Biology subjects

Gerland, U.

Publications and source records attributed to Gerland, U..

15 recordsLinked to original sources

bioRxiv2025

Force Generation by Enhanced Diffusion in Enzyme-Loaded Vesicles

Recent experiments have shown that the diffusion coefficient of some metabolic enzymes increases with the concentration of their cognate substrate, a phenomenon known as enhanced diffusion. In the presence of substrate gradients, enhanced diffusion induces enzymatic drift, resulting in a non-homogeneous enzyme distribution. Here, we study the effects of enhanced diffusion on enzyme-loaded vesicles placed in external substrate gradients using a combination of computer simulations and analytical modeling. We observe that the spatially inhomogeneous enzyme profiles generated by enhanced diffusion result in a pressure gradient across the vesicle, which leads to macroscopically observable effects, such as deformation and self-propulsion of the vesicle. Our analytical model allows us to characterize dependence of the velocity of propulsion on experimentally tunable parameters. The effects predicted by our work provide an avenue for further validation of enhanced diffusion, and might be leveraged for the design of novel synthetic cargo transporters, such as targeted drug delivery systems.

biophysics↗

bioRxiv2024

Sequence motif dynamics in RNA pools

In RNA world scenarios, pools of RNA oligomers form strongly interacting, dynamic systems, which enable molecular evolution. In such pools, RNA oligomers hybridize and dehybridize, ligate and break, ultimately generating longer RNA molecules, which may fold into catalytically active ribozymes. A key process for the elongation of RNA oligomers is templated ligation, which can occur when two RNA strands are adjacently hybridized onto a template strand. Detailed simulations of the dynamics in RNA pools involve a large variety of possible sequences and reactions. Here, we develop a reduced description of these complex dynamics within the space of sequence motifs. We then explore to what extent our reduced description can capture the behavior of detailed simulations that account for the full dynamics in the space of RNA strands. Towards this end, we project the dynamics into a motif space, which accounts only for the abundance of all possible four-nucleotide motifs. A system of ordinary differential equations describes the dynamics of those motifs. Its control parameters are effective rate constants for reactions in motif space, which we obtain from the rate constants for the processes underlying the full dynamics in the space of RNA strands. We find that these reduced motif space dynamics indeed capture important aspects of the informational dynamics of RNA pools in sequence space. This approach could also provide a framework to rationalize and interpret features of the sequence dynamics observed in experimental systems.

biophysics↗

bioRxiv2024

Gradual entry into carbon starvation decreases the death rate of Escherichia coli

Bacterial fitness is determined both by how fast cells grow in nutrient-rich environments and by how well they survive when nutrients are depleted. However, these behaviors are not independent, since the molecular composition of non-growing cells is affected by their prior growth history. For instance, recent work observed that the death rates of Escherichia coli cultures that rapidly entered carbon starvation depend on their prior growth rates, with faster growth leading to exponentially faster death. On the other hand, it is well known that cells adapt their molecular composition as they slow down growth and enter stationary phase, which is generally believed to improve their chance of survival. Hence, the question arises to what extent this adaptation process reduces the subsequent death rate. And how does the duration of the time window during which cells are allowed to adapt determine the reduction in death rate, and thus the fitness benefit of adaptation? Here, we study these quantitative questions by probing the adaptation of E. coli during gradual transitions from exponential growth to carbon starvation. We monitor such transitions in cultures with different initial growth conditions and measure the resulting rates of cell death after the transition. Our experiments demonstrate that cells with the opportunity to adapt their proteome composition before entering a state of starvation exhibit lower death rates compared to those that cannot, across various substrate conditions. The quantitative data is consistent with a theoretical model built on the assumption that before starvation, cells up-regulate a specific sector of the proteome, the effect of which is to decrease the death rate in energy-limiting conditions. This work highlights the influence of the non-genetic memory of a cell, specifically in the form of inherited proteome composition, on bacterial fitness. Our results emphasize that a comprehensive understanding of bacterial fitness requires quantitative characterization of bacterial physiology in all phases of their life cycle, including growth, stationary phase, and death, as well as the transitions between them. AUTHOR SUMMARYBacteria inhabit dynamic environments and are frequently challenged by scarcity of nutrients. A recent study uncovered a curious link - faster bacterial growth leads to more rapid death when resources run out. We find that bacteria that gradually enter starvation exhibit significantly enhanced survival compared to those that do not have the chance to adapt. We interpret the observed quantitative behavior with the help of a theoretical model, which shows that our data is not compatible with a passive adaptation process, which would rely only on the general remodeling of the cellular proteome that is associated with growth transitions. Instead, our data are consistent with an active adaptation via up-regulation of genes that enhance survival during starvation. These results provide a novel perspective on bacterial survival strategies and underscore the importance of quantitatively investigating all phases of bacterial life cycles.

