- by Edirisinghe, J. N., Lerma Ortiz, C., Liu, F., Faria, J. P., Cottingham, R. W., Arkin, A. P., Liu, Q., Henry, C. S.Over a thousand fungal genomes have been sequenced, yet manually curated genome scale metabolic models (GSMs) are available for only a limited number of species. Moreover, these models have often been developed independently, leading to inconsistencies in namespaces, compartment definitions, and pathway representations that hinder comparative analysis, the systematic reuse of prior curation efforts, and the integration of consolidated metabolic knowledge. Here, we present the Consolidated Fungal Core Metabolism Model (CFCMM), constructed by integrating thirteen published fungal models spanning Ascomycota, […]
- by Farinas, M., Bermudez, V., Tsirvouli, E., Zobolas, J., Aittokallio, T., Lehti, K., Flobak, A., Lippestad, K.Effective drug combination therapies can improve cancer treatment, yet the mechanistic basis of drug synergy remains poorly understood. Most computational approaches prioritize predictive accuracy over molecular mechanistic interpretability, providing hence limited insights into how synergistic effects emerge across signalling contexts. We developed Trafikk, a molecular-signalling network-based framework that simulates drug perturbations in cell line-specific computational models to mirror functional outcomes in experimental combination screens. Across two independent large-scale datasets, Trafikk identified synergistic combinations with >77% recall. Functional response predictions revealed […]
- by Monarez, I. D., Kim, E. N., Moon, K., Baker, A.-M., Chen, P. Z., Bressan, D., Miremadi, A., di Pietro, M., Hannon, G. J., Graham, T. A., Fizgerald, R. C., Chang, Y. H., Zhuang, L.Barrett's esophagus (BE) is the precursor lesion of esophageal adenocarcinoma (EAC). It affects approximately 5% of adults in the United States and significantly increases the risk of developing EAC. However, current surveillance strategies cannot reliably distinguish patients who will progress from those who will remain stable. Direct studies of progressor BE are extremely limited due to availability of tissue with known progression outcomes, and have largely been restricted to genomic profiling approaches. The premalignant cellular landscape of progressor BE remains […]
- by Gallo, H., Bucci, V.Forecasting how microbiome-host ecosystems evolve through time simultaneously at the compositional and functional level remains a central challenge in biology. While dynamical systems models (DSMs) can infer and predict community composition from longitudinal abundance data, and constraint-based metabolic models (CBMMs) can estimate metabolic fluxes from genome-scale reconstructions, no existing framework unifies these approaches to generate mechanistically grounded, time-resolved forecasts of both microbial abundances and metabolite dynamics from ecological data alone. Here, we introduce the Dynamical Systems Constrained Metabolic Modeling (DySCoMeMo) […]
- by Maxian, O., Munro, E., Dinner, A.A key question in cell biology is how cell-scale organization emerges from a given set of molecular players and rules of interaction. Given its multiscale nature, addressing this question requires a combination of experimental perturbation, mathematical modeling, and parameter inference. We leverage recent advances in each of these fields, focusing in particular on neural-network methods for simulation-based inference, to study how cell-scale patterns of Rho GTPase activity are defined by molecular-scale activator-inhibitor interactions with filamentous actin. We show that variations […]
- by Kazemeini, A., Prieto, J., Balaji Kuttae, S., Siokis, A., Singh, G., Passban, P., Andreani, T.Quantitative Systems Pharmacology (QSP) models play an inherently interventional role in pharmaceutical research and development, functioning as executable causal systems for designing, evaluating, and replacing clinical trials. However, deploying QSP as an experimental planning engine remains constrained by the difficulty of translating unstructured literature descriptions of clinical or preclinical scenarios into reproducible, simulation-ready model interventions. Motivated by this issue, we propose an agent-based framework that operationalizes QSP models as intervention-ready experimental systems by automatically extracting and executing literature-derived scenarios. The […]
- by de Baat, A., Levin, M.Metabolic networks are typically viewed as homeostatic systems that stabilize flux, energy charge, redox balance, and metabolite availability under perturbation. However, it remains unclear whether the same feedback architectures that support metabolic robustness can also generate learning-like, experience-dependent adaptation. Here, we develop a coarse-grained dynamical model of mammalian energy metabolism to test whether prior perturbation can improve future metabolic responses. The model represents core glucose, glutamine, fatty acid, and oxidative phosphorylation pathways as coupled ordinary differential equations with Michaelis-Menten-type fluxes, […]
