Integrative Network Analysis Research Articles

Integrative network analysis reveals subtype-specific long non-coding RNA regulatory mechanisms in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSC) is one of most common malignancies with high mortality worldwide. Importantly, the molecular heterogeneity of HNSC complicates the clinical diagnosis and treatment, leading to poor overall survival outcomes. To dissect the complex heterogeneity, recent studies have reported multiple molecular subtyping systems. For instance, HNSC can be subdivided to four distinct molecular subtypes: atypical, basal, classical, and mesenchymal, of which the mesenchymal subtype is characterized by upregulated epithelial-mesenchymal transition (EMT) and associated with poorer survival outcomes. Despite a wealth of studies into the complex molecular heterogeneity, the regulatory mechanism specific to this aggressive subtype remain largely unclear. Herein, we developed a network-based bioinformatics framework that integrates lncRNA and mRNA expression profiles to elucidate the subtype-specific regulatory mechanisms. Applying the framework to HNSC, we identified a clinically relevant lncRNA LNCOG as a key master regulator mediating EMT underlying the mesenchymal subtype. Five genes with strong prognostic values, namely ANXA5, ITGA5, CCBE1, P4HA2, and EPHX3, were predicted to be the putative targets of LNCOG and subsequently validated in other independent datasets. By integrative analysis of the miRNA expression profiles, we found that LNCOG may act as a ceRNA to sponge miR-148a-3p thereby upregulating ITGA5 to promote HNSC progression. Furthermore, our drug sensitivity analysis demonstrated that the five putative targets of LNCOG were also predictive of the sensitivities of multiple FDA-approved drugs. In summary, our bioinformatics framework facilitates the dissection of cancer subtype-specific lncRNA regulatory mechanisms, providing potential novel biomarkers for more optimized treatment of HNSC.

Uncovering the pharmacological mechanisms of Zizhu ointment against diabetic ulcer by integrating network analysis and experimental evaluation in vivo and in vitro.

Diabetic ulcer (DU) has been recognized as one of the most prevalent and serious complications of diabetes. However, the clinical efficacy of standard treatments for DU remains poor. Traditional Chinese medicine (TCM) shows a positive therapeutic effect on DU. Specifically, Zizhu ointment (ZZO) has been widely used to treat DU in long-term clinical practice, but the exact mechanism by which it promotes DU wound healing remains unknown. In this study, network analysis and high-performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) were conducted to identify the active compounds of ZZO. We detected isovalerylshikonin (ISO), mandenol, daidzein, kaempferol, and formononetin in both network analysis and UPLC-HRMS. Moreover, ZZO could ameliorate DU by regulating the phosphatidylinositol-3-kinase (PI3K)/protein kinase B (AKT) and inflammation signaling pathways, according to the results of KEGG analysis. We established a DU mouse model with a high-fat diet and streptozotocin injection in vivo to evaluate the network analysis result. The experimental results showed that ZZO could inhibit inflammation, remodel fibrous tissue, and promote angiogenesis in the DU area, facilitating wound healing in DU mice. Moreover, the PI3K/AKT signaling pathway was indeed activated by ZZO treatment, promoting macrophage M2 polarization. In addition, we used molecular docking technology to evaluate the binding sites between ZZO and the PI3K/AKT pathway. The results showed that ISO has a good binding interaction with AKT. Moreover, ISO promoted M2 polarization in macrophages in a dose-dependent manner in vitro. Our study found that ZZO could promote DU wound healing by inhibiting inflammation, which was achieved by macrophage M2 polarization through activating the PI3K/AKT pathway. Further studies have demonstrated that ISO plays major role in the above process. These findings provide a theoretical basis for further preclinical evaluation and lay a foundation for nano-gel compound treatment with ZZO.

