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Early identification of human pathogens is crucial for the effective treatment of bloodstream infections to prevent sepsis. Since pathogens that are present in small numbers are usually difficult to detect directly, we hypothesize that the behavior of the immune cells that are present in large numbers may provide indirect evidence about the causative pathogen of the infection. We previously applied time-lapse microscopy to observe that neutrophils isolated from human whole-blood samples, which had been infected with the human-pathogenic fungus Candida albicans or C. glabrata, indeed exhibited a characteristic morphodynamic behavior. Tracking the neutrophil movement and shape dynamics over time, combined with machine learning approach, the accuracy for the differentiation between the two Candida species was about 75%. In this study, the focus is on improving the classification accuracy of the Candida species using advanced deep learning methods. We implemented (i) gated recurrent unit (GRU) networks and transformer-based networks for video data, and (ii) convolutional neural networks (CNNs) for individual frames of the time-lapse microscopy data. While the GRU and transformer-based approaches yielded promising results with 96% and 100% accuracy, respectively, the classification based on videos proved to be very time-consuming and required several hours. In contrast, the CNN model for individual microscopy frames yielded results within minutes, and, utilizing a majority-vote technique, achieved 100% accuracy both in identifying the pathogen-free blood samples and in distinguishing between the Candida species. The applied CNN demonstrates the potential for automatically differentiating bloodstream Candida infections with high accuracy and efficiency. We further analysed the results of the CNN using explainable artificial intelligence (XAI) techniques to understand the critical features and patterns, thereby shedding light on potential key morphodynamic characteristics of neutrophils in response to different Candida species. This approach could provide new insights into host-pathogen interactions and may facilitate the development of rapid, automated diagnostic tools for differentiating fungal species in blood samples.

Abstract Quantitative imaging in life sciences has evolved into a powerful approach combining advanced microscopy acquisition and automated analysis of image data. The focus of the present study is on the imaging-based evaluation of the posterior cricoarytenoid muscle (PCA) influenced by long-term functional electrical stimulation (FES), which may assist the inspiration of patients with bilateral vocal fold paresis. To this end, muscle cross-sections of the PCA of sheep were examined by quantitative image analysis. Previous investigations of the muscle fibers and the collagen amount have not revealed signs of atrophy and fibrosis due to FES by a laryngeal pacemaker. It was therefore hypothesized that regardless of the stimulation parameters the fat in the muscle cross-sections would not be significantly altered. We here extending our previous investigations using quantitative imaging of intramuscular fat in cross-sections. In order to perform this analysis both reliably and faster than a qualitative evaluation and time-consuming manual annotation, the selection of the automated method was of crucial importance. To this end, our recently established deep neural network IMFSegNet, which provides more accurate results compared to standard machine learning approaches, was applied to more than 300 H&E stained muscle cross-sections from 22 sheep. It was found that there were no significant differences in the amount of intramuscular fat between the PCA with and without long-term FES, nor were any significant differences found between the low and high duty cycle stimulated groups. This study on a human-like animal model not only confirms the hypothesis that FES with the selected parameters has no negative impact on the PCA, but also demonstrates that objective and automated deep learning-based quantitative imaging is a powerful tool for such a challenging analysis.

Abstract A wide variety of treatments have been developed to improve respiratory function and quality of life in patients with bilateral vocal fold paresis (BVFP). One experimental method is the electrical activation of the posterior cricoarytenoid (PCA) muscle with a laryngeal pacemaker (LP) to open the vocal folds. We used an ovine (sheep) model of unilateral VFP to study the long-term effects of functional electrical stimulation on the PCA muscles. The left recurrent laryngeal nerve was cryo-damaged in all animals and an LP was implanted except for the controls. After a reinnervation phase of six months, animals were pooled into groups that received either no treatment, implantation of an LP only, or implantation of an LP and six months of stimulation with different duty cycles. Automated image analysis of fluorescently stained PCA cross-sections was performed to assess relevant muscle characteristics. We observed a fast-to-slow fibre type shift in response to nerve damage and stimulation, but no complete conversion to a slow-twitch-muscle. Fibre size, proportion of hybrid fibres, and intramuscular collagen content were not substantially altered by the stimulation. These results demonstrate that 30 Hz burst stimulation with duty cycles of 40% and 70% did not induce PCA atrophy or fibrosis. Thus, long-term stimulation with an LP is a promising approach for treating BVFP in humans without compromising muscle conditions.

BackgroundLimited availability and side effects of opioids have led to an increased use of non-opioid analgesia in animal disease models. However, by affecting the immune-inflammatory reactions, analgesia may disrupt the resolution of the host inflammation and modulate the survival in septic animals. This study used a clinically relevant sepsis mouse model of peritoneal contamination and infection (PCI) to investigate the antinociceptive and anti-inflammatory properties of two non-opioid analgesics.MethodsAdult C57BL/6J mice were intraperitoneally injected with a human feces suspension and received either no analgesics (Non-A), Meloxicam, or Metamizole orally. The mice were monitored for pain and illness. Mortality was assessed at 7 days post-PCI. A separate group of mice was sacrificed 24 hours after infection. Blood, peritoneal lavage fluid (PLF), liver, and spleen were harvested for pathogen load quantification via qPCR, macrophage phenotyping, neutrophil infiltration/activation, and systemic/tissue cytokine release by flow cytometry.ResultsMeloxicam but not Metamizole reduced the mortality of septic mice by 31% on day 7 compared to the Non-A group. Both analgesics effectively alleviated pain but did not affect illness severity, body weight, and temperature. Meloxicam quadrupled the bacterial burden in the blood and PLF. In high IL-6 responders, Meloxicam treatment was associated with reduced circulating IL-10 and IL-1β compared to the Non-A septic group. In low IL-6 responders, Meloxicam increased circulating MCP-1 levels and decreased PGE2 levels compared to Non-A septic mice. Notably, Meloxicam reduced spleen neutrophil infiltration by 20% compared to two other sepsis groups.ConclusionMetamizole and Meloxicam effectively relieved pain and increased the animals’ basal activity in the PCI sepsis model. Meloxicam prolonged survival yet triggered maladaptive responses due to its immunosuppressive features that decreased tissue bacterial clearance during sepsis. In contrast, Metamizole constitutes a safe and effective non-opioid alternative for analgesic control in the non-surgical PCI sepsis model.

ABSTRACT Sphingofungins are sphinganine analog mycotoxins acting as inhibitors of serine palmitoyl transferases, enzymes responsible for the first step in the sphingolipid biosynthesis. Eukaryotic cells are highly organized with various structures and organelles to facilitate cellular processes and chemical reactions, including the ones occurring as part of the secondary metabolism. We studied how sphingofungin biosynthesis is compartmentalized in the human-pathogenic fungus Aspergillus fumigatus, and we observed that it takes place in the endoplasmic reticulum (ER), ER-derived vesicles, and the cytosol. This implies that sphingofungin and sphingolipid biosynthesis colocalize to some extent. Automated analysis of confocal microscopy images confirmed the colocalization of the fluorescent proteins. Moreover, we demonstrated that the cluster-associated aminotransferase (SphA) and 3-ketoreductase (SphF) play a bifunctional role, supporting sphingolipid biosynthesis, and thereby antagonizing the toxic effects caused by sphingofungin production.IMPORTANCEA balanced sphingolipid homeostasis is critical for the proper functioning of eukaryotic cells. To this end, sphingolipid inhibitors have therapeutic potential against diseases related to the deregulation of sphingolipid balance. In addition, some of them have significant antifungal activity, suggesting that sphingolipid inhibitors-producing fungi have evolved mechanisms to escape self-poisoning. Here, we propose a novel self-defense mechanism, with cluster-associated genes coding for enzymes that play a dual role, being involved in both sphingofungin and sphingolipid production.