- by Peluso, M., Tackmann, J., von Mering, C.Motivation: Accurately modelling how microbial communities assemble and change across hosts and environments is essential for analysis and intervention. Typical pipelines capture limited generalisable structure and often depend on fixed ecological unit definitions. Results: We present Susagi (Set Unsupervised Assessment of Genetic Imposters), a permutation-invariant denoising transformer that operates directly on sets of bacterial SSU rRNA gene embeddings to learn a member-level stability function. The model was trained on 2 x 10^6 bacterial community samples. We show that it reliably […]
- by Ikuta, D., Tamaki, R., Wada, S., Onishi, K., Nishikawa, M., Sakai, Y., Katsuda, T.Hepatocyte transplantation is a promising alternative to liver transplantation; however, it currently serves only as a temporary treatment until a donor organ becomes available. In contrast, animal studies have demonstrated "liver repopulation", a phenomenon in which transplanted hepatocytes progressively replace host hepatocytes. Despite extensive documentation, the mechanisms driving this process remain poorly understood. More fundamentally, it remains unclear whether liver repopulation is driven by active cell-cell interactions between host and transplanted hepatocytes that induce host cell death, or whether it […]
- by Scott, W. T., Puentes Jacome, L. A., Nijsse, B., Wang, J., Stouten, G. R., Koehorst, J. J., Smidt, H., Edwards, E. A., Schaap, P. J., Kleerebezem, R.Organohalide-respiring bacteria (OHRB), such as Dehalobacter, play key roles in the bioremediation of anoxic environments contaminated with chlorinated aromatic compounds. These obligate anaerobes rely on syntrophic interactions to obtain essential resources–hydrogen, acetate, and corrinoid cofactors–from acetogens and fermenters. However, the metabolic interactions enabling complete reductive dehalogenation of compounds like 1,2,4-trichlorobenzene (1,2,4-TCB) to benzene remain incompletely understood. In this study, we asked: (1) What are the key microbial taxa and their functional roles within a Dehalobacter-containing anaerobic microbial community detoxifying chlorinated […]
- by Stein, G., Mueller, P., Vallet, M., Cirri, E., Lange, L., Heller, E. A., Winter, J., Graeler, M. H., Ueberschaar, N., Maurer, A., Dobrowolny, H., Meyer-Lotz, G., Steiner, J., Engmann, O.Chronic stress is widely studied as a brain-centered driver of depression, yet its effects across the body remain unclear. Here, we define chronic stress as a coordinated molecular state across tissues in mice. Using a whole-body proteomic atlas of 13 tissues, we find that stress effects are strongest in peripheral metabolic and endocrine organs, whereas classical stress-associated brain regions show comparatively modest changes. Cross-organ analyses reveal structured, tissue-specific responses rather than uniform shifts. Inhibition of the stress-regulated receptor NPBWR1 reverses […]
- by Devlin, L., Oudard, V., Barthe, M., Gosselin-Monplaisir, T., Dupin, J.-B., Condamine, F., Baudry, J., Cocaign-Bousquet, M., Millard, P., Enjalbert, B.The long-held view that acetate, one of the main fermentation by-products of Escherichia coli, is toxic to microbial growth is currently challenged. Here, we demonstrate that acetate promotes E. coli adaptation to nutrient changes by accelerating growth resumption, with as little as 250 {micro}M acetate being sufficient to shorten the lag phase by several hours. Acetate was found to be consumed via acetyl-CoA synthetase very early after the nutrient change. Transcriptomics, metabolomics and 13C-isotope labeling experiments show that acetate replenishes […]
- by Schaffranke, A., Kueken, A., Nikoloski, Z.SummaryRecent advances in analysis of biochemical networks have contributed the identification of their modular structure based on the concept of multi reaction dependencies and kinetic coupling of reaction rates (Kuken et al., 2022; Langary et al., 2025). Existing implementations of the algorithms to study modular structure do not scale well with the size of the networks, prohibiting their application with genome-scale networks. Here, we introduce COCOA.jl, a multithreaded Julia package for identification of concordant and kinetic modules, with applications in […]
- by Wieland, V., Blum, T., Iriady, I., Reverte-Salisa, L., Pathirana, D., Foerster, I., Weighardt, H., Hasenauer, J.The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor involved in xenobiotic sensing, as well as development, immunity, and tissue homeostasis. AhR signaling can proceed through a canonical and non-canonical pathway; the present study focuses on the canonical pathway. While ligand-dependent differences in binding affinities and direct ligand degradation kinetics are well known, and subtle differences in ligand binding can shape downstream signaling, it is still unclear which biochemical reaction steps within the canonical pathway are responsible for distinct […]
