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Keywords:

  • mouse;
  • intravenous;
  • gastrointestinal;
  • Candida ;
  • immunity;
  • therapy

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Mouse models of systemic Candida infection
  5. Candida virulence and behaviour in vivo
  6. Host responses during infection and disease
  7. The role of mouse infection models in the development of new diagnostics and therapies
  8. Outlook
  9. Acknowledgements
  10. References

Some Candida species are common commensals, which can become opportunistic pathogens in susceptible hosts. In severely ill patients, Candida species, particularly Candida albicans, can cause life-threatening systemic infections. These infections are difficult to diagnose, as symptoms are similar to those of systemic bacterial infections. These difficulties can lead to delays in initiation in antifungal therapy, which contributes to the high mortality rates (>40%) associated with these infections. In order to investigate systemic Candida infection, mouse models have been developed that mimic human disease, the most common being the intravenous infection model and the gastrointestinal colonization and dissemination model. This review discusses the two models and the contributions that they have made to our understanding of fungal virulence, host response to infection and the development of novel antifungal therapies and diagnostics.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Mouse models of systemic Candida infection
  5. Candida virulence and behaviour in vivo
  6. Host responses during infection and disease
  7. The role of mouse infection models in the development of new diagnostics and therapies
  8. Outlook
  9. Acknowledgements
  10. References

A select number of Candida species are usually found as harmless commensals in the gastrointestinal tract, oral cavity and genital area of healthy individuals. Candida spp. can be isolated from the majority of healthy individuals, with the highest fungal counts found in the duodenum (Kusne et al., 1994). The most common species isolated is Candida albicans, with Candida parapsilosis, Candida glabrata, Candida tropicalis, Candida dubliniensis and Candida krusei also found (Kusne et al., 1994; Scanlan & Marchesi, 2008).

Candida species are opportunistic pathogens and, in hosts with altered immune or physiological responses, can cause infections ranging from superficial mucosal lesions (thrush) to disseminated or bloodstream infection. Candida species cause approximately 11% of all bloodstream infections (reviewed in MacCallum, 2010), with C. albicans generally the most frequently isolated fungal species. It should be noted, however, that in some geographical areas and in certain patient groups, other Candida species are more commonly isolated (reviewed in MacCallum, 2010). This frequent isolation of C. albicans is partly due to the fact that this species is the most common commensal, but may also be a reflection of the greater virulence of this species (Arendrup et al., 2002). In general, isolates obtained from blood samples are identical, or highly similar, to those obtained from commensal sites of the same individuals, suggesting endogenous origins of infection (Bougnoux et al., 2006; Odds et al., 2006; Miranda et al., 2009).

One of the major problems with clinical systemic Candida infection is the difficulty in the diagnosis of infection. Bloodstream Candida infections tend to present clinically with nonspecific symptoms, similar to those seen with systemic bacterial infections. This can lead to delays in the initiation of effective antifungal therapy, as antifungals may not be administered until the patient fails to respond to antibacterials. These delays contribute to the high mortality rates (>40%) associated with Candida bloodstream infection (Morrell et al., 2005), which can be further compounded by intrinsic or acquired antifungal drug resistance of Candida species (Sanglard & Odds, 2002; Ostrosky-Zeichner et al., 2003).

Because of the problems in the diagnosis of human infection, models of systemic Candida infection are essential for our understanding of disease initiation and progression, and also to allow the development and evaluation of novel, more effective, diagnostics and therapies. In recent years, minihosts (e.g. Drosophila melanogaster, Caenorhabditis elegans and Galleria mellonella larvae; reviewed in Chamilos et al., 2007) have been used to study aspects of Candida disseminated infection; however, it is only in mammalian hosts that fungal disease can be fully studied. Although larger mammals, such as piglets, rabbits, guinea-pigs and rats, can be used to investigate candidiasis, the majority of studies have been carried out in mice. This is mainly due to economic factors, ease of handling, the availability of knockout mouse strains and other reagents for analyses of host responses and the availability of well-characterized, reproducible infection models. This review discusses murine models of systemic Candida infection, their contribution to our understanding of these infections and their use to evaluate diagnostics and therapies.

