A Comparative Analysis of Naïve Exosomes and Enhanced Exosomes with a Focus on the Treatment Potential in Ovarian Disorders.

Exosome-based therapy has emerged as a promising strategy for addressing diverse disorders, indicating the need for further exploration of the potential therapeutic effects of the exosome cargos. This study introduces "enhanced exosomes", a novel type of exosomes developed through a novel cell culture system. These specific exosomes may become potent therapeutic agents for treating ovarian disorders. In this study, we conducted a comparative analysis of the protein and miRNA cargo compositions of enhanced exosomes and naïve exosomes. Our findings revealed distinct cargo compositions in enhanced exosomes, featuring upregulated proteins such as EFEMP1, HtrA1, PAM, and SDF4, suggesting their potential for treating ovarian disorders. MicroRNA profiling revealed that miR-1-3p, miR-103a-3p, miR-122-5p, miR-1271-5p, miR-133a-3p, miR-184, miR-203a-3p, and miR-206 are key players in regulating ovarian cancer and chemosensitivity by affecting cell cycle progression, cell proliferation, and cell development. We examined polycystic ovary syndrome and premature ovarian insufficiency and identified the altered expression of various miRNAs, such as miR-125b-5p and miR-130b-3p, for diagnostic insights. This study highlights the potential of enhanced exosomes as new therapeutic agents for women's reproductive health, offering a detailed understanding of the impact of their cargo on ovarian disorders.

MiRNA-miRNA interaction network in peripheral blood of patients with myocardial infarction: a gene expression meta-analysis.

In recent years, investigations have revealed that microRNAs (miRNAs) can bind together and form a miRNA-miRNA-mRNA regulatory network that alters the consequence of miRNA-mRNA interaction. If we consider the miRNA that binds to mRNA as the primary miRNA and the miRNA that binds to the primary miRNA as the secondary one, secondry miRNAs can act as master regulators upstream of primary miRNAs and their target mRNAs. One of the distinguishing characteristics of secondary miRNAs as master regulators within a diverse set of differentially expressed genes is the absence of direct target mRNA for them. Instead, these master regulators exclusively govern the regulation of miRNAs that target specific mRNAs. Through in silico analysis, we identified 18 miRNAs among 385 differentially expressed miRNAs (DEmiRNAs) with no direct target mRNAs among 58 differentially expressed mRNAs (DEmRNAs) in peripheral blood of patients with myocardial infarction (MI). Instead, these secondary miRNAs targeted 9 primary miRNAs that had 36 direct targets among 58 DEmRNAs. We found that one primary miRNA might be regulated by more than one secondary miRNAs and each secondary miRNA can target more than one primary miRNAs. Among identified miRNA-miRNA-mRNA networks miR-188-5p/miR-299-3p/natural killer cell granule protein (NKG7), miR-200a-3p/miR-199b-5p/granzyme B (GZMB), and miR-377-3p/miR-581/oviductal glycoprotein 1 (OVGP1) exhibited higher scors in terms of expression levels (>2-fold increase or decrease) and strengh of interactions (ΔG < -5). Given the extensive network of miRNA interactions, focusing on master regulators opens up avenues for identifying key regulatory nodes for more effective therapeutic strategies.

The effect of saffron and its extracts on the treatment of breast cancer: A narrative review.

Breast cancer (BC) is the most prevalent malignancy in women and the second most common disease worldwide, affecting approximately one million individuals annually. Despite the efficacy of conventional chemotherapy, medication resistance and adverse effects limit its effectiveness, leading researchers to explore alternative treatments, including herbal remedies. Saffron, a well-known spice derived from the Crocus sativus L. plant, has shown potential as a BC treatment. The active components of saffron exhibit anti-cancer properties by inducing apoptosis, inhibiting cell division, and modulating signaling pathways implicated in cancer development, such as PI3K/AKT, NF-κB, and MAPK. Clinical findings suggest that saffron can alleviate chemotherapy-induced symptoms, reduce serum tumor marker levels, and enhance quality of life. Preliminary clinical trials are investigating the safety and efficacy of saffron in treating BC, with recent evidence indicating that recommended doses of saffron supplementation are well-tolerated and safe. This review provides an overview of the anti-tumor effects of saffron and its unique chemical composition in BC. However, further research and clinical studies are imperative to fully comprehend the potential of saffron in adjuvant therapy for BC patients.

