Search results for: 16S rDNA gene

Authors: Omar S. Sharaf

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The mitochondrial 12s rRNA (mt-12s rDNA) gene for pig-specific was developed to detect material from pork species in different products collected from Jordanian market. The amplification PCR products of 359 bp and 531 bp were successfully amplified from the cyt b gene of pig the amplification product using mt-12S rDNA gene were successfully produced a single band with a molecular size of 456 bp. In the present work, the PCR amplification of mtDNA of cytochrome b has been shown as a suitable tool for rapid detection of pig DNA. 100 samples from different dairy, gelatin and chocolate based products and 50 samples from baby food formula were collected and tested to a presence of any pig derivatives. It was found that 10% of chocolate based products, 12% of gelatin and 56% from dairy products and 5.2% from baby food formula showed single band from mt-12S rDNA gene.

Keywords: halal food, baby infant formula, chocolate based products, PCR, Jordan

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Authors: M. J. Norashirene, Y. Zakiah, S. Nurdiana, I. Nur Hilwani, M. H. Siti Khairiyah, M. J. Muhamad Arif

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In this study, six bacterial isolates of a slightly thermophilic organism from the Sg. Klah hot spring, Malaysia were successfully isolated and designated as M7T55D1, M7T55D2, M7T55D3, M7T53D1, M7T53D2 and M7T53D3 respectively. The bacterial isolates were screened for their cellulose hydrolytic ability on Carboxymethlycellulose agar medium. The isolated bacterial strains were identified morphologically, biochemically and molecularly with the aid of 16S rDNA sequencing. All of the bacteria showed their optimum growth at a slightly alkaline pH of 7.5 with a temperature of 55°C. All strains were Gram-negative, non-spore forming type, strictly aerobic, catalase-positive and oxidase-positive with the ability to produce thermostable cellulase. Based on BLASTn results, bacterial isolates of M7T55D2 and M7T53D1 gave the highest homology (97%) with similarity to Tepidimonas ignava while isolates M7T55D1, M7T55D3, M7T53D2 and M7T53D3 showed their closest homology (97%-98%) with Tepidimonas thermarum. These cellulolytic thermophiles might have a commercial potential to produce valuable thermostable cellulase.

Keywords: cellulase, cellulolytic, thermophiles, 16S rDNA gene

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Authors: Irina S. Kolesnikova, Alexander A. Dolskiy, Natalya A. Lemskaya, Yulia V. Maksimova, Asia R. Shorina, Alena S. Telepova, Alexander S. Graphodatsky, Dmitry V. Yudkin

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A cytogenetic and molecular genetic study of the family with a male child who had mental retardation and autistic features revealed an abnormal chromosome 13 bearing an enlarged p-arm with amplified ribosomal DNA (rDNA) in a boy and his father. Cytogenetic analysis using standard G-banding and FISH with labeled rDNA probes revealed an abnormal chromosome 13 with an enlarged p-arms due to rDNA amplification in a male child, who had clinically confirmed mental retardation and an autistic behavior. This chromosome is evidently inherited from the father, who has morphologically the same chromosome, but is healthy. The karyotype of the mother was normal. Ag-NOR staining showed brightly stained large whole-p-arm nucleolus organizer regions (NORs) in a child and normal-sized NORs in his father with 13p+-NOR-amount mosaicism. qRT-PCR with specific primers showed highly increased levels of 18S, 28S and 5,8 S ribosomal RNA (rRNA) in the patient’s blood samples compared to a normal healthy control donor. Both patient’s father and mother had no elevated levels of rRNAs expression. Thus, in this case, rRNA level seems to correlate with mental retardation in familial individuals with 13p+. Our findings of rRNA overexpression in a patient with mental retardation and his parents may show a possible link between the karyotype (p-arm enlargement due to rDNA amplification), rDNA functionality (rRNA overexpression), functional changes in the brain and mental retardation. The study is supported by Russian Science Foundation Grant 15-15-10001.

