Biological network analysis with CentiScaPe: centralities and experimental dataset integration

RiceMetaSys: Drought-miR, a one-stop solution for drought responsive miRNAs-mRNA module in rice

MicroRNAs are key players involved in stress responses in plants and reports are available on the role of miRNAs in drought stress response in rice. This work reports the development of a database, RiceMetaSys: Drought-miR, based on the meta-analysis of publicly available sRNA datasets. From 28 drought stress-specific sRNA datasets, we identified 216 drought-responsive miRNAs (DRMs). The major features of the database include genotype-, tissue- and miRNA ID-specific search options and comparison of genotypes to identify common miRNAs. Co-localization of the DRMs with the known quantitative trait loci (QTLs), i.e., meta-QTL regions governing drought tolerance in rice pertaining to different drought adaptive traits, narrowed down this to 37 promising DRMs. To identify the high confidence target genes of DRMs under drought stress, degradome datasets and web resource on drought-responsive genes (RiceMetaSys: DRG) were used. Out of the 216 unique DRMs, only 193 had targets with high stringent parameters. Out of the 1081 target genes identified by Degradome datasets, 730 showed differential expression under drought stress in at least one accession. To retrieve complete information on the target genes, the database has been linked with RiceMetaSys: DRG. Further, we updated the RiceMetaSys: DRGv1 developed earlier with the addition of DRGs identified from RNA-seq datasets from five rice genotypes. We also identified 759 putative novel miRNAs and their target genes employing stringent criteria. Novel miRNA search has all the search options of known miRNAs and additionally, it gives information on their in silico validation features. Simple sequence repeat markers for both the miRNAs and their target genes have also been designed and made available in the database. Network analysis of the target genes identified 60 hub genes which primarily act through abscisic acid pathway and jasmonic acid pathway. Co-localization of the hub genes with the meta-QTL regions governing drought tolerance narrowed down this to 16 most promising DRGs. Database URL: http://14.139.229.201/RiceMetaSys_miRNA Updated database of RiceMetaSys URL: http://14.139.229.201/RiceMetaSysA/Drought/.

Uncovering the ferroptosis related mechanism of laduviglusib in the cell-type-specific targets of the striatum in Huntington's disease

Huntington's disease (HD) is a dominantly inherited neurodegenerative disorder featured by abnormal movements, arising from the extensive neuronal loss and glial dysfunction in the striatum. Although the causes and pathogenetic mechanisms of HD are well established, the development of disease-modifying pharmacological therapies for HD remains a formidable challenge. Laduviglusib has demonstrated neuroprotective effects through the enhancement of mitochondrial function in the striatum of HD animal models. Ferroptosis is a nonapoptotic form of cell death that occurs as a consequence of lethal iron-dependent lipid peroxidation and mitochondrial dysfunction. However, the ferroptosis-related mechanisms underlying the neuroprotective effects of laduviglusib in the striatum of HD patients remain largely uncharted. In this study, we leveraged single-nucleus RNA sequencing data obtained from the striatum of HD patients in stages 2-4 to identify differentially expressed genes within distinct cell-type. We subsequently integrated these differentially expressed genes of HD, laduviglusib target genes and ferroptosis-related genes to predict the ferroptosis-related mechanisms underpinning the neuroprotective effects of laduviglusib in HD patients. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses unveiled that the effects of laduviglusib on direct pathway striatal projection neurons (dSPNs) is mainly associated with Th17 cell differentiation pathways. Conversely, its impact on indirect pathway striatal projection neurons (iSPNs) extends to the Neurotrophin signaling pathway, FoxO signaling pathway, and reactive oxygen species pathway. In microglia, laduviglusib appears to contribute to HD pathology via mechanisms related to Th17 cell differentiation and the FoxO signaling pathway. Further, molecular docking results indicated favorable binding of laduviglusib with PARP1 (associated with dSPNs and iSPNs), SCD (associated with astrocytes), ALOX5 (associated with microglia), and HIF1A (associated with dSPNs, iSPNs, and microglia). In addition, the KEGG results suggest that laduviglusib may enhance mitochondrial function and protect against neuronal loss by targeting ferroptosis-related signaling pathways, particularly mediated by ALOX5 in microglia. These findings provide valuable insights into the potential mechanisms through which laduviglusib exerts its effects on distinct cell-types within the HD striatum.

Construction of protein-protein interaction network in sulfate-reducing bacteria: Unveiling of global response to Hg

Sulfate-reducing bacteria (SRB) play pivotal roles in the biotransformation of mercury (Hg). However, unrevealed global responses of SRB to Hg have restricted our understanding of details of Hg biotransformation processes. The absence of protein-protein interaction (PPI) network under Hg stimuli has been a bottleneck of proteomic analysis for molecular mechanisms of Hg transformation. This study constructed the first comprehensive PPI network of SRB in response to Hg, encompassing 67 connected nodes, 26 independent nodes, and 121 edges, covering 93% of differentially expressed proteins from both previous studies and this study. The network suggested that proteomic changes of SRB in response to Hg occurred globally, including microbial metabolism in diverse environments, carbon metabolism, nucleic acid metabolism and translation, nucleic acid repair, transport systems, nitrogen metabolism, and methyltransferase activity, partial of which could cover the known knowledge. Antibiotic resistance was the original response revealed by this network, providing insights into of Hg biotransformation mechanisms. This study firstly provided the foundational network for a comprehensive understanding of SRB's responses to Hg, convenient for exploration of potential targets for Hg biotransformation. Furthermore, the network indicated that Hg enhances the metabolic activities and modification pathways of SRB to maintain cellular activities, shedding light on the influences of Hg on the carbon, nitrogen, and sulfur cycles at the cellular level.

A Tiny Viral Protein, SARS-CoV-2-ORF7b: Functional Molecular Mechanisms

This study presents the interaction with the human host metabolism of SARS-CoV-2 ORF7b protein (43 aa), using a protein-protein interaction network analysis. After pruning, we selected from BioGRID the 51 most significant proteins among 2753 proven interactions and 1708 interactors specific to ORF7b. We used these proteins as functional seeds, and we obtained a significant network of 551 nodes via STRING. We performed topological analysis and calculated topological distributions by Cytoscape. By following a hub-and-spoke network architectural model, we were able to identify seven proteins that ranked high as hubs and an additional seven as bottlenecks. Through this interaction model, we identified significant GO-processes (5057 terms in 15 categories) induced in human metabolism by ORF7b. We discovered high statistical significance processes of dysregulated molecular cell mechanisms caused by acting ORF7b. We detected disease-related human proteins and their involvement in metabolic roles, how they relate in a distorted way to signaling and/or functional systems, in particular intra- and inter-cellular signaling systems, and the molecular mechanisms that supervise programmed cell death, with mechanisms similar to that of cancer metastasis diffusion. A cluster analysis showed 10 compact and significant functional clusters, where two of them overlap in a Giant Connected Component core of 206 total nodes. These two clusters contain most of the high-rank nodes. ORF7b acts through these two clusters, inducing most of the metabolic dysregulation. We conducted a co-regulation and transcriptional analysis by hub and bottleneck proteins. This analysis allowed us to define the transcription factors and miRNAs that control the high-ranking proteins and the dysregulated processes within the limits of the poor knowledge that these sectors still impose.

Interactome Analysis of Visceral Adipose Tissue Elucidates Gene Regulatory Networks and Novel Gene Candidates in Obesity

Objective

Visceral adiposity is associated with increased proinflammatory activity, insulin resistance, diabetes risk and mortality rate. Numerous individual genes have been associated with obesity, but studies investigating gene-regulatory networks in human visceral obesity are lacking.

Methods

We analyzed gene-regulatory networks in human visceral adipose tissue (VAT) from 48 obese and 11 non-obese Chinese subjects using gene co-expression and network construction with RNA-sequencing data. We also conducted RNA interference-based tests on selected genes for adipocyte differentiation effects.

Results

A scale-free gene co-expression network was constructed from 360 differentially expressed genes between obese and non-obese VAT (absolute log fold-change >1, FDR<0.05) with edge probability >0.8. Gene regulatory network analysis identified candidate transcription factors associated with differentially expressed genes. Fifteen subnetworks (communities) displayed altered connectivity patterns between obese and non-obese networks. Genes in pro-inflammatory pathways showed increased network connectivities in obese VAT whereas the oxidative phosphorylation pathway displayed reduced connections (enrichment FDR<0.05). Functional screening via RNA interference identified SOX30 and OSBPL3 as potential network-derived gene candidates influencing adipocyte differentiation.

Conclusions

This interactome-based approach highlights the network architecture, identifies novel candidate genes, and leads to new hypotheses regarding network-assisted gene regulation in obese vs. non-obese VAT.What is already known about this subject?: Visceral adipose tissue (VAT) is associated with increased levels of proinflammatory activity, insulin resistance, diabetes risk and mortality rate.Gene expression studies have identified candidate genes associated with proinflammatory function in VAT.What are the new findings in your manuscript?: Using integrative network-science, we identified co-expression and gene regulatory networks that are differentially regulated in VAT samples from subjects with and without obesityWe used functional testing (adipocyte differentiation) to validate a subset of novel candidate genes with minimal prior reported associations to obesityHow might your results change the direction of research or the focus of clinical practice: Network biology-based investigation provides a new avenue to our understanding of gene function in visceral adiposityFunctional validation screen allows for the identification of novel gene candidates that may be targeted for the treatment of adipose tissue dysfunction in obesity.