The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis

In recent years, a growing interest in the characterization of the molecular basis of psoriasis has been observed. However, despite the availability of a large amount of molecular data, many pathogenic mechanisms of psoriasis are still poorly understood. In this study, we performed an integrated analysis of 23 public transcriptomic datasets encompassing both lesional and uninvolved skin samples from psoriasis patients. We defined comprehensive gene co-expression network models of psoriatic lesions and uninvolved skin. Moreover, we curated and exploited a wide range of functional information from multiple public sources in order to systematically annotate the inferred networks. The integrated analysis of transcriptomics data and co-expression networks highlighted genes that are frequently dysregulated and show aberrant patterns of connectivity in the psoriatic lesion compared with the unaffected skin. Our approach allowed us to also identify plausible, previously unknown, actors in the expression of the psoriasis phenotype. Finally, we characterized communities of co-expressed genes associated with relevant molecular functions and expression signatures of specific immune cell types associated with the psoriasis lesion. Overall, integrating experimental driven results with curated functional information from public repositories represents an efficient approach to empower knowledge generation about psoriasis and may be applicable to other complex diseases.

Integrative network analysis interweaves the missing links in cardiomyopathy diseasome

Cardiomyopathies are progressive disease conditions that give rise to an abnormal heart phenotype and are a leading cause of heart failures in the general population. These are complex diseases that show co-morbidity with other diseases. The molecular interaction network in the localised disease neighbourhood is an important step toward deciphering molecular mechanisms underlying these complex conditions. In this pursuit, we employed network medicine techniques to systematically investigate cardiomyopathy’s genetic interplay with other diseases and uncover the molecular players underlying these associations. We predicted a set of candidate genes in cardiomyopathy by exploring the DIAMOnD algorithm on the human interactome. We next revealed how these candidate genes form association across different diseases and highlighted the predominant association with brain, cancer and metabolic diseases. Through integrative systems analysis of molecular pathways, heart-specific mouse knockout data and disease tissue-specific transcriptomic data, we screened and ascertained prominent candidates that show abnormal heart phenotype, including NOS3, MMP2 and SIRT1. Our computational analysis broadens the understanding of the genetic associations of cardiomyopathies with other diseases and holds great potential in cardiomyopathy research.

Transcriptome analysis of intestine from alk-SMase knockout mice reveals the effect of alk-SMase

ObjectiveIntestinal alkaline sphingomyelinase (alk-SMase) generates ceramide and inactivates platelet-activating factor associated with digestion and inhibition of cancer. There is few study to analyze the correlated function and characterize the genes related to alk-SMase comprehensively. We characterised transcriptome landscapes of intestine tissues from alk-SMase knockout (KO) mice aiming to identify novel associated genes and research targets.MethodsWe performed the high-resolution RNA sequencing of alk-SMase KO mice and compared them to wild type (WT) mice. Differentially expressed genes (DEGs) for the training group were screened. Functional enrichment analysis of the DEGs between KO mice and WT mice was implemented using the Database for Annotation, Visualization and Integrated Discovery (DAVID). An integrated protein–protein interaction (PPI) and Kyoto Encyclopedia of Genes and Genomes (KEGG) network was chose to study the relationship of differentially expressed gene. Moreover, quantitative real-time polymerase chain reaction (qPCR) was further used to validate the accuracy of RNA-seq technology.ResultsOur RNA-seq data found 97 differentially expressed mRNAs between the WT mice and alk-SMase gene NPP7 KO mice, in which 32 were significantly up-regulated and 65 were down-regulated, including protein coding genes, non-coding RNAs. Notably, the results of gene ontology functional enrichment analysis indicated that DEGs were functionally associated with the immune response, regulation of cell proliferation and development related terms. Additionally, an integrated network analysis was shown that some modules was significantly related to alk-SMase and with accordance of previously results. We chose 6 of these genes randomly were validated the accuracy of RNA-seq technology using qPCR and 2 genes showed difference significantly (P < 0.05).ConclusionsWe investigated the potential biological significant of alk-SMase with high resolution genome-wide transcriptome of alk-SMase knockout mice. The results revealed new insight into the functional modules related to alk-SMase was involved in the intestinal related diseases.

