不同抗性苹果品种应答轮纹病菌胁迫的差异蛋白质组分析

为鉴定不同抗性苹果(Malus domestica)品种响应轮纹病菌胁迫的抗性相关蛋白表达差异, 以抗病品种华月及易感品种金冠为试材, 采用高通量同位素标记定量(IBT)技术结合液相色谱-串联质谱(LC-MS)鉴定技术, 对病原菌处理前后抗、感病品种叶片的蛋白质组差异表达进行分析, 共鉴定出171个差异表达蛋白(DEPs)。GO富集及KEGG通路分析表明, 在细胞组分、分子功能和生物过程3类中共注释到686个GO条目, 其中52个DEPs注释于KEGG通路的18个显著差异途径(P<0.05)。亚细胞定位预测分析表明, 171个DEPs中有170个分别定位于8类细胞器。蛋白功能注释分析表明, 46个DEPs注释于7类抗性相关蛋白, 包括类甜蛋白、过氧化物酶、多酚氧化酶、过敏原蛋白、几丁质酶、内切葡聚糖酶以及主乳胶蛋白。此外, 还对抗性相关蛋白的表达特点及基因定量结果进行了分析。该研究结果可为进一步解析抗、感病苹果品种应答轮纹病菌胁迫的抗性机制提供参考。     

Quantitative proteomics analysis of human vitreous in rhegmatogenous retinal detachment associated with choroidal detachment by data-independent acquisition mass spectrometry

The prognosis of rhegmatogenous retinal detachment (RRD) with choroidal detachment (RRDCD) is often poor and complicated. This study focused on the identification of the characteristic proteins and signal pathways associated with the etiology of RRDCD and to provide guidance for diagnosis and treatment of RRDCD. In this study, vitreous humor samples were obtained from 16 RRDCD patients, 14 with RRD, 12 with idiopathic epiretinal macular membrane (IEMM), and 5 healthy controls from donated corpse eyes. Data-independent acquisition mass spectrometry and bioinformatics analysis were employed to identify differentially expressed proteins (DEPs). In the vitreous humor, 14,842 peptides were identified. Patients with RRDCD had 249 DEPs (93 upregulated and 156 downregulated), with 89 in patients with RRD and 61 in patients with IEMM. Enrichment analysis of the GO and Kyoto Encyclopedia of Genes and Genomes DEP databases indicated functional clusters related to inflammation and immunity, protein degradation and absorption, cell adhesion molecules (CAMs), the hedgehog signaling pathway, and lipid metabolism. Weighted gene co-expression network analysis showed that DEPs with positive co-expression of RRDCD participated in immune-related pathways led by the complement and coagulation cascade, whereas DEPs with negative co-expression of RRDCD participated in protein degradation and absorption, CAMs, and the hedgehog signaling pathway. In summary, our study provides important clues and the theoretical basis for exploring the pathogenesis, progression, and prognosis of ocular fundus disease.

     

利用蛋白质组学研究新德里金属b-内酰胺酶1对鲍曼不动杆菌的影响

【目的】比较临床分离的亲缘关系近的多药耐药鲍曼不动杆菌MDR-ZJ06(blaNDM-1–)和ABC3229(blaNDM-1+)的差异蛋白质组,以期发现新德里金属?-内酰胺酶1(New Delhimetallo-β-lactamase-1,NDM-1)对鲍曼不动杆菌生长代谢的影响。【方法】利用2-DE联合MALDI-TOF MS/MS技术鉴定差异表达蛋白,并在GO注析的基础上,对差异蛋白进行通路分析、功能分类和富集分析,并作出蛋白与蛋白相互作用网络。【结果】发现ABC3299相对于MDR-ZJ06有51个差异表达蛋白,其中11个蛋白表达上调,40个蛋白表达下调,并且这些差异蛋白主要涉及降低碳代谢、氨基酸代谢、脂肪酸代谢和细胞壁合成,增加铁离子转运系统形成。【结论】这个结果揭示了NDM-1可能是通过减缓细菌自身的代谢,增加自身铁的摄取使细菌机体系统地抵抗抗生素从而达到耐药。     

