13 research outputs found

    The Role of Systems Biology in Deciphering Asthma Heterogeneity

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    Asthma is one of the most common and lifelong and chronic inflammatory diseases characterized by inflammation, bronchial hyperresponsiveness, and airway obstruction episodes. It is a heterogeneous disease of varying and overlapping phenotypes with many confounding factors playing a role in disease susceptibility and management. Such multifactorial disorders will benefit from using systems biology as a strategy to elucidate molecular insights from complex, quantitative, massive clinical, and biological data that will help to understand the underlying disease mechanism, early detection, and treatment planning. Systems biology is an approach that uses the comprehensive understanding of living systems through bioinformatics, mathematical, and computational techniques to model diverse high-throughput molecular, cellular, and the physiologic profiling of healthy and diseased populations to define biological processes. The use of systems biology has helped understand and enrich our knowledge of asthma heterogeneity and molecular basis; however, such methods have their limitations. The translational benefits of these studies are few, and it is recommended to reanalyze the different studies and omics in conjugation with one another which may help understand the reasons for this variation and help overcome the limitations of understanding the heterogeneity in asthma pathology. In this review, we aim to show the different factors that play a role in asthma heterogeneity and how systems biology may aid in understanding and deciphering the molecular basis of asthma

    Understanding the Role of Innate Immune Cells and Identifying Genes in Breast Cancer Microenvironment

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    The innate immune system is the first line of defense against invading pathogens and has a major role in clearing transformed cells, besides its essential role in activating the adaptive immune system. Macrophages, dendritic cells, NK cells, and granulocytes are part of the innate immune system that accumulate in the tumor microenvironment such as breast cancer. These cells induce inflammation in situ by secreting cytokines and chemokines that promote tumor growth and progression, in addition to orchestrating the activities of other immune cells. In breast cancer microenvironment, innate immune cells are skewed towards immunosuppression that may lead to tumor evasion. However, the mechanisms by which immune cells could interact with breast cancer cells are complex and not fully understood. Therefore, the importance of the mammary tumor microenvironment in the development, growth, and progression of cancer is widely recognized. With the advances of using bioinformatics and analyzing data from gene banks, several genes involved in NK cells of breast cancer individuals have been identified. In this review, we discuss the activities of certain genes involved in the cross-talk among NK cells and breast cancer. Consequently, altering tumor immune microenvironment can make breast tumors more responsive to immunotherapy

    Microbial metabolic genes crucial for S. aureus biofilms: an insight from re-analysis of publicly available microarray datasets

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    Bacterial biofilms are microbial lifestyles found in all environments. Up to 80% of human infections and 60-70% of hospital-acquired infections have a biofilm origin, with Staphylococcus aureus one of the leading causes of these infections. Microorganisms in biofilms exhibit significant antimicrobial resistance which poses important treatment challenges, hence the urgent need to identify novel antibiofilm strategies. Microbes form biofilms in response to various factors, and once these 3-dimentional structures form they are highly recalcitrant to removal. The switch from planktonic lifestyle to the biofilm protected mode of growth results in a phenotypic shift in the behavior of the microorganisms in terms of growth rate and gene expression. Given these changes, investigation of microbial gene expression and their modulation at different stages of biofilm maturation is needed to provide vital insight into the behaviour of biofilm cells. In this study, we analysed publicly available transcriptomic dataset of S. aureus biofilm at different stages of maturation to identify consistently upregulated genes irrespective of the biofilm maturation stage. Our reanalysis identified a total of 6 differentially expressed genes upregulated in both 48 and 144-h old S. aureus biofilms. Functional analysis revealed that these genes encode for proteins which play a role in key microbial metabolic pathways. However, these genes, as yet, are unrelated or poorly studied in the context of biofilm. Moreover, the findings of this in silico work, suggest that these genes may represent potential novel targets for the development of more effective antibiofilm strategies against S. aureus biofilm-associated infections

