IL4I1 Is a Metabolic Immune Checkpoint that Activates the AHR and Promotes Tumor Progression.

Aryl hydrocarbon receptor (AHR) activation by tryptophan (Trp) catabolites enhances tumor malignancy and suppresses anti-tumor immunity. The context specificity of AHR target genes has so far impeded systematic investigation of AHR activity and its upstream enzymes across human cancers. A pan-tissue AHR signature, derived by natural language processing, revealed that across 32 tumor entities, interleukin-4-induced-1 (IL4I1) associates more frequently with AHR activity than IDO1 or TDO2, hitherto recognized as the main Trp-catabolic enzymes. IL4I1 activates the AHR through the generation of indole metabolites and kynurenic acid. It associates with reduced survival in glioma patients, promotes cancer cell motility, and suppresses adaptive immunity, thereby enhancing the progression of chronic lymphocytic leukemia (CLL) in mice. Immune checkpoint blockade (ICB) induces IDO1 and IL4I1. As IDO1 inhibitors do not block IL4I1, IL4I1 may explain the failure of clinical studies combining ICB with IDO1 inhibition. Taken together, IL4I1 blockade opens new avenues for cancer therapy.

Metabolic Adaptation Establishes Disease Tolerance to Sepsis.

Sepsis is an often lethal syndrome resulting from maladaptive immune and metabolic responses to infection, compromising host homeostasis. Disease tolerance is a defense strategy against infection that preserves host homeostasis without exerting a direct negative impact on pathogens. Here, we demonstrate that induction of the iron-sequestering ferritin H chain (FTH) in response to polymicrobial infections is critical to establish disease tolerance to sepsis. The protective effect of FTH is exerted via a mechanism that counters iron-driven oxidative inhibition of the liver glucose-6-phosphatase (G6Pase), and in doing so, sustains endogenous glucose production via liver gluconeogenesis. This is required to prevent the development of hypoglycemia that otherwise compromises disease tolerance to sepsis. FTH overexpression or ferritin administration establish disease tolerance therapeutically. In conclusion, disease tolerance to sepsis relies on a crosstalk between adaptive responses controlling iron and glucose metabolism, required to maintain blood glucose within a physiologic range compatible with host survival.

Candida albicans translocation through the intestinal epithelial barrier is promoted by fungal zinc acquisition and limited by NFκB-mediated barrier protection.

The opportunistic fungal pathogen Candida albicans thrives on human mucosal surfaces as a harmless commensal, but frequently causes infections under certain predisposing conditions. Translocation across the intestinal barrier into the bloodstream by intestine-colonizing C. albicans cells serves as the main source of disseminated candidiasis. However, the host and microbial mechanisms behind this process remain unclear. In this study we identified fungal and host factors specifically involved in infection of intestinal epithelial cells (IECs) using dual-RNA sequencing. Our data suggest that host-cell damage mediated by the peptide toxin candidalysin-encoding gene ECE1 facilitates fungal zinc acquisition. This in turn is crucial for the full virulence potential of C. albicans during infection. IECs in turn exhibit a filamentation- and damage-specific response to C. albicans infection, including NFκB, MAPK, and TNF signaling. NFκB activation by IECs limits candidalysin-mediated host-cell damage and mediates maintenance of the intestinal barrier and cell-cell junctions to further restrict fungal translocation. This is the first study to show that candidalysin-mediated damage is necessary for C. albicans nutrient acquisition during infection and to explain how IECs counteract damage and limit fungal translocation via NFκB-mediated maintenance of the intestinal barrier.

CD56-mediated activation of human natural killer cells is triggered by Aspergillus fumigatus galactosaminogalactan.

