Biology subjects

Schuster, S.

Publications and source records attributed to Schuster, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Dysregulation of epithelial differentiation architecture underlies field cancerization in head and neck cancer

Head and neck squamous cell carcinoma (HNSCC) has exceptionally high recurrence rates, exceeding 50%, contributing to mortality and morbidity. This recurrence rate is proposed to be due to field cancerization, a phenomenon where tumor-adjacent "field" tissue that appears histologically normal harbors molecular changes that prime it for subsequent tumor growth. Current models attribute field cancerization to shared driver mutations between tumors and adjacent at-risk tissue, but this assumption has never been directly tested. To comprehensively characterize this phenomenon, we profiled patient-matched tumor, normal-adjacent field (NAF), contralateral normal, and blood samples from HPV-negative HNSCC patients using whole genome sequencing, targeted driver gene sequencing, single-nucleus multiome profiling, spatial transcriptomics and functional proliferation assays. While histologically normal NAF tissues did harbor expanded mutant clones, these mutations rarely overlapped with paired tumors and were not shared across patients, suggesting molecular features beyond mutations are altered in NAF. Single-cell multiomics revealed that NAF epithelium loses its normal organizational hierarchy: basal stem cell markers persist in differentiated cells, while terminal differentiation programs fail to activate, with reconfiguration of both gene regulatory networks and cell-cell interactions. Proliferating cells appeared in tissue layers normally restricted to post-mitotic cells, a pattern typically seen only in overt dysplasia. Within this disrupted hierarchy, a distinct epithelial state arose in NAF that expressed both normal epithelial and tumor-associated markers, which we localized to the parabasal layers using immunofluorescence and spatial transcriptomics. Together, our findings demonstrate that field cancerization operates through epithelial hierarchy disorganization that disrupts differentiation, generates cells with tumor-like features, and may create a permissive environment for the expansion of cancer-associated mutations, all within tissue that appears histologically normal.

cancer biology↗

bioRxiv2026

Strong correlation between amino acid frequency and codon degeneracy in genetic codes across all domains of life

Since the discovery of the genetic code, a frequently discussed question is whether the numbers of synonymous codons for the various amino acids are randomly distributed or were shaped by evolutionary constraints. In this study, we analyze for the standard as well as alternative genetic codes, the correlations between codon degeneracy and amino acid frequencies in proteins (neglecting differences in gene expression). To taking into account the effect of GC content, expected codon frequencies rather than codon multiplicity need to be considered. A strong correlation of these frequencies with amino acid abundance is revealed. Furthermore, we identify consistent patterns of over- and underrepresentation of amino acids across domains of cellular life as well as viruses. For example, the codons for glutamate, aspartate, lysine, and methionine are consistently overrepresented across domains, while cysteine, arginine, histidine, and proline are underrepresented. Subsequently, we discuss the role of biosynthesis costs of amino acids and other factors such as the order of amino acid recruitment in early evolution, exposure to oxidative stress, and sulphur availability. We hypothesize that in a first phase of evolution, the genetic code evolved in a way so as to comply with the different demands for amino acids. In a second phase, after the code was frozen, changes in demand led to deviations from the strong correlation between codon multiplicity and amino acid frequency by natural selection. This comprehensive analysis offers new insights into the interplay between genetic code structure and amino acid usage across all domains of life.

genomics↗

bioRxiv2026

Systematic De-Risking of TCR-Mimic Therapeutics Through Proteome-Wide Off-Target Landscaping and a Generalizable Design Rule Framework

TCR-mimic (TCRm) antibodies targeting peptide-human leukocyte antigen (pHLA) complexes enable precision immunotherapy against intracellular antigens, including cancer-testis antigens (CTAs). Achieving high specificity, however, remains challenging because of the vast diversity of the human immunopeptidome and the associated risk of off-target recognition. Here, we introduce ValidaTe, a unified framework for the proteome-scale prediction, validation, and mitigation of off-target liabilities in pHLA-directed therapeutics. ValidaTe integrates rational target prioritization, peptide-centric binder selection, proteome-wide off-target prediction, and therapeutic engineering into a hierarchical de-risking workflow. Using the CTA MAGE-A4 as a proof-of-concept, we identify the TCRm antibodies VR-4 and VR-6 with superior specificity and demonstrate how this workflow enables the discovery of safer pHLA-targeted binders. Furthermore, ValidaTe establishes the basis for the WiFi (Widened Fingerprint) engineering principle, which rationally combines TCRms with complementary off-target fingerprints in trivalent T-cell engagers to minimize unintended interactions while preserving potent target-specific activity. Together, these findings establish a generalizable framework for the rational development of safer and more selective pHLA-targeted therapeutics. We further discuss how orthogonal proteomic characterization may complement this workflow as a final layer of translational safety assessment prior to clinical development. TeaserValidaTe accelerates safe pHLA-targeted immunotherapy through proteome-wide off-target mapping and WiFi design

