Biology subjects

Wortel, M. T.

Publications and source records attributed to Wortel, M. T..

11 recordsLinked to original sources

bioRxiv2026

A bifidobacterial enzyme orchestrates ecology and function of infant gut bacterial community

Human milk oligosaccharides (HMOs) are abundant and structurally diverse glycans that shape the development of infant gut microbiota. Yet, how individual HMOs and bacterial genes drive the community assembly remain elusive. Here, we reconstructed an eight-member infant Bacterial Community (iBaCo) from representing dominant taxa in human infant feces. When individual HMOs were the sole carbohydrate source, they showed deterministic effects on the iBaCo composition and metabolic output. Notably, the tetramer HMO lacto-N-tetraose (LNT), in spite of its identical monomer composition as lacto-N-neotetraose (LNnT), showed a strong effect on maintaining Bifidobacterium breve abundance in iBaCo, whereas LNnT did not. Monoculture growth profiling, proteomics, enzymatic kinetic assay, and molecular docking revealed that {beta}-galactosidase D4BMY8 and the relevant downstream pathways are induced by LNT and that D4BMY8 has substrate preference on LNT over LNnT, enabling a faster growth of Bi. breve and accumulation of acetate and lactate in LNT compared to LNnT. Metabolic flux analysis indicated that the substrate-preference of {beta}-galactosidase D4BMY8 drives the skewed energy cost toward lactate/acetate metabolic output. Finally, the D4BMY8-encoding gene lacZ5 is widely spread in all isolated Bi. breve genomes, but divergently distributed in infant metagenome-assembled Bi. breve genomes. Together, we demonstrated that a single enzyme-substrate interaction could orchestrate the composition and metabolic function of an infant bacterial community, which may contribute to the assembly of dynamic infant gut microbiota. Our integrative approach provides a mechanistic framework for understanding the interaction between diet, microbial community, and infant gut health.

microbiology↗

bioRxiv2025

Additive effects of environmental and demographic variation shape the repeatability of evolution across replicated experiments

The repeatability of evolution is fundamentally important for understanding the origin and diversification of life as well as for developing evolutionary forecasting tools. Repeatability is limited by stochasticity, here defined as changes that are independent of genotypic fitness effects. Over short timescales, the two main sources of stochasticity of evolutionary change are environmental stochasticity and demographic (life-history) stochasticity. Quantifying the relative importance of these two sources of stochasticity in driving fitness outcomes is crucially important for predicting evolutionary responses. To gain insights in the effects of stochasticity, five institutes replicated an evolutionary experiment exposing Caenorhabditis elegans to novel rearing conditions. Replication across the institutes led to variation in selective environments, e.g. through divergent microbiomes among institutes. Replication within institutes was done across demographic treatments that influence the potential for population-size dependent fluctuations in allele frequencies (drift) and genetic hitchhiking (draft). We found high among-institute variation in fitness outcomes, which was partially explained by variation in microbiota. Whereas lab-specific effects explained most of the variance in mean fitness, the repeatability of fitness outcomes depended more on demographic heterogeneity. Specifically, population bottlenecks resulted in high among-replicate variation in fitness. When combined, environmental and demographic stochasticity additively reduced repeatability, underlining their additive importance in developing evolutionary forecasting tools. These results further highlight the importance of statistically integrating heterogeneity in experimental evolution to identify factors constraining outcome repeatability and study replicability.

evolutionary biology↗

bioRxiv2024

Modelling interactions that determine core gut microbiome stability to predict microbiome perturbation by opportunistic pathogens

The gut microbiome plays a crucial role in host homeostasis, with implications for nutrition, immune development, metabolism, and protection against pathogens. Disturbance of the microbiome by microbial invasion can be negative or positive: invasions of opportunistic pathogens can cause disease while dysbiotic states need invasions to recover. However, the complexity of the microbiome challenges our understanding of what factors determine the ability of microbes to invade. In this study we measure interactions between members of a SynCom of prominent gut bacteria with supernatant assays. We measure relative abundances of growth of co-cultures up to four species to validate a generalised Lotka-Volterra model parameterized with these supernatant assays. We predict differential invasion profiles of the opportunistic pathogens Escherichia coli and Bacteroides ovatus based on their monoculture growth profiles and interactions with other species. With experimental data of both predicted invasion and resistant communities we confirm model predictions of invasion success. Our model shows that both negative interactions within a community and neutral to positive interactions with the invading species promote invasion success, but the interactions towards the invading species dominate. Our validated approach opens the way for testing of interactions of human gut microbiome species, thereby developing inventions to avoid pathogenic overgrowth and therapies to enhance health-benefitting invasions. ImportanceThe stability of the human gut microbiome is crucial for host health, with opportunistic pathogen invasions causing diseases and healthy strain replacements needed for recovery. The microbiotas complexity complicates understanding its stabilizing mechanisms. This study uses a 10-species synthetic community of common gut microbiota to predict stable communities and invasion success. We employ supernatant experiments to parameterize a computational model, accurately predicting community composition and invasion success of Escherichia coli and Bacteroides ovatus. Our findings show that interactions within the resident community and with the invader are important, but the latter dominate. These results pave the way for larger-scale studies to characterize gut microbiome interactions and properties that resist invasions, potentially benefiting health through improved probiotics and faecal microbiota transplants.