Invasive aspergillosis causes significant morbidity and mortality in immunocompromised patients. Natural killer (NK) cells are pivotal for antifungal defense. Thus far, CD56 is the only known pathogen recognition receptor on NK cells triggering potent antifungal activity against Aspergillus fumigatus. However, the underlying cellular mechanisms and the fungal ligand of CD56 have remained unknown. Using purified cell wall components, biochemical treatments, and ger mutants with altered cell wall composition, we herein found that CD56 interacts with the A. fumigatus cell wall carbohydrate galactosaminogalactan (GAG). This interaction induced NK-cell activation, degranulation, and secretion of immune-enhancing chemokines and cytotoxic effectors. Supernatants from GAG-stimulated NK cells elicited antifungal activity and enhanced antifungal effector responses of polymorphonuclear cells. In conclusion, we identified A. fumigatus GAG as a ligand of CD56 on human primary NK cells, stimulating potent antifungal effector responses and activating other immune cells.

Disruption of the Aspergillus fumigatus RNA interference machinery alters the conidial transcriptome.

The RNA interference (RNAi) pathway has evolved numerous functionalities in eukaryotes, with many on display in Kingdom Fungi. RNAi can regulate gene expression, facilitate drug resistance, or even be altogether lost to improve growth potential in some fungal pathogens. In the WHO fungal priority pathogen, Aspergillus fumigatus, the RNAi system is known to be intact and functional. To extend our limited understanding of A. fumigatus RNAi, we first investigated the genetic variation in RNAi-associated genes in a collection of 217 environmental and 83 clinical genomes, where we found that RNAi components are conserved even in clinical strains. Using endogenously expressed inverted-repeat transgenes complementary to a conditionally essential gene (pabA) or a nonessential gene (pksP), we determined that a subset of the RNAi componentry is active in inverted-repeat transgene silencing in conidia and mycelium. Analysis of mRNA-seq data from RNAi double-knockout strains linked the A. fumigatus dicer-like enzymes (DclA/B) and RNA-dependent RNA polymerases (RrpA/B) to regulation of conidial ribosome biogenesis genes; however, surprisingly few endogenous small RNAs were identified in conidia that could explain this broad change. Although RNAi was not clearly linked to growth or stress response defects in the RNAi knockouts, serial passaging of RNAi knockout strains for six generations resulted in lineages with diminished spore production over time, indicating that loss of RNAi can exert a fitness cost on the fungus. Cumulatively, A. fumigatus RNAi appears to play an active role in defense against double-stranded RNA species alongside a previously unappreciated housekeeping function in regulation of conidial ribosomal biogenesis genes.

GePI: large-scale text mining, customized retrieval and flexible filtering of gene/protein interactions.

We present GePI, a novel Web server for large-scale text mining of molecular interactions from the scientific biomedical literature. GePI leverages natural language processing techniques to identify genes and related entities, interactions between those entities and biomolecular events involving them. GePI supports rapid retrieval of interactions based on powerful search options to contextualize queries targeting (lists of) genes of interest. Contextualization is enabled by full-text filters constraining the search for interactions to either sentences or paragraphs, with or without pre-defined gene lists. Our knowledge graph is updated several times a week ensuring the most recent information to be available at all times. The result page provides an overview of the outcome of a search, with accompanying interaction statistics and visualizations. A table (downloadable in Excel format) gives direct access to the retrieved interaction pairs, together with information about the molecular entities, the factual certainty of the interactions (as verbatim expressed by the authors), and a text snippet from the original document that verbalizes each interaction. In summary, our Web application offers free, easy-to-use, and up-to-date monitoring of gene and protein interaction information, in company with flexible query formulation and filtering options. GePI is available at https://gepi.coling.uni-jena.de/.

Phosphoproteomics Profiling Defines a Target Landscape of the Basophilic Protein Kinases AKT, S6K, and RSK in Skeletal Myotubes.