Mouse models of systemic Candida infection

  1. Top of page
  2. Abstract
  3. Introduction
  4. Mouse models of systemic Candida infection
  5. Candida virulence and behaviour in vivo
  6. Host responses during infection and disease
  7. The role of mouse infection models in the development of new diagnostics and therapies
  8. Outlook
  9. Acknowledgements
  10. References

Murine models of disseminated Candida infection fall into two main categories: the intravenous infection model and the gastrointestinal colonization and dissemination model. This review focuses mainly on C. albicans, as the majority of published studies have focused on this pathogen; however, an increasing number of studies are using these same mouse models to investigate systemic infection caused by other Candida species.

The murine intravenous model of disseminated C. albicans infection is a well-characterized and reproducible infection model (Louria et al., 1963; Papadimitriou & Ashman, 1986; MacCallum & Odds, 2005). Fungal cells are injected intravenously via the lateral tail vein, spreading rapidly throughout the body. In this model, infection is controlled in most organs, but progresses in the kidneys and, at higher inoculum levels, in the brain (MacCallum & Odds, 2005), with sepsis the eventual cause of death (Spellberg et al., 2005). This model mimics infection development after fungal cells have entered the bloodstream from the gut, and can include immunosuppression regimens to model those severely immunosuppressed patients at particular risk of disseminated infection.

Gastrointestinal colonization and dissemination models require colonization of the mouse gastrointestinal tract with C. albicans, either in infant mice or after antifungal/antibacterial treatment of adults, which is followed by dissemination. In the infant mouse model, C. albicans cells rapidly disseminate from the gut to the liver and, less frequently, to the kidneys and spleen (Pope et al., 1979; Field et al., 1981). Where dissemination does not occur and mice survive, there is persistent colonization of the gastrointestinal tract. In the adult mouse colonization and dissemination model, adult mice are infected with C. albicans in the chow, drinking water or by gavage. Fungal colonization is highest in the stomach, caecum and small intestine (Sandovsky-Losica et al., 1992; Mellado et al., 2000; Clemons et al., 2006). Colonization can be maintained by continuous antibiotic therapy and can be monitored noninvasively by faecal fungal counts. Subsequent treatment with immunosuppressive and/or mucosa-damaging agents leads to dissemination of fungal cells to the liver, kidneys and spleen (Sandovsky-Losica et al., 1992; Clemons et al., 2006; Koh et al., 2008). This model has been used to monitor dissemination of both C. albicans and C. tropicalis; however, C. parapsilosis was found to be unable to disseminate from the gut (Mellado et al., 2000). This model is probably a more accurate reflection of how infection can initiate in some human patients, with the dissemination of commensal organisms occurring when defects in the immune system and mucosal barriers are no longer effective in preventing fungal gut translocation (Koh et al., 2008). It is interesting to note that, similar to the at-risk patient population, there remains a considerable variation in the number of animals that develop disseminated infection, requiring increased numbers of animals to obtain statistically significant results (Sandovsky-Losica et al., 1992; Clemons et al., 2006; Koh et al., 2008).

One important point to bear in mind, when modelling Candida infection in mice, is that C. albicans and other human pathogenic Candida species are not natural commensals or pathogens of mice (Savage & Dubos, 1967). There are also immune differences between mice and humans (Rehli, 2002; Jiang et al., 2010; Gibbons & Spencer, 2011). Because of these points, researchers should take great care in extrapolating results from mouse models to the human situation.

Candida virulence and behaviour in vivo

  1. Top of page
  2. Abstract
  3. Introduction
  4. Mouse models of systemic Candida infection
  5. Candida virulence and behaviour in vivo
  6. Host responses during infection and disease
  7. The role of mouse infection models in the development of new diagnostics and therapies
  8. Outlook
  9. Acknowledgements
  10. References

Mouse models have been invaluable in increasing our understanding of the behaviour of Candida species, particularly C. albicans, in the host. Assaying the virulence of clinical isolates in these models has demonstrated considerable variation, both between species and within species, which was not linked to the clinical source of the isolate (Wingard et al., 1982; Mellado et al., 2000; Brieland et al., 2001; Arendrup et al., 2002; Asmundsdottir et al., 2009; MacCallum et al., 2009b). Virulence differences have also been evident when the same strain, or isolate, has been compared in the two systemic infection mouse models (Wingard et al., 1982; de Repentigny et al., 1992; Bendel et al., 2003), suggesting that different virulence factors are required in the different models.

