基于微阵列技术的缺氧/复氧诱导下血管内皮细胞转录组分析

Comparative transcriptomic analysis of vascular endothelial cells after hypoxia/re-oxygenation induction based on microarray technology # # 基于微阵列技术的缺氧/复氧诱导下血管内皮细胞转录组分析 1 2 3 first-author 1 2 3 1 2 3 4 1 2 3 1 2 3 corresp ‡Corresponding Author ‡Corresponding Author †E-mail:luyuanqiang@zju.edu.cn †E-mail:luyuanqiang@zju.edu.cn luyuanqiang@zju.edu.cn Department of Emergency Medicine, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China Department of Emergency Medicine, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China Department of Geriatric Medicine, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China Department of Geriatric Medicine, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China Zhejiang Provincial Key Laboratory for Diagnosis and Treatment of Aging and Physic-chemical Injury Diseases, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China Zhejiang Provincial Key Laboratory for Diagnosis and Treatment of Aging and Physic-chemical Injury Diseases, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China Objective: 2 To provide comprehensive data to understand mechanisms of vascular endothelial cell (VEC) response to hypoxia/re-oxygenation. Methods: 2 Human umbilical vein endothelial cells (HUVECs) were employed to construct hypoxia/re-oxygenation-induced VEC transcriptome profiling. Cells incubated under 5% O 2 , 5% CO 2 , and 90% N 2 for 3 h followed by 95% air and 5% CO 2 for 1 h were used in the hypoxia/re-oxygenation group. Those incubated only under 95% air and 5% CO 2 were used in the normoxia control group. Results: 2 By using a well-established microarray chip consisting of 58 339 probes, the study identified 372 differentially expressed genes. While part of the genes are known to be VEC hypoxia/re-oxygenation-related, serving as a good control, a large number of genes related to VEC hypoxia/re-oxygenation were identified for the first time. Through bioinformatic analysis of these genes, we identified that multiple pathways were involved in the reaction. Subsequently, we applied real-time polymerase chain reaction (PCR) and western blot techniques to validate the microarray data. It was found that the expression of apoptosis-related proteins, like pleckstrin homology-like domain family A member 1 (PHLDA1), was also consistently up-regulated in the hypoxia/re-oxygenation group. STRING analysis found that significantly differentially expressed genes SLC38A3 , SLC5A5 , Lnc-SLC36A4-1 , and Lnc-PLEKHJ1-1 may have physical or/and functional protein–protein interactions with PHLDA1. Conclusions: 2 The data from this study have built a foundation to develop many hypotheses to further explore the hypoxia/re-oxygenation mechanisms, an area with great clinical significance for multiple diseases. 目的 2 应用全转录组芯片研究缺氧/复氧诱导下人脐静脉内皮细胞(HUVEC)的转录组轮廓. 创新点 2 血管内皮细胞(VEC)缺氧/复氧损伤被视定为许多生理和病理过程中导致器官功能障碍的重要驱动因素.然而,其详细病理生理机制和基因表达谱信息尚未阐明.本研究首次应用全转录组芯片技术研究VEC缺氧/复氧诱导下的转录组轮廓. 方法 2 采用缺氧孵育3 h后复氧1 h的HUVEC为缺氧/复氧组,同时常氧孵育的HUVEC为常氧对照组.应用含58 339条探针的全转录组芯片检测每组三个样本.对差异表达基因进行生信分析和功能验证. 结论 2 本研究发现372个有意义的差异表达基因探针.相关基因涵盖多种途径和功能,例如氧自由基的产生、钙超载、炎症、糖脂代谢、内皮细胞增殖、分化、细胞骨架及通透性调节、细胞裂解、凋亡和血管生成.另外,实验进一步表明,差异表达基因pleckstrin同源样域家族A成员1(PHLDA1)的mRNA和蛋白质表达结果与微阵列结果一致.STRING分析发现, PHLDA1 可能与差异表达基因 SLC38A3 、 SLC5A5 、 Lnc-SLC36A4-1 和 Lnc-PLEKHJ1-1 具有物理性和/或功能性相互作用,这有望揭示VEC在缺氧/复氧环境下长链非编码RNA(lncRNA)的相关机制. Human umbilical vein endothelial cells (HUVECs) Hypoxia Re-oxygenation Microarray Pleckstrin homology-like domain family A member 1 (PHLDA1) Long non-coding RNA (lncRNA) 人脐静脉内皮细胞 缺氧 复氧 微阵列 PHLDA1 长链非编码RNA Introduction 1 Vascular endothelial cells (VECs) function as a barrier and active tissue in the inner layer of blood vessels, and play an important role in the reaction of organ ischemia, hypoxia, and inflammatory immunity. VECs participate in the regulation of many important balances by secreting a variety of active substances and regulating organ blood flow and coagulation, leukocyte and platelet activity (Nallamshetty et al., 2013 2013 ; Lim To et al., 2015 2015 ; Baldea et al., 2018 2018 ). It has been reported that the endothelial cells seem to provide better hypoxia tolerance than many other cells (Filippi et al., 2018 2018 ), and the relatively full extent VEC gene expression induced by hypoxia has been established (Urbanek et al., 2014 2014 ; Sun et al., 2015 2015 ; Wu et al., 2015 2015 ; Tang et al., 2016 2016 ; Baldea et al., 2018 2018 ). However, hypoxia/re-oxygenation is the common feature and may have more adverse consequences in many physiological and pathological processes, such as inflammation, obstructive sleep apnea, diabetes, atherosclerosis, myocardial infarction, ischemic stroke, pulmonary embolism, shock, cardiac arrest, cardiac pulmonary bypass, organ transplantation, and tumorigenesis (Atkeson et al., 2009 2009 ; Shay and Celeste Simon, 2012 2012 ; Bader et al., 2015 2015 ; Pan J et al., 2015 2015 ; Jiang et al., 2017 2017 ; Xie et al., 2017 2017 ; Li F et al., 2018 2018 ; Li WY et al., 2018 