Phosphorylation-dependent signal transduction plays an important role in regulating the functions and fate of skeletal muscle cells. Central players in the phospho-signaling network are the protein kinases AKT, S6K, and RSK as part of the PI3K-AKT-mTOR-S6K and RAF-MEK-ERK-RSK pathways. However, despite their functional importance, knowledge about their specific targets is incomplete because these kinases share the same basophilic substrate motif RxRxxp[ST]. To address this, we performed a multifaceted quantitative phosphoproteomics study of skeletal myotubes following kinase inhibition. Our data corroborate a cross talk between AKT and RAF, a negative feedback loop of RSK on ERK, and a putative connection between RSK and PI3K signaling. Altogether, we report a kinase target landscape containing 49 so far unknown target sites. AKT, S6K, and RSK phosphorylate numerous proteins involved in muscle development, integrity, and functions, and signaling converges on factors that are central for the skeletal muscle cytoskeleton. Whereas AKT controls insulin signaling and impinges on GTPase signaling, nuclear signaling is characteristic for RSK. Our data further support a role of RSK in glucose metabolism. Shared targets have functions in RNA maturation, stability, and translation, which suggests that these basophilic kinases establish an intricate signaling network to orchestrate and regulate processes involved in translation.

Distinct transcriptional responses to fludioxonil in Aspergillus fumigatus and its ΔtcsC and Δskn7 mutants reveal a crucial role for Skn7 in the cell wall reorganizations triggered by this antifungal.

BACKGROUND: Aspergillus fumigatus is a major fungal pathogen that causes severe problems due to its increasing resistance to many therapeutic agents. Fludioxonil is a compound that triggers a lethal activation of the fungal-specific High Osmolarity Glycerol pathway. Its pronounced antifungal activity against A. fumigatus and other pathogenic molds renders this agent an attractive lead substance for the development of new therapeutics. The group III hydride histidine kinase TcsC and its downstream target Skn7 are key elements of the multistep phosphorelay that represents the initial section of the High Osmolarity Glycerol pathway. Loss of tcsC results in resistance to fludioxonil, whereas a Δskn7 mutant is partially, but not completely resistant. RESULTS: In this study, we compared the fludioxonil-induced transcriptional responses in the ΔtcsC and Δskn7 mutant and their parental A. fumigatus strain. The number of differentially expressed genes correlates well with the susceptibility level of the individual strains. The wild type and, to a lesser extend also the Δskn7 mutant, showed a multi-faceted stress response involving genes linked to ribosomal and peroxisomal function, iron homeostasis and oxidative stress. A marked difference between the sensitive wild type and the largely resistant Δskn7 mutant was evident for many cell wall-related genes and in particular those involved in the biosynthesis of chitin. Biochemical data corroborate this differential gene expression that does not occur in response to hyperosmotic stress. CONCLUSIONS: Our data reveal that fludioxonil induces a strong and TcsC-dependent stress that affects many aspects of the cellular machinery. The data also demonstrate a link between Skn7 and the cell wall reorganizations that foster the characteristic ballooning and the subsequent lysis of fludioxonil-treated cells.

Global hypomethylation in childhood asthma identified by genome-wide DNA-methylation sequencing preferentially affects enhancer regions.

BACKGROUND: Childhood asthma is a result of a complex interaction of genetic and environmental components causing epigenetic and immune dysregulation, airway inflammation and impaired lung function. Although different microarray based EWAS studies have been conducted, the impact of epigenetic regulation in asthma development is still widely unknown. We have therefore applied unbiased whole genome bisulfite sequencing (WGBS) to characterize global DNA-methylation profiles of asthmatic children compared to healthy controls. METHODS: Peripheral blood samples of 40 asthmatic and 42 control children aged 5-15 years from three birth cohorts were sequenced together with paired cord blood samples. Identified differentially methylated regions (DMRs) were categorized in genotype-associated, cell-type-dependent, or prenatally primed. Network analysis and subsequent natural language processing of DMR-associated genes was complemented by targeted analysis of functional translation of epigenetic regulation on the transcriptional and protein level. RESULTS: In total, 158 DMRs were identified in asthmatic children compared to controls of which 37% were related to the eosinophil content. A global hypomethylation was identified affecting predominantly enhancer regions and regulating key immune genes such as IL4, IL5RA, and EPX. These DMRs were confirmed in n = 267 samples and could be linked to aberrant gene expression. Out of the 158 DMRs identified in the established phenotype, 56 were perturbed already at birth and linked, at least in part, to prenatal influences such as tobacco smoke exposure or phthalate exposure. CONCLUSION: This is the first epigenetic study based on whole genome sequencing to identify marked dysregulation of enhancer regions as a hallmark of childhood asthma.