One of the major uses of mouse models of disseminated infection has been in the evaluation of specific gene products in the virulence of Candida, particularly C. albicans. Although both mouse models of disseminated infection have been used to evaluate the contribution of specific gene products to C. albicans virulence, the majority of studies have been carried out by intravenous infection of mice. From the large number of C. albicans mutants tested in the intravenous infection model, 217 genes have been identified as contributing to C. albicans virulence (Table 1) (Candida Genome Database; Skrzypek et al., 2010). By contrast, only a limited number of studies have used the gastrointestinal model to assay C. albicans virulence, but six genes have been identified as contributing to virulence in this model (Table 2) (Candida Genome Database; Skrzypek et al., 2010). GO term analyses of the virulence-associated gene lists show filamentous growth to be important in C. albicans virulence in both models (Tables 1 and 2). In addition, for the intravenous infection model, the cell wall and responses to chemicals, stresses and drugs are also important for full virulence (Table 1).

Table 1.   Genes contributing to Candida albicans virulence in the intravenous mouse systemic infection model
GO termGenes/totalFrequency (%)Gene(s)
  1. Virulence phenotypes of Candida albicans mutants were obtained by searching the Candida Genome Database (http://www.candidagenome.org) (Skrzypek et al., 2010).

Pathogenesis158/21772.8MKC1 NAG6 SAP3 SIT4 NAG1 SFL2 DAC1 YVH1 NAG3 IRO1 CHS7 URA3 SET1 CDC24 ADE5,7 FOX2 ECM33 VPS4 NOT4 CAT1 HSP90 SAP1 RIM101 PHR1 AGE3 CEK1 TCC1 NAG4 TPS2 IRS4 WAL1 LIG4 CYR1 VPS28 RIM8 RVS167 BGL2 SRV2 BNI1 IFF4 PTC1 YPT72 HEX1 CNH1 INP51 CSP37 VAM3 GPI7 FAS2 BUD2 PHO100 RFG1 MNT1 VPS21 VPS34 NMT1 GLN3 ERG24 BEM1 PDE2 SPT3 PLD1 ALO1 CHS3 FLO8 CPP1 SWE1 RSR1 CMP1 HEM3 TUP1 UTR2 MIT1 TOP1 RVS161 YHB1 SAP2 DFG16 HET1 ALS1 MTLA1 NDT80 ASC1 CNB1 MDS3 RTT109 BIG1 SLK19 HGT4 SNF7 UME6 RCK2 PMT1 SUN41 MDR1 HOG1 CHK1 RFX2 HWP1 HSX11 RBT1 IFF11 SOD1 CDC42 SSK1 UBI4 ICL1 NOT5 AFT2 MNN2 HSL1 HAP43 TPK2 ACE2 SCH9 SAP7 RAS1 CSH3 NIK1 TTR1 PLB1 MAD2 FTR1 CHS1 CAS5 EFG1 SOD5 ADE2 TEC1 CDC11 CLA4 CDC10 RBT4 CST20 MTLALPHA2 GNA1 PMT6 ERG3 NRG1 LEU2 ESS1 MP65 SLD1 TPS1 BMH1 KEX2 SSD1 LIP8 PMT4 CRK1 HWP2 SSN6 GCS1 INT1 ASH1 CTF1 GOA1 MTS1
