteristics (Figure 1). Because of these double optimized control of cultivation, minimized production bonds, carotenoids are sensitive to reactions such as time and the natural origin of the synthesized dyes (Wu
*Corresponding author. E-mail: [email protected]. Tel: + 55 41 33173449.
Author(s) agree that this article remains permanently open access under the terms of the Creative Commons Attribution License 4.0 International License 140 Afr. J. Biotechnol.
Zeaxanthin Lycopene
Torularhodin Astaxanthin
-carotene Torulene
Lutein Canthaxanthin
Figure 1. Molecular structures of carotenoids. Adapted from Sperstad et al. (2006) and Eldahshan and Singab (2003).
and Liu, 2007; Tinoi et al., 2005). Modern biotechnology techniques such as screening Excessive consumption of artificial pigments presents methods based on 16S rDNA and HPLC-Diode array-MS serious health risks due to their toxicity, and these allowed the isolation of new bacteria belonging to the include allergic reactions, cancer, asthma, abdominal families Sphingobacteriaceae and Sphingomonadaceae pain, nausea, hepatic and renal damage (Srivastava, producing zeaxanthin (Asker et al., 2012). The study of 2015; Wrolstad and Culver, 2012). Natural carotenoids, Thawornwiriyanun et al. (2012) demonstrated that the however, present bioactive properties that could improve bacteria Sphingomonas natatoria KODA19-6, identified health, and many of them constitute a part of the human based on the 16S rRNA gene sequence and associated diet (Chen et al., 2012). Carotenoids in the diet are with sponges that produce bioactive pigments in the Gulf composed of lutein, zeaxanthine, β-cryptoxanthin, α- of Thailand, presented a productivity of 6.27 μg/L.h of carotene, β-carotene and lycopene (Berman et al., 2015). zeaxanthin in optimal growth conditions. Individuals who consumed carotenoids such as lutein and Studies of metabolic engineering for enhancing zeaxanthin presented reduced risk of breast cancer and carotenoids production by preventing the accumulation of lower incidence of eye problems (Eliassen et al., 2012). toxic metabolites and flux imbalance improved The intake of lycopene presented health benefits significantly the heterologous production of zeaxanthin in because of its high antioxidant power, reducing the risk of Escherichia coli, reaching 722.46 mg/L and 23.16 mg/g heart failure and prostate cancer (Raghavarao and dry cell weight. The expression of the genes of the Jampani, 2015). The consumption of foods that contain mevalonate (MEV) pathway from Saccharomyces β-carotene reduces the risk related to cardiovascular cerevisiae using the tunable intergenic regions (TIGRs), disease, which is the leading cause of death worldwide. and the dynamical regulation of the TIGR-mediated MEV Also, foods supplemented with β-carotene demonstrated pathway by using isopentenyl pyrophosphate and protection against esophageal cancer (Woodside et al., farnesyl pyrophosphate responsive promoter was 2014). performed, for preventing the accumulation of the toxic Some microbial carotenoids already produced metabolites (Shen et al., 2016). industrially include ankaflavin (Monascus sp.), anthraquinone (Penicillium oxalicum), monascorubramin (Monascus sp.), riboflavin (Ashbya gossypi), Carotenoids produced by bacteria rubropunctatin (Monascus sp.) and β-carotene (Blakeslea trispora). Others still under research or development Several bacteria have been studied due to the stage include astaxanthin, canthaxanthin, lycopene, biotechnological potential for the production of pigments, naphtoquinone, rubrolone, torularhodin and zeaxanthin among them the bacteria belonging to the thermophilic (Fraser and Bramley, 2004). Table 1 presents the halophilic species Halococcus morrhuae and Zeaxanthin productivity or yield of carotenoids depending on the Halobacterium salinarum that Lycopene present red and orange choice of the substrate and microorganism. colonies (Grant and Larsen, 1989). The H. salinarum
Torularhodin Astaxanthin
-carotene Torulene
Lutein Canthaxanthin Cardoso et al. 141
Table 1. Productivity or yield of carotenoids depending on the choice of the substrate and microorganism.
Microorganism Carotenoid Substrate Productivity References Astaxanthin, β-carotene, canthaxanthin, neoxanthin, violaxanthin and Nannochloropsis gaditana - 393.0 - 773.7 mg.kg-1 dry biomass Millao and Uquiche, 2016 zeaxanthin
Dietzia natronolimnaea HS-1 Canthaxanthin Glucose 7.67 mg.L-1 Gharibzahedi et al., 2012
Torularhodin, Sporobolomyces ruberrimus H110 Glucose and pure glycerol 0.0064 g.L-1h-1 Cardoso et al., 2016 torulene, β-carotene and γ-carotene
Paracoccus bacterial strain A-581-1 β-Carotene, echinenone, anthaxanthin, phoenicoxanthin, β- Sources of carbon, nitrogen and Hirasawa and Tsubokura, 91.9 mg.L-1 (FERM BP-4671) cryptoxanthin, Astaxanthin, asteroidenone, adonixanthiy, zeaxanthin inorganic substances 2014
Chlorella zofingiensis Canthaxanthin - 150 mg.L-1 Li et al., 2006.
Gordonia amicalis HS-11 1-OH-4-keto-carotene and 1-OH-carotene n-Hexadecane 714.31/0.9 μg.g-1 dry weight Sowani et al., 2016
β-Carotene, torularhodin, Rhodotorula glutinis Glucose 206 μg.g–1 dry weight Davoli et al., 2004 torulene and γ-carotene
Saccharomyces cerevisiae mutants β-Carotene Glucose 251.8 μg.g-1 dry weight Li et al., 2013
β-Carotene, torularhodin Glucose, molasses, sucrose and whey Rhodotorula mucilaginosa 35.0 mg.g-1 Aksu and Eren, 2005 torulene lactose sugars
Scenedesmus sp. β-Carotene, astaxanthin and lutein Autotrophic 9 mg.L-1.d-1 Pribyl et al., 2015
Rhodosporidium toruloides NCYC 921 β-Carotene Glucose 0.29 g.L-1.h-1 Dias et al., 2015
bacterioruberin is the most found carotenoid Mycobacterium brevicaie, Mycobacterium (Roukas et al., 2002). Studies have shown that (Asker and Ohta, 1999). The Flavobacterium sp. lacticola, Rhodobacter sphaeroides, Rhodococcus carbon and nitrogen sources (Naveena et al., is a known marine bacterium related to optimum maris, Streptomyces chrestomyceticus and 2006), inorganic salts (Fang et al., 2010), production of zeaxanthin (Masetto et al., 2001), Erwinia uredovora also have the ability to chemical agents (Bhosale et al., 2004) and metal and Haloferax alexandrinus has good industrial synthesize carotenoids (Dannert, 2000). ions (Giotta et al., 2006) result in higher or lower perspective for the production of canthaxanthin The production of carotenoids by non- synthesis of pigments. (Asker and Ohta, 2002). Other bacteria such as photosynthetic bacteria is influenced by the Production of carotenoids is directly associated Agrobacterium aurantiacum and modified composition of the culture medium and also by with light, which sometimes favors or inhibits the Escherichia coli (Misawa et al., 1990), temperature, agitation speed and aeration production of some types of carotenoids in 142 Afr. J. Biotechnol.
different microorganisms. For example, under intense pigments such as β-carotene and lycopene (Joshi et al., light, the synthesis of carotenoids by Spirulina platensis 2003). was enhanced (Liu, 1984) and the Flavobacterium sp. Usually the fungi grow at temperatures between 25 and was positive for the production of zeaxanthin (Arakawa et 30°C (Garbayo et al., 2003; Estrada et al., 2009; al., 1977). Studies suggest that the production of Csernetics et al., 2011). Studies have demonstrated that pigments by chemotrophic bacteria such as the fungus Gibberella fujikuroi is influenced by light in its Rhodopseudomonas spheroides and H. salinarum is a mycelial growth, in the presence of light there is way of protection of the cell against the harmful effects of production of orange carotenoids and in the dark there is light (Dundas and Larsen, 1962). no carotenoids production (Garbayo et al., 2003). As previously mentioned, the production of carotenoids is influenced by factors such as light, pH, temperature and Carotenoids produced by yeasts and filamentous culture medium (Burja et al., 2006; Ramirez et al, 2001; fungi Santos et al., 2016).
Among the microorganisms capable of synthesizing carotenoids are yeasts and filamentous fungi. The best Carotenoids produced by microalgae known genera of carotenoid producing yeasts are Rhodotorula, Rhodosporidium, Sporobolomyces The growing demand for natural alternatives for the (Cardoso et al., 2016), Phaffia (Johnson and Lewis, industry and the extensive research on strains of 1979) and Sporidiobolus (Buzzini et al., 2007). The microalgae makes them potentially attractive. Especially, compositions of carotenoids are similar, consisting of β- because they produce special carotenoids in specific carotene, γ-carotene, torulene and torularhodin. The stress conditions (Gateau et al., 2016). torulene is the carotenoid of higher occurrence in yeasts The composition and productivity of carotenoids in (Zoz et al., 2015). algae is greatly influenced by environmental conditions Results of many studies indicate that carotenoids (D’Alessandro and Filho, 2016), such as salinity and production by yeasts can become industrially viable by nutrients available in the culture medium (Beihui and using by-products as carbon sources (Buzzini et al., Kun, 2001; Bocanera et al., 2004; Fazeli et al., 2006; Abe 2007); this also reduces the environmental problems et al., 2007; Raja et al., 2007; Rao et al., 2007). The linked to waste and effluent emissions (Buzzini, 2001). green microalgae can produce the following carotenoids: According to the literature the yeast Rhodotorula glutinis Xanthin, violaxanthin, neoxanthin, α-carotene, β- 22P together with Lactobacillus helveticus 12A presented carotene, lutein and others. For example, Chlorella yields of around 8.4 mg/L of carotenoids (Frengova et al., contains 93% of lutein, 2.6% of α-carotene and β- 1995), besides, Phaffia rhodozyma presented optimum carotene, 1.3% of zeaxanthin, 0.2% of xanthophylls and yield of astaxanthin and β-carotene (Johnson and 0.2% of β-cryptoxanthin (Inbaraj et al., 2006). The main Schroeder, 1995b). traded microalgae are Arthrospira (Spirulina), Chlorella, In addition to the light that is related to carotenoids Dunaliella salina and Aphanizomenon flos-aquae production, the pH is another factor that affects the (Spolaore et al., 2006). production yield (Frengova et al., 1994). According to Spirulina is a prokaryotic microalga, also classified as studies with P. rhodozyma, the ideal pH for growth was cyanobacteria, produced in several countries, the largest 5.8, while the highest astaxanthin production was in pH producer being China. It is used commercially due to its 5.0 (Johnson and Gil-Hwan, 1990). Other studies with the metabolic products such as phycocyanin, used as food yeast Xanthophyllomyces dendrorhous achieved a additive. One of the possible process configurations for maximum concentration of 27 mg/L of astaxanthin under Spirulina production utilizes heterotrophic fermentation controlled conditions, pH 6.0 in the first 80 hours, reactors containing sugars in the absence of light (Lu et followed by pH 4.0 in 144 hours of growth culture (Hu et al., 2011). The Chinese production uses the combination al., 2006). of bicarbonate and air to provide CO2 to produce The production of pigments by fungi dates to hundreds Chlorella vulgaris and Spurulina in an autotrophic of years, in the Asian continent (Mapari et al., 2005). The process (Chen et al., 2016). ascomycete Monascus purpureus was so named Traditionally grown in Japan, Chlorella recently gained because of its reddish color in rice contaminated with this prominence in China. Industrially, it presents higher yield fungus (Dufossé, 2006). The pigments produced by than Spirulina, however, the production process has to be Monascus can be yellow, orange and red; the red carefully controlled in order to avoid contamination. pigments being more interesting for industrial applications Centrifugation methods are used to harvest the algal (Mukherjee and Singh, 2011). A company in the Czech biomass, which is after spray-dried and can be Republic isolated a red coloring Penicillium oxalicum in commercialized in the form of powder, tablets or capsules submerged culture with sucrose and molasses (Dufossé (Chen et al., 2016). et al., 2014). The European countries have used the The salt-tolerant microalga Dunaliella salina is famous for fungus Blakeslea trispora for the industrial production of commercially producing β-carotene (Raja et al., 2007). Cardoso et al. 143
India presents the largest production of carotenoids techniques coupled with other techniques that confer derived from microalgae, followed by Australia, the selectivity and separation efficiency. The purification and United States and China (Dufossé et al., 2005). identification of carotenoids can be performed by liquid Researches indicated the production of carotenoids by chromatography coupled to mass spectrometry (LC-MS) Botryococcus brauniis, and confirmed the presence of (Oliver and Palou, 2001; Ravanello et al., 2003; Stafsnes canthaxanthin, astaxanthin and β-carotene (Abe et al., et al., 2010; Davoli et al., 2007), comparing the mass 2007). The microalga Haematococcus is of high spectra with standards or databases (Martínez-Laborda commercial interest due to the production of astaxanthin, et al., 1990). If they are not available, coupling the the main producers being the United States, Japan and methods of Diode Array Detectors (DAD), Photodiode India (Dufossé et al., 2005). The microalga Botryococcus Array (PDA) or UV-VIS (Fong et al., 2001) with sp., found in sweet pond water in Mahabalipuram, Tamil chromatography LC-MS/MS contributes with the results. Nadu, India, showed high lutein and β-carotene contents. A recent study analyzed the pigment canthaxanthin The authors suggest further studies to optimize the using an UV-HPLC method, with separation in a growing process of Botryococcus due to its high industrial Lichrospher 100 RP-18 silica column, the isocratic mobile potential (Rao et al., 2007). phase used was acetonitrile and methanol (80:20, v/v) at a flow rate of 2 mL/min (Gharibzahedi et al., 2012). Also, the carotenoids produced by Haloferax alexandrines TMT EXTRACTION, PURIFICATION AND IDENTIFICATION strain were analyzed by HPLC, and the carotenoids β- OF CAROTENOIDS carotene, 3-hydroxyechinenone, γ-carotene, cis- astaxanthin, lycopene, anhydrobacterioruberin, Although the evolution of biotechnology contributed to the bacterioruberin isomer, bacterioruberin and optimization of the synthesis of carotenoids, there is still canthaxanthin were identified (Asker et al., 2002). The need for research to improve the process efficiency and separation and purification of canthaxanthin from the commercial gain. The fermentation process is followed by microalga Chlorella zofingiensis was performed using a separation and purification methods to recover the high speed countercurrent chromatography technique pigments, and these usually represent the major (HSCCC), which successfully yielded 98.7% of purity production costs. After the extraction methods are set from 150 mg of crude extract (Li et al., 2006). according to the characteristic of the sample, procedures The bacteria of the genus Micrococcus produce to obtain the pure carotenoid are followed (Feltl et al., different colored pigments, yellow, green and red. It is 2005). Most of the studies involving carotenoid extraction known that the main pigments of Micrococcus roseus and purification were performed at laboratory scale. have been purified by the HPLC system and the In order to release the intracellular carotenoids, it is molecular weight of the samples has been determined by necessary break the cell (Valduga et al., 2009) to extract mass spectra. Samples were analyzed on a C-18 its components. It is at this stage that comes the column, eluting with 80 to 100% ethanol at 470 nm with challenge of recovering the compounds extracted with photodiode detector, under controlled conditions. The minimum possible damage due to the high sensitivity of main carotenoid detected was β-carotene (Shivaji et al., the molecule out of its environment (Pennacchi et al., 1991). 2014). Pigments of the bacteria Micrococcus luteus and of the Carotenoid extraction techniques use organic solvents yeast R. glutinis were purified with HPLC, using binary to disperse the substances, the most commonly used solvents such as ethyl-methyl ether and tert-butyl ether, solvents are acetone, chloroform, dichloromethane, previously filtered on a cellulose 0.2 µm filter and with the hexane, cyclohexane, methanol, ethanol, isopropanol, reverse polymer phase C-30 at 10°C. The substances of benzene, carbon disulfide, diethyl ether and the interest were detected and identified applying a PDA and technology of Supercritical Fluid Extraction (SFE) with using apo-CAR as internal standard. It was possible to carbon dioxide, which has been diffused in recent works. identify key carotenoids, including cis and trans isomers Purification can be carried out by conventional (Kaiser et al., 2007). procedures such as adsorption column chromatography, The purification of pigments from the yeast Phaffia differential extraction, countercurrent extraction and rhodozyma was performed by chromatography using differential crystallization (Mezzomo and Ferreira, 2016). acetone and identification was performed by electronic The development of methods for the separation of absorption mass spectroscopy, confirming the synthesis carotenoids from the Paracoccus bacterium was of astaxanthin by the yeast (Johnson and Lewis, 1979). performed by precipitation from the culture of the The production of lycopene by Yarrowia lipolytica was producer bacterium, centrifugation, filtration or confirmed using HPLC with various compositions of the decantation at acidic pH. Carotenoids were then mobile phase, water, methanol, acetonitrile and ethyl quantified by high performance liquid chromatography acetate (Matthäus et al., 2014). (HPLC) (Hirasawa and Tsubokura, 2014). Studies with Saccharomyces cerevisiae ULI3 succeeded Most studies involving carotenoids used chromatography succeeded in converting β-carotene to β-apo-100- 144 Afr. J. Biotechnol.