    The Role of Systems Biology in Deciphering Asthma Heterogeneity

    No full text
    Asthma is one of the most common and lifelong and chronic inflammatory diseases characterized by inflammation, bronchial hyperresponsiveness, and airway obstruction episodes. It is a heterogeneous disease of varying and overlapping phenotypes with many confounding factors playing a role in disease susceptibility and management. Such multifactorial disorders will benefit from using systems biology as a strategy to elucidate molecular insights from complex, quantitative, massive clinical, and biological data that will help to understand the underlying disease mechanism, early detection, and treatment planning. Systems biology is an approach that uses the comprehensive understanding of living systems through bioinformatics, mathematical, and computational techniques to model diverse high-throughput molecular, cellular, and the physiologic profiling of healthy and diseased populations to define biological processes. The use of systems biology has helped understand and enrich our knowledge of asthma heterogeneity and molecular basis; however, such methods have their limitations. The translational benefits of these studies are few, and it is recommended to reanalyze the different studies and omics in conjugation with one another which may help understand the reasons for this variation and help overcome the limitations of understanding the heterogeneity in asthma pathology. In this review, we aim to show the different factors that play a role in asthma heterogeneity and how systems biology may aid in understanding and deciphering the molecular basis of asthma

    Divulging a Pleiotropic Role of Succinate Receptor SUCNR1 in Renal Cell Carcinoma Microenvironment

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    The succinate receptor, SUCNR1, has been attributed to tumor progression, metastasis, and immune response modulation upon its activation via the oncometabolite succinate. Nonetheless, little is known about the prognostic relevance of SUCNR1 and its association with tumor immune infiltrates and microbiota in renal cell carcinoma (RCC). Herein, publicly available platforms including Human Protein Atlas, cBioPortal, TIMER2.0, and TISIDB were utilized to depict a divergent implication of SUCNR1 in the immune microenvironment of clear cell RCC (KIRC) and papillary RCC (KIRP); the two major subtypes of RCC. Our results showed that the SUCNR1 expression level was augmented in RCC compared to other solid cancers, yet with opposite survival rate predictions in RCC subtypes. Consequently, a higher expression level of SUCNR1 was associated with a good disease-specific survival rate (p = 5.797 × 10−5) in KIRC patients albeit a poor prognostic prediction in KIRP patients (p = 1.9282 × 10−3). Intriguingly, SUCNR1 was mainly correlated to immunomodulators and diverse immune infiltrates in KIRP. Additionally, the SUCNR1 was mostly associated with a repertoire of microbes including beneficial bacteria that likely influenced a better disease-specific survival rate in KIRC. Our findings illustrate a significant novel subtype-specific role of SUCNR1 in RCC which potentially modulates tumor immune infiltration and microbiome signature, hence altering the prognosis of cancer patients

    Differentially Expressed Genes of Natural Killer Cells Can Distinguish Rheumatoid Arthritis Patients from Healthy Controls

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    Rheumatoid arthritis (RA) is one of the most prevalent autoimmune diseases, while its molecular triggers are not fully understood. A few studies have shown that natural killer (NK) cells may play either a pathogenic or a protective role in RA. In this study, we sought to explore NK cell markers that could be plausibly used in evaluating the differences among healthy controls and RA patients. Publicly available transcriptome datasets from RA patients and healthy volunteers were analyzed, in order to identify differentially expressed genes (DEGs) between 1. different immune cells as compared to NK cells, and 2. NK cells of RA patients and healthy controls. The identified DEGs were validated using 16 healthy controls and 17 RA patients. Peripheral blood mononuclear cells (PBMCs) were separated by Ficoll density gradient method, while NK cells were isolated using RosetteSep technique. RNA was extracted and gene expression was assessed using RT-qPCR. All selected genes were differentially expressed in NK cells compared to PBMCs. CD56, CXCL16, PECAM-1, ITGB7, BTK, TLR10, and IL-1β were significantly upregulated, while CCL2, CCR4, RELA and IBTK were downregulated in the NK cells of RA patients when compared to healthy controls. Therefore, these NK specific genes might be used as promising biomarkers for RA diagnosis