Changes in mRNA and miRNA expression in the prelimbic cortex related to depression-like syndrome induced by chronic social defeat stress in mice

Major depressive disorder is a complex psychiatric disorder with a high prevalence rate worldwide. Previous studies have demonstrated the involvement of the prelimbic cortex (PL) in mediating depressive-like behavior, however, the exact molecular mechanism taking place in the PL remains unclear. In the present study, we conducted high-throughput sequencing of mRNAs and miRNAs in PL tissue harvested from chronic social defeat stress (CSDS) susceptible male mice. We identified 59 differentially expressed mRNAs and 6 differentially expressed miRNAs, in which 40 mRNAs and 3 miRNAs were up-regulated, while 19 mRNAs and 3 miRNAs were down-regulated. Integrated analysis of miRNA-mRNA networks suggested that GPR35 signaling might be involved in CSDS-induced depressive-like behaviors. RT-PCR and western blot assays validated that Abra, Sell and GPR35 were up-regulated. Functionally, inhibition of GPR35 in the PL ameliorated CSDS-induced depressive-like behaviors. Thus, the present study provided a global view of mRNA and miRNA profiles in the PL of male stress susceptible mice, and suggested that GPR35 signaling was associated with CSDS-induced depressive-like behaviors. These results may be valuable for further investigations of the molecular regulatory mechanisms in stress-induced depression.

Abstract 14044: Leveraging Multi-Omics to Identify Biologically-Informed Clusters of Individuals With Differing Underlying Disease Risk Mechanisms Using an Innovative Network Modelling Approach

Background: The rates of known cardiometabolic risk elevation are highly variable among patients suggesting that there are other risk mediators underlying diseases. We hypothesized that using cutting-edge and innovative multi-omics integrative network analysis in conjunction with the consensus clustering approach would identify clusters of individuals which may represent novel functional and/or pathophysiological risk mechanisms of cardiometabolic disorders. Methods: The genetically predicted levels of metabolites and proteins constructed from the GWAS data of Framingham/Malmö and KORA-TWINS were imputed in 13,562 BioVU participants. These 2 layers of omics data were integrated using similarity network fusion in conjunction with consensus clustering approaches. The identified clusters of individuals were tested for associations with 14 cardiometabolic diseases using logistic regression adjusting for known risk factors to identify endotypic determinants of diseases. Pathway analysis comparing each cluster to the rest of participants was performed using Reactome and MetaboAnalyst. Results: We identified 5 clusters across which LDL-C was significantly (p=0.001) different. The significant associations were found for cluster 1 with coronary artery disease (p=0.04), cluster 2 with cardiomyopathy(p=0.004) and atrial fibrillation (p=0.03) and cluster 4 with congenital heart disease (p=0.03) [ Fig 1 ]. Thus, clusters 1, 2 and 4 are endotypic determinants of the above diseases. Each of these clusters was associated with distinct pathways indicating candidate mechanisms of diseases related to the clusters. Conclusions: This novel discovery-oriented multi-omics clustering method identified biologically-related subgroups of individuals and revealed novel risk mechanism and biomarkers of cardiometabolic diseases. The innovative network-based models advance precision medicine by enabling future prognostic risk prediction tools.

Distributed flexibility to maintain security margin through decentralised TSO–DSO coordination

The increasing role of distribution networks as an active entity in the whole power and energy system, development of a unified power flow method to provide an integrated analysis of transmission and distribution networks becomes essential. Traditional methods have not addressed the challenge of voltage security in the coordination, while disconnecting the whole distribution network is considered as a solution for preventing major issues. This paper proposes a decentralised scheme for the coordination of transmission and distribution networks while maintaining the voltage security of the whole integrated system. At the transmission level, the transmission network operator (TSO) solves a centralised optimisation problem to minimise the system load curtailment while maintaining the system security margin. The TSO communicates the required set-points in the interface with distribution grids to the distribution system operators (DSOs.) At the distribution level, the DSOs utilise their available distributed flexibilities, such as conservation voltage reduction and feeder reconfiguration, to provide the required set-points and preserve the whole system security margin, with minimum load curtailment. This decentralised optimisation scheme preserves the system security with minimum information exchange between operators, as well as minimum physical load curtailment. The distributed flexibilities of all DSOs are utilised to meet the required security margin of the whole system. The proposed TSO–DSO coordination model is applied to the IEEE 118-bus transmission network, and the 83-bus practical distribution network of Taiwan Power Company and IEEE 33-bus feeder are considered as the connected distribution networks. The results show that the distributed flexibilities are capable of reducing the system demand to preserve the desired security margin, without any need for imposing direct load curtailment.