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Vol. 16(4), pp. 147-162, 25 January 2017 DOI: 10.5897/AJB2016.15718 Article Number: BF266A562535 ISSN 1684-5315 African Journal of Biotechnology Copyright © 2017 Author(s) retain the copyright of this article http://www.academicjournals.org/AJB
Full Length Research Paper
Relationship analysis between gene expression profiles and rat liver cirrhosis occurrence
Gaiping Wang1,2, Congcong Zhao1,2, Meng Chen1,2, Shasha Chen1,2, Cuifang Chang2 and Cunshuan Xu2*
1College of Life Science, Henan Normal University, Xinxiang, Henan Province, China. 2State Key Laboratory Cultivation Base for Cell Differentiation Regulation, Henan Normal University, Xinxiang, Henan Province, China.
Received 9 October, 2016; Accepted 16 January, 2017
Liver cirrhosis (LC) is a kind of liver disease which is pathologically characterized by abnormality and necrosis of hepatic cells, proliferation of fibrous tissue, nodular regeneration and pseudolobule formation. To explore the mechanism of LC occurrence at the level of mRNA, Rat Genome 230 2.0 Array was used to detect gene expression profiles of rat fibrotic livers in 3, 6 and 9 weeks after CCl4 treatment in this study. It was found that a total of 305 genes including 153 up-regulated, 150 down-regulated and 2 up/down-regulated genes, were related to LC occurrence. Then, k-means clustering was employed to classify above 305 genes into 5 clusters based on gene expression similarity, and EASE analysis further indicated that the above genes were mainly associated with metabolic process, stress reaction, cell growth and apoptosis/death. Thereafter, ingenuity pathway analysis (IPA) software was used to analyze potential effects of the above-mentioned 305 genes, and the results suggested that lipid metabolism and cell growth were inhibited while cell apoptosis/death was activated, but immune/inflammatory response was first activated and then inhibited. Furthermore, IPA also predicted that several signal pathways “ERK/MAPK Signaling”, “p38 MAPK”, “Endothelin-1 Signaling”, “Growth Hormone Signaling”, “LPS/IL-1-mediated inhibition of RXR function” and “IL-6 Signaling” were involved in regulating the occurrence of liver cirrhosis. It was concluded that 305 genes and 3 kinds of physiological activities were closely related to LC occurrence.
Key words: Liver cirrhosis, gene expression profile, systems biology analysis, physiological activity.
INTRODUCTION
Liver cirrhosis (LC), a chronic liver disease of progression regeneration of hepatocytes (Zhou et al., 2014). and diffusivity, is usually caused by viral hepatitis, long- Moreover, the sustained liver damages induced by the term excessive drinking, long-term cholestasis, chemical above-mentioned factors can activate hepatic stellate toxin or drugs, liver congestion, parasitosis, genetic and cells (HSCs), and then result in over abundant synthesis metabolic diseases, etc., which are able to trigger the and insufficient degradation of collagens (Pereira et al., following processes: apoptosis and compensatory 2010). Consequently, liver tissues are restructured, and
*Corresponding author. E-mail: [email protected]. Tel: +86-373-3326001. Fax: +86-373-3326524.
Author(s) agree that this article remains permanently open access under the terms of the Creative Commons Attribution License 4.0 International License 148 Afr. J. Biotechnol.
then liver cirrhosis occurs. Histopathological detection of liver tissues in LC Many cytokines have been reported to be involved in the initiation of liver cirrhosis. Tumor necrosis factor alpha Small cuboids of about 5 × 5 × (2-3) mm from the right lobe of the liver were fixed with 10% neutral-buffered formalin for 24 h and (TNFα) and transforming growth factor beta (TGFβ) could washed for 24 h. Then, they were routinely dehydrated with a stimulate activation of HSCs, which are known to be graded series of ethanol, cleared in xylene, embedded in paraffin, activated as the predominant cells responsible for liver sectioned at 5 μm thickness. Afterwards, the slices were stained fibrosis. Furthermore, interleukins (ILs) were shown to with haematoxylin for 3 min, immerged in ammonia water (pH 8.0) have complicated effects on immune response, for 30 s, and counterstained with 0.5% eosin for 5 min. Finally, they were dehydrated by gradient ethanol, cleared in xylene and sealed inflammation, and liver fibrogenesis (Zhou et al., 2014). with neutral gum. Histopathologic examinations of the liver sections Chou et al. (2006) demonstrated that IL-10 inhibited were conducted and peer-reviewed. fibrogenic and pro-inflammatory gene responses in CCl4- induced mice, and Zhang et al. (2007) showed that IL-10 Rat Genome 230 2.0 microarray detection presented an anti-fibrogenic effect by down-regulating the activity of HSCs. CCl4 is widely used for inducing liver Total RNA was extracted from the frozen mixed middle parts of right fibrosis and cirrhosis in animal models, leading to the lobes of all the rats at each time point according to the Trizol mini kit production of CCl3 and CCl3OO· free radicals (Chavez et (Invitrogen Corporation, Carlsbad, California, USA) and purified al., 2012). Previously, Chan et al. (2016) examined and according to the RNeasy mini protocol (Qiagen, Inc, Valencia, compared gene expression profiles of cirrhotic livers and California, USA). Then, the total RNA was regarded as qualified sample when 28S to 18S RNA was equal to 2:1. After that, total noncirrhotic livers from 40 patients who underwent liver RNA from liver tissues at 0, 3, 6 and 9 weeks of rat model of LC resection or liver transplantation with Affymetrix HuGene were applied for microarray analysis using Rat Genome 230 2.0 2.0 Chip, and found that a total of 213 genes were Array (Affymetrix Inc., Santa Clara, CA, USA). To minimize significantly differentially expressed for more than two- technical errors in the array analyses, the liver sample was detected fold change in cirrhotic livers. However, the small sample repeatedly for three times at each time point by Rat Genome 230 2.0 Array, totaling 3 arrays × 4 time points(Xu et al., 2011). size and heterogeneous patient characteristics may limit the conclusions, thus more gene symbols need further investigation. Identification of liver cirrhosis-related genes To further compare the gene expression profiles of Affymetrix GCOS 2.0 was used to convert the images showing normal liver tissue and that of LC at broader gene expression abundance into signal values, signal detection transcriptional level, this study established a model of rat values (P, A, M) and experiment/control values (Ri). To normalize LC induced by CCl4 to analyze the gene expression the data of each array, all signals were scaled to a target intensity of changes during liver cirrhosis and then to explore the 200. When P value is < 0.05, it means that the gene is present (P), processes of occurrence and progression of liver when < 0.065, marginal (M), and when > 0.065, means marked cirrhosis. The data obtained from the gene expression absent (A). On the other hand, the normalized signal values in LC to that in control were used to calculate the relative value, that is, profiles could provide more useful information on the ratio value of gene expression abundance. When ratio value is ≥ 3, global gene expression changes due to CCl4 it means that gene expression was significantly up-regulated, when administration and bring important insights into the ≤ 0.33, it means significantly down-regulated, and when 0.33-2.99, mechanisms of LC. it means biologically insignificant. To minimize the technical errors from microarray analysis, each sample was tested at least three times using Rat Genome 230 2.0 microarray, and the average value was considered as a reliable value. The genes in LC which MATERIALS AND METHODS has expressed significantly were considered as LC-related genes (supplementary Table 1). Preparation of rat model of liver cirrhosis
Quantitative real-time PCR A total of 30 healthy male Sprague-Dawley rats, each weighting 180±20 g, were supplied by the Experimental Animal Center of To verifying the chip data, four genes were selected for RT-PCR Henan Normal University, and were housed at 21±2°C; relative analysis. The primers were designed with Primer Express 2.0 humidity, 60±10%; illumination time, 12 h/day (8:00-20:00). They software according to the sequences of target genes LCN2 were randomly divided into model group (LC) with 24 rats and (NM_130741), MYC (NM_012603), CCND1 (NM_171992) and control group with 6 rats. Rats in LC were fed with normal food and SPINK3 (NM_012674) and synthesized by Shanghai Generay 0.35 g/L phenobarbital sodium solution in the first week. A dose of Biotech Co., Ltd. The gene-specific primers were the following: 0.5 ml/100 g of CCl4 diluted 2:3 with colza oil was injected into their forward primer 5'-CACCCTGTACGGAAGAACC-3' and reverse abdominal cavity twice per week in 2 to 4 weeks, and their single primer 5'-CACATCCCAGTCAGCCAC-3' for LCN2, forward primer drinking water was 10% alcohol. Their drinking water was 5'-GAGGAGAAACGAGCTGAAGCG-3' and reverse primer 5'- exchanged with 30% alcohol in 5 to 9 weeks. At the same time, the TGAACGGACAGGATGTAGGC-3' for MYC, forward primer 5'- same amount of physiological saline was injected into those in the CCTGACTGCCGAGAAGTTGTGC-3' and reverse primer 5'- control group at the corresponding time. At 3, 6 and 9 weeks after TGGAGGGTGGGTTGGAAATGAA-3' for CCND1, and forward CCl4 administration, the liver tissues from the middle part of right primer 5'-CACCCTGCACAGTTCGTC-3' and reverse primer 5'- lobe were collected in RNase-free tubes and stored at -80°C until AGGGCAATTAGGCGTTTT-3' for SPINK3. Then, 2 µg total RNA use. All operations and handling procedures were carried out in from each of sample was reverse-transcribed using random primers accordance with the current Animal Protection Law of China. and reverse transcription kit (Promega, A3500, USA). First-strand Wang et al. 149
Figure 1. Histopathological changes of liver tissues obtained from liver cirrhosis rats following 0 (A), 3 (B), 6 (C) and 9 (D) weeks of CCl4 administration (HE, 200×).
cDNA samples were subject to quantitative PCR amplification using and physiological processes and signal transduction pathways SYBR® Green I on the Rotor-Gene 3000A (Corbett Research, could be obtained from the modules of “Diseases and Bio- Australia). Every sample was analyzed in triplicate. Standard curves functions” and “Heat-map” in “Canonical Pathways” through were generated from five repeated ten-fold serial dilutions of cDNA, comparison analyses. and the copy numbers of target genes in every milliliter of the sample were calculated according to standard curves (Wang and Xu, 2010). RESULTS
Ethical approval Pathological changes of liver tissues during the occurrence and development of rat liver cirrhosis All applicable international, national, and/or institutional guidelines for the care and use of animals were followed. For rat normal livers, the structure of hepatic lobes and liver sinusoid were clear. Hepatocytes were orderly Bioinformatics analysis arranged and shaped in polygon (Figure 1A). In the third week of LC group induced by CCl , central venous was In order to characterize the expression patterns of the genes 4 involved in LC, k-means clustering was applied to classify the congested obviously, and spotty necrosis was observed differentially expressed genes, then the genes mapped in each with increased number of cells undergoing hydropic cluster during the entire time course of LC were assigned to DAVID degeneration (Figure 1B). At the sixth week, steatosis functional analysis, after that, Expression Analysis Systematic was increasingly severe, pseudolobules began to form Explorer (EASE) software was utilized to determine whether the partly, and a few fibrous hyperplasia scattered (Figure Gene Ontology (GO) categories are over-represented or not 1C). At 9 weeks, infiltration of inflammatory cell was according to a modified Fisher's exact test (Otu et al., 2007). Physiological processes were selected according to EASE score further enhanced, and fibrous collagens were becoming (P-value), and only these processes assigned with P-value < 0.05 thick gradually. Furthermore, fibrous septa, pseudolobule were considered to be significantly over-represented during liver and regenerative nodules of liver emerged, and cirrhosis occurrence. In addition, to detect whether such fasciculus appeared in pseudolobule (Figure 1D). physiological processes were activated or inhibited based on the distinct up- and down-regulation pattern of the expressed genes, and to predict the potential predominant pathways, differentially expressed genes were analyzed by ingenuity pathway analysis Comparison analysis of the detection results of real- (IPA) version 9.0 software (Kramer et al., 2014). First, a dataset time RT-PCR and microarray containing these differentially expressed genes was uploaded into “Dataset Files” of the IPA. Then IPA core analysis was performed, To evaluate the validity of the chip data obtained in this 150 Afr. J. Biotechnol.