immunology↗

bioRxiv2026

Deep learning representations of human Immune Health for precision immunology

The human immune system is composed of [~]30-50 distinct cell types, each of which can exist in different states of activation or differentiation. Indeed, the mammalian immune system has evolved to sense and respond to infections, cancers, injuries, and changes in tissue or host homeostasis (1). Moreover, an increasingly large fraction of approved drugs target the immune system directly, and/or cause immune changes (2-4). A key feature of the immune system is to store some of this information, for example as innate or adaptive immune memory (5). In addition, rewiring of immune network architecture induced by disease, environmental exposures, drug treatments, and/or chronological age allows the immune system to store information in the pattern of connections and activity across populations of immune cells. This ensemble information storage, in addition to changes to individual cells, functions as a major way the immune system encodes aspects of immune history and future potential. Genetic information can identify inherited risk alleles, but cannot capture the continual remodeling of the immune system shaped by exposures, infection, inflammation, therapy, and aging (6, 7). To define and use such ensemble immunotypes, we developed a self-supervised deep learning framework that transforms high-dimensional immune profiles into representations of immune health. MAESTRO (MAsked Encoding Set TRansformer with self-distillatiOn) encodes a set of cells from an individual into an embedding that captures immune cell population-level organization. Pretrained on 1,792 peripheral blood samples comprising over 418 million immune cells across 13 clinical diagnoses, MAESTRO learns immune fingerprints that are stable within individuals yet diverse across populations, states of health, disease, and treatment, providing a quantitative basis for comparing immune states across individuals and over time. These fingerprints capture immune architecture beyond coarse cell type proportions, enabling patient-efficient clinical prediction using simple task specific models. MAESTRO model embeddings retain a temporal dimension of immune history and potential, reflecting signatures of past exposures and baseline features that predict future immune responses. Finally, we demonstrate a translational precision immunotherapy application by testing this approach in metastatic Pancreatic Ductal Adenocarcinoma (PDAC), where pretreatment immune landscape circuitry maps enable patient stratification and therapeutic response prediction. Overall, we developed a large, attention-based model that captures deep network architecture of immune states through self- supervised representations of immune cytometry data as a reusable foundation for precision immunology, converting immune complexity into clinically actionable embeddings for diagnosis, monitoring, and therapy selection.

immunology↗

bioRxiv2026

Cooperation, privatization and cheating in microbial exoenzyme synthesis: theoretical analysis in view of biotechnological applications

This study presents a mathematical framework for investigating the dynamics of coexistence and competition among heterotrophic microbes across different time scales. Focusing on metabolic interactions, we examine how three strategies: public metabolizing, private metabolizing, and cheating, shape population behaviour. The framework integrates generalized Lotka-Volterra dynamics with evolutionary game theory to capture the effects of resource exchange, particularly glucose made available by public metabolizers and sucrose as a shared substrate driving population growth. Game-theoretic payoffs encode ecological costs and benefits, enabling analysis of frequency-dependent interactions among strategies. To capture evolutionary realism, we implement laboratory-inspired simulations in which strategies can switch between generations, mimicking mutation or phenotypic plasticity in microbial populations. These eco-evolutionary dynamics reveal conditions under which all three strategies coexist at interior equilibria and show how variation in growth advantages and, illustratively, phenotype-switching perturbations produce evolutionary shifts. Numerical analysis identifies ecological thresholds and fitness asymmetries that determine system robustness, long-term coexistence, and the persistence of a synthetic, cross-kingdom system linked by nutrient exchange. Together, these insights provide general principles for microbial coexistence and offer design guidelines for ecosystem engineering, biotechnological applications, and the construction of stable synthetic communities under ecological and evolutionary constraints.

ecology↗

bioRxiv2026

Analyzing the dynamics in defense/counter-defense games among hosts and pathogens