Abstract Diffusion and mobility are essential for cellular functions, as molecules are usually distributed throughout the cell and have to meet to interact and perform their function. This also involves the cytosolic migration of cellular organelles. However, observing such diffusion and interaction dynamics is challenging due to the high spatial and temporal resolution required and the accurate analysis of the diffusional tracks. The latter is especially important when identifying anomalous diffusion events, such as directed motions, which are often rare. Here, we investigate the migration modes of peroxisome organelles in the cytosol of living cells. Peroxisomes predominantly migrate randomly, but occasionally they bind to the cell's microtubular network and perform directed migration, which is difficult to quantify, and so far, accurate analysis of switching between these migration modes is missing. We set out to solve this limitation by experiments and analysis with high statistical accuracy. Specifically, we collect temporal diffusion tracks of thousands of individual peroxisomes in the HEK 293 cell line using two-dimensional spinning disc fluorescence microscopy at a high acquisition rate of 10 frames/s. We use a Hidden Markov Model with two hidden states to (1) automatically identify directed migration segments of the tracks and (2) quantify the migration properties for comparison between states and between different experimental conditions. Comparing different cellular conditions, we show that the knockout of the peroxisomal membrane protein PEX14 leads to a decrease in the directed movement due to a lowered binding probability to the microtubule. However, it does not eradicate binding, highlighting further microtubule-binding mechanisms of peroxisomes than via PEX14. In contrast, structural changes of the microtubular network explain perceived eradication of directed movement by disassembly of microtubules by Nocodazole-treatment.

Abstract 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.

The assessment of muscle condition is of great importance in various research areas. In particular, evaluating the degree of intramuscular fat (IMF) in tissue sections is a challenging task, which today is still mostly performed qualitatively or quantitatively by a highly subjective and error-prone manual analysis. We here realize the mission to make automated IMF analysis possible that (i) minimizes subjectivity, (ii) provides accurate and quantitative results quickly, and (iii) is cost-effective using standard hematoxylin and eosin (H&E) stained tissue sections. To address all these needs in a deep learning approach, we utilized the convolutional encoder-decoder network SegNet to train the specialized network IMFSegNet allowing to accurately quantify the spatial distribution of IMF in histological sections. Our fully automated analysis was validated on 17 H&E-stained muscle sections from individual sheep and compared to various state-of-the-art approaches. Not only does IMFSegNet outperform all other approaches, but this neural network also provides fully automated and highly accurate results utilizing the most cost-effective procedures of sample preparation and imaging. Furthermore, we shed light on the opacity of black-box approaches such as neural networks by applying an explainable artificial intelligence technique to clarify that the success of IMFSegNet actually lies in identifying the hard-to-detect IMF structures. Embedded in our open-source visual programming language JIPipe that does not require programming skills, it can be expected that IMFSegNet advances muscle condition assessment in basic research across multiple areas as well as in research fields focusing on translational clinical applications.

ABSTRACT Streptococcus pneumoniae-induced hemolytic uremic syndrome (Sp-HUS) is a kidney disease characterized by microangiopathic hemolytic anemia, thrombocytopenia, and acute kidney injury. This disease is frequently underdiagnosed and its pathophysiology is poorly understood. In this work, we compared clinical strains, isolated from infant Sp-HUS patients, with a reference pathogenic strain D39, for host cytotoxicity and further explored the role of Sp-derived extracellular vesicles (EVs) in the pathogenesis of an HUS infection. In comparison with the wild-type strain, pneumococcal HUS strains caused significant lysis of human erythrocytes and increased the release of hydrogen peroxide. Isolated Sp-HUS EVs were characterized by performing dynamic light-scattering microscopy and proteomic analysis. Sp-HUS strain released EVs at a constant concentration during growth, yet the size of the EVs varied and several subpopulations emerged at later time points. The cargo of the Sp-HUS EVs included several virulence factors at high abundance, i.e., the ribosomal subunit assembly factor BipA, the pneumococcal surface protein A, the lytic enzyme LytC, several sugar utilization, and fatty acid synthesis proteins. Sp-HUS EVs strongly downregulated the expression of the endothelial surface marker platelet endothelial cell adhesion molecule-1 and were internalized by human endothelial cells. Sp-HUS EVs elicited the release of pro-inflammatory cytokines (interleukin [IL]-1β, IL-6) and chemokines (CCL2, CCL3, CXCL1) by human monocytes. These findings shed new light on the overall function of Sp-EVs, in the scope of infection-mediated HUS, and suggest new avenues of research for exploring the usefulness of Sp-EVs as therapeutic and diagnostic targets. IMPORTANCE Streptococcus pneumoniae-associated hemolytic uremic syndrome (Sp-HUS) is a serious and underdiagnosed deadly complication of invasive pneumococcal disease. Despite the introduction of the pneumococcal vaccine, cases of Sp-HUS continue to emerge, especially in children under the age of 2. While a lot has been studied regarding pneumococcal proteins and their role on Sp-HUS pathophysiology, little is known about the role of extracellular vesicles (EVs). In our work, we isolate and initially characterize EVs from a reference pathogenic strain (D39) and a strain isolated from a 2-year-old patient suffering from Sp-HUS. We demonstrate that despite lacking cytotoxicity toward human cells, Sp-HUS EVs are highly internalized by endothelial cells and can trigger cytokine and chemokine production in monocytes. In addition, this work specifically highlights the distinct morphological characteristics of Sp-HUS EVs and their unique cargo. Overall, this work sheds new light into potentially relevant players contained in EVs that might elucidate about pneumococcal EVs biogenesis or pose as interesting candidates for vaccine design.

Rapid identification of pathogens is required for early diagnosis and treatment of life-threatening bloodstream infections in humans. This requirement is driving the current developments of molecular diagnostic tools identifying pathogens from human whole blood after successful isolation and cultivation. An alternative approach is to determine pathogen-specific signatures from human host immune cells that have been exposed to pathogens. We hypothesise that activated immune cells, such as neutrophils, may exhibit a characteristic behaviour — for instance in terms of their speed, dynamic cell morphology — that allows (i) identifying the type of pathogen indirectly and (ii) providing information on therapeutic efficacy. In this feasibility study, we propose a method for the quantitative assessment of static and morphodynamic features of neutrophils based on label-free time-lapse imaging data. We investigate neutrophil activation phenotypes after confrontation with fungal pathogens and isolation from a human whole-blood assay. In particular, we applied a machine learning supported approach to time-lapse microscopy data from different infection scenarios and were able to distinguish between Candida albicans and C. glabrata infection scenarios with test accuracies well above 75%, and to identify pathogen-free samples with accuracy reaching 100%. These results significantly exceed the test accuracies achieved using state-of-the-art deep neural networks to classify neutrophils by their morphodynamics.