Keywords: mental retardation, ribosomal DNA–rDNA, ribosomal RNA–rRNA, nucleolus organizer region–NOR, chromosome 13

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Authors: Manjula Weerasekera, Chris Sissons, Lisa Wong, Sally Anderson, Ann Holmes, Richard Cannon

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The aim of this study was to characterize bacterial population and yeasts in saliva by Polymerase chain reaction followed by denaturing gradient gel electrophoresis (PCR-DGGE) and measure yeast levels by culture. PCR-DGGE was performed to identify oral bacteria and yeasts in 24 saliva samples. DNA was extracted and used to generate DNA amplicons of the V2–V3 hypervariable region of the bacterial 16S rDNA gene using PCR. Further universal primers targeting the large subunit rDNA gene (25S-28S) of fungi were used to amplify yeasts present in human saliva. Resulting PCR products were subjected to denaturing gradient gel electrophoresis using Universal mutation detection system. DGGE bands were extracted and sequenced using Sanger method. A potential relationship was evaluated between groups of bacteria identified by cluster analysis of DGGE fingerprints with the yeast levels and with their diversity. Significant interpersonal variation of salivary microbiome was observed. Cluster and principal component analysis of the bacterial DGGE patterns yielded three significant major clusters, and outliers. Seventeen of the 24 (71%) saliva samples were yeast positive going up to 10³ cfu/mL. Predominately, C. albicans, and six other species of yeast were detected. The presence, amount and species of yeast showed no clear relationship to the bacterial clusters. Microbial community in saliva showed a significant variation between individuals. A lack of association between yeasts and the bacterial fingerprints in saliva suggests the significant ecological person-specific independence in highly complex oral biofilm systems under normal oral conditions.

Keywords: bacteria, denaturing gradient gel electrophoresis, oral biofilm, yeasts

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Authors: Mohammad Aladwan, Adelia Skripova

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Bioremediation aspects of crude oil-polluted fields can be achieved by isolation and identification of bacterial species from oil-contaminated soil in order to choose the most active isolates and increase the strength of others. In this study, oil-degrading bacteria were isolated and identified from oil-contaminated soil samples in northeastern Jordan. The bacterial growth count (CFU/g) was between 1.06×10⁵ and 0.75×10⁹. Eighty-two bacterial isolates were characterized by their morphology and biochemical tests. The identified bacterial genera included: Klebsiella, Staphylococcus, Citrobacter, Lactobacillus, Alcaligenes, Pseudomonas, Hafnia, Micrococcus, Rhodococcus, Serratia, Enterobacter, Bacillus, Salmonella, Mycobacterium, Corynebacterium, and Acetobacter. Molecular identification of a universal primer 16S rDNA gene was used to identify four bacterial isolates: Microbacterium esteraromaticum strain L20, Pseudomonas stutzeri strain 13636M, Klebsilla pneumoniae, and uncultured Klebsilla sp., known as new strains. Our results indicate that their specific oil-degrading bacteria isolates might have a high strength of oil degradation from oil-contaminated sites. Staphylococcus intermedius (75%), Corynebacterium xerosis (75%), and Pseudomonas fluorescens (50%) showed a high growth rate on different types of hydrocarbons, such as crude oil, toluene, naphthalene, and hexane. In addition, monooxygenase and catechol 2,3-dioxygenase were detected in 17 bacterial isolates, indicating their superior hydrocarbon degradation potential. Total petroleum hydrocarbons were analyzed using gas chromatography for soil samples. Soil samples M5, M7, and M8 showed the highest levels (43,645, 47,805, and 45,991 ppm, respectively), and M4 had the lowest level (7,514 ppm). All soil samples were analyzed for heavy metal contamination (Cu, Cd, Mn, Zn, and Pb). Site M7 contains the highest levels of Cu, Mn, and Pb, while Site M8 contains the highest levels of Mn and Zn. In the future, these isolates of bacteria can be used for the cleanup of oil-contaminated soil.

Keywords: bioremediation, 16S rDNA gene, oil-degrading bacteria, hydrocarbons

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Authors: Yu-Chen Hu

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Gene editing by CRISPR and gene regulation by microRNA or CRISPR activation have dramatically changed the way to manipulate cellular gene expression and cell fate. In recent years, various gene editing and gene manipulation technologies have been applied to control stem cell differentiation to enhance tissue regeneration. This research will focus on how to develop CRISPR, CRISPR activation (CRISPRa), CRISPR inhibition (CRISPRi), as well as bi-directional CRISPR-AI gene regulation technologies to control cell differentiation and bone regeneration. Moreover, in this study, CRISPR/Cas13d-mediated RNA editng for miRNA editing and bone regeneration will be discussed.

Keywords: gene therapy, bone regeneration, stem cell, CRISPR, gene regulation

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Authors: Fadhl Alakwaa

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One of the sustainable goals of the system biology is understanding gene-gene interactions. Hence, gene regulatory networks (GRN) need to be constructed for understanding the disease ontology and to reduce the cost of drug development. To construct gene regulatory from gene expression we need to overcome many challenges such as data denoising and dimensionality. In this paper, we develop an integrated system to reduce data dimension and remove the noise. The generated network from our system was validated via available interaction databases and was compared to previous methods. The result revealed the performance of our proposed method.

