A Nuclear Magnetic Resonance-Based Metabolomic Study to Identify Metabolite Differences between Iranian Isolates of Leishmania major and Leishmania tropica.

Background: Cutaneous leishmaniasis caused by Leishmania species (L. spp) is one of the most important parasitic diseases in humans. To gain information on the metabolite variations and biochemical pathways between L. spp, we used the comparative metabolome of metacyclic promastigotes in the Iranian isolates of L. major and L. tropica by proton nuclear magnetic resonance (1H-NMR). Methods: L. tropica and L. major were collected from three areas of Iran, namely Gonbad, Mashhad, and Bam, between 2017 and 2018, and were cultured. The metacyclic promastigote of each species was separated, and cell metabolites were extracted. 1H-NMR spectroscopy was applied, and the data were processed using ProMatab in MATLAB (version 7.8.0.347). Multivariate statistical analyses, including the principal component analysis and the orthogonal projections to latent structures discriminant analysis, were performed to identify the discriminative metabolites between the two L. spp. Metabolites with variable influences in projection values of more than one and a P value of less than 0.05 were marked as significant differences. Results: A set of metabolites were detected, and 24 significantly differentially expressed metabolites were found between the metacyclic forms of L. major and L. tropica isolates. The top differential metabolites were methionine, aspartate, betaine, and acetylcarnitine, which were increased more in L. tropica than L. major (P<0.005), whereas asparagine, 3-hydroxybutyrate, L-proline, and kynurenine were increased significantly in L. major (P<0.01). The significantly altered metabolites were involved in eight metabolic pathways. Conclusion: Metabolomics, as an invaluable technique, yielded significant metabolites, and their biochemical pathways related to the metacyclic promastigotes of L. major and L. tropica. The findings offer greater insights into parasite biology and how pathogens adapt to their hosts.

Evaluation of gene expression change in eosinophilic gastroenteritis.

AIM: Screening differentially expressed genes (DEGs) related to Eosinophilic gastroenteritis (EG) to introduce possible biomarkers. BACKGROUND: EG as a rare gastrointestinal disorder is characterized with gastrointestinal bleeding, crampy generalized abdominal pain, diarrhea, nausea, vomiting, and weight loss. In this study gene expression profile of patients is analysis via protein-protein interaction (PPI) analysis to reveal new prospective of disease. METHODS: Top significant genes of gene expression profiles of 5 gastric antrum EG patients and 5gastric antrum control from GEO which were matched via boxplot analysis were screened via PPI network by using Cytoscape software and STRING database. Numbers of 20 top nodes of query DEGs based on degree value were introduced as central nodes which 7 critical central genes among them were identified. Gene ontology enrichment for the 20 central genes was done by using CluGO. Action map for the central genes was performed by applying CluePedia. RESULTS: Among 20 central nodes, TXN, PRDX2, NR3C1, GRB2, PIK3C3, AP2B1 and REPS1 were recognized as critical central genes. Nine biological terms were determined that most of them were involved in the transport processes. CONCLUSION: The introduced possible biomarkers can be used in the differential diagnosis of the disease and also in treatment of disorder.

Introducing Critical Pain-related Genes: A System Biology Approach.

INTRODUCTION: Pain is valuable in diagnosis and also warning of the patients. Many molecular reagents are introduced which are related to pain. In this research, the pain-related genes are screened to identify the critical ones. METHODS: First, the pain-related genes were pulling out from the STRING database, and Cytoscape software was used to make the interactome unit. Then the central genes and their neighbors were analyzed. Finally, the genes were clustered, and the essential genes were introduced. RESULTS: After analyzing 159 genes of the network, FOS, IL6, TNF, TAC1, IL8, and KNG1 were identified as the essential genes. Further analysis revealed that 88 genes are directly connected to the central genes. More resolution led to ignoring TNF and IL8 and considering SCN-alpha and PAICS as additional critical nodes. CONCLUSION: Six critical genes related to pain were identified. They can be potentially considered as new drug targets. Further investigation is required to introduce the central genes as a pain killer.