An integrative analysis of lncRNAs and mRNAs highlights the potential roles of lncRNAs in the process of follicle selection in Taihang chickens

Taihang chickens are a domestic breed distributed throughout Hebei province in the Taihang Mountains of China and are characterized by their high meat and egg quality. However, the relatively limited egg production by this breed constrains their more widespread commercial utilization. The follicle selection process is closely linked to oocyte development and ovulation, making it a key determinant of laying performance and fecundity in hens. To understand the biological basis for such follicle selection and to identify the associated regulatory pathways, we conducted a genome-wide analysis of long noncoding RNAs (lncRNAs) and mRNAs from the pre-hierarchical follicles and hierarchical follicles of Taihang laying hens. We identified 81 lncRNAs and 528 mRNAs that were differentially expressed during follicle selection, and integrated network analyses suggested that these RNAs were associated with the cell cycle, focal adhesion, oocyte meiosis, peroxisome proliferator-activated receptor signaling, and steroid hormone biosynthesis pathways. The identified lncRNAs were also predicted to influence a series of target genes in cis and trans, suggesting that they may be important regulators of ovarian follicular development. Overall, the present analysis of lncRNA and mRNA expression patterns associated with ovarian follicle development offers a new foundation for future studies of reproductive physiology in Taihang chickens, highlighting new opportunities to improve the laying performance of this important domestic breed.

IReNA: Integrated regulatory network analysis of single-cell transcriptomes and chromatin accessibility profiles

Recently, single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) have been developed to separately measure transcriptomes and chromatin accessibility profiles at the single-cell resolution. However, few methods can reliably integrate these data to perform regulatory network analysis. Here, we developed integrated regulatory network analysis (IReNA) for network inference through the integrated analysis of scRNA-seq and scATAC-seq data, network modularization, transcription factor enrichment, and construction of simplified intermodular regulatory networks. Using public datasets, we showed that integrated network analysis of scRNA-seq data with scATAC-seq data is more precise to identify known regulators than scRNA-seq data analysis alone. Moreover, IReNA outperformed currently available methods in identifying known regulators. IReNA facilitates the systems-level understanding of biological regulatory mechanisms and is available at https://github.com/jiang-junyao/IReNA.

Culturomic-, metagenomic-, and transcriptomic-based characterization of commensal lactic acid bacteria isolated from domestic dogs using Caenorhabditis elegans as a model for aging.

In tandem with the fast expansion of the pet-economy industry, the present aging research has been noticing the function of probiotics in extending the healthy lifetime of domestic animals. In this study, we aimed to understand the bacterial compositions of canine feces and isolating lactic acid bacteria (LAB) as commensal LAB as novel potential probiotics for the use of antiaging using Caenorhabditis elegans surrogate animal model. Under an anaerobic, culturomic, and metagenomic analysis, a total of 305 commensal LAB were isolated from diverse domestic dogs, and four strains, Lactobacillus amylolyticus, L. salivarius, Enterococcus hirae, and E. faecium, made prominence as commensal LAB by enhancing C. elegans life span and restored neuronal degeneration induced by aging by upregulating skn-1, ser-7, and odr-3, 7, 10. Importantly, whole transcriptome results and integrative network analysis revealed extensive mRNA encoding protein domains and functional pathways of naturally aging C. elegans were examined and we built the gene informatics basis. Taken together, our findings proposed that a specific gene network corresponding to the pathways differentially expressed during the aging and selected commensal LAB as potential probiotic strains could be provided beneficial effects in the aging of domestic animals by modulating the dynamics of gut microbiota.