Keywords: gene regulatory network, biclustering, denoising, system biology

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Authors: Restu Misrianti

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The amino acid variation of Asn (allele A) at position 631 in Mx gene was specific to positive antiviral to avian viral desease. This research was aimed at identifying polymorphism of Mx gene in duck using molecular technique. Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) technique was used to select the genotype of AA, AG and GG. There were thirteen duck from Indragiri Hulu regency (Riau Province) used in this experiment. DNA amplification results showed that the Mx gene in duck is found in a 73 bp fragment. Mx gene in duck did not show any polymorphism. The frequency of the resistant allele (AA) was 0%, while the frequency of the susceptible allele (GG) was 100%.

Keywords: duck, Mx gene, PCR, RFLP

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Authors: Saeid Doaei

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The various studies have examined the relationship between FTO gene expression and macronutrients levels. In order to obtain better viewpoint from this interactions, all of the existing studies were reviewed systematically. All published papers have been obtained and reviewed using standard and sensitive keywords from databases such as CINAHL, Embase, PubMed, PsycInfo, and the Cochrane, from 1990 to 2016. The results indicated that all of 6 studies that met the inclusion criteria (from a total of 428 published article) found FTO gene expression changes at short-term follow-ups. Four of six studies found an increased FTO gene expression after calorie restriction, while two of them indicated decreased FTO gene expression. The effect of protein, carbohydrate and fat were separately assessed and suggested by all of six studies. In conclusion, the level of FTO gene expression in hypothalamus is related to macronutrients levels. Future research should evaluate the long-term impact of dietary interventions.

Keywords: obesity, gene expression, FTO, macronutrients

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Authors: Mona Heydari, Ehsan Motamedian, Seyed Abbas Shojaosadati

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Prediction of perturbations after genetic manipulation (especially gene knockout) is one of the important challenges in systems biology. In this paper, a new algorithm is introduced that integrates microarray data into the metabolic model. The algorithm was used to study the change in the cell phenotype after knockout of Gss gene in Escherichia coli BW25113. Algorithm implementation indicated that gene deletion resulted in more activation of the metabolic network. Growth yield was more and less regulating gene were identified for mutant in comparison with the wild-type strain.

Keywords: metabolic network, gene knockout, flux balance analysis, microarray data, integration

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Authors: Rashad R. Al-Hindi

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The aim of this study was to isolate and identify lactic acid bacteria and evaluate their therapeutic and food preservation importance. Ninety-three suspected lactic acid bacteria (LAB) were isolated from thirteen different raw and fermented milk of indigenous sources in the Kingdom of Saudi Arabia. The identification of forty-six selected LAB strains and genetic relatedness were performed based on 16S rDNA gene sequence comparison. The LAB counts in certain samples were higher under microaerobic than anaerobic conditions. The identified LAB belonged to genera Enterococcus (16 strains), Lactobacillus (9 strains), Weissella (10 strains), Streptococcus (8 strains) and Lactococcus (3 strains). Phylogenetic tree generated from the full-length (~1.6 kb) sequences confirmed previous findings. Utilization of shorter 16S rDNA sequences (~1.0 kb) also discriminated among strains of which V2 region was the most effective. None of the strains exhibited resistance to clinically relevant antibiotics or undesirable hemolytic activity, while they differed in other probiotic characteristics, e.g., tolerance to acidic pH, resistance to bile salt, and antibacterial activity. In conclusion, the isolates Lactobacillus casei MSJ1, Lactobacillus casei Dwan5, Lactobacillus plantarum EyLan2 and Enterococcus faecium Gail-BawZir8 are likely the best probiotic LAB and we speculate that studying the synergistic effects of bacterial combinations might result in the occurrence of more effective probiotic potential. We argue that the raw and fermented milk of animals hosted in Saudi Arabia, especially stirred yogurt (Laban) made from camel milk, are rich in LAB with promising probiotics potential.