Filamentous growth114/21752.5MKC1 SIT4 NAG1 SFL2 DAC1 YVH1 IRO1 URA3 SET1 CDC24 ECM33 VPS4 NOT4 CAT1 HSP90 RIM101 PHR1 AGE3 CEK1 TCC1 KRE9 TPS2 IRS4 WAL1 LIG4 CYR1 VPS28 RIM8 GPR1 RVS167 SRV2 BNI1 INP51 GPI7 BUD2 RFG1 MNT1 DRG1 VPS34 GLN3 ERG24 BEM1 PDE2 SPT3 PLD1 ALO1 CHS3 FLO8 CPP1 RSR1 CMP1 TUP1 UTR2 TOP1 RVS161 DFG16 ALS1 NDT80 SFL1 ASC1 CNB1 MDS3 BIG1 SNF7 UME6 RCK2 PMT1 CHO1 CDC19 HOG1 CHK1 MNS1 HWP1 CRZ1 SOD1 CDC42 SSK1 UBI4 ECM25 NOT5 AFT2 MNN2 HSL1 TPK2 ACE2 SCH9 RAS1 CSH3 NIK1 SKN7 CAS5 EFG1 AAF1 TEC1 CDC11 CLA4 CDC10 CST20 PMT6 ERG3 NRG1 ESS1 MP65 SLD1 TPS1 BMH1 KEX2 PMR1 PMT4 CRK1 HWP2 SSN6 ASH1 GOA1
Response to chemical stimulus80/21736.9MKC1 NAG6 SIT4 HSP70 NAG3 CDC24 UTP15 VPS4 SEN2 CAT1 HSP90 RIM101 PHR1 AGE3 MGM101 CEK1 NAG4 TPS2 SLN1 CYR1 VPS28 TRX1 SRV2 PTC1 ERG2 RPB8 RPF2 VPS34 GLN3 ERG24 BEM1 PDE2 PLD1 ALO1 SWE1 CMP1 NOP14 TUP1 YHB1 NDT80 SFL1 ASC1 CNB1 HGT4 SNF7 RCK2 PMT1 MDR1 HMG1 HOG1 RFX2 CRZ1 SOD1 CDC42 SSK1 HSL1 ACE2 SCH9 RAS1 SKN7 TTR1 MAD2 PKC1 CAS5 ERB1 SOD5 TEC1 CLA4 RBT4 CST20 PMT6 ERG3 NRG1 TIP1 PMT4 UTP5 SSN6 GCS1 HMX1 GOA1
Response to stress52/21724MKC1 SIT4 HSP70 SET1 CAT1 HSP90 RIM101 MGM101 CTA8 TPS2 SLN1 LIG4 CYR1 TRX1 PTC1 CNH1 VPS34 ALO1 CMP1 RVS161 YHB1 NDT80 RTT109 SNF7 RCK2 MDR1 HOG1 RFX2 SOD1 SSK1 UBI4 HAP43 TPK2 SCH9 RAS1 NIK1 SKN7 TTR1 MAD2 FTR1 PKC1 CAS5 EFG1 SOD5 ROM2 CST20 TPS1 BMH1 SSD1 ATC1 GCS1 GOA1
Response to drug49/21722.6MKC1 NAG6 NAG3 UTP15 SEN2 HSP90 RIM101 PHR1 AGE3 MGM101 CEK1 NAG4 CYR1 VPS28 SRV2 ERG2 RPB8 RPF2 VPS34 GLN3 ERG24 PDE2 SWE1 CMP1 NOP14 TUP1 NDT80 SFL1 CNB1 SNF7 PMT1 MDR1 HMG1 CRZ1 HSL1 ACE2 MAD2 PKC1 CAS5 ERB1 CLA4 RBT4 PMT6 ERG3 NRG1 TIP1 PMT4 UTP5 SSN6
Cellular cell wall organization41/21718.9MKC1 SIT4 YVH1 ECM33 PHR1 CEK1 KRE9 IRS4 VPS28 RVS167 BGL2 SAP10 INP51 MNT1 PDE2 CHS3 CMP1 UTR2 RVS161 CNB1 SLK19 SNF7 RCK2 PMT1 SUN41 HOG1 HWP1 XOG1 RBT1 SOD1 SSK1 ECM25 ACE2 PKC1 CAS5 SAP9 CDC10 CST20 PMR1 SSD1 PMT4
Interspecies interaction41/21718.9SAP3 HSP70 URA3 SET1 ECM33 CAT1 SAP1 RIM101 PHR1 IRS4 CYR1 RIM8 BGL2 SAP10 MNT1 PDE2 TUP1 UTR2 YHB1 SAP2 ALS1 BIG1 SUN41 CDC19 RFX2 HWP1 SSK1 HSL1 TPK2 RAS1 PLB1 EFG1 SOD5 AAF1 TEC1 SAP9 CDC10 MP65 SSD1 INT1 FBA1
Host interaction38/21717.5SAP3 HSP70 URA3 SET1 ECM33 CAT1 SAP1 RIM101 PHR1 IRS4 CYR1 RIM8 BGL2 SAP10 PDE2 TUP1 UTR2 YHB1 SAP2 ALS1 BIG1 SUN41 CDC19 RFX2 HWP1 SSK1 TPK2 RAS1 PLB1 EFG1 SOD5 AAF1 TEC1 SAP9 CDC10 MP65 SSD1 FBA1
Protein modification34/21715.7MKC1 NGG1 SIT4 YVH1 SET1 NOT4 HST3 CEK1 OCH1 TRX1 PTC1 GPI7 MNT1 VPS34 NMT1 CWH41 SPT3 RTT109 RCK2 PMT1 HOG1 MNS1 UBI4 NOT5 MNN2 HSL1 TPK2 SCH9 PKC1 CST20 PMT6 PMR1 PMT4 CRK1
