Predicted Interaction Network Research Articles

Characterization of plasma-derived small extracellular vesicle miRNA and protein cargo in hereditary angioedema

Hereditary angioedema (HAE) is an inherited disorder causing attacks of subcutaneous tissue or mucosa swelling. The disease burden and attack frequencies vary significantly among patients. This is the first pilot study investigating small extracellular vesicles (sEV) as potential disease modulators in HAE.Plasma-derived sEVs from HAE patients and healthy donors (HD) were thoroughly characterized by Western blot, transmission electron microscopy, nanoparticle tracking and bead-based flow cytometry. The miRNA content of sEVs was examined by nCounter technology and used to predict sEV-based pathomechanisms in silico. All sEV readouts were analyzed regarding HAE-related changes and associations with clinical parameters and attack frequency.Total sEV protein levels were elevated in HAE patients compared to HD. In HAE patients, lower levels of sEVs carrying CD8, CD209, CD81, CD24 and CD44 were measured. sEV miRNA profiling revealed 84 HAE-exclusive and 30 significantly HAE-upregulated candidates. Core hubs of their predicted interaction networks were AGO2, VEGF, RGS5, MTA1, IFG1 and BAX. A set of 12 and 36 sEV miRNAs were restricted to patients with absent attacks or patients with present attacks during prophylactic therapy, respectively.sEVs, especially sEV miRNAs, could contribute to disease pathogenesis and differential attack frequencies. They emerged as disease modulators in HAE and require further study to reveal underlying mechanisms.

Isolation and Characterization of Phenylalanine Ammonia Lyase (PAL) Genes in Ferula pseudalliacea: Insights into the Phenylpropanoid Pathway.

Phenylalanine ammonia lyase (PAL) is a key enzyme regulating the biosynthesis of the compounds of the phenylpropanoid pathway. This study aimed to isolate and characterize PAL genes from Ferula pseudalliacea Rech.f. (Apiales: Apiaceae) to better understand the regulation of metabolite production. Three PAL gene isoforms (FpPAL1-3) were identified and cloned using the 3'-RACE technique and confirmed by sequencing. Bioinformatics analysis revealed important structural features, such as phosphorylation sites, physicochemical properties, and evolutionary relationships. Expression analysis by qPCR demonstrated the differential transcription profiles of each FpPAL isoform across roots, stems, leaves, flowers, and seeds. FpPAL1 showed the highest expression in stems, FpPAL2 in roots and flowers, and FpPAL3 in flowers. The presence of three isoforms of PAL in F. pseudalliacea, along with the diversity of PAL genes and their tissue-specific expression profiles, suggests that complex modes of regulation exist for phenylpropanoid biosynthesis in this important medicinal plant. The predicted interaction network revealed associations with key metabolic pathways, emphasizing the multifaceted roles of these PAL genes. In silico biochemical analyses revealed the hydrophilicity of the FpPAL isozyme; however, further analysis of substrate specificity and enzyme kinetics can clarify the specific role of each FpPAL isozyme. These comprehensive results increase the understanding of PAL genes in F. pseudalliacea, helping to characterize their contributions to secondary metabolite biosynthesis.

Integrating miRNA and full-length transcriptome profiling to elucidate the mechanism of muscle growth in Muscovy ducks reveals key roles for miR-301a-3p/ANKRD1

