Reprogramming of macrophages employing gene regulatory and metabolic network models

Upon exposure to different stimuli, resting macrophages undergo classical or alternative polarization into distinct phenotypes that can cause fatal dysfunction in a large range of diseases, such as systemic infection leading to sepsis or the generation of an immunosuppressive tumor microenvironment. Investigating gene regulatory and metabolic networks, we observed two metabolic switches during polarization. Most prominently, anaerobic glycolysis was utilized by M1-polarized macrophages, while the biosynthesis of inosine monophosphate was upregulated in M2-polarized macrophages. Moreover, we observed a switch in the urea cycle. Gene regulatory network models revealed E2F1, MYC, PPARγ and STAT6 to be the major players in the distinct signatures of these polarization events. Employing functional assays targeting these regulators, we observed the repolarization of M2-like cells into M1-like cells, as evidenced by their specific gene expression signatures and cytokine secretion profiles. The predicted regulators are essential to maintaining the M2-like phenotype and function and thus represent potential targets for the therapeutic reprogramming of immunosuppressive M2-like macrophages.

[1]  R. König,et al.  Cognate Interaction With CD4+ T Cells Instructs Tumor-Associated Macrophages to Acquire M1-Like Phenotype , 2019, Front. Immunol..

[2]  Abhishek K. Jha,et al.  Network integration of parallel metabolic and transcriptional data reveals metabolic modules that regulate macrophage polarization. , 2015, Immunity.

[3]  S. Schuster,et al.  Causes of upregulation of glycolysis in lymphocytes upon stimulation. A comparison with other cell types. , 2015, Biochimie.

[4]  S. Gordon,et al.  Metabolism of glucose, glutamine, long-chain fatty acids and ketone bodies by murine macrophages. , 1986, The Biochemical journal.

[5]  M. Boothby,et al.  Paired Stat6 C-terminal transcription activation domains required both for inhibition of an IFN-responsive promoter and trans-activation. , 1999, Journal of immunology.

[6]  M. J. Cody,et al.  TLR4, but not TLR2, mediates IFN-β–induced STAT1α/β-dependent gene expression in macrophages , 2002, Nature Immunology.

[7]  G. Evan,et al.  Role of c-MYC in alternative activation of human macrophages and tumor-associated macrophage biology. , 2012, Blood.

[8]  Markus J. Herrgård,et al.  Network-based prediction of human tissue-specific metabolism , 2008, Nature Biotechnology.

[9]  P. Sætrom,et al.  Regulation of Inflammatory Phenotype in Macrophages by a Diabetes-Induced Long Noncoding RNA , 2014, Diabetes.

[10]  Jun Li,et al.  Macrophage polarization and function with emphasis on the evolving roles of coordinated regulation of cellular signaling pathways. , 2014, Cellular signalling.

[11]  Avi Ma'ayan,et al.  ChEA: transcription factor regulation inferred from integrating genome-wide ChIP-X experiments , 2010, Bioinform..

[12]  S. Snapper,et al.  Anti-inflammatory effect of IL-10 mediated by metabolic reprogramming of macrophages , 2017, Science.

[13]  M. Sieweke,et al.  Beyond Stem Cells: Self-Renewal of Differentiated Macrophages , 2013, Science.

[14]  M. Weller,et al.  Immunosuppressive mechanisms in glioblastoma. , 2015, Neuro-oncology.

[15]  J. Demoulin,et al.  A Minimal Connected Network of Transcription Factors Regulated in Human Tumors and Its Application to the Quest for Universal Cancer Biomarkers , 2012, PloS one.

[16]  M. Barrachina,et al.  The Expression of MHC Class II Genes in Macrophages Is Cell Cycle Dependent1 , 2000, The Journal of Immunology.

[17]  W. Shi,et al.  The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote , 2013, Nucleic acids research.

[18]  Marcus Oswald,et al.  Estimating the activity of transcription factors by the effect on their target genes , 2014, Bioinform..

[19]  T. Rőszer,et al.  Understanding the Mysterious M2 Macrophage through Activation Markers and Effector Mechanisms , 2015, Mediators of inflammation.

[20]  D. Hardie,et al.  Metabolism of inflammation limited by AMPK and pseudo-starvation , 2013, Nature.

[21]  Divya Vats,et al.  Oxidative metabolism and PGC-1beta attenuate macrophage-mediated inflammation. , 2006, Cell metabolism.

[22]  Frank Brombacher,et al.  Macrophage-specific PPARγ controls alternative activation and improves insulin resistance , 2007, Nature.