2018 ; Wang et al., 2018 2018 ; Zhang et al., 2018 2018 ; Pan H et al., 2019 2019 ). In contrast to general belief, VEC hypoxia/re-oxygenation injury has recently been identified as a driver rather than a bystander to result in the possible development of organ dysfunction (Carden and Granger, 2000 2000 ). So far, increased free radical generation and excessive activation of inflammatory responses are considered as important pathogeneses of endothelial hypoxia/re-oxygenation injury (Shay and Celeste Simon, 2012 2012 ; Wu et al., 2015 2015 ; Tang et al., 2016 2016 ; Ferrucci et al., 2018 2018 ; Filippi et al., 2018 2018 ; Taylor et al., 2018 2018 ; Haybar et al., 2019 2019 ). It is a potentially serious problem, but the detailed physiological processes and transcriptome profiling of VECs after exposure to hypoxia/re-oxygenation have not yet been elucidated. The present research is the first to focus on the comprehensive gene expression of hypoxia/re-oxygenation-induced human umbilical vein endothelial cells (HUVECs) using a microarray technique. Materials and methods 1 Cell lines and cell culture 2 HUVECs were kindly provided by Procell Life Science & Technology Co., Ltd. (Wuhan, China). High-glucose Dulbecco’s modified Eagle medium (DMEM; Thermo Fisher Scientific, Shanghai, China) had 10% (0.1 g/mL) fetal bovine serum (Biological Industries Israel Beit Haemek Ltd., Beit Haemek, Israel), and 100 U/mL streptomycin and 100 U/mL penicillin (Genom, Hangzhou, China) added were used for cell culture. Before being induced by hypoxia/re-oxygenation, cells in all groups were replaced with fresh medium at 37 °C under 5% CO 2 and 95% air for 12 h. Then, HUVECs in the hypoxia group were incubated under 5% O 2 , 5% CO 2 , and 90% N 2 by 3131 Single Tri-gas 184L incubator (Thermo Fisher Scientific) for 3 h (Niu et al., 2019 2019 ); HUVECs in the hypoxia/re-oxygenation group were incubated under 5% O 2 , 5% CO 2 , and 90% N 2 for 3 h followed by 95% air and 5% CO 2 for 1 h; HUVECs in the normoxia group were cultured under 95% air and 5% CO 2 . Construction of transcriptome profile 2 Agilent SurePrint G3 Human Gene Expression v3 Microarray (8×60K; Design ID 072363, Agilent, Palo Alto, CA, USA) was used for the construction of transcriptome profiling. Each of three samples from the hypoxia/re-oxygenation and normoxia groups was used for the microarray experiment. Total RNA was extracted using TRIzol (Life Technologies, Waltham, MA, USA), quantified using the NanoDrop ND-2000 (Thermo Fisher Scientific), and assessed for integrity using Agilent Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA, USA) following the manufacturer’s instructions. Total RNA (0.2 μg) of each sample was used for library construction based on the manufacturer’s standard protocols. The Agilent Scanner G2505C (Agilent Technologies) was used for array scanning. Feature Extraction software (Version 10.7.1.1, Agilent Technologies) was used to extract raw data by reading array images. Analysis of microarray raw data 2 The software GeneSpring (Version 13.1, Agilent Technologies) was employed to normalize the raw data with the quantile algorithm. The probes that at least 100% of the values in any one out of all conditions have flags in “Detected” were chosen for differentially expressed gene analysis. Fold change of ≥2.0 and P value of ≤0.05 calculated with the t -test were used as the threshold set to identify a differentially expressed gene. Afterwards, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were applied to explore the potential functions and pathways of these differentially expressed genes. Fold enrichment of GO/KEGG analysis=(list hits/list total)/(population hits/population total), where “list hits” is the number of differentially expressed genes annotated to each GO/KEGG entry, “list total” is the number of differentially expressed genes involved in GO/KEGG analysis, “population hits” is the number of genes in whole microarray annotated to each GO/KEGG entry, and “population total” is the number of genes in whole microarray involved in GO/KEGG analysis. P ≤0.05 indicates significant enrichment. The distinguishable gene expression pattern among samples was established by hierarchical clustering. The raw and normalized data have been submitted to the National Center of Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database ( http://www.ncbi.nlm http://www.ncbi.nlm . nih.gov/geo), GSE144715. Real-time PCR 2 The quantitative real-time polymerase chain reaction (qRT-PCR) was used for the messenger RNA (mRNA) expression assay. Total RNA was extracted from cells using the RNeasy® Plus Mini kit (Redwood City, USA). The qRT-PCR was performed using TB Green™ Premix Ex Taq™ II kit (TaKaRa, Japan). The specific primers were synthesized by Sangon Biotech Co., Ltd. (Shanghai, China). PHLDA1 -forward: 5'-GG AGAGTAGCGGCTGCAAAG-3', PHLDA1 -reverse: 5'-CCTCGGTGAGGATGCAACAC-3'. Biosystems™ 7500 Fast Dx Real-Time PCR system (Thermo Fisher Scientific) was