Biology subjects

Waschina, S.

Publications and source records attributed to Waschina, S..

12 recordsLinked to original sources

bioRxiv2025

Systematic screening of tryptophan metabolism identifies site- and microbial-specific signatures of tryptophan utilization in experimental colitis

BackgroundAltered tryptophan (Trp) metabolism and disrupted nicotinamide adenine dinucleotide (NAD) synthesis are hallmarks of IBD, yet how intestinal microbiota contribute to these metabolic shifts during intestinal inflammation remains poorly understood. MethodsWe used targeted metabolomics to systematically profile Trp- and NAD-related metabolites across multiple biological compartments - including tissues, luminal contents, stool, and serum - in mice treated with dextran sulfate sodium (DSS) alone or in combination with a broad-spectrum antibiotic (ABX) cocktail. ResultsMicrobial depletion significantly attenuated colitis and increased host Trp bioavailability, implicating the gut microbiota as a competitive Trp consumer. In DSS colitis, Trp degradation along the kynurenine pathway (KP) was exaggerated but blocked at the key KP enzyme quinolinate phosphoribosyltransferase (QPRT), resulting in mucosal NAD(H) depletion. ABX co-treatment normalized metabolite conversion along the KP and restored mucosal NAD(H) levels, revealing a dual role of the gut microbiota during colitis: while they compete with the host for Trp utilization, they simultaneously shape host KP regulation and NAD de novo synthesis, supporting host energy homeostasis. ConclusionOur findings demonstrate that mucosal NAD de novo synthesis is a microbially regulated metabolic process that alleviates intestinal inflammation and may represent a novel therapeutic target in IBD through modulation of the gut microbiota or their metabolites.

immunology↗

bioRxiv2025

Escherichia-Shigella expansion and metabolite dysregulation in type 3c diabetes

Emerging evidence supports a bidirectional gut-pancreas axis in which microbial dysbiosis, barrier dysfunction, and altered metabolite fluxes contribute to pancreatogenic diabetes (T3cDM). Whether gut microbial changes reflect systemic metabolic disturbances or primarily arise from exocrine pancreatic insufficiency (EPI) remains unclear. We profiled the gut microbiome of 48 outpatients with T3cDM, type 1 diabetes (T1DM), and healthy controls. Genus-level 16S rRNA data were analysed using cross-validated LASSO logistic regression and patient-specific community metabolic models. T3cDM showed reduced -diversity and distinct {beta}-diversity compared with T1DM and controls. Key compositional shifts included enrichment of Enterobacteriaceae (notably Escherichia-Shigella) and Streptococcaceae in T3cDM. LASSO models discriminated T3cDM from T1DM (AUC 0.867; accuracy 0.818), highlighting Blautia, Escherichia-Shigella, Streptococcus, Clostridium, and Faecalibacterium as predictors. Metabolic modelling indicated elevated Escherichia-Shigella growth in T3cDM and disease-specific metabolite fluxes. Gut microbial shifts in T3cDM predominantly reflect EPI rather than systemic metabolic disturbances characteristic of T1DM, underscoring the central role of exocrine pancreatic dysfunction in shaping the gut microbiome and its metabolic activity.

microbiology↗

bioRxiv2025

Convergent genomic responses of human gut bacteria to variations in industrialization

To what extent gut bacteria respond to the distinct ecological pressures imposed by human lifestyle remains unclear. Here, we investigate how genomic adaptation in gut bacteria differ between industrialized and non-industrialized human populations. We generated a broad collection of isolate genomes spanning diverse host geographies, lifestyles, species, and strains. We first found that compared to MAGs, paired isolate genomes recover more functional elements and signals of horizontal gene transfers (HGTs). Leveraging isolate genomes from multiple species, we find that strains from industrialized hosts experience an expansion of proteome size and harbor greater pangenome fluidity, driven by recent events of HGTs. Gene- and variant-level analyses reveal convergent patterns of lifestyle-specific adaptation in functions that are critical for ecological adaptation, such as stress response, cell envelope remodeling and central metabolism. Our results demonstrate that industrialization imprints evolutionary signatures on gut bacterial genomes, illuminating the effects of rapidly changing environments on human biology.

evolutionary biology↗

bioRxiv2025

Genome-scale metabolic models predict diet- and lifestyle-driven shifts of ecological interactions in the gut microbiome