BackgroundThe popularity of Muscovy ducks is attributed not only to their conformation traits but also to their slightly higher content of breast and leg meat, as well as their stronger-tasting meat compared to that of typical domestic ducks. However, there is a lack of comprehensive systematic research on the development of breast muscle in Muscovy ducks. In addition, since the number of skeletal muscle myofibers is established during the embryonic period, this study conducted a full-length transcriptome sequencing and microRNA sequencing of the breast muscle. Muscovy ducks at four developmental stages, namely Embryonic Day 21 (E21), Embryonic Day 27 (E27), Hatching Day (D0), and Post-hatching Day 7 (D7), were used to isolate total RNA for analysis.ResultsA total of 68,161 genes and 472 mature microRNAs were identified. In order to uncover deeper insights into the regulation of mRNA by miRNAs, we conducted an integration of the differentially expressed miRNAs (known as DEMs) with the differentially expressed genes (referred to as DEGs) across various developmental stages. This integration allowed us to make predictions regarding the interactions between miRNAs and mRNA. Through this analysis, we identified a total of 274 DEGs that may serve as potential targets for the 68 DEMs. In the predicted miRNA‒mRNA interaction networks, let-7b, miR-133a-3p, miR-301a-3p, and miR-338-3p were the hub miRNAs. In addition, multiple DEMs also showed predicted target relationships with the DEGs associated with skeletal system development. These identified DEGs and DEMs as well as their predicted interaction networks involved in the regulation of energy homeostasis and muscle development were most likely to play critical roles in facilitating the embryo-to-hatchling transition. A candidate miRNA, miR-301a-3p, exhibited increased expression during the differentiation of satellite cells and was downregulated in the breast muscle tissues of Muscovy ducks at E21 compared to E27. A dual-luciferase reporter assay suggested that the ANKRD1 gene, which encodes a transcription factor, is a direct target of miR-301a-3p.ConclusionsmiR-301a-3p suppressed the posttranscriptional activity of ANKRD1, which is an activator of satellite cell proliferation, as determined with gain- and loss-of-function experiments. miR-301a-3p functions as an inducer of myogenesis by targeting the ANKRD1 gene in Muscovy ducks. These results provide novel insights into the early developmental process of black Muscovy breast muscles and will improve understanding of the underlying molecular mechanisms.

Genome-Wide Identification and Expression Pattern Profiling of the Aquaporin Gene Family in Papaya (Carica papaya L.).

Aquaporins (AQPs) are mainly responsible for the transportation of water and other small molecules such as CO2 and H2O2, and they perform diverse functions in plant growth, in development, and under stress conditions. They are also active participants in cell signal transduction in plants. However, little is known about AQP diversity, biological functions, and protein characteristics in papaya. To better understand the structure and function of CpAQPs in papaya, a total of 29 CpAQPs were identified and classified into five subfamilies. Analysis of gene structure and conserved motifs revealed that CpAQPs exhibited a degree of conservation, with some differentiation among subfamilies. The predicted interaction network showed that the PIP subfamily had the strongest protein interactions within the subfamily, while the SIP subfamily showed extensive interaction with members of the PIP, TIP, NIP, and XIP subfamilies. Furthermore, the analysis of CpAQPs' promoters revealed a large number of cis-elements participating in light, hormone, and stress responses. CpAQPs exhibited different expression patterns in various tissues and under different stress conditions. Collectively, these results provided a foundation for further functional investigations of CpAQPs in ripening, as well as leaf, flower, fruit, and seed development. They also shed light on the potential roles of CpAQP genes in response to environmental factors, offering valuable insights into their biological functions in papaya.

Degron Pathways and Leishmaniasis: Debating Potential Roles of Leishmania spp. Proteases Activity on Guiding Hosts Immune Response and Their Relevance to the Development of Vaccines.

Degrons are short peptide sequences that signalize target sites for protein degradation by proteases. Herein, we bring forth the discussion on degrons present in proteins related to the immune system of Mus musculus that are potential targets for cysteine and serine proteases of Leishmania spp. and their possible roles on host immune regulation by parasites. The Merops database was used to identify protease substrates and proteases sequence motifs, while MAST/MEME Suite was applied to find degron motifs in murine cytokines (IFN-y, IL-4, IL-5, IL-13, IL-17) and transcription factors (NF-kappaB, STAT-1, AP-1, CREB, and BACH2). STRING tool was used to construct an interaction network for the immune factors and SWISS-MODEL server to generate three-dimensional models of proteins. In silico assays confirm the occurrence of degrons in the selected immune response factors. Further analyses were conducted only in those with resolved three-dimensional structures. The predicted interaction network of degron-containing M. musculus proteins shows the possibility that the specific activity of parasite proteases could interfere with the trend of Th1/Th2 immune responses. Data suggest that degrons may play a role in the immune responses in leishmaniases as targets for parasite proteases activity, directing the degradation of specific immune-related factors.

