Genetic Architecture of Group A Streptococcal Necrotizing Soft Tissue Infections in the Mouse

Abstract

Host genetic variations play an important role in several pathogenic diseases, and we have previously provided strong evidences that these genetic variations contribute significantly to differences in susceptibility and clinical outcomes of invasive Group A Streptococcus (GAS) infections, including sepsis and necrotizing soft tissue infections (NSTIs). Our initial studies with conventional mouse strains revealed that host genetic variations and sex differences play an important role in orchestrating the severity, susceptibility and outcomes of NSTIs. To understand the complex genetic architecture of NSTIs, we utilized an unbiased, forward systems genetics approach in an advanced recombinant inbred (ARI) panel of mouse strains (BXD). Through this approach, we uncovered interactions between host genetics, and other non-genetic cofactors including sex, age and body weight in determining susceptibility to NSTIs. We mapped three NSTIs-associated phenotypic traits (i.e., survival, percent weight change, and lesion size) to underlying host genetic variations by using the WebQTL tool, and identified four NSTIs-associated quantitative genetic loci (QTL) for survival on mouse chromosome (Chr) 2, for weight change on Chr 7, and for lesion size on Chr 6 and 18 respectively. These QTL harbor several polymorphic genes. Identification of multiple QTL highlighted the complexity of the host-pathogen interactions involved in NSTI pathogenesis. We then analyzed and rank-ordered host candidate genes in these QTL by using the QTLminer tool and then developed a list of 375 candidate genes on the basis of annotation data and biological relevance to NSTIs. Further differential expression analyses revealed 125 genes to be significantly differentially regulated in susceptible strains compared to their uninfected controls. Several of these genes are involved in innate immunity, inflammatory response, cell growth, development and proliferation, and apoptosis. Additional network analyses using ingenuity pathway analysis (IPA) of these 125 genes revealed interleukin-1 beta network as key network involved in modulating the differential susceptibility to GAS NSTIs.

Association between cytokine response, the LRINEC score and outcome in patients with necrotising soft tissue infection: a multicentre, prospective study

“…Interestingly, IL-1β proved to be an independent predictor for 30-day mortality. Further support for IL-1β as a potentially useful marker for NSTI was recently provided in a murine model of streptococcal NSTI, in which IL-1β response network was identified as a key network involved in modulating severity of streptococcal NSTI 34 . Another limitation to this study is the limited time of follow-up regarding amputation.…”

Port d’Entrée for Respiratory Infections – Does the Influenza A Virus Pave the Way for Bacteria?

“…Most of the bacterial and viral species under study are human pathogens. In recent years it was also shown that host genetic variations and sex differences have an impact on predisposition, severity, and outcome of infection ( Chella Krishnan et al, 2015 , 2016 ) While C57BL/6 and BALB/c mice are characterized by a higher resistance, DBA/2 strains are more susceptible and permissive to bacterial and viral strains ( Alymova et al, 2011 ; Chella Krishnan et al, 2015 , 2016 ). In addition, transmission of IAV and bacteria is inefficient in adult mice, thus requiring alternative animal models, including neonatal mice or ferrets ( Diavatopoulos et al, 2010 ; McCullers et al, 2010 ).…”

Heterogeneity in FoxP3- and GARP/LAP-Expressing T Regulatory Cells in an HLA Class II Transgenic Murine Model of Necrotizing Soft Tissue Infections by Group A Streptococcus

“…An HLA-II tg mouse model of NSTI for Treg analysis. In order to understand the mechanisms and disease signatures underlying NSTI, we used a forward-genetics approach in an advanced recombinant inbred BxD mouse model specifically optimized for NSTI (24). To elucidate the role of HLA-II alleles and their influence on T-effector and Treg polarization during NSTI, we used a subcutaneous skin infection model of GASmediated NSTI in HLA-II transgenic mice that mimic lesions and inflammatory responses observed in humans.…”

“…We used the clinical isolate M1 GAS 2006 for the in vivo studies. GAS 2006 was grown under static conditions in Todd-Hewitt broth supplemented with 1.5% yeast extract for 17 h at 37°C (11,24,41). The bacteria were harvested by centrifugation, washed three times with sterile endotoxin-free Dulbecco's phosphate-buffered saline (DPBS), and resuspended in DPBS.…”