Healthy aging index and its link with relative education between individual and neighborhood: a population-based, cohort study

ObjectivesThere is increasing recognition of the importance of neighborhood socioeconomic status (SES) for establishing an age-friendly society. Despite the benefits of improved neighborhood SES, little is known about the link of relative education between individuals and neighborhoods with healthy aging. This study aims to construct a healthy aging index (HAI) accounting for indicators’ interlinkages and to test the association of the HAI with relative education between neighborhoods and individuals.MethodsThe study used data from the China Health and Retirement Longitudinal Study from 2011 to 2018, including middle-aged and older adults (≥ 45 years). The final sample comprised 11633 participants residing in 443 neighborhoods with 34123 observations. Based on 13 health indicators, a hybrid method integrating network analysis with TOPSIS was applied to construct a HAI accounting for health interlinkages. Weighted multilevel linear and ordered logistic models were used to estimate the effects of neighborhood education.ResultsAmong the 11633 participants (mean [SD] age, 58.20 [8.91] years; 6415 women [52.82%]), the mean (SD) HAI was 48.94 (7.55) at baseline, showing a downward trend with age. Approximately 10% of participants had a HAI trajectory characterized by a low starting point and fast decline. A one-year increase in neighborhood education was independently associated with a 0.37-point increase (95% CI, 0.23–0.52) in HAI. Regardless of individual education, each participant tended to gain benefits from a neighborhood with higher education. However, the effects of increased neighborhood education were weaker for individuals whose education was lower than the neighborhood average.ConclusionsThe HAI is an interaction system. Improving neighborhood education was beneficial to healthy aging, but individuals with lower education relative to the neighborhood average may experience poor person–environment fit and obtain fewer benefits from improved neighborhood education. Thus, in the process of improving neighborhood SES, individual-based interventions should be conducted for individuals whose education level is lower than the neighborhood average to achieve person–environment fit.

Weakly activated core neuroinflammation pathways were identified as a central signaling mechanism contributing to the chronic neurodegeneration in Alzheimer's disease.

ObjectivesNeuroinflammation signaling has been identified as an important hallmark of Alzheimer’s disease (AD) in addition to amyloid β plaques (Aβ) and neurofibrillary tangles (NFTs). However, the molecular mechanisms and biological processes of neuroinflammation remain unclear and have not well delineated using transcriptomics data available. Our objectives are to uncover the core neuroinflammation signaling pathways in AD using integrative network analysis on the transcriptomics data.Materials and methodsFrom a novel perspective, i.e., investigating weakly activated molecular signals (rather than the strongly activated molecular signals), we developed integrative and systems biology network analysis to uncover potential core neuroinflammation signaling targets and pathways in AD using the two large-scale transcriptomics datasets, i.e., Mayo Clinic (77 controls and 81 AD samples) and ROSMAP (97 controls and 260 AD samples).ResultsOur analysis identified interesting core neuroinflammation signaling pathways, which are not systematically reported in the previous studies of AD. Specifically, we identified 7 categories of signaling pathways implicated on AD and related to virus infection: immune response, x-core signaling, apoptosis, lipid dysfunctional, biosynthesis and metabolism, and mineral absorption signaling pathways. More interestingly, most of the genes in the virus infection, immune response, and x-core signaling pathways are associated with inflammation molecular functions. The x-core signaling pathways were defined as a group of 9 signaling proteins: MAPK, Rap1, NF-kappa B, HIF-1, PI3K-Akt, Wnt, TGF-beta, Hippo, and TNF, which indicated the core neuroinflammation signaling pathways responding to the low-level and weakly activated inflammation and hypoxia and leading to the chronic neurodegeneration. It is interesting to investigate the detailed signaling cascades of these weakly activated neuroinflammation signaling pathways causing neurodegeneration in a chronic process, and consequently uncover novel therapeutic targets for effective AD treatment and prevention.ConclusionsThe potential core neuroinflammation and associated signaling targets and pathways were identified using integrative network analysis on two large-scale transcriptomics datasets of AD.

Comparative Metabolomics Analysis Reveals the Unique Nutritional Characteristics of Breed and Feed on Muscles in Chinese Taihe Black-Bone Silky Fowl.