used for the PCR reaction. Applied Biosystems™ 7500 Fast Real-Time PCR software (Thermo Fisher Scientific) was employed for quantitative analysis. Relative quantification was analyzed by the 2 −ΔΔ C T method. β-Actin was used as housekeeping control. Western blot assay 2 The protein expression was detected by western blot. Extracted protein from cells was quantified by BCA Protein Assay kit (Thermo Fisher Scientific), mixed with 5×sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) sample loading buffer (Beyotime Biotechnology, Shanghai, China), boiled, separated by 12% (0.12 g/mL) SDS-PAGE (80 V in the stacking gel and 120 V in the separating gel), and transferred to a polyvinylidene fluoride (PVDF) membrane at 200 mA (Millipore, Billerica, MA, USA). The PVDF membrane was then blocked with 5% (0.05 g/mL) skimmed milk/phosphate-buffered saline with Tween 20 (PBST) for 60 min at room temperature, and incubated with rabbit monoclonal for PHLDA1 (Abcom, Shanghai, China) or β-actin (CST, Danvers, MA, USA) at 4 °C overnight, followed by being incubated in 5% (0.05 g/mL) skimmed milk/PBST containing anti-rabbit peroxidase-conjugated secondary antibodies (Proteintech, Wuhan, China) for 60 min at room temperature. Finally, the membranes were washed with PBST. The images of the western blot were acquired using Image Lab 3.0 by Bio-Rad ChemiDoc System (Bio-Rad, Hercules, California, USA). Protein interaction analysis 2 The STRING database was used for protein–protein interaction analysis ( http://string-db.org http://string-db.org ). Statistical analysis 2 The continuous data were expressed as mean±standard deviation (SD). Statistical analysis between means was determined using the Student’s t -test. P value of < 0.05 was considered statistically significant. Results 1 Reliability and repeatability analyses of microarray-based hypoxia/re-oxygenation-induced HUVEC transcriptome profiling 2 HUVECs were employed to construct hypoxia/re-oxygenation-induced VEC transcriptome profiling using an Agilent SurePrint G3 Human Gene Expression v3 Microarray. HUVECs incubated under 5% O 2 , 5% CO 2 , and 90% N 2 for 3 h followed by 95% air and 5% CO 2 for 1 h were used as the hypoxia/re-oxygenation group. HUVECs incubated under 95% air and 5% CO 2 were used as the normoxia control group. Rigorous data analysis was applied to ensure that genes identified by microarray analysis were truly differentially expressed. After exclusion of absent calls and probes that were expressed in fewer than half of experimental samples, 29 986 out of an initial 58 339 probes (51.4%) were considered for analysis (Fig. 1a 1a ). Principal component analysis (PCA) was used to evaluate the distribution of samples in the hypoxia/re-oxygenation and normoxic control groups. The results showed that the biological repeatability and uniformity of the experimental samples were both high, which means that the experimental design was reasonable (Fig. 1b 1b ). (a) Composition analysis of microarray-based HUVEC hypoxia/re-oxygenation expression profile. A total of 58 339 probes were used for microarray; 28 353 probes, which were not detected in more than half of samples, were invalid probes (48.6%); 29 986 probes, which were detected in more than three samples, were used for transcriptome profiling analysis (51.4%). (b) Principal component analysis (PCA). The closer the samples of the same group were in the two-dimensional space, the more representative these samples are and the better the biological repetition was. HUVEC: human umbilical vein endothelial cell; H/R_HUVEC: hypoxia/re-oxygenated group; CG_HUVEC: normoxia control group Hypoxia/re-oxygenation-related differentially expressed gene probes 2 In this study, a statistically significant up-regulation or down-regulation of differentially expressed genes was screened according to fold change of ≥2.0 and P value of ≤0.05. This is represented by a volcano plot (Fig. 2a 2a ). A total of 372 differentially expressed gene probes, including 106 up-regulated and 266 down-regulated gene probes, were identified. These differentially expressed gene probes were represented by a heat map of a hierarchical clustering based on HUVEC O 2 condition (Fig. 2b 2b ); the figure demonstrates very low inter-sample variation in gene expression between replicates. The top 30 differentially expressed gene probes with Entrez Gene ID that are most strongly up-regulated and down-regulated following exposure to hypoxia/re-oxygenation are listed in Tables 1 1 and 2 2 . The full list of differentially regulated gene probes is shown in Table S1 S1 ) and is available at http://www http://www . ncbi.nlm.nih.gov/geo (GSE144715). (a) Volcano plot for differential expression screening. To analyze the significantly differently expressed genes between samples in the hypoxia/re-oxygenated and normoxia groups using the t -test, the log 2 value of fold change is used as the abscissa, and the negative log 10 value of the P value of the t -test is used as