Network pharmacology analysis of the therapeutic mechanisms of the traditional Chinese herbal formula Lian Hua Qing Wen in Corona virus disease 2019 (COVID-19), gives fundamental support to the clinical use of LHQW

BackgroundThe traditional Chinese Medicine (TCM) herbal formula Lian Hua Qing Wen (LHQW) improves the results of COVID-19 treatment. Three very recent studies analyzed with network pharmacology some working mechanisms of LHQW. However, we used more techniques and also included Angiotensin converting enzyme 2 (ACE2) (a SARS-CoV receptor, possibly the viral entry point in alveolar lung cells) and the immune system, as cytokine storm is essential in the late phase.PurposeExtensive detailed Network Pharmacology analysis of the LHQW- treatment mechanism in COVID-19.MethodsTCM-herb-meridian and protein interaction network (PIN) of LHQW, based on LHQW herbs meridian information and the protein-protein interaction (PPI) information of the LHQW-component targets. Hub and topological property analyses to obtain crucial targets and construct the crucial LHQW-PIN. Functional modules determination using MCODE, GO and KEGG pathway analysis of biological processes and pathway enrichment. Intersection calculations between the LHQW-proteins and ACE2 co-expression-proteins.ResultsLHQW herbs have relationships to Stomach-, Heart-, Liver- and Spleen-systems, but most (10 of the 13 herbs) to the Lung system, indicating specific effects in lung diseases. The crucial LHQW PIN has the scale-free property, contains 2,480 targets, 160,266 PPIs and thirty functional modules. Six modules are enriched in leukocyte-mediated immunity, the interferon-gamma-mediated signaling pathway, immune response regulating signaling pathway, interleukin 23 mediated signaling pathway and Fc gamma receptor-mediated phagocytosis (GO analysis). These 6 are also enriched in cancer, immune system-, and viral infection diseases (KEGG). LHQW shared 189 proteins with ACE2 co-expression proteins.ConclusionsDetailed network analysis shows, that LHQW herbal TCM treatment modulates the inflammatory process, exerts antiviral effects and repairs lung injury. Moreover, it also relieves the “cytokine storm” and improves ACE2-expression-disorder-caused symptoms. These innovative findings give a rational pharmacological basis and support for treating COVID-19 and possibly other diseases with LHQW.     

金针菇成熟期和伸长期菌盖的转录组与蛋白组比较分析

菌盖是大型真菌的重要组成部分,也是其产生有性孢子的部位,但是其发育机制仍不明确。本研究以金针菇Flammulina filiformis为材料,采用转录组和蛋白组联合分析的方法,比较分析了金针菇成熟期和伸长期菌盖的差异基因与蛋白,并对其进行GO (gene ontology)功能聚类分析、KEGG (Kyoto encyclopedia of genes and genomes)富集分析和蛋白互作网络分析。本研究筛选到差异表达基因有1 391个,差异表达蛋白147个,均以上调表达为主。GO功能聚类分析结果表明,催化活性(catalytic activity)条目富集基因最多,其次是细胞组分(cell part)、细胞过程(cellular process)和细胞器(organelle)。KEGG富集分析结果表明,差异表达基因和蛋白主要富集在碳水化合物代谢通路(carbohydrate metabolism)和氨基酸代谢通路(amino acid metabolism)等。本研究选取了9个关键的差异表达基因,使用实时荧光定量PCR (real-time quantitative PCR,RT-qPCR)对其表达量进行了验证。RT-qPCR验证结果与转录组测序结果相一致。蛋白互作网络分析表明,水解酶类、结构域类和转录调节类蛋白为互作网络的主要结点。本研究联合转录组、蛋白组测序数据,通过分析差异基因与蛋白,为深入了解金针菇菌盖发育机制提供数据参考。     