Identification of genetic variants associated with diabetic kidney disease in multiple Korean cohorts via a genome-wide association study mega-analysis

BackgroundThe pathogenesis of diabetic kidney disease (DKD) is complex, involving metabolic and hemodynamic factors. Although DKD has been established as a heritable disorder and several genetic studies have been conducted, the identification of unique genetic variants for DKD is limited by its multiplex classification based on the phenotypes of diabetes mellitus (DM) and chronic kidney disease (CKD). Thus, we aimed to identify the genetic variants related to DKD that differentiate it from type 2 DM and CKD.MethodsWe conducted a large-scale genome-wide association study mega-analysis, combining Korean multi-cohorts using multinomial logistic regression. A total of 33,879 patients were classified into four groups—normal, DM without CKD, CKD without DM, and DKD—and were further analyzed to identify novel single-nucleotide polymorphisms (SNPs) associated with DKD. Additionally, fine-mapping analysis was conducted to investigate whether the variants of interest contribute to a trait. Conditional analyses adjusting for the effect of type 1 DM (T1D)-associated HLA variants were also performed to remove confounding factors of genetic association with T1D. Moreover, analysis of expression quantitative trait loci (eQTL) was performed using the Genotype-Tissue Expression project. Differentially expressed genes (DEGs) were analyzed using the Gene Expression Omnibus database (GSE30529). The significant eQTL DEGs were used to explore the predicted interaction networks using search tools for the retrieval of interacting genes and proteins.ResultsWe identified three novel SNPs [rs3128852 (P = 8.21×10−25), rs117744700 (P = 8.28×10−10), and rs28366355 (P = 2.04×10−8)] associated with DKD. Moreover, the fine-mapping study validated the causal relationship between rs3128852 and DKD. rs3128852 is an eQTL for TRIM27 in whole blood tissues and HLA-A in adipose-subcutaneous tissues. rs28366355 is an eQTL for HLA-group genes present in most tissues.ConclusionsWe successfully identified SNPs (rs3128852, rs117744700, and rs28366355) associated with DKD and verified the causal association between rs3128852 and DKD. According to the in silico analysis, TRIM27 and HLA-A can define DKD pathophysiology and are associated with immune response and autophagy. However, further research is necessary to understand the mechanism of immunity and autophagy in the pathophysiology of DKD and to prevent and treat DKD.

A Genome-Wide Association Study of Genetic Variants of Apolipoprotein A1 Levels and Their Association with Vitamin D in Korean Cohorts.

Dyslipidemia is an important independent risk factor for cardiovascular disease (CVD). Specifically, apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), and the ApoB/A1 ratio have been linked to CVD. We conducted a genome-wide association study meta-analysis of two Korean cohorts containing a total of 12,924 patients to identify novel single nucleotide polymorphisms (SNPs) associated with ApoA1 and ApoB levels and the ApoB/A1 ratio. Additionally, an expression quantitative trait locus (eQTL) and differentially expressed genes (DEGs) analysis were performed. The statistically significant eQTL, DEG, and Gene Ontology (GO) results were used to explore the predicted interaction networks and retrieve the interacting genes and proteins. We identified three novel SNPs (rs11066280, p = 3.46 ; rs1227162, p = 2.98 ; rs73216931, p = 5.62 ) associated with ApoA1. SNP rs73216931 was an eQTL for KMT5A in the pancreas and whole blood. The network analysis revealed that HECTD4 and MYL2:LINC1405 are associated with AKT1. Our in silico analysis of ApoA1 genetic variants revealed heart muscle-related signals. ApoA1 also correlated positively with vitamin D, and genes associated with ApoA1 and vitamin D were found. Our data imply that more research into ApoA1 is needed to understand the links between dyslipidemia and CVD and vitamin D and CVD.

In vitro and in silico assessment of cytotoxicity and chromosome instability induced by saxitoxin in human derived neural cell line

In freshwater, saxitoxins (STX) are produced by different cyanobacteria genera, including Raphidiopsis. Data regarding cytogenotoxicity effects of STX on human cells are scarse, this merit further studies of its toxicology. This study assessed the cytotoxicity and the chromosome instability of STX on SHSY-5Y human cell line. The CBMN assay allows the detection of chromosome breaks and abnormal chromosomal segregation. Additionally, in silico systems biology approach, used to search for known and predicted interaction networks, was applied to study the interactions between STX and SHSY-5Y cellular components. The results of the CBMN assay demonstrated that STX concentrations of 2.5 - 10 µg/L induced cytostasis and chromosome instability in a dose-response relationship. Apoptosis was detected after exposure of SHSY-5Y cultured cells to STX concentration of 10 µg/L. The results of the systems biology analysis revealed the interaction of STX with proteins related with acetylcoline pathway, cell cycle regulation and apoptosis. Furthermore, combining the in vitro and in silico approachs, it was possible to suggest a mechanism of action of STX in SHSY-5Y cells. Overall, the data demonstrated the cytotoxicity and mutagenicity of environmentally relevant concentrations of STX. These results should be considered when setting up guidelines for monitoring STX in water supply.