Long non-coding RNAs as potential biomarkers or therapeutic targets in gastric cancer.

Aim: This study aimed to find lncRNAs and mRNAs that were expressed differently by combining microarray datasets from different studies. This was done to find important target genes in gastric cancer for anti-cancer therapy. Background: Gastric cancer (GC) is the fourth most frequent and second-most deadly malignancy worldwide. Thus, genetic diagnosis and treatment should focus on genetic and epigenetic variables. Based on several studies, disordered expression of non-coding RNAs (ncRNAs), such as lncRNAs, regulate gastric cancer invasion and metastasis. Besides, lncRNAs cooperatively regulate gene expression and GC progression. Methods: We obtained differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) from three GC tissue microarray datasets by meta-analysis and screened genes using the "Limma" package. Then, using the RNAInter database, we allocated DEmRNAs to each DElncRNA. ClusterProfiler and GOplot programs were used to analyze function enrichment pathways and gene ontologies for final DEmRNAs. Results: A total of 9 differentially expressed lncRNAs (DElncRNAs) (5 up-regulated and 4 down-regulated), and 856 DEmRNAs (451 up-regulated and 405 down-regulated) between tumor and adjacent normal samples were found. Finally, 117 differentially expressed mRNAs were predicted as interactors of six DElncRNAs (H19, WT1-AS, EMX2OS, HOTAIR, ZEB1-AS1, and LINC00261). Conclusion: In order to promote cancer therapeutics and give knowledge on the process of carcinogenesis, our study projected a network of drug-gene interactions for discovered genes and presented relevant prospective biomarkers for the prognosis of patients with stomach cancer.

Investigating unique genes of five molecular subtypes of breast cancer using penalized logistic regression.

Background: Breast cancer (BC) is the most common cancer and the fifth cause of death in women worldwide. Exploring unique genes for cancers has been interesting. Patients and Methods: This study aimed to explore unique genes of five molecular subtypes of BC in women using penalized logistic regression models. For this purpose, microarray data of five independent GEO data sets were combined. This combination includes genetic information of 324 women with BC and 12 healthy women. Least absolute shrinkage and selection operator (LASSO) logistic regression and adaptive LASSO logistic regression were used to extract unique genes. The biological process of extracted genes was evaluated in an open-source GOnet web application. R software version 3.6.0 with the glmnet package was used for fitting the models. Results: Totally, 119 genes were extracted among 15 pairwise comparisons. Seventeen genes (14%) showed overlap between comparative groups. According to GO enrichment analysis, the biological process of extracted genes was enriched in negative and positive regulation biological processes, and molecular function tracking revealed that most genes are involved in kinase and transferring activities. On the other hand, we identified unique genes for each comparative group and the subsequent pathways for them. However, a significant pathway was not identified for genes in normal-like versus ERBB2 and luminal A, basal versus control, and lumina B versus luminal A groups. Conclusion: Most genes selected by LASSO logistic regression and adaptive LASSO logistic regression identified unique genes and related pathways for comparative subgroups of BC, which would be useful to comprehend the molecular differences between subgroups that would be considered for further research and therapeutic approaches in the future.

Misexpression of LINC01410, FOSL1, and MAFB in peripheral blood mononuclear cells associated with diabetic nephropathy.

