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- Aspergillus (2)
- Alternaria (1)
- AurisID (1)
- Candida albicans (1)
- Candida auris (1)
- Fungiplex Candida Auris (1)
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- Purpureocillium (1)
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- antifungal susceptibility (1)
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- commercial kits (1)
- computational biology and bioinformatics (1)
- computational models (1)
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- eye infection (1)
- fungal infection (1)
- galactomannan (1)
- host-pathogen interaction (1)
- immunology (1)
- infection (1)
- inflammation (1)
- innate immunity (1)
- keratitis (1)
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- natamycin (1)
- neutrophils (1)
- pediatric (1)
- protein kinases (1)
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- real-time PCR (1)
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- strain specificity (1)
- whole blood ex vivo model (1)
- zinc cluster transcription factor (1)
Fungal eye infections can lead to loss of vision and blindness. The disease is most prevalent in the tropics, although case numbers in moderate climates are increasing as well. This study aimed to determine the dominating filamentous fungi causing eye infections in Germany and their antifungal susceptibility profiles in order to improve treatment, including cases with unidentified pathogenic fungi. As such, we studied all filamentous fungi isolated from the eye or associated materials that were sent to the NRZMyk between 2014 and 2020. All strains were molecularly identified and antifungal susceptibility testing according to the EUCAST protocol was performed for common species. In total, 242 strains of 66 species were received. Fusarium was the dominating genus, followed by Aspergillus, Purpureocillium, Alternaria, and Scedosporium. The most prevalent species in eye samples were Fusarium petroliphilum, F. keratoplasticum, and F. solani of the Fusarium solani species complex. The spectrum of species comprises less susceptible taxa for amphotericin B, natamycin, and azoles, including voriconazole. Natamycin is effective for most species but not for Aspergillus flavus or Purpureocillium spp. Some strains of F. solani show MICs higher than 16 mg/L. Our data underline the importance of species identification for correct treatment.
Murine infection models are widely used to study systemic candidiasis caused by C. albicans. Whole-blood models can help to elucidate host-pathogens interactions and have been used for several Candida species in human blood. We adapted the human whole-blood model to murine blood. Unlike human blood, murine blood was unable to reduce fungal burden and more substantial filamentation of C. albicans was observed. This coincided with less fungal association with leukocytes, especially neutrophils. The lower neutrophil number in murine blood only partially explains insufficient infection and filamentation control, as spiking with murine neutrophils had only limited effects on fungal killing. Furthermore, increased fungal survival is not mediated by enhanced filamentation, as a filament-deficient mutant was likewise not eliminated. We also observed host-dependent differences for interaction of platelets with C. albicans, showing enhanced platelet aggregation, adhesion and activation in murine blood. For human blood, opsonization was shown to decrease platelet interaction suggesting that complement factors interfere with fungus-to-platelet binding. Our results reveal substantial differences between murine and human whole-blood models infected with C. albicans and thereby demonstrate limitations in the translatability of this ex vivo model between hosts.
Data on biomarker-assisted diagnosis of invasive aspergillosis (IA) in pediatric patients is scarce. Therefore, we conducted a cohort study over two years including 404 serum specimens of 26 pediatric patients after allogeneic hematopoietic stem cell transplantation (alloSCT). Sera were tested prospectively twice weekly for Aspergillus-specific DNA, galactomannan (GM), and retrospectively for (1→3)-β-D-glucan (BDG). Three probable IA and two possible invasive fungal disease (IFD) cases were identified using the European Organization for Research and Treatment of Cancer and the Mycoses Study Group (EORTC/MSGERC) 2019 consensus definitions. Sensitivity and specificity for diagnosis of probable IA and possible IFD was 80% (95% confidential interval (CI): 28–99%) and 55% (95% CI: 32–77%) for BDG, 40% (95% CI: 5–85%) and 100% (95% CI: 83–100%) for GM, and 60% (95% CI: 15–95%) and 95% (95% CI: 75–100%) for Aspergillus-specific real-time PCR. However, sensitivities have to be interpreted with great caution due to the limited number of IA cases. Interestingly, the low specificity of BDG was largely caused by false-positive BDG results that clustered around the date of alloSCT. The following strategies were able to increase BDG specificity: two consecutive positive BDG tests for diagnosis (specificity 80% (95% CI: 56–94%)); using an optimized cutoff value of 306 pg/mL (specificity 90% (95% CI: 68–99%)) and testing BDG only after the acute posttransplant phase. In summary, BDG can help to diagnose IA in pediatric alloSCT recipients. However, due to the poor specificity either an increased cutoff value should be utilized or BDG results should be confirmed by an alternative Aspergillus assay.
