Iranian Journal of Biotechnology最新文献

Background: In-silico analysis provides a fast, simple, and cost-free method for identifying potentially pathogenic single nucleotide variants.

Objective: To propose a simple and relatively fast method for the prediction of variant pathogenicity using free online in-silico (IS) tools with AURKA gene as a model.

Materials and methods: We aim to propose a methodology to predict variants with high pathogenic potential using computational analysis, using AURKA gene as model. We predicted a protein model and analyzed 209 out of 64,369 AURKA variants obtained from Ensembl database. We used bioinformatic tools to predict pathogenicity. The results were compared through the VarSome website, which includes its own pathogenicity score and the American College of Medical Genetics (ACMG) classification.

Results: Out of the 209 analyzed variants, 16 were considered pathogenic, and 13 were located in the catalytic domain. The most frequent protein changes were size and hydrophobicity modifications of amino acids. Proline and Glycine amino acid substitutions were the most frequent changes predicted as pathogenic. These bioinformatic tools predicted functional changes, such as protein up or down-regulation, gain or loss of molecule interactions, and structural protein modifications. When compared to the ACMG classification, 10 out of 16 variants were considered likely pathogenic, with 7 out of 10 changes at Proline/Glycine substitutions.

Conclusion: This method allows quick and cost-free bulk variant screening to identify variants with pathogenic potential for further association and/or functional studies.

Background: Coagulation factor VIII (FVIII) is applied for spontaneous hemorrhaging inhibition and excessive bleeding after trauma in patients with hemophilia A. High-quality human recombinant factor VIII (rFVIII) has been produced relatively in large quantities in cultured mammalian cells. NS0 is one of the most common mammalian cell lines for therapeutic protein production. Production of rFVIII has increased due to low FVIII expression levels and rising demand for hemophilia A prophylactic treatment. Several methods have been developed to prevent cell cycle progression in mammalian cells for increased recombinant protein yields.

Objective: The aim of the study was to investigate the level of recombinant BDD-FVIII expression in NS0 mouse myeloma cells. Additionally, the study aimed to determine the effects of chemical drugs, Mitomycin C, Lovastatin, and Metformin on the secretion of FVIII through cell cycle arrest.

Materials and methods: We cultured NS0 cells and transfected them with the 2 μg pcDNA3-hBDDFVIII plasmid by Lipofectamine 3000. The cells were treated with 10 μg.mL^-1 Mitomycin C, 20 μM Lovastatin, and 20 mM Metformin separately. After 24 and 48 hours, the samples were collected and, protein expression was analyzed using RT-PCR, Dot blot, and ELISA.

Results: A higher protein expression level was observed in treated cells 24h and 48h after treatment with all three drugs. According to real-time PCR, Metformin treatment resulted in the highest expression level within 24 h (P=0.0026), followed by Mitomycin C treatment within 48 h (P=0.0030).

Conclusion: The NS0 cell line can be regarded as a suitable host for FVIII production. FVIII protein expression level was increased by using Lovastatin, Metformin, and Mitomycin C drugs. Further investigations are suggested, and the potential application of these drugs to increase recombinant protein yield can be used to produce therapeutic proteins in the industry.

Background: The early detection of infectious microorganisms is crucial for preventing and controlling the transmission of diseases. This article provides a comprehensive review of biosensors based on various diagnostic methods for measuring airborne pathogens.

Objective: This article aims to explore recent advancements in the field of biosensors tailored for the detection and monitoring of airborne microorganisms, offering insights into emerging technologies and their potential applications in environmental surveillance and public health management.

Materials and methods: The study summarizes the research conducted on novel methods of detecting airborne microorganisms using different biological sensors, as well as the application of signal amplification technologies such as polymerase chain reaction (PCR), immunoassay reactions, molecular imprinted polymers (MIP) technique, lectin and cascade reactions, and nanomaterials.

Results: Antibody and PCR detection methods are effective for specific microbial strains, but they have limitations including limited stability, high cost, and the need for skilled operators with basic knowledge of the target structure. Biosensors based on MIP and lectin offer a low-cost, stable, sensitive, and selective alternative to antibodies and PCR. However, challenges remain, such as the detection of small gas molecules by MIP and the lower sensitivity of lectins compared to antibodies. Additionally, achieving high sensitivity in complex environments poses difficulties for both methods.