Uncoupling of mucosal gene regulation, mRNA splicing and adherent microbiota signatures in inflammatory bowel disease.

OBJECTIVE: An inadequate host response to the intestinal microbiota likely contributes to the manifestation and progression of human inflammatory bowel disease (IBD). However, molecular approaches to unravelling the nature of the defective crosstalk and its consequences for intestinal metabolic and immunological networks are lacking. We assessed the mucosal transcript levels, splicing architecture and mucosa-attached microbial communities of patients with IBD to obtain a comprehensive view of the underlying, hitherto poorly characterised interactions, and how these are altered in IBD. DESIGN: Mucosal biopsies from Crohn's disease and patients with UC, disease controls and healthy individuals (n=63) were subjected to microbiome, transcriptome and splicing analysis, employing next-generation sequencing. The three data levels were integrated by different bioinformatic approaches, including systems biology-inspired network and pathway analysis. RESULTS: Microbiota, host transcript levels and host splicing patterns were influenced most strongly by tissue differences, followed by the effect of inflammation. Both factors point towards a substantial disease-related alteration of metabolic processes. We also observed a strong enrichment of splicing events in inflamed tissues, accompanied by an alteration of the mucosa-attached bacterial taxa. Finally, we noted a striking uncoupling of the three molecular entities when moving from healthy individuals via disease controls to patients with IBD. CONCLUSIONS: Our results provide strong evidence that the interplay between microbiome and host transcriptome, which normally characterises a state of intestinal homeostasis, is drastically perturbed in Crohn's disease and UC. Consequently, integrating multiple OMICs levels appears to be a promising approach to further disentangle the complexity of IBD.

SBMLmod: a Python-based web application and web service for efficient data integration and model simulation.

BACKGROUND: Systems Biology Markup Language (SBML) is the standard model representation and description language in systems biology. Enriching and analysing systems biology models by integrating the multitude of available data, increases the predictive power of these models. This may be a daunting task, which commonly requires bioinformatic competence and scripting. RESULTS: We present SBMLmod, a Python-based web application and service, that automates integration of high throughput data into SBML models. Subsequent steady state analysis is readily accessible via the web service COPASIWS. We illustrate the utility of SBMLmod by integrating gene expression data from different healthy tissues as well as from a cancer dataset into a previously published model of mammalian tryptophan metabolism. CONCLUSION: SBMLmod is a user-friendly platform for model modification and simulation. The web application is available at http://sbmlmod.uit.no , whereas the WSDL definition file for the web service is accessible via http://sbmlmod.uit.no/SBMLmod.wsdl . Furthermore, the entire package can be downloaded from https://github.com/MolecularBioinformatics/sbml-mod-ws . We envision that SBMLmod will make automated model modification and simulation available to a broader research community.

A refined genome-scale reconstruction of Chlamydomonas metabolism provides a platform for systems-level analyses.

Microalgae have reemerged as organisms of prime biotechnological interest due to their ability to synthesize a suite of valuable chemicals. To harness the capabilities of these organisms, we need a comprehensive systems-level understanding of their metabolism, which can be fundamentally achieved through large-scale mechanistic models of metabolism. In this study, we present a revised and significantly improved genome-scale metabolic model for the widely-studied microalga, Chlamydomonas reinhardtii. The model, iCre1355, represents a major advance over previous models, both in content and predictive power. iCre1355 encompasses a broad range of metabolic functions encoded across the nuclear, chloroplast and mitochondrial genomes accounting for 1355 genes (1460 transcripts), 2394 and 1133 metabolites. We found improved performance over the previous metabolic model based on comparisons of predictive accuracy across 306 phenotypes (from 81 mutants), lipid yield analysis and growth rates derived from chemostat-grown cells (under three conditions). Measurement of macronutrient uptake revealed carbon and phosphate to be good predictors of growth rate, while nitrogen consumption appeared to be in excess. We analyzed high-resolution time series transcriptomics data using iCre1355 to uncover dynamic pathway-level changes that occur in response to nitrogen starvation and changes in light intensity. This approach enabled accurate prediction of growth rates, the cessation of growth and accumulation of triacylglycerols during nitrogen starvation, and the temporal response of different growth-associated pathways to increased light intensity. Thus, iCre1355 represents an experimentally validated genome-scale reconstruction of C. reinhardtii metabolism that should serve as a useful resource for studying the metabolic processes of this and related microalgae.

