Novel approach for identification of influenza virus host range and zoonotic transmissible sequences by determination of host-related associative positions in viral genome segments

Background: Recent (2013 and 2009) zoonotic transmission of avian or porcine influenza to humans highlights an increase in host range by evading species barriers. Gene reassortment or antigenic shift between viruses from two or more hosts can generate a new life-threatening virus when the new shuffled virus is no longer recognized by antibodies existing within human populations. There is no large scale study to help understand the underlying mechanisms of host transmission. Furthermore, there is no clear understanding of how different segments of the influenza genome contribute in the final determination of host range. Methods: To obtain insight into the rules underpinning host range determination, various supervised machine learning algorithms were employed to mine reassortment changes in different viral segments in a range of hosts. Our multi-host dataset contained whole segments of 674 influenza strains organized into three host categories: avian, human, and swine. Some of the sequences were assigned to multiple hosts. In point of fact, the datasets are a form of multi-labeled dataset and we utilized a multi-label learning method to identify discriminative sequence sites. Then algorithms such as CBA, Ripper, and decision tree were applied to extract informative and descriptive association rules for each viral protein segment. Result: We found informative rules in all segments that are common within the same host class but varied between different hosts. For example, for infection of an avian host, HA14V and NS1230S were the most important discriminative and combinatorial positions. Conclusion: Host range identification is facilitated by high support combined rules in this study. Our major goal was to detect discriminative genomic positions that were able to identify multi host viruses, because such viruses are likely to cause pandemic or disastrous epidemics.Fatemeh Kargarfard, Ashkan Sami, Manijeh Mohammadi-Dehcheshmeh and Esmaeil Ebrahimi

Petal: a reliable explant for direct bulblet regeneration of endangered wild populations of Fritillaria imperialis L.

Wild populations of Fritillaria imperialis L. are facing extinction and need urgent conservation. This paper presents an efficient system for in vitro direct bulblet regeneration of these populations by petal culturing of flower buds. Petals at different developmental stages, green-closed flower bud (before nectar secretion) and red-closed flower bud (beginning of nectar secretion), were used as explants, and the effects of various proportions of cytokinin to auxin on direct bulblet regeneration pathway were evaluated. More explants switched on direct regeneration pathway in combination of auxins (0.6 mg l−1 NAA + 0.4 mg l−1 IAA) with higher level of cytokinin (1 mg l−1 BAP). In contrast, auxins (0.6 mg l−1 NAA + 0.4 mg l−1 IAA) with lower level of cytokinin (0.1 mg l−1 BAP) produced more bulblets per regenerated explant. In green-closed flower bud stage, direct bulblets regenerated from the end of petal where it was connected to the receptacle, while nectar secretion site was the place of bulblet formation in red-closed flower bud stage. In addition, genotype-dependency of direct bulblet regeneration pathway was investigated by using two different wild populations of Fritillaria imperialis. This plant regeneration procedure was applicable to different Fritillaria genotypes and regenerated bulblets were normal.Manijeh Mohammadi-Dehcheshmeh, Ahmad Khalighi, Roohangiz Naderi, Manoochehr Sardari, Esmaeil Ebrahimi

THE ROLE OF SOCIAL CAPITAL IN INTRAPRENEURSHIP OF HEALTH DEPARTMENT STAFF

An organization with high social capital can lead to blossoming of new ideas in people with impacts on information sharing and implicit and explicit knowledge transfer. The new ideas make creative people and this creates innovation and entrepreneurship in the organization in the same way. This study was conducted to investigate the relationship between social capital and intrapreneurship in Health Department staff at Ahvaz Jundishapur University of Medical Sciences. This is a correlational descriptive study. The population consisted of 90 managers and experts at the Department of Health in Ahvaz Jundishapur University of Medical Sciences selected by census sampling method. Data analyses were performed using SPSS software (version 16). Two valid questionnaires including social capital and intrapreneurship were used for data collecting. Descriptive statistics (frequency, percentage, mean, and standard deviation) and analytic statistics (Spearman correlation coefficient) were used. Mean social capital was 101.04 of a total of 155 points. Among the dimensions of social capital, relational dimension with a mean 46 out of 70 and structural dimension a mean 36.21 out of 55 was obtained, respectively. The cognitive dimension, with an average of 18.83 total score out of 30 was the least average. The mean of the intrapreneurship was 97.11 out of 155. The results showed that there is a positive and significant relationship between the social capital and its dimensions (cognitive, structural, and relational) with intrapreneurship (P<0.001). Information is exchanged more often in organizations with higher levels of participation, commitment, and trust. Finally, it makes the individual have a lot of time for thinking, creativity, innovation, and entrepreneurship. Keywords: Social capital, Intrapreneurship, Healt