physiology↗

bioRxiv2024

Theoretical Analysis of Nonenzymatic RNA Replication within the Virtual Circular Genome Scenario

The transition from prebiotic chemistry to living systems requires the emergence of a scheme for enzyme-free genetic replication. Here, we analyze a recently proposed prebiotic replication scenario, the so-called Virtual Circular Genome (VCG) [Zhou et al., RNA 27, 1-11 (2021)]: Replication takes place in a pool of oligomers, where each oligomer contains a subsequence of a circular genome, such that the oligomers encode the full genome collectively. While the sequence of the circular genome may be reconstructed based on long oligomers, monomers and short oligomers merely act as replication feedstock. We observe a competition between the predominantly error-free ligation of a feedstock molecule to a long oligomer and the predominantly erroneous ligation of two long oligomers. Increasing the length of long oligomers and reducing their concentration decreases the fraction of erroneous ligations, enabling high-fidelity replication in the VCG. Alternatively, the formation of erroneous products can be suppressed if each ligation involves at least one monomer, while ligations between two long oligomers are effectively prevented. This kinetic discrimination (favoring monomer incorporation over oligomer-oligomer ligation) may be an intrinsic property of the activation chemistry, or can be externally imposed by selectively activating only monomers in the pool. Surprisingly, under these conditions, shorter oligomers are extended by monomers more quickly than long oligomers, a phenomenon which has already been observed experimentally [Ding et al., JACS 145, 7504-7515 (2023)]. Our work provides a theoretical explanation for this behavior, and predicts its dependence on system parameters such as the concentration of long oligomers. Taken together, the VCG constitutes a promising scenario of prebiotic information replication: It could mitigate challenges of in non-enzymatic copying via template-directed polymerization, such as short lengths of copied products and high error rates.

biophysics↗

bioRxiv2024

From Brownian to deterministic motor movement in a DNA-based molecular rotor

Molecular devices that have an anisotropic, periodic potential landscape can be operated as Brownian motors. When the potential landscape is cyclically switched with a chemical reaction or an external force, such devices can harness random Brownian fluctuations to generate directed motion. Recently, directed Brownian motor-like rotatory movement was demonstrated with an electrically switched DNA origami rotor with designed, ratchet-like obstacles. Here, we demonstrate that also the intrinsic anisotropy of DNA origami rotors that originally were not designed as Brownian motor devices is sufficient to result in motor movement. We show that for low amplitudes of an external switching field such devices operate as Brownian motors, while at higher amplitudes the movement is better described by the deterministic motion of an overdamped electrical motor. We characterize the amplitude and frequency dependence of the movements in both regimes, showing that after an initial steep rise the angular speed peaks and drops for excessive driving amplitudes and frequencies. The characteristics of the rotor movement are well described by a simple stochastic model of the system.

biophysics↗

bioRxiv2023

The French flag problem revisited: Creating robust and tunable axial patterns without global signaling

Wolperts French flag problem conceptualizes the task of forming axial patterns with broad regions in multicellular systems. Wolpert described two different solutions to his problem, the balancing model and thresholding of a morphogen gradient, both of which require global, long-range signaling between cells. Since global signaling becomes challenging in large multicellular systems, we computationally explore alternative solutions, which use only local cell-cell signaling and are simple enough to potentially be implemented in natural or synthetic systems. We employ cellular automata rules to describe local signal processing logics, and search for rules capable of robust and tunable axial patterning with evolutionary algorithms. This yields large sets of successful rules, which however display only few types of behavior. We introduce a rule alignment and consensus procedure to identify patterning modules that are responsible for the different behaviors. With these modules as building blocks, we then construct local schemes for axial patterning, which function also in the presence of noise and growth, and for patterns with a larger number of different regions. The regulatory logic underlying these modules could therefore serve as the basis for the design of synthetic patterning systems, and as a conceptual framework for the interpretation of biological mechanisms.