In the dynamic interplay between hosts and pathogens, hosts may produce a defense compound that acts as a toxin to deter pathogen attack. Conversely, pathogens may evolve to produce a counter-defense enzyme, neutralizing the hosts toxin. This evolutionary arms race incurs costs for both parties, prompting adaptations and strategic shifts. We conceptualize this interaction as an asymmetric game, with hosts and pathogens as players, and their potential responses - defense, counter-defense, or inaction - as their strategic options. In this scenario, if the pathogens counter-defense enzyme is entirely effective, then the hosts toxin is rendered obsolete. However, should the host cease toxin production, the pathogens enzyme becomes redundant, ironically reinstating the toxins utility. This interaction leads to potential red-queen cycles in defense and counter-defense strategies under certain conditions, or a balanced, optimal production of toxin and enzymes by hosts and parasites, respectively. To explore this, we introduce a game-theoretical model incorporating replicator dynamics to examine temporal shifts in strategy from active (counter-)defense to non-(counter-)defense and back. In addition, we analyze compromise strategies and interpret them as bet-hedging-like. We provide a deterministic illustration of how partial defense and counter-defense generate a fitness-buffering structure in unpredictable environments and increase the geometric mean fitness of the population. In conclusion, our analysis supports the notion of continuous periodic adjustments in strategies, notably in the levels of defensive and counter-defensive measures.

systems biology↗

bioRxiv2025

EpiTox: A Multi-Modular Framework for Population-Aware Off-Target Prediction Highlighting MAGE-A3 Cross-Reactivity

Targeting intracellular tumor antigens presented by peptide human leukocyte antigen (pHLA) complexes offers a promising immunotherapeutic strategy for patients with limited treatment options. However, development of pHLA-targeted drugs such as T-cell receptor (TCR) mimic antibodies (TCRm) and TCR-based therapeutics remains challenging due to severe offtumor and off-target toxicities arising from incomplete pHLA off-target profiling. The fatal neurological toxicities observed in the MAGEA3 TCR-T cell trial, potentially linked to unanticipated cross-reactivity with EPS8L2- and MAGEA12-derived peptides, underscore the urgent need for more comprehensive safety assessment. While current preclinical de-risking methods utilize sequence similarity searches, they lack the layered integration of genetic context, HLA binding profiles, and structured risk assessment needed to comprehensively evaluate peptide cross-reactivity. To address these limitations, we developed EpiTox, a computational multi-modular platform that systematically identifies and evaluates pHLA off-targets. EpiTox integrates proteome-wide sequence similarity, genetic context, HLA binding profiles, and layered risk assessment to provide a holistic evaluation of potential cross-reactive peptides. Using MAGEA3 as a model, EpiTox identified known toxic off-targets and predicted novel epitopes. Notably, an anti-MAGEA3 therapeutic TCRm antibody bound several newly predicted off-targets, including three SNP-derived peptides. By enabling comprehensive and predictive preclinical safety screening, Epi-Tox supports safer TCRm drug development and may help prevent future clinical failures.

bioinformatics↗

bioRxiv2025

Beyond Sequence Similarity: ML-Powered Identification of pHLA Off-Targets for TCR-Mimic Antibodies Using High Throughput Binding Kinetics

T-cell receptor mimic (TCRm) antibodies are an emerging class of tumor-targeting agents used in advanced immunother-apies such as bispecific T-cell engagers and CAR-T cells. Unlike conventional antibodies, TCRms are designed to recognize peptide-human leukocyte antigen (pHLA) complexes that present intracellular tumor-derived peptides on the cell surface. Due to the typically low surface abundance and high sequence similarity of pHLAs, TCRms require high affinity and exceptional specificity to avoid off-target toxicity. Conventional methods for off-target identification such as sequence similarity searches, motif-based screening, and structural modelling focus on the peptide and are limited in detecting cross-reactive peptides with little or no sequence homology to the target. To address this gap, we developed EpiPredict, a TCRm-specific machine learning framework trained on high-throughput kinetic off-target screening data. EpiPredict learns an antibody-specific mapping from peptide sequence to binding strength, enabling prediction of interactions with unmeasured pHLA sequences, including sequence-dissimilar peptides. We applied EpiPredict to two distinct TCRms targeting the cancer-testis antigen MAGE-A4. The model successfully predicted multiple off-targets with minimal sequence similarity to the intended epitope, many of which were experimentally validated via T2 cell binding assays. These findings establish EpiPredict as a valuable tool for lead optimization of TCRms, enabling the identification of antibody-specific off-targets beyond the scope of traditional peptide-centric methods and supporting the preclinical de-risking of TCRm-based therapies.