1.Microbiomes and their host environments form complex, interconnected ecosystems. The microbial species within a microbiome, on the one hand, compete for resources, while on the other hand, they exchange vital metabolites to support their survival. These interactions are influenced by the microbial genetic repertoire, environmental conditions, and the availability of nutrients. We developed EcoGS (http://www.github.com/KaletaLab/EcoGS), a metabolic modelling tool designed to predict ecological interactions between pairs of microbes. Applying EcoGS to the microbiomes of two distinct human cohorts revealed a shift from collaborative to exploitative ecological interactions associated with higher dietary intake of simple sugars (glucose and fructose), in diabetic individuals and those living in industrialised lifestyles. On the other hand, the consumption of Cobalamin (vitamin B12), phylloquinone (vitamin K1) and biotin (vitamin B7), among other compounds, was associated with increased collaboration in the gut microbiome. We conclude that the abundance of simple sugars as an energy source reduces the necessity for microbes to cooperate, thereby increasing competition and hostility among microbiome members. Moreover, our study proposes multiple compounds, such as urate, deoxyadenosine, deoxyguanosine, and hypoxanthine, for in vitro validation tests as dietary interventions that have the potential to restore the ecological balance amongst the community. EcoGS serves as a valuable tool for exploring microbiome dynamics and their connections to environmental changes and disease.

systems biology↗

bioRxiv2025

Degradation of rutin and genistein and the effect on human bacterial fecal populations of obese and non-obese

This study re-evaluates the microbial degradation of rutin and genistein, emphasizing health-related metabotypes and novel degradation and transformation products of these compounds. In silico predictions and calculations were made to determine the molecular formulae of metabolites derived from precursor molecules by methylation, sulfation, and dehydroxylation. To validate these, anaerobic, ex vivo experiments were conducted with pooled fecal samples of obese and non-obese test persons (n=7 per group) over 48 hours, followed by 16S rRNA gene sequencing and semi-targeted high-resolution mass spectrometry analysis. We identified 46 rutin and 23 genistein metabolites, including novel methylated and sulfated derivatives. Microbial analysis revealed that the plant compounds influenced 34 bacterial families and 83 genera. Rutin inhibited obesity-associated genera while promoting butyrate-producing bacteria in BMI >40 samples, but reduced health-associated bifidobacteria and increased enterobacteria. Both compounds stimulated Eggerthella. These findings highlight significant microbial and metabolic shifts induced by plant-derived compounds, suggesting potential health implications.

microbiology↗

bioRxiv2024

Metabolic modeling reveals the aging-associated decline of host-microbiome metabolic interactions in mice

Aging is the predominant cause of morbidity and mortality in industrialized countries. The specific molecular mechanisms that drive aging are poorly understood, especially the contribution of the microbiota in these processes. Here, we combined multi-omics with metabolic modeling in mice to comprehensively characterize host-microbiome interactions and how they are affected by aging. Our findings reveal a complex dependency of host metabolism on microbial functions, including previously known as well as novel interactions. We observed a pronounced reduction in metabolic activity within the aging microbiome, which we attribute to reduced beneficial interactions in the microbial community and a reduction in its metabolic output. These microbial changes coincided with a corresponding downregulation of key host pathways predicted by our model to be dependent on the microbiome that are crucial for maintaining intestinal barrier function, cellular replication, and homeostasis. Our results elucidate microbiome-host interactions that potentially influence host aging processes, focusing on microbial nucleotide metabolism as a pivotal factor in aging dynamics. These pathways could serve as future targets for the development of microbiome-based therapies against aging. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC="FIGDIR/small/587009v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@a8e7faorg.highwire.dtl.DTLVardef@115f35aorg.highwire.dtl.DTLVardef@1bbf32org.highwire.dtl.DTLVardef@1a58c7f_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2023

Mass lysis of bacterial predators drives the enrichment of antibiotic resistance in soil microbial communities