- by Odendaal, C., Krebs, O., Bakker, B. M.The mitochondrial fatty acid {beta}-oxidation (mFAO) is an important source of energy when carbohydrate stores are depleted. It is also involved in many diseases, including inherited fatty-acid oxidation deficiencies (mFAODs). Patients with the same genetic variant often present with clinically heterogeneous phenotypes, but the mechanisms contributing to this heterogeneity are poorly understood. To investigate the underlying pathophysiology of different mFAODs, we constructed a computational model of mFAO in human liver, based on experimentally determined enzyme kinetics. A recognised, but seldom […]
- by Andriot, I., Grossiord, D., Beno, N., Chabin, T., Laboure, H., Lucchi, G., Martin, C., Mourabit, O., Piornos, J. A., Saint-Georges, L., Salles, C., Trelea, I. C., Peltier, C.Aroma perception during food consumption results from the combined effects of food composition, oral processing (such as chewing and saliva action), the release and transport of volatile compounds toward the olfactory epithelium, followed by cognitive integration in the brain. Recent advances in real-time analytical techniques, particularly Proton Transfer Reaction-Time-of-Flight Mass Spectrometry (PTR-ToF-MS), enable in vivo monitoring of aroma release with high temporal resolution and have become widely used for analyzing the composition of exhaled air. However, the interpretation of aroma […]
- by Khurana, T. K., Wu, L. Y., Gherardini, P. F., Moeinzadeh, S., Mohseni, M., Yasar, F. G., Dettloff, R., Poelma, J., Sabri, S., Scaramozza, A., Li, Y., Rouzbeh, N., Elder, N., Deshmukh, S., Majd, A., Gupta, R., Farahvashi, S., Thomas, I., Betts, C., Charbonier, F., Roberts, D., Hsiung, P.-L., Zargari-Pariset, E., Yau, R., Vila, O. F., Phillips, M., Xiao, C., Wang, J., Zhou, Y., Adhikari, P., Taing, M., Farjami, E., Javanmardi, B., Siu, M., The Cellanome Development Team,, Valente, C., Cox, C., Geiger-Schuller, K., Turley, S. J., Rozenblatt-Rosen, O., Fattahi, F., Ecker, J. R., Jones, J. R., GaDynamic transitions between cell states underlie both normal physiology and disease. However, most single-cell technologies capture only static snapshots. To address this gap, we developed a platform that integrates light-guided hydrogel polymerization with computer vision to generate on-demand compartments around live cells, enabling longitudinal imaging of cellular behavior paired with whole-transcriptome profiling of the same cells at scale. These data link dynamic phenotypes with molecular programs, enabling deeper characterization of cellular states. This approach revealed an adaptive, drug-resistant state in […]
- by Shenhar, B., Strauss, T., Alon, U.A central question in Geroscience is whether early-life mortality, which declines from birth to sexual maturity, and late-life mortality, which grows exponentially in time, can be understood within a shared conceptual framework. We show that stochastic threshold models can explain both phases by incorporating heterogeneity in neonatal vulnerability. Using U.S. National Center for Health Statistics data, we find that infant mortality risk is strongly associated with neonatal clinical markers such as Apgar scores, gestational age, and birth weight, suggesting that […]
- by Guarnieri, J., Trovao, N. S., Schwartz, R. E.Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infection in infants, older adults, and immunocompromised individuals. The molecular mechanisms linking acute RSV infection to disease severity and long-term complications remain incompletely understood. Herein, we conducted a comprehensive multi-omic analysis of 12 independent datasets encompassing epigenomics, transcriptomics, proteomics, and metabolomics across diverse systems, including in vitro infection models, clinical cohorts, longitudinal pediatric studies, vaccination models, and multiple viral strains. Across these experimental platforms and omic analysis, RSV […]
- by Jiang, Y., Movassaghi, C. S., Munoz-Estrada, J., Sundararaman, N., Momenzadeh, A., Meyer, J. G.Large-scale mass spectrometry-based proteomic screening could reveal cellular mechanisms of drug action at systems resolution but remains limited by experimental complexity and the difficulty of extracting insight from high-dimensional datasets. Here, we describe an end-to-end platform that combines semi-automated sample preparation, rapid LC-MS/MS, and AI agent-based data analysis to enable scalable proteomic screening. In a screen of 172 compounds in HepG2 cells, we generated 1,232 proteomes with more than 8,700 quantified proteins in approximately three weeks. Agentic AI reduced data […]
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