The Chinese Taihe Black-bone silky fowl (TBsf) is the homology of medicine and food and has high nutritional and medical value all over the world. However, the nutritional compositions and potential metabolite biomarkers of Taihe silky fowl in muscles are still poorly understood. In this study, we investigated the differences in nutritional components between TBsf and another similar breed (Black Feathered chicken and laid green-shelled eggs, BF-gsc). Meanwhile, we also explored the divergences in muscle characteristics of Taihe silky fowl fed with two different diets; that is, normal chicken feed (TBsf-ncf) and Broussonetia papyrifera-fermented feed (TBsf-bpf). Firstly, the growth performance and biochemical index of Taihe silky fowl was significantly different compared with black-feathered chicken. Secondly, we identified the metabolic alterations in Taihe silky fowl by performing an un-targeted UHPLC-Q-TOF-MS/MS analysis. Our results suggested that all the metabonomic characteristics had obvious separation between TBsf-ncf, TBsf-bpf and BF-gsc groups, both in the positive and negative ion mode by PCA analysis. Next, OPLS-DA multivariate analysis revealed that 57 metabolites (in positive mode) and 49 metabolites (in negative mode) were identified as differential metabolites between the TBsf-ncf and BF-gsc groups. These differential metabolites were mainly enriched to ABC transporters, biosynthesis of amino acids and aminoacyl-tRNA biosynthesis. Besides, 47 metabolites (in positive) and 13 metabolites (in negative) were differentially regulated between the TBsf-ncf and TBsf-bpf groups, which were majorly involved in histidine metabolism and linoleic metabolism. Furthermore, the integrated network analysis suggested that DL-arginine, DL-isoleucine, linoleoylcarnitine, stearoylcarnitine (positive) and ricionleic acid, D-proline, and uric acid (negative) were the significant metabolic biomarkers in Taihe silky fowl. Moreover, the metabolites of primaquine, ticlpoidine, riboflavin, acetylcarnitine (positive) and salicylic acid, acetaminophen sulfate, and glutamic acid (negative) were markedly changed in the Taihe silky fowl fed with BP-fermented feed. In summary, a global survey of the nutritional components and metabolite differences was performed in muscle tissues of Taihe silky fowl between various breeds and feeds. Meanwhile, our study provided valuable information for nutritional components and metabolic biomarkers in Chinese Taihe silky fowl, which greatly promoted the economic value of the black-boned chicken industry and laid a solid theoretical foundation for the development of chicken products with greater added value in future.

Analyzing integrated network of methylation and gene expression profiles in lung squamous cell carcinoma

Gene expression, DNA methylation, and their organizational relationships are commonly altered in lung squamous cell carcinoma (LUSC). To elucidate these complex interactions, we reconstructed a differentially expressed gene network and a differentially methylated cytosine (DMC) network by partial information decomposition and an inverse correlation algorithm, respectively. Then, we performed graph union to integrate the networks. Community detection and enrichment analysis of the integrated network revealed close interactions between the cell cycle, keratinization, immune system, and xenobiotic metabolism gene sets in LUSC. DMC analysis showed that hypomethylation targeted the gene sets responsible for cell cycle, keratinization, and NRF2 pathways. On the other hand, hypermethylated genes affected circulatory system development, the immune system, extracellular matrix organization, and cilium organization. By centrality measurement, we identified NCAPG2, PSMG3, and FADD as hub genes that were highly connected to other nodes and might play important roles in LUSC gene dysregulation. We also found that the genes with high betweenness centrality are more likely to affect patients’ survival than those with low betweenness centrality. These results showed that the integrated network analysis enabled us to obtain a global view of the interactions and regulations in LUSC.

Integrating pharmacokinetics and network analysis to investigate the mechanism of Moutan Cortex in blood-heat and blood stasis syndrome