Improved high-quality reference genome of red drum facilitates the processes of resistance-related gene exploration

Sciaenops ocellatus is among the most important artificially introduced farmed fish across 11 countries and regions. However, the frequent occurrence of extreme weather events and breeding escapes have placed great pressure on local marine biodiversity and ecosystems. We reported the de novo assembly and annotation with a contig N50 of 28.30 Mb using PacBio HiFi sequencing and Hi-C technologies, which resulted in a 283-fold increase in contig N50 length and improvement in continuity and quality in complex repetitive region for S. ocellatus compared to the previous version. In total, 257.36 Mb of repetitive sequences accounted for 35.48% of the genome, and 22,845 protein-coding genes associated with a BUSCO value of 98.32%, were identified by genome annotation. Moreover, 54 hub genes rapidly responding to hypoosmotic stress were identified by WGCNA. The high-quality chromosome-scale S. ocellatus genome and candidate resistance-related gene sets will not only provide a genomic basis for genetic improvement via molecular breeding, but will also lay an important foundation for investigating the molecular regulation of rapid responses to stress.

Current trends of host-pathogen relationship in shrimp infectious disease via computational protein-protein interaction: A bibliometric analysis

Protein-protein interactions (PPIs) are essential for understanding cell physiology in normal and pathological conditions, as they might involve in all cellular processes. PPIs have been widely used to elucidate the pathobiology of human and plant diseases. Therefore, they can also be used to unveil the pathobiology of infectious diseases in shrimp, which is one of the high-risk factors influencing the success or failure of shrimp production. PPI network analysis, specifically host-pathogen PPI (HP-PPI), provides insights into the molecular interactions between the shrimp and pathogens. This review quantitatively analyzed the research trends within this field through bibliometric analysis using specific keywords, countries, authors, organizations, journals, and documents. This analysis has screened 206 records from the Scopus database for determining eligibility, resulting in 179 papers that were retrieved for bibliometric analysis. The analysis revealed that China and Thailand were the driving forces behind this specific field of research and frequently collaborated with the United States. Aquaculture and Diseases of Aquatic Organisms were the prominent sources for publications in this field. The main keywords identified included "white spot syndrome virus," "WSSV," and "shrimp." We discovered that studies on HP-PPI are currently quite scarce. As a result, we further discussed the significance of HP-PPI by highlighting various approaches that have been previously adopted. These findings not only emphasize the importance of HP-PPI but also pave the way for future researchers to explore the pathogenesis of infectious diseases in shrimp. By doing so, preventative measures and enhanced treatment strategies can be identified.

Exploration of potential targets and mechanisms of naringenin in the treatment of nonalcoholic fatty liver disease through network pharmacology

OBJECTIVE

This study aimed to use network pharmacology to investigate the molecular mechanisms and potential targets of naringenin (NR) for nonalcoholic fatty liver disease (NAFLD) treatment to offer new drug development ideas.

METHODS

The structure and compound information of NR were obtained from PubChem and the traditional Chinese medicine system pharmacology database and analysis platform. The traditional Chinese medicine system pharmacology database and analysis platform Database, Comparative Toxicogenomics Database and Encyclopedia of Traditional Chinese Medicine Database were then used to predict the related targets of NR. Online mendelian inheritance in man, Disgenet, Gene cards, The therapeutic target database and Drug bank were used to screen NAFLD targets, and the intersection analysis was performed with the targets of NR active components to obtain the targets of NR in the treatment of NAFLD. The protein-protein interaction network of therapeutic targets was constructed by protein-protein interaction networks functional enrichment analysis 11.0, and gene ontology (GO) functional enrichment analysis and Kyoto encyclopedia of genes and genomes pathway enrichment analysis of therapeutic targets was performed by Metascape platform.

RESULTS

In this study, 171 NR targets and 1748 potential targets of NAFLD were screened, and 89 crossover targets and 16 core targets were screened and finally obtained. A total of 176 GO items were obtained by GO enrichment analysis (P < .05), including 389 biological process, 6 cell composition and 30 molecular function. A total of 137 signaling pathways were obtained by Kyoto encyclopedia of genes and genomes pathway enrichment and screening (P < .05). The core targets of NR in the treatment of NAFLD are TP53, CASP3, PRKCA, AKT1, RELA, PPARG, NCOA2, CYP1A1, ESR1, MAPK3, STAT3, JAK1, MAPK1, TNF, PPARA and PRKCB. Enrichment analysis showed that NR mainly involved in biological processes such as cellular response to nitrogen compound, regulation of miRNA transcription and negative regulation of miRNA-mediated gene silencing. It regulates Hepatitis B, Lipid and atherosclerosis, cytomegalovirus infection, Hepatitis C, AGE-RAGE signaling pathway in diabetic patients complications and other ways play a role in the treatment of NAFLD.

CONCLUSIONS

The therapeutic effect of NR on NAFLD has the characteristics of multi-targets and multi-pathways, which provides a preliminary theoretical basis for clinical trials and the development of new drugs.

Differentially Expressed Genes, miRNAs and Network Models: A Strategy to Shed Light on Molecular Interactions Driving HNSCC Tumorigenesis

Head and neck squamous cell carcinoma (HNSCC) is among the most common cancer worldwide, accounting for hundreds thousands deaths annually. Unfortunately, most patients are diagnosed in an advanced stage and only a percentage respond favorably to therapies. To help fill this gap, we hereby propose a retrospective in silico study to shed light on gene-miRNA interactions driving the development of HNSCC. Moreover, to identify topological biomarkers as a source for designing new drugs. To achieve this, gene and miRNA profiles from patients and controls are holistically reevaluated using protein-protein interaction (PPI) and bipartite miRNA-target networks. Cytoskeletal remodeling, extracellular matrix (ECM), immune system, proteolysis, and energy metabolism have emerged as major functional modules involved in the pathogenesis of HNSCC. Of note, the landscape of our findings depicts a concerted molecular action in activating genes promoting cell cycle and proliferation, and inactivating those suppressive. In this scenario, genes, including VEGFA, EMP1, PPL, KRAS, MET, TP53, MMPs and HOXs, and miRNAs, including mir-6728 and mir-99a, emerge as key players in the molecular interactions driving HNSCC tumorigenesis. Despite the heterogeneity characterizing these HNSCC subtypes, and the limitations of a study pointing to relationships that could be context dependent, the overlap with previously published studies is encouraging. Hence, it supports further investigation for key molecules, both those already and not correlated to HNSCC.

Integration of Omics Data and Network Models to Unveil Negative Aspects of SARS-CoV-2, from Pathogenic Mechanisms to Drug Repurposing

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COVID-19 health emergency, affecting and killing millions of people worldwide. Following SARS-CoV-2 infection, COVID-19 patients show a spectrum of symptoms ranging from asymptomatic to very severe manifestations. In particular, bronchial and pulmonary cells, involved at the initial stage, trigger a hyper-inflammation phase, damaging a wide range of organs, including the heart, brain, liver, intestine and kidney. Due to the urgent need for solutions to limit the virus' spread, most efforts were initially devoted to mapping outbreak trajectories and variant emergence, as well as to the rapid search for effective therapeutic strategies. Samples collected from hospitalized or dead COVID-19 patients from the early stages of pandemic have been analyzed over time, and to date they still represent an invaluable source of information to shed light on the molecular mechanisms underlying the organ/tissue damage, the knowledge of which could offer new opportunities for diagnostics and therapeutic designs. For these purposes, in combination with clinical data, omics profiles and network models play a key role providing a holistic view of the pathways, processes and functions most affected by viral infection. In fact, in addition to epidemiological purposes, networks are being increasingly adopted for the integration of multiomics data, and recently their use has expanded to the identification of drug targets or the repositioning of existing drugs. These topics will be covered here by exploring the landscape of SARS-CoV-2 survey-based studies using systems biology approaches derived from omics data, paying particular attention to those that have considered samples of human origin.

microRNA-96 targets the INS/AKT/GLUT4 signaling axis: Association with and effect on diabetic retinopathy

Background

miR-96-5p is a highly expressed microRNA in the retina of subjects with diabetes. The INS/AKT/GLUT4 signaling axis is the main cell signaling pathway of glucose uptake in cells. Here, we investigated the role of miR-96-5p in this signaling pathway.

Methods

Expression levels of miR-96-5p and its target genes were measured under high glucose conditions, in the retina of streptozotocin-induced diabetic mice, in the retina of AAV-2-eGFP-miR-96 or GFP intravitreal injected mice and in the retina of human donors with diabetic retinopathy (DR). MTT, wound healing, tube formation, Western blot, TUNEL, angiogenesis assays and hematoxylin-eosin staining of the retinal sections were performed.