Keywords: fermented foods, lactic acid bacteria, probiotics, Saudi Arabia

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Authors: Omaima A. Sharaf, Tarek A. Moussa, Said M. Badr El-Din, H. Moawad

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Background: Polycyclic aromatic hydrocarbons (PAHs) pose great environmental and human health concerns for their widespread occurrence, persistence, and carcinogenic properties. PAHs releases due to anthropogenic activities to the wider environment have led to higher concentrations of these contaminants than would be expected from natural processes alone. This may result in a wide range of environmental problems that can accumulate in agricultural ecosystems, which threatened to become a negative impact on sustainable agricultural development. Thus, this study aimed to evaluate the physico-chemical, and microbial properties of the compost leachate (CL) to assess its role as nutrient and microbial source (biostimulation/bioaugmentation) for developing a cost-effective bioremediation technology for PAHs contaminated sites. Material and Methods: PAHs-degrading bacteria were isolated from CL that was collected from a composting site located in central Scotland, UK. Isolation was carried out by enrichment using phenanthrene (PHR), pyrene (PYR) and benzo(a)pyrene (BaP) as the sole source of carbon and energy. The isolates were characterized using a variety of phenotypic and molecular properties. Six different isolates were identified based on the difference in morphological and biochemical tests. The efficiency of these isolates in PAHs utilization was assessed. Further analysis was performed to define taxonomical status and phylogenic relation between the most potent PAHs-utilizing bacterial strains and other standard strains, using molecular approach by partial 16S rDNA gene sequence analysis. Results indicated that the 16S rDNA sequence analysis confirmed the results of biochemical identification, as both of biochemical and molecular identification of the isolates assigned them to Bacillus licheniformis, Pseudomonas aeruginosa, Alcaligenes faecalis, Serratia marcescens, Enterobacter cloacae and Providenicia which were identified as the prominent PAHs-utilizers isolated from CL. Conclusion: This study indicates that the CL samples contain a diverse population of PAHs-degrading bacteria and the use of CL may have a potential for bioremediation of PAHs contaminated sites.

Keywords: polycyclic aromatic hydrocarbons, physico-chemical analyses, compost leachate, microbial and biochemical analyses, phylogenic relations, 16S rDNA sequence analysis

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Authors: Vikas Kumar, Kailash Chandra, Kaomud Tyagi

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The insect order Thysanoptera includes small insects commonly called thrips. As insect vectors, only thrips are capable of Tospoviruses transmission (genus Tospovirus, family Bunyaviridae) affecting various crops. Currently, fifteen species of subfamily Thripinae (Thripidae) have been reported as vectors for tospoviruses. Frankliniella schultzei, which is reported as act as a vector for at least five tospovirses, have been suspected to be a species complex with more than one species. It is one of the historical unresolved issues where, two species namely, F. schultzei Trybom and F. sulphurea Schmutz were erected from South Africa and Srilanaka respectively. These two species were considered to be valid until 1968 when sulphurea was treated as colour morph (pale form) and synonymised under schultzei (dark form) However, these two have been considered as valid species by some of the thrips workers. Parallel studies have indicated that brown form of schultzei is a vector for tospoviruses while yellow form is a non-vector. However, recent studies have shown that yellow populations have also been documented as vectors. In view of all these facts, it is highly important to have a clear understanding whether these colour forms represent true species or merely different populations with different vector carrying capacities and whether there is some hidden diversity in 'Frankliniella schultzei species complex'. In this study, we aim to study the 'Frankliniella schultzei species complex' with molecular spectacles with DNA data from India and Australia and Africa. A total of fifty-five specimens was collected from diverse locations in India and Australia. We generated molecular data using partial fragments of mitochondrial cytochrome c oxidase I gene (mtCOI) and 28S rRNA gene. For COI dataset, there were seventy-four sequences, out of which data on fifty-five was generated in the current study and others were retrieved from NCBI. All the four different tree construction methods: neighbor-joining, maximum parsimony, maximum likelihood and Bayesian analysis, yielded the same tree topology and produced five cryptic species with high genetic divergence. For, rDNA, there were forty-five sequences, out of which data on thirty-nine was generated in the current study and others were retrieved from NCBI. The four tree building methods yielded four cryptic species with high bootstrap support value/posterior probability. Here we could not retrieve one cryptic species from South Africa as we could not generate data on rDNA from South Africa and sequence for rDNA from African region were not available in the database. The results of multiple species delimitation methods (barcode index numbers, automatic barcode gap discovery, general mixed Yule-coalescent, and Poisson-tree-processes) also supported the phylogenetic data and produced 5 and 4 Molecular Operational Taxonomic Units (MOTUs) for mtCOI and 28S dataset respectively. These results of our study indicate the likelihood that F. sulphurea may be a valid species, however, more morphological and molecular data is required on specimens from type localities of these two species and comparison with type specimens.