Figure 2. Verification of gene expression in CCl4-induced liver cirrhosis by real-time PCR. The results of RT-PCR and Rat Genome 230 2.0 Array are presented as real line and dotted line, respectively.
study, several genes were selected for real time RT-PCR the above-mentioned 305 genes were divided into up- assay to detect their expression changes in liver tissues and down-regulation groups and classified into 5 clusters of CCl4-induced liver cirrhosis. The genes surveyed were by k-means with log2 fold change according to gene composed of four up-regulated genes: LCN2, MYC, expression similarity (Figure 3A): Cluster 1 (C1) included CCND1 and SPINK3. The comparative results indicated 85 genes, which exhibited down-regulated expression that, although there were somewhat differences in the pattern in 6 and 9 weeks. Though, 64 genes in C2 were relative degree of up- or down-regulation measured by down-regulated at each time point during LC, no the above two methods, expression profiles of these four significant expression change was observed among genes detected by real-time RT-PCR were almost in different time points. C3 involved 13 genes which were accordance with those obtained by chip analysis in 3, 6 strikingly up-regulated at 9 weeks. 121 genes were and 9 weeks of rat liver cirrhosis, suggesting that array contained in C4, and strengthened in expression level in results were reliable (Figure 2). both 6 and 9 weeks. There were 22 genes classified into C5, which displayed increasing trend at 3 and 9 weeks during the occurrence of LC (Figure 3B). Expression profiles of significantly expressed genes during rat liver cirrhosis Functional enrichment analysis of significantly Rat Genome 230 2.0 Array was used to detect gene expressed genes during rat liver cirrhosis expression profiles of LC in 3, 6 and 9 weeks, and the obtained microarray data were submitted to the Gene After the expression patterns of liver cirrhosis-related Expression Omnibus database with the accession genes were characterized, DAVID analysis was carried number of GSE73499. As a result, 305 known genes out for the gene sets of C1-5 in Figure 3, and then the were found to be significantly changed in expression, over-represented GO categories with EASE scores (P including 153 up-regulated, 150 down-regulated genes values) of < 0.05 were selected. C1 was enriched with and 2 up/down-regulated genes (Table S1). Subsequently, categories of metabolic processes and regulation of cell Wang et al. 151
Figure 3. Global comparison of gene expression patterns in liver cirrhosis. A. K- means clustering of a total of 305 genes. Red and green colors denote the expression level higher and lower than the control, respectively. B. Five clusters (C1 to C5) display different gene expression profiles over time in the development of LC.
growth. Obviously, lipid metabolic processes were results showed that inflammation response was slightly involved in C2 and inflammation response-related genes activated at 3 weeks but obviously inhibited at 6 and 9 were mainly observed in C3 and C5. Meanwhile, stress weeks, which displayed the same trend as that of response, cell apoptosis/death and cell growth were immune response of cells. Meanwhile, among several predominant in C4. In brief, a total of 305 genes were categories of lipid metabolism, only fatty acid metabolism divided into three categories with metabolic processes was activated at 3 weeks and inhibited at 6 weeks while scattering in C1 and C2, stress reaction enriched in C3, conversion of fatty acid, concentration of cholesterol and C4 and C5, and cell growth and apoptosis/death involved sterol all showed the trend of suppression. Proliferation of in C1 and C4 (Table 1). liver cells and hepatocytes were both inhibited, and cell death and apoptosis of hepatocytes were accordingly activated. Activity prediction of bio-processes and signal To display the relationships between expression pathways during rat liver cirrhosis changes of genes and activities of physiological processes during the occurrence of LC, the gene A total of 305 genes were uploaded to IPA software for regulatory networks regulating three main categories of core analysis and comparison analysis, and bio-functions bio-process were predicted and respectively shown in of LC at three time points were obtained (Figure 4). The Figure 5. The 12 genes regulating inflammation were all 152 Afr. J. Biotechnol.
Table 1. Over-represented functional categories in five clusters during rat liver cirrhosis occurrence.
Enriched biological process Number of genes #P-value Enriched biological process Number of genes #P-value Cluster 1 Cluster 4 Oxygen transport 4 2.90E-05 Response to organic substance 29 5.70E-10 Oxidation reduction 12 2.80E-04 Response to hormone stimulus 19 1.20E-07 Lipid catabolic process 6 6.50E-04 Response to endogenous stimulus 20 1.30E-07 Positive regulation of growth 5 1.20E-03 Response to drug 14 2.20E-06 Positive regulation of cell growth 4 2.10E-03 Response to extracellular stimulus 13 5.60E-06 Regulation of carbohydrate catabolic process 3 4.80E-03 Response to inorganic substance 11 6.10E-05 Phospholipid metabolic process 5 9.60E-03 Regulation of cell growth 9 6.70E-05 Organophosphate metabolic process 5 1.20E-02 Response to nutrient levels 11 9.30E-05 Regulation of glucose metabolic process 3 2.10E-02 Response to wounding 13 1.60E-04 Carboxylic acid biosynthetic process 4 4.30E-02 Regulation of growth 10 6.90E-04 Proteolysis 9 4.70E-02 Regulation of inflammatory response 5 4.00E-03 Cluster 2 negative regulation of apoptosis 9 5.60E-03 Lipid biosynthetic process 11 9.50E-08 Negative regulation of cell death 9 6.20E-03 Steroid metabolic process 9 2.30E-07 Inflammatory response 7 8.30E-03 Sterol metabolic process 7 5.20E-07 Regulation of apoptosis 13 8.40E-03 Fatty acid metabolic process 9 5.50E-07 Regulation of cell death 13 9.60E-03 Sterol biosynthetic process 5 5.10E-06 Positive regulation of cell cycle 4 1.20E-02 Cholesterol metabolic process 6 8.20E-06 Regulation of cell cycle 7 1.50E-02 Steroid biosynthetic process 6 9.40E-06 Anti-apoptosis 5 3.00E-02 Oxidation reduction 11 9.70E-05 Defense response 8 4.30E-02 Cholesterol biosynthetic process 4 1.20E-04 Cluster 5 Fatty acid biosynthetic process 3 3.50E-02 Immune response 8 2.70E-07 Cluster 3 Antigen processing and presentation 4 1.30E-04 Immunoglobulin C1-set 4 1.30E-05 Adaptive immune response 3 2.90E-03 Immunoglobulin-like 4 9.60E-04 Immunoglobulin/major histocompatibility complex 3 1.10E-03
#Represents EASE score (a modified Fisher’s exact test).
all up-regulated at 3 weeks, and 5 of them inflammation attenuation at 9 weeks. Expression inhibiting fatty acid metabolism at 6 weeks. At 9 participated in activating inflammation response. changes of genes involved in fatty acid weeks, fatty acid metabolism was slightly boosted At 6 weeks, 14 genes including 6 up-regulated metabolism showed that 6 up-regulated genes by 9 genes, which included 6 up-regulated and 3 and 8 down-regulated might be involved in from a total of 11 genes strikingly activated the down-regulated genes. As for the proliferation and inhibiting inflammation, and 13 genes with 7 up- process at 3 weeks. However, 8 up-regulated and death of liver cells during LC, this study found that regulated and 6 down-regulated genes led to 1 down-regulated genes might play vital roles in cell death of hepatocytes was induced at 9 weeks Wang et al. 153
Figure 4. Biofunction heatmap of 305 significantly expressed genes predicted by IPA software. The color of heatmap square represents the activity of biofunctions. Jacinth represents activation of biofunction, and blue represents inhibition of biofunction.
by 3 down-regulated and 1 up-regulated genes, but 4 induced liver fibrosis at broader transcriptional level, this genes with 3 up-regulated suppressed proliferation of study used Rat Genome 230 2.0 Array including 24619 liver cells at 6 weeks and 4 genes with 2 up-regulated genes to detect the gene expression profiles of liver cells inhibited the process at 9 weeks. in rats following 3, 6 and 9 weeks after CCl4 adminis- In addition, to clarify which signaling pathway might tration. It was found that 305 genes were significantly play important role in liver cirrhosis, pathway analysis changed, including 153 up-regulated, 150 down- was performed to associate the differentially expressed regulated and 2 up/down-regulated genes. DAVID genes with canonical signaling pathways by IPA functional analysis categorized the differentially expressed software. The enriched “Heat-map” in the “Canonical genes into 3 groups including metabolic process, stress Pathways” was amputated in Figure 6. Obviously, reaction, cell growth and apoptosis/death. IPA further “ERK/MAPK Signaling” and “p38 MAPK” involved in predicted activities of enriched bio-processes and regulation of cell proliferation were both activated at 6 potential signaling pathways during rat liver cirrhosis, and 9 weeks, “Endothelin-1 Signaling” was at 6 weeks, which could provide information for the understanding of while “Growth Hormone Signaling” was strikingly inhibited the pathophysiological changes of cirrhotic liver. at 6 weeks. Moreover, “LPS/IL-1-mediated inhibition of Hepatic fibrosis was always concomitant with RXR function” and “IL-6 Signaling” were similar, which hepatic inflammation (Wu et al., 2015). In this study, were activated at 6 weeks, but inhibited at 9 weeks. stress reaction-associated genes were enriched in C3, C4 and C5, they displayed increased expression at mRNA level. However, IPA software predicted that DISCUSSION inflammation response and immune response were significantly activated only at 3 weeks in bio-function heat Though several studies have detected gene expression map (Figure 4). Similarly, several previous studies profiles associated with toxin-induced liver fibrosis or demonstrated that liver injury could stimulate immune cirrhosis in rats and mice, the number of tested genes system, and then induce immune response (Zhang et al., remains to be improved (Gant et al., 2003; Liu et al., 2009; Dienes and Drebber, 2010). Therefore, CCl4- 2009). Furthermore, the studies in humans always induced hepatic injury may lead to the activation of investigated the patients with liver fibrosis resulting from inflammation and immune response during the early HBV and HCV infection or liver cancer, and the small stage of liver cirrhosis. On the contrary, inflammation and patient sample size and heterogeneous patient immune responses were inhibited at 6 and 9 weeks in characteristics may always lead to the limitations of Figure 4. Accordingly, Ji et al. (2012) found that the top conclusions. To further systematically study the toxin- network of down-regulated proteins expressed by HSCs 154 Afr. J. Biotechnol.
Figure 5. Gene regulatory networks associated with several functional categories during liver cirrhosis occurrence. A. Regulatory network of inflammatory response at 3 (A1), 6 (A2) and 9 weeks (A3). B. Regulatory network of fatty acid metabolism at 3 weeks (B1), 6 (B2) and 9 weeks (B3). C. Regulatory network of cell death of hepatocytes at 9 weeks (C1) and proliferation of liver cell at 6 (C2) and 9 weeks (C3).