Results

miR-96-5p expression was increased under high glucose conditions in mouse retinal pigment epithelial (mRPE) cells, in the retina of mice receiving AAV-2 carrying miR-96 and STZ-treated mice. Expression of the miR-96-5p target genes related to the INS/AKT/GLUT4 signaling pathway was reduced following miR-96-5p overexpression. mmu-miR-96-5p expression decreased cell proliferation and thicknesses of retinal layers. Cell migration, tube formation, vascular length, angiogenesis, and TUNEL-positive cells were increased.

Conclusions

In in vitro and in vivo studies and in human retinal tissues, miR-96-5p regulated the expression of the PIK3R1, PRKCE, AKT1, AKT2, and AKT3 genes in the INS/AKT axis and some genes involved in GLUT4 trafficking, such as Pak1, Snap23, RAB2a, and Ehd1. Because disruption of the INS/AKT/GLUT4 signaling axis causes advanced glycation end product accumulation and inflammatory responses, the inhibition of miR-96-5p expression could ameliorate DR.

Reduced G protein signaling despite impaired internalization and β-arrestin recruitment in patients carrying a CXCR4Leu317fsX3 mutation causing WHIM syndrome

WHIM syndrome is an inherited immune disorder caused by an autosomal dominant heterozygous mutation in CXCR4. The disease is characterized by neutropenia/leukopenia (secondary to retention of mature neutrophils in bone marrow), recurrent bacterial infections, treatment-refractory warts, and hypogammaglobulinemia. All mutations reported in WHIM patients lead to the truncations in the C-terminal domain of CXCR4, R334X being the most frequent. This defect prevents receptor internalization and enhances both calcium mobilization and ERK phosphorylation, resulting in increased chemotaxis in response to the unique ligand CXCL12. Here, we describe 3 patients presenting neutropenia and myelokathexis, but normal lymphocyte count and immunoglobulin levels, carrying what we believe to be a novel Leu317fsX3 mutation in CXCR4, leading to a complete truncation of its intracellular tail. The analysis of the L317fsX3 mutation in cells derived from patients and in vitro cellular models reveals unique signaling features in comparison with R334X mutation. The L317fsX3 mutation impairs CXCR4 downregulation and β-arrestin recruitment in response to CXCL12 and reduces other signaling events - including ERK1/2 phosphorylation, calcium mobilization, and chemotaxis - all processes that are typically enhanced in cells carrying the R334X mutation. Our findings suggest that, overall, the L317fsX3 mutation may be causative of a form of WHIM syndrome not associated with an augmented CXCR4 response to CXCL12.

Circular RNA Expression Signatures Provide Promising Diagnostic and Therapeutic Biomarkers for Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is a known hematologic malignancy associated with a growing incidence and post-treatment relapse. Hence, finding a reliable diagnostic biomarker for CLL is crucial. Circular RNAs (circRNAs) represent a new class of RNA involved in many biological processes and diseases. This study aimed to define a circRNA-based panel for the early diagnosis of CLL. To this point, the list of the most deregulated circRNAs in CLL cell models was retrieved using bioinformatic algorithms and applied to the verified CLL patients' online datasets as the training cohort (n = 100). The diagnostic performance of potential biomarkers represented in individual and discriminating panels, was then analyzed between CLL Binet stages and validated in individual sample sets I (n = 220) and II (n = 251). We also estimated the 5-year overall survival (OS), introduced the cancer-related signaling pathways regulated by the announced circRNAs, and provided a list of possible therapeutic compounds to control the CLL. These findings show that the detected circRNA biomarkers exhibit better predictive performance compared to current validated clinical risk scales, and are applicable for the early detection and treatment of CLL.

The Protein Network in Subcutaneous Fat Biopsies from Patients with AL Amyloidosis: More Than Diagnosis?

AL amyloidosis is caused by the misfolding of immunoglobulin light chains leading to an impaired function of tissues and organs in which they accumulate. Due to the paucity of -omics profiles from undissected samples, few studies have addressed amyloid-related damage system wide. To fill this gap, we evaluated proteome changes in the abdominal subcutaneous adipose tissue of patients affected by the AL isotypes κ and λ. Through our retrospective analysis based on graph theory, we have herein deduced new insights representing a step forward from the pioneering proteomic investigations previously published by our group. ECM/cytoskeleton, oxidative stress and proteostasis were confirmed as leading processes. In this scenario, some proteins, including glutathione peroxidase 1 (GPX1), tubulins and the TRiC complex, were classified as biologically and topologically relevant. These and other results overlap with those already reported for other amyloidoses, supporting the hypothesis that amyloidogenic proteins could induce similar mechanisms independently of the main fibril precursor and of the target tissues/organs. Of course, further studies based on larger patient cohorts and different tissues/organs will be essential, which would be a key point that would allow for a more robust selection of the main molecular players and a more accurate correlation with clinical aspects.

Trojan-horse silk fibroin nanocarriers loaded with a re-call antigen to redirect immunity against cancer

BACKGROUND

The current challenge for immunotherapies is to generate effective antitumor immunity. Since tumor immune escape mechanisms do not impact pre-existing and consolidated immune responses, we tested the hypothesis of redirecting a pregenerated immunity to cancer: to recall a non-tumor antigen response against the tumor, silk fibroin nanoparticles (SFNs) have been selected as 'Trojan-horse' carriers, promoting the antigen uptake by the tumor cells.

METHODS

SFNs have been loaded with either ovalbumin (OVA) or CpG oligonucleotide (CpG) as antigen or adjuvant, respectively. In vitro uptake of SFNs by tumor (B16/F10 melanoma and MB49 bladder cancer) or dendritic cells, as well as the presence of OVA-specific T cells in splenic and tumor-infiltrating lymphocytes, were assessed by cytometric analyses. Proof-of-concept of in vivo efficacy was achieved in an OVA-hyperimmune B16/F10 murine melanoma model: SFNs-OVA or SFNs-CpG were injected, separately or in association, into the subcutaneous peritumoral area. Cancer dimensions/survival time were monitored, while, at the molecular level, system biology approaches based on graph theory and experimental proteomic data were performed.

RESULTS

SFNs were efficiently in vitro uptaken by cancer and dendritic cells. In vivo peritumor administration of SFNs-OVA redirected OVA-specific cytotoxic T cells intratumorally. Proteomics and systems biology showed that peritumoral treatment with either SFNs-OVA or SFNs-CpG dramatically modified tumor microenvironment with respect to the control (CTR), mainly involving functional modules and hubs related to angiogenesis, inflammatory mediators, immune function, T complex and serpins expression, redox homeostasis, and energetic metabolism. Both SFNs-OVA and SFNs-CpG significantly delayed melanoma growth/survival time, and their effect was additive.

CONCLUSIONS

Both SFNs-OVA and SFNs-CpG induce effective anticancer response through complementary mechanisms and show the efficacy of an innovative active immunotherapy approach based on the redirection of pre-existing immunity against cancer cells. This approach could be universally applied for solid cancer treatments if translated into the clinic using re-call antigens of childhood vaccination.

Systems biology network reveals the correlation between COX-2 expression and Ch 7q copy number alterations in Ch 11q-deleted pediatric neuroblastoma tumors

Tumor-associated inflammation and chromosomal aberrations can play crucial roles in cancer development and progression. In neuroblastoma (NB), the enzyme cyclooxygenase-2 (COX-2) is associated with copy number alterations on the long arm of chromosome 11 (Ch 11q), defining an aggressive disease subset. This retrospective study included formalin-fixed paraffin-embedded tumor samples collected from nine patients during diagnosis at the pediatric Pequeno Principe Hospital, Curitiba, PR, Brazil, and post-chemotherapy (CT). COX-2 expression was evaluated using immunohistochemistry and correlated with the genome profile of paired pre- and post-CT samples, determined by array comparative genomic hybridization. A systems biology approach elucidated the PTGS2 network interaction. The results showed positive correlations between pre-CT Ch 7q gain and COX-2 expression (ρ = 0.825; p-value = 0.006) and negative correlations between Ch 7q gain and Ch 11q deletion (ρ = −0.919; p-value = 0.0005). Three samples showed Ch 11q deletion and Ch 7q gain. Network analysis identified a direct connection between CAV-1 (Ch 7q) and COX-2 in NB tumors and highlighted the connection between amplified genes in Ch 7q and deleted ones in 11q. The identification of hub-bottleneck-switch genes provides new biological insights into this connection between NB, tumorigenesis, and inflammation.

