Dynamic Interplay of Host and Pathogens in an Avian Whole-Blood Model

Spatiotemporal modeling quantifies cellular contributions to uptake of Aspergillus fumigatus in the human lung

The human lung is confronted daily with thousands of microbial invaders reaching the lower respiratory tract. An efficient response by the resident type 1 and type 2 alveolar epithelial cells (AECs) and alveolar macrophages (AMs) cells during the early hours of innate immunity is a prerequisite to maintain a non-inflammatory state, but foremost to rapidly remove harmful substances. One such human-pathogenic invader is the opportunistic fungus Aspergillus fumigatus. If the spherical conidia are not cleared in time, they swell reaching approximately twice of their initial size and germinate to develop hyphae around six hours post-infection. This process of morphological change is crucial as it enables the pathogen to invade the alveolar epithelium and to reach the bloodstream, but also makes it conspicuous for the immune system. During this process, conidia are first in contact with AECs then with migrating AMs, both attempting to internalize and clear the fungus. However, the relative contribution of AMs and AECs to uptake of A. fumigatus remains an open question, especially the capabilities of the barely investigated type 1 AECs. In this study, we present a bottom-up modeling approach to incorporate experimental data on the dynamic increase of the conidial diameter and A. fumigatus uptake by AECs and AMs in a hybrid agent-based model (hABM) for the to-scale simulation of virtual infection scenarios in the human alveolus. By screening a wide range of parameters, we found that type 1 AECs, which cover approximately 95% of the alveolar surface, are likely to have a greater impact on uptake than type 2 AECs. Moreover, the majority of infection scenarios across the regime of tested parameters were cleared through uptake by AMs, whereas the contribution to conidial uptake by AECs was observed to be limited, indicating that their crucial support might mostly consist in mediating chemokine secretion for AM recruitment. Regardless, as the first host cell being confronted with A. fumigatus conidia, our results evidence the large potential impact of type 1 AECs antimicrobial activities, underlining the requirement of increasing experimental efforts on this alveolar constituent.

Surrogate infection model predicts optimal alveolar macrophage number for clearance of Aspergillus fumigatus infections

The immune system has to fight off hundreds of microbial invaders every day, such as the human-pathogenic fungus Aspergillus fumigatus. The fungal conidia can reach the lower respiratory tract, swell and form hyphae within six hours causing life-threatening invasive aspergillosis. Invading pathogens are continuously recognized and eliminated by alveolar macrophages (AM). Their number plays an essential role, but remains controversial with measurements varying by a factor greater than ten for the human lung. We here investigate the impact of the AM number on the clearance of A. fumigatus conidia in humans and mice using analytical and numerical modeling approaches. A three-dimensional to-scale hybrid agent-based model (hABM) of the human and murine alveolus allowed us to simulate millions of virtual infection scenarios, and to gain quantitative insights into the infection dynamics for varying AM numbers and infection doses. Since hABM simulations are computationally expensive, we derived and trained an analytical surrogate infection model on the large dataset of numerical simulations. This enables reducing the number of hABM simulations while still providing (i) accurate and immediate predictions on infection progression, (ii) quantitative hypotheses on the infection dynamics under healthy and immunocompromised conditions, and (iii) optimal AM numbers for combating A. fumigatus infections in humans and mice.

Differential gene expression reveals host factors for viral shedding variation in mallards (Anas platyrhynchos) infected with low-pathogenic avian influenza virus

Intraspecific variation in pathogen shedding impacts disease transmission dynamics; therefore, understanding the host factors associated with individual variation in pathogen shedding is key to controlling and preventing outbreaks. In this study, ileum and bursa of Fabricius tissues of wild-bred mallards (Anas platyrhynchos) infected with low-pathogenic avian influenza (LPAIV) were evaluated at various post-infection time points to determine genetic host factors associated with intraspecific variation in viral shedding. By analysing transcriptome sequencing data (RNA-seq), we found that LPAIV-infected wild-bred mallards do not exhibit differential gene expression compared to uninfected birds, but that gene expression was associated with cloacal viral shedding quantity early in the infection. In both tissues, immune gene expression was higher in high/moderate shedding birds compared to low shedding birds, and significant positive relationships with viral shedding were observed. In the ileum, expression for host genes involved in viral cell entry was lower in low shedders compared to moderate shedders at 1 day post-infection (DPI), and expression for host genes promoting viral replication was higher in high shedders compared to low shedders at 2 DPI. Our findings indicate that viral shedding is a key factor for gene expression differences in LPAIV-infected wild-bred mallards, and the genes identified in this study could be important for understanding the molecular mechanisms driving intraspecific variation in pathogen shedding.

