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Unveiling differentially expressed genes upon regulation of transcription factors in sepsis

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Abstract

In this study, we integrated the gene expression data of sepsis to reveal more precise genome-wide expression signature to shed light on the pathological mechanism of sepsis. Differentially expressed genes via integrating five microarray datasets from the Gene Expression Omnibus database were obtained. The gene function and involved pathways of differentially expressed genes (DEGs) were detected by GeneCodis3. Transcription factors (TFs) targeting top 20 dysregulated DEGs (including up- and downregulated genes) were found based on the TRANSFAC. A total of 1339 DEGs were detected including 788 upregulated and 551 downregulated genes. These genes were mostly involved in DNA-dependent transcription regulation, blood coagulation, and innate immune response, pathogenic escherichia coli infection, epithelial cell signaling in helicobacter pylori infection, and chemokine signaling pathway. TFs bioinformatic analysis of 20 DEGs generated 374 pairs of TF-target gene involving 47 TFs. At last, we found that five top ten upregulated DEGs (S100A8, S100A9, S100A12, PGLYRP1 and MMP9) and three downregulated DEGs (ZNF84, CYB561A3 and BST1) were under the regulation of three hub TFs of Pax-4, POU2F1, and Nkx2–5. The identified eight DEGs may be regarded as the diagnosis marker and drug target for sepsis.

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References

  • Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR (2001) Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med 29:1303–1310

    Article  CAS  Google Scholar 

  • Annane D, Aegerter P, Jars-Guincestre MC, Guidet B (2003) Current epidemiology of septic shock: the CUB-Rea network. Am J Respir Crit Care Med 168:165–172. doi:10.1164/rccm.2201087

    Article  Google Scholar 

  • Assou S et al (2009) A gene expression signature shared by human mature oocytes and embryonic stem cells. BMC Genom 10:10. doi:10.1186/1471-2164-10-10

    Article  Google Scholar 

  • Brunkhorst FM, Reinhart K (2009) Diagnosis and causal treatment of sepsis. Der Internist 50:810–816. doi:10.1007/s00108-008-2287-5

    Article  CAS  Google Scholar 

  • Calvano SE et al (2005) A network-based analysis of systemic inflammation in humans. Nature 437:1032–1037. doi:10.1038/nature03985

    Article  CAS  Google Scholar 

  • Cazalis MA et al (2014) Early and dynamic changes in gene expression in septic shock patients: a genome-wide approach. Intensive Care Med Exp 2:20. doi:10.1186/s40635-014-0020-3

    Article  Google Scholar 

  • Chang KH, Wu YR, Chen YC, Fung HC, Lee-Chen GJ, Chen CM (2015) STK39, But Not BST1, HLA-DQB1, and SPPL2B polymorphism, is associated with Han-Chinese Parkinson’s disease in Taiwan. Medicine 94:e1690. doi:10.1097/md.0000000000001690

    Article  CAS  Google Scholar 

  • de Montmollin E, Annane D (2011) Year in review 2010: critical care-multiple organ dysfunction and sepsis. Crit care 15:236. doi:10.1186/cc10359

    Article  Google Scholar 

  • Diboun I, Wernisch L, Orengo CA, Koltzenburg M (2006) Microarray analysis after RNA amplification can detect pronounced differences in gene expression using limma. BMC Genom 7:252. doi:10.1186/1471-2164-7-252

    Article  Google Scholar 

  • Dziarski R, Platt KA, Gelius E, Steiner H, Gupta D (2003) Defect in neutrophil killing and increased susceptibility to infection with nonpathogenic gram-positive bacteria in peptidoglycan recognition protein-S (PGRP-S)-deficient mice. Blood 102:689–697. doi:10.1182/blood-2002-12-3853

    Article  CAS  Google Scholar 

  • Foell D et al (2013) Proinflammatory S100A12 can activate human monocytes via Toll-like receptor 4. Am J Respir Crit Care Med 187:1324–1334. doi:10.1164/rccm.201209-1602OC

    Article  CAS  Google Scholar 

  • Galliera E, Tacchini L, Corsi Romanelli MM (2015) Matrix metalloproteinases as biomarkers of disease: updates and new insights. Clin Chem Lab Med 53:349–355. doi:10.1515/cclm-2014-0520

    Article  CAS  Google Scholar 

  • Hoesel B, Schmid JA (2013) The complexity of NF-kappaB signaling in inflammation and cancer. Mol cancer 12:86. doi:10.1186/1476-4598-12-86

    Article  CAS  Google Scholar 

  • Inoue H, Nomiyama J, Nakai K, Matsutani A, Tanizawa Y, Oka Y (1998) Isolation of full-length cDNA of mouse PAX4 gene and identification of its human homologue. Biochem Biophys Res Commun 243:628–633. doi:10.1006/bbrc.1998.8144