Exploration of potential targets and mechanisms of Naringenin in treating autism spectrum disorder via network pharmacology and molecular docking

Naringenin (NR) is a kind of flavonoid which plays a great role in the treatment of autism spectrum disorder (ASD). However, the underlying mechanism of NR in treating ASD still remains unclear. This study used network pharmacology and molecular docking to examine the potential targets and pharmacological mechanism of NR on ASD. Targets related to NR were screened from Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP), Encyclopedia of Traditional Chinese Medicine Database (ETCM), Traditional Chinese Medicine Integrated Database (TCMID), PharmaMapper database, and targets related to ASD were screened from Online Mendelian Inheritance In Man (OMIM), Disgenet, GeneCards, Therapeutic Target Database (TTD), Drugbank, and ETCM. Screened of the intersected gene targets. Then, we used the protein-protein interaction (PPI) networks to construct a PPI network and used Network Analyzer plug-in to perform topological analysis to screen out the core target. We used Metascape platform to perform gene ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and used Chem draw, Pymol, AutoDock 1.5.6 software for molecular docking verification with core targets. A total of 149 targets of NR and 1594 potential targets of ASD were screened, and 43 intersected targets and 8 key targets were obtained and screened. A total of 176 GO items were obtained by GO enrichment analysis (P < .05), 153 entries on biological process (BP), 12 entries on BP and 11entries on cell composition (CC) were included. A total of 100 signaling pathways were obtained by KEGG pathway enrichment screening (P < .05).The pathways that are closely related to the pathogenesis of ASD are estrogen signaling, thyroid hormone signaling pathway, prolactin signaling pathway, and endocrine resistance pathway. Molecular docking results showed that NR had the best docking activity with the core target CASP3, and had good binding ability with AKT1, ESR1, ACTB and MAPK3. Taken together, our findings support that NR exerts therapeutic effects on ASD with multi-target, and multi-pathway characteristics, which provides a preliminary theoretical basis for clinical trials. The mechanism of anti-oxidative stress response, anti-apoptosis, regulation of cell growth and metabolism, anti-inflammatory, balance hormone levels may be important for the therapeutic effect.

Resistance Training Modulates Reticulum Endoplasmic Stress, Independent of Oxidative and Inflammatory Responses, in Elderly People

Aging is related to changes in the redox status, low-grade inflammation, and decreased endoplasmic reticulum unfolded protein response (UPR). Exercise has been shown to regulate the inflammatory response, balance redox homeostasis, and ameliorate the UPR. This work aimed to investigate the effects of resistance training on changes in the UPR, oxidative status, and inflammatory responses in peripheral blood mononuclear cells of elderly subjects. Thirty elderly subjects volunteered to participate in an 8-week resistance training program, and 11 youth subjects were included for basal assessments. Klotho, heat shock protein 60 (HSP60), oxidative marker expression (catalase, glutathione, lipid peroxidation, nuclear factor erythroid 2-related factor 2, protein carbonyls, reactive oxygen species, and superoxide dismutase 1 and 2), the IRE1 arm of UPR, and TLR4/TRAF6/pIRAK1 pathway activation were evaluated before and following training. No changes in the HSP60 and Klotho protein content, oxidative status markers, and TLR4/TRAF6/pIRAK1 pathway activation were found with exercise. However, an attenuation of the reduced pIRE1/IRE1 ratio was observed following training. Systems biology analysis showed that a low number of proteins (RPS27A, SYVN1, HSPA5, and XBP1) are associated with IRE1, where XBP1 and RPS27A are essential nodes according to the centrality analysis. Additionally, a gene ontology analysis confirms that endoplasmic reticulum stress is a key mechanism modulated by IRE1. These findings might partially support the modulatory effect of resistance training on the endoplasmic reticulum in the elderly.

A Systems Biology Approach on the Regulatory Footprint of Human Endogenous Retroviruses (HERVs)

Human endogenous retroviruses (HERVs) are a family of endogenous retroviruses that comprise the ~8.93% of the human genome sequence, with a high proportion being human specific. The recent expansion of repeated HERV sequences has offered a framework for genetic and epigenetic innovation. In the current report, a systematic approach is implemented to catalogue regulatory elements within HERVs, as a roadmap to potential functions of HERV sequences in gene networks. ENCODE Project has offered a wealth of epigenetic data based on omics technologies. I analyzed the presence of HERV sequences on consensus cis-regulatory elements (cCREs) from ENCODE data. On the one side, HERVs are in 1 out of 9 cCREs (>100.000 cCREs in total), dispersed within the genome and present in cis-regulatory regions of ~81% of human genes, as calculated following gene enrichment analysis. On the other side, promoter-associated HERV cCREs are present adjacent to (in a 200 bp window) the transcription start sites of 256 human genes. Regulatory network production, followed by centrality analysis led to the discovery of 90 core genes containing HERV-associated promoters. Pathway analysis on the core network genes and their immediate neighbors revealed a regulatory footprint that, among others, is associated with inflammation, chemokine signaling and response to viral infection. Collectively, these results support the concept that the expansion of regulatory sequences derived from HERVs is critical for epigenetic innovation that may have wired together genes into novel transcriptional networks with critical roles in cellular physiology and pathology.

Microvesicles released from activated CD4+ T cells alter microvascular endothelial cell function

BACKGROUND

Microvesicles are vesicles shed by plasma membranes following cell activation and apoptosis. The role of lymphocyte-derived microvesicles in endothelial function remains poorly understood.

METHODS

CD4⁺ T cells isolated from peripheral blood of healthy human donors were stimulated using anti-CD3/anti-CD28-coated beads. Proteomic profiling of microvesicles was performed using linear discriminant analysis (LDA) from activated T cells (MV.Act) and nonactivated T cells (MV.NAct). In addition, data processing analysis was performed using MaxQUANT workflow. Differentially expressed proteins found in MV.Act or MV.NAct samples with identification frequency = 100%, which were selected by both LDA (p < .01) and MaxQUANT (p < .01) workflows, were defined as "high-confidence" differentially expressed proteins. Functional effects of MV.Act on human primary microvascular endothelial cells were analysed.

RESULTS

T cells released large amounts of microvesicles upon stimulation. Proteomic profiling of microvesicles using LDA identified 2279 proteins (n = 2110 and n = 851 proteins in MV.Act and MV.NAct, respectively). Protein-protein interaction network models reconstructed from both differentially expressed proteins (n = 594; LDA p ≤ .01) and "high-confidence" differentially expressed proteins (n = 98; p ≤ .01) revealed that MV.Act were enriched with proteins related to immune responses, protein translation, cytoskeleton organisation and TNFα-induced apoptosis. For instance, MV.Act were highly enriched with IFN-γ, a key proinflammatory pathway related to effector CD4⁺ T cells. Endothelial cell incubation with MV.Act induced superoxide generation, apoptosis, endothelial wound healing impairment and endothelial monolayer barrier disruption.

CONCLUSIONS

T cell receptor-mediated activation of CD4⁺ T cells stimulates the release of microvesicles enriched with proteins involved in immune responses, inflammation and apoptosis. T cell-derived microvesicles alter microvascular endothelial function and barrier permeability, potentially promoting tissue inflammation.

Downregulation of MicroRNA-1 and Its Potential Molecular Mechanism in Nasopharyngeal Cancer: An Investigation Combined with In Silico and In-House Immunohistochemistry Validation

Background

This study was aimed at elucidating the molecular biological mechanisms of microRNA-1 (miR-1) in nasopharyngeal carcinoma (NPC).

Method

In this study, we performed a pooled analysis of miR-1 expression data derived from public databases, such as GEO, ArrayExpress, TCGA, and GTEx. The miRWalk 2.0 database, combined with the mRNA microarray datasets, was used to screen the target genes, and the genes were then subjected to Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis using the DAVID 6.8 database. We then used the STRING 11.0 database and Cytoscape 3.80 software to construct a protein-protein interaction (PPI) network for screening hub genes. Immunohistochemistry (IHC) was further used to validate the expression of hub genes. Finally, potential therapeutic agents for NPC were screened by the Connectivity Map (cMap) database.

Results

Pooled analysis showed that miR-1 expression was significantly decreased in NPC (SMD = −0.57; P < 0.05). The summary receiver operating characteristic curve suggested that miR-1 had a good ability to distinguish cancerous tissues from noncancerous tissues (AUC = 0.78). The results of GO analysis focused on mitotic nuclear division, DNA replication, cell division, cell adhesion, extracellular space, kinesin complex, and extracellular matrix (ECM) structural constituent. The KEGG analysis suggested that the target genes played a role in key signaling pathways, such as cell cycle, focal adhesion, cytokine-cytokine receptor interaction, ECM-receptor interaction, and PI3K/Akt signaling pathway. The PPI network suggested that cyclin-dependent kinase 1 (CDK1) was the hub gene, and the CDK1 protein was subsequently confirmed to be significantly upregulated in NPC tissues by IHC. Finally, potential therapeutic drugs, such as masitinib, were obtained by the cMap database.

Conclusion

miR-1 may play a vital part in NPC tumorigenesis and progression by regulating focal adhesion kinase to participate in cell mitosis, regulating ECM degradation, and affecting the PI3K/Akt signaling pathway. miR-1 has the potential to be a therapeutic target for NPC.