Interaction of Salmonella Gallinarum and Salmonella Enteritidis with peripheral leucocytes of hens with different laying performance

Salmonella enterica ssp. enterica serovars Enteritidis (SE) and Gallinarum (SG) cause different diseases in chickens. However, both are able to reach the blood stream where heterophils and monocytes are potentially able to phagocytose and kill the pathogens. Using an ex vivo chicken whole blood infection model, we compared the complex interactions of the differentially host-adapted SE and SG with immune cells in blood samples of two White Leghorn chicken lines showing different laying performance (WLA: high producer; R11: low producer). In order to examine the dynamic interaction between peripheral blood leucocytes and the Salmonella serovars, we performed flow cytometric analyses and survival assays measuring (i) leucocyte numbers, (ii) pathogen association with immune cells, (iii) Salmonella viability and (iv) immune gene transcription in infected whole blood over a four-hour co-culture period. Inoculation of blood from the two chicken lines with Salmonella led primarily to an interaction of the bacteria with monocytes, followed by heterophils and thrombocytes. We found higher proportions of monocytes associated with SE than with SG. In blood samples of high producing chickens, a decrease in the numbers of both heterophils and Salmonella was observed. The Salmonella challenge induced transcription of interleukin-8 (IL-8) which was more pronounced in SG- than SE-inoculated blood of R11. In conclusion, the stronger interaction of monocytes with SE than SG and the better survivability of Salmonella in blood of low-producer chickens shows that the host-pathogen interaction and the strength of the immune defence depend on both the Salmonella serovar and the chicken line.

Comparative assessment of immune evasion mechanisms in human whole-blood infection assays by a systems biology approach

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.

Significant Differences in Host-Pathogen Interactions Between Murine and Human Whole Blood

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.

Hybrid Agent-Based Modeling of Aspergillus fumigatus Infection to Quantitatively Investigate the Role of Pores of Kohn in Human Alveoli

The healthy state of an organism is constantly threatened by external cues. Due to the daily inhalation of hundreds of particles and pathogens, the immune system needs to constantly accomplish the task of pathogen clearance in order to maintain this healthy state. However, infection dynamics are highly influenced by the peculiar anatomy of the human lung. Lung alveoli that are packed in alveolar sacs are interconnected by so called Pores of Kohn. Mainly due to the lack of in vivo methods, the role of Pores of Kohn in the mammalian lung is still under debate and partly contradicting hypotheses remain to be investigated. Although it was shown by electron microscopy that Pores of Kohn may serve as passageways for immune cells, their impact on the infection dynamics in the lung is still unknown under in vivo conditions. In the present study, we apply a hybrid agent-based infection model to quantitatively compare three different scenarios and discuss the importance of Pores of Kohn during infections of Aspergillus fumigatus. A. fumigatus is an airborne opportunistic fungus with rising incidences causing severe infections in immunocompromised patients that are associated with high mortality rates. Our hybrid agent-based model incorporates immune cell dynamics of alveolar macrophages – the resident phagocytes in the lung – as well as molecular dynamics of diffusing chemokines that attract alveolar macrophages to the site of infection. Consequently, this model allows a quantitative comparison of three different scenarios and to study the importance of Pores of Kohn. This enables us to demonstrate how passaging of alveolar macrophages and chemokine diffusion affect A. fumigatus infection dynamics. We show that Pores of Kohn alter important infection clearance mechanisms, such as the spatial distribution of macrophages and the effect of chemokine signaling. However, despite these differences, a lack of passageways for alveolar macrophages does impede infection clearance only to a minor extend. Furthermore, we quantify the importance of recruited macrophages in comparison to resident macrophages.