Engineering Human Pancreatic RNase 1 as an Immunotherapeutic Agent for Cancer Therapy Through Computational and Experimental Studies.

Most plant and bacterial toxins are highly immunogenic with non-specific toxic effects. Human ribonucleases are thought to provide a promising basis for reducing the toxic agent's immunogenic properties, which are candidates for cancer therapy. In the cell, the ribonuclease inhibitor (RI) protein binds to the ribonuclease enzyme and forms a tight complex. This study aimed to engineer and provide a gene construct encoding an improved version of Human Pancreatic RNase 1 (HP-RNase 1) to reduce connection to RI and modulate the immunogenic effects of immunotoxins. To further characterize the interaction complex of HP-RNase 1 and RI, we established various in silico and in vitro approaches. These methods allowed us to specifically monitor interactions within native and engineered HP-RNase 1/RI complexes. In silico research involved molecular dynamics (MD) simulations of native and mutant HP-RNase 1 in their free form and when bound to RI. For HP-RNase 1 engineering, we designed five mutations (K8A/N72A/N89A/R92D/E112/A) based on literature studies, as this combination proved effective for the intended investigation. Then, the cDNA encoding HP-RNase 1 was generated by RT-PCR from blood and cloned into the pSYN2 expression vector. Consequently, wild-type and the engineered HP-RNase 1 were over-expressed in E. coli TG1 and purified using an IMAC column directed against a poly-his tag. The protein products were detected by SDS-PAGE and Western blot analysis. HP-RNase 1 catalytic activity, in the presence of various concentrations of RI, demonstrated that the mutated version of the protein is able to escape the ribonuclease inhibitor and target the RNA substrate 2.5 folds more than that of the wild type. From these data, we tend to suggest the engineered recombinant HP-RNase 1 potentially as a new immunotherapeutic agent for application in human cancer therapy.

The constitutively active pSMAD2/3 relatively improves the proliferation of chicken primordial germ cells.

In many multicellular organisms, mature gametes originate from primordial germ cells (PGCs). Improvements in the culture of PGCs are important not only for developmental biology research, but also for preserving endangered species, and for genome editing and transgenic animal technologies. SMAD2/3 appear to be powerful regulators of gene expression; however, their potential positive impact on the regulation of PGC proliferation has not been taken into consideration. Here, the effect of TGF-ß signaling as the upstream activator of SMAD2/3 transcription factors was evaluated on chicken PGCs' proliferation. For this, chicken PGCs at stages 26-28 Hamburger-Hamilton were obtained from the embryonic gonadal regions and cultured on different feeders or feeder-free substrates. The results showed that TGF-ß signaling agonists (IDE1 and Activin-A) improved PGC proliferation to some extent while treatment with SB431542, the antagonist of TGF-ß, disrupted PGCs' proliferation. However, the transfection of PGCs with constitutively active SMAD2/3 (SMAD2/3CA) resulted in improved PGC proliferation for more than 5 weeks. The results confirmed the interactions between overexpressed SMAD2/3CA and pluripotency-associated genes NANOG, OCT4, and SOX2. According to the results, the application of SMAD2/3CA could represent a step toward achieving an efficient expansion of avian PGCs.

Bioinformatics and pathway enrichment analysis identified hub genes and potential biomarker for gastric cancer prognosis.

Introduction: Gastric cancer is one of the most common cancers in the world. This study aimed to identify genes, biomarkers, and metabolic pathways affecting gastric cancer using bioinformatic analysis and meta-analysis. Methods: Datasets containing gene expression profiles of tumor lesions and adjacent non-tumor mucosa samples were downloaded. Common differentially expressed genes between data sets were selected to identify hub genes and further analysis. Gene Expression Profiling and Interactive Analyses (GEPIA) and the Kaplan-Meier method were used to further validate the expression level of genes and plot the overall survivalcurve, respectively. Results and disscussion: KEGG pathway analysis showed that the most important pathway was enriched in ECM-receptor interaction. Hub genes includingCOL1A2, FN1, BGN, THBS2, COL5A2, COL6A3, SPARC and COL12A1 wereidentified. The top interactive miRNAs including miR-29a-3p, miR-101-3p,miR-183-5p, and miR-15a-5p targeted the most hub genes. The survival chart showed an increase in mortality in patients with gastric cancer, which shows the importance of the role of these genes in the development of the disease and can be considered candidate genes in the prevention and early diagnosis of gastric cancer.

Identification of Key Genes and Potential Pathways Associated with Mastitis Induced by E. coli.

