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An unbiased systems genetics approach to mapping genetic loci modulating susceptibility to severe streptococcal sepsis.

Abdeltawab NF, Aziz RK, Kansal R, Rowe SL, Su Y, Gardner L, Brannen C, Nooh MM, Attia RR, Abdelsamed HA, Taylor WL, Lu L, Williams RW, Kotb M - PLoS Pathog. (2008)

Bottom Line: We had provided evidence that HLA class II allelic variation contributes significantly to differences in systemic disease severity by modulating host responses to streptococcal superantigens.By analyzing disease phenotypes in the context of mice genotypes we identified a highly significant quantitative trait locus (QTL) on Chromosome 2 between 22 and 34 Mb that strongly predicts disease severity, accounting for 25%-30% of variance.This QTL harbors several polymorphic genes known to regulate immune responses to bacterial infections.

View Article: PubMed Central - PubMed

Affiliation: Mid-South Center for Biodefense and Security, The University of Tennessee Health Science Center, Memphis, Tennessee, United States of America.

ABSTRACT
Striking individual differences in severity of group A streptococcal (GAS) sepsis have been noted, even among patients infected with the same bacterial strain. We had provided evidence that HLA class II allelic variation contributes significantly to differences in systemic disease severity by modulating host responses to streptococcal superantigens. Inasmuch as the bacteria produce additional virulence factors that participate in the pathogenesis of this complex disease, we sought to identify additional gene networks modulating GAS sepsis. Accordingly, we applied a systems genetics approach using a panel of advanced recombinant inbred mice. By analyzing disease phenotypes in the context of mice genotypes we identified a highly significant quantitative trait locus (QTL) on Chromosome 2 between 22 and 34 Mb that strongly predicts disease severity, accounting for 25%-30% of variance. This QTL harbors several polymorphic genes known to regulate immune responses to bacterial infections. We evaluated candidate genes within this QTL using multiple parameters that included linkage, gene ontology, variation in gene expression, cocitation networks, and biological relevance, and identified interleukin1 alpha and prostaglandin E synthases pathways as key networks involved in modulating GAS sepsis severity. The association of GAS sepsis with multiple pathways underscores the complexity of traits modulating GAS sepsis and provides a powerful approach for analyzing interactive traits affecting outcomes of other infectious diseases.

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Related in: MedlinePlus

Patterns of differential gene expression levels of candidate genes post infection in susceptible and resistant strains.Quantitative PCR results showing levels of gene expression of 14 genes with significant (P = 0.05–0.08) change post-infection in susceptible and resistant strains, expressed as Log fold differences in gene expression level post-infection. Genes are grouped to three groups, a) genes up regulated in susceptible strains post-infection and decreased in resistant strains post-infection, b) genes down regulated in both susceptible and resistant strains post-infection, and c) genes up regulated in both susceptible and resistant strains post-infection. Susceptible strains are represented as solid black bars, and resistant strains as dashed bars. The bars represent 2–4 biological replicates run in three technical replicates each and significance is based on t-test. Anapc2, anaphase promoting complex subunit 2; Entpd2, ectonucleoside triphosphate diphosphohydrolase 2; Edf1, endothelial differentiation-related factor 1; Garnl3, GTPase activating RANGAP domain-like 3; Il1a, interleukin 1 alpha; Il1rn, interleukin 1receptor antagonist; Nfatc2, nuclear factor of activated t-cells, cytoplasmic, calcineurin-dependent 2; Phpt1, phosphohistidine phosphatase 1; Ptges, prostaglandin E synthase; Ptges2, prostaglandin E synthase 2; Psmd5, proteasome (prosome, macropain) 26S subunit, non-ATPase 5; Ppp2r4, Protein phosphatase 2A regulatory subunit B; Sh2d3c, SH2 domain containing 3C; Traf1, TNF a receptor associated factor 1.
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ppat-1000042-g004: Patterns of differential gene expression levels of candidate genes post infection in susceptible and resistant strains.Quantitative PCR results showing levels of gene expression of 14 genes with significant (P = 0.05–0.08) change post-infection in susceptible and resistant strains, expressed as Log fold differences in gene expression level post-infection. Genes are grouped to three groups, a) genes up regulated in susceptible strains post-infection and decreased in resistant strains post-infection, b) genes down regulated in both susceptible and resistant strains post-infection, and c) genes up regulated in both susceptible and resistant strains post-infection. Susceptible strains are represented as solid black bars, and resistant strains as dashed bars. The bars represent 2–4 biological replicates run in three technical replicates each and significance is based on t-test. Anapc2, anaphase promoting complex subunit 2; Entpd2, ectonucleoside triphosphate diphosphohydrolase 2; Edf1, endothelial differentiation-related factor 1; Garnl3, GTPase activating RANGAP domain-like 3; Il1a, interleukin 1 alpha; Il1rn, interleukin 1receptor antagonist; Nfatc2, nuclear factor of activated t-cells, cytoplasmic, calcineurin-dependent 2; Phpt1, phosphohistidine phosphatase 1; Ptges, prostaglandin E synthase; Ptges2, prostaglandin E synthase 2; Psmd5, proteasome (prosome, macropain) 26S subunit, non-ATPase 5; Ppp2r4, Protein phosphatase 2A regulatory subunit B; Sh2d3c, SH2 domain containing 3C; Traf1, TNF a receptor associated factor 1.

