Contributions to understanding the immune system Immunomics

1 contributions understanding immune system

1.1 immune cell activation , differentiation

1.1.1 b lymphocyte anergy
1.1.2 lymphocyte differentiation
1.1.3 lymphoid malignancies


1.2 immune response

1.2.1 macrophage responses bacteria
1.2.2 dendritic response pathogen


1.3 distinguishing immune cell types
1.4 immune cell regulatory networks

contributions understanding immune system

immunomics has made considerable impact on understanding of immune system uncovering differences in gene expression profiles of cell types, characterizing immune response, illuminating immune cell lineages , relationship, , establishing gene regulatory networks. whereas following list of contributions not complete, meant demonstrate broad application of immunomic research , powerful consequences on immunology.

immune cell activation , differentiation
b lymphocyte anergy

microarrays have discovered gene expression patterns correlate antigen-induced activation or anergy in b lymphocytes. lymphocyte anergy pathways involve induction of some, not of signaling pathways used during lymphocyte activation. example, nfat , mapk/erk kinase pathways expressed in anergic (or “tolerant) cell lines, whereas nf-kb , c-jun n-terminal kinases pathways not. of 300 genes altered in expression after antigen-stimulated naïve b cells, 8 of these genes regulated in tolerant b cells. understanding these “tolerance” pathways have important implications designing immunosuppressive drugs. these gene expression signatures of tolerant b cells used during drug screens probe compounds mimic functional effects of natural tolerance.

lymphocyte differentiation

gene expression profiles during human lymphocyte differentiation has followed mature, naïve b cells resting state through germinal center reactions , terminal differentiation. these studies have shown germinal center b cells represent distinct stage in differentiation because gene expression profile different activated peripheral b cells. although no in vitro culture system has been able induce resting peripheral b cells adopt full germinal center phenotype, these gene expression profiles can used measure success of in vitro cultures in mimicking germinal center state being developed.

lymphoid malignancies

about 9 of every 10 human lymphoid cancers derive b cells. distinct immunome-wide expression patterns in large number of diffuse large cell lymphoma (dlcl)– common form of non-hodgkin’s lymphoma – have identified @ least 2 different subtypes in thought single disease. 1 subset of these dlcls shows similar gene expression pattern of normal germinal center b cells , implies tumor cell originated germinal center b cell. other surveys of b cell malignancies show follicular lymphomas share expression features germinal center b cells, whereas chronic lymphocytic leukemia cells resemble resting peripheral blood lymphocytes. furthermore, heterogeneity in each of these cell lines suggest different subtypes exist within each type of lymphoma, has been shown in dlcl. such knowledge can used direct patients appropriate therapy.

immune response
macrophage responses bacteria

microarrays have analyzed global responses of macrophages different microorganisms , have confirmed these responses sustain , control inflammatory processes, , kill microorganisms. these independent studies have been able better describe how macrophages mount attacks against different microorganisms. “core transcriptional response” observed induce 132 genes , repress 59 genes. induced genes include pro-inflammatory chemokines , cytokines, , respective receptors. “pathogen-specific response” observed.

dendritic response pathogen

dendritic cells (dcs) macrophages sustain inflammatory processes , participate in innate immune system response, can prime adaptive immunity. gene expression analyses have shown dcs can “multi-task” temporally segregating different functions. after recognizing infectious agent, immature dcs transition state of activation via core response characterized rapid downregulation of genes involved pathogen recognition , phagocytosis, upregulation of cytokine , chemokine genes recruit other immune cells side of inflammations; , expression of genes control migratory capacity. activated dcs enabled migrate non-lymphoid tissues lymph nodes, can prime t-cell responses. these dcs responses related innate immunity , consist of “core transcriptional response” of dcs. pathogen-specific responses have stronger influence on dc’s ability regulate adaptive immunity.

distinguishing immune cell types

comparing distinctions between immune cells’ overall transcriptional program can generate plots position each cell type best reflect expression profile relative other cells , can reveal interesting relationships between cell types. example, transcriptional profiles thymic medullary epithelial immune cells mapped closer lymphocytes other epithelia. can suggest functional interaction exists between these 2 cells type , requires sharing of particular transcripts , proteins. when comparing gene expression profiles cells of blood system, t-cell , b-cell subsets tightly group respective cell types.

by looking @ transcriptional profile of different t-cells, scientists have shown natural killer t-cells close variant of conventional cd4+ t cells, rather intermediary cell-type between t cells , natural killer cells. additionally, dcs, natural killer cells, , b cells tightly grouped based on global expression profiles. may have been expected b lymphocytes , t lymphocytes cluster separately each other, or natural killer cells more closely related t cells because share common precursors, cytolytic activity, , similar activation markers. therefore, immunomics has established relationship between cell lineages depart classical views. additionally, may better explain observed plasticity in lymphoid , myeloid cell differentiation because of considerable overlap between global expression profiles of these different lineages.

immune cell regulatory networks

networks represent broadest level of genetic interactions , aim link genes , transcripts in immunological genome. cellular phenotypes , differentiation states established activity of these networks of co-regulated genes. 1 of complete networks in immunology has deciphered regulatory connections among normal , transformed human b cells. analysis suggests hierarchical network small number of highly connected genes (called “hubs”) regulated interactions. proto-oncogene myc emerged major hub , highly influential regulator b cells. notably, myc found directly control bysl, highly conserved, poorly characterized gene, , largest hub in whole b cell network. suggests bysl encodes important cellular molecule , critical effecter of myc function, , motivates additional studies elucidate function. therefore, using gene expression data create networks can reveal genes highly influential in immune cell differentiation pre-genomic technologies had not yet identified.