Mastitis is one of the most important diseases of dairy cattle. It is an infectious disease leading to an inflammatory reaction in the cow's mammary gland. Escherichia coli is one of the common bacteria which induce mastitis in cows. The aim of this study was to identify key genes and potential pathways associated with mastitis induced by E. coli in dairy cattle using bioinformatics analysis. The gene expression profile of ten samples including five adjacent tissues from a quarter infected with Escherichia coli and five tissues from a healthy quarter of dairy cattle was assessed using GEO2R. Gene ontology and pathway analysis were performed using bioinformatics tools. A total of 156 differentially expressed genes were detected which 95 genes were upregulated and 61 genes were downregulated in adjacent tissue of quarter infected compared with healthy tissue. Cellular oxidant detoxification and oxidation-reduction process were the most significant biological process terms in gene ontology analysis. The most important pathways of DEGs were the biosynthesis of amino acids, p53 signaling pathway, and Metabolic pathways. Three important modules were identified and their path enrichment analysis was performed. There are 10 core genes, among which SOD2, COL1A2, COL3A1, POSTN, ALDH18A1, and CBS may be the main genes associated with mastitis, which can be considered as candidate genes in the prevention and carly diagnosis program of mastitis.

Transcriptome Analysis of Breast Muscle Reveals Pathways Related to Protein Deposition in High Feed Efficiency of Native Turkeys.

Feed efficiency is important due to the high cost of food, which accounts for about 70% of the total cost of a turkey breeding system. Native poultry are an important genetic resource in poultry breeding programs. This study aimed to conduct a global transcriptome analysis of native male turkeys which have been phenotyped for high and low feed efficiency. Feed efficiency traits were recorded during the experimental period. After slaughter, the three most efficient and three least efficient male turkeys were selected for RNA-Seq analysis. A total of 365 genes with different expressions in muscle tissue were identified between turkeys with a high feed efficiency compared to turkeys with a low feed efficiency. In the pathway analysis of up-regulated genes, major pathways included the "metabolism of glycine, serine, and threonine"; the "adipocytokine signaling pathway" and the "biosynthesis of amino acids". In the pathway analysis of down-regulated genes, the major pathways included "dorso-ventral axis formation" and "actin cytoskeleton regulation". In addition, gene set enrichment analyses were performed, which showed that high feed efficiency birds exhibit an increased expression of genes related to the biosynthesis of amino acids and low feed efficiency birds an increased expression of genes related to the immune response. Furthermore, functional analysis and protein network interaction analysis revealed that genes including GATM, PSAT1, PSPH, PHGDH, VCAM1, CD44, KRAS, SRC, CAV3, NEDD9, and PTPRQ were key genes for feed efficiency. These key genes may be good potential candidates for biomarkers of feed efficiency in genetic selection in turkeys.

Identification of hub genes involved in apparent metabolizable energy of chickens.

Feed efficiency is one of the most economically significant traits in a breeding program. Apparent metabolizable energy is the most used method to evaluate energy utilization for feed efficiency. The purpose of this study was to identify candidate genes of chickens with divergent apparent metabolizable energy by bioinformatics analysis. The gene expression profile of duodenal of the highest and lowest apparent metabolizable energy-ranked birds were analyzed. Differentially expressed genes were picked out using GEO2R tool. Gene ontology and pathway analysis were performed using bioinformatics tools. Cytoscape software was used to visualize protein-protein network. There were 201 DEGs, including 99 up-regulated genes enriched in metabolic pathways, Cellular senescence and Focal adhesion, and 102 down-regulated genes enriched in metabolic pathways, Regulation of actin cytoskeleton, Neuroactive ligand-receptor interaction, Calcium signaling pathway and Focal adhesion. Two important modules were detected and pathway enrichment analysis showed that they were mainly associated with Focal adhesion, Regulation of actin cytoskeleton and RNA transport. Fifteen hub genes were selected and among them, ITGA8, CDC42 and GSK3B might be the core genes related to apparent metabolizable energy of chickens. These hub genes can be used as biomarkers for apparent metabolizable energy and feed efficiency in breeding program of chickens.

The statistical power of genome-wide association studies for threshold traits with different frequencies of causal variants.

This study aimed to investigate the effects of incidence rate, heritability, and polygenic variance on the statistical power of genome-wide association studies (GWAS) for threshold traits. Different incidence rates of threshold trait (1, 3, 5, 10, 25, 40, 50, 60, 75 and 90%), heritability (10 and 25%), and polygenic variance ratio (0 and 25%) were simulated separately for common (MAF ≥ 0.05), low-frequency (0.05 > MAF ≥ 0.01), and rare (MAF < 0.01) variants. Association studies were performed by logistic and linear mixed models. The highest statistical powers were observed in common and low-frequency variants with an incidence of 25-50% and 10-40%, respectively, but for rare variants, the highest statistical power was observed at low incidence. For all causal variant frequencies, the estimated heritability decline with an increase in incidence rate. We found high statistical power for traits with high heritability. In contrast, those with a high polygenic variance ratio have lower statistical power to detect common causal variants using a linear mixed model. These results demonstrate that the incidence rate of threshold traits, heritability, and polygenic variance may affect the statistical power of GWAS. Therefore, it is recommended that the effect of incidence rate, heritability, and polygenic variance be considered in designing GWAS for threshold traits.

