Gut microbiota dysbiosis is associated with altered tryptophan metabolism and dysregulated inflammatory response in severe COVID-19

Essex, M.; Pascual-Leone, B. M.; Löber, U.; Kuhring, M.; Zhang, B.; Bruening, U.; Fritsche-Guenther, R.; Krzanowski, M.; Vernengo, F. F.; Brumhard, S.; Röwekamp, I.; Bielecka, A. A.; Lesker, T. R.; Wyler, E.; Landthaler, M.; Mantei, A.; Meisel, C.; Caesar, S.; Thiebeault, C.; Corman, V.; Marko, L.; Suttorp, N.; Strowig, T.; Kurth, F.; Sander, L. E.; Li, Y.; Kirwan, J. A.; Forslund, S. K.; Opitz, B.

doi:10.1101/2022.12.02.518860

Home/Archive/bioRxiv

bioRxiv · 10.1101/2022.12.02.518860

Gut microbiota dysbiosis is associated with altered tryptophan metabolism and dysregulated inflammatory response in severe COVID-19

View original source ↗Export metadata ↓

Abstract

The clinical course of the 2019 coronavirus disease (COVID-19) is variable and to a substantial degree still unpredictable, especially in persons who have neither been vaccinated nor recovered from previous infection. We hypothesized that disease progression and inflammatory responses were associated with alterations in the microbiome and metabolome. To test this, we integrated metagenome, metabolome, cytokine, and transcriptome profiles of longitudinally collected samples from hospitalized COVID-19 patients at the beginning of the pandemic (before vaccines or variants of concern) and non-infected controls, and leveraged detailed clinical information and post-hoc confounder analysis to identify robust within- and cross-omics associations. Severe COVID-19 was directly associated with a depletion of potentially beneficial intestinal microbes mainly belonging to Clostridiales, whereas oropharyngeal microbiota disturbance appeared to be mainly driven by antibiotic use. COVID-19 severity was also associated with enhanced plasma concentrations of kynurenine, and reduced levels of various other tryptophan metabolites, lysophosphatidylcholines, and secondary bile acids. Decreased abundance of Clostridiales potentially mediated the observed reduction in 5-hydroxytryptophan levels. Moreover, altered plasma levels of various tryptophan metabolites and lower abundances of Clostridiales explained significant increases in the production of IL-6, IFN{gamma} and/or TNF. Collectively, our study identifies correlated microbiome and metabolome alterations as a potential contributor to inflammatory dysregulation in severe COVID-19. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=150 HEIGHT=200 SRC="FIGDIR/small/518860v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@afc4edorg.highwire.dtl.DTLVardef@1a9ac2aorg.highwire.dtl.DTLVardef@65fb46org.highwire.dtl.DTLVardef@153ee6a_HPS_FORMAT_FIGEXP M_FIG C_FIG

Explore related subjects

systems biology Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Essex, M., Pascual-Leone, B. M., Löber, U., Kuhring, M., Zhang, B., Bruening, U., Fritsche-Guenther, R., Krzanowski, M., Vernengo, F. F., Brumhard, S., Röwekamp, I., Bielecka, A. A., Lesker, T. R., Wyler, E., Landthaler, M., Mantei, A., Meisel, C., Caesar, S., Thiebeault, C., Corman, V., Marko, L., Suttorp, N., Strowig, T., Kurth, F., Sander, L. E., Li, Y., Kirwan, J. A., Forslund, S. K., Opitz, B.. 2022-12-02. Gut microbiota dysbiosis is associated with altered tryptophan metabolism and dysregulated inflammatory response in severe COVID-19. https://doi.org/10.1101/2022.12.02.518860

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Limit-pushing overexpression reveals constraints on protein abundance

Proteins are often classified as toxic or non-toxic without measuring the abundance reached, leaving constraints on tolerable protein abundance unresolved. We established a limit-pushing approach in Saccharomyces cerevisiae combining strong inducible expression with gTOW-mediated high-copy selection to counteract copy-number compensation while measuring protein abundance and growth. Nearly all of approximately 80 chromosome I proteins severely inhibited growth or reduced viability at sufficiently high abundance. We established IE50, the expression level associated with a 50% reduction in growth rate, to quantify their widely varying overexpression tolerance. IE50 was positively associated with predicted structural order and cytoplasmic localization propensity and negatively associated with sulphur content. Single-cell imaging linked higher tolerance to proteins remaining cytoplasmic without becoming aggregation-positive and revealed abundance-dependent changes in localization and organelle morphology. At extreme abundance, Fun12, Nup60, and Pex22 generated distinct large-scale intracellular states through specific sequence regions. These findings establish overexpression toxicity as a quantitative property linked to protein characteristics and reveal both constraints on tolerable abundance and sequence-dependent capacities for intracellular organization.

systems biology↗

bioRxiv2026

Accessing Enzyme Kinetic Data and Prediction Methods at Scale

Enzyme kinetic parameters inform metabolic models, yet experimental measurements are sparse. A growing body of work predicts them from protein and substrate features, but software fragmentation hinders adoption, so downstream tools lock into the most accessible method. We present OpenKinetics Predictor (at predictor.openkinetics.org), an open-source platform integrating thirteen methods in isolated environments behind one interface. The platform optionally reports similarity between query proteins and each method's training data to contextualise reliability. A common featurisation-prediction abstraction keeps it extensible, and independent parties, including original authors, contributed many methods. We pair it with a data portal (at data.openkinetics.org) that exposes CatLog, a curated kinetic dataset, with precomputed embeddings, predicted binding sites, and standardised splits. Both offer a web interface and an API, and the GECKO modelling toolbox already calls the predictor API. As a case study, we predict across an E. coli model and find inter-predictor agreement varies with metabolic context and data availability.

systems biology↗

bioRxiv2026

A thermoregulatory design principle for transitions into hypometabolism

Mammals entering torpor or hibernation undergo an abrupt transition from normothermia to hypothermia, yet how thermoregulation enables this switch remains poorly understood. Here, we identify dynamical signatures that precede these transitions and a mathematical principle that can generate them. In fasting-induced torpor in mice, body-temperature fluctuations increased before torpor onset, providing an early-warning signal that tracked proximity to the transition better than temperature decline alone. A heat-balance model showed that reducing how strongly the effective heat-loss coefficient depends on body temperature reorganizes thermoregulatory stability, allowing a low-temperature equilibrium to emerge while the normothermic state remains stable. This organization is consistent with a symmetry-broken pitchfork involving a saddle-node. Similar increases in temperature fluctuations preceded hibernation onset in hamsters. These findings link pre-transition temperature dynamics to changes in the underlying thermoregulatory landscape and provide a framework for detecting and understanding transitions from normothermia to hypothermia.

systems biology↗