Figure 6. Signaling pathway heatmap of 305 significantly expressed genes predicted by IPA software. The color of heatmap square represents the activity of biofunctions. Jacinth represents activation of biofunction, and blue represents inhibition of biofunction. Wang et al. 155
was involved in immune response and speculated that Present study demonstrated that CYP1A1 was up- the immune response of HSCs was impaired upon regulated at three time points and activated fatty acid activation. However, it deserves further study to identify metabolism at 3 and 9 weeks, suggesting that CYP1A1 whether the decreased inflammation and immune may also play a protective role by activating fatty acid responses were due to the activation of HSCs after 6 and metabolism in liver cirrhosis. According to the IPA 9 weeks of CCl4 administration. Among the genes analysis, LPS/IL-1-mediated inhibition of RXR function participating in inflammation, A2M was always used as a ranked first in the identified canonical pathways, and the biological indicator to assess hepatic fibrosis and study performed by Raghu et al. (2012) indicated that this cirrhosis, and was found to be up-regulated at 3 weeks in pathway was involved in ethanol metabolism in alcoholic this study. Gangadharan et al. (2007) pointed out that the fatty liver. On the other hand, different concentration of expression of A2M was strengthened with the alcohol were supplied for the model rats in this study, development of hepatic fibrosis, which was consistent thus LPS/IL-1-mediated inhibition of RXR function might with the current study result. Wald et al. (2004) found participate in rat LC occurrence by regulating lipid that up-regulation of CXCL12 in liver during chronic HCV metabolism. In addition, one previous study proved that and HBV infection may support the establishment of a IL-6 had positive effects on hepatic lipid metabolism chronic inflammatory state and a progressive fibrotic (Hassan et al., 2014). Therefore, IL-6 signaling pathway process, thus the down-regulation of CXCL12 at 6 and 9 may be involved in modulating lipid metabolism during weeks lead to inflammation response inhibition, as shown liver cirrhosis. in Figure 5A and indicated an accordingly result. The up- Cell proliferation and apoptosis/death related biological regulation of SPP1 might be a primary pathway of HSC processes were enriched in C1 and 4 with different gene activation (Erkan et al., 2010). Consistently, its expression profiles. The study performed by Jiang et al. expression was increased in 6 weeks of LC in this study. (2015) showed that the levels of early, late apoptosis and One of the IL-1 family members, IL-33 was down- cell death were significantly higher in the cirrhosis model. regulated at the mRNA level in 6 and 9 weeks, and it has Accordingly, this study showed that cell death and been identified as an important factor contributing to apoptosis of hepatocytes were activated in “Diseases and inflammatory response and liver injury (Wang et al., Bio-functions” analysis by IPA. However, proliferation of 2012), which together suggested its important role in liver cells and hepatocytes were both found to be inhibiting inflammation during the occurrence of liver inhibited. On the other hand, Chen et al. (1999) found cirrhosis. IL-6 showed both pro-inflammatory and anti- that proliferation continued in spite of increasing inflammatory effects on hepatic system through apoptosis of hepatocytes apoptosis at 72 h after ERK/MAPK signaling (Hassan et al., 2014), and IL-6 subcutaneous injection of 50% CCl4. Thus, it is signaling and ERK/MAPK signaling pathways were both speculated that proliferation of liver cells might be enriched in “canonical pathway” by IPA (Figure 6), which inhibited due to the intense stimulation of CCl4 and showed the important roles of above two pathways in alcohol in this study. The oncogene MET played an regulating inflammation during liver cirrhosis occurrence. important part in preventing Fas-mediated apoptosis of The genes involved in metabolic processes were hepatocytes (Zou et al., 2007), and proliferation and decreased at the mRNA level and enriched in C1 and 2, survival of hepatocytes were impaired in mice with Met which exhibited the same trend as the activities of mutants after partial hepatectomy (Borowiak et al., 2004). metabolic processes, such as conversion of fatty acid, Consistent with the above results, this study showed that concentration of cholesterol and sterol. Previous studies the down-regulation of MET at 9 weeks may activate cell proved that lipid metabolism was severely impaired in death of hepatocytes and its up-regulation at 9 weeks liver cirrhosis originating from hepatitis C and B viruses may suppress proliferation of liver cells. It is well known (Vere et al., 2012), implying that the process of lipid that CDKN1A inhibits the activity of cyclin-dependent metabolism was attenuated during liver cirrhosis. kinase 2 (CDK2) and arrests cell cycle at G1. Accordingly, Surprisingly, fatty acid metabolism was activated at 3 its up-regulation may account for the activated cell death weeks and slightly inhibited at 6 weeks. Moreover, the of hepatocytes at 9 weeks and inhibitory proliferation of regulatory network of fatty acid metabolism showed that liver cells at 6 and 9 weeks. Proliferation and activation of the up-regulation of FABP4 at three time points HSCs could be suppressed via ERK/MAPK in hepatic participated in activating fatty acid metabolism (Figure fibrosis (Peng et al., 2014), and p38 MAPK was also 5B). FABP4 is one of fatty acid binding proteins, and the associated with cell apoptosis in liver fibrosis (Wang et expression of FABP4 and FABP5 was enhanced during al., 2015), so it could be concluded that the above two cirrhosis in hepatocarcinogenesis of rat model (Liu et al., pathways, which were both enriched in Figure 6, play a 2009), which was not contradictory with our result and vital role in cell growth and apoptosis/death during liver indicated an alteration of fat metabolism. One previous cirrhosis occurrence. study showed that cytochrome P450 (CYP) 1A1 could In conclusion, Rat Genome 230 2.0 Array detection and protect lung from oxidative injury by decreasing levels of gene synergy analysis identified a total of 305 genes, lipid hydroperoxides (Lingappan et al., 2014), and the which were differentially expressed at 3, 6 and 9 weeks 156 Afr. J. Biotechnol.
and associated with liver cirrhosis occurrence. These 11(4):2941-2946. genes were involved in three primary physiological Kramer A, Green J, Pollard J Jr., Tugendreich S (2014). Causal analysis approaches in Ingenuity Pathway Analysis. Bioinformatics 30(4):523- activities based on GO annotation and several potential 530. related pathways according to IPA software. In the future, Lingappan K, Jiang W, Wang L, Wang G, Couroucli XI, Shivanna B, the result above will be confirmed using gene addition Welty SE, Barrios R, Khan MF, Nebert DW, Roberts LJ, Moorthy B and RNA interference, etc. and provide more information (2014). Mice deficient in the gene for cytochrome P450 (CYP)1A1 are more susceptible than wild-type to hyperoxic lung injury: evidence for for therapy and prevention of liver cirrhosis. protective role of CYP1A1 against oxidative stress. Toxicol. Sci. 141(1):68-77. Liu YF, Zha BS, Zhang HL, Zhu XJ, Li YH, Zhu J, Guan XH, Feng ZQ, Conflict of Interests Zhang JP (2009). Characteristic gene expression profiles in the progression from liver cirrhosis to carcinoma induced by The authors have not declared any conflict of interests. diethylnitrosamine in a rat model. J. Exp. Clin. Cancer Res. 28:107. Otu HH, Naxerova K, Ho K, Can H, Nesbitt N, Libermann TA, Karp SJ (2007). Restoration of liver mass after injury requires proliferative and ACKNOWLEDGEMENTS not embryonic transcriptional patterns. J. Biol. Chem. 282(15):11197- 11204. This study was funded by the National Natural Science Peng Y, Yang H, Wang N, Ouyang Y, Yi Y, Liao L, Shen H, Hu G, Wang Foundation Project of China (No. 81200317), the Natural Z, Tao L (2014). Fluorofenidone attenuates hepatic fibrosis by suppressing the proliferation and activation of hepatic stellate cells. Science Foundation of China (No. 31572270) and the Am. J. Physiol. Gastrointest. Liver Physiol. 306(3):G253-263. Major Scientific and Technological Projects of Henan (No. Pereira TN, Walsh MJ, Lewindon PJ, Ramm GA (2010). Paediatric 111100910600). cholestatic liver disease: Diagnosis, assessment of disease progression and mechanisms of fibrogenesis. World J. Gastrointest. Pathophysiol. 1(2):69-84. Raghu R, Liu CT, Tsai MH, Tang X, Kalari KR, Subramanian S, Sheen REFERENCES LY (2012). Transcriptome analysis of garlic-induced hepatoprotection
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Supplementary Table 1. Expression abundance of 305 significantly changed genes during rat liver cirrhosis occurrence.
Progression of liver cirrhosis occurrence Gene symbol 3 weeks 6 weeks 9 weeks A1bg 0.005 0.004 0.008 Obp3 0.029 0.004 0.004 Dhrs7 0.072 0.041 0.013 LOC259245 0.092 0.016 0.013 Akr1b7 0.114 0.041 0.037 Mup5 0.156 0.081 0.052 Mlc1 0.153 0.167 0.145 Nfe2 0.171 0.055 0.086 RGD1562844 0.158 0.199 0.145 Ddhd1 0.216 0.103 0.109 Hsd17b2 0.248 0.094 0.247 Idi1 0.239 0.128 0.252 Tm7sf2 0.258 0.089 0.184 Abcg5 0.153 0.263 0.193 Abcg8 0.233 0.277 0.137 Sc4mol 0.223 0.129 0.279 Aacs 0.226 0.181 0.295 Mtmr7 0.313 0.182 0.165 Cdh17 0.203 0.263 0.316 Hmgcs1 0.283 0.159 0.328 Akr1c6 0.330 0.071 0.089 Lox 0.370 0.239 0.308 Prlr 0.371 0.196 0.268 Ldlr 0.394 0.383 0.278 Acadsb 0.402 0.360 0.091 Cyp8b1 0.110 0.368 0.413 Acss2 0.417 0.235 0.285 Nudt11 0.041 0.319 0.422 Mpdz 0.425 0.173 0.233 Trim24 0.290 0.356 0.429 Inmt 0.432 0.103 0.098 Gpam 0.435 0.239 0.151 Oat 0.436 0.244 0.136 Cyp51 0.436 0.274 0.388 Stac3 0.439 0.119 0.081 Hal 0.439 0.181 0.137 Ela1 0.456 0.389 0.207 Acat2 0.456 0.258 0.308 Cyp3a9 0.474 0.101 0.178 Serpina6 0.485 0.157 0.313 Fads2 0.493 0.225 0.470 Met 0.521 0.455 0.208 Xiap 0.437 0.531 0.172 Sqle 0.319 0.258 0.538 Bche 0.538 0.415 0.249 Pcsk9 0.544 0.223 0.467 Fmo1 0.545 0.089 0.184 Mgst3 0.566 0.303 0.260 rnf141 0.567 0.474 0.286 158 Afr. J. Biotechnol.
Supplementary Table 1. Contd.
Hacl1 0.575 0.323 0.285 Hdhd3 0.575 0.328 0.304 Acf 0.579 0.513 0.180 Gstm3 0.580 0.331 0.248 Hnf4a 0.580 0.573 0.286 Onecut1 0.586 0.390 0.212 Ppp1r3c 0.588 0.252 0.238 Chodl 0.589 0.132 0.293 Cryl1 0.592 0.063 0.282 Prelid2 0.599 0.255 0.353 RGD1309362 0.603 0.054 0.416 Rod1 0.529 0.607 0.245 Hes6 0.616 0.253 0.394 Fcna 0.626 0.281 0.423 Cyp1a2 0.626 0.100 0.145 Hmgcr 0.286 0.495 0.636 Bdh1 0.645 0.283 0.356 Hrasls3 0.650 0.187 0.313 RGD1310862 0.356 0.655 0.205 Srd5a1 0.656 0.103 0.130 Ghr 0.664 0.269 0.237 Avpr1a 0.670 0.320 0.325 Cxcl12 0.672 0.183 0.219 Il1r1 0.676 0.492 0.137 Mcpt9 0.680 0.201 0.324 Fads1 0.686 0.199 0.433 Dpys 0.714 0.318 0.328 Akr1c12 0.714 0.239 0.497 Ntf3 0.715 0.102 0.081 Ceacam1 0.717 0.414 0.275 LOC287167 0.717 0.202 0.436 Obfc2a 0.720 0.284 0.354 Sds 0.232 0.730 0.311 Slc23a1 0.731 0.270 0.338 Elovl5 0.736 0.354 0.169 Akr1c18 0.743 0.238 0.349 Car3 0.744 0.005 0.012 Gzma 0.747 0.096 0.362 Igf2bp3 0.750 0.207 0.219 LOC360919 0.753 0.304 0.349 Klrg1 0.755 0.172 0.237 Prf1 0.735 0.142 0.758 Mpeg1 0.759 0.333 0.256 Coch 0.765 0.470 0.188 Lipc 0.772 0.234 0.320 Dpt 0.776 0.273 0.464 Lin7a 0.779 0.234 0.194 Bhmt 0.794 0.272 0.419 Gckr 0.795 0.269 0.341 Aadac 0.807 0.226 0.323 Cyp2c 0.808 0.010 0.012 Eraf 0.816 0.062 0.102 Wang et al. 159
Supplementary Table 1. Contd.
Abhd5 0.821 0.571 0.293 Il33 0.833 0.241 0.240 Angptl3 0.838 0.281 0.407 Cpb1 0.842 0.241 0.229 Hba-a2 0.869 0.206 0.514 Bbox1 0.872 0.367 0.307 Enpp3 0.872 0.351 0.247 Sult1c1 0.891 0.099 0.096 Pgcp 0.892 0.218 0.287 C6 0.905 0.130 0.199 Nr1d1 0.222 0.278 0.912 Igf1 0.914 0.299 0.376 Sez6 0.924 0.043 0.199 Hbb 0.942 0.183 0.474 Ppp1r3b 0.943 0.163 0.218 Serpina4 0.948 0.310 0.403 Esr1 0.953 0.300 0.053 Thrsp 1.000 0.298 0.351 Apol3 1.001 0.290 0.580 MGC72973 1.032 0.117 0.378 Afm 1.040 0.315 0.376 Slc13a5 1.076 0.303 0.238 LOC246266 1.076 0.161 0.235 Es1 1.081 0.115 0.308 Ethe1 1.081 0.264 0.343 Abca8a 1.097 0.306 0.338 Cpt1a 0.181 1.106 0.666 Cml4 1.141 0.093 0.137 Hao2 1.167 0.210 0.246 LOC306096 1.203 0.442 0.150 Gzmm 1.207 0.213 1.155 Alas2 1.220 0.221 0.510 Igfals 1.291 0.250 0.433 Ubd 1.291 0.228 1.167 Cxcl13 1.312 0.266 0.963 IgG-2a 0.232 1.167 1.372 Ccl5 1.002 0.222 1.373 Nrep 1.517 0.040 0.092 Plac8 1.553 0.231 0.758 RGD1562625 0.135 0.696 1.567 Gbp2 1.312 0.199 1.631 Mcpt10 1.713 0.035 0.383 S100a8 1.854 0.545 0.273 S100a9 2.048 0.439 0.260 MGC108823 2.214 0.134 1.178 Alox15 2.252 0.135 0.311 Pla2g2a 2.317 0.169 0.993 RatNP-3b 2.338 0.529 0.041 RGD1563818 2.361 0.282 1.322 Igfbp4 2.570 2.878 3.056 Edem2 1.291 3.327 2.744 RT1-Da 2.683 0.859 3.328 160 Afr. J. Biotechnol.
Supplementary Table 1. Contd.