biophysics↗

bioRxiv2021

Optimal spatial allocation of enzymes as an investment problem

Given a limited number of molecular components, cells face various allocation problems demanding decisions on how to distribute their resources. For instance, cells decide which enzymes to produce at what quantity, but also where to position them. Here we focus on the spatial allocation problem of how to distribute enzymes such as to maximize the total reaction flux produced by them in a system with given geometry and boundary conditions. So far, such distributions have been studied by computational optimization, but a deeper theoretical understanding was lacking. We derive an optimal allocation principle, which demands that the available enzymes are distributed such that the marginal flux returns at each occupied position are equal. This homogeneous marginal returns criterion (HMR criterion) corresponds to a portfolio optimization criterion in a scenario where each investment globally feeds back onto all payoffs. The HMR criterion allows us to analytically understand and characterize a localization-delocalization transition in the optimal enzyme distribution that was previously observed numerically. In particular, our analysis reveals the generality of the transition, and produces a practical test for the optimality of enzyme localization by comparing the reaction flux to the influx of substrate. Based on these results, we devise an additive construction algorithm, which builds up optimal enzyme arrangements systematically rather than by trial and error. Taken together, our results reveal a common principle in allocation problems from biology and economics, which can also serve as a design principle for synthetic biomolecular systems.

bioengineering↗

bioRxiv2021

A kinetic error filtering mechanism for enzyme-free copying of nucleic acid sequences

Accurate copying of nucleic acid sequences is essential for self-replicating systems. Modern cells achieve error ratios as low as 10-9 with sophisticated enzymes capable of kinetic proofreading. In contrast, experiments probing enzyme-free copying of RNA and DNA as potential prebiotic replication processes find error ratios on the order of 10%. Given this low intrinsic copying fidelity, plausible scenarios for the spontaneous emergence of molecular evolution require an accuracy-enhancing mechanism. Here, we study a kinetic error filtering scenario that dramatically boosts the likelihood of producing exact copies of nucleic acid sequences. The mechanism exploits the observation that initial errors in template-directed polymerization of both DNA and RNA are likely to trigger a cascade of consecutive errors and significantly stall downstream extension. We incorporate these characteristics into a mathematical model with experimentally estimated parameters, and leverage this model to probe to what extent accurate and faulty polymerization products can be kinetically discriminated. While limiting the time window for polymerization prevents completion of erroneous strands, resulting in a pool in which full-length products show an enhanced accuracy, this comes at the price of a concomitant reduction in yield. We show that this fidelity-yield trade-off can be circumvented via repeated copying attempts in cyclically varying environments such as the temperature cycles occurring naturally in the vicinity of hydrothermal systems. This setting could produce exact copies of sequences as long as 50mers within their lifetime, facilitating the emergence and maintenance of catalytically active oligonucleotides.

evolutionary biology↗

bioRxiv2021

A thermal fuse in methionine biosynthesis arrests growth and protects Escherichia coli at elevated temperatures

Adaptive stress resistance in microbes is mostly attributed to the expression of stress response genes, such as heat shock proteins, which prevent deterioration of cellular material. Here, we report a novel response of E. coli to heat stress: induction of a growth-arrested state, caused by degradation of an enzyme in the methionine biosynthesis pathway (MetA). While MetA degradation is detrimental for proliferation, we show that the resulting growth arrest has a direct benefit for survival at high temperatures; it protects cells when temperatures rise beyond 50{degrees}C, increasing the survival chances by over 1000-fold. Using a combination of experiments and mathematical modelling, we show that degradation of MetA leads to the coexistence of growing and non-growing cells, allowing microbes to bet-hedge between continued growth if conditions remain bearable and survival if conditions worsen. We test our model experimentally and verify quantitatively how protein expression, degradation rates and environmental stresses affect the partitioning between growing and non-growing cells. Because growth arrest can be abolished with simple mutations, such as point mutations of MetA and knock-outs of proteases, we interpret the breakdown of methionine synthesis as a system that has evolved to disintegrate at high temperature and shut off growth, analogous to thermal fuses used in engineering to shut off electricity when the device could be damaged by overheating.