the ordinate to obtain the volcano plot. Gray dots: genes with the P value of > 0.05; Green dots: genes with absolute fold change of < 2 and P value of ≤0.05; Red dots: genes with fold change of ≥2 and P value ≤0.05; These are significantly up-regulated differentially expressed genes. Blue dots: genes with fold change of ≤−2 and P value of ≤0.05; These are significantly down-regulated differentially expressed genes. (b) Heat map of a hierarchical clustering based on HUVEC O 2 condition. Gene expression profiling of hypoxia/re-oxygenation and normoxia HUVECs demonstrated that a total of 372 probes were differentially expressed (fold change of < 2, P value of ≤0.05). A heat map is generated where each row representes one probe set and each column representes one experimental sample. The probes are ordered by correlation and significance. The intensity of color in a cell represents the normalized expression of the probe, where red and green colorings depict high and low expression, respectively, in the hypoxia/re-oxygenation condition compared to the normoxia control The fold change is (hypoxia/re-oxygenation group)/(normoxia group) Probe name Gene name Gene symbol Gene identifier Entrez Gene ID Fold change * * P value A_23_P21057 Septin 1 SEPT1 NM_052838 1731 9.36 0.03 A_32_P211248 Long intergenic non-protein coding RNA 1405 LINC01405 NR_036513 100131138 9.23 0.01 A_21_P0012449 Long intergenic non-protein coding RNA 971 LINC00971 NR_033860 440970 5.77 0.03 A_21_P0000019 Lysine demethylase 4C KDM4C NM_001146695 23081 5.70 0.03 A_24_P366122 Acyl-CoA binding domain containing 4 ACBD4 NM_024722 79777 4.95 0.01 A_24_P160380 PDZ and LIM domain 2 PDLIM2 NM_176871 64236 4.84 0.01 A_22_P00002166 Family with sequence similarity 229, member A FAM229A NM_001167676 100128071 4.39 0.03 A_33_P3285271 Flavin containing dimethylaniline monooxygenase 6 pseudogene FMO6P NR_002601 388714 3.88 0.02 A_33_P3422085 SPANX family member N2 SPANXN2 NM_001009615 494119 3.73 0.02 A_23_P159893 Chordin-like 1 CHRDL1 NM_145234 91851 3.64 0.04 A_22_P00014410 SACS antisense RNA 1 SACS-AS1 NR_103450 100506680 3.51 0.05 A_33_P3423425 Zinc finger protein 770 ZNF770 NM_014106 54989 3.49 0.00 A_24_P322229 RAS like family 10 member B RASL10B NM_033315 91608 3.39 0.02 A_33_P3211078 High mobility group AT-hook 2 HMGA2 NM_001300918 8091 3.33 0.04 A_21_P0001900 Gastric cancer associated transcript 1 GACAT1 NR_126369 104326057 3.22 0.01 A_33_P3384710 Family with sequence similarity 222 member B FAM222B NM_001288631 55731 3.19 0.01 A_23_P420692 Protein tyrosine phosphatase receptor type F (PTPRF) interacting protein α 4 PPFIA4 XM_006711588 8497 3.04 0.02 A_33_P3286953 ADAM metallopeptidase with thrombospondin type 1 motif 6 ADAMTS6 NM_197941 11174 2.96 0.02 A_23_P102000 C-X-C motif chemokine receptor 4 CXCR4 NM_001008540 7852 2.95 0.05 A_33_P3294302 Pleckstrin homology-like domainfamily A member 1 PHLDA1 NM_007350 22822 2.87 0.02 A_21_P0006019 Uncharacterized LOC101927358 LOC101927358 NR_121182 101927358 2.84 0.03 A_22_P00009701 Uncharacterized LOC100131655 LOC100131655 NR_040024 100131655 2.81 0.05 A_24_P362904 6-Phosphofructo-2-kinase/fructose-2,6-biphosphatase 4 PFKFB4 NM_004567 5210 2.81 0.05 A_33_P3771067 Uncharacterized LOC283140 LOC283140 NR_126004 283140 2.79 0.02 A_23_P46131 Family with sequence similarity 110 member D FAM110D NM_024869 79927 2.67 0.04 A_23_P45751 Chloride channel accessory 4 CLCA4 NM_012128 22802 2.66 0.02 A_23_P16415 Low density lipoprotein (LDL) receptor-related protein 3 LRP3 NM_002333 4037 2.66 0.04 A_23_P62647 Signaling lymphocytic activation molecule family member 1 SLAMF1 NM_003037 6504 2.64 0.02 A_24_P221575 RUN and FYVE domain containing 3 RUFY3 NM_001037442 22902 2.63 0.03 A_33_P3222018 Chromobox 3 CBX3 NM_007276 11335 2.62 0.03 The fold change is (normoxia group)/(hypoxia/re-oxygenation group) Probe name Gene name Gene symbol Gene identifier Entrez Gene ID Fold change * * P value A_21_P0007488 Long intergenic non-protein coding RNA 1490 LINC01490 NR_120468 101928420 33.12 0.00 A_22_P00018708 Uncharacterized LOC101927913 LOC101927913 XR_241962 101927913 7.43 0.03 A_23_P389500 Regenerating family member 1 β REG1B NM_006507 5968 6.02 0.00 A_22_P00020802 Uncharacterized LOC101927694 LOC101927694 NR_104648 101927694 5.67 0.04 A_33_P3268035 Lysozyme-like 1 LYZL1 NM_032517 84569 5.35 0.03 A_24_P327084 Serine protease 33 PRSS33 NM_152891 260429 5.02 0.00 A_23_P86411 Myosin IIIA MYO3A NM_017433 53904 4.47 0.01 A_23_P111978 Potassium two-pore-domain channel subfamily K member 9 KCNK9 NM_001282534 51305 4.46 0.01 A_21_P0009060 Uncharacterized LOC101928035 LOC101928035 NR_104657 101928035 4.31 0.01 A_23_P36050 Olfactory receptor family 8 subfamily K member 3 (gene/pseudogene) OR8K3 NM_001005202 219473 4.26 0.03 A_23_P502590 Killer cell immunoglobulin-like receptor, two Ig domains and short cytoplasmic tail 4 KIR2DS4 NM_012314 3809 4.17 0.05 A_33_P3238182 Long intergenic non-protein coding RNA 588 LINC00588 NR_026772 26138 4.14 0.03 