金针菇菌柄发育的转录组与蛋白组分析

菌柄是金针菇等食用菌的主要商品部位,但其生长机制仍不明确。本研究对金针菇伸长期和成熟期菌柄进行了转录组联合蛋白组分析,结果显示,两样本显著性差异表达基因和蛋白分别为721个和61个,均以上调表达为主。GO（gene ontology）功能聚类分析表明：有72.41%的差异表达基因富集在催化活性（catalytic activity）条目下。细胞组分（cell part）和绑定结合（binding）条目同时富集了较多的差异表达基因和蛋白。KEGG通路富集分析显示：碳水化合物代谢通路（carbohydrate metabolism）和氨基酸代谢通路（amino acid metabolism）富集的差异表达基因较多。差异表达蛋白富集较多的通路是单环菌素生物合成（monobactam biosynthesis,ko00261）、链霉素生物合成（streptomycin biosynthesis,ko00521）和有机含硒化合物代谢（selenocompound metabolism,ko00450）等。内质网蛋白质加工（protein processing in endoplasmic reticulum,ko04141）和MAPK信号通路（MAPK signaling pathway-yeast,ko04011）在转录组和蛋白组的KEGG富集分析中均为差异通路。本研究联合转录组和蛋白组数据筛选了40个金针菇菌柄发育中差异表达基因,为深入研究揭示食用菌菌柄发育过程提供候选基因。     

Novel insights into plasma biomarker candidates in patients with chronic mountain sickness based on proteomics

Chronic mountain sickness (CMS) is a progressive incapacitating syndrome induced by lifelong exposure to hypoxia. In the present study, proteomic analysis was used to identify the differentially expressed proteins (DEPs) and then evaluate the potential plasma biomarkers between CMS and non-CMS groups. A total of 145 DEPs were detected in CMS Han Chinese people who live in the plateau (CMS-HPu), among which 89 were significantly up-regulated and 56 were significantly down-regulated. GO enrichment analysis showed that various biological processes were enriched, including the hydrogen peroxide metabolic/catabolic process, reactive oxygen species (ROS) metabolic, and acute inflammatory response. Protein–protein interaction analysis showed that antioxidant activity, the hydrogen peroxide catabolic process and peroxidase activity were primarily mapped in interaction proteins. Nine modules showed significantly clustering based on WGCNA analysis, with two being the most significant, and GO analysis showed that proteins of both modules were primarily enriched in oxidative stress-related biological processes. Four DEPs increased in CMS patients were evaluated as the candidate biomarkers, and three showed significant AUC: hemoglobin β chain (HB-β), thioredoxin-1 (TRX1), and phosphoglycerate kinase 1 (PGK1). The present study provides insights into the pathogenesis of CMS and further evaluates the potentially biomarkers for its prevention and treatment of it.     

Assessing the biological significance of gene expression signatures and co-expression modules by studying their network properties

Microarray experiments have been extensively used to define signatures, which are sets of genes that can be considered markers of experimental conditions (typically diseases). Paradoxically, in spite of the apparent functional role that might be attributed to such gene sets, signatures do not seem to be reproducible across experiments. Given the close relationship between function and protein interaction, network properties can be used to study to what extent signatures are composed of genes whose resulting proteins show a considerable level of interaction (and consequently a putative common functional role).We have analysed 618 signatures and 507 modules of co-expression in cancer looking for significant values of four main protein-protein interaction (PPI) network parameters: connection degree, cluster coefficient, betweenness and number of components. A total of 3904 gene ontology (GO) modules, 146 KEGG pathways, and 263 Biocarta pathways have been used as functional modules of reference.Co-expression modules found in microarray experiments display a high level of connectivity, similar to the one shown by conventional modules based on functional definitions (GO, KEGG and Biocarta). A general observation for all the classes studied is that the networks formed by the modules improve their topological parameters when an external protein is allowed to be introduced within the paths (up to the 70% of GO modules show network parameters beyond the random expectation). This fact suggests that functional definitions are incomplete and some genes might still be missing. Conversely, signatures are clearly not capturing the altered functions in the corresponding studies. This is probably because the way in which the genes have been selected in the signatures is too conservative. These results suggest that gene selection methods which take into account relationships among genes should be superior to methods that assume independence among genes outside their functional contexts.     