immunology↗

bioRxiv2025

Branched-chain amino acid assimilation promotes mixotrophy of ammonia-oxidizing archaeal sponge symbionts

Ammonia-oxidizing archaea (AOA) frequently form symbiotic associations with marine sponges. While free-living AOA are generally considered metabolically constrained chemolithoautotrophs, sponge-associated AOA encode for a branched-chain amino acid (BCAA) transporter, suggesting mixotrophic potential. Here, we test the unusual mixotrophic lifestyle of sponge-associated AOA by tracing the assimilation of 13C- and 15N-labeled BCAA in the sponge holobiont Ianthella basta. We demonstrate that BCAA degradation fuels ammonia oxidation and quantify BCAA uptake at the single-cell level by combining stable isotope probing, catalyzed reporter deposition fluorescence in situ hybridization, and nanoscale secondary ion mass spectrometry. Our results reveal that sponge-associated AOA are mixotrophic, assimilating BCAA as an additional carbon and nitrogen source. This metabolic adaptation may modulate BCAA availability in the holobiont, potentially regulating the hosts mTOR pathway. Collectively, our study reveals a novel nutritional interaction in sponge holobionts and challenges the perception of constrained metabolic capacities of AOA.

microbiology↗

bioRxiv2025

Disrupted α-ketoglutarate homeostasis trains monocyte-derived macrophages towards M2-like phenotype in long-term treated HIV-infection

Cells of the myeloid lineage, particularly monocytes and macrophages, are central to HIV pathogenesis, contributing to viral persistence and immune regulation during suppressive therapy. We hypothesized that metabolic reprogramming and altered chemokine signaling in people with HIV (PWH) on long-term ART impair monocyte trafficking and macrophage polarization. Using single-cell RNA sequencing, immunophenotyping, and metabolic modeling, we identified altered receptor expression and disrupted metabolic flux linked to reduced monocyte migration. Plasma secretome profiling revealed a nonclassical inflammatory microenvironment, while integrative multi-omics and single-cell proteomics of monocyte-derived macrophages (MDMs) demonstrated metabolic rewiring of the Glycolysis-TCA Anaplerosis Axis, orchestrated in part by elevated -ketoglutarate (AKG). Differentiation with PWH serum or AKG, skewed MDMs toward an M2-like phenotype, and enhanced HIV susceptibility. Together, these systems-level and mechanistic analyses reveal that metabolic training drives macrophage dysfunction in well-treated PWH, sustaining low-grade inflammation and highlighting potential therapeutic targets.

systems biology↗

bioRxiv2024

Learning and cognition in a decision made at reflex speed

It is widely accepted that more time and information yield better decisions. However, some decisions manage to combine speed and accuracy in an unusual way. Potentially their trick could be to use simplifying heuristics that works well for the most common condition but would lack flexibility otherwise. Here we describe an unexpected level of flexibility in a complex highspeed decision that is made faster than an Olympic sprinter can respond to the start gun. In this decision, archerfish observe the initial speed, direction, and height of falling prey and then use these initial values to turn right towards were ballistically falling prey would later land. To analyze the limits in flexibility of this highspeed decision we first developed and critically tested a system that allowed us to replace the usual ballistic relation between initial prey motion and the expected landing point with another deterministic rule. We discovered that, surprisingly, adult fish could reprogram their highspeed decision to the new rule. Moreover, after reprogramming their decision fish were immediately able to generalize their decision to novel untrained settings, showing a remarkable degree of abstraction in how the decision circuit represented the novel rule. The decision circuit is even capable of simultaneously using two distinct sets of rules, one for each of two visually distinct objects. The flexibility and level of cognition are unexpected for a decision that lacks a speed-accuracy tradeoff and is made in less than 100 ms. Our findings demonstrate the enormous potential highspeed decision making can have and strongly suggest that we presently underappreciate this form of decision making.

animal behavior and cognition↗

bioRxiv2024

Directed evolution-based discovery of ligands for in vivo restimulation of CAR-T cells