ABSTRACT Alveolar macrophages belong to the first line of defense against inhaled conidia of the human-pathogenic fungus Aspergillus fumigatus. In lung alveoli, they contribute to phagocytosis and elimination of conidia. As a counterdefense, conidia have a gray-green pigment that enables them to survive in phagosomes of macrophages for some time. Previously, we showed that this conidial pigment interferes with the formation of flotillin-dependent lipid raft microdomains in the phagosomal membrane, thereby preventing the formation of functional phagolysosomes. Besides flotillins, stomatin is a major component of lipid rafts and can be targeted to the membrane. However, only limited information on stomatin is available, in particular on its role in defense against pathogens. To determine the function of this integral membrane protein, a stomatin-deficient macrophage line was generated by CRISPR/Cas9 gene editing. Immunofluorescence microscopy and flow cytometry revealed that stomatin contributes to the phagocytosis of conidia and is important for recruitment of the β-glucan receptor dectin-1 to both the cytoplasmic membrane and phagosomal membrane. In stomatin knockout cells, fusion of phagosomes and lysosomes, recruitment of the vATPase to phagosomes, and tumor necrosis factor alpha (TNF-α) levels were reduced when cells were infected with pigmentless conidia. Thus, our data suggest that stomatin is involved in maturation of phagosomes via fostering fusion of phagosomes with lysosomes. IMPORTANCE Stomatin is an integral membrane protein that contributes to the uptake of microbes, e.g., spores of the human-pathogenic fungus Aspergillus fumigatus. By generation of a stomatin-deficient macrophage line by advanced genetic engineering, we found that stomatin is involved in the recruitment of the β-glucan receptor dectin-1 to the phagosomal membrane of macrophages. Furthermore, stomatin is involved in maturation of phagosomes via fostering fusion of phagosomes with lysosomes. The data provide new insights on the important role of stomatin in the immune response against human-pathogenic fungi.

Correlative light and electron microscopy is a powerful tool to study the internal structure of cells. It combines the mutual benefit of correlating light (LM) and electron (EM) microscopy information. The EM images only contain contrast information. Therefore, some of the detailed structures cannot be specified from these images alone, especially when different cell organelle are contacted. However, the classical approach of overlaying LM onto EM images to assign functional to structural information is hampered by the large discrepancy in structural detail visible in the LM images. This paper aims at investigating an optimized approach which we call EM-guided deconvolution. This applies to living cells structures before fixation as well as previously fixed sample. It attempts to automatically assign fluorescence-labeled structures to structural details visible in the EM image to bridge the gaps in both resolution and specificity between the two imaging modes. We tested our approach on simulations, correlative data of multi-color beads and previously published data of biological samples.

Abstract Jaundice, the clinical hallmark of infection‐associated liver dysfunction, reflects altered membrane organization of the canalicular pole of hepatocytes and portends poor outcomes. Mice lacking phosphoinositide 3‐kinase‐γ (PI3Kγ) are protected against membrane disintegration and hepatic excretory dysfunction. However, they exhibit a severe immune defect that hinders neutrophil recruitment to sites of infection. To exploit the therapeutic potential of PI3Kγ inhibition in sepsis, a targeted approach to deliver drugs to hepatic parenchymal cells without compromising other cells, in particular immune cells, seems warranted. Here, we demonstrate that nanocarriers functionalized through DY‐635, a fluorescent polymethine dye, and a ligand of organic anion transporters can selectively deliver therapeutics to hepatic parenchymal cells. Applying this strategy to a murine model of sepsis, we observed the PI3Kγ‐dependent restoration of biliary canalicular architecture, maintained excretory liver function, and improved survival without impairing host defense mechanisms. This strategy carries the potential to expand targeted nanomedicines to disease entities with systemic inflammation and concomitantly impaired barrier functionality.

ABSTRACT The fungus Rhizopus microsporus harbors a bacterial endosymbiont (Mycetohabitans rhizoxinica) for the production of the antimitotic toxin rhizoxin. Although rhizoxin is the causative agent of rice seedling blight, the toxinogenic bacterial-fungal alliance is, not restricted to the plant disease. It has been detected in numerous environmental isolates from geographically distinct sites covering all five continents, thus raising questions regarding the ecological role of rhizoxin beyond rice seedling blight. Here, we show that rhizoxin serves the fungal host in fending off protozoan and metazoan predators. Fluorescence microscopy and coculture experiments with the fungivorous amoeba Protostelium aurantium revealed that ingestion of R. microsporus spores is toxic to P. aurantium. This amoebicidal effect is caused by the dominant bacterial rhizoxin congener rhizoxin S2, which is also lethal toward the model nematode Caenorhabditis elegans. By combining stereomicroscopy, automated image analysis, and quantification of nematode movement, we show that the fungivorous nematode Aphelenchus avenae actively feeds on R. microsporus that is lacking endosymbionts, whereas worms coincubated with symbiotic R. microsporus are significantly less lively. This study uncovers an unexpected ecological role of rhizoxin as shield against micropredators. This finding suggests that predators may function as an evolutionary driving force to maintain toxin-producing endosymbionts in nonpathogenic fungi. IMPORTANCE The soil community is a complex system characterized by predator-prey interactions. Fungi have developed effective strategies to defend themselves against predators. Understanding these strategies is of critical importance for ecology, medicine, and biotechnology. In this study, we shed light on the defense mechanisms of the phytopathogenic Rhizopus-Mycetohabitans symbiosis that has spread worldwide. We report an unexpected role of rhizoxin, a secondary metabolite produced by the bacterium M. rhizoxinica residing within the hyphae of R. microsporus. We show that this bacterial secondary metabolite is utilized by the fungal host to successfully fend off fungivorous protozoan and metazoan predators and thus identified a fundamentally new function of this infamous cytotoxic compound. This endosymbiont-dependent predator defense illustrates an unusual strategy employed by fungi that has broader implications, since it may serve as a model for understanding how animal predation acts as an evolutionary driving force to maintain endosymbionts in nonpathogenic fungi.

Abstract 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.

Although multispectral optoacoustic tomography (MSOT) significantly evolved over the last several years, there is a lack of quantitative methods for analysing this type of image data. Current analytical methods characterise the MSOT signal in manually defined regions of interest outlining selected tissue areas. These methods demand expert knowledge of the sample anatomy, are time consuming, highly subjective and prone to user bias. Here we present our fully automated open-source MSOT cluster analysis toolkit Mcat that was designed to overcome these shortcomings. It employs a deep learning-based approach for initial image segmentation followed by unsupervised machine learning to identify regions of similar signal kinetics. It provides an objective and automated approach to quantify the pharmacokinetics and extract the biodistribution of biomarkers from MSOT data. We exemplify our generally applicable analysis method by quantifying liver function in a preclinical sepsis model whilst highlighting the advantages of our new approach compared to the severe limitations of existing analysis procedures.

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.