AIMS: Currently, diabetic nephropathy (DN) is considered the leading cause of the end-stage renal disease (ESRD). However, its specific molecular mechanism is still unclear, and there is still a lack of effective diagnostic and therapeutic methods. METHOD: A pathway was assumed after bioinformatics analysis of GEO datasets related to individuals with various levels of DN, LINC01410, MAFB, and FOSL1. Then, 46 patients with type 2 diabetes (T2DM) and different levels of albuminuria, and 12 individuals without diabetes, were selected. qPCR was performed to evaluate gene expression. One-way ANOVA followed by Tukey's -and linear trend tests were performed to analyze gene expression in different stages of the disease. Moreover, receiver operating characteristic (ROC) curves and the correlation between LINC01410, FOSL1, and MAFB were analyzed. RESULTS: LINC01410, MAFB, and FOSL1 were selected based on bioinformatics analyses. The qPCR results showed that the expression of LINC01410 decreased, and FOSL1 and MAFB increased in micro-and macroalbuminuria groups compared to normoalbuminuria groups (P < 0.05). ROC curves demonstrated a significant diagnostic accuracy of LINC01410, MAFB, and FOSL1 between DN and participants with normoalbuminuria (P < 0.05). Pearson's correlation analysis revealed a positive association between the expressions of FOSL1 and MAFB (p = 0.01, r = 0.39). However, there was no correlation between LINC01410 with MAFB and FOSL1 (p = 0.23 and p = 0.21, respectively). CONCLUSION: Dysregulation of LINC01410, MAFB, and FOSL1 is related to DN. These results may provide new insights into the role of LINC01410, MAFB, and FOSL1 as potential biomarkers in DN.

Detection of key mRNAs in liver tissue of hepatocellular carcinoma patients based on machine learning and bioinformatics analysis.

One methodology extensively used to develop biomarkers is the precise detection of highly responsive genes that can distinguish cancer samples from healthy samples. The purpose of this study was to screen for potential hepatocellular carcinoma (HCC) biomarkers based on non-fusion integrative multi-platform meta-analysis method. The gene expression profiles of liver tissue samples from two microarray platforms were initially analyzed using a meta-analysis based on an empirical Bayesian method to robust discover differentially expressed genes in HCC and non-tumor tissues. Then, using the bioinformatics technique of weighted correlation network analysis, the highly associated prioritized Differentially Expressed Genes (DEGs) were clustered. Co-expression network and topological analysis were utilized to identify sub-clusters and confirm candidate genes. Next, a diagnostic model was developed and validated using a machine learning algorithm. To construct a prognostic model, the Cox proportional hazard regression analysis was applied and validated. We identified three genes as specific biomarkers for the diagnosis of HCC based on accuracy and feasibility. The diagnostic model's area under the curve was 0.931 with confidence interval of 0.923-0.952.•Non-fusion integrative multi-platform meta-analysis method.•Classification methods and biomarkers recognition via machine learning method.•Biomarker validation models.

Bioinformatics-based identification of miRNAs, mRNA, and regulatory signaling pathways involved in esophageal squamous cell carcinoma.

Aim: The current study analyzed the miRNA microarray dataset (GSE66274) and gene expression microarray dataset (GSE38129) with similar samples to achieve a better understanding of miRNA-mRNA interactions. Background: The most common form of esophageal cancer is esophageal squamous cell carcinoma (ESCC). While, miRNAs are well recognized as having a critical regulatory role in human cancer, their responsibilities and mechanisms of miRNA-mRNA in ESCC are unknown. Methods: Differentially expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs) were identified using the LIMMA package in R. In total, 478 DEmRNA (224 upregulated and 254 downregulated) and 39 DEmiRNA (15 upregulated and 24 downregulated) were screened. The RNAInter database analyzed miRNA-mRNA interactions; then, the miRNA-mRNA network was visualized by Cytoscape software. ClusterProfiler packages were used to perform gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses for DEmRNA as targets of DEmiRNAs. Results: KEGG pathway analysis indicated that the p53 signaling pathway, ECM-receptor interaction, and AGE-RAGE signaling pathway were significant. Cellular response to amino acid stimulus, negative regulation of apoptotic signaling pathway, and endoderm formation were most prevalent in the biological process category. Additionally, the collagen-containing extracellular matrix, actomyosin complex collagen trimers, basement membrane, and extracellular matrix structural constituent were more enriched. Conclusion: Overall, the present survey provides evidence that could support the prognosis of esophageal tumors in the future.

