The purpose of this article was to introduce a method for determination of lung fungal burden in mice with IA by utilizing GMS-stained lung histological sections for image analysis and quantification. In this study, treatment with the β-glucan-synthesis-targeting antifungal drug caspofungin14 did not improve survival or fungal burden in neutropenic wild-type mice with IA8. However, in the absence of eosinophils or γδ T cells, survival and fungal burden improved. The results of our study also demonstrated that comparable results may be obtained by GMS fungal burden in comparison to the widely-used fungal DNA qPCR method6.
There are several benefits to utilizing GMS fungal burden quantification. First, the process may utilize existing histological samples, thus potentially reducing the number of experiments required to determine significant differences. Second, in this study, less animals were required for GMS fungal burden quantification to achieve significant differences in comparison to qPCR of fungal DNA (Figure 6, Figure 7). Third, comparison of fungal burden in different isolates by qPCR may be affected by isolate-dependent differences in ribosomal DNA copy number15. In contrast, GMS quantification is not affected by copy number, as fungal burden is determined by relative levels of lung fungal growth. Thus, the use of GMS quantification for fungal burden reduces the use of vertebrate animals and does not require pre-determination of rDNA copy number. Finally, in addition to modifying fungal morphology, caspofungin therapy increases fungal fragmentation, and thus may artificially increase fungal burden when measured by isolation of colony forming units from lung homogenates12,16,17. Thus, GMS quantification of fungal burden avoids several limitations inherent with other commonly used methods.
However, the limitations of GMS quantification and/or this study are important to note. First, the authors assumed a comparable distribution of hyphal growth throughout the lungs of each experimental group, and thus used quantification from 4 representative 10x objective fields as a representative measurement for the fungal burden in the entire lung (Figure 6B). It is possible that in some instances the relative distribution, size, and density of hyphal foci would sufficiently differ so that the fungal burden would appear different with this method and equivalent by the qPCR method. However, our additional results with whole lung section quantification using the 4X objective fields showed similar, albeit less statistically significant, differences between groups (Figure 6C). The standard error of this quantification was increased with this strategy, likely due to decreased hyphal resolution with the 4X objective and increased background in suboptimal fields. Therefore, a representative quantification of fewer fields at higher magnification is preferred. Second, only a single, central section was used for each sample. It is possible, based on the fungal isolates or mice strains used, that some studies may result in an uneven distribution of hyphal growth. In those instances, additional sections throughout each paraffin block should be quantified to obtain a more representative burden. Third, in experiments that induce substantial production of mucins (i.e., quantifying airway fungal growth in allergic bronchopulmonary aspergillosis (ABPA)18 or cystic fibrosis (CF)18), GMS reactivity with polysaccharide-rich mucins19 could yield non-specific GMS+ results and thus skew some samples in favor of higher fungal burden. Since only the neutropenic model of IA was used in this study, it is possible that the use of other immune competent or suppressive models could results in less comparable results. Despite these caveats, GMS quantification provides a comparable technique to determine fungal burden, and its continued use in additional studies may further validate the utility of this method as consistent, reliable, and cost-effective.