The complement system is part of the innate immune system and plays an important role in the host defense against infectious pathogens. One of the main effects is the opsonization of foreign invaders and subsequent uptake by phagocytosis. Due to the continuous default basal level of active complement molecules, a tight regulation is required to protect the body's own cells (self cells) from opsonization and from complement damage. A major complement regulator is Factor H, which is recruited from the fluid phase and attaches to cell surfaces where it effectively controls complement activation. Besides self cells, pathogens also have the ability to bind Factor H; they can thus escape opsonization and phagocytosis causing severe infections. In order to advance our understanding of the opsonization process at a quantitative level, we developed a mathematical model for the dynamics of the complement system—termed DynaCoSys model—that is based on ordinary differential equations for cell surface-bound molecules and on partial differential equations for concentration profiles of the fluid phase molecules in the environment of cells. This hybrid differential equation approach allows to model the complement cascade focusing on the role of active C3b in the fluid phase and on the cell surface as well as on its inactivation on the cell surface. The DynaCoSys model enables us to quantitatively predict the conditions under which Factor H mediated complement evasion occurs. Furthermore, investigating the quantitative impact of model parameters by a sensitivity analysis, we identify the driving processes of complement activation and regulation in both the self and non-self regime. The two regimes are defined by a critical Factor H concentration on the cell surface and we use the model to investigate the differential impact of complement model parameters on this threshold value. The dynamic modeling on the surface of pathogens are further relevant to understand pathophysiological situations where Factor H mutants and defective Factor H binding to target surfaces results in pathophysiology such as renal and retinal disease. In the future, this DynaCoSys model will be extended to also enable evaluating treatment strategies of complement-related diseases.

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.

Phagocytosis is series of steps where the pathogens and the immune cells interact during an invasion. This starts with the adhesion process between the host and pathogen cells, and is followed by the engulfment of the pathogens. Many analytical methods that are applied to characterize phagocytosis based on imaging the host–pathogen confrontation assays rely on the fluorescence labeling of cells. However, the potential effect of the membrane labeling on the quantitative results of the confrontation assays has not been studied in detail. In this study, we determine whether the fluorescence labeling processes themselves influence the results of the phagocytosis measurements. Here, alveolar macrophages, which form one of the most important compartments of the innate immune system, were used as an example of host cells, whereas Aspergillus fumigatus and Lichtheimia corymbifera that cause aspergillosis and mucormycosis, respectively, were studied as examples for pathogens. At first, our study investigated the importance of the sequence of steps of the fixation process when preparing the confrontation assay sample for microscopy studies. Here we showed that applying the fixation agent before the counter-staining causes miscalculations during the determination of the phagocytic measures. Furthermore, we also found that staining the macrophages with various concentrations of DID, as a typical membrane label, in most cases altered the capability of macrophages to phagocytose FITC-stained A. fumigatus and L. corymbifera spores in comparison with unlabeled macrophages. This effect of the DID staining showed a differential character dependent upon the labeling status and the specific type of pathogen. Moreover, labeling the spores of A. fumigatus and L. corymbifera with FITC increased the phagocytic measures during confrontation with unlabeled macrophages when compared to label-free spores. Overall, our study confirms that the staining process itself may significantly manipulate the quantitative outcome of the confrontation assay. As a result of our study, we also developed a user-friendly image analysis tool that analyses confrontation assays both with and without fluorescence labeling of the host cells and of the pathogens. Our image analysis algorithm saves experimental work effort and time, provides more precise results when calculating the phagocytic measures, and delivers a convenient analysis tool for the biologists to monitor host–pathogen interactions as they happen without the artifacts that fluorescence labeling imposes on biological interactions.

ABSTRACT Polymorphonuclear granulocytes (PMNs) are indispensable for controlling life-threatening fungal infections. In addition to various effector mechanisms, PMNs also produce extracellular vesicles (EVs). Their contribution to antifungal defense has remained unexplored. We reveal that the clinically important human-pathogenic fungus Aspergillus fumigatus triggers PMNs to release a distinct set of antifungal EVs (afEVs). Proteome analyses indicated that afEVs are enriched in antimicrobial proteins. The cargo and the release kinetics of EVs are modulated by the fungal strain confronted. Tracking of afEVs indicated that they associated with fungal cells and even entered fungal hyphae, resulting in alterations in the morphology of the fungal cell wall and dose-dependent antifungal effects. To assess as a proof of concept whether the antimicrobial proteins found in afEVs might contribute to growth inhibition of hyphae when present in the fungal cytoplasm, two human proteins enriched in afEVs, cathepsin G and azurocidin, were heterologously expressed in fungal hyphae. This led to reduced fungal growth relative to that of a control strain producing the human retinol binding protein 7. In conclusion, extracellular vesicles produced by neutrophils in response to A. fumigatus infection are able to associate with the fungus, limit growth, and elicit cell damage by delivering antifungal cargo. This finding offers an intriguing, previously overlooked mechanism of antifungal defense against A. fumigatus. IMPORTANCE Invasive fungal infections caused by the mold Aspergillus fumigatus are a growing concern in the clinic due to the increasing use of immunosuppressive therapies and increasing antifungal drug resistance. These infections result in high rates of mortality, as treatment and diagnostic options remain limited. In healthy individuals, neutrophilic granulocytes are critical for elimination of A. fumigatus from the host; however, the exact extracellular mechanism of neutrophil-mediated antifungal activity remains unresolved. Here, we present a mode of antifungal defense employed by human neutrophils against A. fumigatus not previously described. We found that extracellular vesicles produced by neutrophils in response to A. fumigatus infection are able to associate with the fungus, limit growth, and elicit cell damage by delivering antifungal cargo. In the end, antifungal extracellular vesicle biology provides a significant step forward in our understanding of A. fumigatus host pathogenesis and opens up novel diagnostic and therapeutic possibilities.

The fungal pathogen Candida albicans forms polymorphic biofilms where hyphal morphogenesis and metabolic adaptation are tightly coordinated by a complex intertwined network of transcription factors. The sensing and metabolism of amino acids play important roles during various phases of biofilm development – from adhesion to maturation. Stp2 is a transcription factor that activates the expression of amino acid permease genes and is required for environmental alkalinization and hyphal growth in vitro and during macrophage phagocytosis. While it is well established that Stp2 is activated in response to external amino acids, its role in biofilm formation remains unknown. In addition to widely used techniques, we applied newly developed approaches for automated image analysis to quantify Stp2-regulated filamentation and biofilm growth. Our results show that in the stp2Δ deletion mutant adherence to abiotic surfaces and initial germ tube formation were strongly impaired, but formed mature biofilms with cell density and morphological structures comparable to the control strains. Stp2-dependent nutrient adaptation appeared to play an important role in biofilm development: stp2Δ biofilms formed under continuous nutrient flow displayed an overall reduction in biofilm formation, whereas under steady conditions the mutant strain formed biofilms with lower metabolic activity, resulting in increased cell survival and biofilm longevity. A deletion of STP2 led to increased rapamycin susceptibility and transcriptional activation of GCN4, the transcriptional regulator of the general amino acid control pathway, demonstrating a connection of Stp2 to other nutrient-responsive pathways. In summary, the transcription factor Stp2 is important for C. albicans biofilm formation, where it contributes to adherence and induction of morphogenesis, and mediates nutrient adaption and cell longevity in mature biofilms.

Microbial survival in blood is an essential step toward the development of disseminated diseases and blood stream infections. For poultry, however, little is known about the interactions of host cells and pathogens in blood. We established an ex vivo chicken whole-blood infection assay as a tool to analyze interactions between host cells and three model pathogens, Escherichia coli, Staphylococcus aureus, and Candida albicans. Following a systems biology approach, we complemented the experimental measurements with functional and quantitative immune characteristics by virtual infection modeling. All three pathogens were killed in whole blood, but each to a different extent and with different kinetics. Monocytes, and to a lesser extent heterophils, associated with pathogens. Both association with host cells and transcriptional activation of genes encoding immune-associated functions differed depending on both the pathogen and the genetic background of the chickens. Our results provide first insights into quantitative interactions of three model pathogens with different immune cell populations in avian blood, demonstrating a broad spectrum of different characteristics during the immune response that depends on the pathogen and the chicken line.