Organelle organization33/21715.2MKC1 NGG1 NAG6 SIT4 YVH1 SET1 VPS4 HST3 HSP90 AGE3 MGM101 WAL1 TRX1 BNI1 PTC1 YPT72 VAM3 BUD2 VPS21 RPF2 VPS34 SPT3 TUP1 TOP1 RVS161 RTT109 SNF7 MAD2 PKC1 CDC11 CDC10 CST20 TIP1
Signal transduction33/21715.2MKC1 SIT4 YVH1 CDC24 HSP90 RIM101 CEK1 SLN1 CYR1 GPR1 SRV2 PTC1 BUD2 PDE2 CPP1 RSR1 ASC1 MDS3 HGT4 SNF7 RCK2 HOG1 CHK1 CRZ1 CDC42 SSK1 TPK2 RAS1 NIK1 SKN7 PKC1 CST20 BMH1
Carbohydrate metabolism31/21714.3NAG1 DAC1 CHS7 FOX2 OCH1 KRE9 TPS2 MNT1 CWH41 FBP1 CHS3 UTR2 BIG1 HGT4 PMT1 CDC19 MNS1 XOG1 ICL1 MNN2 ROT2 CHS1 GNA1 PMT6 MP65 TPS1 BMH1 PMR1 PMT4 ATC1 FBA1
Transport30/21713.8NAG6 HSP70 NAG3 CHS7 VPS4 AGE3 NAG4 WAL1 VPS28 RVS167 TRX1 YPT72 CNH1 VAM3 VPS21 VPS34 PLD1 RVS161 HET1 ALR1 HGT4 SNF7 MDR1 MNN2 CSH3 FTR1 CLA4 CST20 TIP1 PMR1
Lipid metabolism22/21710.1FOX2 VPS4 HST3 DPP3 INP51 GPI7 FAS2 ERG2 VPS34 ERG24 PLD1 ERG4 MIT1 CHO1 HMG1 HSX11 PLB5 ERG3 SLD1 LIP8 CTF1 MTS1
RNA metabolism18/2178.3MKC1 DBP8 SIT4 UTP15 SEN2 HBR3 PTC1 RPB8 RPF2 NAN1 SPT3 NOP14 TOP1 NOT5 ERB1 ESS1 UTP4 UTP5
Cell development17/2177.8YVH1 SET1 RIM101 PLD1 CHS3 MDS3 HOG1 SCH9 RAS1 EFG1 CDC11 CLA4 CDC10 CST20 NRG1 BMH1 GOA1
Cell cycle17/2177.8SIT4 YVH1 AGE3 CEK1 RIM8 BNI1 BUD2 SWE1 RSR1 TOP1 HSL1 ACE2 MAD2 CHS1 CST20 BMH1 INT1
Vesicle-mediated transport16/2177.4CHS7 VPS4 AGE3 WAL1 RVS167 TRX1 YPT72 VAM3 VPS21 VPS34 PLD1 RVS161 SNF7 CSH3 TIP1 PMR1
Cellular membrane organization15/2176.9NAG6 VPS4 AGE3 WAL1 RVS167 TRX1 YPT72 VAM3 VPS21 VPS34 PDE2 RVS161 SNF7 SLD1 TIP1
Biofilm formation14/2176.5MKC1 VAM3 ALS1 MDS3 PMT1 SUN41 MDR1 CHK1 HWP1 ACE2 EFG1 TEC1 PMT6 PMT4
Cellular homeostasis14/2176.5IRO1 ADE5,7 CNH1 VAM3 CMP1 DFG16 ASC1 CNB1 HOG1 SOD1 HAP43 TTR1 FTR1 HMX1
Cell adhesion13/2176IFF4 MNT1 TUP1 ALS1 ASC1 HWP1 NOT5 EFG1 AAF1 TEC1 DFI1 MP65 INT1
Cytokinesis12/2175.5MKC1 BNI1 BUD2 BEM1 RSR1 SUN41 CDC42 CHS1 CLA4 CDC10 CST20 INT1
Conjugation12/2175.5CDC24 CEK1 PTC1 BEM1 PLD1 CMP1 RVS161 CNB1 CDC42 CST20 MP65 KEX2
Ribosome biogenesis11/2175.1DBP8 YVH1 UTP15 WAL1 HBR3 RPF2 NAN1 NOP14 ERB1 UTP4 UTP5
Table 2.   Genes contributing to Candida albicans virulence in the gastrointestinal colonization and dissemination mouse infection model
GO termFrequencyGene(s)
Genes/total(%)
  1. Virulence phenotypes of Candida albicans mutants were obtained by searching the Candida Genome Database (http://www.candidagenome.org) (Skrzypek et al., 2010).