Computing the various pathways of penicillin synthesis and their molar yields.

More than 80 years after its discovery, penicillin is still a widely used and commercially highly important antibiotic. Here, we analyse the metabolic network of penicillin synthesis in Penicillium chrysogenum based on the concept of elementary flux modes. In particular, we consider the synthesis of the invariant molecular core of the various subtypes of penicillin and the two major ways of incorporating sulfur: transsulfuration and direct sulfhydrylation. 66 elementary modes producing this invariant core are obtained. These show four different yields with respect to glucose, notably ½, 2/5, 1/3, and 2/7, with the highest yield of ½ occurring only when direct sulfhydrylation is used and α-aminoadipate is completely recycled. In the case of no recycling of this intermediate, we find the maximum yield to be 2/7. We compare these values with earlier literature values. Our analysis provides a systematic overview of the redundancy in penicillin synthesis and a detailed insight into the corresponding routes. Moreover, we derive suggestions for potential knockouts that could increase the average yield.

High-Throughput Profiling of Candida auris Isolates Reveals Clade-Specific Metabolic Differences.

Candida auris, a multidrug-resistant human fungal pathogen that causes outbreaks of invasive infections, emerged as four distinct geographical clades. Previous studies identified genomic and proteomic differences in nutrient utilization on comparison to Candida albicans, suggesting that certain metabolic features may contribute to C. auris emergence. Since no high-throughput clade-specific metabolic characterization has been described yet, we performed a phenotypic screening of C. auris strains from all 4 clades on 664 nutrients, 120 chemicals, and 24 stressors. We identified common and clade- or strain-specific responses, including the preferred utilization of various dipeptides as nitrogen source and the inability of the clade II isolate AR 0381 to withstand chemical stress. Further analysis of the metabolic properties of C. auris isolates showed robust growth on intermediates of the tricarboxylic acid cycle, such as citrate and succinic and malic acids. However, there was reduced or no growth on pyruvate, lactic acid, or acetate, likely due to the lack of the monocarboxylic acid transporter Jen1, which is conserved in most pathogenic Candida species. Comparison of C. auris and C. albicans transcriptomes of cells grown on alternative carbon sources and dipeptides as a nitrogen source revealed common as well as species-unique responses. C. auris induced a significant number of genes with no ortholog in C. albicans, e.g., genes similar to the nicotinic acid transporter TNA1 (alternative carbon sources) and to the oligopeptide transporter (OPT) family (dipeptides). Thus, C. auris possesses unique metabolic features which could have contributed to its emergence as a pathogen. IMPORTANCE Four main clades of the emerging, multidrug-resistant human pathogen Candida auris have been identified, and they differ in their susceptibilities to antifungals and disinfectants. Moreover, clade- and strain-specific metabolic differences have been identified, but a comprehensive overview of nutritional characteristics and resistance to various stressors is missing. Here, we performed high-throughput phenotypic characterization of C. auris on various nutrients, stressors, and chemicals and obtained transcriptomes of cells grown on selected nutrients. The generated data sets identified multiple clade- and strain-specific phenotypes and induction of C. auris-specific metabolic genes, showing unique metabolic properties. The presented work provides a large amount of information for further investigations that could explain the role of metabolism in emergence and pathogenicity of this multidrug-resistant fungus.