Presence of a Mitovirus Is Associated with Alteration of the Mitochondrial Proteome, as Revealed by Protein–Protein Interaction (PPI) and Co-Expression Network Models in Chenopodium quinoa Plants

Simple Summary

Plants often harbor persistent plant virus infection transmitted only vertically through seeds, resulting in no obvious symptoms (cryptic infections). Several studies have shown that such cryptic infections provide resilience against abiotic (and biotic) stress. We have recently discovered a new group of cryptic plant viruses infecting mitochondria (plant mitovirus). Mitochondria are cellular organelles displaying a pivotal role in protecting cells from the stress of nature . Here, we look at the proteomic alterations caused by the mitovirus cryptic infection of Chenopodium quinoa by Systems Biology approaches allowing one to evaluate data at holistic level. Quinoa is a domesticated plant species with many exciting features of abiotic stress resistance, and it is distinguished by its exceptional nutritional characteristics, such as the content and quality of proteins, minerals, lipids, and tocopherols. These features determined the growing interest for the quinoa crop by the scientific community and international organizations since they provide opportunities to produce high-value grains in arid, high-salt and high-UV agroecological environments. We discovered that quinoa lines hosting mitovirus activate some metabolic processes that might help them face drought. These findings present a new perspective for breeding crop plants through the augmented genome provided by accessory cryptic viruses to be investigated in the future.

Abstract

Plant mitoviruses belong to Mitoviridae family and consist of positive single-stranded RNA genomes replicating exclusively in host mitochondria. We previously reported the biological characterization of a replicating plant mitovirus, designated Chenopodium quinoa mitovirus 1 (CqMV1), in some Chenopodium quinoa accessions. In this study, we analyzed the mitochondrial proteome from leaves of quinoa, infected and not infected by CqMV1. Furthermore, by protein–protein interaction and co-expression network models, we provided a system perspective of how CqMV1 affects mitochondrial functionality. We found that CqMV1 is associated with changes in mitochondrial protein expression in a mild but well-defined way. In quinoa-infected plants, we observed up-regulation of functional modules involved in amino acid catabolism, mitochondrial respiratory chain, proteolysis, folding/stress response and redox homeostasis. In this context, some proteins, including BCE2 (lipoamide acyltransferase component of branched-chain alpha-keto acid dehydrogenase complex), DELTA-OAT (ornithine aminotransferase) and GR-RBP2 (glycine-rich RNA-binding protein 2) were interesting because all up-regulated and network hubs in infected plants; together with other hubs, including CAT (catalase) and APX3 (L-ascorbate peroxidase 3), they play a role in stress response and redox homeostasis. These proteins could be related to the higher tolerance degree to drought we observed in CqMV1-infected plants. Although a specific causative link could not be established by our experimental approach at this stage, the results suggest a new mechanistic hypothesis that demands further in-depth functional studies.

Systems biology and machine learning approaches identify drug targets in diabetic nephropathy

Diabetic nephropathy (DN), the leading cause of end-stage renal disease, has become a massive global health burden. Despite considerable efforts, the underlying mechanisms have not yet been comprehensively understood. In this study, a systematic approach was utilized to identify the microRNA signature in DN and to introduce novel drug targets (DTs) in DN. Using microarray profiling followed by qPCR confirmation, 13 and 6 differentially expressed (DE) microRNAs were identified in the kidney cortex and medulla, respectively. The microRNA-target interaction networks for each anatomical compartment were constructed and central nodes were identified. Moreover, enrichment analysis was performed to identify key signaling pathways. To develop a strategy for DT prediction, the human proteome was annotated with 65 biochemical characteristics and 23 network topology parameters. Furthermore, all proteins targeted by at least one FDA-approved drug were identified. Next, mGMDH-AFS, a high-performance machine learning algorithm capable of tolerating massive imbalanced size of the classes, was developed to classify DT and non-DT proteins. The sensitivity, specificity, accuracy, and precision of the proposed method were 90%, 86%, 88%, and 89%, respectively. Moreover, it significantly outperformed the state-of-the-art (P-value ≤ 0.05) and showed very good diagnostic accuracy and high agreement between predicted and observed class labels. The cortex and medulla networks were then analyzed with this validated machine to identify potential DTs. Among the high-rank DT candidates are Egfr, Prkce, clic5, Kit, and Agtr1a which is a current well-known target in DN. In conclusion, a combination of experimental and computational approaches was exploited to provide a holistic insight into the disorder for introducing novel therapeutic targets.

Alterations in T-Cell Transcription Factors and Cytokine Gene Expression in Late-Onset Alzheimer's Disease

BACKGROUND

Late-onset Alzheimer's disease (LOAD) is associated with many environmental and genetic factors. The effect of systemic inflammation on the pathogenesis of neurodegenerative diseases such as AD has been strongly suggested. T helper cells (Th) are one of the important components of the immune system and can easily infiltrate the brain in pathological conditions. The development of each Th-subset depends on the production of unique cytokines and their main regulator.

OBJECTIVE

This study aimed to compare the mRNA levels of Th-related genes derived from peripheral blood mononuclear cells of LOAD patients with control. Also, the identification of the most important Th1/Th2 genes and downstream pathways that may be involved in the pathogenesis of AD was followed by computational approaches.

METHODS

This study invloved 30 patients with LOAD and 30 non-demented controls. The relative expression of T-cell cytokines (IFN-γ, TNF-α, IL-4, and IL-5) and transcription factors (T-bet and GATA-3) were assessed using real-time PCR. Additionally, protein-protein interaction (PPI) was investigated by gene network construction.

RESULTS

A significant decrease at T-bet, IFN-γ, TNF-α, and GATA-3 mRNA levels was detected in the LOAD group, compared to the controls. However, there was no significant difference in IL-4 or IL-5 mRNA levels. Network analysis revealed a list of the highly connected protein (hubs) related to mitogen-activated protein kinase (MAPK) signaling and Th17 cell differentiation pathways.

CONCLUSION

The findings point to a molecular dysregulation in Th-related genes, which can promising in the early diagnosis or targeted interventions of AD. Furthermore, the PPI analysis showed that upstream off-target stimulation may involve MAPK cascade activation and Th17 axis induction.

CD4+ T-Cell Activation Prompts Suppressive Function by Extracellular Vesicle-Associated MicroRNAs

MicroRNAs (miRNAs), small non-coding molecules targeting messenger RNAs and inhibiting protein translation, modulate key biological processes, including cell growth and development, energy utilization, and homeostasis. In particular, miRNAs control the differentiation, survival, and activation of CD4 ⁺ T conventional (Tconv) cells, key players of the adaptive immunity, and regulate the physiological response to infections and the pathological loss of immune homeostasis in autoimmunity. Upon T-cell receptor (TCR) stimulation, the described global miRNA quantitative decrease occurring in T cells is believed to promote the acquisition of effector functions by relaxing the post-transcriptional repression of genes associated with proliferation and cell activity. MiRNAs were initially thought to get downregulated uniquely by intracellular degradation; on the other hand, miRNA secretion via extracellular vesicles (EVs) represents an additional mechanism of rapid downregulation. By focusing on molecular interactions by means of graph theory, we have found that miRNAs released by TCR-stimulated Tconv cells are significantly enriched for targeting transcripts upregulated upon stimulation, including those encoding for crucial proteins associated with Tconv cell activation and function. Based on this computational approach, we present our perspective based on the following hypothesis: a stimulated Tconv cell will release miRNAs targeting genes associated with the effector function in the extracellular space in association with EVs, which will thus possess a suppressive potential toward other Tconv cells in the paracrine environment. We also propose possible future directions of investigation aimed at taking advantage of these phenomena to control Tconv cell effector function in health and autoimmunity.

Establishment of an Immune-Related Gene Signature for Risk Stratification for Patients with Glioma

Glioma is a frequently seen primary malignant intracranial tumor, characterized by poor prognosis. The study is aimed at constructing a prognostic model for risk stratification in patients suffering from glioma. Weighted gene coexpression network analysis (WGCNA), integrated transcriptome analysis, and combining immune-related genes (IRGs) were used to identify core differentially expressed IRGs (DE IRGs). Subsequently, univariate and multivariate Cox regression analyses were utilized to establish an immune-related risk score (IRRS) model for risk stratification for glioma patients. Furthermore, a nomogram was developed for predicting glioma patients' overall survival (OS). The turquoise module (cor = 0.67; P < 0.001) and its genes (n = 1092) were significantly pertinent to glioma progression. Ultimately, multivariate Cox regression analysis constructed an IRRS model based on VEGFA, SOCS3, SPP1, and TGFB2 core DE IRGs, with a C-index of 0.811 (95% CI: 0.786-0.836). Then, Kaplan-Meier (KM) survival curves revealed that patients presenting high risk had a dismal outcome (P < 0.0001). Also, this IRRS model was found to be an independent prognostic indicator of gliomas' survival prediction, with HR of 1.89 (95% CI: 1.252-2.85) and 2.17 (95% CI: 1.493-3.14) in the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets, respectively. We established the IRRS prognostic model, capable of effectively stratifying glioma population, convenient for decision-making in clinical practice.