Keywords: DNA barcoding, species complex, thrips, species delimitation

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Authors: Alhadi Bustaman, Soeganda Formalidin, Titin Siswantining

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DNA microarray technology is used to analyze thousand gene expression data simultaneously and a very important task for drug development and test, function annotation, and cancer diagnosis. Various clustering methods have been used for analyzing gene expression data. However, when analyzing very large and heterogeneous collections of gene expression data, conventional clustering methods often cannot produce a satisfactory solution. Biclustering algorithm has been used as an alternative approach to identifying structures from gene expression data. In this paper, we introduce a transform technique based on singular value decomposition to identify normalized matrix of gene expression data followed by Mixed-Clustering algorithm and the Lift algorithm, inspired in the node-deletion and node-addition phases proposed by Cheng and Church based on Agglomerative Hierarchical Clustering (AHC). Experimental study on standard datasets demonstrated the effectiveness of the algorithm in gene expression data.

Keywords: agglomerative hierarchical clustering (AHC), biclustering, gene expression data, lymphoma, singular value decomposition (SVD)

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Authors: Hazha Hidayat, Shayma Ibrahim

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Folate metabolism plays a crucial role in the normal development of the neonatal central nervous system. It is regulated by MTHFR gene polymorphism. Any factors, which will affect this metabolism either by hereditary or gene mutation will lead to many mental disorders. The purpose of this study was to investigate whether MTHFR gene mutation contributes to the development of mental retardation and CP combined with mental retardation in Erbil city. DNA was isolated from the peripheral blood samples of 40 cases suffering from mental retardation (MR) and CP combined with MR were recruited, sequence the 4, 6, 7, 8 exons of the MTHFR gene were done to identify the variants. Exons were amplified by PCR technique and then sequenced according to Sanger method to show the differences with MTHFR reference sequences. We observed (14) mutations in 4, 6, 7, 8 exons in the MTHFR gene associated with Cerebral Palsy combined with mental retardation included deletion, insertion, Substitution. The current study provides additional evidence that multiple variations in the MTHFR gene are associated with mental retardation and Cerebral Palsy.

Keywords: methylenetetrahydrofolate reductase (MTHFR) gene, SNPs, homocysteine, sequencing

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Authors: Hala Alshamlan, Ghada Badr, Yousef Alohali

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Cancer is one of the dreadful diseases, which causes considerable death rate in humans. DNA microarray-based gene expression profiling has been emerged as an efficient technique for cancer classification, as well as for diagnosis, prognosis, and treatment purposes. In recent years, a DNA microarray technique has gained more attraction in both scientific and in industrial fields. It is important to determine the informative genes that cause cancer to improve early cancer diagnosis and to give effective chemotherapy treatment. In order to gain deep insight into the cancer classification problem, it is necessary to take a closer look at the proposed gene selection methods. We believe that they should be an integral preprocessing step for cancer classification. Furthermore, finding an accurate gene selection method is a very significant issue in a cancer classification area because it reduces the dimensionality of microarray dataset and selects informative genes. In this paper, we classify and review the state-of-art gene selection methods. We proceed by evaluating the performance of each gene selection approach based on their classification accuracy and number of informative genes. In our evaluation, we will use four benchmark microarray datasets for the cancer diagnosis (leukemia, colon, lung, and prostate). In addition, we compare the performance of gene selection method to investigate the effective gene selection method that has the ability to identify a small set of marker genes, and ensure high cancer classification accuracy. To the best of our knowledge, this is the first attempt to compare gene selection approaches for cancer classification using microarray gene expression profile.

Keywords: gene selection, feature selection, cancer classification, microarray, gene expression profile

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Authors: Somyung Oh, Jeonghyeon Ha, Kyungwon Lee, Sejong Oh

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Microarray is a general scheme to find differentially expressed genes for target concept. The output is expressed by heat map, and biologists analyze related terms of gene ontology to find some characteristics of differentially expressed genes. In this paper, we propose integrated visualization tool for heat map and gene ontology graph. Previous two methods are used by static manner and separated way. Proposed visualization tool integrates them and users can interactively manage it. Users may easily find and confirm related terms of gene ontology for given differentially expressed genes. Proposed tool also visualize connections between genes on heat map and gene ontology graph. We expect biologists to find new meaningful topics by proposed tool.