Protein-Protein Interaction Analysis of Common Top Genes in Obsessive-Compulsive Disorder (OCD) and Schizophrenia: Towards New Drug Approach Obsessive-Compulsive disorder (OCD) and Schizophrenia Comorbidity Gene Analysis.

Comorbidty is common among psychiatric disorders including obsessive-compulsive disorder and schizophrenia with a high rate. Many studies suggested that the disorders may have same etiological bases. In this regard, shared pathways of glutamate, dopaminergic, and serotonin are the known ones. Here, the common significant genes are examined to understand the possible molecular origin of the disorders in terms of sequence and functional features. Exploring the underling mechanisms of OCD and schizophrenia is important to achieve a better treatment options. Methods of Cytoscape software following R statistical software were applied for this purpose. Needleman-Wunsch global alignment algorithm was used to determine pair-wise similarities followed by clustering methods, AGNES and PAM in R statistical programming software. The results indicate that SLC1A1, DRD2, DRD4, BDNF, ESR1, CDH2, GRIN2B, TNFa, GABBR1, and OLIG2 are significantly common for the two disorders and PPI network analysis showed the important key genes in the interaction profile. ESR1 (estrogen receptor α) as a key hub-bottleneck gene regulates many underling mechanisms of the brain. Application of global alignments indicates some of the genes with sequence similarities also elucidate similar biological terms.

Barrett's esophagus transits to a cancer condition via potential biomarkers.

AIM: In this study, the transcriptome profile of Barrett's esophagus (BE) was examined for identification potential related biomarkers in view of interacting charactering. BACKGROUND: Since BE is known as a precursor of esophageal cancer, the molecular studies of this condition could be essential. METHODS: Gene expression data of BE in comparison with normal cases, GSE34619 was retrieved from Gene Expression Omnibus. Differentially expressed genes (DEGs) were determined applying GEO2R online software. The DEGs then were analyzed in terms of centrality properties via constructing an interaction network. RESULTS: The data indicate that there are two sets of hub-bottlenecks panels with distinguishable values in BE. The first group shows that BE is very susceptible to develop cancer, and the second one implied on central characteristic of some DEGs as previously were also reported for BE pathogenicity. In addition, these genes are also implicated in cancer shift from certain conditions. CONCLUSION: On the whole, taking together these findings explain and support the cancerous origin of BE and introduced a panel of nominated biomarkers that could be more specific for BE rather than other types of esophageal problems. However, a complementary study to support this claim is suggested.

Prevalence of GBV-C among Iranian HBV positive patients using PCR-RFLP technique.

AIM: The aim of this study was to investigate the prevalence of GBV-C among Iranian HBV positive patients using PCR-RFLP technique. BACKGROUND: GBV-C was a member of flaviviridae family and recently propose to classify as members of a fourth genus in this family, named Pegivirus and suggest that at least one quarter of the world's population has been infected with this virus. GBV-C can be transmitted via the blood-borne route, although vertical and sexual transmission is very well documented. PATIENTS AND METHODS: 100 serum samples were collected from HBsAg positive patients in 2011-2012. RNA was extracted with Qiagene mini kit. cDNA was synthesized by Reverse Transcriptase method and amplified by Semi- nested PCR method. After designing specific primers, the semi nested PCR was optimized, then sequences of PCR products were analyzed with software such as neb cutter, and sites of restriction enzymes were determined and suitable enzymes were selected for RFLP (Restriction Fragment Length Polymorphism). RESULTS: PCR products were analyzed in 2% agarose gels containing ethidium bromide and were visualized with ultraviolet (UV) light. A 230 bp band was observed in comparison with 100 kb ladder; this band indicates our target gene of GBV-C genome have been isolate from serum samples. CONCLUSION: It seems that Co-infection of GBV-C and HBV are common and This method had acceptable sensitivity for detecting GBV-C and determining its genotype, and more affordable than the other techniques; so the results of this study showed the prevalence of GBV-C were 12 serums of 100 serums HBsAg positive in goal population and one sample from 12 GBV-C positive serums was genotype 3 and the others were genotype 2.