Transcription factors linked to the molecular signatures in the development of hepatocellular carcinoma on a cirrhotic background

Mechanisms underlying the regulation of gene expression in cancer have been surveyed for decades to find novel prognostic factors and new targets for molecular targeted therapies in cancer. Because most cases of liver cancer are associated with liver cirrhosis, we aimed to analyze the gene expression signatures and the gene regulatory mechanism in hepatocellular carcinoma (HCC) on a cirrhotic background using high-throughput data analysis. In the present study, three valid array-based datasets containing HCC and liver cirrhosis samples were obtained to identify common differentially expressed genes (DEGs). Moreover, a comprehensive data analysis was conducted based on RNA-Seq data and using Kaplan-Meier curve analysis to find molecular signatures that reduce patients' survival rate. Furthermore, we proposed a gene regulatory network (GRN) to explore the possible regulatory mechanism of these molecular signatures by transcription factors in HCC progression from cirrhosis. Besides, we analyzed protein-protein interactions, gene ontology (GO), and pathway enrichment to elucidate the cellular and molecular function of the GRN elements in HCC. In this way, we found a list of 231 molecular signatures in HCC derived from cirrhosis. We also found the importance of TCF4, RUNX1, HINFP, KDM2B, MAF, JUN, NR5A2, NFYA, and AR as key differentially expressed transcription factors (DETFs) in the progression of HCC from cirrhosis. In conclusion, the identified molecular signatures and their transcription factors propose candidate prognostic markers and possible molecular targets in the progression of HCC.

Characterization of Circulating Extracellular Vesicle Surface Antigens in Patients With Primary Aldosteronism

[Figure: see text].

Analysing omics data sets with weighted nodes networks (WNNets)

Current trends in biomedical research indicate data integration as a fundamental step towards precision medicine. In this context, network models allow representing and analysing complex biological processes. However, although effective in unveiling network properties, these models fail in considering the individual, biochemical variations occurring at molecular level. As a consequence, the analysis of these models partially loses its predictive power. To overcome these limitations, Weighted Nodes Networks (WNNets) were developed. WNNets allow to easily and effectively weigh nodes using experimental information from multiple conditions. In this study, the characteristics of WNNets were described and a proteomics data set was modelled and analysed. Results suggested that degree, an established centrality index, may offer a novel perspective about the functional role of nodes in WNNets. Indeed, degree allowed retrieving significant differences between experimental conditions, highlighting relevant proteins, and provided a novel interpretation for degree itself, opening new perspectives in experimental data modelling and analysis. Overall, WNNets may be used to model any high-throughput experimental data set requiring weighted nodes. Finally, improving the power of the analysis by using centralities such as betweenness may provide further biological insights and unveil novel, interesting characteristics of WNNets.

Equine Mesenchymal Stem/Stromal Cells Freeze-Dried Secretome (Lyosecretome) for the Treatment of Musculoskeletal Diseases: Production Process Validation and Batch Release Test for Clinical Use

In the last decades, it has been demonstrated that the regenerative therapeutic efficacy of mesenchymal stromal cells is primarily due to the secretion of soluble factors and extracellular vesicles, collectively known as secretome. In this context, our work described the preparation and characterization of a freeze-dried secretome (Lyosecretome) from adipose tissue-derived mesenchymal stromal cells for the therapy of equine musculoskeletal disorder. An intraarticular injectable pharmaceutical powder has been formulated, and the technological process has been validated in an authorized facility for veterinary clinical-use medicinal production. Critical parameters for quality control and batch release have been identified regarding (i) physicochemical properties; (ii) extracellular vesicle morphology, size distribution, and surface biomarker; (iii) protein and lipid content; (iv) requirements for injectable pharmaceutical dosage forms such as sterility, bacterial endotoxin, and Mycoplasma; and (v) in vitro potency tests, as anti-elastase activity and proliferative activity on musculoskeletal cell lines (tenocytes and chondrocytes) and mesenchymal stromal cells. Finally, proteins putatively responsible for the biological effects have been identified by Lyosecretome proteomic investigation: IL10RA, MXRA5, RARRES2, and ANXA1 modulate the inflammatory process RARRES2, NOD1, SERPINE1, and SERPINB9 with antibacterial activity. The work provides a proof-of-concept for the manufacturing of clinical-grade equine freeze-dried secretome, and prototypes are now available for safety and efficacy clinical trials in the treatment of equine musculoskeletal diseases

Integrated regulatory network based on lncRNA-miRNA-mRNA-TF reveals key genes and sub-networks associated with dilated cardiomyopathy

Dilated Cardiomyopathy (DCM) is a multifactorial condition often leading to heart failure in many clinical cases. Due to the high number of DCMincidence reported as familial, a gene level network based study was conducted utilizing high throughput next generation sequencing data. We exploited the exome and transcriptome sequencing data in NCBI-SRA database to construct a high confidence scale-free regulatory network consisting of lncRNA, miRNA, mRNA and Transcription Factors (TFs). Analysis of RNA-Seq data revealed 477 differentially expressed coding transcripts and 77 lncRNAs. 268 miRNAs regulated either lncRNAs or mRNAs. Out of the 477 coding transcripts that are deregulated, 82 were TFs. We identified three major hub nodeslncRNA (XIST), miRNA (hsa-miR-195-5p) and mRNA (NOVA1) from the network. We also found putative disease associations of DCM with diabetes and DCM with hypoventillation syndrome. Five highly connected modules were also identified from the network. The hubs showed significant connectivity with the modules.Through this study we were able to gain insights into the underlying lncRNA-miRNA-mRNA-TF network. From a high throughput dataset we have isolated a handful of probable targets that may be utilized for studying the mechanisms of DCM development and progression to heart failure.

Weighted gene co-expression network analysis to define pivotal modules and genes in diabetic heart failure

This research was carried out to reveal specific hub genes involved in diabetic heart failure, as well as remarkable pathways that hub genes locate. The GSE26887 dataset from the GEO website was downloaded. The gene co-expression network was generated and central modules were analyzed to identify key genes using the WGCNA method. Functional analyses were conducted on genes of the clinical interest modules via Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene ontology (GO) enrichment, associated with protein-protein interaction (PPI) network construction in a sequence. Centrality parameters of the PPI network were determined using the CentiScape plugin in Cytoscape. Key genes, defined as genes in the ≥95% percentile of the degree distribution of significantly perturbed networks, were identified. Twenty gene co-expression modules were detected by WGCNA analysis. The module marked in light yellow exhibited the most significant association with diabetes (P=0.08). Genes involved in this module were primarily located in immune response, plasma membrane and receptor binding, as shown by the GO analysis. These genes were primarily assembled in endocytosis and phagosomes for KEGG pathway enrichment. Three key genes, STK39, HLA-DPB1 and RAB5C, which may be key genes for diabetic heart failure, were identified. To our knowledge, our study is the first to have constructed the co-expression network involved in diabetic heart failure using the WGCNA method. The results of the present study have provided better understanding the molecular mechanism of diabetic heart failure.

Gray matter abnormalities follow non-random patterns of co-alteration in autism: Meta-connectomic evidence

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by atypical brain anatomy and connectivity. Graph-theoretical methods have mainly been applied to detect altered patterns of white matter tracts and functional brain activation in individuals with ASD. The network topology of gray matter (GM) abnormalities in ASD remains relatively unexplored.

METHODS

An innovative meta-connectomic analysis on voxel-based morphometry data (45 experiments, 1,786 subjects with ASD) was performed in order to investigate whether GM variations can develop in a distinct pattern of co-alteration across the brain. This pattern was then compared with normative profiles of structural and genetic co-expression maps. Graph measures of centrality and clustering were also applied to identify brain areas with the highest topological hierarchy and core sub-graph components within the co-alteration network observed in ASD.

RESULTS

Individuals with ASD exhibit a distinctive and topologically defined pattern of GM co-alteration that moderately follows the structural connectivity constraints. This was not observed with respect to the pattern of genetic co-expression. Hub regions of the co-alteration network were mainly left-lateralized, encompassing the precuneus, ventral anterior cingulate, and middle occipital gyrus. Regions of the default mode network appear to be central in the topology of co-alterations.

CONCLUSION

These findings shed new light on the pathobiology of ASD, suggesting a network-level dysfunction among spatially distributed GM regions. At the same time, this study supports pathoconnectomics as an insightful approach to better understand neuropsychiatric disorders.

Caloric Restriction Promotes Immunometabolic Reprogramming Leading to Protection from Tuberculosis

There is a strong relationship between metabolic state and susceptibility to Mycobacterium tuberculosis (MTB) infection, with energy metabolism setting the basis for an exaggerated immuno-inflammatory response, which concurs with MTB pathogenesis. Herein, we show that controlled caloric restriction (CR), not leading to malnutrition, protects susceptible DBA/2 mice against pulmonary MTB infection by reducing bacterial load, lung immunopathology, and generation of foam cells, an MTB reservoir in lung granulomas. Mechanistically, CR induced a metabolic shift toward glycolysis, and decreased both fatty acid oxidation and mTOR activity associated with induction of autophagy in immune cells. An integrated multi-omics approach revealed a specific CR-induced metabolomic, transcriptomic, and proteomic signature leading to reduced lung damage and protective remodeling of lung interstitial tightness able to limit MTB spreading. Our data propose CR as a feasible immunometabolic manipulation to control MTB infection, and this approach offers an unexpected strategy to boost immunity against MTB.

Immune profiling of plasma-derived extracellular vesicles identifies Parkinson disease

Objective

To develop a diagnostic model based on plasma-derived extracellular vesicle (EV) subpopulations in Parkinson disease (PD) and atypical parkinsonism (AP), we applied an innovative flow cytometric multiplex bead-based platform.