Genome-scale metabolic modeling of Aspergillus fumigatus strains reveals growth dependencies on the lung microbiome.

Aspergillus fumigatus, an opportunistic human pathogen, frequently infects the lungs of people with cystic fibrosis and is one of the most common causes of infectious-disease death in immunocompromised patients. Here, we construct 252 strain-specific, genome-scale metabolic models of this important fungal pathogen to study and better understand the metabolic component of its pathogenic versatility. The models show that 23.1% of A. fumigatus metabolic reactions are not conserved across strains and are mainly associated with amino acid, nucleotide, and nitrogen metabolism. Profiles of non-conserved reactions and growth-supporting reaction fluxes are sufficient to differentiate strains, for example by environmental or clinical origin. In addition, shotgun metagenomics analysis of sputum from 40 cystic fibrosis patients (15 females, 25 males) before and after diagnosis with an A. fumigatus colonization suggests that the fungus shapes the lung microbiome towards a more beneficial fungal growth environment associated with aromatic amino acid availability and the shikimate pathway. Our findings are starting points for the development of drugs or microbiome intervention strategies targeting fungal metabolic needs for survival and colonization in the non-native environment of the human lung.

Pathogen-specific innate immune response patterns are distinctly affected by genetic diversity.

Innate immune responses vary by pathogen and host genetics. We analyze quantitative trait loci (eQTLs) and transcriptomes of monocytes from 215 individuals stimulated by fungal, Gram-negative or Gram-positive bacterial pathogens. We identify conserved monocyte responses to bacterial pathogens and a distinct antifungal response. These include 745 response eQTLs (reQTLs) and corresponding genes with pathogen-specific effects, which we find first in samples of male donors and subsequently confirm for selected reQTLs in females. reQTLs affect predominantly upregulated genes that regulate immune response via e.g., NOD-like, C-type lectin, Toll-like and complement receptor-signaling pathways. Hence, reQTLs provide a functional explanation for individual differences in innate response patterns. Our identified reQTLs are also associated with cancer, autoimmunity, inflammatory and infectious diseases as shown by external genome-wide association studies. Thus, reQTLs help to explain interindividual variation in immune response to infection and provide candidate genes for variants associated with a range of diseases.

From environmental adaptation to host survival: Attributes that mediate pathogenicity of Candida auris.

Candida species are a major cause of invasive fungal infections. While Candida albicans, C. glabrata, C. parapsilosis, and C. tropicalis are the most dominant species causing life-threatening candidiasis, C. auris recently emerged as a new species causing invasive infections with high rates of clinical treatment failures. To mimic initial phases of systemic Candida infections with dissemination via the bloodstream and to elucidate the pathogenic potential of C. auris, we used an ex vivo whole blood infection model. Similar to other clinically relevant Candida spp., C. auris is efficiently killed in human blood, but showed characteristic patterns of immune cell association, survival rates, and cytokine induction. Dual-species transcriptional profiling of C. auris-infected blood revealed a unique C. auris gene expression program during infection, while the host response proofed similar and conserved compared to other Candida species. C. auris-specific responses included adaptation and survival strategies, such as counteracting oxidative burst of immune cells, but also expression of potential virulence factors, (drug) transporters, and cell surface-associated genes. Despite comparable pathogenicity to other Candida species in our model, C. auris-specific transcriptional adaptations as well as its increased stress resistance and long-term environmental survival, likely contribute to the high risk of contamination and distribution in a nosocomial setting. Moreover, infections of neutrophils with pre-starved C. auris cells suggest that environmental preconditioning can have modulatory effects on the early host interaction. In summary, we present novel insights into C. auris pathogenicity, revealing adaptations to human blood and environmental niches distinctive from other Candida species.

Candida albicans SR-Like Protein Kinases Regulate Different Cellular Processes: Sky1 Is Involved in Control of Ion Homeostasis, While Sky2 Is Important for Dipeptide Utilization.