LncRNAs related key pathways and genes in ischemic stroke by weighted gene co-expression network analysis (WGCNA)

BackgroundIschemic stroke (IS) was a significant public health concern and long-chain noncoding RNAs (lncRNAs) were gaining particular importance in stroke biology, however, the potential mechanism of lncRNAs in IS was not fully understood.MethodsIn this study, three diagnosed patients with IS and three controls were selected to establish the lncRNA library. Weighted gene co-expression network analysis (WGCNA) was applied to screen key lncRNA modules associated with IS. The key lncRNAs were identified by module membership (MM) and gene significance (GS). The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was used to identify the key pathways and protein-protein interaction (PPI) network method was used to identify the key genes.ResultsA total of 3627 lncRNAs were investigated, followed by an analysis of 17 modules, and only one module was highly associated with the IS. The top 10 lncRNAs were identified based on GS and MM. KEGG pathways analysis revealed the top two pathways of the Human T cell Lymphotropic Virus-1 (HTLV-1) infection and the mTOR signaling pathway might influence the progress of IS. Further, genes meeting the top two degree (AKT1 and MAPK14) were selected as the hub genes in the PPI network.ConclusionTo summarize, this study identified the key pathways and genes, which might serve as biomarkers and targets for precise diagnosis and treatment of IS in the future.     

茶足柄瘤蚜茧蜂滞育和非滞育蛹中与能量代谢相关的差异表达蛋白

【目的】本研究旨在从蛋白质组整体层面阐明茶足柄瘤蚜茧蜂Lysiphlebus testaceipes蛹滞育背后的多蛋白调控,重点筛选与能量代谢相关的滞育关联蛋白并分析其功能,有助于更好地理解茶足柄瘤蚜茧蜂蛹滞育的代谢机制。【方法】利用同位素标记相对和绝对定量(isobaric tags for relative and absolute quantification, iTRAQ)技术比较了茶足柄瘤蚜茧蜂滞育蛹与非滞育蛹的蛋白含量;利用GO, KEGG网络数据库等生物信息学方法分析鉴定茶足柄瘤蚜茧蜂滞育蛹与非滞育蛹中差异表达蛋白(differentially expressed proteins, DEPs)。【结果】分析得到茶足柄瘤蚜茧蜂滞蛹与非滞育蛹DEPs有135个,包括滞育蛹中上调表达蛋白有38个,下调表达蛋白有97个。GO和KEGG富集分析表明,与天冬氨酸转运、L-谷氨酸转运、胆碱脱氢酶活性和胆碱生物合成甘氨酸甜菜碱条目以及氧化磷酸化通路相关的蛋白上调表达。【结论】氧化磷酸化通路相关蛋白在茶足柄瘤蚜茧蜂滞育过程中呈显著上调表达,说明能量代谢与该蜂滞育密切相关,并推测氧化磷酸化...     

基于蛋白组学的脓毒症补体凝血级联通路及标志物KLKB1研究

摘要 目的：通过蛋白质组学方法鉴定脓毒症关键通路及诊断标志物。方法：选取2019年1月至12月西南医科大学附属医院急诊科收治的56例脓毒症患者（脓毒症组）,另取同期50名健康体检志愿者（对照组）。采用随机抽样法分别选取两组中12名脓毒症患者和8名健康体检志愿者,利用非数据依赖模式（DIA）进行血清蛋白数据采集,将数据上传至iDEP在线平台分析脓毒症患者外周血中差异表达蛋白,进一步对这些差异蛋白进行生物信息学分析,包括主成分分析（PCA）、基因本体富集分析（GO）、通路富集分析和蛋白-蛋白相互作用网络（PPI）分析,进而筛选出脓毒症关键蛋白。采用酶联免疫吸附试验（ELISA）对脓毒症组、对照组进行关键蛋白表达验证分析。采用受试者工作特征（ROC）曲线分析关键蛋白对脓毒症的诊断效能。结果：蛋白质组学分析共鉴定出690个蛋白,筛选出171个差异表达蛋白（DEPs）,其中39个蛋白显著下调,132个蛋白显著上调。DEPs富集的核心通路为补体和凝血级联通路。该条通路中的血清激肽释放酶 1（KLKB1）在脓毒症组的表达水平为（121.80±55.63 ng/mL）,显著高于对照组的（68.30±57.11 ng/mL）,差异具有统计学意义（t=4.881,P=0.000）。根据ELISA结果进行脓毒症诊断ROC曲线分析得出,KLKB1蛋白诊断脓毒症的 AUC（95%CI）为0.759（0.594～0.923）。结论：补体和凝血级联通路为脓毒症免疫途径的重要通路,KLKB1具有较好的脓毒症诊断特性,可能是脓毒症潜在的诊断生物标志物。     