Mentions: We found that 28 out of a representative 37 genes were differentially expressed post-infection (Table S2), of those 14 genes were down regulated in resistant group while up regulated in susceptible group post-infection. Nine genes were down regulated in both groups post-infection, and five were up regulated in both groups post-infection (Table S2). Fourteen of the 28 differentially expressed genes showed significant change post-infection in both resistant and susceptible strains (Table 1 and Figure 4). In general, susceptible strains showed increase in the relative expression levels post-infection (19 genes) of both pro and anti-inflammatory genes, e.g. interleukin1 alpha (Il1 α), and Il1 receptor antagonist (Il1rn) respectively. By contrast, in the resistant BXD strains, most of the tested genes showed a decrease (23 genes) in expression levels post-infection with few exceptions (five genes) e.g. TNF receptor associated factor 1 (Traf1) (Figure 4 and Table S2). Differentially expressed genes were associated with both innate and early adaptive immune response. Among those associated with early immune response, Il1a, Il1rn, prostaglandin E synthase (Ptges), and Ptges2 were up regulated in susceptible strains, whereas their levels decreased in resistant strains. Several of the differentially expressed genes show polymorphisms as SNPs between the parental strains B6 and D2, suggesting that these polymorphic genes modulate differential response to infection (Table S3). The differential expression of IL-1α was confirmed at the protein level (data not shown).


An unbiased systems genetics approach to mapping genetic loci modulating susceptibility to severe streptococcal sepsis.

Abdeltawab NF, Aziz RK, Kansal R, Rowe SL, Su Y, Gardner L, Brannen C, Nooh MM, Attia RR, Abdelsamed HA, Taylor WL, Lu L, Williams RW, Kotb M - PLoS Pathog. (2008)

Patterns of differential gene expression levels of candidate genes post infection in susceptible and resistant strains.Quantitative PCR results showing levels of gene expression of 14 genes with significant (P = 0.05–0.08) change post-infection in susceptible and resistant strains, expressed as Log fold differences in gene expression level post-infection. Genes are grouped to three groups, a) genes up regulated in susceptible strains post-infection and decreased in resistant strains post-infection, b) genes down regulated in both susceptible and resistant strains post-infection, and c) genes up regulated in both susceptible and resistant strains post-infection. Susceptible strains are represented as solid black bars, and resistant strains as dashed bars. The bars represent 2–4 biological replicates run in three technical replicates each and significance is based on t-test. Anapc2, anaphase promoting complex subunit 2; Entpd2, ectonucleoside triphosphate diphosphohydrolase 2; Edf1, endothelial differentiation-related factor 1; Garnl3, GTPase activating RANGAP domain-like 3; Il1a, interleukin 1 alpha; Il1rn, interleukin 1receptor antagonist; Nfatc2, nuclear factor of activated t-cells, cytoplasmic, calcineurin-dependent 2; Phpt1, phosphohistidine phosphatase 1; Ptges, prostaglandin E synthase; Ptges2, prostaglandin E synthase 2; Psmd5, proteasome (prosome, macropain) 26S subunit, non-ATPase 5; Ppp2r4, Protein phosphatase 2A regulatory subunit B; Sh2d3c, SH2 domain containing 3C; Traf1, TNF a receptor associated factor 1.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2277464&req=5

