This article is part of the supplement: UT-ORNL-KBRIN Bioinformatics Summit 2008 .

Poster presentation

Bioinformatics analysis of immune response to group A streptococcal sepsis integrating quantitative trait loci mapping with genome-wide expression studies

Nourtan Abdeltawab^1,5, Rita Kansal¹, Sarah Rowe⁵, Lidia Gardner¹, Charity Brannen¹, Mohammed Nooh^1,2,5, Santhosh Mukundan¹, Hossam Abdelsamed^1,2,5, Ramy Attia^1,5, William Taylor⁴, Lu Lu³, Robert Williams³ and Malak Kotb^1,2,5

¹Department of Ophthalmology, University of Tennessee Health Science Center, Memphis, TN 38163, USA

²Department of Molecular Sciences, University of Tennessee Health Science Center, Memphis, TN 38163, USA

³Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN 38163, USA

⁴Molecular Resource Center, University of Tennessee Health Science Center, Memphis, TN 38163, USA

⁵Veterans Affairs Medical Center, Memphis, TN 38104, USA

author email corresponding author email

from UT-ORNL-KBRIN Bioinformatics Summit 2008
Cadiz, KY, USA. 28–30 March 2008

BMC Bioinformatics 2008, 9(Suppl 7):P6doi:10.1186/1471-2105-9-S7-P6

The electronic version of this abstract is the complete one and can be found online at: http://www.biomedcentral.com/1471-2105/9/S7/P6

Published:

8 July 2008

© 2008 Abdeltawab et al; licensee BioMed Central Ltd.

Poster presentation

Individuals infected with genetically identical group A streptococcal (GAS) strains develop starkly different disease progression and outcome [1]. We reported that HLA class II allelic variation contributes to differences in systemic disease severity by modulating host responses to streptococcal superantigens [2]. Inasmuch as the bacteria produce additional virulence factors, we sought to identify additional host gene networks modulating GAS sepsis. Accordingly, we used two parallel approaches to define these gene networks, quantitative trait loci (QTL) mapping and genome-wide transcriptome analyses. To map QTLs modulating response to severe GAS sepsis, we used advanced recombinant inbred (ARI) strains, which are genetically diverse strains that have common ancestral parents [3]. We chose to use BXD strains of ARI mice, as parental strains C57Bl/6J (B6) and DBA/2J (D2) show differential response to GAS sepsis and BXD strains are heavily genotyped at 13377 SNPs and microsatellite markers. BXD strains, derived from B6 and D2 parental strains, are homozygous inbred lines, each of which is genetically distinct. Using 30 different BXD strains (n = 5–26 mice per strain), we identified significant QTLs on chromosome 2 that strongly modulate disease severity [4]. To narrow down these mapped QTLs, we applied bioinformatics tools including: linkage, interval specific haplotype analyses, and gene ontology and we identified multiple candidate gene networks modulating immune response to sepsis.

As a parallel approach, we performed genome-wide transcriptome analyses comparing resistant and susceptible strains. This comparison revealed 93 genes that were differentially regulated in mice spleens 36 h post-infection. These genes belonged to gene networks involving immune response to sepsis; particularly notable examples were prostaglandin (Ptges) and interleukin1 (IL-1) family pathways. Quantitative expression analyses, using real time PCR, of prostaglandin E synthase (Ptges), Ptges 2, Il1 and Il1 receptor antagonist (Il1rn) showed upregulation of these genes in spleens of susceptible strains post-infection. This upregulation in Il1 expression in susceptible strains was mirrored on protein levels as measured as plasma cytokines. Interestingly the gene networks that we identified using the two approaches share many common pathways. Therefore, integration of QTL mapping with differential gene expression uncovered multiple pathways modulating differential susceptibility to severe GAS sepsis, underscoring the complexity of traits modulating severe GAS sepsis.

Acknowledgements

This work was supported by grant AI4 0198-06 from NIH National Institute of Allergy and Infectious Diseases NIAID (to M.K.), the Research and Development Office, Medical Research Service, Department of Veterans Affairs (Merit Award to M.K.) and the U.S. Army Medical Research Grant W81XWH-05-1-0227 (to M.K.).

Development and maintenance of Gene Network and the BXD Colony is partly supported by INIA and Human Brain Project funded jointly by the NIMH, NIDA, and NIAAA (P20-DA 21131, U01AA13499 to R.W.W.), NCI MMHCC (U01CA105417 to R.W.W.), and the Biomedical Informatics Research Network (BIRN), NCRR (U24 RR021760 to R.W.W.).

References

1. Chatellier S, Ihendyane N, Kansal RG, Khambaty F, Basma H, Norrby-Teglund A, Low DE, McGeer A, Kotb M: Genetic relatedness and superantigen expression in group A streptococcus serotype M1 isolates from patients with severe and nonsevere invasive diseases.

   Infect Immun 2000, 68(6):3523-3534. PubMed Abstract | Publisher Full Text | PubMed Central Full Text

2. Kotb M, Norrby-Teglund A, McGeer A, El-Sherbini H, Dorak MT, Khurshid A, Green K, Peeples J, Wade J, Thomson G, et al.: An immunogenetic and molecular basis for differences in outcomes of invasive group A streptococcal infections.

   Nat Med 2002, 8(12):1398-1404. PubMed Abstract | Publisher Full Text

3. Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice.

   BMC Genet 2004, 5:7. PubMed Abstract | BioMed Central Full Text | PubMed Central Full Text

4. Abdeltawab N, Aziz RK, Kansal R, Rowe S, Su Y, Gardner LA, Brannen C, Nooh M, Attia R, Abdelsamed H, et al.: An unbiased systems genetics approach to mapping genetic loci modulating susceptibility to severe streptococcal sepsis.

   PLoS Pathog 2008, in press. PubMed Abstract | Publisher Full Text | PubMed Central Full Text

Have something to say? Post a comment on this article!