Methods

Plasma-derived EVs were isolated from PD, matched healthy controls, multiple system atrophy (MSA), and AP with tauopathies (AP-Tau). The expression levels of 37 EV surface markers were measured by flow cytometry and correlated with clinical scales. A diagnostic model based on EV surface markers expression was built via supervised machine learning algorithms and validated in an external cohort.

Results

Distinctive pools of EV surface markers related to inflammatory and immune cells stratified patients according to the clinical diagnosis. PD and MSA displayed a greater pool of overexpressed immune markers, suggesting a different immune dysregulation in PD and MSA vs AP-Tau. The receiver operating characteristic curve analysis of a compound EV marker showed optimal diagnostic performance for PD (area under the curve [AUC] 0.908; sensitivity 96.3%, specificity 78.9%) and MSA (AUC 0.974; sensitivity 100%, specificity 94.7%) and good accuracy for AP-Tau (AUC 0.718; sensitivity 77.8%, specificity 89.5%). A diagnostic model based on EV marker expression correctly classified 88.9% of patients with reliable diagnostic performance after internal and external validations.

Conclusions

Immune profiling of plasmatic EVs represents a crucial step toward the identification of biomarkers of disease for PD and AP.

Unraveling the proteomic changes involved in the resistance response of Cajanus platycarpus to herbivory by Helicoverpa armigera

The pigeonpea wild relative Cajanus platycarpus is resistant to Helicoverpa armigera, one of the major pests responsible for yield losses in Cajanus cajan. Deciphering the molecular mechanism underlying host plant resistance is pertinent to identify proteins that aid in the mitigation of the insect pest. The present study adopted comparative proteomics as a tool to interpret the resistance mechanism(s) in C. platycarpus vis-à-vis C. cajan during continued herbivory (up to 96 h). Over-representation analysis of the differentially expressed proteins implicated a multi-dimensional resistance response accomplished by both physical and chemical barriers in C. platycarpus. While the chemical basis for resistance was depicted by the upregulation of proteins playing a rate limiting role in the phenylpropanoid pathway, the physical basis was provided by the regulation of proteins involved in microtubule assembly and synthesis of lignins. Upregulation of proteins in the polyamine pathway indicated the role of metabolite conjugates to be negatively affecting herbivore growth. Reallocation of resources and diversion of metabolic flux to support the production of secondary metabolites could be the probable approach in the wild relative against herbivory. Our study provided deeper insights into the pod borer resistance mechanism in C. platycarpus for utility in crop improvement. KEY POINTS: • Pod borer resistance in Cajanus platycarpus is multi-dimensional. • Pod borer resistance has been arbitrated to cell wall rigidity and secondary metabolites. • Phenylpropanoid pathway derivatives apparently shaped the plant chemical defense against pod borer.

Molecular classification and immunologic characteristics of immunoreactive high‐grade serous ovarian cancer

High‐grade serous ovarian cancer (HGS‐OvCa) is one of the most lethal gynaecological malignancies. Molecular classification identified an immunoreactive subtype of HGS‐OvCa; however, the immunologic characteristics of immunoreactive HGS‐OvcA remain unclear. In this study, 121 immunoreactive HGS‐OvCa samples were identified from a meta‐analysis of 5 large transcriptome profiling data sets using a cross‐platform immunoreactive HGS‐OvCa subgroup‐specific classifier. By comparing the gene expression profiles of immunoreactive HGS‐OvCa samples and normal tissues, 653 differentially expressed genes (DEGs) were identified. KEGG pathway analysis revealed that the leukocyte transendothelial migration pathways were significantly enriched in the immunoreactive HGS‐OvCa. Protein‐protein interaction analysis identified a module that showed strong involvement of the immune‐related chemokine signalling pathway. Moreover, the GSEA enrichment analysis showed a T‐cell subgroup and M1 macrophages were significantly enriched in immunoreactive OvCa compared with normal samples. Macrophage infiltration levels were significantly elevated in immunoreactive HGS‐OvCa compared with other OvCa subtypes. In addition, expression of immune checkpoint molecules VTCN1 and IDO1 was significantly increased in immunoreactive HGS‐OvCa. In summary, our results suggest that the immunoreactive HGS‐OvCa has unique molecular characteristics and a tumour‐associated immune microenvironment featured by increased infiltration of macrophages, rather than lymphocytes. VTCN1 could be potential targets for the treatment of immunoreactive HGS‐OvCa.

Deciphering the Novel Target Genes Involved in the Epigenetics of Hepatocellular Carcinoma Using Graph Theory Approach

Background

Even after decades of research, cancer, by and large, remains a challenge and is one of the major causes of death worldwide. For a very long time, it was believed that cancer is simply an outcome of changes at the genetic level but today, it has become a well-established fact that both genetics and epigenetics work together resulting in the transformation of normal cells to cancerous cells.

Objective

In the present scenario, researchers are focusing on targeting epigenetic machinery. The main advantage of targeting epigenetic mechanisms is their reversibility. Thus, cells can be reprogrammed to their normal state. Graph theory is a powerful gift of mathematics which allows us to understand complex networks.

Methodology

In this study, graph theory was utilized for quantitative analysis of the epigenetic network of hepato-cellular carcinoma (HCC) and subsequently finding out the important vertices in the network thus obtained. Secondly, this network was utilized to locate novel targets for hepato-cellular carcinoma epigenetic therapy.

Results

The vertices represent the genes involved in the epigenetic mechanism of HCC. Topological parameters like clustering coefficient, eccentricity, degree, etc. have been evaluated for the assessment of the essentiality of the node in the epigenetic network.

Conclusion

The top ten novel epigenetic target genes involved in HCC reported in this study are cdk6, cdk4, cdkn2a, smad7, smad3, ccnd1, e2f1, sf3b1, ctnnb1, and tgfb1.

LncRNAs Predicted to Interfere With the Gene Regulation Activity of miR-637 and miR-196a-5p in GBM

Rigorous molecular characterization of biological systems has uncovered a variety of gene variations underlying normal and disease states and a remarkable complexity in the forms of RNA transcripts that exist. A recent concept, competitive endogenous RNA, suggests that some non-coding RNAs can bind to miRNAs to modulate their role in gene expression. Here, we used several platforms, integrating mRNA, non-coding RNAs and protein data to generate an RNA-protein network that may be dysregulated in human glioblastoma multiforme (GBM). Publicly available microarray data for mRNA and miRNA were used to identify differentially expressed miRNAs and mRNAs in GBM relative to non-neoplastic tissue samples. Target miRNAs were further selected based on their prognostic significance, and the intersection of their target gene set with the differentially expressed gene set in Venn diagrams. Two miRNAs, miR-637 and miR-196a-5p, were associated with poor and better prognosis, respectively, in GBM patients. Non-coding RNAs, ENSG00000203739/ENSG00000271646 and TPTEP1, were predicted to be miRNA target genes for miR-637 and miR-196a-5p and positively correlated with the selected mRNA, CYBRD1 and RUFY2. A local protein interaction network was constructed using these two mRNAs. Predictions based on the ENSG00000203739/ENSG00000271646-miR-637-CYBRD1 and TPTEP1-miR-196a-5p-RUFY2 regulation axes indicated that the two proteins may act as an oncogene and tumor suppressor, respectively, in the development of GBM. These results highlight competitive endogenous RNA networks as alternative molecular therapeutic targets in the treatment of the disease.

miR-497-5p mediates starvation-induced death in colon cancer cells by targeting acyl-CoA synthetase-5 and modulation of lipid metabolism

Modulation of fatty acids metabolism is an appropriate strategy for starvation-induced death in tumor cancers. Colon cancer cells express a high level of acyl-CoA synthetase-5 (ACSL5), and as yet no therapeutic approach has been achieved. Herein, ACSL5-related microRNAs (miRNAs) were identified via TargetScan, and their impacts on ACSL5 and lipid content along with metabolic activity, cell cycle, migration, and invasion of colorectal cancer (CRC) cells were examined, and subsequently compared with transcriptome for better visualization of intracellular-signaling networks. In vivo analysis was performed using BALB/c mice xenograft model of CRC injected with target miRNA. Clinical significances were also evaluated in 80 CRC tumors and matched adjacent normal tissues. There was a reverse correlation between ACSL5 and miR-497-5p, which miR-497-5p overexpression modulated CRC cell proliferation and development. A similar observation was received from the in vivo examination in which intratumoral injection of miR-497-5p reversed the tumor growth in the CRC xenograft model. Downregulation of miR-497-5p correlated with tumor differentiation, tumor, node, and metastasis staging, lymph node metastasis, and poor survival in patients with CRC. These results suggested that miR-497-5p upregulation could be considered as a therapeutic strategy for modulation of lipid metabolism in colon cancer.