Atf5 1.530 3.107 3.336 Cbr1 1.104 3.382 2.923 Ddx60 3.391 0.592 2.100 Nupr1 0.681 3.404 2.621 Lbp 3.445 2.516 2.454 Ncdn 1.114 3.492 3.265 Spna2 1.404 3.225 3.514 Cd24 1.205 1.148 3.521 Myo1c 1.594 3.585 3.318 Btg2 1.666 3.601 2.169 S100a10 1.367 3.336 3.623 Mapkapk2 1.962 3.631 3.043 Ccl2 1.864 2.509 3.635 Hdc 3.671 0.732 0.378 Usp2 1.746 3.689 2.687 Rbm3 1.690 3.738 3.180 Traf4af1 1.784 3.724 3.757 Cd74 2.807 1.089 3.764 Clec12a 3.319 1.466 3.788 Soat1 1.173 3.807 2.949 Gfra1 1.750 3.808 2.314 Cotl1 3.823 1.566 3.219 Flywch1 2.075 3.022 3.851 App 1.503 3.860 2.445 Ctgf 1.509 3.875 3.857 Dcn 3.917 3.708 3.706 Rrm2 1.126 3.928 1.835 Pck2 1.222 3.947 2.841 Slc38a2 1.001 3.970 1.985 Pfkl 2.535 2.618 3.985 Pir 1.776 4.070 3.766 Spsb4 1.708 3.744 4.081 Ablim3 0.707 4.104 3.204 RT1-Db1 2.400 0.754 4.124 Serpina7 3.710 3.432 4.132 Cxcl16 2.297 2.225 4.209 Cyp4b1 1.150 3.104 4.257 Pla2g12a 0.929 4.286 3.490 Ccnd1 0.949 3.613 4.292 Srm 1.471 4.303 3.930 Btg3 1.063 4.311 4.207 Zfp385a 4.351 1.735 1.942 Ptn 4.383 1.395 2.533 LOC683626 2.209 3.103 4.440 Pdgfa 1.703 2.791 4.459 Fos 1.770 4.547 2.523 RT1-N3 2.236 1.104 4.597 Pla1a 1.179 4.707 4.004 Igfbp2 0.612 3.738 4.741 Ckap4 2.998 3.685 4.757 Hyou1 1.846 4.843 3.731 Aebp1 1.172 1.570 4.897 Wang et al. 161
Supplementary Table 1. Contd.
Pcolce 4.932 1.615 1.592 LOC361187 1.647 4.962 4.302 Tes 1.575 4.261 4.972 Fam111a 0.544 0.556 4.972 Nr4a1 1.268 5.006 2.703 Ccl21b 5.030 1.804 2.764 Npdc1 2.632 4.606 5.067 Rab3d 1.126 5.101 4.847 Ica1 1.603 5.206 5.164 Abcb1 0.618 5.207 3.767 Irs2 2.126 5.208 2.043 Fkbp11 0.997 5.323 4.778 Bcl6 5.461 1.281 3.746 LOC681825 3.493 3.552 5.469 Slc25a4 1.343 3.060 5.494 Prickle2 5.328 3.544 5.538 Cidea 1.736 5.329 5.542 Adrm1 2.292 4.132 5.624 Dhdds 2.549 5.690 5.258 Spp1 1.805 5.704 2.261 Nos1ap 5.714 2.998 2.463 LOC365157 2.219 4.504 5.762 Dennd2d 1.761 2.765 5.811 Anxa7 1.847 5.834 5.836 Tnnc2 1.779 6.093 3.798 Reep5 2.516 5.872 6.145 Clec7a 3.888 4.033 6.162 Pqlc3 2.502 6.096 6.183 Asns 2.113 6.196 5.662 Igfbp1 1.056 6.312 5.326 Myh10 3.458 4.611 6.662 Bex4 1.127 1.543 6.668 Lum 6.787 0.723 0.848 Oasl1 1.903 4.369 6.872 Gpx3 2.287 4.757 6.883 S100g 0.898 6.971 5.912 Bspry 2.366 6.809 6.991 RT1-CE5 1.320 1.028 7.001 Pbk 2.628 7.012 4.277 Cgref1 1.259 7.053 4.872 LOC362795 0.724 0.523 7.152 Gstp1 0.879 2.427 7.194 Lincr 1.476 3.505 7.270 Myc 2.576 7.331 5.226 Cxcl1 7.413 0.993 1.197 Tox3 3.737 7.298 7.467 Enc1 2.561 7.512 3.685 Rnd1 3.684 7.555 7.522 Hspb1 2.527 6.311 7.893 Tmed3 1.618 8.022 6.415 Vnn1 1.731 8.081 6.716 Pcp4l1 1.005 1.218 8.113 162 Afr. J. Biotechnol.
Supplementary Table 1. Contd.
Cdkn1a 3.569 8.119 7.376 Bhlhb8 2.129 7.531 8.448 Serpine1 2.755 3.941 8.586 Rem2 4.792 8.620 6.934 Sh3bgr 4.204 8.757 8.595 Gpnmb 2.920 6.653 8.788 Rgs4 8.959 5.400 5.049 Lilrb4 2.296 3.458 9.011 Akr7a3 2.162 6.311 9.121 Akr1b8 0.873 1.608 9.582 Ring1 6.703 7.331 9.689 Pcp4 0.799 1.258 10.412 Gpx2 3.009 10.687 9.666 Postn 10.745 0.539 0.935 Acot2 1.481 10.866 6.868 Cyp17a1 2.685 11.085 9.566 Scaf1 8.567 8.356 11.347 Atf3 2.527 8.949 11.591 RGD1566401 1.117 1.487 11.601 Isyna1 1.645 11.894 10.741 Cox6a2 1.970 12.000 10.512 Nol3 2.457 9.860 12.008 Trib3 0.801 12.373 12.319 Cyp2b1 /// Cyp2b2 12.623 1.016 0.912 Fgf21 0.955 6.058 13.133 Cd276 3.949 12.009 13.710 Unc5b 4.182 14.772 14.855 Lcn2 5.647 15.412 0.760 Vldlr 3.737 15.570 13.131 Gem 2.225 17.132 6.219 Alpl 10.652 18.307 10.562 Mmp12 2.476 19.972 14.961 Scg2 20.482 0.791 0.834 Snx10 6.939 21.618 10.195 Fst 14.207 22.048 3.130 Rasl12 24.162 3.256 2.943 Spink1 25.380 13.585 19.196 Chpf 10.369 28.440 24.419 Cyp1a1 3.196 28.905 18.476 RT1-Bb 15.655 0.963 32.081 Abcc3 11.740 31.599 39.378 Gstm4 6.834 40.822 32.680 Fabp4 14.192 41.421 31.021 Phgdh 4.555 38.181 41.810 Gucy2c 12.064 98.808 115.513 Acot1 6.487 665.790 700.727 Cxcl9 1.947 0.319 3.334 A2m 27.695 0.171 0.325
Vol. 16(4), pp. 163-170, 25 January 2017 DOI: 10.5897/AJB2016.15776 Article Number: D74472B62537 ISSN 1684-5315 African Journal of Biotechnology Copyright © 2017 Author(s) retain the copyright of this article http://www.academicjournals.org/AJB
Full Length Research Paper
Molecular identification, micronutrient content, antifungal and hemolytic activity of starfish Asterias amurensis collected from Kobe coast, Japan
Farhana Sharmin*, Shoichiro Ishizaki and Yuji Nagashima
Graduate School of Marine Science and Technology, Tokyo University of Marine Science and Technology, Konan 4-5-7, Minato, Tokyo108-8477, Japan.
Received 11 November, 2016; Accepted 6 January, 2017
The starfish Asterias amurensis is one of the common species in Japanese coastal area. The species is considered an extremely rich source of biological active compounds, including saponin. Saponins are secondary metabolites and exhibit a wide spectrum of biological activities. The species of starfish caught in Kobe, Hyogo prefecture, Japan, was analyzed for species identification and micronutrient content. The starfish extract was evaluated for different biological properties and its fractions obtained using thin layer chromatography (TLC). Nucleotide sequence analysis of the 16S rRNA gene fragment of mitochondrial DNA indicated that partial sequences of PCR products of the species was identical with that of A. amurensis. The micronutrient contents results showed that nitrogen (N) content of the starfish was 1.50% of dry weight and the copper content was 2.10 µg/g. The crude extract of A. amurensis exhibited predominant growth inhibitory activity against six human fungal pathogens and also showed hemolytic activity against 2% sheep erythrocyte. The present findings suggest the possible pharmacological applications of A. amurensis that can be used as food ingredients and antifungal component.
Key words: Asterias amurensis, crude extract, biological property, saponin, antifungal component.
INTRODUCTION
Nowadays, invasion of exotic species has become a invertebrates and possess many useful pharmacological major concern in the marine environment since the and biological activities. Oreaster reticulates, Luidia number of human-mediated introduction has increased senegalensis and Echinaster sp. have been used as (Ruiz et al., 2000). Many studies researching marine traditional medicine for thousands of years in China and invertebrates to determine the therapeutic potential of North-eastern Brazil to treat asthma, bronchitis, diabetes, their bioactive materials have been showing very and heart and stomach diseases (Alves and Alves, promising results (Lee et al., 2014). Starfish are marine 2011). Various biological active compounds and
*Corresponding author. E-mail: [email protected].
Author(s) agree that this article remains permanently open access under the terms of the Creative Commons Attribution License 4.0 International License 164 Afr. J. Biotechnol.
molecules have recently been identified from starfish Species identification based on DNA analysis such as glycosylceramide, steroidal glycosides, ceramide, and cerebrosides (Ishii et al., 2006; Suh et al., Genomic DNA was extracted from tube feet of starfish sample by using Quick gene-810 (Kurabo, Tokyo, Japan) as recommended by 2011). Saponins are a group of natural plant glycosides, the manufacturer. The DNA concentration (ng/µl) was measured by characterized by their strong foam-forming properties in a Biospec Nano (Shimadzu Corporation, Tokyo, Japan). A partial aqueous solution that occur in a wide range of plant region of the mitochondrial 16S rRNA gene was amplified by the species (Osbourn, 1996). The presence of saponin has conventional polymerase chain reaction (PCR) using universal been reported in more than 100 families of plants out of primers ( 6S rL, ’-CGCCTGTTTATCAAAAACAT- ’ d 16SbrH, ’-CCGGTCGAAACTCAGATCACGT- ’ PCR was performed in 50 which at least 150 kinds of natural saponins have been µl volume containing 5 µ f ge mic DNA, μ f dNTP, μ f 0 found to possess significant anti-cancer properties (Man × Ex T q buffer, 0 μ f Ex T q DNA p ymer se (T k r Shuz , et al., 2010). Saponins have also been commonly J p , d µ f 0 μM f e ch primer PCR mp ific ti was employed in some other sector in medical practice performed with Veriti thermal cycler (Applied Biosystems, Foster because of their potential health benefits. In addition, City, CA, USA). Amplifying conditions were 98°C for 10 s in many plant saponins have been isolated and they exhibit denaturing, 53°C for 30 s in annealing, and 72°C for 60s in extension for 30 cycles. The amplified PCR products were run in broad spectrum of biological uses, such as anti-cancer, 1.2% agarose gel containing SYBR Safe DNA Gel Stain (Invitrogen, anti-inflammatory, ion channel blocking, immune Carlsbad, CA, USA). The gel was run at 100 V for 30 min and stimulating, antifungal, and anti-thrombotic property (Lee visualized using LAS-4000 mini documentation system (Fujifilm et al., 2014; Thao et al., 2014). Cooperation, Tokyo, Japan). The PCR samples were sequenced The starfish A. amurensis, called the northern Pacific with BigDye® terminator V3.1 Cycle Sequencing Kit and ABI 3130 starfish, is a predator of the marine benthic system that is Genetic Analyzer (Applied Biosystems, Foster City, CA, USA) and the obtained sequence data were analyzed by SeqEd Version 1.0.3 listed in the top 100 invasive species globally (Lowe et (Perkin Elmer, Foster City, CA, USA) software. The sequences al., 2000). The species was identified as a serious pest were subjected to blast search with national center for species because of its ability to consume a wide range of biotechnology information (NCBI) data base. These sequences food sources including mussels, scallops, and clams were then aligned using the default settings in Clustal W package in (Global invasive species database, 2016). The wastes of the MEGA 6 software (Tamura et al., 2013). them results in serious environmental pollution. Furthermore the large outbreak of starfish causes Analysis of inorganic components significant loss of the marine ecosystem and fishing gears (Kim, 1969). There is no effective method to control The micronutrient content of starfish was determined. Briefly, these large outbreaks of starfish. Recently, many studies starfish was cut into small pieces and 1 g of starfish sample dissolved in a furnace and diluted to 200 mL with 1 N HCl. The have been conducted to examine the activity of saponin diluted solution was then analyzed using combustion thermal against bacteria, fungi and even tumor cells (Robin et al., conductivity (CTC) and inductively coupled plasma (ICP) 2013). However, little information about the biological spectrophotometer method. Moisture content was determined with properties of starfish saponin has been reported. minced starfish sample by drying in an oven at a temperature of Extensive investigation of starfish, both chemically and 105°C for 5 h (Luo et al., 2011). pharmacologically, is now a demandable issue for utilization of starfish resources. Preparation of crude extracts Therefore, it is necessary to clarify the molecular identification and biological properties of starfish for the The extraction procedure was followed according to the method advanced utilization of starfish resources. In this context, described by Yasumoto et al. (1966). Briefly, one kilogram of first of all species identification of starfish was done by starfish was cut into small pieces and then minced using a food grinder (Kitchen Aid, St. Joseph, Michigan, USA). The extraction PCR amplification method from the view point of large was carried out with 3 L of methanol and repeated twice with 2 L of species variation. The micronutrient content of A. methanol. The extract was filtered through Whatman filter paper No. amurensis was evaluated for utilizing these in animal 2. The filtrate was concentrated up to 250 ml with a rotary feed and plant growth promotion. Based on these evaporator (EYELA, Tokyo, Japan) under reduced pressure at experiments, we evaluated biological properties such as 45ºC. The concentrate was stirred with an equal volume of water antifungal and hemolytic activity of A. amurensis. (250 ml) and defatted with 250 ml benzene. After being freed from benzene, pH of the extract was adjusted to 3 with 1N hydrochloric acid and then neutralized using 1N sodium hydroxide. The extract was dialyzed through an ultra-filtration membrane (MWCO: 1000, MATERIALS AND METHODS Millipore-amicon, Billerica, MA, USA) and then partitioned with n- butanol three times. After the n-butanol extract was concentrated Sample collection up to 150 ml, three volume of diethyl ether and a half volume of water were added. Finally, the aqueous layer was lyophilized and stored in a desiccator until further analysis. The crude extract A. amurensis was collected from the coast of Kobe, Hyogo prefecture, Japan (latitude N d gitude f samples (20 mg/ml) were applied to thin layer chromatography E in February 2014 and immediately brought to the (TLC) plates (silica gel 60 F254, 10 × 20 cm, layer thickness 0.25 laboratory in fresh conditions in ice. Freshly collected samples were mm, particle size of 10- 0 μm; Merck, D rmst dt, Germ y , immediately washed to remove mud and other particles and developed in chloroform:methanol:water (65:35:10, lower phase) as subsequently stored at -60°C until use. the mobile phase. Plates were then sprayed with 50% sulfuric acid Sharmin et al. 165