[23]  S. Ruchholtz,et al.  Induced Hypothermia Does Not Harm Hemodynamics after Polytrauma: A Porcine Model , 2015, Mediators of inflammation.

[24]  K. Aird,et al.  Deoxyribonucleotide Triphosphate Metabolism in Cancer and Metabolic Disease , 2018, Front. Endocrinol..

[25]  T. Bíró,et al.  Bacterial Sepsis Increases Survival in Metastatic Melanoma: Chlamydophila Pneumoniae Induces Macrophage Polarization and Tumor Regression. , 2016, The Journal of investigative dermatology.

[26]  Wolfgang Huber,et al.  Love MI, Huber W, Anders S.. Moderated estimation of fold change and dispersion for RNA-Seq data with DESeq2. Genome Biol 15: 550 , 2014 .

[27]  p50 nuclear factor-kappaB overexpression in tumor-associated macrophages inhibits M1 inflammatory responses and antitumor resistance. , 2006, Cancer research.

[28]  Alan Aderem,et al.  Phagocytosis and the inflammatory response. , 2003, The Journal of infectious diseases.

[29]  Richard D. Smith,et al.  Proteomic Investigation of the Time Course Responses of RAW 264.7 Macrophages to Infection with Salmonella enterica , 2009, Infection and Immunity.

[30]  L. Joosten,et al.  Broad defects in the energy metabolism of leukocytes underlie immunoparalysis in sepsis , 2016, Nature Immunology.

[31]  Cole Trapnell,et al.  TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions , 2013, Genome Biology.

[32]  Federica Toffalini,et al.  Transcription factor regulation can be accurately predicted from the presence of target gene signatures in microarray gene expression data , 2010, Nucleic acids research.

[33]  Susan R. Quinn,et al.  Pyruvate Kinase M2 Regulates Hif-1α Activity and IL-1β Induction and Is a Critical Determinant of the Warburg Effect in LPS-Activated Macrophages. , 2015, Cell metabolism.

[34]  Data production leads,et al.  An integrated encyclopedia of DNA elements in the human genome , 2012 .

[35]  Rui Li,et al.  Transcription Factor E2F1 Suppresses Dendritic Cell Maturation , 2010, The Journal of Immunology.

[36]  Jeffrey D Orth,et al.  What is flux balance analysis? , 2010, Nature Biotechnology.

[37]  V. Nguyen,et al.  IL-4-activated STAT-6 inhibits IFN-gamma-induced CD40 gene expression in macrophages/microglia. , 2000, Journal of immunology.

[38]  Ernesto S. Nakayasu,et al.  Model-driven multi-omic data analysis elucidates metabolic immunomodulators of macrophage activation , 2012, Molecular systems biology.

[39]  Hedi Peterson,et al.  g:Profiler—a web server for functional interpretation of gene lists (2016 update) , 2016, Nucleic Acids Res..

[40]  angesichts der Corona-Pandemie,et al.  UPDATE , 1973, The Lancet.

[41]  Magdalena I. Swanson,et al.  PAZAR: a framework for collection and dissemination of cis-regulatory sequence annotation , 2007, Genome Biology.

[42]  Gordana Vunjak-Novakovic,et al.  Sequential delivery of immunomodulatory cytokines to facilitate the M1-to-M2 transition of macrophages and enhance vascularization of bone scaffolds. , 2015, Biomaterials.

[43]  Wei Shi,et al.  featureCounts: an efficient general purpose program for assigning sequence reads to genomic features , 2013, Bioinform..

[44]  R. Curi,et al.  A past and present overview of macrophage metabolism and functional outcomes. , 2017, Clinical science.

[45]  K. Zeller,et al.  Global Regulation of Nucleotide Biosynthetic Genes by c-Myc , 2008, PloS one.

[46]  R. Hotchkiss,et al.  Immunosuppression in sepsis: a novel understanding of the disorder and a new therapeutic approach. , 2013, The Lancet. Infectious diseases.

[47]  Björn Usadel,et al.  Trimmomatic: a flexible trimmer for Illumina sequence data , 2014, Bioinform..

[48]  B. Rubin,et al.  Mechanisms of Action and Clinical Application of Macrolides as Immunomodulatory Medications , 2010, Clinical Microbiology Reviews.

[49]  E A Anan'ko,et al.  [TRRD: a database of transcription regulatory regions in eukaryotic genes]. , 1997, Molekuliarnaia biologiia.

[50]  D. Zhuang,et al.  Direct role of nucleotide metabolism in C-MYC-dependent proliferation of melanoma cells , 2008, Cell cycle.