microbiology↗

bioRxiv2024

Progression of ampC amplification during de novo amoxicillin resistance development in E. coli

Beta-lactam antibiotics are the most applied antimicrobials in human and veterinarian health care. Hence, beta-lactam resistance is a major health problem. Gene amplification of AmpC beta-lactamase is a main contributor to de novo {beta}-lactam resistance in E. coli. However, the time course of amplification and the accompanying DNA mutations are unclear. Here, we study the progression of ampC amplification and ampC promoter mutations in the evolution of resistance by stepwise increasing amoxicillin concentration. AmpC promoter mutations occur by day two, while the amplification by a factor of approximately eight occurs after more than six days of amoxicillin exposure. The combination of amplification and promoter mutations increase ampC mRNA level by an average factor of 200 after 22 days. An IS1 insertion was identified in the amplification junction, suggesting the amplification is facilitated by mobile genetic elements transposition. In order to identify the essential genes for ampC amplification, the chromosomal mutations of strains with induced amoxicillin resistance were compared a similarly evolved resistant {Delta}ampC knockout. The evolved {Delta}ampC contained several resistance mutations that were absent in the WT, which accumulated more mutations in stress response genes. The amoxicillin evolved {Delta}ampC does not show amplification of the fragment around the original ampC position but exhibits a large duplication or triplication at another position, suggesting selection of genes to amplify is essential for resistance adaption. IMPORTANCEAmoxicillin is one of the most used antimicrobial against bacterial infections. DNA fragments containing ampC are amplified upon prolonged and stepwise increasing exposure to amoxicillin. These ampC amplification fragments have been identified in extended-spectrum beta-lactamases (ESBLs) plasmids, which are considered the main cause of beta- lactam resistance. Understanding the progression of ampC amplification enables amoxicillin resistance prevention. In this study, we show the time course of two important factors for ampC transcription enhancement, ampC amplification and ampC promoter mutations, during de novo amoxicillin resistance evolution. We propose that the transposon IS1 contributes to the amplification and that the sigma factor 70 regulates ampC overexpression.

microbiology↗

bioRxiv2023

A modular model integrating metabolism, growth, and cell cycle predicts that fermentation is required to modulate cell size in yeast populations

For unicellular organisms, the reproduction rate and growth are crucial determinants of fitness and, therefore, essential functional manifestations of the organism genotype. Using the budding yeast Saccharomyces cerevisiae as a model organism, we integrated metabolism, which provides energy and building blocks for growth, with cell mass growth and cell cycle progression into a low-granularity, multiscale (from cell to population) computational model. This model predicted that cells with constitutive respiration do not modulate cell size according to the growth conditions. We experimentally validated the model predictions using mutants with defects in the upper part of glycolysis or glucose transport. Plugging in molecular details of cellular subsystems allowed us to refine predictions from the cellular to the molecular level. Our hybrid multiscale modeling approach provides a framework for structuring molecular knowledge and predicting cell phenotypes under various genetic and environmental conditions.