followed by heating at 110°C for 10 min. solution were mixed with 0.5 ml diluents containing 1, 5, 10, 50, 100, 500, and 1000 µg/ml concentrations of individual crude starfish extract in PBS solution. The mixtures were incubated for 30 min at Antifungal activity 37ºC and centrifuged at 270 ×g for 5 min. A volume of 1.5 ml PBS and distilled water were used as minimal and maximal hemolytic The antifungal activity of the starfish extract was performed using controls, respectively. After centrifugation, the presence of a standard well diffusion method. Fungal strains were obtained from suspension of a uniform red color was considered to indicate the Japan Collection of Microorganisms (JCM) and NITE Biological hemolysis, and a button formation in the bottom of the wells Resource Center (NBRC). Two yeasts Saccharomyces cerevisiae c stituted ck f hem ysis A v ume f 0 μ f e ch (JCM 2194) and Rhodotorula glutinis (JCM 8173), the three supernatant was transferred to a 96-well flat bottom micro plate, filamentous fungi such as Aspergillus flavus (JCM 12721), and the absorbance at 540 nm was measured with a micro plate Cladosporium sphaerospermum (NBRC 4460), and Fusarium reader (680 Microplate readers, BIO-RAD, Tokyo, Japan). Each oxysporum (NBRC 5942), and the dermatophyte fungi Trichophyton sample was transferred three times into a 96-well micro plate. The mentagrophytes (NBRC 32410) was tested. Yeast and filamentous experiments was done in triplicate and expressed as mean ± fungi were cultivated on potato dextrose agar, DAIGO (3.9%). standard deviation (SD). Dermatophyte fungi were cultivated on sabouraud agar (4% glucose, 1% bactotrypton and 2% agar). The antifungal activity was evaluated with the disc diffusion method described by Reinheimer Data analysis et al. (1990). One hundred microliters of cultured fungi was uniformly smeared on an agar plate by a smear loop. Then 8 mm Statistical analyses were performed using SPSS software (SPSS diameter sterilized paper disc (Toyo Roshi Kaisha Ltd, Tokyo, 16.0, IBM, USA). Data are expressed as mean ± SD and compared Japan) was loaded with 70 µl of the crude extract sample at the with one way analysis of variance (ANOVA). Significant differences concentrations of 10 mg/ml, and then placed on agar plate. were determined by Tukey’s test at p < 0.05 level. Thereafter, the plates were incubated at 27°C for A. flavus, F. oxysporum, C. sphaerospermum and T. mentagrophytes for 48 h and at 30°C for S. cerevisiae and R. glutinis for 24 h. Tea seed RESULTS AND DISCUSSION saponin was obtained from Sigma Aldrich (St. Louis, MO, USA) used for positive control and distilled water was used for the Identification of starfish species negative control. A clear zone with a diameter was taken as antifungal activity. The whole analytical procedure of the experiment was carried out twice and replicated three times. The First of all, species identification of starfish was done mean value of each experiment was considered for further data based on their phenotypic description including external analyses. structural appearance and morphological characteristics. Subsequently, species identification of starfish by DNA-
Determination of minimum inhibitory concentration (MIC) based method was carried out by a direct DNA sequencing analysis. Partial nucleotide sequence data of The fungal strains were grown on potato dextrose agar and 16S rRNA gene was compared with NCBI gene data sabouraud agar. After incubation, fungal growths were suspended base. Figure 1 shows aligned DNA sequences of the in normal saline (0.9% NaCl). The minimum inhibitory concentration amplified partial 16S rRNA region from the samples. (MIC) values for each crude extract were determined through micro- From the results of the alignment with the estimated dilution assay following a method described by Kumar et al. (2007) with minor modification. A 20 µl crude extract initially prepared (at species, it was found that the partial sequence of the the concentration of 10 mg/ml) and added into the first well. From PCR products from the sample was almost identical with here the solution was transferred into eight consecutive wells and those of A. amurensis (98.1%), although. Thus, it was then 10 µl inocula were added and kept in an incubator at 27°C (A. confirmed that identification of starfish is enabled by flavus, F. oxysporum and C. sphaerospermum) and 30°C (S. using the nucleotide sequence encoding 16S rRNA gene cerevisiae and R. glutinis). The fungal suspensions were adjusted of mtDNA. Mitochondrial gene order has been with broth to a concentration of 1.0 to 5.0×103 spore/ml and stored at 4°C for further analysis. A control was maintained with only demonstrator to be one of the most useful methods for culture medium of fungal cells. Values obtained for crude extract molecular identification (Matsubara et al., 2005). Previous was compared with the values from control and the difference is studies have reported that the rapid diversification and considered as growth inhibit on activity. MIC was defined as the adaptation to modern environments may conceal the lowest concentration of the compound to inhibit the growth of primitive status of asteroid groups (Blake, 1987). microorganisms. The experiments were done in 3 replicates and the mean values of the result were taken. Therefore, it was hypothesized that the universal primer (16SarL and 16SbrH) could be amplified in the partial region of A. amurensis. As a result, partial 16SrRNA Hemolytic activity region of the starfish used in this study could be amplified by using the universal primers. PCR products of A. Sheep blood was obtained from the Japanese Biological Center amurensis had a length of approximately 400 bp (Figure (Tokyo, Japan). Hemolytic activity was determined according to the 1). method described by Charles et al. (2009) with slight modifications.
Briefly, aliquot of 2 ml of blood were washed three times with PBS (phosphate buffer saline) solution (0.15 M NaCl-0.01M Tris-HCl, pH 7.0) by centrifugation at 1090 × g for 5 min at 4°C. Washed Analysis of inorganic components erythrocytes were suspended in the PBS solution to obtain a concentration of 2%. Then, 0.5 ml of erythrocytes and 1 ml of PBS The result of moisture and micronutrient contents of A. 166 Afr. J. Biotechnol.
Sample G A A C T C T C C A A A A A A A T T A C G C T G T T A T C C C T G C G G T A A C T T A T T C C T T T G C T C G C T A T C 60 Asterias amurensis G A A C T C T C C A A A A A A A T T A C G N T G T T A T - - C T G C G G T A A C T T A T T C C T T T G C T C G C T A T C 58 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
Sample T A G C G G A T C A C T T T A T T T T A A A A T G G T T A T T T T T T A T G T T T T T A G C G G A G G C T T T T T A T A 120 Asterias amurensis T A G C G G A T C A C T T T A T T T T A A A A T G G T T A T T T T T T A T G T T T T T A G C G G A G G C T T T T T A T A 118 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
Sample C T C C G C G A T T G C C C C A A T C A A A G T T A G T A T A T T A A A A G G C T A A G A A T A A A A A A T T A G A T T 180 Asterias amurensis C T C C G C G A T T G C C C C A A T C A A A G T T A G T A T A T T A A A A G G C T A A G A A T A A A A A A T T A G A T T 178 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
Sample T T A T A A A A T T T T T A T A A G T T T A A C A T T A G A T T T A T T A T T C T T T A T T A C C A C T A A T A T T T T 240 Asterias amurensis T T A T A A A A T T T T T A T A A G T T T A A C A T T A G A T T T A T T A T T C T T T A T T A C C A C T A A T A T T T T 238 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
Sample T A C T A A A G C T C G A C A G G G T C T T C T C G T C C T A C G A G T T T A T T T C C G C T T C T T C A C G A A A A T 300 Asterias amurensis T A C T A A A G C T C G A C A G G G T C T T C T C G T C C T A C G A G T T T A T T T C C G C T T C T T C A C G A A A A T 298 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
Sample A T A A A A T T C A A G T T A T A A G A A A G A G A C A G C T T A A C C C C A G T C T T G C C A - T T C A T A C C A G C 359 Asterias amurensis A T A A A A T T C A A C T T A T A A G A A A G A G A C A G C T T A A C C C C A G T C T T G C C A C T T C A T A C C A G C 358 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
Sample C T C T A T T T A A G A G G C A A A T G A T T A T G C T A C C T T T G C A C 3 9 7 Asterias amurensis C T C T A T T T A A G A G G C A A - T G A T T A T G C T A C C T T T G C A C 3 9 5 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
Figure 1. Aligned nucleotide sequences of partial mitochondrial 16S ribosomal RNA gene from A. amurensis. The identical nucleotides were shown by dots.
Table 1. Micronutrient contents of A. amurensis.
Content A. amurensis Method Unit Water 63.90 105ºC % C 8.10 CTC % N 1.50 CTC % P 0.06 ICP % K 1.04 ICP % Na 0.32 ICP % Ca 9.40 ICP % Mg 0.60 ICP % Cd 0.13 ICP µg/g Cu 2.10 ICP µg/g Pb 0.25 ICP µg/g Hg 0.03 AAS µg/g As 2.10 ICP µg/g
CTC, Combustion thermal conductivity method; ICP, inductively coupled plasma spectrophotometer method; AAS, atomic absorption spectrometer method.
amurensis is shown in Table 1. The Cu and As content The results in Table 1 showed that there are no great were found with the similar value of 2.10 µg/g. Likewise, differences on the micronutrient content (Hg, Cd, Pb) in high level of Ca content was observed with the value of starfish species. However, Cd, Cu and As contents had 9.40% of dry weight in the inorganic analysis coupled. species-specificity. Ca and P are minerals that have an Sharmin et al. 167
30 a
25 ab ab b b b 20
15
10 Zone ofZone inhibition (mm) 5
0
Figure 2. Antifungal activity of crude extracts from A. amurensis against six fungi, S. cerevisiae (JCM 2194), R. glutinis (JCM 8173), A. flavus (JCM 12721), C. sphaerospermum (NBRC 4460), F. oxysporum (NBRC 5942), and T. mentagrophytes (NBRC 32410) at the concentrations of 10 mg. Values are average of three replicates ± standard deviation. Values with different letters indicate sig ific t differe ces f r p < 0 0 cc rdi g t Tukey’s test
important role to the development and maintenance of found against S. cerevisiae and A. flavus (Figure 2). Choi the skeleton, together with many other physiologic et al. (1999) noted that the methanol and water extracts functions in the body (Bonjour, 2011). The Ca content in of Asterina pectinifera were sensitive to Aspergillus niger fresh starfish is reported 12.97% by Sorensen (2015) but and T. mentagropytes. Recently, Suguna et al. (2014) in our study we have got 9.40%, which might be due to reported that the highest antifungal activity found in n- the variation of species, size, season, source, analytical butanol extract of Luidia maculate against T. method etc. Moisture content of the starfish A. amurensis mentagrophytes was 21.0 ± 1.00 mm. However, in our was detected as 63.9%, which was slightly lower than the study, A. amurensis crude extract showed slightly higher starfish of A. planci with the value of 67.7 to 69.1% by zone inhibition activity (25.5 ± 1.15 mm) against T. weight (Luo et al., 2011). When formulating diets for mentagrophytes than that of L. maculate. In Figure 2, animals (pigs, chicken, and fish) or fertilizer for zone of inhibition was found significantly highest (p<0.05) agriculture sector, it is necessary to consider an in T. mentagrophytes compared to R. glutinis, C. appropriate amount of micronutrient content. Ishii et al. sphaerospermum and F. oxysporum but not with other (2007) reported that the plant growth regulating activities two fungal species (S. cerevisiae and A. flavus). The of metabolites from the starfish A. amurensis, suggest difference in antifungal activity of starfish extract from that these active natural products could be employed for various species, extracted using different procedures, maintaining ecofriendly agricultural production. differ in their biological activities (Sen et al., 1998). Remarkable antifungal activity was exhibited by plant saponins from tea seed against S. cerevisiae and T. Antifungal activity mentagrophytes with growth inhibitory activity of 24.1 and 23.1 mm, respectively. There was no growth inhibitory The antifungal spectra of the crude extract from starfish activity observed against A. flavus, R. glutinis, F. against six fungi are presented in Figure 2. A. amurensis oxysporum, and C. sphaerospermum. exhibited predominant growth inhibitory activity against all the human fungal pathogens tested. Growth inhibitory activity of A. amurensis was in the range of 14.4 to 25.5 Minimum inhibitory concentration (MIC) mm. The strongest antifungal activity was observed in A. amurensis extract against T. mentagrophytes. Next to The extracts that showed antifungal activity in this assay this, moderate levels of growth inhibitory activity were were subjected to the minimum inhibitory concentrations 168 Afr. J. Biotechnol.
Table 2. Minimum inhibitory concentration (MIC) of A. amurensis crude extract against six fungal strains.
Fungal strains MIC (µg/ml) S. cerevisiae 62.50 R. glutinis 50.00 A. flavus 35.71 F. oxysporum 50.00 C. sphaerospermum 83.30 T. mentagrophytes 35.71
Data are the average of 3 independent replicates. Crude extract was added with amount of 500 µg/ml.
120
100
(%) 80
60 hemolysis
40
Percentage ofPercentage 20
0 1 5 10 50 100 500 1000
-20 Concentration of starfish crude extract (µg/ml)
Figure 3. Hemolytic activity of crude extract from A. amurensis against sheep erythrocytes. Hemolytic percents of saline and distilled water were included as minimal and maximal hemolytic controls. The data represent the mean± standard deviation; n=3.