BackgroundRaw Moutan Cortex (RMC) has been used in China and other Asian countries for thousands of years. Its medical application is the treatment of cooling blood and promoting blood circulation. However, its therapeutic mechanism is still undefined.MethodsIn this study, the pharmacokinetics strategy that integrated network analysis was employed to explore the mechanism of RMC in blood-heat and blood stasis syndrome (BHS) model rats. Firstly, Ultra-High performance Liquid Chromatography coupled with Diode Array Detector (UHPLC-DAD) method was developed to determine nine absorbed compounds in rat serum in BHS and normal rats after oral administration of RMC extract respectively. Then the pharmacology network was established based on the relationship between nine compounds absorbed into the blood and BHS targets. Finally, the predicted hub targets were validated experimentally in human umbilical vein endothelial cells (HUVECs).ResultsPharmacokinetic study showed that the pharmacokinetic parameters of nine absorbed compounds had significant differences between BHS and normal groups (p < 0.05). Network analysis showed that 8 target genes, namely, F2, F10, F7, PLAU, MAPK14, MAPK10, AKT1, and NOS3 may be the primary targets regulated by RMC for the treatment of BHS. Among them, targets (F2, F10, F7 and MAPK14, MAPK10, AKT) and 4 active ingredients (paeonol, paeoniflorin, quercetin and oxypaeoniflorin) were selected for evaluating the reliability in vitro experiments, which revealed that the mechanism of RMC against BHS syndrome may inhibit inflammatory pathways and regulate coagulation cascades pathway for cooling and promoting blood circulation.ConclusionThe proposed pharmacokinetics study integrated network analysis strategy provides a combination method to explore the therapeutic mechanism of RMC on BHS.Graphical

Detection of pan-cancer surface protein biomarkers via a network-based approach on transcriptomics data.

Cell surface proteins have been used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. Many of these proteins lie at the top of signaling cascades regulating cell responses and gene expression, therefore acting as 'signaling hubs'. It has been previously demonstrated that the integrated network analysis on transcriptomic data is able to infer cell surface protein activity in breast cancer. Such an approach has been implemented in a publicly available method called 'SURFACER'. SURFACER implements a network-based analysis of transcriptomic data focusing on the overall activity of curated surface proteins, with the final aim to identify those proteins driving major phenotypic changes at a network level, named surface signaling hubs. Here, we show the ability of SURFACER to discover relevant knowledge within and across cancer datasets. We also show how different cancers can be stratified in surface-activity-specific groups. Our strategy may identify cancer-wide markers to design targeted therapies and biomarker-based diagnostic approaches.

Integrative network analysis of circular RNAs reveals regulatory mechanisms for hepatic specification of human iPSC-derived endoderm

BackgroundHuman-induced pluripotent stem cell (hiPSC)-derived functional hepatic endoderm (HE) is supposed to be an alternative option for replacement therapy for end-stage liver disease. However, the high heterogeneity of HE cell populations is still challenging. Hepatic specification of definitive endoderm (DE) is an essential stage for HE induction in vitro. Recent studies have suggested that circular RNAs (circRNAs) determine the fate of stem cells by acting as competing endogenous RNAs (ceRNAs). To date, the relationships between endogenous circRNAs and hepatic specification remain elusive.MethodsThe identities of DE and HE derived from hiPSCs were determined by qPCR, cell immunofluorescence, and ELISA. Differentially expressed circRNAs (DEcircRNAs) were analysed using the Arraystar Human circRNA Array. qPCR was performed to validate the candidate DEcircRNAs. Intersecting differentially expressed genes (DEGs) of the GSE128060 and GSE66282 data sets and the DEcircRNA-predicted mRNAs were imported into Cytoscape for ceRNA networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were involved in the enrichment analysis. Hepatic markers and Wnt/β-catenin were detected in hsa_circ_004658-overexpressing cells by western blotting. Dual-luciferase reporter assays were used to evaluate the direct binding among hsa_circ_004658, miRNA-1200 and CDX2. DE cells were transfected with miR-1200 mimics, adenovirus containing CDX2, and Wnt/β-catenin was detected by western blotting.ResultshiPSC-derived DE and HE were obtained at 4 and 9 days after differentiation, as determined by hepatic markers. During hepatic specification, 626 upregulated and 208 downregulated DEcircRNAs were identified. Nine candidate DEcircRNAs were validated by qPCR. In the ceRNA networks, 111 circRNA–miRNA–mRNA pairs were involved, including 90 pairs associated with hsa_circ_004658. In addition, 53 DEGs were identified among the intersecting mRNAs of the GSE128060 and GSE66282 data sets and the hsa_circ_004658-targeted mRNAs. KEGG and GO analyses showed that the DEGs associated with hsa_circ_004658 were mainly enriched in the WNT signalling pathway. Furthermore, hsa_circ_004658 was preliminarily verified to promote hepatic specification, as determined by hepatic markers (AFP, ALB, HNF4A, and CK19) (p < 0.05). This promotive effect may be related to the inhibition of the Wnt/β-catenin signalling pathway (detected by β-catenin, p-β-catenin, and TCF4) when hsa_circ_004658 was overexpressed (p < 0.05). Dual-luciferase reporter assays showed that there were binding sites for miR-1200 in the hsa_circ_004658 sequence, and confirmed the candidate DEG (CDX2) as a miR-1200 target. The level of miR-1200 decreased and the level of CDX2 protein expression increased when hsa_circ_004658 was overexpressed (p < 0.05). In addition, the results showed that CDX2 may suppress the Wnt/β-catenin signalling during hepatic specification (p < 0.05).ConclusionsThis study analysed the profiles of circRNAs during hepatic specification. We identified the hsa_circ_004658/miR-1200/CDX2 axis and preliminarily verified its effect on the Wnt/β-catenin signalling pathway during hepatic specification. These results provide novel insight into the molecular mechanisms involved in hepatic specification and could improve liver development in the future.Graphical