Modern imaging techniques, such as lightsheet fluorescence microscopy (LSFM), allow the capture of whole organs in three spatial dimensions. The analysis of these big volume image data requires a combination of user-friendly and highly efficient tools. We here present MISA++, an image analysis framework that allows easy integration of custom high-performance C++ tools into third-party applications via standardized components for parallelization, data and parameter handling, command line interface, and communication with third-party applications. We demonstrate its capabilities by implementing a plugin for ImageJ that provides a graphical user interface for any application built with our framework, and a high-performance re-implementation of our Python-based algorithm to segment glomeruli in LSFM images of whole murine kidneys.

Abstract The assessment of bone damage is required to evaluate disease severity and treatment efficacy both in arthritis patients and in experimental arthritis models. Today there is still a lack of in vivo methods that enable the quantification of arthritic processes at an early stage of the disease. We performed longitudinal in vivo imaging with [18F]-fluoride PET/CT before and after experimental arthritis onset for diseased and control DBA/1 mice and assessed arthritis progression by clinical scoring, tracer uptake studies and bone volume as well as surface roughness measurements. Arthritic animals showed significantly increased tracer uptake in the paws compared to non-diseased controls. Automated CT image analysis revealed increased bone surface roughness already in the earliest stage of the disease. Moreover, we observed clear differences between endosteal and periosteal sites of cortical bone regarding surface roughness. This study shows that in vivo PET/CT imaging is a favorable method to study arthritic processes, enabling the quantification of different aspects of the disease like pathological bone turnover and bone alteration. Especially the evaluation of bone surface roughness is sensitive to early pathological changes and can be applied to study the dynamics of bone erosion at different sites of the bones in an automated fashion.

The opportunistic fungal pathogen Aspergillus fumigatus can cause severe infections, particularly in immunocompromised individuals. Upon infection, A. fumigatus faces the powerful and directly acting immune defense of the human host. The mechanisms on how A. fumigatus evades innate immune attack and complement are still poorly understood. Here, we identify A. fumigatus enolase, AfEno1, which was also characterized as fungal allergen, as a surface ligand for human plasma complement regulators. AfEno1 binds factor H, factor-H-like protein 1 (FHL-1), C4b binding protein (C4BP), and plasminogen. Factor H attaches to AfEno1 via two regions, via short conserved repeats (SCRs) 6–7 and 19–20, and FHL-1 contacts AfEno1 via SCRs 6–7. Both regulators when bound to AfEno1 retain cofactor activity and assist in C3b inactivation. Similarly, the classical pathway regulator C4BP binds to AfEno1 and bound to AfEno1; C4BP assists in C4b inactivation. Plasminogen which binds to AfEno1 via lysine residues is accessible for the tissue-type plasminogen activator (tPA), and active plasmin cleaves the chromogenic substrate S2251, degrades fibrinogen, and inactivates C3 and C3b. Plasmin attached to swollen A. fumigatus conidia damages human A549 lung epithelial cells, reduces the cellular metabolic activity, and induces cell retraction, which results in exposure of the extracellular matrix. Thus, A. fumigatus AfEno1 is a moonlighting protein and virulence factor which recruits several human regulators. The attached human regulators allow the fungal pathogen to control complement at the level of C3 and to damage endothelial cell layers and tissue components.

Aspergillus fumigatus is a ubiquitous opportunistic fungal pathogen that can cause severe infections in immunocompromised patients. Conidia that reach the lower respiratory tract are confronted with alveolar macrophages, which are the resident phagocytic cells, constituting the first line of defense. If not efficiently removed in time, A. fumigatus conidia can germinate causing severe infections associated with high mortality rates. Mice are the most extensively used model organism in research on A. fumigatus infections. However, in addition to structural differences in the lung physiology of mice and the human host, applied infection doses in animal experiments are typically orders of magnitude larger compared to the daily inhalation doses of humans. The influence of these factors, which must be taken into account in a quantitative comparison and knowledge transfer from mice to humans, is difficult to measure since in vivo live cell imaging of the infection dynamics under physiological conditions is currently not possible. In the present study, we compare A. fumigatus infection in mice and humans by virtual infection modeling using a hybrid agent-based model that accounts for the respective lung physiology and the impact of a wide range of infection doses on the spatial infection dynamics. Our computer simulations enable comparative quantification of A. fumigatus infection clearance in the two hosts to elucidate (i) the complex interplay between alveolar morphometry and the fungal burden and (ii) the dynamics of infection clearance, which for realistic fungal burdens is found to be more efficiently realized in mice compared to humans.

Iron is an essential micronutrient for most organisms and fungi are no exception. Iron uptake by fungi is facilitated by receptor-mediated internalization of siderophores, heme and reductive iron assimilation (RIA). The RIA employs three protein groups: (i) the ferric reductases (Fre5 proteins), (ii) the multicopper ferroxidases (Fet3) and (iii) the high-affinity iron permeases (Ftr1). Phenotyping under different iron concentrations revealed detrimental effects on spore swelling and hyphal formation under iron depletion, but yeast-like morphology under iron excess. Since access to iron is limited during pathogenesis, pathogens are placed under stress due to nutrient limitations. To combat this, gene duplication and differential gene expression of key iron uptake genes are utilized to acquire iron against the deleterious effects of iron depletion. In the genome of the human pathogenic fungus L. corymbifera, three, four and three copies were identified for FRE5, FTR1 and FET3 genes, respectively. As in other fungi, FET3 and FTR1 are syntenic and co-expressed in L. corymbifera. Expression of FRE5, FTR1 and FET3 genes is highly up-regulated during iron limitation (Fe-), but lower during iron excess (Fe+). Fe- dependent upregulation of gene expression takes place in LcFRE5 II and III, LcFTR1 I and II, as well as LcFET3 I and II suggesting a functional role in pathogenesis. The syntenic LcFTR1 I–LcFET3 I gene pair is co-expressed during germination, whereas LcFTR1 II- LcFET3 II is co-expressed during hyphal proliferation. LcFTR1 I, II and IV were overexpressed in Saccharomyces cerevisiae to represent high and moderate expression of intracellular transport of Fe3+, respectively. Challenge of macrophages with the yeast mutants revealed no obvious role for LcFTR1 I, but possible functions of LcFTR1 II and IVs in recognition by macrophages. RIA expression pattern was used for a new model of interaction between L. corymbifera and macrophages.

Pneumonia is the leading cause of hospitalization worldwide. Besides viruses, bacterial co-infections dramatically exacerbate infection. In general, surfactant protein-A (SP-A) represents a first line of immune defense. In this study, we analyzed whether influenza A virus (IAV) and/or Staphylococcus aureus (S. aureus) infections affect SP-A expression. To closely reflect the situation in the lung, we used a human alveolus-on-a-chip model and a murine pneumonia model. Our results show that S. aureus can reduce extracellular levels of SP-A, most likely attributed to bacterial proteases. Mono-epithelial cell culture experiments reveal that the expression of SP-A is not directly affected by IAV or S. aureus. Yet, the mRNA expression of SP-A is strongly down-regulated by TNF-α, which is highly produced by professional phagocytes in response to bacterial infection. By using the human alveolus-on-a-chip model, we show that the down-regulation of SP-A is strongly dependent on macrophages. In a murine model of pneumonia, we can confirm that S. aureus decreases SP-A levels in vivo. These findings indicate that (I) complex interactions of epithelial and immune cells induce down-regulation of SP-A expression and (II) bacterial mono- and super-infections reduce SP-A expression in the lung, which might contribute to a severe outcome of bacterial pneumonia.

