Compendium of Immune Signatures Identifies Conserved and Species-Specific Biology in Response to Inflammation.

Gene-expression profiling has become a mainstay in immunology, but subtle changes in gene networks related to biological processes are hard to discern when comparing various datasets. For instance, conservation of the transcriptional response to sepsis in mouse models and human disease remains controversial. To improve transcriptional analysis in immunology, we created ImmuneSigDB: a manually annotated compendium of ∼5,000 gene-sets from diverse cell states, experimental manipulations, and genetic perturbations in immunology. Analysis using ImmuneSigDB identified signatures induced in activated myeloid cells and differentiating lymphocytes that were highly conserved between humans and mice. Sepsis triggered conserved patterns of gene expression in humans and mouse models. However, we also identified species-specific biological processes in the sepsis transcriptional response: although both species upregulated phagocytosis-related genes, a mitosis signature was specific to humans. ImmuneSigDB enables granular analysis of transcriptomic data to improve biological understanding of immune processes of the human and mouse immune systems.

[1]  Lincoln Stein,et al.  Reactome: a database of reactions, pathways and biological processes , 2010, Nucleic Acids Res..

[2]  E. Wherry,et al.  Integrating genomic signatures for immunologic discovery. , 2010, Immunity.

[3]  T. Golub,et al.  Identification of an Evolutionarily Conserved Transcriptional Signature of CD8 Memory Differentiation That Is Shared by T and B Cells1 , 2008, The Journal of Immunology.

[4]  Pedro Romero,et al.  Exhaustion of tumor-specific CD8⁺ T cells in metastases from melanoma patients. , 2011, The Journal of clinical investigation.

[5]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[6]  J. Mesirov,et al.  An oncogenic KRAS2 expression signature identified by cross-species gene-expression analysis , 2005, Nature Genetics.

[7]  Virginia Pascual,et al.  A modular analysis framework for blood genomics studies: application to systemic lupus erythematosus. , 2008, Immunity.

[8]  J. Mesirov,et al.  Metagene projection for cross-platform, cross-species characterization of global transcriptional states , 2007, Proceedings of the National Academy of Sciences.

[9]  J. Mesirov,et al.  GenePattern 2.0 , 2006, Nature Genetics.

[10]  I. Weissman,et al.  Memory T and memory B cells share a transcriptional program of self-renewal with long-term hematopoietic stem cells. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[11]  M. Daly,et al.  PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes , 2003, Nature Genetics.

[12]  Helga Thorvaldsdóttir,et al.  Molecular signatures database (MSigDB) 3.0 , 2011, Bioinform..

[13]  Jill P. Mesirov,et al.  GSEA-P: a desktop application for Gene Set Enrichment Analysis , 2007, Bioinform..

[14]  N. Goldstein Mice are not men! , 1994, Hawaii medical journal.

[15]  Pablo Tamayo,et al.  Metagenes and molecular pattern discovery using matrix factorization , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[16]  Dennis B. Troup,et al.  NCBI GEO: mining tens of millions of expression profiles—database and tools update , 2006, Nucleic Acids Res..

[17]  N. Friedman,et al.  Densely Interconnected Transcriptional Circuits Control Cell States in Human Hematopoiesis , 2011, Cell.

[18]  Yoav Gilad,et al.  A reanalysis of mouse ENCODE comparative gene expression data , 2015, F1000Research.

[19]  H. Sebastian Seung,et al.  Algorithms for Non-negative Matrix Factorization , 2000, NIPS.

[20]  D. Koller,et al.  The Immunological Genome Project: networks of gene expression in immune cells , 2008, Nature Immunology.

[21]  Thomas R. Gingeras,et al.  Comparison of the transcriptional landscapes between human and mouse tissues , 2014, Proceedings of the National Academy of Sciences.

[22]  Keizo Takao,et al.  Genomic responses in mouse models greatly mimic human inflammatory diseases , 2014, Proceedings of the National Academy of Sciences.

[23]  Sandra Romero-Steiner,et al.  Molecular signatures of antibody responses derived from a systems biology study of five human vaccines , 2022 .

[24]  J. Mesirov,et al.  Integrative radiogenomic profiling of squamous cell lung cancer. , 2013, Cancer research.

[25]  A. Zaas,et al.  Two Genes on A/J Chromosome 18 Are Associated with Susceptibility to Staphylococcus aureus Infection by Combined Microarray and QTL Analyses , 2010, PLoS pathogens.

[26]  D. Redelmeier,et al.  Translation of research evidence from animals to humans. , 2006, JAMA.

[27]  H. Sebastian Seung,et al.  Learning the parts of objects by non-negative matrix factorization , 1999, Nature.

[28]  Steven J. M. Jones,et al.  Circos: an information aesthetic for comparative genomics. , 2009, Genome research.

[29]  Sean R. Davis,et al.  GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor , 2007, Bioinform..

[30]  Ian W. Dawes,et al.  Gene-expression profiling of peripheral blood mononuclear cells in sepsis* , 2009, Critical care medicine.

[31]  T. Miyakawa,et al.  Genomic responses in mouse models poorly mimic human inflammatory diseases , 2013 .

[32]  R. Gamelli,et al.  Genomic responses in mouse models poorly mimic human inflammatory diseases , 2013, Proceedings of the National Academy of Sciences.

[33]  Terence P. Speed,et al.  A comparison of normalization methods for high density oligonucleotide array data based on variance and bias , 2003, Bioinform..

[34]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[35]  C. Benoist,et al.  Genomic responses to inflammation in mouse models mimic humans: We concur, apples to oranges comparisons won’t do , 2014, Proceedings of the National Academy of Sciences.

[36]  D. Koller,et al.  Conservation and divergence in the transcriptional programs of the human and mouse immune systems , 2013, Proceedings of the National Academy of Sciences.

[37]  Mark M Davis,et al.  A prescription for human immunology. , 2008, Immunity.

[38]  Benjamin M. Bolstad,et al.  affy - analysis of Affymetrix GeneChip data at the probe level , 2004, Bioinform..

[39]  D. Howells,et al.  Can Animal Models of Disease Reliably Inform Human Studies? , 2010, PLoS medicine.

[40]  Björn Nilsson,et al.  Integrative genomic analysis of HIV-specific CD8+ T cells reveals that PD-1 inhibits T cell function by upregulating BATF , 2010, Nature Medicine.

[41]  Ben S. Wittner,et al.  Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1 , 2009, Nature.