(MIC) evaluation and the results are presented in Table A. amurensis exhibited the maximum hemolytic activity 2. The crude extract of A. amurensis showed significant with 98.78 ± 7.63% at 1000 µg/ml concentration. There antifungal activity against A. flavus and T. was no hemolytic activity observed at the concentration mentagrophytes with the MIC value of 35.71 µg/ml for of 1 µg/ml while slightly activity observed at the both. On the other hand, R. glutinis and F. oxysporum concentration of 5 and 10 µg/ml. In general, the increase showed similar MIC value of 50.00 µg/ml. Among six in concentration of test extracts from 50 to 1000 µg/ml fungal strain highest MIC value was obtained in C. has been found to increase the hemolytic activity (Figure sphaerospermum (83.30 µg/ml) followed by 62.5 µg/ml 3). The crude extract of A. amurensis exhibited strong MIC in S. cerevisiae. activity against sheep erythrocytes. Our results support the findings of Imamichi and Yokoyama (2013) who reported that crude extract from pyloric caeca of A. Hemolytic activity amurensis showed high hemolytic activity in rabbit erythrocytes. Hemolytic assays have also been Results of hemolytic activity have shown that, extract of developed for detecting saponin in drugs or plant extracts Sharmin et al. 169
role in the study of saponin. Based on the analysis of the 9 chromatogram and their retention factor, it was observed that these compounds consist together with the polar (1 8 to 6) and non polar (7 to 10) compounds. Raphaela et al. (2014) reported that the polarity of saponin varied 7 because of the sugar units linked to its structure. According to Raphaela et al. (2014) the biological activity of saponins may be affected by many factors such as the aglycone, number, position, and chemical structure of sugar side-chains. Many natural products and materials from marine animals have been used to treat various kind of disease and might be good substances for the development drugs in pharmaceutical sector. 6
5 Conclusion
In this study, we analyzed 16S rRNA gene fragment of mitochondrial DNA and confirmed that 16S rRNA 4 markers are useful and applicable to identify A. amurensis species. The present study revealed the 3 potential antifungal and hemolytic activity of starfish A. 2 amurensis. The biological properties of A. amurensis extended by starfish crude extract are very much 1 appreciable for the future development of novel functional food and pharmaceutical ingredients. Furthermore, the current results have motivated us to carry further studies on isolation and characterization of the bioactive compounds of this starfish in order to evaluate their mechanism and mode of action.
Conflicts of Interests
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Vol. 16(4), pp. 171-178, 25 January 2017 DOI: 10.5897/AJB2016.15785 Article Number: 292290362539 ISSN 1684-5315 African Journal of Biotechnology Copyright © 2017 Author(s) retain the copyright of this article http://www.academicjournals.org/AJB
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Genetic diversity among Sawakni, Berberi and Najdi sheep breeds in Saudi Arabia using microsatellites markers
Ahmed Hossam Mahmoud1*, Ayman swelum2, Mohammad Abul Farah1, Khalid. Alanazi1, 1 3 4 4 Ahmed Rady , Mahmoud Salah , Nabil Amor and Osam Mohammed
1Department of Zoology, College of Science, King Saud University, Riyadh, Saudi Arabia. 2Department of Animal Production, College of Food and Agriculture Sciences, King Saud University, Riyadh, Saudi Arabia. 3Biology Department, College of Science, Jazan University, Jazan, Saudi Arabia. 4KSU Mammals Research Chair, Department of Zoology, College of Science, King Saud University, Riyadh Saudi Arabia.
Received 16 November, 2016; Accepted 19 January, 2017
The present study was conducted to assess the genetic diversity and population genetic structure of three sheep populations namely; Sawakni (SW), Berberi (BR) and Najdi (NJ), in Saudi Arabia, utilizing 45, 18 and 31 individual blood DNA extractions, respectively. Seventeen microsatellite markers were used to genotype these 94 sheep individuals. There were 195 alleles generated employing the 17 microsatellites loci with a mean of 11.47 alleles per locus, with a range of observed and expected heterozygosity from 0.651 to 0.989 and 0.590 to 0.816, respectively. The total number of alleles of 169, 127 and 111, and their means of effective number of alleles of 4.983, 4.192 and 3.781 were observed in SW, BR and NJ populations, respectively. Thirteen of the microsatellites loci studied in SW, seven loci in BR and five loci in NJ were found to be deviated from Hardy-Weinberg Equilibrium. The fixation genetic indices (FST) among the three populations were very low, ranging from 0.029 (between SW and BR) to 0.038 (between NJ and BR), indicating low population differentiation among the three sheep populations. The present study showed that the microsatellite markers are powerful tools in breeding programs, however more microsatellites may be needed for a broad judgment on the genetic status of the sheep populations in Saudi Arabia.
Key words: DNA, genetics, microsatellite, Saudi sheep.
INTRODUCTION
Inbreeding may lead to the loss of genetic variation within become extinct. To prevent the extinction of a breed and the livestock breeds and that the breed itself may conserving its merit, molecular biological approaches,
*Corresponding author. E-mail: [email protected].
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such as the polymerase chain reaction (PCR) technique To reduce the possibility of cross contamination and variation in the (Nicholas et al., 1996), utilizing various DNA markers amplification reactions, master mixes containing all PCR reagents (Erlich, 1991), has been established to study the genetic including the Kapa Taq polymerase enzyme (KAPA Biosystems, Boston, MA, USA) except DNA templates and primers were used. variation within and between different animal resources. The amplification program was performed using the Gene Amp Genetic markers such as DNA fingerprinting (DFP), PCR system 9700 thermocycler (Applied Biosystems, Warrington, randomly amplified polymorphic DNA (RAPD) and UK). The amplification protocol was an initial denaturation step for 2 microsatellites have been used in studying genetic min at 94°C, followed by 35 cycles at 94°C for 30 s, 55 ºC annealing variability, parentage verifications and genome mapping temperature (Table 1) for 30 s and 72°C for 30 s. The final step of the amplification protocol was the extension step at 72°C for 5 min. projects in llama, goat, sheep, cattle, chicken and camel All the reactions were carried out on 96 well PCR plates (Applied (Groenen et al., 2000; Jianlin et al., 2000; Sasse et al., Biosystems, Warrington, UK). The microsatellite primers were 2000; Krüger et al., 2002; Geng et al., 2003; Li et al., labeled with dyes FAM, TAMN, HEX and ROXN and microsatellite 2004; Yang et al., 2004; Peter et al., 2007; Mahmoudi et data were analyzed in the ABI Prism® 3500 Genetic analyzer al., 2010 and Spencer et al., 2010). In sheep, genetic (Applied Biosystems, Warrington, UK). Each analyzed PCR diversity have been investigated by several studies using reaction contained GeneScan® LIZ 500 molecular weight standards (Applied Biosystems, Warrington, UK). The quantity and quality of primers developed for amplification of microsatellite loci DNA were checked by spectrophotometer (Jenway Genova (Diez-Tascon et al., 2000; Hassan et al., 2003; Arora and Spectrophotometer Krackler Scientific Incorporation, USA). Bhatia, 2004; Gutiérrez-Gil et al., 2006; El-fawal, 2006; Peter et al., 2007). In Saudi Arabia, sheep population exceeding 7.2 million Statistical analyses head (Ayadi et al., 2014) and plays an important role in sustenance of life of many local communities. Several The basic parameters for each locus and populations, allele frequencies, observed number of alleles (Na), effective number of breeds of sheep have been identified in different regions alleles (Ne), observed (Ho), expected (He) heterozygosities and in Saudi Arabia based on some morphological Polymorphism Information Content (PIC), were measured using characteristics. They are well adapted to the prevailing Cervus version 3.0.3 (Kalinowski et al., 2007). Deviations from adverse environment of Saudi Arabia; the most popular Hardy-Weinberg equilibrium (HWE) and Wright's F-statistics (FIS, native breeds are Najdi, Naeimi, and Herri breeds FST, and FIT) within and among the sheep populations were calculated by using GenePop version 4.0.10 (Raymond and (Abouheif et al., 1989). Sawakni and Berberi are two Rousset, 1995). We used the Bayesian clustering method exotic breeds introduced to the sheep populations of the implemented in Structure v. 2.3.1 (Pritchard et al., 2000) to evaluate Kingdom of Saudi Arabia from Sudan, and Somalia, the number of genetic units within the 94 individuals of the three respectively. They became popular choices for many studied sheep populations. The likelihood of a specific number of Saudi in the last decade, comparable to Najdi breed for homogenous genetic clusters (K) in the dataset, and the relative many cases. contribution of each individual to each cluster was estimated under admixture model with Markov Chain Monte Carlo (MCMC) of 2.1 × The genetic variations within and among these sheep 106 iterations after a burn-in of 1 × 105, for K = 1 to K = 6. Ten populations are poorly documented. Therefore, the independent simulations for each K (1–6) were performed. The present study was conducted to investigate the genetic most likely number of genetic units was assessed using the diversity within and among three sheep populations resulting likelihood, as well as by examining the modal distribution (Sawakni, Berberi and Najdi), as a way for further of DeltaK (ΔK) (Evanno et al., 2005). development programs of sheep breeding in the Kingdom of Saudi Arabia. RESULTS
MATERIALS AND METHODS The 94 sheep individuals of the three populations: (SW), (BR) and (NJ) were genotyped using 17 microsatellite A total of 94 individuals of sheep belonging to three populations: loci. The seventeen microsatellite loci were polymorphic. Sawakni (45 SW), Berberi (18 BR) and Najdi (31 NJ) were selected from five different localities in Saudi Arabia. Blood samples (10 mL) Table 2 shows, for the three populations, the values of were collected from each sheep by jugular venipuncture into the total number of alleles (Na), mean effective number of vacuum EDTA tubes. DNA was extracted from blood samples alleles (Ne) and observed (Ho) and expected (He) according to the manufacturer’s instructions of a QIAgen DNeasy heterozygosities. A total of 195 alleles were detected in Kit (Hilden, Germany). Table 1 shows the seventeen microsatellite which 169, 127, and 111 alleles were observed primer-pairs, a part of a section of markers recommended by the respectively in SW, BR and NJ populations. Out of these International Society of Animal Genetics (ISAG)/FAO (FAO, 2011), used to investigate the sheep genotypes. Purity and concentration 195 alleles, 61 were designated as private alleles in of each sample was quantified using NanoDrop 2000 which 39 were found in SW, 15 in BR and 7 in NJ spectrophotometer (Thermo Scientific, Wilmington, Delaware, populations. The numbers of effective alleles averaged USA). These markers were selected by taking into account the level 4.893, 4.192 and 4.781 in SW, BR and NJ sheep breeds, of polymorphism previously detected in other studies and the respectively. location on different chromosomes (Peter et al., 2007; Ferrando et The average number of alleles per locus was 11.470, al., 2014; Yilmaz et al., 2015). Polymerase chain reaction (PCR) amplifications were carried out in a 25 µl reaction volume ranging between 7 (locus OarCP34) and 18 (locus containing100 ng of template DNA and 2 µl of each 10 µM primer. HUJ616) alleles. Twelve out of the 17 loci studied have
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Table 1. Primers sequences and labels of the 17 primer pairs used to amplify microsatellite regions in the Ovis aries of the present study.
Locus name Sequences 5’→ 3’ forward/ reverse Label Allele size (bp) Chromosomal location GGAAGCAATGAAATCTATAGCC 7 ILSTS005 56FAM 174-218 TGTTCTGTGAGTTTGTAAGC GTCCATTGCCTCAAATCAATTC 5 MCM527 56-TAMN 165-187 AAACCACTTGACTACTCCCCAA GGACTCTACCAACTGAGCTACAAG SRCRSP5 5HEX 126-158 18 GTTTCTTTGAAATGAAGCTAAAGCAATGC ATTAAAGCATCTTCTCTTTATTTCCTCGC OarFCB128 56FAM 96-130 2 CAGCTGAGCAACTAAGACATACATGCG TTCAAACTACACATTGACAGGG HUJ616 56-ROXN 114-160 13 GGACCTTTGGCAATGGAAGG TTTATTGACAAACTCTCTTCCTAACTCCACC OarHH47 56-TAMN 130-152 18 GTAGTTATTTAAAAAAATATCATACCTCTTAAGG GCTTGCTACATGGAAAGTGC ILSTS11 56FAM 256-294 9 CTAAAATGCAGAGCCCTACC CTCTATCTGTGGAAAAGGTGGG BM8125 56-TAMN 110-130 1 GGGGGTTAGACTTCAACATACG CTATATGTTGCCTTTCCCTTCCTGC OarFCB226 5-HEX 119-153 2 GTGAGTCCCATAGAGCATAAGCTC AATCCAGTGTGTGAAAGACTAATCCAG OarAE129 56FAM 133-159 5 GTAGATCAAGATATAGAATATTTTTCAACACC GTATACACGTGGACACCGCTTTGTAC OarJMP29 56-ROXN 96-150 24 GAAGTGGCAAGATTCAGAGGGGAAG AGAGGATCTGGAAATGGAATC SRCRSP9 56FAM 99-135 12 GCACTCTTTTCAGCCCTAATG GGGTGATCTTAGGGAGGTTTTGGAGG MAF214 56FAM 174-282 16 AATGCAGGAGATCTGAGGCAGGGACG GCTGAACAATGTGATATGTTCAGG OarCP34 56-ROXN 112-130 3 GGGACAATACTGTCTTAGATGCTGC CCCTAGGAGCTTTCAATAAAGAATCGG OarFCB304 5-HEX 150-188 19 CGCTGCTGTCAACTGGGTCAGGG GATCACAAAAAGTTGGATACAACCGTGG MAF209 5-HEX 109-135 17 TCATGCACTTAAGTATGTAGGATGCTG AAAGGCCAGAGTATGCAATTAGGAG MAF65 56-TAMN 123-163 15 CCACTCCTCCTGAGAATATAACATG
more than 10 alleles (ILSTS005, MCM527, SRCRSP5, populations as indicated by the very low values of the OarFCB128, HUJ616, OarHH47, OarFCB226, pairwise fixation genetic indices (Fst) among the three OarJMP29, SRCRSP9, MAF214, OarFCB304 and populations. Fst values ranged from 0.029 (between SW MAF65), and the other five loci possess less than 10 and BR, and between SW and NJ) to 0.038 (between NJ alleles (ILSTS11, BM8125, OarAE129, OarCP34 and and BR) as indicated in Table 4. HWE results (Table 5) MAF209). Observed heterozygosity (Ho) and expected showed that 4, 8 and 12 loci in SW, BR and NJ sheep heterozygosity (He) averaged 0.851 and 0.746, breeds respectively followed HWE, and the rest are respectively (Table 2). deviated from the HWE at p>0.05. The mean of Results of the F-statistics for each of the 17 analyzed Polymorphic Information Content (PIC) for the 17 loci in the three sheep populations are shown in Table 3. microsatellite marker was 0.754, ranged from 0.627 Mean values for FIS, FIT and FST were -0.145, -0.097 and (marker OarAE129) to 0.863 (marker OarFCB226) (Table 0.042, respectively. The low FIS and FIT mean values, 4). which are very close to zero, indicated low level of Bayesian clustering assignment, on SW, BR and NJ inbreeding within and among the populations. It also sheep individuals, revealed that Ln L(K) increased with points towards low genetic differentiation among the the number of clusters tested (K) and reached the highest
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Table 2. Number of alleles (Na), Mean effective number of alleles (Ne), observed (HO) and expected (He) heterozygosities for each locus of the three different sheep populations, SW, BR and NJ.