While studies on anthropogenic activities and antibiotic resistance are numerous, the impact of microbial interactions on resistance in complex communities remains uncertain. Here we demonstrate a correlation between the presence of Myxococcus xanthus in natural soil communities and the abundance of antibiotic-resistant bacteria. Further, introducing M. xanthus isolates also enriches antibiotic resistance. This is due to the mass lysis of M. xanthus cells, which results in a toxic environment that fosters the proliferation of pre-existing resistant bacteria rather than de novo resistance evolution. Metagenomic analysis revealed that this enrichment is not limited to the tested antibiotics in culture-based methods, indicating its broader relevance. Crucially, these findings go beyond laboratory settings, showing M. xanthus introduction enriches resistant isolates in natural soil communities. Finally, we demonstrate that the mass lysis of M. xanthus cells during starvation-induced development--key aspect of the lifecycle of M. xanthus--also results in the enrichment of antibiotic resistance in soil communities. Together, we demonstrate how life-history traits in bacterial predators, like M. xanthus, significantly impact antibiotic resistomes in nature. This study also highlights the complex dynamics at play in the evolution and maintenance of antibiotic resistance, emphasizing the role of interspecies interactions in shaping antibiotic resistance profiles.

evolutionary biology↗

bioRxiv2023

Tryptophan wasting and disease activity as a systems phenomenon in inflammation - an analysis across 13 chronic inflammatory diseases.

Chronic inflammatory diseases (CID) are systems disorders affecting various organs including the intestine, joint and skin. The essential amino acid tryptophan (Trp) is not only used for protein synthesis but can also be catabolized to various bioactive derivatives that are important for cellular energy metabolism and immune regulation. Increased Trp catabolism via the kynurenine pathway is seen across individual CID entities1-5. Here, we assessed the levels of Trp and tryptophan derivatives across 13 CID to investigate the extent and nature of Trp wasting as a systems phenomenon in CID. We found reduced serum Trp levels across the majority of CID and a prevailing negative relationship between Trp and systemic inflammatory marker C-reactive protein (CRP). Increases in the kynurenine-to-Trp ratio (Kyn:Trp) indicate that the kynurenine pathway is a major route for CID-related Trp wasting. However, the extent of Trp depletion and its relationship with disease activity varies by disease, indicating potential differences in Trp metabolism. In addition, we find that amino acid catabolism in chronic inflammation is specific to tryptophan wasting, whereas other proteinogenic amino acids are not affected. Hence, our results suggest that increased Trp catabolism is a common metabolic occurrence in CID that may directly affect systemic immunity. Grant supportThis work was supported by the DFG Cluster of Excellence 1261 "Precision medicine in chronic inflammation" (KA, SSchr, PR, BH, SWa), the BMBF (e:Med Juniorverbund "Try-IBD" 01ZX1915A and 01ZX2215, the e:Med Network iTREAT 01ZX2202A, and GUIDE-IBD 031L0188A), DFG RU5042 (PR, KA), and Innovative Medicines Initiative 2 Joint Undertakings ("Taxonomy, Treatments, Targets and Remission", No. 831434, "ImmUniverse", grant agreement No. 853995, "BIOMAP", grant agreement No. 821511).

immunology↗

bioRxiv2023

Amino acid auxotrophies in human gut bacteria are linked to higher microbiome diversity and long-term stability

Amino acid auxotrophies are prevalent among bacteria. They can govern ecological dynamics in microbial communities and indicate metabolic cross-feeding interactions among coexisting genotypes. Despite the ecological importance of auxotrophies, their distribution and impact on the diversity and function of the human gut microbiome remain poorly understood. This study performed the first systematic analysis of the distribution of amino acid auxotrophies in the human gut microbiome using a combined metabolomic, metagenomic, and metabolic modeling approach. Results showed that amino acid auxotrophies are ubiquitous in the colon microbiome, with tryptophan auxotrophy being the most common. Auxotrophy frequencies were higher for those amino acids that are also essential to the human host. Moreover, a higher overall abundance of auxotrophies was associated with greater microbiome diversity and stability, and the distribution of auxotrophs was found to be related to the human hosts metabolome, including trimethylamine oxide, small aromatic acids, and secondary bile acids. Thus, our results suggest that amino acid auxotrophies are important factors contributing to microbiome ecology and host-microbiome metabolic interactions.

microbiology↗

bioRxiv2023

Metabolic model predictions enable targeted microbiome manipulation through precision prebiotics

