Concordant and discordant gene expression patterns in mouse strains identify best-fit animal model for human tuberculosis

Immunity in infection, inflammation and malignancy differs markedly in man and mouse. Still, we learn about human immunity in large extent from experimental mouse models. We propose a novel data integration approach which identifies concordant and discordant gene expression patterns of the immune responses in heterologous data sets. We have conducted experiments to compare human and murine transcriptional responses to Mycobacterium tuberculosis (Mtb) infection in whole blood (WB) as well as macrophages and compared them with simulated as well as publicly available data. Our results indicate profound differences between patterns of gene expression in innate and adaptive immunity in man and mouse upon Mtb infection. We characterized differential expression of T-cell related genes corresponding to the differences in phenotype between tuberculosis (TB) highly and low susceptible mouse strains. Our approach is general and facilitates the choice of optimal animal model for studies of the human immune response to a particular disease.

[1]  D. Malo,et al.  The Bcg/Ity/Lsh locus: genetic transfer of resistance to infections in C57BL/6J mice transgenic for the Nramp1 Gly169 allele , 1996, Infection and immunity.

[2]  W. Marshall,et al.  Counts and characteristics of macrophage precursors in human peripheral blood. , 1975, Cellular Immunology.

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

[4]  Matthew E. Ritchie,et al.  limma powers differential expression analyses for RNA-sequencing and microarray studies , 2015, Nucleic acids research.

[5]  P. Ricciardi-Castagnoli,et al.  Differential Production of Type I IFN Determines the Reciprocal Levels of IL-10 and Proinflammatory Cytokines Produced by C57BL/6 and BALB/c Macrophages , 2016, The Journal of Immunology.

[6]  D. Chaussabel,et al.  TPL-2–ERK1/2 Signaling Promotes Host Resistance against Intracellular Bacterial Infection by Negative Regulation of Type I IFN Production , 2013, The Journal of Immunology.

[7]  Mahavir Singh,et al.  Silencing Suppressor of Cytokine Signaling-1 (SOCS1) in Macrophages Improves Mycobacterium tuberculosis Control in an Interferon-γ (IFN-γ)-dependent Manner* , 2011, The Journal of Biological Chemistry.

[8]  Pablo Tamayo,et al.  Compendium of Immune Signatures Identifies Conserved and Species-Specific Biology in Response to Inflammation. , 2016, Immunity.

[9]  Y. Lotan,et al.  Bladder Cancer Biomarker Discovery Using Global Metabolomic Profiling of Urine , 2014, PloS one.

[10]  Jinfeng Liu,et al.  Non-canonical inflammasome activation targets caspase-11 , 2011, Nature.

[11]  Albert J. Vilella,et al.  EnsemblCompara GeneTrees: Complete, duplication-aware phylogenetic trees in vertebrates. , 2009, Genome research.

[12]  Stefan H. E. Kaufmann,et al.  Common patterns and disease-related signatures in tuberculosis and sarcoidosis , 2012, Proceedings of the National Academy of Sciences.

[13]  Virginia Pascual,et al.  An Interferon-Inducible Neutrophil-Driven Blood Transcriptional Signature in Human Tuberculosis , 2010, Nature.

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

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

[16]  North,et al.  Resistance ranking of some common inbred mouse strains to Mycobacterium tuberculosis and relationship to major histocompatibility complex haplotype and Nramp1 genotype , 1998, Immunology.

[17]  Vesteinn Thorsson,et al.  Identification of Tuberculosis Susceptibility Genes with Human Macrophage Gene Expression Profiles , 2008, PLoS pathogens.

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

[19]  S. Kaufmann,et al.  Versatile myeloid cell subsets contribute to tuberculosis‐associated inflammation , 2015, European journal of immunology.

[20]  Richard A. Young,et al.  Insights into host responses against pathogens from transcriptional profiling , 2005, Nature Reviews Microbiology.

[21]  R. Wilkinson,et al.  Neutrophils in tuberculosis: friend or foe? , 2012, Trends in immunology.

[22]  Sophia Davidson,et al.  Pathogenic potential of interferon αβ in acute influenza infection , 2014, Nature Communications.

[23]  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.

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

[25]  C. Hughes,et al.  Of Mice and Not Men: Differences between Mouse and Human Immunology , 2004, The Journal of Immunology.

[26]  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.

[27]  V. Mischenko,et al.  Lung cell responses to M. tuberculosis in genetically susceptible and resistant mice following intratracheal challenge , 2004, Clinical and experimental immunology.

[28]  G. Beamer,et al.  Murine models of susceptibility to tuberculosis. , 2005, Archivum immunologiae et therapiae experimentalis.

[29]  I. Orme,et al.  Tuberculosis in Mice Immunological Basis for Reactivation Of , 2001 .

[30]  E. Birney,et al.  Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt , 2009, Nature Protocols.

[31]  R. Cagliani,et al.  Pathogen-Driven Selection in the Human Genome , 2013, International journal of evolutionary biology.

[32]  P. Pontarotti.  Evolutionary Biology: Genome Evolution, Speciation, Coevolution and Origin of Life , 2014, Springer International Publishing.

[33]  J. Schreiber,et al.  MicroRNA-223 controls susceptibility to tuberculosis by regulating lung neutrophil recruitment. , 2013, The Journal of clinical investigation.

[34]  M. Burns,et al.  Case-Control Study , 2020, Definitions.

[35]  G. Ball,et al.  Temporal Expression of Peripheral Blood Leukocyte Biomarkers in a Macaca fascicularis Infection Model of Tuberculosis; Comparison with Human Datasets and Analysis with Parametric/Non-parametric Tools for Improved Diagnostic Biomarker Identification , 2016, PloS one.

[36]  Bart De Moor,et al.  BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis , 2005, Bioinform..

[37]  H. Mollenkopf,et al.  Type I IFN signaling triggers immunopathology in tuberculosis-susceptible mice by modulating lung phagocyte dynamics , 2014, European journal of immunology.

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

[39]  Michael Levin,et al.  Detection of Tuberculosis in HIV-Infected and -Uninfected African Adults Using Whole Blood RNA Expression Signatures: A Case-Control Study , 2013, PLoS medicine.

[40]  S. Kaufmann,et al.  Suppressor of cytokine signaling-3 is affected in T-cells from tuberculosisTB patients. , 2011, Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases.

[41]  Dirk Repsilber,et al.  Functional Correlations of Pathogenesis-Driven Gene Expression Signatures in Tuberculosis , 2011, PloS one.

[42]  Daniel L. Ruderman,et al.  IFN-β-regulated genes show abnormal expression in therapy-naïve relapsing–remitting MS mononuclear cells: Gene expression analysis employing all reported protein–protein interactions , 2008, Journal of Neuroimmunology.

[43]  Teresa Domaszewska,et al.  tmod: an R package for general and multivariate enrichment analysis , 2016 .

[44]  N. Van Rooijen,et al.  Subpopulations of Mouse Blood Monocytes Differ in Maturation Stage and Inflammatory Response1 , 2004, The Journal of Immunology.