SW BR NJ Locus Na Ne Ho He Na Ne Ho He Na Ne Ho He ILSTS005 9.000 5.031 0.933 0.801 9.000 5.786 0.889 0.827 6.000 3.922 0.548 0.745 MCM527 11.000 4.994 0.911 0.800 8.000 4.909 1.000 0.796 9.000 5.045 0.774 0.802 SRCRSP5 9.000 4.099 1.000 0.756 5.000 3.880 1.000 0.742 5.000 3.360 0.452 0.702 OarFCB128 13.000 5.140 0.400 0.805 8.000 5.143 0.778 0.806 8.000 4.711 0.774 0.788 HUJ616 15.000 7.219 1.000 0.861 12.000 6.231 1.000 0.840 5.000 2.758 0.645 0.637 OarHH47 12.000 4.816 1.000 0.792 4.000 2.339 0.833 0.573 9.000 3.105 0.935 0.678 ILSTS11 7.000 4.436 0.933 0.775 7.000 4.596 1.000 0.782 5.000 3.867 0.871 0.741 BM8125 6.000 3.415 1.000 0.707 6.000 3.028 1.000 0.670 8.000 3.891 0.677 0.743 OarFCB226 16.000 7.910 0.733 0.874 11.000 3.682 0.778 0.728 8.000 5.125 0.935 0.805 OarAE129 6.000 2.560 0.978 0.609 6.000 3.115 1.000 0.679 3.000 2.750 0.516 0.636 OarJMP29 10.000 4.436 0.756 0.775 8.000 3.904 1.000 0.744 9.000 4.281 0.839 0.766 SRCRSP9 9.000 5.728 0.933 0.825 8.000 4.291 1.000 0.767 5.000 3.041 0.742 0.671 MAF214 10.000 3.750 0.756 0.733 4.000 2.167 0.722 0.539 4.000 1.990 0.516 0.497 OarCP34 6.000 4.219 0.978 0.763 7.000 4.985 0.944 0.799 6.000 4.418 0.742 0.774 OarFCB304 12.000 5.769 1.000 0.827 10.000 4.985 1.000 0.799 10.000 5.653 0.645 0.823 MAF209 8.000 4.383 0.911 0.772 7.000 3.904 1.000 0.744 6.000 3.041 0.645 0.671 MAF65 10.000 5.273 1.000 0.810 7.000 4.320 1.000 0.769 5.000 3.325 0.968 0.699 Mean 9.941 4.893 0.895 0.782 7.471 4.192 0.938 0.741 6.529 3.781 0.719 0.716 SE 0.725 0.315 0.038 0.015 0.536 0.272 0.024 0.020 0.501 0.240 0.038 0.020
Table 3. F-statistics analysis for each of 17 microsatellite markers among SW, BR and NJ sheep.
Locus Fis Fit Fst ILSTS005 0.001 0.031 0.030 MCM527 -0.120 -0.073 0.042 SRCRSP5 -0.114 -0.093 0.019 OarFCB128 0.186 0.242 0.068 HUJ616 -0.131 -0.057 0.066 OarHH47 -0.355 -0.302 0.039 ILSTS11 -0.220 -0.195 0.020 BM8125 -0.263 -0.224 0.031 OarFCB226 -0.017 0.048 0.064 OarAE129 -0.296 -0.176 0.092 OarJMP29 -0.135 -0.109 0.023 SRCRSP9 -0.182 -0.133 0.041 MAF214 -0.127 -0.037 0.080 OarCP34 -0.140 -0.134 0.006 OarFCB304 -0.080 -0.045 0.033 MAF209 -0.169 -0.130 0.033 MAF65 -0.303 -0.270 0.025 Mean -0.145 -0.097 0.042 SE 0.031 0.031 0.006
value at K = 5 groups (Figure 1a). Based on the ΔK number of clusters (Figure 1a). The estimated individual values, the result of K = 2 seems to be the optimal genotype membership coefficient (Q) in each ancestral
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Table 4. Pairwise population FST values among SW, BR and sheep populations. This range was comparable with that NJ sheep. observed (6-18) in four Romanian sheep populations (Kevorkian et al., 2010; Jakaria et al., 2012). It was Population SW BR higher than that observed by Pramod et al. (2009) in BR 0.029 Vembur sheep population of South India (2-9) and by NJ 0.029 0.038 Radha et al. (2011) in Kilakarsal sheep population (3-12).
SW = Sawakni; BR = Berberi; NJ = Najdi. Yilmaz et al. (2015) found a range of 15 to 31 alleles per locus in Turkish sheep populations (Gökçeada, Kıvırcık, Karacabey Merino, and Sakız) whereas Ricardo et al. (2016) has reported a range of 10 to 23 alleles per locus Table 5. Number of loci significantly deviating from Hardy-Weinberg in the Colombian sheep. In the study of Turkish sheep equilibrium (HWE) and number of alleles at each locus (K) for SW, populations by Yelmaz et al. (2015) they observed a total BR and NJ sheep populations of Saudi Arabia. of 352 alleles with a mean number of 20.71 alleles per locus, whereas in the Colombian sheep, Ricardo et al. Locus SWa BR NJ K PIC (2016) showed 157 alleles with a mean number of alleles ns ILSTS005 *** * 12 0.787 per a locus of 14.27. do Amaral Crispima et al. (2014) MCM527 ns ns ns 11 0.814 showed 100 alleles with mean 12.5 alleles per locus in SRCRSP5 *** ** ns 11 0.704 Pantaneiro sheep in Brazil, Sassi-Zaidy et al. (2014) OarFCB128 *** ns ns 14 0.846 found 270 alleles with a mean of 15.88 alleles per locus HUJ616 * ns ns 18 0.817 in Tunisian sheep, and in a Vembur sheep in South India, OarHH47 ns ns ns 12 0.721 Pramod et al. (2009) found 147 alleles with mean 5.88 ILSTS11 *** ns * 8 0.750 alleles per locus. However, our finding indicated almost BM8125 *** *** ns 9 0.691 mid-point between these values, with actual total number of alleles of 195 and a mean number of alleles per locus OarFCB226 *** ** ** 16 0.863 of 11.470. Private alleles defined in this study as alleles OarAE129 *** *** ns 8 0.627 unique to a single population were observed to be 39, 15 OarJMP29 *** ** ns 13 0.753 ns ns and 7 alleles for SW, BR and NJ sheep populations, SRCRSP9 *** 11 0.777 respectively. Despite the low frequencies of these alleles, ns MAF214 *** *** 11 0.630 however, they can be distinguished among the three OarCP34 *** ** * 7 0.743 sheep populations and can be good indicators as breed OarFCB304 ns ** * 14 0.823 markers. Blackburn et al. (2011) observed two private MAF209 ns ns ns 9 0.722 alleles with low frequencies in the Sary-arkinsskaya MAF65 *** ns * 11 0.756 Kazakh sheep breed. Yilmaz et al. (2015) designated 7 alleles in the Karacabey Merino Turkish sheep breed. aThe breed abbreviations SW, BR and NJ are as follows: Sawakni, Berberi and Najdi, respectively. *SSR loci deviated from HWE at P < Means of effective number of alleles implied by the 0.05. three Saudi sheep populations, SW, BR and NJ, were 4.893, 4.192 and 3.781, respectively, with a grand mean of 4.289. Turkish sheep breed displayed higher mean effective number of alleles of 7.040 (Yilmaz et al., 2015). cluster for the optimal K number is represented in Balochi and Rakhshani sheep breed in Pakistan Figure 1b. For the three populations, averages of Q displayed the lowest average effective number of alleles coefficient were higher than 90%. In particular, SW and of 2.969 (Wajid et al., 2014). The mean observed BR breeds were clearly assigned to a single cluster, and heterozygosity values in the present study were 0.895, the second one includes exclusively NJ individuals 0.938 and 0.719 for SW, BR and NJ sheep breeds, (Figure 1b). The net nucleotide distances, based on allele respectively, with a grand mean of 0.851. This value is frequencies divergence among populations, recorded higher than that reported by other studies of Indonesian between the two clusters reached 2%. sheep (0.574), Coimbatore sheep in India (0.625) Turkish sheep (0.66) and Colombian sheep (0.680) (Jakaria et al., 2012; Hepsibha et al., 2014; Yilmaz et al., 2015; DISCUSSION Ricardo et al., 2016, respectively). On the other hand, the expected heterozygosity (He), the best estimator of Several researchers have investigated the genetic genetic diversity in a population (Kim et al, 2002), was variations among closely related breeds in farm animals 0.782, 0.741 and 0.716 for SW, BR and NJ sheep, using the microsatellite markers (Peter et al., 2007; respectively, with a grand mean of 0.746. It was found to Blackburn et al., 2011). The number of alleles per locus be higher than that reported by other studies in for the three breeds studied ranged from 7 to18, Indonesian sheep (0.687) but was lower than that in indicating of genetic polymorphism within the tested Turkish sheep (0.870) and Colombian sheep (0.770)
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Figure 1. (a) The approximate number of genetic clusters (K) within the three different sheep populations, SW, BR and NJ based on results from the software structure. The “estimated log probability of the data”, Ln Pr(X/K), (Pritchard et al., 2000), and ΔK (Evanno et al., 2005) are shown for each value of K from one to six. (b) The most likely value of K inferred by structure was two. Bar plot of the estimated membership coefficient, Q, for each of the 94 individuals in each of two genetic clusters (K). Each individual is represented by a thin vertical line, which is partitioned into K (2) colored segments that represent the individual's estimated membership fractions in K clusters. Black lines separate individuals of different clusters based on structure analysis, SW+BR and NJ.
(Jakaria et al., 2012; Yilmaz et al., 2015; Ricardo et al., could have resulted from the mutations, migration or 2016, respectively). Interestingly, the lowest Ho was nonrandom mating. Gene flow was high in some observed in SW sheep (0.400) in the OarFCB128 marker populations but lower in others. FIS value for all loci was and the lowest value of He was in the MAF214 marker of 0.145, which indicates that some moderate inbreeding NJ sheep breed (0.497). In general, all breeds showed has likely occurred within each population, although it high genetic diversity for all loci analyzed. A breed with does not explain the genetic variation among the three constant gene and genotype frequencies is said to be in sheep populations under investigation. Outbreeding is HWE (Falconer and Mackay, 1996). Of the most limited due to isolation of breeding groups to specific important steps in this study was to verify whether the geographical regions or even farms. In addition, FST value genotypes studied were in HWE. Results indicated that of 0.042 indicates little genetic differentiation has there were some genotypes with several loci that occurred. A previous study by Radha et al. (2011) using followed HWE (P<0.05); 4, 8 and 12 loci in SW, BR and 25 microsatellite markers in Indian sheep indicated that NJ sheep breeds, respectively. The deviation from HWE seven out of 25 loci in sheep populations were in HWE. may have resulted from reasons which we were unable to The least PIC value was 0.627 (OarAE129) indicating specify. It may have probably resulted from genetic drift that all microsatellite markers were highly polymorphic. or from both artificial and natural selection as well as it The high PIC values and also the average number of
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alleles per each locus indicate the appropriateness of Identification of the preference patterns of different breeds of sheep using the 17 microsatellite markers in investigating the for consumption in Saudi Arabia. Asian Australas. J. Anim. Sci. 2:129-132. genetic diversity within Saudi sheep. Álvarez IJ, Capote A, Traoré N, Fonseca K, Pérez M, Cuervo M (2012). Mean FST values among the three sheep populations Genetic relationships of the Cuban hair sheep inferred from ranged between 0.029 (between SW and BR microsatellite polymorphism. Small Rumin. Res. 104:89-93. populations), 0.029 (between SW and NJ populations) Arora R, Bhatia S (2004). Genetic structure of Muzzafarnagri sheep based on microsatellite analysis. Small Rumin. Res. 54:227-230. and 0.038 (between BR and NJ populations), indicating Ayadi M, Maatar AM, Aljumaah RS, Alshaikh MA, Abouheif MA (2014). little genetic differentiation among Saudi sheep Factors affecting milk yield composition and udder health of Najdi populations. Ferrando et al. (2014) also found close FST ewes. J. Anim. Vet. Adv. 6:28-33. value in six breeds located in the eastern Pyrenees Blackburn HD, Toishibekov Y, Toishibekov M, Welsh CS, Spiller SF, Brown M, Paiva SR (2011). Genetic diversity of Ovis aries ranging from 0.011 to 0.053. When Saudi sheep populations near domestication centers and in the New populations were compared with other populations from World. Genetica 139(9):1169-1178. different countries, the FST values were lower than those Diez-Tascon C, Littlejohn RP, Almeida PAR, Crawford AM (2000). found in this study (Sassi-Zaidy et al., 2014; Álvarez et Genetic variation within the Merino sheep breed: Analysis of closely related populations using microsatellites. 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