1.The microbiome is increasingly receiving attention as an important modulator of host health and disease. However, while numerous mechanisms through which the microbiome influences its host have been identified, there is still a lack of approaches that allow to specifically modulate the abundance of individual microbes or microbial functions of interest. Moreover, current approaches for microbiome manipulation such as fecal transfers often entail a non-specific transfer of entire microbial communities with potentially unwanted side effects. To overcome this limitation, we here propose the concept of precision prebiotics that specifically modulate the abundance of a microbiome member species of interest. In a first step, we show that defining precision prebiotics by compounds that are only taken up by the target species but no other species in a community is usually not possible due to overlapping metabolic niches. Subsequently, we present a metabolic modeling network framework that allows us to define precision prebiotics for a two-member C. elegans microbiome model community comprising the immune-protective Pseudomonas lurida MYb11 and the persistent colonizer Ochrobactrum vermis MYb71. Thus, we predicted compounds that specifically boost the abundance of the host-beneficial MYb11, four of which were experimentally validated in vitro (L-serine, L-threonine, D-mannitol, and {gamma}-aminobutyric acid). L-serine was further assessed in vivo, leading to an increase in MYb11 abundance also in the worm host. Overall, our findings demonstrate that constraint-based metabolic modeling is an effective tool for the design of precision prebiotics as an important cornerstone for future microbiome-targeted therapies.

systems biology↗

bioRxiv2020

Metabolic dissimilarity determines the establishment of cross-feeding interactions in bacteria

The exchange of metabolites among different bacterial genotypes profoundly impacts the structure and function of microbial communities. However, the factors governing the establishment of these cross-feeding interactions remain poorly understood. While shared physiological features may facilitate interactions among more closely related individuals, a lower relatedness should reduce competition and thus increase the potential for synergistic interactions. Here we investigate how the relationship between a metabolite donor and recipient affects the propensity of strains to engage in unidirectional cross-feeding interactions. For this, we performed pairwise cocultivation experiments between four auxotrophic recipients and 25 species of potential amino acid donors. Auxotrophic recipients grew in the vast majority of pairs tested (78%), suggesting metabolic cross-feeding interactions are readily established. Strikingly, both the phylogenetic distance between donor and recipient and the dissimilarity of their metabolic networks were positively associated with the growth of auxotrophic recipients. Analysing the co-growth of species from a gut microbial community in-silico also revealed that recipient genotypes benefitted more from interacting with metabolically dissimilar partners, thus corroborating the empirical results. Together, our work identifies the metabolic dissimilarity between bacterial genotypes as key factor determining the establishment of metabolic cross-feeding interactions in microbial communities. HighlightsO_LIThe exchange of essential metabolites is common in microbial communities C_LIO_LIMetabolic cross-feeding interactions readily establish between auxotrophic and prototrophic bacterial strains C_LIO_LIBoth the phylogenetic and the metabolic dissimilarity between donors and recipients determines the successful establishment of metabolic cross-feeding interactions C_LI

ecology↗

bioRxiv2020

gapseq: Informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models

Microbial metabolic processes greatly impact ecosystem functioning and the physiology of multi-cellular host organisms. The inference of metabolic capabilities and phenotypes from genome sequences with the help of reference biomolecular knowledge stored in online databases remains a major challenge in systems biology. Here, we present gapseq: a novel tool for automated pathway prediction and metabolic network reconstruction from microbial genome sequences. gapseq combines databases of reference protein sequences (UniProt, TCDB), in tandem with pathway and reaction databases (MetaCyc, KEGG, ModelSEED). This enables the prediction of an organism’s metabolic capabilities from sequence homology and pathway topology criteria. By incorporating a novel LP-based gap-filling algorithm, gapseq facilitates the construction of genome-scale metabolic models that are suitable for metabolic phenotype predictions by using constraint-based flux analysis. We validated gapseq by comparing predictions to experimental data for more than 3, 000 bacterial organisms comprising 14, 895 phenotypic traits that include enzyme activity, energy sources, fermentation products, and gene essentiality. This large-scale phenotypic trait prediction test showed, that gapseq yields an overall accuracy of 81% and thereby outperforms other commonly used reconstruction tools. Furthermore, we illustrate the application of gapseq-reconstructed models to simulate biochemical interactions between microorganisms in multi-species communities. Altogether, gapseq is a new method that improves the predictive potential of automated metabolic network reconstructions and further increases their applicability in biotechnological, ecological, and medical research. gapseq is available at https://github.com/jotech/gapseq.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