A_19_P00809368 Long intergenic non-protein coding RNA 1215 LINC01215 NR_110028 101929623 4.06 0.01 A_32_P234926 BANF family member 2 BANF2 NM_001014977 140836 4.04 0.04 A_32_P155666 Endothelin converting enzyme-like 1 ECEL1 NM_004826 9427 4.03 0.00 A_21_P0001945 Uncharacterized LOC101927156 LOC101927156 101927156 4.00 0.03 A_24_P361427 TBC1 domain family member 29 TBC1D29 NM_015594 26083 3.76 0.04 A_22_P00010840 Uncharacterized LOC101927272 LOC101927272 NR_110908 101927272 3.74 0.02 A_21_P0010721 Long intergenic non-protein coding RNA 869 LINC00869 XR_426752 57234 3.62 0.04 A_23_P419156 Opsin 1, short wave sensitive OPN1SW NM_001708 611 3.55 0.02 A_22_P00014526 CFAP44 antisense RNA 1 CFAP44-AS1 NR_046728 100874029 3.49 0.01 A_21_P0004097 Uncharacterized LOC101929261 LOC101929261 XR_241733 101929261 3.47 0.02 A_33_P3235721 Chromosome 11 open reading frame 87 C11orf87 NM_207645 399947 3.42 0.04 A_22_P00002954 Uncharacterized LOC101929261 LOC101929261 XR_241733 101929261 3.38 0.04 A_33_P3882624 Protection of telomeres 1 POT1 NM_015450 25913 3.36 0.00 A_33_P3262635 Cat eye syndrome chromosome region, candidate 1 CECR1 NM_001282225 51816 3.30 0.05 A_21_P0004219 Long intergenic non-protein coding RNA 1018 LINC01018 NR_024424 255167 3.30 0.01 A_33_P3307795 Family with sequence similarity 124 member B FAM124B NM_024785 79843 3.28 0.00 A_22_P00008580 Long intergenic non-protein coding RNA 1231 LINC01231 NR_121585 101929247 3.26 0.03 A_23_P150064 Multimerin 2 MMRN2 NM_024756 79812 3.19 0.04 Pathways and functions mapping with hypoxia/re-oxygenation-sensitive gene probes 2 In order to better understand the genomic response to hypoxia/re-oxygenation of HUVECs, the 372 differentially expressed gene probes were functionally annotated and clustered using GO analysis and KEGG analysis. A total of 803 GO IDs were matched, of which 486 GO IDs were related to a biological process, 149 GO IDs were related to a cellular component, and 168 GO IDs were related to molecular function. Based on the GO analysis results, the molecular and cellular functions related to production of oxygen free radicals, calcium overload, excessive activation of inflammation, and cell injury, including endothelial cell proliferation, apoptosis, angiogenesis, vasoconstriction, and coagulation are listed in Table 3 3 . Fold enrichmen=(list hits/list total)/(population hits/population total), where “list hits” is the number of differentially expressed genes annotated to each Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) entry, “list total” is the number of differentially expressed genes involved in GO/KEGG analysis, “population hits” is the number of genes in whole microarray annotated to each GO/KEGG entry, and “population total” is the number of genes in whole microarray involved in GO/KEGG analysis. P value of fold enrichment, and P ≤0.05 indicates significant enrichment Hypoxia/re-oxygenation-related GO GO ID Related differentially regulated gene Fold enrichment # # P value * * Production of oxygen free radicals  Positive regulation of phospholipase activity GO:0010518 FGFR2 22.13 0.05  Negative regulation of nitric-oxide synthase activity GO:0051001 CNR2 22.13 0.05  Neutrophil activation GO:0042119 CXCR4 17.70 0.06  Nitric-oxide synthase binding GO:0050998 SCN5A 11.94 0.09  Dioxygenase activity GO:0051213 KDM4C 9.83 0.10  Response to hypoxia GO:0001666 CXCR4 , ALDH3A1 2.23 0.23 Calcium overload  G-protein-coupled receptor signaling pathway GO:0007186 GPR31 , OPN1SW , OR13H1 , OR2A2 , NPBWR1 , NPY6R , OR10G8 , OR10J3 , OR8K3 , CCL3L3 , CXCR4 , ADGRG3 , OR10J5 , FFAR2 3.11 0.00  Sodium ion transmembrane transport GO:0035725 SLC5A5 , ASIC2 , SCN5A 6.43 0.01  Lipid digestion GO:0044241 CEL 29.51 0.04  Sodium ion transport GO:0006814 SLC38A3 , SCN5A 4.82 0.07  Phospholipase binding GO:0043274 WAS 9.28 0.11  Calcium channel regulator activity GO:0005246 NPY 5.96 0.16  Phosphatidylinositol phospholipase C activity GO:0004435 PLCH2 5.96 0.16 Excessive activation of inflammation  Negative regulation of interferon-γ biosynthetic process GO:0045077 INHA 35.42 0.03  Neutrophil chemotaxis GO:0030593 ITGA9 , CCL3L3 5.57 0.05  Chemokine-mediated signaling pathway GO:0070098 CCL3L3 , CXCR4 5.09 0.06  Complement activation GO:0006956 C1QA 3.68 0.24  Positive regulation of inflammatory response GO:0050729 CCL3L3 3.10 0.28 Cell injury  Regulation of vascular endothelial growth factor receptor signaling pathway GO:0030947 TMEM204 35.42 0.03  Positive regulation of epithelial cell proliferation GO:0050679 FGFR2 , SCN5A 6.05 0.05  Negative regulation of cell migration involved in sprouting angiogenesis GO:0090051 MMRN2 22.13 0.05  Blood coagulation, intrinsic pathway GO:0007597 VWF 9.83 0.10  Positive regulation of cell proliferation GO:0008284 SLAMF1 , VWCE , FGFR2 , KDM4C , ALDH3A1 2.03 0.11  Regulation of vasoconstriction GO:0019229 ASIC2 8.42 0.12  Angiogenesis GO:0001525 MMRN2 , FGFR2 , NRCAM 2.47 0.13  Positive regulation of apoptotic process GO:0043065 PHLDA1 , HMGA2 , NEURL1 1.89 0.22  DNA damage response, signal transduction by p53 class mediator resulting in cell cycle arrest GO:0006977 PSMB11 2.67 0.32  Apoptotic process GO:0006915 PSMB11 , PHLDA1 , FGFR2 , CXCR4 1.17 0.45  Negative regulation of cell proliferation GO:0008285 CCL3L3 , NEURL1 0.92 0.64 A total of 86 KEGG IDs were matched based on the known information, in which 42 differentially expressed genes were involved. Eleven differentially expressed genes participate in no less than five KEGG pathways, including fibroblast growth factor receptor 2 ( FGFR2 ; 10 KEGG pathways), Wiskott-Aldrich syndrome ( WAS ; 10 KEGG pathways), aldehyde dehydrogenase 3 family, member A1 ( ALDH3A1 ; 9 KEGG pathways), integrin α9 ( ITGA9 ; 8 KEGG pathways), cytochrome c oxidase subunit VIb polypeptide 2 (testis) ( COX6B2 ; 7 KEGG pathways), complement component 1, q subcomponent, A chain ( C1QA ; 6 KEGG pathways), chemokine (C-C motif) ligand 3-like 3 ( CCL3L3 ; 6 KEGG pathways), chemokine (C-C motif) ligand 4-like 2 ( CCL4L2 ; 6 KEGG pathways), carboxyl ester lipase ( CEL ; 5 KEGG pathways), chemokine (C-X-C motif) receptor 4 ( CXCR4 ; 7 KEGG pathways), and von Willebrand factor ( VWF ; 5 KEGG pathways). Among these functionally active differentially expressed genes, VWF is an important endothelial cell injury marker. CCL3L3 , CCL4L2 , CXCR4 , and WAS all participate in the chemokine signaling pathway. Therefore, we showed these two annotated KEGG pathway maps, path: hsa04610 and path:hsa04062, to indicate that these differentially expressed genes may play important roles in hypoxia/re-oxygenation, especially in inflammatory response, endothelial cytoskeleton regulation, permeability, cellular growth and differentiation, cell lysis, apoptosis, reactive oxygen species (ROS) production, and nitric oxide (NO) production (Fig. 3 3 ). (a) von Willebrand factor ( VWF ), complement component 1, q subcomponent, A chain ( C1QA ), and complement and coagulation cascades pathway. On the map of the complement and coagulation cascades pathway, endothelial cell injury marker VWF , which is significantly down-expressed in hypoxia/re-oxygenation group in our database, plays an important role in thrombogenesis, endothelial permeability, and anti-inflammatory responses. C1QA , which is significantly up-expressed in the hypoxia/re-oxygenation group in our database, initiates the complement cascade and is involved in cell lysis, chemotaxis, and phagocytosis. The migration, aggregation, and phagocytosis of neutrophils are the important mechanisms leading to the large release of reactive oxygen species (ROS) during ischemia-reperfusion injury. (b) Chemokine (C-C motif) ligand 3-like 3 ( CCL3L3 ), chemokine (C-C motif) ligand 4-like 2 ( CCL4L2 ), chemokine (C-X-C motif) receptor 4 ( CXCR4 ), Wiskott-Aldrich syndrome ( WAS ), and chemokine signaling pathway. Significantly down-expressed chemokines CCL3L3 and CCL4L2 and significantly up-expressed chemokine receptor CXCR4 are the initiating molecules of the chemokine signaling pathway. This pathway is crucial in cellular growth and differentiation, cell survival and apoptosis, ROS and nitric oxide (NO) production. WAS , which is on one branch involved in regulation of actin cytoskeleton, is significantly down-expressed in the hypoxia/re-oxygenation group in our database Expression verification of differentially expressed gene PHLDA1 and exploration of related function based on HUVEC hypoxia/re-oxygenation transcriptome profiling 2 PHLDA1 was first identified as a potential transcription factor required for Fas expression and activation-induced apoptosis in mouse T cell hybridomas (Moad et al., 2013 2013 ). However, its expression is induced by a variety of external stimuli, and it participates in apoptosis, autophagy, cell proliferation and differentiation, inflammation, and fat metabolism (Johnson et al., 2011 2011 ; Sellheyer and Nelson, 2011 2011 ). Recently, PHLDA1 has received increased attention because of its association with cancer (Nagai, 2016 2016 ; Fearon et al., 2018 2018 ). In our microarray database, PHLDA1 was significantly up-expressed in the hypoxia/re-oxygenation group. Using real-time PCR and western blot assay, we validated that the mRNA and protein were both significantly highly expressed in the hypoxia/re-oxygenation group compared to the normoxia group (Figs. 4a–4c 4a–4c ). Based on the STRING search results of PHLDA1 protein–protein interactions (Fig. 4d 4d ), we found many potentially related proteins SLC38A3, SLC5A5, Lnc-SLC36A4-1, and Lnc-PLEKHJ1-1 in our differentially expressed database. (a, c) Western blot measurement of PHLDA1 expression in HUVECs influenced by hypoxia/re-oxygenation. (b) Effects of hypoxia/re-oxygenation on the mRNA expression of PHLDA1 in HUVECs. Results are normalized to β-actin . Data are expressed as mean±standard deviation (SD), n =3. Normoxia group: HUVECs incubated under 95% air and 5% CO 2 ; Hypoxia group: HUVECs incubated under 5% O 2 , 5% CO 2 and 