Conclusion: The development of sensitive, reliable, accessible, portable, and inexpensive biosensors holds great potential for clinical and environmental applications, including disease diagnosis, treatment monitoring, and point-of-care testing, offering a promising future in this field. This review presents an overview of biosensor detection principles, covering component identification, energy conversion principles, and signal amplification. Additionally, it summarizes the research and applications of biosensors in the detection of airborne microorganisms. The latest advancements and future trends in biosensor detection of airborne microorganisms are also analyzed.

Background: The lipase enzyme (EC: 3.1.1.3) is one of the most important catalysts in food, dairy, detergent, and textile industries.

Objective: This study was performed to identify, isolate and characterize of lipase producing bacterial strain from agrifood wastes and to identify and characterize of their lipase genes.

Materials and methods: In the present study, two lipase-producing isolates were identified from the effluent of Golbahar meat products and Soveyda vegetable oil factories using in silico and in vitro approaches.

Results: The results of morphological, biochemical, and molecular characterizations showed that both lipase-producing isolates belong to the Bacillus amyloliquefaciens species. Phylogenetic analysis confirmed the results of phenotypic, biochemical, and molecular characterizations. The results showed differences between LipA and LipB in the Golbahar and Soveyda isolates. Three different amino acids (residues 14, 100, and 165) were observed in LipA and one different amino acid (residue 102) was detected in LipB extracellular lipases. The protein molecular weight of the two extracted lipases ranged from 20 to 25 kDa. The identified extracellular lipases also had different physicochemical features. The maximum lipase activity of the Golbahar and Soveyda isolates was observed at 45 °C and at the pH of 8, but the Golbahar isolates exhibited higher lipase activity compared to the Soveyda isolates. The Golbahar and Soveyda isolates exhibited different activities in the presence of some ions, inhibitors, denaturing agents, and organic solvents and the Golbahar isolates showed better lipase activity than the Soveyda isolates.

Conclusions: In this study, two extracellular lipase-producing isolates of B. amyloliquefaciens were identified from different food industries, and their characteristics were investigated. The results of various investigations showed that the lipases produced by the Golbahar isolate have better characteristics than the lipases of the Soveyda isolate. The Golbahar lipases have a suitable temperature and pH activity range and maintain their activity in the presence of some ions, inhibitors, denaturing agents, and organic solvents. After further investigation, the Golbahar isolate lipase can be used in various industries. In addition, this lipase can be used enzyme engineering processes and its activity can be arbitrarily changed by targeted mutations. The results of this study can increase our knowledge of extracellular lipases and may turn out to have industrial applications.

Background: Plants are a precious resource of a wide range of secondary metabolites, that are benefitted as flavours, pharmaceuticals, colours, colognes, food additives and also biopesticides.

Objective: The current study tested the impact of silver nanoparticles (AgNPs) on Foeniculum vulgare.

Materials and methods: Foeniculum vulgare seeds were surface sterilized, Vital leaf pieces are grown on MS media including diverse mixtures of plant growth regulators, the special effects of AgNPs plus PGRs on callus propagation were evaluated, and separated compounds of fatty acid and vitamins were identified.

Results: Outcomes revealed that several intensities of AgNPs expressively influenced the callus propagation and significantly raised the callus biomass with combination including the plant growth regulators. Highest fresh (7.32 g.L^-1) biomass addition of callus was remarked on the media elevated in vitro at 20 ppm AgNPs combined with (2 mg.L^-1 2,4-D) and results noted that the callus appeared compact and greenish in colour with 40 ppm AgNPs in combination with (2 mg.L^-1 2,4-D). The results elucidated the amplification of the value of both fatty acids (stearic acid (47.85 %), oleic acid (189.28 %), Linoleic (6.34 %) and Linolenic (0.83 %)), and vitamins (Vitamin E (8.99 U.mg-1) and vitamin A (27.19 U.mg-1) by using MS + 2,4-D (2 mg.L^-1) + AgNPs (20ppm).