Keywords: heat map, gene ontology, microarray, differentially expressed gene

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Authors: Ashraf Y. Z. Khalifa, Mohammed A. Almalki

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Medicago sativa (Alfalfa) is an important forage crop legume worldwide including Saudia Arabia due to its high nutritive value. Soil bacteria exist in root or root-nodules of Medicago sativa in either symbiotic relationships or in associations. The aim of the present study was to isolate and characterize endophytic bacteria that live in association with non-nodulated roots of Medicago sativa growing in Al-Ahsaa region, Saudia Arabia. Several bacterial strains were isolated from sterilized roots of Medicago sativa. Strains were characterized using 16S rRNA gene sequences, phylogenetic relationships analysis, morphological and biochemical characteristics. The strains utilized 50% (10 out of 20) of the different chemical substrates contained in the API20E strip. In general, many strains had the ability to ferment/oxidise all the carbohydrate tested except for rhamnose and the polyol carbohydrate, inositol. Comparative sequence analysis of the 16S rDNA gene indicated that the strains were closely related to the genus Bacillus. Furthermore, the growth parameters of Vigna sinensis were enhanced upon single-inoculation of the isolated strains, compared to the uninoculated control plants. The results highlighted that the root-nodules of Medicago sativa harbor non-nodulating bacterial strains that could have significant agricultural applications.

Keywords: Medicago sativa, endophytic bacteria, Pisum sativum, Vigna sinensis

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Authors: Morteza Haghi, Cigdem Yilmazbas, Ayse Zeynep Uysal, Melisa Tepedelen, Gozde Turkoz Bakirci

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Today, the increase in plastic waste accumulation is an inescapable consequence of environmental pollution; the disposal of these wastes has caused a significant problem. Variable methods have been utilized; however, biodegradation is the most environmentally friendly and low-cost method. Accordingly, the present study aimed to isolate the bacteria capable of biodegradation of plastics. In doing so, we applied the liquid carbon-free basal medium (LCFBM) prepared with deionized water for the isolation of bacterial species obtained from soil samples taken from the Izmir Menemen region. Isolates forming biofilms on plastic were selected and named (PLB3, PLF1, PLB1B) and subjected to a degradation test. FTIR analysis, 16s rDNA amplification, sequencing, identification of isolates were performed. Finally, at the end of the process, a mass loss of 16.6% in PLB3 isolate and 25% in PLF1 isolate was observed, while no mass loss was detected in PLB1B isolate. Only PLF1 and PLB1B created transparent zones on plastic texture. Considering the FTIR result, PLB3 changed plastic structure by 13.6% and PLF1 by 17%, while PLB1B did not change the plastic texture. According to the 16s rDNA sequence analysis, FLP1, PLB1B, and PLB3 isolates were identified as Streptomyces albogriseolus, Enterobacter cloacae, and Klebsiella pneumoniae, respectively.

Keywords: polyethylene, biodegradation, bacteria, 16s rDNA, FTIR

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Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

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The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

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Authors: Rachel Matar, Maxime Merheb

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Chemical drugs have been used for many centuries as the only way to cure diseases until the novel gene therapy has been created in 1960. Gene therapy is based on the insertion, correction, or inactivation of genes to treat people with genetic illness (1). Gene therapy has made wonders in Parkison’s, Alzheimer and multiple sclerosis. In addition to great promises in the healing of deadly diseases like many types of cancer and autoimmune diseases (2). This method implies the use of recombinant DNA technology with the help of different viral and non-viral vectors (3). It is nowadays used in somatic cells as well as embryos and gametes. Beside all the benefits of gene therapy, this technique is deemed by some opponents as an ethically unacceptable treatment as it implies playing with the genes of living organisms.

Keywords: gene therapy, genetic disease, cancer, multiple sclerosis

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Authors: Daina Jonkus, Liga Paura, Tatjana Sjakste, Kristina Dokane

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The aim of this study was to analyse PRKAG3 and RYR1 gene and genotypes frequencies in Latvian White pigs’ breed. Genotypes of RYR1 gene two loci (rs196953058 and rs323041392) in 89 exon and PRKAG3 gene two loci (rs196958025 and rs344045190) in gene promoter were detected in 103 individuals of Latvian white pigs’ breed. Analysis of RYR1 gene loci rs196953058 shows all individuals are homozygous by T allele and all animals are with genotypes TT, its mean - in 2769 position is Phenylalanine. Analysis of RYR1 gene loci rs323041392 shows all individuals are homozygous by G allele and all animals are with genotypes GG, its mean - in 4119 positions is Asparagine. In loci rs196953058 and rs323041392, there were no gene polymorphisms. All analysed individuals by two loci rs196953058-rs323041392 have TT-GG genotypes or Phe-Asp amino acids. In PRKAG3 gene loci rs196958025 and rs344045190 there was gene polymorphisms. In both loci frequencies for A allele was higher: 84.6% for rs196958025 and 73.0% for rs344045190. Analysis of PRKAG3 gene loci rs196958025 shows 74% of individuals are homozygous by An allele and animals are with genotypes AA. Only 4% of individuals are homozygous by G allele and animals are with genotypes GG, which is associated with pale meat colour and higher drip loss. Analysis of PRKAG3 gene loci rs344045190 shows 46% of individuals are homozygous with genotypes AA and 54% of individuals are heterozygous with genotypes AG. There are no individuals with GG genotypes. According to the results, in Latvian white pigs population there are no rs344435545 (RYR1 gene) CT heterozygous or TT recessive homozygous genotypes, which is related to the meat quality and pigs’ stress syndrome; and there are 4% rs196958025 (PRKAG3 gene) GG recessive homozygote genotypes, which is related to the meat quality. Acknowledgment: the investigation is supported by VPP 2014-2017 AgroBioRes Project No. 3 LIVESTOCK.