Pathogenesis5/683.3INT1, PLB1, PLD1, SFL2, TUP1
Filamentous growth4/666.7EFH1, PLD1, SFL2, TUP1
Response to chemical stimulus2/633.3PLD1, TUP1
Response to drug1/616.7TUP1
Interspecies interaction between organisms3/650.0INT1, PLB1, TUP1
Interaction with host2/633.3PLB1, TUP1
Transport1/616.7PLD1
Cell development1/616.7PLD1
Cell cycle1/616.7INT1
Vesicle-mediated transport1/616.7PLD1
Cell adhesion2/633.3INT1, TUP1
Cytokinesis1/616.7INT1
Conjugation1/616.7PLD1

In addition to these gross virulence studies, mouse models have allowed the behaviour of C. albicans within the host to be examined. Reporter systems, such as green fluorescent protein constructs, have allowed C. albicans gene expression in individual cells to be measured in infected organs (Barelle et al., 2004). Considerable heterogeneity was seen between C. albicans cells in infected kidneys. The majority of fungal cells were seen to be assimilating carbon via the glycolytic pathway, but approximately one-third of C. albicans cells were clearly using gluconeogenesis (Barelle et al., 2006); similarly, only a minority (<5%) of fungal cells in infected kidneys were found to be actively responding to oxidative stress during growth in vivo (Enjalbert et al., 2007).

In addition to the above-mentioned reporter systems, gene expression of C. albicans cells in infected organs can be directly measured by quantitative real-time PCR (qRT-PCR). Sufficient fungal RNA can be extracted from infected organs to allow analysis of expression of selected subsets of fungal genes (reviewed in Brown et al., 2007). These studies have focused mainly on virulence factors, such as secreted enzymes and adhesins, and have shown that these genes are expressed in specific niches during infection. The addition of an RNA amplification step, following extraction of RNA from fungal cells from infected kidneys, allows fungal gene expression changes during infection to be analysed by transcript profiling. In comparison with C. albicans cells grown in vitro, fungal cells from infected mouse kidneys demonstrated altered, mostly downregulated, expression of approximately one-fifth of the genome (Andes et al., 2005). These gene expression changes reflected a switch to a filamentous growth form and growth in a glucose-poor environment.

Emergence of fungal drug resistance in an antifungal-treated host has also been studied in mouse systemic infection models (Andes et al., 2006). In the mouse, ineffective antifungal dosing regimens allowed the emergence of resistant isolates, where effective antifungal doses prevented this. In addition, mouse infection models have confirmed that C. albicans strains with specific drug resistance mutations are more resistant to antifungal therapy, with the greatest resistance seen in strains with multiple genomic mutations (Park et al., 2005; MacCallum et al., 2010).