Investigation of gene expression and genetic simultaneous control associated with erectile dysfunction and diabetes.

Diabetes can cause some diseases or abnormalities. One of the disorders caused by diabetes may be erectile dysfunction (ED). ED is sexual dysfunction characterized by the inability to establish or maintain an erect penis during sexual activity and is a common problem of men with chronic type 2 diabetes. These processes, disorders and diseases are highly influenced by the genetics of individuals. In this study, the relationship between genes and diabetes and ED has been explored by a system biology approach. For this purpose, the samples from ten control and diabetic-ED rats were collected. After a search in Gene Expression Omnibus (GEO), series with accession numberGSE2457 comprising of 5 normal and 5 diabetic-ED rats were selected. Raw CEL files of these samples were normalized with robust multi-array average (RMA) expression measure method by using the linear models for microarray data (LIMMA) R package. The extracted probe IDs were transformed into 10451 unique and validated official gene symbols. Then, differentially expressed genes (DEGs) were identified between control and normal penile mucosa by employing the LIMMA R package. DEGs were classified by utilizing KEGG to underlying pathways by Enrichr. The expression values of DEGs were used to construct a gene regulatory network (GRN), by the GENEI3 R package. To analyze the topology of constructed GRNs, betweenness centrality was calculated. Genes with higher betweenness centrality scores were then identified, through the CytoNCA. We then took the commonality of DEGs genes and high-top ranking genes from CytoNCA via a predicted interaction network using GeneMANIAas the most likely important genes in erectile dysfunction. Among the 374 DEGs studied, 146 DEGs showed up-regulation and 228 DEGs displayed down-regulation expression in diabetic-ED rats. According to the Volcano plot, the dpp4, LOC102553868, Ndufa412, Oxct1, Atp2b3 and Zfp91 gene down-regulated and Lpl, Retsat, B4galt1 and Pdk4 genes up-regulated in ED and diabetic rats. Furthermore, genes like dpp4 acted as hubs in the inferred GRN.

Integrated mRNA and miRNA transcriptome analysis provides novel insights into the molecular mechanisms underlying goose pituitary development during the embryo-to-hatchling transition

It is well established that the endocrine system plays a pivotal role in preparing the avian embryos for the abrupt switch from chorioallantoic to pulmonary respiration during the critical embryo-to-hatchling transition. However, as the master gland of the endocrine system, there has been little research focusing on the molecular mechanisms controlling the development and function of the pituitary gland during the peri-hatch period in birds. In the present study, we aimed to determine the genome-wide mRNA and miRNA transcriptome profiles of the pituitary during the embryo-to-hatchling transition period from embryonic day 22 (E22) to post-hatching day 6 (P6) in the goose (Anser cygnoides). Of note, expression of Anser_cygnoides_newGene_32456 and LOC106031011 were significantly different among these 4 stages (i.e., E22, E26, P2, and P6). Meanwhile, the neuroactive ligand-receptor interaction pathway was significantly enriched by the DEGs commonly identified among three pairwise comparisons. At the miRNA transcriptome level, there were not commonly identified DE miRNAs among these 4 stages, while the 418 of their predicted target genes were mutually shared. Both the target genes of DE miRNAs in each comparison and these 418 shared target genes were significantly enriched in the ECM-receptor interaction and focal adhesion pathways. In the predicted miRNA-mRNA interaction networks of these 2 pathways, novel_miRNA_467, novel_miRNA_154, and novel_miRNA_340 were the hub miRNAs. In addition, multiple DE miRNAs also showed predicted target relationships with the DEGs associated with extracellular matrix (ECM) components. Among them, expression of novel_miR_120, tgu-miR-92-3p, and novel_miR_398 was significantly negatively correlated with that of LAMC3 (laminin subunit gamma3), suggesting that these miRNAs may regulate pituitary tissue remodeling and functional changes through targeting LAMC3 during development. These identified DE mRNAs and miRNAs as well as their predicted interaction networks involved in regulation of tissue remodeling and cellular functions were most likely to play critical roles in facilitating the embryo-to-hatchling transition. These results provide novel insights into the early developmental process of avian pituitary gland and will help better understand the underlying molecular mechanisms.