    Article  CAS  Google Scholar 

  • Ishihara K, Hirano T (2000) BST-1/CD157 regulates the humoral immune responses in vivo. Chem Immunol 75:235–255

    Article  CAS  Google Scholar 

  • Kanehisa M, Goto S (2000) KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28:27–30

    Article  CAS  Google Scholar 

  • Kang D, Liu G, Lundstrom A, Gelius E, Steiner H (1998) A peptidoglycan recognition protein in innate immunity conserved from insects to humans. Proc Natl Acad Sci USA 95:10078–10082

    Article  CAS  Google Scholar 

  • Kesh K et al (2015) Association of MMP7-181A→G promoter polymorphism with gastric cancer risk: influence of nicotine in differential allele-specific transcription via increased phosphorylation of cAMP-response element-binding protein (CREB). J Biol Chem 290:14391–14406. doi:10.1074/jbc.M114.630129

    Article  CAS  Google Scholar 

  • Komuro I, Izumo S (1993) Csx: a murine homeobox-containing gene specifically expressed in the developing heart. Proc Natl Acad Sci USA 90:8145–8149

    Article  CAS  Google Scholar 

  • Kurz T, Gustafsson B, Brunk UT (2006) Intralysosomal iron chelation protects against oxidative stress-induced cellular damage. FEBS J 273:3106–3117. doi:10.1111/j.1742-4658.2006.05321.x

    Article  CAS  Google Scholar 

  • Lints TJ, Parsons LM, Hartley L, Lyons I, Harvey RP (1993) Nkx-2.5: a novel murine homeobox gene expressed in early heart progenitor cells and their myogenic descendants. Development 119:419–431

    CAS  Google Scholar 

  • Liu C, Gelius E, Liu G, Steiner H, Dziarski R (2000) Mammalian peptidoglycan recognition protein binds peptidoglycan with high affinity, is expressed in neutrophils, and inhibits bacterial growth. J Biol Chem 275:24490–24499. doi:10.1074/jbc.M001239200

    Article  CAS  Google Scholar 

  • Liu C, Xu Z, Gupta D, Dziarski R (2001) Peptidoglycan recognition proteins: a novel family of four human innate immunity pattern recognition molecules. J Biol Chem 276:34686–34694. doi:10.1074/jbc.M105566200

    Article  CAS  Google Scholar 

  • Lopez-Bergami P, Lau E, Ronai Z (2010) Emerging roles of ATF2 and the dynamic AP1 network in cancer. Nat Rev Cancer 10:65–76. doi:10.1038/nrc2681

    Article  CAS  Google Scholar 

  • McKie AT et al (2001) An iron-regulated ferric reductase associated with the absorption of dietary iron. Science 291:1755–1759. doi:10.1126/science.1057206 (New York, NY)

    Article  CAS  Google Scholar 

  • Mordvinov VA et al (1999) Binding of YY1 and Oct1 to a novel element that downregulates expression of IL-5 in human T cells. J Allergy Clin Immunol 103:1125–1135

    Article  CAS  Google Scholar 

  • Morone S et al (2012) Overexpression of CD157 contributes to epithelial ovarian cancer progression by promoting mesenchymal differentiation. PLoS One 7:e43649. doi:10.1371/journal.pone.0043649

    Article  CAS  Google Scholar 

  • Mullen M, Gonzalez-Perez RR (2016) Leptin-Induced JAK/STAT signaling and cancer growth. Vaccines 4:26. doi:10.3390/vaccines4030026

    Article  Google Scholar 

  • Nakamura T, Ebihara I, Shimada N, Shoji H, Koide H (1998) Modulation of plasma metalloproteinase-9 concentrations and peripheral blood monocyte mRNA levels in patients with septic shock: effect of fiber-immobilized polymyxin B treatment. Am J Med Sci 316:355–360

    CAS  Google Scholar 

  • Pal S, Bhattacharjee A, Ali A, Mandal NC, Mandal SC, Pal M (2014) Chronic inflammation and cancer: potential chemoprevention through nuclear factor kappa B and p53 mutual antagonism. J Immunol 11:23. doi:10.1186/1476-9255-11-23

    Google Scholar 

  • Park SY, Jing X, Gupta D, Dziarski R (2013) Peptidoglycan recognition protein 1 enhances experimental asthma by promoting Th2 and Th17 and limiting regulatory T cell and plasmacytoid dendritic cell responses. J Immunol 190:3480–3492. doi:10.4049/jimmunol.1202675

    Article  CAS  Google Scholar 

  • Pellegrina DV, Severino P, Machado MC, Pinheiro da Silva F, Reis EM (2015) Microarray gene expression analysis of neutrophils from elderly septic patients. Genom Data 6:51–53. doi:10.1016/j.gdata.2015.08.013