Host responses during infection and disease

  1. Top of page
  2. Abstract
  3. Introduction
  4. Mouse models of systemic Candida infection
  5. Candida virulence and behaviour in vivo
  6. Host responses during infection and disease
  7. The role of mouse infection models in the development of new diagnostics and therapies
  8. Outlook
  9. Acknowledgements
  10. References

Mouse models have been instrumental in understanding host responses during the initiation and progression of systemic Candida infection, with the advantage of allowing manipulation of the host, either through use of neutralizing antibodies, immunosuppressive treatment or by creating knockout mice. Such host manipulations allow mimicking of susceptible hosts, for example patients depleted in B cells, T cells, macrophages or neutrophils or with specific gene mutations, and allows the effects of these manipulations on host responses or susceptibility to infection to be analysed.

Modelling disseminated C. albicans infection by intravenous injection in normal mice demonstrated that fungal growth was controlled in the liver and spleen, while fungal burdens increased in the kidneys (MacCallum & Odds, 2005; Lionakis et al., 2010). In the kidneys, fungal burden increases were accompanied by increasing immune infiltrates (MacCallum et al., 2009a; Castillo et al., 2011). This did not occur in other organs. Analyses of cytokine and chemokine levels in infected organs elucidated obvious organ-specific responses, with high cytokine and chemokine levels in infected kidneys, but reduced responses in the spleen (Spellberg et al., 2003; MacCallum et al., 2009a). These differences were also reflected at the transcriptional level, with differential expression of cytokine genes in the kidneys and spleen (Brieland et al., 2001). Again, transcriptional changes were linked with progressive C. albicans infection, with little change in renal cytokine gene expression after infection with an attenuated isolate (MacCallum, 2009).

In a recent study, Lionakis et al. (2011) utilized the mouse intravenous model of systemic candidiasis to characterize immune cell populations in infected organs during disease progression. Neutrophils accumulated in all fungus-infected organs, but a delay in their appearance in the kidneys rendered these organs unprotected during the initial 24 h of infection (Lionakis et al., 2011). Further increases in neutrophils occurred in the kidneys as disease progressed, but in other organs, where fungal growth was controlled, neutrophil accumulation was controlled and macrophages became evident (Lionakis et al., 2011). The results of this study are a major step towards explaining the kidney specificity of progressive C. albicans infection in the mouse model.

Infection of knockout mouse strains has also contributed to our knowledge of host susceptibility to Candida infection. Complement was shown to play an essential role in C. albicans and C. glabrata systemic infections through infection of C3-deficient mice (Tsoni et al., 2009). In addition, pattern recognition receptor knockout mice were critical in demonstrating the importance of dectin-1, TLR2 and TLR4 in the recognition and control of systemic fungal infection (reviewed in Netea & Marodi, 2010). In another example, both tumour necrosis factor-α and interleukin-6 (IL-6) were shown to be critical for normal host responses during disseminated infection, using both the intravenous and the gastrointestinal infection models (reviewed in Mencacci et al., 1998). In contrast, some host genes are only required for normal host responses in one model, or the other, for example IL-12 is important for the gastrointestinal model, but dispensable for the intravenous model (Ashman et al., 2011), and the opposite is true for B cell knockout mice (Wagner et al., 1996).

Mouse strain background can be an important consideration when working with knockout mouse strains as different strains vary in their susceptibility to systemic Candida infection (Marquis et al., 1988; Ashman et al., 1993, 1996). These differences in the knockout mouse strain background, in combination with different fungal isolates, can lead to conflicting results for the roles of host genes in susceptibility to C. albicans infection, such as was found for TLR2 and dectin-1 (reviewed in Netea & Marodi, 2010).

The role of mouse infection models in the development of new diagnostics and therapies

  1. Top of page
  2. Abstract
  3. Introduction
  4. Mouse models of systemic Candida infection
  5. Candida virulence and behaviour in vivo
  6. Host responses during infection and disease
  7. The role of mouse infection models in the development of new diagnostics and therapies
  8. Outlook
  9. Acknowledgements
  10. References

Despite increased understanding of how C. albicans infection progresses, the diagnosis of these infections remains difficult. In addition to other clinical tests, there remains a reliance on positive blood culture to confirm the diagnosis of systemic candidiasis; however, some patient blood samples remain culture negative. Therefore, better diagnostics are required for the detection of systemic Candida infection. Both mouse models of systemic C. albicans infection have been used to evaluate novel diagnostics before a clinical trial (Nichterlein et al., 2003; Uno et al., 2007). Evaluation of new diagnostics in a host where systemic infection can be reliably induced demonstrated that serological tests for Candida mannan and β-glucan were more sensitive than nested PCR and blood culture for the prediction of systemic infection in the mouse (Uno et al., 2007). These tests have been further developed for clinical use, for example Platelia®Candida mannan antigen sandwich enzyme-linked immunosorbent assay (Bio-rad Laboratories) and Fungitell® assay (Associates of Cape Cod Inc.).