ppat-1000042-g004: Patterns of differential gene expression levels of candidate genes post infection in susceptible and resistant strains.Quantitative PCR results showing levels of gene expression of 14 genes with significant (P = 0.05–0.08) change post-infection in susceptible and resistant strains, expressed as Log fold differences in gene expression level post-infection. Genes are grouped to three groups, a) genes up regulated in susceptible strains post-infection and decreased in resistant strains post-infection, b) genes down regulated in both susceptible and resistant strains post-infection, and c) genes up regulated in both susceptible and resistant strains post-infection. Susceptible strains are represented as solid black bars, and resistant strains as dashed bars. The bars represent 2–4 biological replicates run in three technical replicates each and significance is based on t-test. Anapc2, anaphase promoting complex subunit 2; Entpd2, ectonucleoside triphosphate diphosphohydrolase 2; Edf1, endothelial differentiation-related factor 1; Garnl3, GTPase activating RANGAP domain-like 3; Il1a, interleukin 1 alpha; Il1rn, interleukin 1receptor antagonist; Nfatc2, nuclear factor of activated t-cells, cytoplasmic, calcineurin-dependent 2; Phpt1, phosphohistidine phosphatase 1; Ptges, prostaglandin E synthase; Ptges2, prostaglandin E synthase 2; Psmd5, proteasome (prosome, macropain) 26S subunit, non-ATPase 5; Ppp2r4, Protein phosphatase 2A regulatory subunit B; Sh2d3c, SH2 domain containing 3C; Traf1, TNF a receptor associated factor 1.
Mentions: We found that 28 out of a representative 37 genes were differentially expressed post-infection (Table S2), of those 14 genes were down regulated in resistant group while up regulated in susceptible group post-infection. Nine genes were down regulated in both groups post-infection, and five were up regulated in both groups post-infection (Table S2). Fourteen of the 28 differentially expressed genes showed significant change post-infection in both resistant and susceptible strains (Table 1 and Figure 4). In general, susceptible strains showed increase in the relative expression levels post-infection (19 genes) of both pro and anti-inflammatory genes, e.g. interleukin1 alpha (Il1 α), and Il1 receptor antagonist (Il1rn) respectively. By contrast, in the resistant BXD strains, most of the tested genes showed a decrease (23 genes) in expression levels post-infection with few exceptions (five genes) e.g. TNF receptor associated factor 1 (Traf1) (Figure 4 and Table S2). Differentially expressed genes were associated with both innate and early adaptive immune response. Among those associated with early immune response, Il1a, Il1rn, prostaglandin E synthase (Ptges), and Ptges2 were up regulated in susceptible strains, whereas their levels decreased in resistant strains. Several of the differentially expressed genes show polymorphisms as SNPs between the parental strains B6 and D2, suggesting that these polymorphic genes modulate differential response to infection (Table S3). The differential expression of IL-1α was confirmed at the protein level (data not shown).

Bottom Line: We had provided evidence that HLA class II allelic variation contributes significantly to differences in systemic disease severity by modulating host responses to streptococcal superantigens.By analyzing disease phenotypes in the context of mice genotypes we identified a highly significant quantitative trait locus (QTL) on Chromosome 2 between 22 and 34 Mb that strongly predicts disease severity, accounting for 25%-30% of variance.This QTL harbors several polymorphic genes known to regulate immune responses to bacterial infections.

View Article: PubMed Central - PubMed

Affiliation: Mid-South Center for Biodefense and Security, The University of Tennessee Health Science Center, Memphis, Tennessee, United States of America.

ABSTRACT
Striking individual differences in severity of group A streptococcal (GAS) sepsis have been noted, even among patients infected with the same bacterial strain. We had provided evidence that HLA class II allelic variation contributes significantly to differences in systemic disease severity by modulating host responses to streptococcal superantigens. Inasmuch as the bacteria produce additional virulence factors that participate in the pathogenesis of this complex disease, we sought to identify additional gene networks modulating GAS sepsis. Accordingly, we applied a systems genetics approach using a panel of advanced recombinant inbred mice. By analyzing disease phenotypes in the context of mice genotypes we identified a highly significant quantitative trait locus (QTL) on Chromosome 2 between 22 and 34 Mb that strongly predicts disease severity, accounting for 25%-30% of variance. This QTL harbors several polymorphic genes known to regulate immune responses to bacterial infections. We evaluated candidate genes within this QTL using multiple parameters that included linkage, gene ontology, variation in gene expression, cocitation networks, and biological relevance, and identified interleukin1 alpha and prostaglandin E synthases pathways as key networks involved in modulating GAS sepsis severity. The association of GAS sepsis with multiple pathways underscores the complexity of traits modulating GAS sepsis and provides a powerful approach for analyzing interactive traits affecting outcomes of other infectious diseases.

Show MeSH
Related in: MedlinePlus