microbiology↗

bioRxiv2021

Programmable pattern formation in cellular systems with local signaling

Diverse complex systems, ranging from developing embryos to systems of locally communicating agents, display an apparent capability of "programmable" pattern formation: They reproducibly form a target pattern, but this target can be readily changed. A distinguishing feature of such systems, as compared to simpler physical pattern forming systems, is that their subunits are capable of information processing. Here, we explore schemes for programmable pattern formation within a theoretical framework, in which subunits process discrete local signals to update their internal state according to logical rules. We study systems with different update rules, different topologies, and different control schemes, to assess their ability to perform programmable pattern formation and their susceptibility to errors. Only a small subset of systems permits local organizer cells to dictate any target pattern. These systems follow a common principle, whereby a temporal pattern is transcribed into a spatial pattern, reminiscent of the clock-and-wavefront mechanism underlying vertebrate somitogenesis. An alternative scheme employing several different rules can only form a fraction of patterns but is robust with respect to the timing of organizer cell inputs. Our results establish a basis for the design of synthetic systems, and for more detailed models of programmable pattern formation closer to real systems.

synthetic biology↗

bioRxiv2020

Dynamics of chromosomal target search by a membrane-integrated one-component receptor

Membrane proteins account for about one third of the cellular proteome, but it is still unclear how dynamic they are and how they establish functional contacts with cytoplasmic interaction partners. Here, we consider a membrane-integrated one-component receptor that also acts as a transcriptional activator, and analyze how it kinetically locates its specific binding site on the genome. We focus on the case of CadC, the pH receptor of the acid stress response Cad system in E. coli. CadC is a prime example of a one-component signaling protein that directly binds to its cognate target site on the chromosome to regulate transcription. We combined fluorescence microscopy experiments, mathematical analysis, and kinetic Monte Carlo simulations to probe this target search process. Using fluorescently labeled CadC, we measured the time from activation of the receptor until successful binding to the DNA in single cells, exploiting that stable receptor-DNA complexes are visible as fluorescent spots. Our experimental data indicate that CadC is highly mobile in the membrane and finds its target by a 2D diffusion and capture mechanism. DNA mobility is constrained due to the overall chromosome organization, but a labeled DNA locus in the vicinity of the target site appears sufficiently mobile to randomly come close to the membrane. Relocation of the DNA target site to a distant position on the chromosome had almost no effect on the mean search time, which was between four and five minutes in either case. However, a mutant strain with two binding sites displayed a mean search time that was reduced by about a factor of two. This behavior is consistent with simulations of a coarse-grained lattice model for the coupled dynamics of DNA within a cell volume and proteins on its surface. The model also rationalizes the experimentally determined distribution of search times. Overall our findings reveal that DNA target search does not present a much bigger kinetic challenge for membrane-integrated proteins than for cytoplasmic proteins. More generally, diffusion and capture mechanisms may be sufficient for bacterial membrane proteins to establish functional contacts with cytoplasmic targets. Author summaryAdaptation to changing environments is vital to bacteria and is enabled by sophisticated signal transduction systems. While signal transduction by two-component systems is well studied, the signal transduction of membrane-integrated one-component systems, where one protein performs both sensing and response regulation, are insufficiently understood. How can a membrane-integrated protein bind to specific sites on the genome to regulate transcription? Here, we study the kinetics of this process, which involves both protein diffusion within the membrane and conformational fluctuations of the genomic DNA. A well-suited model system for this question is CadC, the signaling protein of the E. coli Cad system involved in pH stress response. Fluorescently labeled CadC forms visible spots in single cells upon stable DNA-binding, marking the end of the protein-DNA search process. Moreover, the start of the search is triggered by a medium shift exposing cells to pH stress. We probe the underlying mechanism by varying the number and position of DNA target sites. We combine these experiments with mathematical analysis and kinetic Monte Carlo simulations of lattice models for the search process. Our results suggest that CadC diffusion in the membrane is pivotal for this search, while the DNA target site is just mobile enough to reach the membrane.