90% N 2 for 3 h; Hypoxia/re-oxygenation group: HUVECs incubated under hypoxia for 3 h followed by 95% air and 5% CO 2 for 1 h. * P < 0.05, compared with the hypoxia/re-oxygenation group. (d) PHLDA1-related protein–protein interaction analysis using STRING database. The interactions include both the direct physical interactions between proteins and the indirect functional correlations between proteins. Related proteins SLC38A3, SLC5A5, Lnc-SLC36A4-1, and Lnc-PLEKHJ1-1 were significantly differentially expressed in our database Discussion 1 The known VEC hypoxia/re-oxygenation injury mechanisms consist of a complex pathophysiology involving activation of cell death programs, endothelial dysfunction, transcriptional reprogramming, and activation of the innate and adaptive immune system. Numerous pathways and signaling cascades are implicated (Salvadori et al., 2015 2015 ). VECs undergo swelling, loss of pinocytotic vesicles, degradation of the cytoskeleton, and lifting from the underlying basement membrane. As a consequence, intercellular contact of endothelial cells is lost, increasing vascular permeability and fluid loss to the interstitial space (Basile et al., 2011 2011 ). In addition, there is impaired endothelial function by directly reducing endothelial NO production at the transcriptional and posttranscriptional levels, leading to vasoconstriction and aggravating tissue ischemia despite reperfusion (McQuillan et al., 1994 1994 ; Liao et al., 1995 1995 ). Another important feature of VEC hypoxia/re-oxygenation injury is the chemotaxis of leukocytes, the accumulation and adhesion of circulating leukocytes (primarily neutrophils) to the endothelial cell surface, and enhanced oxidative stress, leading to vessel inflammation and progression (Eltzschig and Collard, 2004 2004 ). As shown by research, this process is initiated by increased expression of P-selectin on the VECs and interaction of P-selectin with P-selectin glycoprotein 1 (PSGL-1) expressed on the leukocytes. Subsequently, firm adherence of the leucocytes to the endothelium is achieved by the interaction of the β2-integrins lymphocyte function-associated antigen I (LFA-I) and macrophage-l antigen (MAC-I or complement receptor 3 (CR3)) on the leukocyte and the intracellular adhesion molecule 1 (ICAM-I) on the VEC. Platelet endothelial cell adhesion molecule 1 (PECAM-I) facilitates leukocyte transmigration into the interstitial space (Carden and Granger, 2000 2000 ). The present study used whole-transcriptome microarray to explore the genomic response of HUVECs to hypoxia/re-oxygenation. The microarray analysis identified that approximately 29 986 gene probes were involved in regulation under hypoxia/re-oxygenation exposure. Among them, 106 up-regulated gene probes and 266 down-regulated gene probes were identified as the differentially expressed gene probes. These encompass gene probes were involved in a multitude of pathways and functions, including production of oxygen free radicals, calcium overload, excessive activation of inflammation, glucose and lipid metabolism, endothelial cell proliferation, differentiation, cytoskeleton regulation, permeability, cell lysis, apoptosis, and angiogenesis. Many of the aforementioned VEC hypoxia/re-oxygenation-related genes (such as: regulation of actin cytoskeleton-related WAS ; NO synthase-related CNR2 , SCN5A ; regulation of vasoconstriction-related ASIC2 ; neutrophil chemotaxis and adhesion-related CCL3L3 , CCL4L2 , CXCR4 , ITGA9 ; neutrophil activation and ROS-related CXCR4 , KDM4C ; regulation of cell proliferation and apoptosis-related SLAMF1 , VWCE , FGFR2 , KDM4C , ALDH3A1 , NEURL , PHLDA1 , HMGA2 , PSMB11 ) were all found differentially expressed in the hypoxia/re-oxygenation group in our database. However, many VECs functionally related important genes (such as: the endothelial cell injury marker and coagulation-related VWF ; regulation of vascular endothelial growth factor (VEGF) receptor signaling pathway-related TMEM204 ; angiogenesis-related MMRN2 , FGFR2 , NRCAM ) and ischaemia and reperfusion injury (IRI)-related genes (such as: phosphatidylinositol phospholipase C (PLC) activity-related PLCH2 ; ion transport-related SLC38A3 , SCN5A , NPY ; complement activation-related C1QA ; lipid digestion-related CEL ), which were found as the differentially expressed genes, may also play a crucial role in VEC hypoxia/re-oxygenation injury. In fact, many meaningful hypoxia genes, such as hypoxia-inducible factor 1-α ( HIF1A ) and VEGF-related genes, were also contained in the microarray, including probes A_24_P56388 ( HIF1A ), A_33_P3231277 ( HIF1A ), A_22_P00016429 (HIF1A antisense RNA 1 ( HIF1A-AS1 )), A_22_P00020043 ( HIF1A-AS1 ), A_23_P46964 ( HIF1AN ), A_33_P3338152 ( HIF3A ), A_23_P142187 ( HIF3A ), A_23_P338534 ( HIF3A ), A_24_P12401 ( VEGFA ), A_23_P70398 ( VEGFA ), A_23_P1594 ( VEGFB ), A_23_P167096 ( VEGFC ), and A_21_P0003801 ( Lnc-VEGFC-1 ). However, the expression levels of these genes were not