The opportunistic fungal pathogen Aspergillus fumigatus can cause life-threatening infections, particularly in immunocompromised patients. Most pathogenic microbes control host innate immune responses at the earliest time, already before infiltrating host immune cells arrive at the site of infection. Here, we identify Aspf2 as the first A. fumigatus Factor H-binding protein. Aspf2 recruits several human plasma regulators, Factor H, factor-H-like protein 1 (FHL-1), FHR1, and plasminogen. Factor H contacts Aspf2 via two regions located in SCRs6–7 and SCR20. FHL-1 binds via SCRs6–7, and FHR1 via SCRs3–5. Factor H and FHL-1 attached to Aspf2-maintained cofactor activity and assisted in C3b inactivation. A Δaspf2 knockout strain was generated which bound Factor H with 28% and FHL-1 with 42% lower intensity. In agreement with less immune regulator acquisition, when challenged with complement-active normal human serum, Δaspf2 conidia had substantially more C3b (>57%) deposited on their surface. Consequently, Δaspf2 conidia were more efficiently phagocytosed (>20%) and killed (44%) by human neutrophils as wild-type conidia. Furthermore, Aspf2 recruited human plasminogen and, when activated by tissue-type plasminogen activator, newly generated plasmin cleaved the chromogenic substrate S2251 and degraded fibrinogen. Furthermore, plasmin attached to conidia damaged human lung epithelial cells, induced cell retraction, and caused matrix exposure. Thus, Aspf2 is a central immune evasion protein and plasminogen ligand of A. fumigatus. By blocking host innate immune attack and by disrupting human lung epithelial cell layers, Aspf2 assists in early steps of fungal infection and likely allows tissue penetration.

ABSTRACT Life-threatening systemic infections often occur due to the translocation of pathogens across the gut barrier and into the bloodstream. While the microbial and host mechanisms permitting bacterial gut translocation are well characterized, these mechanisms are still unclear for fungal pathogens such as Candida albicans, a leading cause of nosocomial fungal bloodstream infections. In this study, we dissected the cellular mechanisms of translocation of C. albicans across intestinal epithelia in vitro and identified fungal genes associated with this process. We show that fungal translocation is a dynamic process initiated by invasion and followed by cellular damage and loss of epithelial integrity. A screen of >2,000 C. albicans deletion mutants identified genes required for cellular damage of and translocation across enterocytes. Correlation analysis suggests that hypha formation, barrier damage above a minimum threshold level, and a decreased epithelial integrity are required for efficient fungal translocation. Translocation occurs predominantly via a transcellular route, which is associated with fungus-induced necrotic epithelial damage, but not apoptotic cell death. The cytolytic peptide toxin of C. albicans, candidalysin, was found to be essential for damage of enterocytes and was a key factor in subsequent fungal translocation, suggesting that transcellular translocation of C. albicans through intestinal layers is mediated by candidalysin. However, fungal invasion and low-level translocation can also occur via non-transcellular routes in a candidalysin-independent manner. This is the first study showing translocation of a human-pathogenic fungus across the intestinal barrier being mediated by a peptide toxin. IMPORTANCE Candida albicans, usually a harmless fungus colonizing human mucosae, can cause lethal bloodstream infections when it manages to translocate across the intestinal epithelium. This can result from antibiotic treatment, immune dysfunction, or intestinal damage (e.g., during surgery). However, fungal processes may also contribute. In this study, we investigated the translocation process of C. albicans using in vitro cell culture models. Translocation occurs as a stepwise process starting with invasion, followed by epithelial damage and loss of epithelial integrity. The ability to secrete candidalysin, a peptide toxin deriving from the hyphal protein Ece1, is key: C. albicans hyphae, secreting candidalysin, take advantage of a necrotic weakened epithelium to translocate through the intestinal layer.

Diarrhea-positive hemolytic-uremic syndrome (HUS) is a renal disorder that results from infections with Shiga-toxin (Stx)-producing Escherichia coli. The aim of this study was to establish well-defined refined murine models of HUS that can serve as preclinical tools to elucidate molecular mechanisms of disease development. C57BL/6J mice were subjected to different doses of Stx2 purified from an E. coli O157:H7 patient isolate. Animals received 300 ng/kg Stx2 and were sacrificed on day 3 to establish an acute model with fast disease progression. Alternatively, mice received 25 ng/kg Stx2 on days 0, 3, and 6, and were sacrificed on day 7 to establish a subacute model with moderate disease progression. Indicated by a rise in hematocrit, we observed dehydration despite volume substitution in both models, which was less pronounced in mice that underwent the 7-day regime. Compared with sham-treated animals, mice subjected to Stx2 developed profound weight loss, kidney dysfunction (elevation of plasma urea, creatinine, and neutrophil gelatinase-associated lipocalin), kidney injury (tubular injury and loss of endothelial cells), thrombotic microangiopathy (arteriolar microthrombi), and hemolysis (elevation of plasma bilirubin, lactate dehydrogenase, and free hemoglobin). The degree of complement activation (C3c deposition), immune cell invasion (macrophages and T lymphocytes), apoptosis, and proliferation were significantly increased in kidneys of mice subjected to the 7-day but not in kidneys of mice subjected to the 3-day regime. However, glomerular and kidney volume remained mainly unchanged, as assessed by 3D analysis of whole mount kidneys using CD31 staining with light sheet fluorescence microscopy. Gene expression analysis of kidneys revealed a total of only 91 overlapping genes altered in both Stx2 models. In conclusion, we have developed two refined mouse models with different disease progression, both leading to hemolysis, thrombotic microangiopathy, and acute kidney dysfunction and damage as key clinical features of human HUS. While intrarenal changes (apoptosis, proliferation, complement deposition, and immune cell invasion) mainly contribute to the pathophysiology of the subacute model, prerenal pathomechanisms (hypovolemia) play a predominant role in the acute model. Both models allow the further study of the pathomechanisms of most aspects of human HUS and the testing of distinct novel treatment strategies.

The condition of neutropenia, i.e., a reduced absolute neutrophil count in blood, constitutes a major risk factor for severe infections in the affected patients. Candida albicans and Candida glabrata are opportunistic pathogens and the most prevalent fungal species in the human microbiota. In immunocompromised patients, they can become pathogenic and cause infections with high mortality rates. In this study, we use a previously established approach that combines experiments and computational models to investigate the innate immune response during blood stream infections with the two fungal pathogens C. albicans and C. glabrata. First, we determine immune-reaction rates and migration parameters under healthy conditions. Based on these findings, we simulate virtual patients and investigate the impact of neutropenic conditions on the infection outcome with the respective pathogen. Furthermore, we perform in silico treatments of these virtual patients by simulating a medical treatment that enhances neutrophil activity in terms of phagocytosis and migration. We quantify the infection outcome by comparing the response to the two fungal pathogens relative to non-neutropenic individuals. The analysis reveals that these fungal infections in neutropenic patients can be successfully cleared by cytokine treatment of the remaining neutrophils; and that this treatment is more effective for C. glabrata than for C. albicans.