Long noncoding RNAs profiling in ovary during laying and nesting in Muscovy ducks (Cairina moschata)

There are recent reports of the important functions of long noncoding RNAs (lncRNAs) in female reproductive and ovarian development. Studies in which there was characterization of lncRNAs in the ovaries of laying compared with nesting poultry, however, are limited. In this study, RNA libraries were constructed by obtaining sequencing data of ovarian tissues from laying and nesting Muscovy ducks. In the ovarian tissues of Muscovy ducks, a total of 334 differentially abundant mRNA transcripts (DEGs) and 36 differentially abundant lncRNA transcripts were identified in the nesting period, when compared with during the laying period. These results were subsequently validated by qRT-PCR using nine randomly-selected lncRNAs and six randomly-selected DAMTs. Furthermore, the cis- and trans-regulatory target genes of differentially abundant lncRNA transcripts were identified, and lncRNA-gene interaction networks of 34 differentially abundant lncRNAs and 263 DEGs were constructed. A total of 7601 lncRNAs neighboring 10,542 protein-coding genes were identified and found to be enriched in the Wnt signaling pathway and oocyte meiosis pathways associated with follicular development. Overall, only 11 cis-targets and 57 mRNA-mRNA except trans-targets were involved in the lncRNA-gene interaction networks. Based on the interaction networks, nine DEGs were trans-regulated by differentially abundant lncRNAs and 20 differentially abundant lncRNAs were hypothesized to have important functions in the regulation of broodiness in Muscovy ducks. In this study, a predicted interaction network of differentially abundant lncRNAs and DEGs in Muscovy ducks was constructed for the first time leading to an enhanced understanding of lncRNA and gene interactions regulating broodiness.

Transcriptomic investigation of embryonic pectoral muscle reveals increased myogenic processes in Shitou geese compared to Wuzong geese

ABSTRACT 1.Embryonic stages before birth are crucial for poultry muscle development, as this determines muscle mass in adulthood. This study characterised the distinction in embryonic pectoral muscle development between Wuzong (WZE, small) and Shitou (STE, large) geese (two indigenous goose breeds in Guangdong Province, China) at embryonic days 15 (E15), 23 (E23) and the day of hatching (P1) to gain insights into the regulatory mechanisms of muscle development. 2.The results showed that STE had significantly higher myofibre density during E15-P1 and had significantly larger myofibre diameter at E15 than WZE. By RNA-sequencing analysis, 19 507 genes were detected, and 7121 differentially expressed genes (DEGs) were identified. 3.Gene expression distinctions between breeds began increasing from E23, and WZE had different gene expression profiles compared to STE. A GO analysis of DEGs indicated that myo-genes involved at E15 may influence distinct pectoral muscle development characteristics between WZE and STE. The RT-qPCR results were consistent with the RNA-sequencing analysis. Four muscle structure protein coding genes (MYL2, MYL3, TNNI2 and TNNC2 and three other functional genes (CAV3, CACNA1S and NOS1) were identified in a predicted interaction network. These functional genes may interact with muscle structural protein coding genes to regulate embryonic pectoral muscle development in WZE and STE geese. 4.The study revealed that STE and WZE had divergent embryonic pectoral muscle development patterns and these differences may begin before E15.