significantly different between the hypoxic/re-oxygenated group and the normoxia group. On the one hand, it may be because these genes are indeed not significantly different in this model; on the other hand, it may be because they are more active under the condition of hypoxia and are relatively silent after re-oxygenation, while other genes are more active. In addition, it has been found that endothelial cells are particularly resistant to hypoxic stress, and can maintain proliferation even after having been cultured in mild hypoxia in a time-dependent manner (Bader et al., 2015 2015 ; Sun et al., 2015 2015 ; Baldea et al., 2018 2018 ). Our results are also consistent with the above research. As mentioned earlier, PHLDA1 acts as a mediator of apoptosis (Moad et al., 2013 2013 ), plays an important role in cancer (Nagai, 2016 2016 ), and is annotated to “positive regulation of the apoptotic process” GO ID (Table 3 3 ). Expression verification of PHLDA1 mRNA or protein in our study had no obvious change after only exposure to hypoxia for 3 h (5% O 2 ), but was significantly up-expressed after re-oxygenation. This is consistent with our microarray results (Fig. 4 4 ). Recent research has also shown that PHLDA1 was highly expressed in myocardial ischemia-reperfusion injuries, and knockdown of PHLDA1 can attenuate oxidative stress-induced ROS production and apoptosis in cardiomyocytes (Guo et al., 2020 2020 ). PHLDA1 may promote oxidative stress-related apoptosis by binding to BCL2-associated X, apoptosis regulator (BAX). This research further validates our research in which PHLDA1 may play an important role in VEC hypoxia/re-oxygenation injury. Long non-coding RNAs (lncRNAs) in the nucleus have functions in histone modification and block the binding of transcription factors to their promoters or direct transcriptional regulation (E et al., 2018 2018 ; Mansoori et al., 2018 2018 ). More than 200 diseases are related to dysregulated or dysfunctional lncRNAs (Zampetaki et al., 2018 2018 ; Fu et al., 2019 2019 ; Gudenas et al., 2019 2019 ). Thus, exploration and identification of hypoxia/re-oxygenation-associated lncRNAs and their functions may provide a new insight into the understanding of VEC hypoxia/re-oxygenation pathogenesis and define novel therapeutic targets. Recent research reported that lncRNA HIF1A-AS2 can recruit lysine-specific demethylase 1 (LSD1) and epigenetically repress PHLDA1 (Mineo et al., 2016 2016 ). STRING analysis results showed that significantly differentially expressed genes SLC38A3 , SLC5A5 , Lnc-SLC36A4-1 , and Lnc-PLEKHJ1-1 in our database may have physical or/and functional protein–protein interactions with PHLDA1 (Fig. 4d 4d ). The interconnectedness of these genes is expected to reveal some potential hypoxia/re-oxygenation mechanisms related to lncRNAs. However, the validation of PHLDA1 and the analysis of interacting proteins were just one of many new discoveries in this study, and more validation and mechanism studies of the hypoxia/re-oxygenation genes found here will be further revealed. Conclusions 1 In summary, our microarray-based HUVEC hypoxia/re-oxygenation transcriptome profiling research was reasonable in design, with high reliability and repeatability. The differentially expressed genes revealed by the microarray largely compensate for the existing VEC hypoxia/re-oxygenation-related databases. Through GO, KEGG, and STRING analyses, we explored the new VEC hypoxia/re-oxygenation-related functions and protein–protein interactions, and put forward hypotheses for possible mechanisms of some lncRNAs. We believe that the results of this study have significance for understanding the mechanism of VEC hypoxia/re-oxygenation injury. References A Atkeson , SY Yeh , A Malhotra , 等 . Endothelial function in obstructive sleep apnea . 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This article does not contain any studies with human or animal subjects performed by any of the authors. 10.1631/jzus.B2000043 Project supported by the National Natural Science Foundation of China (Nos. 81801572 and 81272075), the Foundation of Key Discipline Construction of Zhejiang Province for Traditional Chinese Medicine (No. 2017-XKA36), the Foundation of Key Research Project of Zhejiang Province for Traditional Chinese Medicine (No. 2019ZZ014), the Medical and Health Science Foundation of Zhejiang Province (No. 2019327552), the Key Research and Development Program of Zhejiang Province (No. 2019C03076), the General Research Program of Zhejiang Provincial Department of Medical and Health (No. 2013KYA066), the Opening Foundation of State Key Laboratory for the Diagnosis and Treatment of Infectious Diseases (Nos. 2018KF02 and 2019KF06), and the Program of Education Department of Zhejiang Province (No. Y201738150), China 2020-02-05 2020-03-11 2022-01-05 Copyright © Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature 2020 2020 Journal of Zhejiang University-SCIENCE B (Biomedicine and Biotechnology) 04 21