Bloodstream infections by the human-pathogenic fungi Candida albicans and Candida glabrata increasingly occur in hospitalized patients and are associated with high mortality rates. The early immune response against these fungi in human blood comprises a concerted action of humoral and cellular components of the innate immune system. Upon entering the blood, the majority of fungal cells will be eliminated by innate immune cells, i.e., neutrophils and monocytes. However, recent studies identified a population of fungal cells that can evade the immune response and thereby may disseminate and cause organ dissemination, which is frequently observed during candidemia. In this study, we investigate the so far unresolved mechanism of fungal immune evasion in human whole blood by testing hypotheses with the help of mathematical modeling. We use a previously established state-based virtual infection model for whole-blood infection with C. albicans to quantify the immune response and identified the fungal immune-evasion mechanism. While this process was assumed to be spontaneous in the previous model, we now hypothesize that the immune-evasion process is mediated by host factors and incorporate such a mechanism in the model. In particular, we propose, based on previous studies that the fungal immune-evasion mechanism could possibly arise through modification of the fungal surface by as of yet unknown proteins that are assumed to be secreted by activated neutrophils. To validate or reject any of the immune-evasion mechanisms, we compared the simulation of both immune-evasion models for different infection scenarios, i.e., infection of whole blood with either C. albicans or C. glabrata under non-neutropenic and neutropenic conditions. We found that under non-neutropenic conditions, both immune-evasion models fit the experimental data from whole-blood infection with C. albicans and C. glabrata. However, differences between the immune-evasion models could be observed for the infection outcome under neutropenic conditions with respect to the distribution of fungal cells across the immune cells. Based on these predictions, we suggested specific experimental studies that might allow for the validation or rejection of the proposed immune-evasion mechanism.

Mathematical modeling and computer simulations have become an integral part of modern biological research. The strength of theoretical approaches is in the simplification of complex biological systems. We here consider the general problem of receptor–ligand binding in the context of antibody–antigen binding. On the one hand, we establish a quantitative mapping between macroscopic binding rates of a deterministic differential equation model and their microscopic equivalents as obtained from simulating the spatiotemporal binding kinetics by stochastic agent-based models. On the other hand, we investigate the impact of various properties of B cell-derived receptors—such as their dimensionality of motion, morphology, and binding valency—on the receptor–ligand binding kinetics. To this end, we implemented an algorithm that simulates antigen binding by B cell-derived receptors with a Y-shaped morphology that can move in different dimensionalities, i.e., either as membrane-anchored receptors or as soluble receptors. The mapping of the macroscopic and microscopic binding rates allowed us to quantitatively compare different agent-based model variants for the different types of B cell-derived receptors. Our results indicate that the dimensionality of motion governs the binding kinetics and that this predominant impact is quantitatively compensated by the bivalency of these receptors.

Staphylococcus aureus colonizes epithelial surfaces, but it can also cause severe infections. The aim of this work was to investigate whether bacterial virulence correlates with defined types of tissue infections. For this, we collected 10–12 clinical S. aureus strains each from nasal colonization, and from patients with endoprosthesis infection, hematogenous osteomyelitis, and sepsis. All strains were characterized by genotypic analysis, and by the expression of virulence factors. The host–pathogen interaction was studied through several functional assays in osteoblast cultures. Additionally, selected strains were tested in a murine sepsis/osteomyelitis model. We did not find characteristic bacterial features for the defined infection types; rather, a wide range in all strain collections regarding cytotoxicity and invasiveness was observed. Interestingly, all strains were able to persist and to form small colony variants (SCVs). However, the low-cytotoxicity strains survived in higher numbers, and were less efficiently cleared by the host than the highly cytotoxic strains. In summary, our results indicate that not only destructive, but also low-cytotoxicity strains are able to induce infections. The low-cytotoxicity strains can successfully survive, and are less efficiently cleared from the host than the highly cytotoxic strains, which represent a source for chronic infections. The understanding of this interplay/evolution between the host and the pathogen during infection, with specific attention towards low-cytotoxicity isolates, will help to optimize treatment strategies for invasive and therapy-refractory infection courses.

Application of personalized medicine requires integration of different data to determine each patient’s unique clinical constitution. The automated analysis of medical data is a growing field where different machine learning techniques are used to minimize the time-consuming task of manual analysis. The evaluation, and often training, of automated classifiers requires manually labelled data as ground truth. In many cases such labelling is not perfect, either because of the data being ambiguous even for a trained expert or because of mistakes. Here we investigated the interobserver variability of image data comprising fluorescently stained circulating tumor cells and its effect on the performance of two automated classifiers, a random forest and a support vector machine. We found that uncertainty in annotation between observers limited the performance of the automated classifiers, especially when it was included in the test set on which classifier performance was measured. The random forest classifier turned out to be resilient to uncertainty in the training data while the support vector machine’s performance is highly dependent on the amount of uncertainty in the training data. We finally introduced the consensus data set as a possible solution for evaluation of automated classifiers that minimizes the penalty of interobserver variability.

Candida albicans bloodstream infection is increasingly frequent and can result in disseminated candidiasis associated with high mortality rates. To analyze the innate immune response against C. albicans, fungal cells were added to human whole-blood samples. After inoculation, C. albicans started to filament and predominantly associate with neutrophils, whereas only a minority of fungal cells became attached to monocytes. While many parameters of host-pathogen interaction were accessible to direct experimental quantification in the whole-blood infection assay, others were not. To overcome these limitations, we generated a virtual infection model that allowed detailed and quantitative predictions on the dynamics of host-pathogen interaction. Experimental time-resolved data were simulated using a state-based modeling approach combined with the Monte Carlo method of simulated annealing to obtain quantitative predictions on a priori unknown transition rates and to identify the main axis of antifungal immunity. Results clearly demonstrated a predominant role of neutrophils, mediated by phagocytosis and intracellular killing as well as the release of antifungal effector molecules upon activation, resulting in extracellular fungicidal activity. Both mechanisms together account for almost [Formula: see text] of C. albicans killing, clearly proving that beside being present in larger numbers than other leukocytes, neutrophils functionally dominate the immune response against C. albicans in human blood. A fraction of C. albicans cells escaped phagocytosis and remained extracellular and viable for up to four hours. This immune escape was independent of filamentation and fungal activity and not linked to exhaustion or inactivation of innate immune cells. The occurrence of C. albicans cells being resistant against phagocytosis may account for the high proportion of dissemination in C. albicans bloodstream infection. Taken together, iterative experiment-model-experiment cycles allowed quantitative analyses of the interplay between host and pathogen in a complex environment like human blood.