    Understanding the Role of Innate Immune Cells and Identifying Genes in Breast Cancer Microenvironment

    No full text
    The innate immune system is the first line of defense against invading pathogens and has a major role in clearing transformed cells, besides its essential role in activating the adaptive immune system. Macrophages, dendritic cells, NK cells, and granulocytes are part of the innate immune system that accumulate in the tumor microenvironment such as breast cancer. These cells induce inflammation in situ by secreting cytokines and chemokines that promote tumor growth and progression, in addition to orchestrating the activities of other immune cells. In breast cancer microenvironment, innate immune cells are skewed towards immunosuppression that may lead to tumor evasion. However, the mechanisms by which immune cells could interact with breast cancer cells are complex and not fully understood. Therefore, the importance of the mammary tumor microenvironment in the development, growth, and progression of cancer is widely recognized. With the advances of using bioinformatics and analyzing data from gene banks, several genes involved in NK cells of breast cancer individuals have been identified. In this review, we discuss the activities of certain genes involved in the cross-talk among NK cells and breast cancer. Consequently, altering tumor immune microenvironment can make breast tumors more responsive to immunotherapy

    EXOC6 (Exocyst Complex Component 6) Is Associated with the Risk of Type 2 Diabetes and Pancreatic β-Cell Dysfunction

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    EXOC6 and EXOC6B (EXOC6/6B) components of the exocyst complex are involved in the secretory granule docking. Recently, EXOC6/6B were anticipated as a molecular link between dysfunctional pancreatic islets and ciliated lung epithelium, making diabetic patients more prone to severe SARS-CoV-2 complications. However, the exact role of EXOC6/6B in pancreatic β-cell function and risk of T2D is not fully understood. Herein, microarray and RNA-sequencing (RNA-seq) expression data demonstrated the expression of EXOC6/6B in human pancreatic islets. Expression of EXOC6/6B was not affected by diabetes status. Exploration of the using the translational human pancreatic islet genotype tissue-expression resource portal (TIGER) revealed three genetic variants (rs947591, rs2488071 and rs2488073) in the EXOC6 gene that were associated (p < 2.5 × 10−20) with the risk of T2D. Exoc6/6b silencing in rat pancreatic β-cells (INS1-832/13) impaired insulin secretion, insulin content, exocytosis machinery and glucose uptake without cytotoxic effect. A significant decrease in the expression Ins1, Ins1, Pdx1, Glut2 and Vamp2 was observed in Exoc6/6b-silenced cells at the mRNA and protein levels. However, NeuroD1, Gck and InsR were not influenced compared to the negative control. In conclusion, our data propose that EXOC6/6B are crucial regulators for insulin secretion and exocytosis machinery in β-cells. This study identified several genetic variants in EXOC6 associated with the risk of T2D. Therefore, EXOC6/6B could provide a new potential target for therapy development or early biomarkers for T2D