Characterization of Differentially Expressed Genes Involved in Pathways Associated with Gastric Cancer

To explore the patterns of gene expression in gastric cancer, a total of 26 paired gastric cancer and noncancerous tissues from patients were enrolled for gene expression microarray analyses. Limma methods were applied to analyze the data, and genes were considered to be significantly differentially expressed if the False Discovery Rate (FDR) value was < 0.01, P-value was <0.01 and the fold change (FC) was >2. Subsequently, Gene Ontology (GO) categories were used to analyze the main functions of the differentially expressed genes. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we found pathways significantly associated with the differential genes. Gene-Act network and co-expression network were built respectively based on the relationships among the genes, proteins and compounds in the database. 2371 mRNAs and 350 lncRNAs considered as significantly differentially expressed genes were selected for the further analysis. The GO categories, pathway analyses and the Gene-Act network showed a consistent result that up-regulated genes were responsible for tumorigenesis, migration, angiogenesis and microenvironment formation, while down-regulated genes were involved in metabolism. These results of this study provide some novel findings on coding RNAs, lncRNAs, pathways and the co-expression network in gastric cancer which will be useful to guide further investigation and target therapy for this disease.     

Identification of biomarkers correlated with hypertrophic cardiomyopathy with co-expression analysis

Hypertrophic cardiomyopathy (HCM) is reported to be the most common genetic heart disease. To identify key module and candidate biomarkers correlated with clinical prognosis of patients with HCM, we carried out this study with co-expression analysis. To construct a co-expression network of hub genes correlated with HCM, the Weighted Gene Co-expression Network Analysis (WGCNA) was performed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by Database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction network analysis of central genes was performed to recognize the interactions of central genes. Gene set enrichment analyses were carried out to discover the possible mechanisms involved in the pathways promoted by hub genes. To validate the hub genes, quantitative real-time polymerase chain reaction (RT-PCR) was performed. Based on the results of topological overlap measure based clustering, 2,351 differentially expressed genes (DEGs) were identified. Those genes were included in six different modules. Of these modules, the yellow and the blue modules showed a pivotal correlation with HCM. DEGs were enriched in immune system procedure associated GO terms and KEGG pathways. We identified nine hub genes (TYROBP, STAT3, CSF1R, ITGAM, SYK, ITGB2, LILRB2, LYN, and HCK) affected the immune system significantly. Among the genes we validated with RT-PCR, TYROBP, CSF1R, and SYK showed significant increasing expression levels in model HCM rats. In conclusion, we identified two modules and nine hub genes, which were prominently associated with HCM. We found that immune system may play a crucial role in the HCM. Accordingly, those genes and pathways might become therapeutic targets with clinical usefulness in the future.     