Keywords: genotype frequencies, pig, PRKAG3, RYR1

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Authors: Hamid Mustafa, Adeela Ajmal, Kim EuiSoo, Noor-ul-Ain

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World wild, buffalo production is considered as most important component of food industry. Efficient buffalo production is related with reproductive performance of this species. Lack of knowledge of reproductive efficiency and its related genes in buffalo species is a major constraint for sustainable buffalo production. In this study, we performed some bioinformatics analysis on Follicle Stimulating Hormone Receptor (FSHR) gene and explored the possible relationship of this gene among different buffalo breeds and with other farm animals. We also found the evolution pattern for this gene among these species. We investigate CDS lengths, Stop codon variation, homology search, signal peptide, isoelectic point, tertiary structure, motifs and phylogenetic tree. The results of this study indicate 4 different motif in this gene, which are Activin-recp, GS motif, STYKc Protein kinase and transmembrane. The results also indicate that this gene has very close relationship with cattle, bison, sheep and goat. Multiple alignment (MA) showed high conservation of motif which indicates constancy of this gene during evolution. The results of this study can be used and applied for better understanding of this gene for better characterization of Follicle Stimulating Hormone Receptor (FSHR) gene structure in different farm animals, which would be helpful for efficient breeding plans for animal’s production.

Keywords: buffalo, FSHR gene, bioinformatics, production

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Authors: Shahram Nanekarania, Majid Goodarzia

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Calpastatin and callipyge have been known as one of the candidate genes in meat quality and quantity. Calpastatin gene has been located to chromosome 5 of sheep and callipyge gene has been localized in the telomeric region on ovine chromosome 18. The objective of this study was identification of calpastatin and callipyge genes polymorphism and analysis of genotype structure in population of Lori sheep kept in Iran. Blood samples were taken from 120 Lori sheep breed and genomic DNA was extracted by salting out method. Polymorphism was identified using the PCR-RFLP technique. The PCR products were digested with MspI and FaqI restriction enzymes for calpastatin gene and callipyge gene, respectively. In this population, three patterns were observed and AA, AB, BB genotype have been identified with the 0.32, 0.63, 0.05 frequencies for calpastatin gene. The results obtained for the callipyge gene revealed that only the wild-type allele A was observed, indicating that only genotype AA was present in the population under consideration.

Keywords: polymorphism, calpastatin, callipyge, PCR-RFLP, Lori sheep

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Authors: Micheal Olaolu Arowolo, Muhammad Azam, Fei He, Mihail Popescu, Dong Xu

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As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Annotating pathway diagrams manually is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy.

Keywords: biological pathway, gene identification, object detection, Siamese network

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Authors: O. Ubani, H. I. Atagana, M. S. Thantsha, R. Adeleke

Abstract:

The oil sludge components (polycyclic aromatic hydrocarbons, PAHs) have been found to be cytotoxic, mutagenic and potentially carcinogenic and microorganisms such as bacteria and fungi can degrade the oil sludge to less toxic compounds such as carbon dioxide, water and salts. In the present study, we isolated different bacteria with PAH-degrading potentials from the co-composting of oil sludge and different animal manure. These bacteria were isolated on the mineral base medium and mineral salt agar plates as a growth control. A total of 31 morphologically distinct isolates were carefully selected from 5 different compost treatments for identification using polymerase chain reaction (PCR) of the 16S rDNA gene with specific primers (16S-P1 PCR and 16S-P2 PCR). The amplicons were sequenced and sequences were compared with the known nucleotides from the gene bank database. The phylogenetical analyses of the isolates showed that they belong to 3 different clades namely Firmicutes, Proteobacteria and Actinobacteria. These bacteria identified were closely related to genera Bacillus, Arthrobacter, Staphylococcus, Brevibacterium, Variovorax, Paenibacillus, Ralstonia and Geobacillus species. The results showed that Bacillus species were more dominant in all treated compost piles. Based on their characteristics these bacterial isolates have high potential to utilise PAHs of different molecular weights as carbon and energy sources. These identified bacteria are of special significance in their capacity to emulsify the PAHs and their ability to utilize them. Thus, they could be potentially useful for bioremediation of oil sludge and composting processes.