    Omics and Male Infertility: Highlighting the Application of Transcriptomic Data

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    Male infertility is a multifaceted disorder affecting approximately 50% of male partners in infertile couples. Over the years, male infertility has been diagnosed mainly through semen analysis, hormone evaluations, medical records and physical examinations, which of course are fundamental, but yet inefficient, because 30% of male infertility cases remain idiopathic. This dilemmatic status of the unknown needs to be addressed with more sophisticated and result-driven technologies and/or techniques. Genetic alterations have been linked with male infertility, thereby unveiling the practicality of investigating this disorder from the “omics” perspective. Omics aims at analyzing the structure and functions of a whole constituent of a given biological function at different levels, including the molecular gene level (genomics), transcript level (transcriptomics), protein level (proteomics) and metabolites level (metabolomics). In the current study, an overview of the four branches of omics and their roles in male infertility are briefly discussed; the potential usefulness of assessing transcriptomic data to understand this pathology is also elucidated. After assessing the publicly obtainable transcriptomic data for datasets on male infertility, a total of 1385 datasets were retrieved, of which 10 datasets met the inclusion criteria and were used for further analysis. These datasets were classified into groups according to the disease or cause of male infertility. The groups include non-obstructive azoospermia (NOA), obstructive azoospermia (OA), non-obstructive and obstructive azoospermia (NOA and OA), spermatogenic dysfunction, sperm dysfunction, and Y chromosome microdeletion. Findings revealed that 8 genes (LDHC, PDHA2, TNP1, TNP2, ODF1, ODF2, SPINK2, PCDHB3) were commonly differentially expressed between all disease groups. Likewise, 56 genes were common between NOA versus NOA and OA (ADAD1, BANF2, BCL2L14, C12orf50, C20orf173, C22orf23, C6orf99, C9orf131, C9orf24, CABS1, CAPZA3, CCDC187, CCDC54, CDKN3, CEP170, CFAP206, CRISP2, CT83, CXorf65, FAM209A, FAM71F1, FAM81B, GALNTL5, GTSF1, H1FNT, HEMGN, HMGB4, KIF2B, LDHC, LOC441601, LYZL2, ODF1, ODF2, PCDHB3, PDHA2, PGK2, PIH1D2, PLCZ1, PROCA1, RIMBP3, ROPN1L, SHCBP1L, SMCP, SPATA16, SPATA19, SPINK2, TEX33, TKTL2, TMCO2, TMCO5A, TNP1, TNP2, TSPAN16, TSSK1B, TTLL2, UBQLN3). These genes, particularly the above-mentioned 8 genes, are involved in diverse biological processes such as germ cell development, spermatid development, spermatid differentiation, regulation of proteolysis, spermatogenesis and metabolic processes. Owing to the stage-specific expression of these genes, any mal-expression can ultimately lead to male infertility. Therefore, currently available data on all branches of omics relating to male fertility can be used to identify biomarkers for diagnosing male infertility, which can potentially help in unravelling some idiopathic cases

    Genetic Variants of the PLCXD3 Gene Are Associated with Risk of Metabolic Syndrome in the Emirati Population

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    Phosphatidylinositol-specific phospholipase C X domain 3 (PLCXD3) has been shown to influence pancreatic β-cell function by disrupting insulin signaling. Herein, we investigated two genetic variants in the PLCXD3 gene in relation to type 2 diabetes (T2D) or metabolic syndrome (MetS) in the Emirati population. In total, 556 adult Emirati individuals (306 T2D and 256 controls) were genotyped for two PLCXD3 variants (rs319013 and rs9292806) using TaqMan genotyping assays. The frequency distribution of minor homozygous CC genotype of rs9292806 and GG genotype of rs319013 were significantly higher in subjects with MetS compared to Non-MetS (p < 0.01). The minor homozygous rs9292806-CC and rs319013-GG genotypes were significantly associated with increased risk of MetS (adj. OR 2.92; 95% CI 1.61–5.3; p < 0.001) (adj. OR 2.62; 95% CI 1.42–4.83; p = 0.002), respectively. However, no associations were detected with T2D. In healthy participants, the homozygous minor genotypes of both rs9292806 and rs319013 were significantly higher fasting glucose (adj. p < 0.005), HbA1c (adj. p < 0.005) and lower HDL-cholesterol (adj. p < 0.05) levels. Data from T2D Knowledge Portal database disclosed a nominal association of rs319013 and rs9292806 with T2D and components of MetS. Bioinformatics prediction analysis showed a deleterious effect of rs9292806 on the regulatory regions of PLCXD3. In conclusion, this study identifies rs319013 and rs9292806 variants of PLCXD3 as additional risk factors for MetS in the Emirati population
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