Novel targets to overcome antiangiogenesis therapy resistance in glioblastoma multiforme: Systems biology approach and suggestion of therapy by galunisertib.

Glioblastoma multiforme (GBM) is a tumor with high microvessel density. Antiangiogenesis therapy (AAT) resistance occurs due to the complex mechanisms involved in angiogenesis, with increased chances of recurrence. The vascular endothelial growth factor (VEGF) pathway is the main pathway of angiogenesis, and anti-VEGF drugs have been ineffective in controlling it. New oncogenes in the VEGF signaling pathway may be new candidates for angiogenesis targeting. Oncogene candidates were chosen using gene expression profiles and databases. Then oncogenes were subjected to gene set enrichment analysis (GSEA) and survival analysis (SA). Molecular docking was conducted to evaluate the interaction of the oncogenes with galunisertib. NRAS, AKT1, and HSPB1 were the most effective oncogenes upregulating genes that play a role in GBM expression in the VEGF signaling pathway. The VEGF and MAPK signaling pathways were found to be effective using GSEA and Kyoto Encyclopedia Gene and Genome pathway analysis. Survival analyses revealed that patients with high HSPB1 expression had poorer overall survival rates than those with low HSPB1 expression. Galunisertib exhibits intermolecular interactions with 6DV5, 5UHV, and 3O96 (binding energy -8.0, -8.6, and -10.3 kcal/mol, respectively). The current AAT should be restrategized to suppress the numerous angiogenic elements to manage angiogenesis and combat AAT resistance in GBM. In silico analysis indicated that NRAS, AKT1, and HSPB1 genes can be the main oncogenes in the VEGF signaling pathway and galunisertib strongly interacts with these genes. Consequently, the use of galunisertib to overcome AAT in GBM in combination therapy can be assessed.

Investigation of genes and pathways involved in breast cancer subtypes through gene expression meta-analysis.

BACKGROUND: Molecular-based studies have revealed heterogeneity in Breast cancer BC while also improving classification and treatment. However, efforts are underway to distinguish between distinct subtypes of breast cancer. In this study, the results of several microarray studies were combined to identify genes and pathways specific to each BC subtype. METHODS: Meta-analysis of multiple gene expression profile datasets was screened to find differentially expressed genes (DEGs) across subtypes of BC and normal breast tissue samples. Protein-protein interaction network and gene set enrichment analysis were used to identify critical genes and pathways associated with BC subtypes. The differentially expressed genes from meta-analysis was validated using an independent comprehensive breast cancer RNA-sequencing dataset obtained from the Cancer Genome Atlas (TCGA). RESULTS: We identified 110 DEGs (13 DEGs in all and 97 DEGs in each subtype) across subtypes of BC. All subtypes had a small set of shared DEGs enriched in the Chemokine receptor bind chemokine pathway. Luminal A specific were enriched in the translational elongation process in mitochondria, and the enhanced process in luminal B subtypes was interferon-alpha/beta signaling. Cell cycle and mitotic DEGs were enriched in the basal-like group. All subtype-specific DEG genes (100%) were successfully validated for Luminal A, Luminal B, ERBB2, and Normal-like. However, the validation percentage for Basal-like group was 77.8%. CONCLUSION: Integrating researches such as a meta-analysis of gene expression might be more effective in uncovering subtype-specific DEGs and pathways than a single-study analysis. It would be more beneficial to increase the number of studies that use matched BC subtypes along with GEO profiling approaches to reach a better result regarding DEGs and reduce probable biases. However, achieving 77.8% overlap in basal-specific genes and complete concordance in specific genes related to other subtypes can implicate the strength of our analysis for discovering the subtype-specific genes.