Mouse models of systemic C. albicans infection have also played a critical role in the early stages of antifungal drug development (Herrera & Guentzel, 1982; Andes, 2005), allowing in vivo antifungal efficacy to be determined. It is important, however, to consider that the results obtained for antifungal agents may differ in mice and humans. An example of this can be seen when triazole therapy is considered. In mice, triazoles are metabolized more quickly than in humans, due to differences in liver cytochrome P450 enzyme activity (Sugar & Liu, 2000). Inhibition of this activity in mice increased azole levels and improved infection outcome (Sugar & Liu, 2000; MacCallum & Odds, 2002b), although this was mouse strain dependent (MacCallum & Odds, 2002a).

Potential antifungal antibodies and vaccines have also been evaluated in mouse models of systemic C. albicans infection (Matthews et al., 2003; Spellberg et al., 2006; Cabezas et al., 2010). Mycograb, a human recombinant antibody against fungal HSP90, possessed antifungal activity in the mouse model and showed synergy when used in combination with amphotericin B (Matthews et al., 2003). Mycograb has since become the first anti-Candida antibody to reach the clinic (Cabezas et al., 2010). The search for vaccines to prevent life-threatening systemic Candida infection in at-risk patients has also utilized the mouse infection model to evaluate whether vaccines are able to protect hosts from subsequent infection. In one example, a vaccine based on the administration of the N-terminus of C. albicans Als1p or Als3p was found to protect immunocompromised and immunocompetent mice from systemic candidiasis (Spellberg et al., 2006). This vaccine, NDV-3, is now being taken forward by NovaDigm and will enter Phase I clinical trials in 2011.

Outlook

  1. Top of page
  2. Abstract
  3. Introduction
  4. Mouse models of systemic Candida infection
  5. Candida virulence and behaviour in vivo
  6. Host responses during infection and disease
  7. The role of mouse infection models in the development of new diagnostics and therapies
  8. Outlook
  9. Acknowledgements
  10. References

Despite limitations due to differences between mice and humans, mouse models of systemic Candida infection have contributed considerably to our current appreciation of host–fungus interactions during systemic infection and have been essential tools in the development of new antifungal therapies and diagnostics. Alternative infection models will continue to play a role in increasing our understanding of systemic Candida infection, with minihosts important in large-scale screening studies and larger mammalian hosts required for modelling certain infections, for example catheter-associated infection. However, mouse models still have more to contribute. Advances in investigative technologies will allow the elucidation of finer details during infection development. These advances include laser capture microdissection, to allow specific areas within infected tissues to be analysed, imaging techniques, which are close to allowing the development of systemic infections to be monitored in live mice, and advances in gene expression (RNAseq) and proteomic analyses, which will produce greater details on host and fungus gene and protein expression during infection. Regardless of future technological changes, mouse models remain an important tool in systemic candidiasis research; these models are essential for the investigation and evaluation of the complex interactions occurring between mammalian host and fungus.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Mouse models of systemic Candida infection
  5. Candida virulence and behaviour in vivo
  6. Host responses during infection and disease
  7. The role of mouse infection models in the development of new diagnostics and therapies
  8. Outlook
  9. Acknowledgements
  10. References

The authors would like to apologize to those investigators whose work was not included due to space constraints. E.K.S. is supported by an NC3Rs PhD studentship and D.M.M. is supported by the Wellcome Trust.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Mouse models of systemic Candida infection
  5. Candida virulence and behaviour in vivo
  6. Host responses during infection and disease
  7. The role of mouse infection models in the development of new diagnostics and therapies
  8. Outlook
  9. Acknowledgements
  10. References
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