Comprehensive proteomic analysis reveals dynamic phospho-profiling in human early erythropoiesis.

Normal early erythropoiesis depends on the precise regulation of protein expression and phosphorylation modification. Dysregulation of protein levels or modification contributes to erythroid disorders. To date, the dynamics of protein phosphorylation profiling across human erythroid development is not fully understood. Here, we characterized quantitative proteomic and phosphoproteomic profiling by tandem mass-tagging technology. We systemically built phospho-expression profiling and expression clusters of 11 414 phosphopeptides for human early erythropoiesis. The standardization methods for multitier integrative analyses revealed multiple functional modules of phosphoproteins (e.g., regulation of the G2/M transition) and active phosphorylated signalling (e.g., cell cycle-related pathways). Our further analysis revealed that CDK family members were the main kinases that phosphorylate substrates in erythroid progenitors and identified that CDK9 played an important role in the proliferation of erythroid progenitors. Collectively, our phosphoproteomic profiling, integrative network analysis and functional studies define landscapes of the phosphoproteome and reveal signalling pathways that are involved in human early erythropoiesis. This study will serve as a valuable resource for further investigations of phosphatase and kinase functions in human erythropoiesis and erythroid-related diseases.

Antibiotic-induced microbiome depletion improves LPS-induced acute lung injury via gut-lung axis

AimsAcute lung injury (ALI) is an acute inflammatory disorder. However, the precise mechanisms underlying the pathology of ALI remain elusive. An increasing evidence suggests the role of the gut-microbiota axis in the pathology of lung injury. This study aimed to investigate whether antibiotic-induced microbiome depletion could affect ALI in mice after lipopolysaccharide (LPS) administration. Main methodsThe effects of antibiotic cocktail (ABX) on ALI in the mice after intratracheally administration of LPS (5 mg/kg) were examined. Furthermore, 16s rRNA analysis and measurement of short-chain fatty acids in feces samples and metabolomics analysis of blood samples were performed. Key findingsLPS significantly increased the interleukin-6 (IL-6) levels in the bronchoalveolar lavage fluid (BALF) of water-treated mice. Interestingly, an ABX significantly attenuated the LPS-induced increase in IL-6 in BALF and lung injury scores. Furthermore, ABX and/or LPS treatment markedly altered the α- and β-diversity of the gut microbiota. There were significant differences in the α- and β-diversity of the water + LPS group and ABX + LPS group. LEfSe analysis identified Enterococusfaecalis, Clostriumtertium, and Bacteroidescaecimyris as potential microbial markers for ABX + LPS group. Untargeted metabolomics analysis identified several plasma metabolites responsible for discriminating water + LPS group from ABX + LPS group. There were correlations between the relative abundance of the microbiome and plasma metabolites. Integrative network analysis showed correlations between IL-6 levels in BALF and several gut microbes (or plasma metabolites). SignificanceThese data suggest that ABX-induced microbiome depletion could protect against LPS-induced ALI via the gut-microbiota-lung axis.