Chimeric antigen receptor (CAR) T cell therapy targeting CD19 elicits remarkable clinical efficacy in B-cell malignancies, but many patients relapse due to failed expansion and/or progressive loss of CAR-T cells. We recently reported a strategy to potently restimulate CAR-T cells in vivo, enhancing their functionality by administration of a vaccine-like stimulus comprised of surrogate peptide ligands for a CAR linked to a lymph node-targeting amphiphilic PEG-lipid (termed CAR-T-vax). Here, we demonstrate a general strategy to generate and optimize peptide mimotopes enabling CAR-T-vax generation for any CAR. Using the clinical CD19 CAR (FMC63) as a test case, we employed yeast surface display to identify peptide binders to soluble IgG versions of FMC63, which were subsequently affinity matured by directed evolution. CAR-T vaccines using these optimized mimotopes triggered marked expansion and memory development of CD19 CAR-T cells in both syngeneic and humanized mouse models of B-ALL/Lymphoma, and enhanced control of disease progression. This approach thus enables vaccine boosting to be applied to any clinically relevant CAR-T cell product.

bioengineering↗

bioRxiv2023

The histone modifier KAT2A presents a selective target in a subset of well-differentiated microsatellite-stable colorectal cancers

BackgroundLysine acetyltransferase 2A (KAT2A) plays a pivotal role in epigenetic gene regulation across various types of cancer. In colorectal cancer (CRC), upregulation of KAT2A is associated with a more aggressive phenotype. Our study aims to elucidate the molecular underpinnings of KAT2A dependency in CRC and assess the consequences of KAT2A depletion. MethodsWe conducted a comprehensive analysis by integrating CRISPR-Cas9 screening data with genomics, transcriptomics, and global acetylation patterns in CRC cell lines to pinpoint molecular markers indicative of KAT2A dependency. Additionally, we characterized the phenotypic effect of a CRISPR-Cas9-mediated KAT2A knockout and chemical inhibition of KAT2A in CRC cell lines and patient- derived 3D spheroid cultures. ResultsOur findings reveal that KAT2A dependency is closely associated with a lower mutational burden and increased differentiation grade in CRC cell lines, independent of the KAT2A expression levels. KAT2A dependent CRC cell lines display enriched H3K27ac marks at gene loci linked to enterocytic differentiation. Loss of KAT2A leads to decreased cell growth and viability, downregulation of proliferation- and stem cell-associated genes, and induction of differentiation markers. ConclusionA specific subset of CRCs with a more differentiated phenotype relies on KAT2A. For these CRC cases, KAT2A might represent a promising novel therapeutic target.

cancer biology↗

bioRxiv2023

Evaluating interchain hydrogen bonds between collagens- A multiple alignment approach

Collagens are structural proteins that are predominantly found in the extracellular matrix of multicellular animals, where they are mainly responsible for the stability and structural integrity of various tissues. All collagens contain polypeptide strands ([a]-chains). There are several types of collagens, some of which differ significantly in form, function, and tissue specificity. Because of their importance in clinical research, they are grouped into subdivisions, the so-called collagen families, and their sequences are often analysed. However, problems arise with highly homologous sequence segments. To increase the accuracy of collagen classification and prediction of their functions, the structure of these collagens and their expression in different tissues could result in a better focus on sequence segments of interest. Here, we analyse collagen families with different levels of conservation. As a result, clusters with high interconnectivity can be found, such as the fibrillar collagens, the COL4 network-forming collagens, and the COL9 FACITs. Furthermore, a large cluster between network-forming, FACIT, and COL28a1 [a]-chains is formed with COL6a3 as a major hub node. The formation of clusters also signifies, why it is important to always analyse the [a]-chains and why structural changes can have a wide range of effects on the body.

systems biology↗

bioRxiv2022

CWLP and PRP940 form plasma-membrane nanodomain complexes with aquaporins, interact with PP2A and contribute to dehydration tolerance