Fragmented tropical forests lose mutualistic plant–animal interactions

AbstractAimForest fragmentation is among the principal causes of global biodiversity loss, yet how it affects mutualistic interactions between plants and animals at large spatial scale is poorly understood. In particular, tropical forest regeneration depends on animal‐mediated seed dispersal, but the seed‐dispersing animals face rapid decline due to forest fragmentation and defaunation. Here, we assess how fragmentation influences the pairwise interactions between 407 seed disperser and 1,424 tree species in a highly fragmented biodiversity hotspot.LocationAtlantic Forest, South America.MethodsWe predicted interaction networks in 912 sites covering the entire biome by combining verified interaction data with co‐occurrence probabilities obtained from a spatially explicit joint species distribution model. We identified keystone seed dispersers by computing a species‐specific keystone index and by selecting those species belonging to the top 5% quantile.ResultsWe show that forest fragmentation affects seed dispersal interactions negatively, and the decreased area of functionally connected forest, rather than increased edge effects, is the main driver behind the loss of interactions. Both the seed disperser availability for the local tree communities and in particular the proportion of interactions provided by keystone seed dispersers decline with increasing degree of fragmentation. Importantly, just 21 keystone species provided >40% of all interactions. The numbers of interactions provided by keystone and non‐keystone species, however, were equally negatively affected by fragmentation, suggesting that seed dispersal interactions may not be rewired under strong fragmentation effects.ConclusionsWe highlight the importance of understanding the fragmentation‐induced compositional shifts in seed disperser communities as they may lead to lagged and multiplicative effects on tree communities. Our results illustrate the utility of model‐based prediction of interaction networks as well as model‐based identification of keystone species as a tool for prioritizing conservation efforts. Similar modelling approaches could be applied to other threatened ecosystems and interaction types globally.

Comparative Analysis of the Ultrastructure Between Discoid and Normal-Shaped Lateral Meniscus

Background: Discoid lateral meniscus (DLM) has long been observed and diagnosed in clinic, whereas its etiology and pathology remain unclear. The aim of this study is to investigate the difference of ultrastructure as regard to cell function and protein expression profile between DLM and normal-shaped lateral meniscus (NLM). Methods and Results: By using the iIsobaric tags for relative and absolute quantification (iTRAQ)-based proteomic analysis was performed to detect the difference of protein profiling between DLM and NLM. Expression of the representative differentially expressed proteins (DEPs) was validated by western blotting and immunohistochemistry (IHC) assays. Gene ontology (GO) enrichment analysis and predicted interaction network were conducted to investigate the biological processes involved. Meanwhile, meniscus cells were isolated from DLM and NLM tissues and processed for proliferation assay and gene expression analysis. Findings: 1314 proteins in total were identified in the inner 2/3 part of DLM and normal-shaped lateral meniscus (NLM) specimens. 21 of them were up-regulated while 4 were down-regulated in the DLM group. Western blotting and IHC assays validated increased Expression expression of fibronectin (FN), periostin (POSTN) and, type IV collagenase (MMP-2) and while decreased expression of hemoglobin subunit beta (HBB) were validated byin DLM compared to those in NLM. western blotting and immunohistochemistry (IHC) assays. Gene ontology (GO) enrichment analysis and predicted interaction network of the differentially expressed proteins (DEPs) indicated that the DEPs were primarily involved in the molecular function of binding and transporting, mediating biological processes such as extracellular matrix (ECM) remolding, response to stimulus and angiogenesis. Proliferation potential Meniscus cells fromof DLM cells was demonstrated to be higher proliferation potential than those fromthat of NLM cells. Compared to mRNA expression in NLM cells, eExpression level of collagen I and aggrecan mRNAs were higher while expressionthat of collagen II and osteocalcin (OC) mRNAs were lower in DLM cells than in NLM cells. No significant difference of mRNA expression of FN, integrin V, integrin 1, POSTN, MMP-2 and HBB was observed between two groups. Interpretation: Ultrastructure of DLM was quite different from that of NLM. Cell proliferation potential and mRNA expression of aggrecan and collagen I were increased in DLM, synthesis of DEPs such as FN, POSTN and MMP-2 were increased while HBB was decreased. In addition, biological processes such as ECM remolding, response to stimulus and angiogenesis had been abnormally activated in DLM. Funding Statement: This study was supported by the National Natural Science Foundations of China (81501852, 81472046, 81271942, 81802200, 81472045), by the Distinguished Youth Foundation of Peking Union Medical College Hospital (JQ201506), by the Beijing nova program (2016), by the Central Level Public Interest Program for Scientific Research Institute (No.13, 2015), by the Basic Scientific Research Business Project of Central Public-interest Scientific Institution of Chinese Academy of Medical Sciences (2015PT320013), and by the National Key R&D program of China (2018YFF0301105). Declaration of Interests: All the authors declare no conflicts of interests. Ethics Approval Statement: Written informed consents were received from all the patients prior to their participation in the study. This study was approved by the Ethical Committee of Clinical Investigation of PUMCH.

