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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.

Fungi of the genus Mortierella occur ubiquitously in soils where they play pivotal roles in carbon cycling, xenobiont degradation, and promoting plant growth. These important fungi are, however, threatened by micropredators such as fungivorous nematodes, and yet little is known about their protective tactics. We report that Mortierella verticillata NRRL 6337 harbors a bacterial endosymbiont that efficiently shields its host from nematode attacks with anthelmintic metabolites. Microscopic investigation and 16S ribosomal DNA analysis revealed that a previously overlooked bacterial symbiont belonging to the genus Mycoavidus dwells in M. verticillata hyphae. Metabolic profiling of the wild-type fungus and a symbiont-free strain obtained by antibiotic treatment as well as genome analyses revealed that highly cytotoxic macrolactones (CJ-12,950 and CJ-13,357, syn. necroxime C and D), initially thought to be metabolites of the soil-inhabiting fungus, are actually biosynthesized by the endosymbiont. According to comparative genomics, the symbiont belongs to a new species (Candidatus Mycoavidus necroximicus) with 12% of its 2.2 Mb genome dedicated to natural product biosynthesis, including the modular polyketide-nonribosomal peptide synthetase for necroxime assembly. Using Caenorhabditis elegans and the fungivorous nematode Aphelenchus avenae as test strains, we show that necroximes exert highly potent anthelmintic activities. Effective host protection was demonstrated in cocultures of nematodes with symbiotic and chemically complemented aposymbiotic fungal strains. Image analysis and mathematical quantification of nematode movement enabled evaluation of the potency. Our work describes a relevant role for endofungal bacteria in protecting fungi against mycophagous nematodes.

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.

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.

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. 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.

The soil community is a complex system characterized by predator-prey interactions. Fungi have developed effective strategies to defend themselves against predators. 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.

Understanding the complex interplay between host and pathogen during infection is critical for developing diagnostics and improving therapeutic interventions. Among the diverse arsenal employed by the host, antimicrobial peptides (AMP) play a key role in the defense against pathogens. We propose an immune evasion mechanism termed “Complex-mediated evasion” (CME), that allows pathogens to protect themselves against AMP and investigate it through mathematical modeling and computer simulations. To achieve CME, we hypothesize that the pathogen secretes defense molecules that bind AMP. When bound within the complex, AMP are unable to harm the pathogen. Due to molecular gradients, complexes may diffuse away from the pathogen, enhancing the protective effect of the mechanism by decreasing the concentration of AMP in the vicinity of the pathogen. We establish a mathematical model to (i) explore the sensitivity of the mechanism to various parameters and (ii) simulate the immune evasion of the human-pathogenic fungus Candida albicans .

Cell migration involves dynamic changes in cell shape. Intricate patterns of cell shape can be analyzed and classified using advanced shape descriptors, including spherical harmonics (SPHARM). Though SPHARM have been used to analyze and classify migrating cells, such classification did not exploit SPHARM spectra in their dynamics. Here, we examine whether additional information from dynamic SPHARM improves classification of cell migration patterns. We combine the static and dynamic SPHARM approach with a support-vector-machine classifier and compare their classification accuracies. We demonstrate that the dynamic SPHARM analysis classifies cell migration patterns more accurately than the static one for both synthetic and experimental data. Furthermore, by comparing the computed accuracies with that of a naive classifier, we can identify the experimental conditions and model parameters that significantly affect cell shape. This capability should – in the future – help to pinpoint factors that play an essential role in cell migration.

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.

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.