Conclusion: Application of a combination of AgNPs along with PGRs led to callus proliferation in Foeniculum vulgare L. In vitro. But, the unaccompanied use of AgNPs was originate inductive in the biosynthesis of greater quantities of special fatty acids and vitamin metabolites.

Background: Breast cancer ranks as the second highest cause of cancer-linked deaths in women, with varying rates between Western and Asian countries. The consumption of phytoestrogens can influence breast cancer occurrence.

Objective: To comprehend how soy isoflavones impact breast cancer cells, we conducted a meta-analysis, combining gene expression data from multiple studies. This approach aimed to identify crucial transcriptional characteristics driving breast cancer cell response to soy phytoestrogens.

Materials and methods: The gene expression profiles obtained from the Gene Expression Omnibus and Array Express and were grouped into control and isoflavones exposure conditions. We performed a meta-analysis based on the effect size combination method to identify the differentially expressed genes (DEGs). In addition, we performed Gene Ontology (GO) enrichment analysis, pathway analysis, weighted gene co-expression network analysis (WGCNA) and recursive support vector machine (R-SVM) algorithm.

Results: Based on this meta-analysis, we identified 3,890 DEGs, of which 2,173 were up-regulated and 1,717 were down-regulated. For example, SGCG, PLK2, and TBC1D9 were the most highly down-regulated genes and EGR3, WISP2, and FKBP4 were the most highly expressed genes in the isoflavones exposure condition. The functional enrichment and pathway analysis were revealed "cell division" and "cell cycle" among the most enriched terms. Among the identified DEGs, 269 transcription factor (TF) genes belonged to 42 TF families, where the C₂H₂ ZF, bZIP, and bHLH were the most prominent families. We also employed the R-SVM for detecting the most important genes to classify samples into isoflavones exposure and control conditions. It identified a subset of 100 DEGs related to regulation of cell growth, response to estradiol, and intermediate ribonucleoside monophosphate in the purine (IMP) metabolic process. Moreover, the WGCNA separated the DEGs into five discrete modules strongly enriched for genes involved in cell division, DNA replication, embryonic digit morphogenesis, and cell-cell adhesion.

Conclusion: Our analysis provides evidence suggesting that isoflavone affects various mechanisms in cells, including pathways associated with NF-κB, Akt, MAPK, Wnt, Notch, p53, and AR pathways, which can lead to the induction of apoptosis, the alteration of the cell cycle, the inhibition of angiogenesis, and interference in the redox state of cells. These findings can shed light on the molecular mechanisms that underlie the response of breast cancer cells to isoflavones.

Objectives: This study aims to introduce a methodology for identifying medicinal plants that contain effective natural compounds with the most possible synergistic effects to inhibit cancer survival and proliferation in a multi-targeted manner.

Materials and methods: To select targets, the signaling pathways involved in cancer development were defined from the KEGG database, and the protein-protein interactions (PPIs) of genes within these pathways were investigated using the STRING software. Then 14 proteins with the highest degree were identified as targets. Using the NPASS database, natural compounds were initially filtered based on their IC₅₀ against 50 cancer cell lines. Finally, a total of 1,107 natural compounds were docked to the 14 selected targets involved in cancer and 5 targets involved in general drug side effects.

Results: The targets with the highest protein interactions, as identified by PPI analysis on cancer signaling pathways, were selected as hub proteins. Natural compounds with IC₅₀ less than 20000 nM against cancer cell lines were then docked to these selected targets using the NPASS database. Natural compounds with low binding energy to the selected targets were identified as potential synergistic inhibitors of cancer progression if used together. Additionally, plants reported with the widest range of identified natural compounds were introduced as potential sources of synergistic effects against cancer development.

Conclusions: We have proposed a methodology for pre-screening the natural compounds database to identify potential compounds with a high likelihood of producing a synergistic response against multiple molecular mechanisms in cancer. However, further validation methods are necessary to confirm their effectiveness.

Background: Colorectal cancer (CRC) is one of the leading causes of cancer-related mortalities across the globe. Accumulating evidence shows that individuals having sleep disorders such as insomnia are at high risk of developing CRC, yet the association of sleep disorders with CRC risk is still unclear. Here, we investigated the potential molecular connections between CRC and insomnia using integrative in silico approaches.