Genome-wide evaluation of transcriptomic responses of human tissues to smoke: A systems biology study.

The harmful compounds in various sources of smoke threaten human health. So far, many studies have investigated the effects of compounds of smoke on transcriptome changes in different human tissues. However, no study has been conducted on the effects of these compounds on transcriptome changes in different human tissues simultaneously. Hence, the present study was conducted to identify smoke-related genes (SRGs) and their response mechanisms to smoke in various human cells and tissues using systems biology based methods. A total of 6,484 SRGs were identified in the studied tissues, among which 4,095 SRGs were up-regulated and 2,389 SRGs were down-regulated. Totally, 459 SRGs were smoke-related transcription factors (SRTFs). Gene regulatory network analysis showed that the studied cells and tissues have different gene regulation and responses to compounds of smoke. The comparison of different tissues revealed no common SRG among the all studied tissues. However, the CYP1B1 gene was common among seven cells and tissues, and had the same expression trend. Network analysis showed that the CYP1B1 is a hub gene among SRGs in various cells and tissues. To the best of our knowledge, for the first time, our results showed that compounds of smoke induce and increase the expression of CYP1B1 key gene in all target and non-target tissues of human. Moreover, despite the specific characteristics of CYP1B1 gene and its identical expression trend in target and non-target tissues, it can be used as a biomarker for diagnosis and prognosis.

Comprehensive analysis of ceRNA networks to determine genes related to prognosis, overall survival, and immune infiltration in clear cell renal carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is one of the common subtypes of kidney cancer. Circular RNAs (circRNAs) act as competing endogenous RNAs (ceRNAs) to affect the expression of microRNAs (miRNAs), and hence the expression of genes involved in the development and progression of ccRCC. However, these interactions have not been sufficiently explored. METHODS: The differential expression of circRNAs (DEC) was extracted from the GEO database, and the expression of circRNAs was analyzed by the Limma R package. The interaction of miRNAs with circRNAs was predicted using (cancer-specific circRNA database) CSCD and circinteractome database. The genes affected by the miRNAs were predicted by miRwalk version 3, and the differential expression was retrieved using TCGA. Functional enrichment was assessed and a PPI network was created using DAVID and Cytoscape, respectively. The genes with significant interactions (hub-genes) were screened, and the total survival rate of ccRCC patients was extracted from the Gene Expression Profiling Interactive Analysis (GEPIA) database. To confirm the expression of OS genes we used the Immunohistochemistry (IHC) data and TCGA database. The correlation between gene expression and immune cell infiltration was investigated using TIMER2.0. Finally, potential drug candidates were predicted by the cMAP database. RESULTS: Four DECs (hsa_circ_0003340, hsa_circ_0007836, hsa_circ_0020303, and hsa_circ_0001873) were identified, along with 11 interacting miRNAs (miR-1224-3p, miR-1294, miR-1205, miR-1231, miR-615-5p, miR-940, miR-1283, and miR-1305). These miRNAs were predicted to affect 1282 target genes, and function enrichment was used to identify the genes involved in cancer biology. 18 hub-genes (CCR1, VCAM1, NCF2, LAPTM5, NCKAP1L, CTSS, BTK, LILRB2, CD53, MPEG1, C3AR1, GPR183, C1QA, C1QC, P2RY8, LY86, CYBB, and IKZF1) were identified from a PPI network. VCAM1, NCF2, CTSS, LILRB2, MPEG1, C3AR1, P2RY8, and CYBB could affect the survival of ccRCC patients. The hub-gene expression was correlated with tumor immune cell infiltration and patient prognosis. Two potantial drug candidates, naphazoline and lithocholic acid could play a role in ccRCC therapy, as well other cancers. CONCLUSION: This bioinformatics analysis brings a new insight into the role of circRNA/miRNA/mRNA interactions in ccRCC pathogenesis, prognosis, and possible drug treatment or immunotherapy.