Keywords: bioaugmentation, biodegradation, bioremediation, composting, oil sludge, PAHs, animal manures

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Authors: Sanaa Rashed Abdallah, Yasser F. Hassan

Abstract:

The paper will introduce an approach where a rough sets, gene expression programming and rough neural networks are used cooperatively for learning and classification support. The Objective of gene expression programming rough neural networks (GEP-RNN) approach is to obtain new classified data with minimum error in training and testing process. Starting point of gene expression programming rough neural networks (GEP-RNN) approach is an information system and the output from this approach is a structure of rough neural networks which is including the weights and thresholds with minimum classification error.

Keywords: rough sets, gene expression programming, rough neural networks, classification

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Authors: Yudi Zhao, Ziyun Zhou, Yueting Yao, Shuying Dai, Zhiling Yan, Longyu Yang, Chuanyin Li, Li Shi, Yufeng Yao

Abstract:

HPV16 E4 gene plays an important role in viral genome amplification and release. Therefore, a variation of the E4 gene nucleic acid sequence may affect the carcinogenicity of HPV16. In order to understand the relationship between the variation of HPV16 E4 gene and cervical cancer, this study was to amplify and sequence the DNA sequences of E4 genes in 118 HPV16-positive cervical cancer patients and 151 HPV16-positive asymptomatic individuals. After obtaining E4 gene sequences, the phylogenetic trees were constructed by the Neighbor-joining method for gene variation analysis. The results showed that: 1) The distribution of HPV16 variants between the case group and the control group differed greatly (P = 0.015)，and the Asian-American（AA）variant was likely to relate to the occurrence of cervical cancer. 2) DNA sequence analysis showed that there were significant differences in the distribution of 8 variants between the case group and the control group (P < 0.05). And 3) In European (EUR) variant, two variations, C3384T (L18L) and A3449G (P39P), were associated with the initiation and development of cervical cancer. The results suggested that the variation of HPV16 E4 gene may be a contributor affecting the occurrence as well as the development of cervical cancer, and different HPV16 variants may have different carcinogenic capability.

Keywords: cervical cancer, HPV16, E4 gene, variations

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Authors: I. Boroňová, J. Bernasovská, J. Kľoc, Z. Tomková, E. Petrejčíková, S. Mačeková, J. Poráčová, M. M. Blaščáková

Abstract:

Osteoporosis is a common multifactorial disease with a strong genetic component characterized by reduced bone mass and increased risk of fractures. Genetic factors play an important role in the pathogenesis of osteoporosis. The aim of our study was to identify the genotype and allele distribution of T245G polymorphism in OPG gene in Slovak postmenopausal women. A total of 200 unrelated Slovak postmenopausal women with diagnosed osteoporosis and 200 normal controls were genotyped for T245G (rs3134069) polymorphism of OPG gene. Genotyping was performed using the Custom Taqman®SNP Genotyping assays. Genotypes and alleles frequencies showed no significant differences (p=0.5551; p=0.6022). The results of the present study confirm the importance of T245G polymorphism in OPG gene in the pathogenesis of osteoporosis.

Keywords: OPG gene, T245G polymorphism, osteoporosis, T245G polymorphism, real-time PCR

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Authors: Tiancheng Lan

Abstract:

E10A is a kind of replication-defective adenovirus which carries the human endostatin gene to inhibit the growth of tumors. Kringle 5(K5) has almost the same function as angiostatin to also inhibit the growth of tumors since they are all the byproduct of the proteolytic cleavage of plasminogen. Tumor size increasing can be suppressed because both of the endostatin and K5 can restrain the angiogenesis process. Therefore, in order to improve the treatment effect on tumor, 2A peptide is used to construct a fusion gene carrying both E10A and K5. Using 2A peptide is an ideal strategy when a fusion gene is expressed because it can avoid many problems during the expression of more than one kind of protein. The overlap extension PCR is also used to connect 2A peptide with E10A and K5. The final construction of fusion gene E10A-2A-K5 can provide a possible new method of the anti-angiogenesis treatment with a better expression performance.

Keywords: E10A, Kringle 5, 2A peptide, overlap extension PCR

Procedia PDF Downloads 150