The C-type hybrid-proline-rich protein (HyPRP) AtCWLP and its homolog AtPRP940 are referred as cell wall (CW)-plasma-membrane (PM) linker proteins, but little is known about their functions. Here we show that N-terminal proline-rich domains of CWLP and PRP940, containing glycosylated hydroxyproline residues, contact the CW, while their C-terminal 8CM domains function as PM-scaffolds. Both proteins are detected in PM nanodomains (PM-ND) and show co-localization and co-immunoprecipitation with aquaporins PIP2;1 and PIP2;7. Inhibition of actin polymerization by latrunculin B promotes CWLP-endosome appearance, while blocking the actomyosin-based transport by a truncated form of myosin XI-K relaxes lateral boundaries of CWLP-PIP2;1 PD-NDs. Mass spectrometry data indicate that CWLP co-purifies with dynamins implicated in fission of endocytic PD-ND invaginations. Lack of co-localization and co-immunoprecipitation with aquaporin-binding flotillin (FLOT2) indicates that CWLP and PRP940 mark a new distinct type of PM-ND. Yeast two-hybrid and co-immunoprecipitation assays demonstrate that CWLP and PRP940 interact with multiple aquaporins and several protein phosphatase PP2A-B regulatory subunits. By preventing irreversible separation of CW and PM, and likely assisting PP2A-mediated dephosphorylation of aquaporins and closure of their water channels, overexpression of CWLP confers tolerance to plasmolysis, dehydration and freezing in Arabidopsis and to water shortage in potato plants. Summary StatementArabidopsis Hybrid-Proline-Rich Proteins CWLP and PRP940 occur in association with dynamins, recruit PP2A protein phosphatases to aquaporin water channels in plasma-membrane (PM) nanodomains and elevate tolerance to cellular dehydration.

plant biology↗

bioRxiv2021

Connexins evolved after early chordates lost innexin diversity

Gap junction channels are formed by two unrelated protein families. Non-chordates use the primordial innexins, while chordates use connexins that superseded the gap junction function of innexins. Chordates retained innexin-homologs, but N-glycosylation prevents them from forming gap junctions. It is puzzling why chordates seem to exclusively use the new gap junction protein and why no chordates should exist that use non-glycosylated innexins to form gap junctions. Here, we identified glycosylation sites of 2270 innexins from 152 non-chordate and 274 chordate species. Among all chordates, we found not a single innexin without glycosylation sites. Surprisingly, the glycosylation motif is also widespread among non-chordate innexins indicating that glycosylated innexins are not a novelty of chordates. In addition, we discovered a loss of innexin diversity during the early chordate evolution. Most importantly, the most basal living chordates, which lack connexins, exclusively possess innexins with glycosylation sites. A bottleneck effect might thus explain why connexins have become the only protein used to form chordate gap junctions.

evolutionary biology↗

bioRxiv2021

The landscape of toxic intermediates in the metabolic networks of pathogenic fungi reveals targets for antifungal drugs

The burden of fungal infections for humans, animals and plants is widely underestimated and comprises deadly infections as well as great economic costs. Despite that, antifungal drugs are scarce and emergence of resistance in fungal strains contributes to a high mortality. To overcome this shortage, we propose toxic intermediates and their controlling enzymes in metabolic pathways as a resource for new targets and provide a web-service, FunTox-Networks to explore the landscape of toxic intermediates in the metabolic networks of fungal pathogens. The toxicity of metabolites is predicted by a new random forest regression model and is available for over one hundred fungal species. Further, for major fungal pathogens, metabolic networks from the KEGG database were enriched with data of toxicity and regulatory effort for each enzyme to support identification of targets. We determined several toxic intermediates in fungal-specific pathways like amino acid synthesis, nitrogen and sulfur assimilation, and the glyoxylate bypass. For the latter, we show experimentally that growth of the pathogen Candida albicans is inhibited when the detoxifying enzymes Mls1 and Hbr2 are deleted and toxic glyoxylate accumulates in the cell. Thus, toxic pathway intermediates and their controlling enzymes represent an untapped resource of antifungal targets.

systems biology↗

bioRxiv2021

Dynamic optimization reveals alveolar epithelial cells as key mediators of host defense in invasive aspergillosis

Aspergillus fumigatus is an important human fungal pathogen and its conidia are constantly inhaled by humans. In immunocompromised individuals, conidia can grow out as hyphae that damage lung epithelium. The resulting invasive aspergillosis is associated with devastating mortality rates. Since infection is a race between the innate immune system and the outgrowth of A. fumigatus conidia, we use dynamic optimization to obtain insight into the recruitment and depletion of alveolar macrophages and neutrophils. Using this model, we obtain key insights into major determinants of infection outcome on host and pathogen side. On the pathogen side, we predict in silico and confirm in vitro that germination speed is a key virulence trait of fungal pathogens due to the vulnerability of conidia against host defense. On the host side, we find that epithelial cells play a so far underappreciated role in fungal clearance and are potent mediators of cytokine release which we confirm ex vivo. Further, our model affirms the importance of neutrophils in invasive aspergillosis and underlines that the role of macrophages remains elusive. We expect that our model will contribute to improvement of treatment protocols by focusing on the critical components of immune response to fungi but also fungal virulence.

systems biology↗