systems biology↗

bioRxiv2023

Conditions for coexistence of β-lactamase mutants

{beta}-lactamases play an important role in antibiotic resistant bacterial infections. Understanding the spread of these enzymes may inform the development of better drug therapies. However, this is complicated by the fact that {beta}-lactamases reduce the antibiotic concentration in their environment, thereby altering their own selective advantage via eco-evolutionary feedback. We investigated the effect of such feedback on the spread of bacterial strains expressing {beta}-lactamase enzymes conferring different levels of resistance to the cephalosporin cefotaxime. Specifically, we conducted head-to-head competitions between two clinically observed {beta}-lactamase mutants, TEM-19 and TEM-52, with low and high activity against cefotaxime, respectively. By experimentally varying nutrient levels, we altered cell density and hence the strength of ecological feedback and examined its impact on competitive fitness and strain coexistence across a range of cefotaxime concentrations. A population dynamic model, parameterized solely with independently measured traits, revealed cell density as the key mediator of this feedback. Our results show that cell density dictates whether the resistant strain (TEM-52) outcompetes or stably coexists with the susceptible strain (TEM-19). By validating our model with experimental data, we showed that it can reasonably predict the equilibrium frequencies based on dose-dependent growth rates and antibiotic degradation rates of both strains. Our study emphasizes the importance of considering ecological feedback for understanding the fate of antibiotic-degrading mutants, including in clinical environments. ImportanceSince the discovery of penicillin, {beta}-lactam antibiotics have become the most widely used antibiotics to treat bacterial infections. Their applicability is decreasing because bacteria evolve resistance via expression of antibiotic-degrading {beta}-lactamase enzymes. Because the spread of resistance is a large health problem, th prediction of resistance evolution is a big target. Several mutations increasing resistance have been studied, but as enzymes with increased activity spread, cells deactivate the {beta}-lactam antibiotics and thereby open a niche for susceptible variants. This eco-evolutionary feedback complicates the prediction of resistance evolution and makes it context dependent. Here, we show that both the cell density and the antibiotic concentration affect the success of a new {beta}-lactamase variant and whether it can invade, replace, or coexist with an ancestor variant. With a mathematical model we can predict the success of new variants and therefore predict evolutionary paths depending on the environmental variables.

evolutionary biology↗

bioRxiv2021

Population genetic bottleneck has only marginal effects on fitness evolution and its repeatability in dioecious C. elegans

The predictability of evolution is expected to depend on the relative contribution of deterministic and stochastic processes. This ratio is modulated by effective population size. Smaller effective populations harbor less genetic diversity and stochastic processes are generally expected to play a larger role, leading to less repeatable evolutionary trajectories. Empirical insight into the relationship between effective population size and repeatability is limited and focused mostly on asexual organisms. Here, we tested whether fitness evolution was less repeatable after a population bottleneck in obligately outcrossing populations of Caenorhabditis elegans. Replicated populations founded by 500, 50, or 5 individuals (no/moderate/strong bottleneck) were exposed to a novel environment with a different bacterial prey. As a proxy for fitness, population size was measured after one week of growth before and after 15 weeks of evolution. Surprisingly, we found no significant differences among treatments in their fitness evolution. Even though the strong bottleneck reduced the relative contribution of selection to fitness variation, this did not translate to a significant reduction in the repeatability of fitness evolution. Thus, although a bottleneck reduced the contribution of deterministic processes, we conclude that the predictability of evolution may not universally depend on effective population size, especially in sexual organisms.

evolutionary biology↗

bioRxiv2021

Evolutionary coexistence in a fluctuating environment by specialization on resource level

Microbial communities in fluctuating environments, such as the human gut or repeated dilutions in the laboratory, contain a wealth of diversity. Diversity contributes to the stability and function of communities and is maintained by underlying mechanisms. When nutrient levels fluctuate over time, one possibly relevant mechanism is that types specialize on low and high nutrient levels. The relevance of this process is supported by observations of coexistence in the laboratory, and by simple models, that show that negative frequency dependence of two such types can stabilize coexistence. However, as microbial populations are often large and numerous, they evolve. Our aim is to determine what happens when species can evolve; whether evolutionary branching can create diversity or whether evolution will destabilize coexistence. We derive the selection coefficient in fluctuating environments and use adaptive dynamics to find that evolutionary stable coexistence requires a special type of trade-off between growth at low and high nutrients. We do not find support for the necessary trade-off in data available for the bacterium Escherichia coli and the yeast Saccharomyces cerevisiae on glucose. However, this type data is scarce, and might exist for other species or in different conditions. Moreover, we do find evidence for the right trade-off and evolutionarily stable coexistence of the two species together. Since we find this coexistence in the scarce data that is available, we predict that specialization on resource level is a relevant mechanism for species diversity in microbial communities in fluctuating environments in natural settings.

microbiology↗

bioRxiv2019

Coupled fast and slow feedbacks lead to continual evolution: A general modeling approach