biophysics↗

bioRxiv2020

Four different mechanisms for switching cell polarity

The mechanisms and design principles of regulatory systems establishing stable polarized protein patterns within cells are well studied. However, cells can also dynamically control their cell polarity. Here, we ask how an upstream signaling system can switch the orientation of a polarized pattern. We use a mathematical model of a core polarity system based on three proteins as the basis to study different mechanisms of signal-induced polarity switching. The analysis of this model reveals four general classes of switching mechanisms with qualitatively distinct behaviors: the transient oscillator switch, the reset switch, the prime-release switch, and the push switch. Each of these regulatory mechanisms effectively implements the function of a spatial toggle switch, however with different characteristics in their nonlinear and stochastic dynamics. We identify these characteristics and also discuss experimental signatures of each type of switching mechanism.

biophysics↗

bioRxiv2020

Trade-offs and design principles in the spatial organization of catalytic particles

Spatial organization of catalytic particles is ubiquitous in biological systems across different length scales, from enzyme complexes to metabolically coupled cells. Despite the different scales, these systems share common features of localized reactions with partially hindered diffusive transport, determined by the collective arrangement of the catalysts. Yet it remains largely unexplored how different arrangements affect the interplay between the reaction and transport dynamics, which ultimately determines the flux through the reaction pathway. Here we show that two fundamental trade-offs arise, the first between efficient inter-catalyst transport and depletion of substrate, and the second between steric confinement of intermediate products and accessibility of catalysts to substrate. We use a model reaction pathway to characterize the general design principles for the arrangement of catalysts that emerge from the interplay of these trade-offs. We find that the question of optimal catalyst arrangements generalizes the famous Thomson problem of electrostatics.

biophysics↗

bioRxiv2020

Effective Dynamics of Nucleosome Configurations at the Yeast PHO5 Promoter

Chromatin dynamics are mediated by remodeling enzymes and play crucial roles in gene regulation, as established in a paradigmatic model, the yeast PHO5 promoter. However, effective nucleosome dynamics, i.e. trajectories of promoter nucleosome configurations, remain elusive. Here, we infer such dynamics from the integration of published single-molecule data that capture multi-nucleosome configurations for repressed to fully active PHO5 promoter states with other existing histone turnover and new chromatin accessibility data. We devised and systematically investigated a new class of "regulated on-off-slide" models simulating global and local nucleosome (dis)assembly and sliding. Only seven of 68 145 models agreed well with all data. All seven models involve sliding and the known central role of the N-2 nucleosome, but regulate promoter state transitions by modulating just one assembly rather than disassembly process. This is consistent with but challenges common interpretations of previous observations at the PHO5 promoter and suggests chromatin opening by binding competitions.

molecular biology↗

bioRxiv2018

Emergence of robust nucleosome patterns from an interplay of positioning mechanisms

Proper positioning of nucleosomes in eukaryotic cells is determined by a complex interplay of factors, including nucleosome-nucleosome interactions, DNA sequence, and active chromatin remodeling. Yet, characteristic features of nucleosome positioning, such as gene-averaged nucleosome patterns, are surprisingly robust across perturbations, conditions, and species. Here, we explore how this robustness arises despite the underlying complexity. We leverage mathematical models to show that a large class of positioning mechanisms merely affects the quantitative characteristics of qualitatively robust positioning patterns. We demonstrate how statistical positioning emerges as an effective description from the complex interplay of different positioning mechanisms, which ultimately only renormalize the model parameter quantifying the effective softness of nucleosomes. This renormalization can be species-specific, rationalizing a puzzling discrepancy between the effective nucleosome softness of S. pombe and S. cerevisiae. More generally, we establish a quantitative framework for dissecting the interplay of different nucleosome positioning determinants.

biophysics↗