Aspergillus fumigatus is one of the most important human fungal pathogens, causing life-threatening diseases. Since humans inhale hundreds to thousands of fungal conidia every day, the lower respiratory tract is the primary site of infection. Current interaction networks of the innate immune response attribute fungal recognition and detection to alveolar macrophages, which are thought to be the first cells to get in contact with the fungus. At present, these networks are derived from in vitro or in situ assays, as the peculiar physiology of the human lung makes in vivo experiments, including imaging on the cell-level, hard to realize. We implemented a spatio-temporal agent-based model of a human alveolus in order to perform in silico experiments of a virtual infection scenario, for an alveolus infected with A. fumigatus under physiological conditions. The virtual analog captures the three-dimensional alveolar morphology consisting of the two major alveolar epithelial cell types and the pores of Kohn as well as the dynamic process of respiration. To the best of our knowledge this is the first agent-based model of a dynamic human alveolus in the presence of respiration. A key readout of our simulations is the first-passage-time of alveolar macrophages, which is the period of time that elapses until the first physical macrophage-conidium contact is established. We tested for random and chemotactic migration modes of alveolar macrophages and varied their corresponding parameter sets. The resulting first-passage-time distributions imply that randomly migrating macrophages fail to find the conidium before the start of germination, whereas guidance by chemotactic signals derived from the alveolar epithelial cell associated with the fungus enables a secure and successful discovery of the pathogen in time.

Cell migration is the driving force behind the dynamics of many diverse biological processes. Even though microscopy experiments are routinely performed today by which populations of cells are visualized in space and time, valuable information contained in image data is often disregarded because statistical analyses are performed at the level of cell populations rather than at the single-cell level. Image-based systems biology is a modern approach that aims at quantitatively analyzing and modeling biological processes by developing novel strategies and tools for the interpretation of image data. In this study, we take first steps towards a fully automated characterization and parameter-free classification of cell track data that can be generally applied to tracked objects as obtained from image data. The requirements to achieve this aim include: (i) combination of different measures for single cell tracks, such as the confinement ratio and the asphericity of the track volume, and (ii) computation of these measures in a staggered fashion to retrieve local information from all possible combinations of track segments. We demonstrate for a population of synthetic cell tracks as well as for in vitro neutrophil tracks obtained from microscopy experiment that the information contained in the track data is fully exploited in this way and does not require any prior knowledge, which keeps the analysis unbiased and general. The identification of cells that show the same type of migration behavior within the population of all cells is achieved via agglomerative hierarchical clustering of cell tracks in the parameter space of the staggered measures. The recognition of characteristic patterns is highly desired to advance our knowledge about the dynamics of biological processes.

Mitochondrial dynamics and mitophagy play a key role in ensuring mitochondrial quality control. Impairment thereof was proposed to be causative to neurodegenerative diseases, diabetes, and cancer. Accumulation of mitochondrial dysfunction was further linked to aging. Here we applied a probabilistic modeling approach integrating our current knowledge on mitochondrial biology allowing us to simulate mitochondrial function and quality control during aging in silico. We demonstrate that cycles of fusion and fission and mitophagy indeed are essential for ensuring a high average quality of mitochondria, even under conditions in which random molecular damage is present. Prompted by earlier observations that mitochondrial fission itself can cause a partial drop in mitochondrial membrane potential, we tested the consequences of mitochondrial dynamics being harmful on its own. Next to directly impairing mitochondrial function, pre-existing molecular damage may be propagated and enhanced across the mitochondrial population by content mixing. In this situation, such an infection-like phenomenon impairs mitochondrial quality control progressively. However, when imposing an age-dependent deceleration of cycles of fusion and fission, we observe a delay in the loss of average quality of mitochondria. This provides a rational why fusion and fission rates are reduced during aging and why loss of a mitochondrial fission factor can extend life span in fungi. We propose the 'mitochondrial infectious damage adaptation' (MIDA) model according to which a deceleration of fusion-fission cycles reflects a systemic adaptation increasing life span.

Aspergillus fumigatus is a ubiquitous airborne fungus and opportunistic human pathogen. In immunocompromised hosts, the fungus can cause life-threatening diseases like invasive pulmonary aspergillosis. Since the incidence of fungal systemic infections drastically increased over the last years, it is a major goal to investigate the pathobiology of A. fumigatus and in particular the interactions of A. fumigatus conidia with immune cells. Many of these studies include the activity of immune effector cells, in particular of macrophages, when they are confronted with conidia of A. fumigus wild-type and mutant strains. Here, we report the development of an automated analysis of confocal laser scanning microscopy images from macrophages coincubated with different A. fumigatus strains. At present, microscopy images are often analysed manually, including cell counting and determination of interrelations between cells, which is very time consuming and error-prone. Automation of this process overcomes these disadvantages and standardises the analysis, which is a prerequisite for further systems biological studies including mathematical modeling of the infection process. For this purpose, the cells in our experimental setup were differentially stained and monitored by confocal laser scanning microscopy. To perform the image analysis in an automatic fashion, we developed a ruleset that is generally applicable to phagocytosis assays and in the present case was processed by the software Definiens Developer XD. As a result of a complete image analysis we obtained features such as size, shape, number of cells and cell-cell contacts. The analysis reported here, reveals that different mutants of A. fumigatus have a major influence on the ability of macrophages to adhere and to phagocytose the respective conidia. In particular, we observe that the phagocytosis ratio and the aggregation behaviour of pksP mutant compared to wild-type conidia are both significantly increased.

BACKGROUND:The immune system is a complex adaptive system of cells and molecules that are interwoven in a highly organized communication network. Primary immune deficiencies are disorders in which essential parts of the immune system are absent or do not function according to plan. X-linked agammaglobulinemia is a B-lymphocyte maturation disorder in which the production of immunoglobulin is prohibited by a genetic defect. Patients have to be put on life-long immunoglobulin substitution therapy in order to prevent recurrent and persistent opportunistic infections. METHODOLOGY:We formulate an immune response model in terms of stochastic differential equations and perform a systematic analysis of empirical therapy protocols that differ in the treatment frequency. The model accounts for the immunoglobulin reduction by natural degradation and by antigenic consumption, as well as for the periodic immunoglobulin replenishment that gives rise to an inhomogeneous distribution of immunoglobulin specificities in the shape space. Results are obtained from computer simulations and from analytical calculations within the framework of the Fokker-Planck formalism, which enables us to derive closed expressions for undetermined model parameters such as the infection clearance rate. CONCLUSIONS:We find that the critical value of the clearance rate, below which a chronic infection develops, is strongly dependent on the strength of fluctuations in the administered immunoglobulin dose per treatment and is an increasing function of the treatment frequency. The comparative analysis of therapy protocols with regard to the treatment frequency yields quantitative predictions of therapeutic relevance, where the choice of the optimal treatment frequency reveals a conflict of competing interests: In order to diminish immunomodulatory effects and to make good economic sense, therapeutic immunoglobulin levels should be kept close to physiological levels, implying high treatment frequencies. However, clearing infections without additional medication is more reliably achieved by substitution therapies with low treatment frequencies. Our immune response model predicts that the compromise solution of immunoglobulin substitution therapy has a treatment frequency in the range from one infusion per week to one infusion per two weeks.

The interaction of T cells and antigen-presenting cells is central to adaptive immunity and involves the formation of immunological synapses in many cases. The surface molecules of the cells form a characteristic spatial pattern whose formation mechanisms and function are largely unknown. We perform computer simulations of recent experiments on geometrically repatterned immunological synapses and explain the emerging structure as well as the formation dynamics. Only the combination of in vitro experiments and computer simulations has the potential to pinpoint the kind of interactions involved. The presented simulations make clear predictions for the structure of the immunological synapse and elucidate the role of a self-organizing attraction between complexes of T cell receptor and peptide-MHC molecule, versus a centrally directed motion of these complexes.