Biology subjects

Ilker, E.

Publications and source records attributed to Ilker, E..

6 recordsLinked to original sources

bioRxiv2026

Heterogeneous flux capacity and oxygen sensitivity lead to subcellular ETC flux gradients in mouse oocytes

Mitochondria are metabolic hubs of the cell that provide energy and metabolites to meet the energetic, biosynthetic and signaling demands of the cell. Mitochondrial activities are characterized by the metabolic fluxes through their internal metabolic pathways. One of the most important mitochondrial metabolic pathways is the electron transport chain (ETC), where electron carriers such as NADH donate their electrons to oxygen to power mitochondrial respiration. Mitochondrial activities are dynamically and spatially regulated during organism development to ensure robust development. Recent work has revealed the existence of a subcellular ETC flux gradient within a single mouse oocyte, where mitochondria closer to the cell membrane display a higher ETC flux, but the mechanism underlying the formation of this gradient is unknown. In this work, we study the origin of the ETC flux gradients by modulating them through perturbations of external oxygen concentration and temperature. Interpreting the data with spatial kinetic modeling of mitochondrial respiration, we discover that the subcellular ETC flux gradient cannot be explained by reaction-diffusion of oxygen alone, but is a result of mitochondrial heterogeneity where mitochondria closer to the cell membrane display larger ETC flux capacity and lower oxygen sensitivity. Our work suggests that kinetically distinct subpopulations of mitochondria are spatially sorted according to their metabolic activities to form intracellular metabolic gradients.

biophysics↗

bioRxiv2023

Bioenergetic costs and the evolution of noise regulation by microRNAs

Noise control, together with other regulatory functions facilitated by microRNAs (miRNAs), is believed to have played important roles in the evolution of multicellular eukaryotic organisms. miRNAs can dampen protein fluctuations via enhanced degradation of mRNAs, but this requires compensation by increased mRNA transcription to maintain the same expression levels. The overall mechanism is metabolically expensive, leading to questions about how it might have evolved in the first place. We develop a stochastic model of miRNA noise regulation, coupled with a detailed analysis of the associated metabolic costs. Additionally we calculate binding free energies for a range of miRNA seeds, the short sequences which govern target recognition. We argue that natural selection may have fine-tuned the Michaelis-Menten constant KM describing miRNA-mRNA affinity, and show supporting evidence from analysis of experimental data. KM is constrained by seed length, and optimal noise control (minimum protein variance at a given energy cost) is achievable for seeds of 6-7 nucleotides in length, the most commonly observed types. Moreover, at optimality the degree of noise reduction approaches the theoretical bound set by the Wiener-Kolmogorov linear filter. The results illustrate how selective pressure toward energy efficiency has potentially shaped a crucial regulatory pathway in eukaryotes.

biophysics↗

bioRxiv2021

Evolution of a confluent gut epithelium under cyclic stretching

The progress of food in the gastrointestinal (GI) tract is driven by a peristaltic motion generated by the muscle belt surrounding the GI tract. In turn, the response of the intestinal epithelial cells to the peristaltic stresses affects the dynamics of the epithelial structure. In this work, we study the effect of cyclic stretching (0.125 Hz, 10% strain) on the spatial organization of the intestinal epithelium using intestinal cells deposited on a flat elastomeric substrate to mimic the peristaltic motion in vitro. A confluent monolayer of Caco-2 cells is grown on a PDMS chip to probe the morphological and orientational response of the tissue to cyclic stretching. The PDMS chips are either covalently or non-covalently coated with laminin to recapitulate the basement membrane. We observe a significant orientational response where the cells rearrange their long axes perpendicular to the stretching direction for both coating conditions. The experiment is modeled by a vertex model where the cells store elastic energy with varying strain and effectively have a rotational diffusive motion through rearrangements of their shapes. The model also predicts a transition between the perpendicular orientation and orientation at an oblique angle determined by the level of the cell elastic anisotropy. It provides a general framework to study cell response and relaxation dynamics under cyclic stretching across different cell types. We also discuss potential relevance of peristalsis in determining planar cell polarity in 3D architectures.