Genotoxicity of zinc oxide nanoparticles: an in vivo and in silico study.

Zinc oxide (ZnO) NPs are being used worldwide in consumer products and industrial applications. Based on predefined pathways, this study synthesized and characterized the nanostructures of ZnO NPs. The genotoxic effects of these nanomaterials were evaluated using a short-term in vivo bioassay, the somatic mutation and recombination test (SMART) in Drosophila melanogaster. In addition, a systems biology approach was used to search for known and predicted interaction networks between ZnO and proteins. The results observed in this study after in vivo exposure indicate that ZnO NPs are genotoxic and that homologous recombination (HR) was the main mechanism inducing loss of heterozygosis in the somatic cells of D. melanogaster. The results of in silico analysis indicated that ZnO is associated with the nuclear factor-kappa-beta (NFKB) protein family. In accordance with this model, ZnO exposure decreases the levels of NFKB inhibitory protein in the cell, consequently increasing NFKB dimers in the nucleus and inducing DNA double strand breaks (DSB) repair via HR. This excess level of HR can be observed in the SMART results. Assessing the mutagenic/recombinagenic effect of nanomaterials is essential in the development of strategies to protect human and environmental integrity.

MiR-30 Family Potentially Targeting PI3K-SIAH2 Predicted Interaction Network Represents a Novel Putative Theranostic Panel in Non-small Cell Lung Cancer.

Non-small cell lung cancer (NSCLC) comprises about 84% of all lung cancers. Many treatment options are available but the survival rate is still very low due to drug resistance. It has been found that phosphoinositide-3-kinase (PI3K) affects sensitivity to tyrosine kinase inhibitors (TKIs), including gefitinib and erlotinib. Expression level of seven in absentia homolog 2 (SIAH2), an E3 ubiquitin-protein ligase, is upregulated in NSCLC and correlated with tumor grade. However, the relationship between PI3K and SIAH2 remains unclear and therefore it is not known whether they can act as treatment co-targets and theranostic dual markers for overcoming TKI resistance. It is worthy to note that PI3K and SIAH2 are potentially regulated by a common group of microRNAs in miR-30 family. Our bioinformatics analyses showed upregulated SIAH2 expression in NSCLC based on mass spectrometry data, explored its indirect interaction with PI3K and predicted their targeting microRNAs in common. We have also explored the potential role of miR-30 family in the modulation of PI3K-SIAH2 interaction in NSCLC.

Unraveling Molecular Differences of Gastric Cancer by Label-Free Quantitative Proteomics Analysis.

Gastric cancer (GC) has significant morbidity and mortality worldwide and especially in China. Its molecular pathogenesis has not been thoroughly elaborated. The acknowledged biomarkers for diagnosis, prognosis, recurrence monitoring and treatment are lacking. Proteins from matched pairs of human GC and adjacent tissues were analyzed by a coupled label-free Mass Spectrometry (MS) approach, followed by functional annotation with software analysis. Nano-LC-MS/MS, quantitative real-time polymerase chain reaction (qRT-PCR), western blot and immunohistochemistry were used to validate dysregulated proteins. One hundred forty-six dysregulated proteins with more than twofold expressions were quantified, 22 of which were first reported to be relevant with GC. Most of them were involved in cancers and gastrointestinal disease. The expression of a panel of four upregulated nucleic acid binding proteins, heterogeneous nuclear ribonucleoprotein hnRNPA2B1, hnRNPD, hnRNPL and Y-box binding protein 1 (YBX-1) were validated by Nano-LC-MS/MS, qRT-PCR, western blot and immunohistochemistry assays in ten GC patients’ tissues. They were located in the keynotes of a predicted interaction network and might play important roles in abnormal cell growth. The label-free quantitative proteomic approach provides a deeper understanding and novel insight into GC-related molecular changes and possible mechanisms. It also provides some potential biomarkers for clinical diagnosis.