Identification of Key Genes and the Pathophysiology Associated With Major Depressive Disorder Patients Based on Integrated Bioinformatics Analysis

Background: At present, laboratory blood tests to support major depressive disorder (MDD) diagnosis are not available. This study aimed to screen potential mRNAs for peripheral blood biomarkers and novel pathophysiology of MDD. Methods: The present study utilized public data from two mRNA microarray datasets to analyze the hub genes changes related to MDD. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of differentially expressed genes (DEGs) were performed. Finally, some potential mRNA quality biomarkers for hub gene expression in blood were identified. Results: A total of 25 significantly co-upregulated DEGs and 98 co-downregulated DEGs were obtained from two datasets. The pathway enrichment analyses showed that co-upregulated genes were significantly enriched in the regulation of cell-matrix adhesion and mitochondrial membrane permeability which were involved in the apoptotic process. Co-downregulated genes were mainly involved in the neutrophil activation which in turn was involved in the immune response, degranulation and cell-mediated immunity, positive regulation of immune response, the Toll-like receptor signaling pathway, and the NOD-like receptor signaling pathway. From the PPI network, 14 hub genes were obtained. Among them, the subnetworks of PLCG1, BCL2A1, TLR8, FADD, and TLR4 screened out from our study have been shown to play a role in immune and inflammation responses. Discussion: The potential molecular mechanisms that have been identified simultaneously include innate immunity, neuroinflammation, and neurotrophic factors for synapse function and development.

Competitive Endogenous RNA Network Construction and Comparison of Lung Squamous Cell Carcinoma in Smokers and Nonsmokers

Background

Lung squamous cell carcinoma (LUSC) is a subtype of highly malignant lung cancer with poor prognosis, for which smoking is the main risk factor. However, the underlying genetic and molecular mechanisms of smoking-related LUSC remain largely unknown.

Methods

We mined existing LUSC-related mRNA, miRNA, and lncRNA transcriptome data and corresponding clinical data from The Cancer Genome Atlas (TCGA) database and divided them into smoking and nonsmoking groups, followed by differential expression analysis. Functional enrichment analysis of the unique differentially expressed mRNAs of the two groups was performed using the DAVID database. Subsequently, the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network of LUSC in smoking and nonsmoking groups was constructed. Finally, survival analyses were performed to determine the effects of differentially expressed lncRNAs/mRNAs/miRNAs that were involved in the ceRNA network on overall survival and to discover the hub genes.

Results

A total of 1696 lncRNAs, 125 miRNAs, and 3246 mRNAs and 1784 lncRNAs, 96 miRNAs, and 3229 mRNAs with differentially expressed profiles were identified in the smoking and nonsmoking groups, respectively. The ceRNA network and survival analysis revealed four lncRNAs (LINC00466, DLX6-AS1, LINC00261, and AGBL1), one miRNA (hsa-mir-210), and two mRNAs (CITED2 and ENPP4), with the potential as biomarkers for smoking-related LUSC diagnosis and prognosis.

Conclusion

Taken together, our research has identified the differences in the ceRNA regulatory networks between smoking and nonsmoking LUSC, which could lay the foundation for future clinical research.

Neuro-Inflammation in Pediatric Traumatic Brain Injury-from Mechanisms to Inflammatory Networks

Compared to traumatic brain injury (TBI) in the adult population, pediatric TBI has received less research attention, despite its potential long-term impact on the lives of many children around the world. After numerous clinical trials and preclinical research studies examining various secondary mechanisms of injury, no definitive treatment has been found for pediatric TBIs of any severity. With the advent of high-throughput and high-resolution molecular biology and imaging techniques, inflammation has become an appealing target, due to its mixed effects on outcome, depending on the time point examined. In this review, we outline key mechanisms of inflammation, the contribution and interactions of the peripheral and CNS-based immune cells, and highlight knowledge gaps pertaining to inflammation in pediatric TBI. We also introduce the application of network analysis to leverage growing multivariate and non-linear inflammation data sets with the goal to gain a more comprehensive view of inflammation and develop prognostic and treatment tools in pediatric TBI.

Transcriptomics-based screening of molecular signatures associated with patients overall survival and their key regulators in subtypes of breast cancer

Molecular subtypes of breast cancer are associated with differences in prognosis and strategies of molecular targeted therapies. Gene regulatory mechanisms as one of the reasons might modulate these differences. In the present study, we proposed a comprehensive data analysis and systems biology approach to explore molecular signatures which reduce the chance of patients overall survival and the possible mechanisms of their regulation by transcription factors (TFs) and microRNAs (miRNAs) in the main subtypes of breast tumor consist of Basal like, Her2 enriched, Luminal A and Luminal B breast cancer. In this regards, we used available microarray datasets to assess common differentially expressed genes (DEGs) in breast cancer subtypes. Using Kaplan-Meier curve analysis we identified common DEGs which are associated with decreasing in the overall survival of breast cancer patients. Furthermore, gene regulatory networks (GRNs) were depicted based on TFs and miRNAs with interest target genes. Then GRNs were analyzed and using five algorithms (Control centrality, Betweenness, Degree, Classification, and MCDS) the key regulators were identified for each subtype. In this study, we highlighted mechanisms underlying the regulation of breast cancer molecular signatures by TFs and miRNAs which their alteration reduce the chance of survival rate in each subtype of breast cancer. Our current study in a holistic insight revealed the importance of some genes and their regulators as potential prognostic markers and/or therapeutic targets in breast cancer patients.

A detailed image of rutin underlying intracellular signaling pathways in human SW480 colorectal cancer cells based on miRNAs-lncRNAs-mRNAs-TFs interactions

Natural dietary ingredients like flavonoids are important for body improvement against diseases. The flavonol rutin is widely found in fruits and vegetables and shows significant anticancer properties. However, the underlined signaling pathways have not been elucidated yet. In this study, the impacts of various doses of rutin (400-700 mM/ml) have been examined on human colon cancer SW480 cells metabolism, cell cycle, and apoptosis. The transcriptome was analyzed by bioinformatics tools and the interactions between rutin modulated microRNAs (miRNAs), long noncoding RNAs (lncRNAs), messenger RNAs (mRNAs), and transcription factors (TFs) were built, filtered and enriched. A dose of 600 mM of rutin significantly decreased cells metabolic activity, halved the population and arrested the cell cycle at the sub-G1 phase. The enrichment analysis of miRNAs-lncRNAs-mRNAs-TFs network showed that these effects were mediated through alteration of glucose, lipid, and protein metabolism, modulating endoplasmic reticulum stress responses, negative regulation of cell cycle process, and inducing the extrinsic and intrinsic apoptotic signaling pathways. Additionally, the key parent nodes of each annotation were illustrated. These findings create a detailed image of rutin underlying intracellular signaling pathways in CRC and also help us to better understand the role of dietary natural compounds in cancer treatment.

cuRnet: an R package for graph traversing on GPU

BACKGROUND

R has become the de-facto reference analysis environment in Bioinformatics. Plenty of tools are available as packages that extend the R functionality, and many of them target the analysis of biological networks. Several algorithms for graphs, which are the most adopted mathematical representation of networks, are well-known examples of applications that require high-performance computing, and for which classic sequential implementations are becoming inappropriate. In this context, parallel approaches targeting GPU architectures are becoming pervasive to deal with the execution time constraints. Although R packages for parallel execution on GPUs are already available, none of them provides graph algorithms.

RESULTS

This work presents cuRnet, a R package that provides a parallel implementation for GPUs of the breath-first search (BFS), the single-source shortest paths (SSSP), and the strongly connected components (SCC) algorithms. The package allows offloading computing intensive applications to GPU devices for massively parallel computation and to speed up the runtime up to one order of magnitude with respect to the standard sequential computations on CPU. We have tested cuRnet on a benchmark of large protein interaction networks and for the interpretation of high-throughput omics data thought network analysis.

CONCLUSIONS

cuRnet is a R package to speed up graph traversal and analysis through parallel computation on GPUs. We show the efficiency of cuRnet applied both to biological network analysis, which requires basic graph algorithms, and to complex existing procedures built upon such algorithms.

Gene's hubs in retinal diseases: A retinal disease network

BACKGROUND

Retinal diseases associated with the dysfunction or death of photoreceptors are a major cause of blindness around the world, improvements in genetics tools, like next generation sequencing (NGS) allows the discovery of genes and genetic changes that lead to many of those retinal diseases. Though, there very few databases that explores a wide spectrum of retinal diseases, phenotypes, genes, and proteins, thus creating the need for a more comprehensive database, that groups all these parameters.

METHODS

Multiple open access databases were compiled into a new comprehensive database. A biological network was then crated, and organized using Cytoscape. The network was scrutinized for presence of hubs, measuring the concentration of grouped nodes. Finally, a trace back analysis was performed in areas were the power law reports a high r-squared value near one, that indicates high nodes density.

RESULTS

This work leads to creation of a retinal database that includes 324 diseases, 803 genes, 463 phenotypes, and 2461 proteins. Four biological networks (1) a disease and gene network connected by common phenotypes, (2) a disease and phenotype network connected by common genes, (3) a disease and gene network with shared disease or gene as the cause of an edge, and (4) a protein and disease network. The resulting networks will allow users to have easier searching for retinal diseases, phenotypes, genes, and proteins and their interrelationships.

CONCLUSIONS

These networks have a broader range of information than previously available ones, helping clinicians in the comprehension of this complex group of diseases.