A new insight into sex-specific non-coding RNAs and networks in response to SARS-CoV-2.

SARS-CoV-2 is the RNA virus responsible for COVID-19, the prognosis of which has been found to be slightly worse in men. The present study aimed to analyze the expression of different mRNAs and their regulatory molecules (miRNAs and lncRNAs) to consider the potential existence of sex-specific expression patterns and COVID-19 susceptibility using bioinformatics analysis. The binding sites of all human mature miRNA sequences on the SARS-CoV-2 genome nucleotide sequence were predicted by the miRanda tool. Sequencing data was excavated using the Galaxy web server from GSE157103, and the output of feature counts was analyzed using DEseq2 packages to obtain differentially expressed genes (DEGs). Gene set enrichment analysis (GSEA) and DEG annotation analyses were performed using the ToppGene and Metascape tools. Using the RNA Interactome Database, we predicted interactions between differentially expressed lncRNAs and differentially expressed mRNAs. Finally, their networks were constructed with top miRNAs. We identified 11 miRNAs with three to five binding sites on the SARS-COVID-2 genome reference. MiR-29c-3p, miR-21-3p, and miR-6838-5p occupied four binding sites, and miR-29a-3p had five binding sites on the SARS-CoV-2 genome. Moreover, miR-29a-3p, and miR-29c-3p were the top miRNAs targeting DEGs. The expression levels of miRNAs (125, 181b, 130a, 29a, b, c, 212, 181a, 133a) changed in males with COVID-19, in whom they regulated ACE2 expression and affected the immune response by affecting phagosomes, complement activation, and cell-matrix adhesion. Our results indicated that XIST lncRNA was up-regulated, and TTTY14, TTTY10, and ZFY-AS1 lncRN as were down-regulated in both ICU and non-ICU men with COVID-19. Dysregulation of noncoding-RNAs has critical effects on the pathophysiology of men with COVID-19, which is why they may be used as biomarkers and therapeutic agents. Overall, our results indicated that the miR-29 family target regulation patterns and might become promising biomarkers for severity and survival outcome in men with COVID-19.

Exploring VEGF-Linked Pathways: Investigating Multiple miRNAs for Their Therapeutic Potential in Angiogenesis Targets and as Biomarkers in Recurrent Glioblastoma Multiforme.

Alternative pathways frequently operate as the origins of resistance to drugs that block the vascular endothelial growth factor (VEGF) pathway. To find possible therapeutic targets and indicators, this study explored the VEGF pathway and how miRNAs control it in recurrent glioblastoma multiforme (rGBM). Differentially expressed miRNAs (DEmiRNAs) were identified by using GBM GSE profiles (GSE32466). To find pathways containing DEmiRNAs, VEGF pathway genes, and their related genes, DIANA-miRPath v3.0 and the ToppGene database were utilized. miRNAs linked to VEGF signaling pathway genes, interactional genes, and DEmiRNAs were discovered by extracting common pathways. The ability of these miRNAs to distinguish rGBM patients from those with primary GBM was assessed using ROC analysis. The study revealed that in rGBM, 30 miRNAs were significantly up-regulated and 49 miRNAs were considerably down-regulated. Among them, the VEGF pathway was connected to 22 up-regulated miRNAs and 29 down-regulated miRNAs. The MAPK pathway shared the most genes with the VEGF pathway, accounting for 1,014 of the interacting genes, which were discovered to have interactions with VEGF signaling pathway genes. Furthermore, 14 miRNAs were identified as having a great deal of potential as molecular biomarkers and therapeutic targets for rGBM. The results indicate that the VEGF pathway in rGBM is regulated by a number of interrelated pathways. The discovered miRNAs hold promise as rGBM biomarkers and therapeutic targets, offering possibilities for novel therapy strategies and aiding rGBM diagnosis and prognosis.