Analysis of differentially expressed genes in malignant biliary strictures.

Microarray data were collected from bile duct samples from subjects with malignant biliary strictures by endoscopic retrograde cholangiopancreatography to screen for key genes associated with this disease. A predicted interaction network was constructed for these genes to interpret their functions. The gene expression dataset GSE34166 (10 samples: 6 malignant and 4 benign control samples) was downloaded from the Gene Expression Omnibus database. R package scripts were used to process the data and screen for differentially expressed genes. Genes identified were uploaded to the analysis tool String 8.3 to generate a gene interaction network. A hub gene was identified by calculating the node degree. The interaction network of the hub gene with other genes in the human genome was constructed and screened (score >0.9), and pathway-enrichment analysis was performed to elucidate the hub gene function. In total, 377 differentially expressed genes were identified and a network comprising 209 pairs of interactions was constructed. The most critical hub gene was identified as GSTA1, and a GSTA1-based interaction network was constructed consisting of 25 genes (containing the differentially expressed gene GSTA3). The cytochrome P450 (CYP450)-metabolic pathway displayed the most significant enrichment. Additionally, 4 transcription factors and their binding sites were also identified. In conclusion, we have identified the differentially expressed genes GSTA1 (a hub gene) and GSTA3, which may cause abnormal gene expression and tumorigenesis through CYP450-metabolic pathways. The transcription factors and their binding sites in the promoter of the hub gene provide potential directions for future drug design.

Predicting whole genome protein interaction networks from primary sequence data in model and non-model organisms using ENTS

BackgroundThe large-scale identification of physical protein-protein interactions (PPIs) is an important step toward understanding how biological networks evolve and generate emergent phenotypes. However, experimental identification of PPIs is a laborious and error-prone process, and current methods of PPI prediction tend to be highly conservative or require large amounts of functional data that may not be available for newly-sequenced organisms.ResultsIn this study we demonstrate a random-forest based technique, ENTS, for the computational prediction of protein-protein interactions based only on primary sequence data. Our approach is able to efficiently predict interactions on a whole-genome scale for any eukaryotic organism, using pairwise combinations of conserved domains and predicted subcellular localization of proteins as input features. We present the first predicted interactome for the forest tree Populus trichocarpa in addition to the predicted interactomes for Saccharomyces cerevisiae, Homo sapiens, Mus musculus, and Arabidopsis thaliana. Comparing our approach to other PPI predictors, we find that ENTS performs comparably to or better than a number of existing approaches, including several that utilize a variety of functional information for their predictions. We also find that the predicted interactions are biologically meaningful, as indicated by similarity in functional annotations and enrichment of co-expressed genes in public microarray datasets. Furthermore, we demonstrate some of the biological insights that can be gained from these predicted interaction networks. We show that the predicted interactions yield informative groupings of P. trichocarpa metabolic pathways, literature-supported associations among human disease states, and theory-supported insight into the evolutionary dynamics of duplicated genes in paleopolyploid plants.ConclusionWe conclude that the ENTS classifier will be a valuable tool for the de novo annotation of genome sequences, providing initial clues about regulatory and metabolic network topology, and revealing relationships that are not immediately obvious from traditional homology-based annotations.

Using biotic interaction networks for prediction in biodiversity and emerging diseases.

Networks offer a powerful tool for understanding and visualizing inter-species ecological and evolutionary interactions. Previously considered examples, such as trophic networks, are just representations of experimentally observed direct interactions. However, species interactions are so rich and complex it is not feasible to directly observe more than a small fraction. In this paper, using data mining techniques, we show how potential interactions can be inferred from geographic data, rather than by direct observation. An important application area for this methodology is that of emerging diseases, where, often, little is known about inter-species interactions, such as between vectors and reservoirs. Here, we show how using geographic data, biotic interaction networks that model statistical dependencies between species distributions can be used to infer and understand inter-species interactions. Furthermore, we show how such networks can be used to build prediction models. For example, for predicting the most important reservoirs of a disease, or the degree of disease risk associated with a geographical area. We illustrate the general methodology by considering an important emerging disease - Leishmaniasis. This data mining methodology allows for the use of geographic data to construct inferential biotic interaction networks which can then be used to build prediction models with a wide range of applications in ecology, biodiversity and emerging diseases.