Abstract
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.
Highlights
Immunity in infection, inflammation and malignancy differs markedly in man and mouse
We included only the 1:1 orthologs as defined by species interlinking in the Ensembl database, where homology predictions are generated by implementing maximum likelihood phylogenetic gene trees[24]
The obtained r2 values indicated no significant correlation in the gene expression of human and murine whole blood or macrophage transcriptomic profiles upon Mycobacterium tuberculosis (Mtb) infection (Table S1)
Summary
Inflammation and malignancy differs markedly in man and mouse. In first approaches towards evaluating similarity of immune responses to specific stimuli, Seok et al.[4] and Takao & Miyakawa[5] employed the same data sets from total blood leukocytes from patients and corresponding mouse models to calculate correlations in murine and human gene expression. A collection of over 5,000 immune system-specific gene sets based on publicly available data sets from mice and man was compiled[8] This collection facilitates access to gene modules regulated concordantly in immunologically relevant comparisons of various cell-state perturbations and diseases from either human or murine studies. Such analysis can be followed by identification of genes which drive phenotypic differences in both species. This can result in lack of attribution of a major biological importance to genes playing crucial roles in a given disease
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