The effect of A1298c polymorphism of the MTHFR gene on anti-Müllerian hormone levels: experimental and Web-based analysis.

BACKGROUND: The 5,10-methylenetetrahydrofolate reductase (MTHFR) is an important enzyme of folate and methionine metabolism, which is expressed in human oocytes and preimplantation. Due to the involvement of MTHFR in female reproduction, we tend to evaluate the influence of MTHFR A1298C polymorphism on ovarian marker reserves such as serum anti-Müllerian hormone (AMH) levels in women after in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI). METHODS: A total of 100 women, who underwent ART treatment due to male factor infertility, were recruited into this study. MTHFR A1298C polymorphism was detected by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique, and serum AMH concentrations were measured by an ultrasensitive enzyme-linked immunosorbent assay (ELISA). RESULTS: Women with the CC genotype had higher AMH levels (4.15 ± 1.67 ng/ml), albeit not significant, than carriers with other genotypes after ovarian stimulation. No significant differences existed in terms of miscarriage and live birth rates among different genotype groups. CONCLUSION: The presence of the C mutant allele of the 1298 polymorphism in the MTHFR gene led to an increasing trend in serum AMH concentrations; however, the numbers of oocytes retrieved decreased in women with mutated genotypes. The influence of the MTHFR C677T polymorphism on embryo quality and pregnancy rate after ART cycles remains unclear.

High affinity of host human microRNAs to SARS-CoV-2 genome: An in silico analysis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) caused by a novel betacoronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has attracted top health concerns worldwide within a few months after its appearance. Since viruses are highly dependent on the host small RNAs (microRNAs) for their replication and propagation, in this study, top miRNAs targeting SARS-CoV-2 genome and top miRNAs targeting differentially expressed genes (DEGs) in lungs of patients infected with SARS-CoV-2, were predicted. METHODS: All human mature miRNA sequences were acquired from miRBase database. MiRanda tool was used to predict the potential human miRNA binding sites on the SARS-CoV-2 genome. EdgeR identified differentially expressed genes (DEGs) in response to SARS-CoV-2 infection from GEO147507 data. Gene Set Enrichment Analysis (GSEA) and DEGs annotation analysis were performed using ToppGene and Metascape tools. RESULTS: 160 miRNAs with a perfect matching in the seed region were identified. Among them, there was 15 miRNAs with more than three binding sites and 12 miRNAs with a free energy binding of -29 kCal/Mol. MiR-29 family had the most binding sites (11 sites) on the SARS-CoV-2 genome. MiR-21 occupied four binding sites and was among the top miRNAs that targeted up-regulated DEGs. In addition to miR-21, miR-16, let-7b, let-7e, and miR-146a were the top miRNAs targeting DEGs. CONCLUSION: Collectively, more experimental studies especially miRNA-based studies are needed to explore detailed molecular mechanisms of SARS-CoV-2 infection. Moreover, the role of DEGs including STAT1, CCND1, CXCL-10, and MAPKAPK2 in SARS-CoV-2 should be investigated to identify the similarities and differences between SARS-CoV-2 and other respiratory viruses.

Evaluation of FTO rs9939609 and MC4R rs17782313 Polymorphisms as Prognostic Biomarkers of Obesity: A Population-based Cross-sectional Study.