    Article  Google Scholar 

  • Phillips K, Luisi B (2000) The virtuoso of versatility: POU proteins that flex to fit. J Mol Biol 302:1023–1039. doi:10.1006/jmbi.2000.4107

    Article  CAS  Google Scholar 

  • Ramana KV, Tammali R, Srivastava SK (2010) Inhibition of aldose reductase prevents growth factor-induced G1-S phase transition through the AKT/phosphoinositide 3-kinase/E2F-1 pathway in human colon cancer cells. Mol Cancer Ther 9:813–824. doi:10.1158/1535-7163.mct-09-0795

    Article  CAS  Google Scholar 

  • Roth J, Vogl T, Sorg C, Sunderkotter C (2003) Phagocyte-specific S100 proteins: a novel group of proinflammatory molecules. Trends Immunol 24:155–158

    Article  CAS  Google Scholar 

  • Ryan AK, Rosenfeld MG (1997) POU domain family values: flexibility, partnerships, and developmental codes. Genes Dev 11:1207–1225

    Article  CAS  Google Scholar 

  • Smoot ME, Ono K, Ruscheinski J, Wang PL, Ideker T (2011) Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27:431–432. doi:10.1093/bioinformatics/btq675

    Article  CAS  Google Scholar 

  • Speake C et al (2015) An interactive web application for the dissemination of human systems immunology data. J Trans Med 13:196. doi:10.1186/s12967-015-0541-x

    Article  Google Scholar 

  • Standage SW, Wong HR (2011) Biomarkers for pediatric sepsis and septic shock. Expert Rev Anti Infect Ther 9:71–79. doi:10.1586/eri.10.154

    Article  CAS  Google Scholar 

  • Tabas-Madrid D, Nogales-Cadenas R, Pascual-Montano A (2012) GeneCodis3: a non-redundant and modular enrichment analysis tool for functional genomics. Nucleic Acids Res 40:W478–W483. doi:10.1093/nar/gks402

    Article  CAS  Google Scholar 

  • Terrin G et al (2011) Serum calprotectin: an antimicrobial peptide as a new marker for the diagnosis of sepsis in very low birth weight newborns. Clin Dev Immunol 2011:291085. doi:10.1155/2011/291085

    Article  Google Scholar 

  • Tydell CC, Yount N, Tran D, Yuan J, Selsted ME (2002) Isolation, characterization, and antimicrobial properties of bovine oligosaccharide-binding protein. A microbicidal granule protein of eosinophils and neutrophils. J Biol Chem 277:19658–19664. doi:10.1074/jbc.M200659200

    Article  CAS  Google Scholar 

  • Vandooren J, Van den Steen PE, Opdenakker G (2013) Biochemistry and molecular biology of gelatinase B or matrix metalloproteinase-9 (MMP-9): the next decade. Crit Rev Biochem Mol Biol 48:222–272. doi:10.3109/10409238.2013.770819

    Article  CAS  Google Scholar 

  • Walther C et al (1991) Pax: a murine multigene family of paired box-containing genes. Genomics 11:424–434

    Article  CAS  Google Scholar 

  • Wang D, DuBois RN (2010) Therapeutic potential of peroxisome proliferator-activated receptors in chronic inflammation and colorectal cancer. Gastroenterol Clin North Am 39:697–707. doi:10.1016/j.gtc.2010.08.014

    Article  Google Scholar 

  • Wingender E (2008) The TRANSFAC project as an example of framework technology that supports the analysis of genomic regulation. Brief Bioinform 9:326–332. doi:10.1093/bib/bbn016

    Article  CAS  Google Scholar 

  • Yepes S, Torres MM, Andrade RE (2015) Clustering of expression data in chronic lymphocytic leukemia reveals new molecular subdivisions. PLoS One 10:e0137132. doi:10.1371/journal.pone.0137132

    Article  Google Scholar 

  • Young MD, Wakefield MJ, Smyth GK, Oshlack A (2010) Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol 11:R14. doi:10.1186/gb-2010-11-2-r14

    Article  Google Scholar 

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Author notes

  1. Junli Zhang and Yuelei Cheng contributed equally to this paper and should be considered as co-first authors

Authors and Affiliations

  1. Department of Emergency Medicine, Affiliated Hospital of Taishan Medical University of Shandong Province, No.706 TaiShan Street, Taishan District, Taian, 271000, China

    Junli Zhang, Yuelei Cheng & Jian Liu

  2. Department of Pediatrics, Affiliated Hospital of Taishan Medical University of Shandong Province, Taian, China

    Minmin Duan & Nannan Qi

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  1. Junli Zhang
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Correspondence to Jian Liu.

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Zhang, J., Cheng, Y., Duan, M. et al. Unveiling differentially expressed genes upon regulation of transcription factors in sepsis. 3 Biotech 7, 46 (2017). https://doi.org/10.1007/s13205-017-0713-x

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