The Red Queen Hypothesis, which suggests that continual evolution can result from solely biotic interactions, has been studied in macroevolutionary and microevolutionary contexts. While microevolutionary studies have described examples in which evolution does not cease, understanding which general conditions lead to continual evolution or to stasis remains a major challenge. In many cases, it is unclear which experimental features or model assumptions are necessary for the observed continual evolution to emerge, and whether the described behavior is robust to variations in the given setup. Here, we aim to find the minimal set of conditions under which continual evolution occurs. To this end, we present a theoretical framework that does not assume any specific functional form and, therefore, can be applied to a wide variety of systems. Our framework is also general enough to cast predictions about both monomorphic and polymorphic populations. We show that the combination of a fast positive and a slow negative feedback causes continual evolution to emerge even from the evolution of one single evolving trait, provided that the ecological timescale is sufficiently separated from the timescales of mutation and the negative feedback. Our approach and results thus contribute to a deeper understanding of the evolutionary dynamics resulting from biotic interactions.

evolutionary biology↗

bioRxiv2017

Low affinity membrane transporters can increase net substrate uptake rate by reducing efflux

Cells require membrane-located transporter proteins to import nutrients from the environment. Many organisms have several similar transporters for the same nutrient, which differ in their affinity. Typically, high affinity transporters are expressed when substrate is scarce and low affinity ones when substrate is more abundant. The benefit of using low affinity transporters when high affinity ones are available has so far remained unclear. Here, we investigate two hypotheses. First, it was previously hypothesized that a trade-off between the affinity and the maximal catalytic rate explains this phenomenon. We find some theoretical and experimental support for this hypothesis, but no conclusive evidence. Secondly, we propose a new hypothesis: for uptake by facilitated diffusion, at saturating extracellular substrate concentrations, lowering the affinity enhances the net uptake rate by reducing the substrate efflux rate. As a consequence, there exists an optimal, external substrate concentration dependent transporter affinity. An in silico analysis of glycolysis in Saccharomyces cerevisiae shows that using the low affinity HXT3 transporter instead of the high affinity HXT6 enhances the steady-state flux by 36%. We tried to test this hypothesis using yeast strains expressing a single glucose transporter that was modified to have either a high or a low affinity. Due to the intimate and reciprocal link between glucose perception and metabolism, direct experimental proof for this hypothesis remained inconclusive in our hands. Still, our theoretical results provide a novel reason for the presence of low affinity transport systems which might have more general implications for enzyme catalyzed conversions.

microbiology↗

bioRxiv2017

Profiling metabolic flux modes by enzyme cost reveals variable trade-offs between growth and yield in Escherichia coli.

Microbes may maximize the number of daughter cells per time or per amount of nutrients consumed. These two strategies correspond, respectively, to the use of enzyme-efficient or substrate-efficient metabolic pathways. In reality, fast growth is often associated with wasteful, yield-inefficient metabolism, and a general thermodynamic trade-off between growth rate and biomass yield has been proposed to explain this. We studied growth rate/yield trade-offs by using a novel modeling framework, Enzyme-Flux Cost Minimization (EFCM) and by assuming that the growth rate depends directly on the enzyme investment per rate of biomass production. In a comprehensive mathematical model of core metabolism in E. coli, we screened all elementary flux modes leading to cell synthesis, characterized them by the growth rates and yields they provide, and studied the shape of the resulting rate/yield Pareto front. By varying the model parameters, we found that the rate/yield trade-off is not universal, but depends on metabolic kinetics and environmental conditions. A prominent trade-off emerges under oxygen-limited growth, where yield-inefficient pathways support a 2-to-3 times higher growth rate than yield-efficient pathways. EFCM can be widely used to predict optimal metabolic states and growth rates under varying nutrient levels, perturbations of enzyme parameters, and single or multiple gene knockouts.\n\nAuthor SummaryWhen cells compete for nutrients, those that grow faster and produce more offspring per time are favored by natural selection. In contrast, when cells need to maximize the cell number at a limited nutrient supply, fast growth does not matter and an efficient use of nutrients (i.e. high biomass yield) is essential. This raises a basic question about metabolism: can cells achieve high growth rates and yields simultaneously, or is there a conflict between the two goals? Using a new modeling method called Enzymatic Flux Cost Minimization (EFCM), we predict cellular growth rates and find that growth rate/yield trade-offs and the ensuing preference for enzyme-efficient or substrate-efficient metabolic pathways are not universal, but depend on growth conditions such as external glucose and oxygen concentrations.

systems biology↗