In silico analysis of different signal peptides to discover a panel of appropriate signal peptides for secretory production of Interferon-beta 1b in Escherichia coli.

Signal peptides (SPs) are one of the most important factors for suitable secretion of the recombinant  heterologous proteins in Escherichia coli (E. coli). The objective of this study was to identify a panel of signal peptides (among the 90 biologically active SPs) required for the secretory production of interferon-beta 1b (IFN-beta 1b) recombinant protein into the periplasmic space of E. coli host. In the initial step, after predicting the accurate locations of the cleavage sites of signal peptides and their discrimination scores using SignalP 4.1 server, 31 SPs were eliminated from further analysis because their discrimination scores were less than 0.5 or their cleavage sites were inappropriately located. Therefore, only 59 SPs could be theoretically applied to secrete IFN-beta 1b into the periplasmic space of E. coli. The physico-chemical and the solubility properties, which are necessary parameters for selecting appropriate SPs, were predicted using ProtParam and SOLpro servers using the 59 remaining signal peptides. The final subcellular localization of IFN-beta 1b in combination with different SPs was predicted using ProtComB server. Consequently, according to the ranking of 59  confirmed SPs, the obtained results revealed that SPs Flagellar P-ring protein (flgI), Glucan 1,3-beta-glucosidase I/II (EXG1) and outer membrane protein C (OmpC) were theoretically the most potent and desirable SPs for secretion of recombinant IFN-beta 1b into the periplasmic space of E. coli. For further studies in the future, the experimental investigations on the obtained results will be considered.

Estrogen receptor alpha gene expression in breast cancer tissues from the Iranian population--a pilot study.

Estrogen receptor alpha (ERα) is one of the major sub-types of estrogen receptors. ERα plays an important role in cellular proliferation and differentiation, chiefly in mammary tissues. In the present study we aimed to quantify of ERα mRNA and protein expression in breast tissues from the Iranian population using a real-time PCR assay. Twenty nine breast tissues including 19 adenocarcinomas and 10 normal controls were recruited from the Iranian population. mRNA extraction and cDNA synthesis were performed from these tissues using commercial kits. ERα mRNA and protein expression was quantified using real-time PCR and immunohistochemistry respectively. The results showed high expression of ERα mRNA (68%) and protein (53%) in the majority of breast cancer tissues compared to normal breast tissues (p=0.035). Also, high ERα mRNA was associated with tumour size of breast carcinomas. In this study, we first reported the expression of ERα in Iranian patients with breast cancers and demonstrated prevalence of the expression to be similar to breast cancers noted in other populations.

Analysis of genetic diversity of chukar partridge (Alectoris chukar) populations in Khorasan-e-Razavi province of Iran by RAPD-PCR.

RAPD markers were used to investigate population genetic parameters of an endangered partridge, Alectoris chukar, in four areas of Iran, as a part of a genetic conservation program. The aim of this study was to analyze the genetic similarity among these populations. Blood samples from 75 birds were used for DNA extraction and RAPD-PCR analysis of 67 loci, with 28 polymorphic bands (41.79%). The populations of Kalat-e-Nader and Mashhad were found to be closely related, as were the Torbat-e-Jaam and the Quchan populations. Mean heterozygosity for all populations was 0.4405 ± 0.0755. The results indicate that chukar partridge genetic diversity in Khorasan-e-Razavi province is sufficient and the amount of gene flow among populations is acceptable.

Genetic polymorphism at the candidate gene in Iranian Sistani cattle (Bos indicus).

The genotypes for Leptin, Kappa-Casein, Calpastatin and BoLA-DRB3 loci were determined by polymerase chain reaction and restriction enzyme digestion method in native Iranian breed cattle, Sistani. Blood samples were collected from Sistani Breeding Station located in Zehak, Zabol in Iran. The extraction of genomic DNA was based on Guanidin Thiocyanate-Silica gel method. After PCR reaction, amplicons were digested with appropriate restriction enzymes. The Calpastatin locus had 3 genotypes with frequencies of 0.62, 0.29 and 0.09 for MM, MN and NN, respectively; kappa-Casein and Leptin had 3 genotypes with frequencies of 0.27, 0.57 and 0.16 for kappa-Casein, 0.77, 0.22 and 0.01 for Leptin for AA, AB and BB genotypes, respectively. For BoLA-DRB3 we identified 19 alleles, that DRB3. 2*8 had the highest allelic frequency (22.4%) and DRB3. 2*3, *29, *37 and *51 had the lowest allelic frequency (1%). One of the 19 alleles had a new pattern. Average heterozygosity values for all loci were low. Chi2-test did not confirm the Hardy-Weinberg equilibrium for Leptin and Calpastatin in this population. These data provide evidence that Iranian's Sistani breed have a good genetic variability, which opens interesting prospects for future selection programs, especially marker-assistant selection.