biophysics↗

bioRxiv2021

Counterdiabatic control of biophysical processes

The biochemical reaction networks that regulate living systems are all stochastic to varying degrees. The resulting randomness affects biological outcomes at multiple scales, from the functional states of single proteins in a cell to the evolutionary trajectory of whole populations. Controlling how the distribution of these outcomes changes over time--via external interventions like time-varying concentrations of chemical species--is a complex challenge. In this work, we show how counterdiabatic (CD) driving, first developed to control quantum systems, provides a versatile tool for steering biological processes. We develop a practical graph-theoretic framework for CD driving in discrete-state continuous-time Markov networks. Though CD driving is limited to target trajectories that are instantaneous stationary states, we show how to generalize the approach to allow for non-stationary targets and local control--where only a subset of system states are targeted. The latter is particularly useful for biological implementations where there may be only a small number of available external control knobs, insufficient for global control. We derive simple graphical criteria for when local versus global control is possible. Finally, we illustrate the formalism with global control of a genetic regulatory switch and local control in chaperone-assisted protein folding. The derived control protocols in the chaperone system closely resemble natural control strategies seen in experimental measurements of heat shock response in yeast and E. coli.

biophysics↗

bioRxiv2019

Controlling the speed and trajectory of evolution with counterdiabatic driving

The pace and unpredictability of evolution are critically relevant in a variety of modern challenges: combating drug resistance in pathogens and cancer, understanding how species respond to environmental perturbations like climate change, and developing artificial selection approaches for agriculture. Great progress has been made in quantitative modeling of evolution using fitness landscapes, allowing a degree of prediction for future evolutionary histories. Yet fine-grained control of the speed and the distributions of these trajectories remains elusive. We propose an approach to achieve this using ideas originally developed in a completely different context - counterdiabatic driving to control the behavior of quantum states for applications like quantum computing and manipulating ultra-cold atoms. Implementing these ideas for the first time in a biological context, we show how a set of external control parameters (i.e. varying drug concentrations / types, temperature, nutrients) can guide the probability distribution of genotypes in a population along a specified path and time interval. This level of control, allowing empirical optimization of evolutionary speed and trajectories, has myriad potential applications, from enhancing adaptive therapies for diseases, to the development of thermotolerant crops in preparation for climate change, to accelerating bioengineering methods built on evolutionary models, like directed evolution of biomolecules.

evolutionary biology↗

bioRxiv2018

Modeling the growth of organisms validates a general relation between metabolic costs and natural selection

Metabolism and evolution are closely connected: if a mutation incurs extra energetic costs for an organism, there is a baseline selective disadvantage that may or may not be compensated for by other adaptive effects. A long-standing, but to date unproven, hypothesis is that this disadvantage is equal to the fractional cost relative to the total resting metabolic expenditure. This hypothesis has found a recent resurgence as a powerful tool for quantitatively understanding the strength of selection among different classes of organisms. Our work explores the validity of the hypothesis from first principles through a generalized metabolic growth model, versions of which have been successful in describing organismal growth from single cells to higher animals. We build a mathematical framework to calculate how perturbations in maintenance and synthesis costs translate into contributions to the selection coefficient, a measure of relative fitness. This allows us to show that the hypothesis is an approximation to the actual baseline selection coefficient. Moreover we can directly derive the correct prefactor in its functional form, as well as analytical bounds on the accuracy of the hypothesis for any given realization of the model. We illustrate our general framework using a special case of the growth model, which we show provides a quantitative description of overall metabolic synthesis and maintenance expenditures in data collected from a wide array of unicellular organisms (both prokaryotes and eukaryotes). In all these cases we demonstrate that the hypothesis is an excellent approximation, allowing estimates of baseline selection coefficients to within 15% of their actual values. Even in a broader biological parameter range, covering growth data from multicellular organisms, the hypothesis continues to work well, always within an order of magnitude of the correct result. Our work thus justifies its use as a versatile tool, setting the stage for its wider deployment.

evolutionary biology↗