Protein kinases play a crucial role in regulating cellular processes such as growth, proliferation, environmental adaptation and stress responses. Serine-arginine (SR) protein kinases are highly conserved in eukaryotes and regulate fundamental processes such as constitutive and alternative splicing, mRNA processing and ion homeostasis. The Candida albicans genome encodes two (Sky1, Sky2) and the Candida glabrata genome has one homolog (Sky1) of the human SR protein kinase 1, but their functions have not yet been investigated. We used deletion strains of the corresponding genes in both fungi to study their cellular functions. C. glabrata and C. albicans strains lacking SKY1 exhibited higher resistance to osmotic stress and toxic polyamine concentrations, similar to Saccharomyces cerevisiae sky1Δ mutants. Deletion of SKY2 in C. albicans resulted in impaired utilization of various dipeptides as the sole nitrogen source. Subsequent phosphoproteomic analysis identified the di- and tripeptide transporter Ptr22 as a potential Sky2 substrate. Sky2 seems to be involved in Ptr22 regulation since overexpression of PTR22 in the sky2Δ mutant restored the ability to grow on dipeptides and made the cells more susceptible to the dipeptide antifungals Polyoxin D and Nikkomycin Z. Altogether, our results demonstrate that C. albicans and C. glabrata Sky1 protein kinases are functionally similar to Sky1 in S. cerevisiae, whereas C. albicans Sky2, a unique kinase of the CTG clade, likely regulates dipeptide uptake via Ptr22.

Lactobacillus rhamnosus colonisation antagonizes Candida albicans by forcing metabolic adaptations that compromise pathogenicity.

Intestinal microbiota dysbiosis can initiate overgrowth of commensal Candida species - a major predisposing factor for disseminated candidiasis. Commensal bacteria such as Lactobacillus rhamnosus can antagonize Candida albicans pathogenicity. Here, we investigate the interplay between C. albicans, L. rhamnosus, and intestinal epithelial cells by integrating transcriptional and metabolic profiling, and reverse genetics. Untargeted metabolomics and in silico modelling indicate that intestinal epithelial cells foster bacterial growth metabolically, leading to bacterial production of antivirulence compounds. In addition, bacterial growth modifies the metabolic environment, including removal of C. albicans' favoured nutrient sources. This is accompanied by transcriptional and metabolic changes in C. albicans, including altered expression of virulence-related genes. Our results indicate that intestinal colonization with bacteria can antagonize C. albicans by reshaping the metabolic environment, forcing metabolic adaptations that reduce fungal pathogenicity.

Molecular Profiling Reveals Characteristic and Decisive Signatures in Patients after Allogeneic Stem Cell Transplantation Suffering from Invasive Pulmonary Aspergillosis.

Despite available diagnostic tests and recent advances, diagnosis of pulmonary invasive aspergillosis (IPA) remains challenging. We performed a longitudinal case-control pilot study to identify host-specific, novel, and immune-relevant molecular candidates indicating IPA in patients post allogeneic stem cell transplantation (alloSCT). Supported by differential gene expression analysis of six relevant in vitro studies, we conducted RNA sequencing of three alloSCT patients categorized as probable IPA cases and their matched controls without Aspergillus infection (66 samples in total). We additionally performed immunoassay analysis for all patient samples to gain a multi-omics perspective. Profiling analysis suggested LGALS2, MMP1, IL-8, and caspase-3 as potential host molecular candidates indicating IPA in investigated alloSCT patients. MMP1, IL-8, and caspase-3 were evaluated further in alloSCT patients for their potential to differentiate possible IPA cases and patients suffering from COVID-19-associated pulmonary aspergillosis (CAPA) and appropriate control patients. Possible IPA cases showed differences in IL-8 and caspase-3 serum levels compared with matched controls. Furthermore, we observed significant differences in IL-8 and caspase-3 levels among CAPA patients compared with control patients. With our conceptual work, we demonstrate the potential value of considering the human immune response during Aspergillus infection to identify immune-relevant molecular candidates indicating IPA in alloSCT patients. These human host candidates together with already established fungal biomarkers might improve the accuracy of IPA diagnostic tools.