Computational systems biology analysis of biomarkers in lung cancer; unravelling genomic regions which frequently encode biomarkers, enriched pathways, and new candidates

Exponentially growing scientific knowledge in scientific publications has resulted in the emergence of a new interdisciplinary science of literature mining. In text mining, the machine reads the published literature and transfers the discovered knowledge to mathematical-like formulas. In an integrative approach in this study, we used text mining in combination with network discovery, pathway analysis, and enrichment analysis of genomic regions for better understanding of biomarkers in lung cancer. Particular attention was paid to non-coding biomarkers. In total, 60 MicroRNA biomarkers were reported for lung cancer, including some prognostic biomarkers. MIR21, MIR155, MALAT1, and MIR31 were the top non-coding RNA biomarkers of lung cancer. Text mining identified 447 proteins which have been studied as biomarkers in lung cancer. EGFR (receptor), TP53 (transcription factor), KRAS, CDKN2A, ENO2, KRT19, RASSF1, GRP (ligand), SHOX2 (transcription factor), and ERBB2 (receptor) were the most studied proteins. Within small molecules, thymosin-a1, oestrogen, and 8-OHdG have received more attention. We found some chromosomal bands, such as 7q32.2, 18q12.1, 6p12, 11p15.5, and 3p21.3 that are highly involved in deriving lung cancer biomarkers.Ibrahim O. Alanazi, Sami A. AlYahya, Esmaeil Ebrahimie, Manijeh Mohammadi-Dehcheshme

Insights from the Echinacea purpurea (L.) Moench transcriptome: Global reprogramming of gene expression patterns towards activation of secondary metabolism pathways

Echinacea purpurea (L.) Moench is an important medicinal plant with a wide range of therapeutic potentials that is extensively applied in pharmaceutical industry. The molecular bases and regulatory mechanisms of active compounds in E. purpurea, are yet to be fully described. In the study, to explore genome-wide transcriptional and metabolic changes, seedlings elicited by methyl jasmonate (MeJA) were analyzed by integrative transcriptome sequencing and quantitative chemical profiling. The plants exposed to MeJA significantly increased accumulation of phenolic compounds content as well as phenylalanine ammonia-lyase (PAL) activity, compared with control plants. The assembly of the clean reads generated 85,736 unigenes, in which more than 52% were annotated. Transcriptome analysis revealed that MeJA induces major transcriptional changes, especially metabolic, and signal transduction pathways. Overall, 5538 differentially expressed genes were identified after MeJA application that some of them were assigned to transcription factors (TFs), protein kinases (PKs), and transporters involved in phenolic secondary metabolite biosynthesis. Moreover, core genes in the pathways of phenylalanine and phenylpropanoid were affected by MeJA. A transcriptional regulatory network from transcriptome profiles of TFs and genes involved in phenolics biosynthesis pathway were constructed that identified hub genes which might play central regulatory roles in secondary metabolite biosynthesis. The current study provides a comprehensive genomic dataset that can serve as a resource to better understanding of the phenolic biosynthesis and improveing metabolic engineering strategies for overproduction of bioactive metabolites in Echinacea industry.Ahmad Tahmasebi, Esmaeil Ebrahimie, Hassan Pakniyat, Mansour Ebrahimi, Manijeh Mohammadi-Dehcheshme

Genome-wide analysis of cytosolic and chloroplastic isoforms of glutathione reductase in plant cells

In recent years regarding the climate change and subsequent environmental stresses, there has been an increasing interest in finding and characterizing of new antioxidant enzymes. Glutathione reductase (GR) is an antioxidant enzyme with central role in maintaining the reduced glutathione pool during stress. So far, however, there has been little discussion on genome-wide analysis of this enzyme. In this study, different computational biology approaches (EST analysis, feature selection, and evolutionary analysis) were exploited to identify the key protein properties influencing on cytosolic and chloroplastic isoforms of glutathione reductase in plants. A specific targeting signal peptide was found in chloroplastic isoforms, while cytosolic isoforms carry a cytosolic domain. This domain may affect the biochemical properties of the different GR isoforms. Moreover, specific functional motifs were discovered in cytosolic and chloroplastic isoforms implying a link between subcellular localization of GR and functional. Phylogenetic analysis of GR nucleotide and protein sequences showed that diversification of this gene family could be dated back to the early stage of plant evolution, possibly by duplication event before the divergence of monocot and dicot. A high degree of gene structure conservation of localized isoforms in the same subcellular compartment also reflects this process providing an evidence for a close relationship among proteins located in the same subcellular compartment. Study of glutathione reductase expression by EST analysis highlighted cytosolic isoforms as the main isofonin responding to stress condition.Ahmad Tahmasebi, Farzaneh Aram, Mansour Ebrahimi, Manijeh Mohammadi-Dehcheshmeh and Esmaeil Ebrahimiehttp://www.cabdirect.org/abstracts/20123132574.htm