OBJECTIVES: Obesity is a significant risk factor for a number of chronic diseases, including diabetes, cardiovascular diseases, and cancer. Obesity usually results from a combination of causes and contributing factors, including genetics and lifestyle choices. Many studies have shown an association of single nucleotide polymorphisms (SNPs) in the fat mass and obesity-associated (FTO) and the melanocortin-4 receptor (MC4R) genes with body mass index (BMI). Therefore, recognizing the main genes and their relevant genetic variants will aid prediction of obesity risk. The aim of our study was to investigate the frequency of rs9939609 and rs17782313 polymorphisms in FTO and MC4R genes in an Iranian population. METHODS: We enrolled 130 obese patients and 83 healthy weight controls and calculated their BMI. Genomic DNA was extracted from peripheral blood and the frequency of rs9939609 and rs17782313 polymorphisms in FTO and MC4R genes was determined using the tetra-primer amplification refractory mutation system-polymerase chain reaction (ARMS-PCR). RESULTS: Significant associations were found between FTO rs9939609 and BMI. Where homozygous risk allele carriers (A-A) have significant higher odds ratio (OR) of being obese than individuals with normal BMI (OR = 6.927, p < 0.005, 95% confidence interval (CI): 3.48-13.78). No significant correlation between MC4R rs17782313 and obesity were observed when compared to healthy weight individuals. Although subjects with C-C genotype had higher odds of obesity (OR = 1.889, p = 0.077, 95%CI: 0.92-3.84). CONCLUSIONS: This study shows a relationship between FTO polymorphism and increased BMI, therefore, SNP in the FTO gene influence changes in BMI and can be considered a prognostic marker of obesity risk.

A Systematic In Silico Analysis of the Legionellaceae Family for Identification of Novel Drug Target Candidates.

The family Legionellaceae consists of Gram-negative bacteria that are widely distributed in aquatic environments around the world. This family consists of a single genus, Legionella, that is recognized as an important cause of community-acquired pneumonia and hospital-acquired pneumonia. Legionella consists of intracellular pathogens, thus cellular pharmacokinetic and pharmacodynamic properties of an antibiotic against these bacteria as well as uptake and subcellular distribution into macrophages should be considered for a successful outcome of disease. Treatment strategies for Legionella infection require a combination of multiple antibiotics. Hence, because of the possible development of resistance to the drugs during therapy, a new alternative targeted therapy is yielding promising results. In this study, a comprehensive in silico target identification pipeline was performed on members of the family Legionellaceae to identify the best targets. Using a homology-based computational pipeline method, new drug targets were identified. Of 4,358 analyzed proteins, 18 proteins, including proteins involved in metabolism (amino acid, energy, and lipid metabolisms), cellular transport, cell division, and cell motility, were selected as the final putative drug targets. These proteins play an important role in the survival and propagation of Legionella infection. In conclusion, homology-based methods could improve the identification of novel drug targets and the drug discovery process, which can potentially be effective for the prevention and treatment of Legionella infections.

Genome-Wide Identification of Potential Drug Target in Enterobacteriaceae Family: A Homology-Based Method.

The Enterobacteriaceae is a large family of Gram-negative, facultative anaerobic, non-spore forming rod-shaped bacteria that includes harmless and pathogenic organisms. The emergence and development of drug resistance in Enterobacteriaceae is complicating the treatment of serious infections. The aim of this study is to predict and characterize putative drug targets in Enterobacteriaceae family employing a homology-based computational method. The final putative drug targets were qualitatively characterized via cellular function prediction, subcellular localization prediction, broad-spectrum, and druggability analyses. Of 6,327 analyzed proteins, 35 proteins were selected as final putative drug targets in Enterobacteriaceae family. These putative drug targets were involved in different vital pathways like metabolism, biosynthesis of macromolecule, and cell division. Predicted drug targets were also localized in the cytoplasm and cytoplasmic membrane of the pathogen that acts as antimicrobial or vaccine targets. Of 35 drug targets, 5 targets were druggable and 30 targets were not druggable and were predicted as novel drug targets, which should be further evaluated to develop new antimicrobial. Thirteen drug targets were considered as broad-spectrum targets. It is expected that results of our study could facilitate the production of novel antibacterial for efficient treatment of infections caused by Enterobacteriaceae pathogens.