[51]  F. Finkelman,et al.  Local Macrophage Proliferation, Rather than Recruitment from the Blood, Is a Signature of TH2 Inflammation , 2011, Science.

[52]  Y. Ohmori,et al.  STAT6 Is Required for the Anti-inflammatory Activity of Interleukin-4 in Mouse Peritoneal Macrophages* , 1998, The Journal of Biological Chemistry.

[53]  E. Pearce,et al.  Immunometabolism governs dendritic cell and macrophage function , 2016, The Journal of experimental medicine.

[54]  J. Rathmell,et al.  A guide to immunometabolism for immunologists , 2016, Nature Reviews Immunology.

[55]  A. Nagler,et al.  Multiple myeloma cells recruit tumor-supportive macrophages through the CXCR4/CXCL12 axis and promote their polarization toward the M2 phenotype , 2014, Oncotarget.

[56]  ENCODEConsortium,et al.  An Integrated Encyclopedia of DNA Elements in the Human Genome , 2012, Nature.

[57]  R. Eils,et al.  Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast , 2016, Nucleic acids research.

[58]  Silvano Sozzani,et al.  The chemokine system in diverse forms of macrophage activation and polarization. , 2004, Trends in immunology.

[59]  Y. Ohmori,et al.  Anti-Inflammatory Cytokine Interleukin-4 Inhibits Inducible Nitric Oxide Synthase Gene Expression in the Mouse Macrophage Cell Line RAW264.7 through the Repression of Octamer-Dependent Transcription , 2013, Mediators of inflammation.

[60]  Ivan Ovcharenko,et al.  ECRbase: database of evolutionary conserved regions, promoters, and transcription factor binding sites in vertebrate genomes , 2007, Bioinform..

[61]  Neil Swainston,et al.  Improving metabolic flux predictions using absolute gene expression data , 2012, BMC Systems Biology.

[62]  V. Nguyen,et al.  IL-4-Activated STAT-6 Inhibits IFN-γ-Induced CD40 Gene Expression in Macrophages/Microglia1 , 2000, The Journal of Immunology.

[63]  Qingju Zhou,et al.  Involvement of JNK signaling in IL4‐induced M2 macrophage polarization , 2017, Experimental cell research.

[64]  H. Salamon,et al.  Infection with Mycobacterium tuberculosis induces the Warburg effect in mouse lungs , 2015, Scientific Reports.

[65]  T. Petrova,et al.  Microenvironmental regulation of tumour angiogenesis , 2017, Nature Reviews Cancer.

[66]  W. Huber,et al.  Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 , 2014, Genome Biology.

[67]  Lihua Liu,et al.  TRED: a Transcriptional Regulatory Element Database and a platform for in silico gene regulation studies , 2004, Nucleic Acids Res..

[68]  Ivana V. Yang,et al.  Novel regulators of the systemic response to lipopolysaccharide. , 2011, American journal of respiratory cell and molecular biology.

[69]  D. Hess,et al.  Escherichia coli and TNF-alpha modulate macrophage phagocytosis of Candida glabrata. , 2009, The Journal of surgical research.

[70]  Bernhard O. Palsson,et al.  Context-Specific Metabolic Networks Are Consistent with Experiments , 2008, PLoS Comput. Biol..

[71]  J. Michael Cherry,et al.  ENCODE data at the ENCODE portal , 2015, Nucleic Acids Res..

[72]  D. Green,et al.  Anthracyclines induce DNA damage response-mediated protection against severe sepsis. , 2013, Immunity.

[73]  Steven M. Gallo,et al.  The NFI-Regulome Database: A tool for annotation and analysis of control regions of genes regulated by Nuclear Factor I transcription factors , 2011, Journal of Clinical Bioinformatics.

[74]  R. Mahadevan,et al.  The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. , 2003, Metabolic engineering.

[75]  Jaak Vilo,et al.  g:Profiler—a web server for functional interpretation of gene lists (2011 update) , 2011, Nucleic Acids Res..

[76]  S. Inoue,et al.  Sepsis induces incomplete M2 phenotype polarization in peritoneal exudate cells in mice , 2016, Journal of Intensive Care.

[77]  E. Negelein,et al.  THE METABOLISM OF CARCINOMA CELLS , 2011 .

[78]  S. Lucas,et al.  Reprogramming of Tumor-Associated Macrophages with Anticancer Therapies: Radiotherapy versus Chemo- and Immunotherapies , 2017, Front. Immunol..