Root and shoot parts of strawberry: factories for production of functional human pro-insulin

Diabetes, a disease caused by excessive blood sugar, is caused by the lack of insulin. For commercial production, insulin is made in bacteria or yeast by protein recombinant technology. The focus of this research is evaluating another resource and producing of recombinant insulin protein in as strawberry as this plant has high potential in production of pharmaceutical proteins. Strawberry is a suitable bioreactor for production of recombinant proteins especially edible vaccines. In this research, human pro-insulin gene was cloned in pCAMBIA1304 vector under CaMV35S promoter and NOS terminator. Agrobacterium tumefaciens LBA4404, AGL1, EHA105, EHA101, C58, C58 (pGV2260) and C58 (pGV3101) strains were used for transformation of pro-insulin gene into strawberry cv. Camarosa, Selva, Sarian Hybrid, Pajaro, Paros, Gaviota, Alpine. Additionally, Agrobacterium rhizogenes K599, R1000, A4 and MSU440 strains were utilized for gene transformation into hairy roots. PCR analysis indicated the presence of transformed human pro-insulin gene in the strawberry and hairy roots. Also, its transcription was confirmed using RT-PCR. Furthermore, the analysis of plants, fruits and hairy roots at the level of proteins using dot blot, ELISA, SDS-PAGE and ECL tests re-confirmed the expression of this protein in the transgenic plants as well as hairy roots. Protein purification of human pro-insulin from transgenic tissues was performed using affinity chromatography. Finally, the bioassay of recombinant pro-insulin was performed. The analysis of second generations of transgenic plants (T1) at DNA and protein levels was also performed as a complementary experiment. This study opens a new avenue in molecular farming of human pro-insulin through its mass production in roots and shoots of strawberry.Ashkan Tavizi, Mokhtar Jalali Javaran, Ahmad Moieni, Manijeh Mohammadi-Dehcheshmeh, Mehdi Mohebodini, Esmaeil Ebrahimi

Application of neural networks methods to define the most important features contributing to xylanase enzyme thermostability

The importance of finding or making thermostable enzymes in different industries have been highlighted. Therefore, it is inevitable to understand the features involving in enzymes' thermostability. Different approaches have been employed to extract or manufacture thermostable enzymes. Here we have looked at features contributing to Endo-1,4,beta-xylanase (EC 3.2.1.8) thermostability, the key enzyme with possible applications in waste treatment, fuel and chemical production and paper industries. We trained different neural networks with/without feature selection and classification modelling on all available xylanase enzymes amino acids sequences to find features contributing to enzyme thermal stability.M. Ebrahimi, E. Ebrahimie, M. Ebrahimi, T. Deihimi, A. Delavari, M. Mohammadi-dehcheshme

Comparative study of ammonium transporters in different organisms by study of a large number of structural protein features via data mining algorithms

Ammonium is an excellent nitrogen source, and ammonium transfer is a fundamental process in most organisms. Membrane transport of ammonium is the key component of nitrogen metabolism mediated by Ammonium Transporter/Methylamine Permease/Rhesus (AMT/MEP/Rh) protein family. Ammonium transporters play different physiological roles in various organisms. Here, we looked at the protein characteristics of ammonium transporters in different organisms to create a link between protein characteristics and the organism. In order to increase the accuracy and precision of the employed models, for the first time, an attempt was made to cover all structural aspects of ammonium transporters in animals, bacteria, fungi, plants, and human by extracting and calculating 874 protein attributes of primary, secondary, and tertiary structures for each ammonium transporter. Then, various weighting and modeling algorithms were applied to determine how structural protein features change between organisms. Considering a large number of protein attributes made it possible to detect key protein characteristics in the structure of ammonium transporters. The results, for the first time, indicated that His-based features including count/frequency of His and frequency/count of Ile-His were the most significant features generating different types of ammonium transporters within organisms. Within different tested models, the C5.0 model was the most efficient and precise model for discrimination of organism type, based on ammonium transporter sequence, with the precision of 94.85%. The determination of protein characteristics of ammonium transporters in different organisms provides a new vista for understanding the evolution of transporters based on the modulation of protein characteristics and facilitates engineering of new transporters. In our point of view, dissecting a large number of structural protein characteristics through data mining algorithms provides a novel functional strategy for studying evolution and phylogeny. This research will serve as a basis for future studies on engineering novel ammonium transporters.Ehsan Tahrokh, Mansour Ebrahimi, Mahdi Ebrahimi, Fatemeh Zamansani, Narjes Rahpeyma Sarvestani, Manijeh Mohammadi-Dehcheshmeh, Mohammad Reza Ghaemi and Esmaeil Ebrahimi