应用GSEA和WGCNA方法分析细菌性败血症宿主关键差异基因及意义

【目的】采用生物信息学方法分析公共数据库来源的细菌性败血症患者全血转录组学表达谱,探讨细菌败血症相关的宿主关键差异基因及意义。【方法】基于GEO数据库中GSE80496和GSE72829全血转录组基因数据集,采用GEO2R、基因集富集分析(GSEA)联用加权基因共表达网络分析(WGCNA)筛选细菌性败血症患者相比健康人群显著改变的差异基因,通过R软件对交集基因进行GO功能分析和KEGG富集分析。同时,通过String 11.0和Cytoscape分析枢纽基因,验证枢纽基因在数据集GSE72809(Health组52例,Definedsepsis组52例)全血标本中的表达情况,并探讨婴儿性别、月(胎)龄、出生体重、是否接触抗生素等因素与靶基因表达谱间的关系。【结果】分析GSE80496和GSE72829数据集分别筛选得到932个基因和319个基因,联合WGCNA枢纽模块交集得到与细菌性败血症发病相关的10个枢纽基因(MMP9、ITGAM、CSTD、GAPDH、PGLYRP1、FOLR3、OSCAR、TLR5、IL1RN和TIMP1);GSEA分析获得关键通路(氨基酸糖类-核糖代谢、PPAR信号通路、聚糖生物合成通路、自噬调控通路、补体、凝血因子级联反应、尼古丁和烟酰胺代谢、不饱和脂肪酸生物合成和阿尔兹海默症通路)及生物学过程(类固醇激素分泌、腺苷酸环化酶的激活、细胞外基质降解和金属离子运输)。【结论】本项研究通过GEO2R、GSEA联用WGCNA分析,筛选出与细菌性败血症发病相关的2个枢纽模块、10个枢纽基因以及一些关键信号通路和生物学过程,可为后续深入研究细菌性败血症致病机制奠定理论依据。     

Isobaric tag for relative and absolute quantitation based quantitative proteomics reveals unique urinary protein profiles in patients with preeclampsia

Preeclampsia (PE) is one of the most significant pregnancy‐related hypertensive disorders. Currently, there are no useful markers to predict the onset of the condition in pregnant women. To provide further insights into the pathogenesis of PE and identify biomarkers of the condition, we used isobaric tags for relative and absolute quantitation (iTRAQ) proteomics coupled with 2‐D LC‐MS/MS, to analyze urinary protein profiles from 7 PE patients and 7 normotensive pregnant women. A total of 294 proteins were abnormally expressed in PE patients. Of these, 233 were significantly down‐regulated and 61 proteins were significantly up‐regulated. Bioinformatics analysis using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database, found that the most differentially expressed proteins (DEPs) were involved in coagulation and complement pathways, the renin‐angiotensin system and cell adhesion molecules (CAMs) pathways. We further validated three of the DEPs, including serotransferrin (TF) and complement factor B (CFB) by immunoblottingand serum paraoxonase/arylesterase 1 (PON1) by ELISA using 14 pairs of urine samples from PE patients and normal pregnant women. Taken together, our results provide the basis for further understanding the pathogenesis of PE and identifying predictive biomarkers.     

Identification of biomarkers of chromophobe renal cell carcinoma by weighted gene co-expression network analysis

Background

Chromophobe renal cell carcinoma (ChRCC) is the second common subtype of non-clear cell renal cell carcinoma (nccRCC), which accounting for 4–5% of renal cell carcinoma (RCC). However, there is no effective bio-marker to predict clinical outcomes of this malignant disease. Bioinformatic methods may provide a feasible potential to solve this problem.

Methods

In this study, differentially expressed genes (DEGs) of ChRCC samples on The Cancer Genome Atlas database were filtered out to construct co-expression modules by weighted gene co-expression network analysis and the key module were identified by calculating module-trait correlations. Functional analysis was performed on the key module and candidate hub genes were screened out by co-expression and MCODE analysis. Afterwards, real hub genes were filter out in an independent dataset GSE15641 and validated by survival analysis.

Results

Overall 2215 DEGs were screened out to construct eight co-expression modules. Brown module was identified as the key module for the highest correlations with pathologic stage, neoplasm status and survival status. 29 candidate hub genes were identified. GO and KEGG analysis demonstrated most candidate genes were enriched in mitotic cell cycle. Three real hub genes (SKA1, ERCC6L, GTSE-1) were selected out after mapping candidate genes to GSE15641 and two of them (SKA1, ERCC6L) were significantly related to overall survivals of ChRCC patients.

Conclusions

In summary, our findings identified molecular markers correlated with progression and prognosis of ChRCC, which might provide new implications for improving risk evaluation, therapeutic intervention, and prognosis prediction in ChRCC patients.