Objective: This study aims to explore the potential molecular connections between CRC and insomnia utilizing integrative in-silico methodologies.

Methods and methods: Gene expression microarray datasets for CRC and insomnia samples were retrieved from the NCBI-GEO database and analyzed using R. Functional enrichment analysis of common differentially expressed genes (DEGs) was performed by the g: Profiler tool. Cytoscape software was used to construct a protein-protein interaction network and hub gene identification. Expression profiles of hub genes in TCGA datasets were also determined, and predicted miRNAs targeting hub genes were analyzed by miRNA target prediction tools.

Results: Our results revealed a total of 113 shared DEGs between the CRC and insomnia datasets. Six genes (HSP8A, GAPDH, HSP90AA1, EEF1G, RPS6, and RPLP0), which were also differently expressed in TCGA datasets, were prioritized as hub genes and were found to be enriched in pathways related to protein synthesis. hsa-miR-324-3p, hsa-miR-769-3p, and hsa-miR-16-5p were identified as promising miRNA biomarkers for two diseases.

Conclusions: Our in-silico analysis provides promising evidence of the molecular link between CRC and insomnia and highlights multiple potential molecular biomarkers and pathways. Validation of the results by wet lab work can be utilized for novel translational and precision medicine applications to alleviate the public health burden of CRC.

Background: The main problem in the recombinant protein expression in E. coli strains, especially for high-yield production, is the accumulation in un-folded and inactive inclusion bodies. A suitable solution is the direction into the soluble cytoplasmic products by solubilizing tags. The use of inteins with self-cleaving ability, in addition to increase the chance of soluble protein expression, facilitates their purification process.

Evidence acquisition: In this review article, papers related to the use of intein tags for soluble expression or protein purification were collected regardless the time limit. Available databases including Pubmed, google scholar, ScienceDirect, Web of Science, Scopus, and Embase was searched. The best condition for soluble expression or purification was focused in all articles.

Results: There are various intein tags commercially available in expression vectors that results in gaining our goal in facilitating the recombinant protein solubilization as well as its simple purification. It is enough to induce the self-cleavage property of the intein, which varies according to the type of intein used. In this way, the target protein is easily separated from the purification tag without the need to add protease enzymes such as enterokinase or treatment with various chemicals. The most common affinity tag in intein-based systems is Chitin Binding Domain attached to the chitin resin.

Conclusions: In this review article, we introduced proteins or peptides which produced in fusion to intein tags and discussed about their expression condition and purification process in order to enhance the chance of soluble expression and intein cleavage in a single stage, respectively.

Background: DNA methylation plays important roles in regulating various biological processes, including self-renewal, differentiation and regenerative capacity of stem cells. Previous studies have demonstrated that lineage-specific differentiation of mesenchymal stem cells can be promoted using nontoxic chromatin-modifying drugs.

Objectives: Here we evaluated the impact of RG108, a known DNA methyltransferase inhibitor, on the expression of pluripotency genes in human adipose tissue-derived stem cells (hADSCs) and their proliferation and differentiation.

Materials and methods: Human ADSCs were isolated by collagenase treatment and characterized. Then, ADSCs were treated with 5 µM RG108 for four days. The control and RG108-treated cells were analyzed for the cell cycle progression, apoptosis and the expression of pluripotency genes. Also, ADSCs were cultured in adipogenic and osteogenic differentiation media for three weeks and were assessed by Oil Red O and Alizarin Red S staining and qPCR analysis.

Results: We showed that RG108 treatment increased proliferation of hADSCs and upregulated the expression of pluripotency-related genes. Additionally, RG108 had a positive impact on the differentiation capability of ADSCs. This was evident through elevated levels of Oil Red O staining in the RG108 treatment group. Also, qPCR analysis showed the upregulation of some adipogenic and osteogenic markers by RG108.

Conclusion: These findings indicate that pretreatment with RG108 improves the differentiation potential of ADSCs, probably making these cells more beneficial for cell therapy applications.