The fungal cell wall is essential for the maintenance of cellular integrity and mediates interactions of the cells with the environment. It is a highly flexible organelle whose composition and organization is modulated in response to changing growth conditions. In the pathogenic yeast Candida albicans, a network of signaling pathways regulates the structure of the cell wall, and mutants with defects in these pathways are hypersensitive to cell wall stress. By harnessing a library of genetically activated forms of all C. albicans zinc cluster transcription factors, we found that a hyperactive Czf1 rescued the hypersensitivity to cell wall stress of different protein kinase deletion mutants. The hyperactive Czf1 induced the expression of many genes with cell wall-related functions and caused visible changes in the cell wall structure. C. albicans czf1Δ mutants were hypersensitive to the antifungal drug caspofungin, which inhibits cell wall biosynthesis. The changes in cell wall architecture caused by hyperactivity or absence of Czf1 resulted in an increased recognition of C. albicans by human neutrophils. Our results show that Czf1, which is known as a regulator of filamentous growth and white-opaque switching, controls the expression of cell wall genes and modulates the architecture of the cell wall.
Candida auris is an emerging pathogen with resistance to many commonly used antifungal agents. Infections with C. auris require rapid and reliable detection methods to initiate successful medical treatment and contain hospital outbreaks. Conventional identification methods are prone to errors and can lead to misidentifications. PCR-based assays, in turn, can provide reliable results with low turnaround times. However, only limited data are available on the performance of commercially available assays for C. auris detection. In the present study, the two commercially available PCR assays AurisID (OLM, Newcastle Upon Tyne, UK) and Fungiplex Candida Auris RUO Real-Time PCR (Bruker, Bremen, Germany) were challenged with 29 C. auris isolates from all five clades and eight other Candida species as controls. AurisID reliably detected C. auris with a limit of detection (LoD) of 1 genome copies/reaction. However, false positive results were obtained with high DNA amounts of the closely related species C. haemulonii, C. duobushaemulonii and C. pseudohaemulonii. The Fungiplex Candida Auris RUO Real-Time PCR kit detected C. auris with an LoD of 9 copies/reaction. No false positive results were obtained with this assay. In addition, C. auris could also be detected in human blood samples spiked with pure fungal cultures by both kits. In summary, both kits could detect C. auris-DNA at low DNA concentrations but differed slightly in their limits of detection and specificity.
Computer simulations of mathematical models open up the possibility of assessing hypotheses generated by experiments on pathogen immune evasion in human whole-blood infection assays. We apply an interdisciplinary systems biology approach in which virtual infection models implemented for the dissection of specific immune mechanisms are combined with experimental studies to validate or falsify the respective hypotheses. Focusing on the assessment of mechanisms that enable pathogens to evade the immune response in the early time course of a whole-blood infection, the least-square error (LSE) as a measure for the quantitative agreement between the theoretical and experimental kinetics is combined with the Akaike information criterion (AIC) as a measure for the model quality depending on its complexity. In particular, we compare mathematical models with three different types of pathogen immune evasion as well as all their combinations: (i) spontaneous immune evasion, (ii) evasion mediated by immune cells, and (iii) pre-existence of an immune-evasive pathogen subpopulation. For example, by testing theoretical predictions in subsequent imaging experiments, we demonstrate that the simple hypothesis of having a subpopulation of pre-existing immune-evasive pathogens can be ruled out. Furthermore, in this study we extend our previous whole-blood infection assays for the two fungal pathogens Candida albicans and C. glabrata by the bacterial pathogen Staphylococcus aureus and calibrated the model predictions to the time-resolved experimental data for each pathogen. Our quantitative assessment generally reveals that models with a lower number of parameters are not only scored with better AIC values, but also exhibit lower values for the LSE. Furthermore, we describe in detail model-specific and pathogen-specific patterns in the kinetics of cell populations that may be measured in future experiments to distinguish and pinpoint the underlying immune mechanisms.
Ex vivo immune profiling in patient blood enables quantification of innate immune effector functions
(2021)
The assessment of a patient’s immune function is critical in many clinical situations. In complex clinical immune dysfunction like sepsis, which results from a loss of immune homeostasis due to microbial infection, a plethora of pro- and anti-inflammatory stimuli may occur consecutively or simultaneously. Thus, any immunomodulatory therapy would require in-depth knowledge of an individual patient’s immune status at a given time. Whereas lab-based immune profiling often relies solely on quantification of cell numbers, we used an ex vivo whole-blood infection model in combination with biomathematical modeling to quantify functional parameters of innate immune cells in blood from patients undergoing cardiac surgery. These patients experience a well-characterized inflammatory insult, which results in mitigation of the pathogen-specific response patterns towards Staphylococcus aureus and Candida albicans that are characteristic of healthy people and our patients at baseline. This not only interferes with the elimination of these pathogens from blood, but also selectively augments the escape of C. albicans from phagocytosis. In summary, our model could serve as a valuable functional immune assay for recording and evaluating innate responses to infection.