Biology subjects

Phillips, R.

Publications and source records attributed to Phillips, R..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Specific cPRC1 complexes are co-opted to mediate oncogenic gene repression in diffuse midline glioma

Diffuse midline glioma (DMG) is a fatal childhood brain tumour characterised primarily by mutant histone H3 (H3K27M). H3K27M causes a global reduction in Polycomb Repressive Complex 2 (PRC2)-mediated H3K27me3 by inhibiting PRC2 enzymatic activity. Paradoxically, PRC2 is essential in DMG tumour cells where residual complex activity is required for oncogenic gene repression, although the molecular mechanisms acting downstream of PRC2 in this context are poorly understood. Here, weve discovered this oncogenic gene repression is mediated by specific canonical PRC1 (cPRC1) formations. By combining CRISPR screening, biochemical and chromatin mapping approaches with functional perturbations we show that cPRC1 complexes containing CBX4 and PCGF4 drive oncogenic gene repression downstream of H3K27me3 in DMG cells. Remarkably, the altered H3K27me3 modification landscape characteristic of these tumours rewires the distribution of cPRC1 complexes on chromatin. CBX4 and PCGF4 containing cPRC1 accumulate at sites of H3K27me3 while other cPRC1 formations are displaced. Despite accounting for <5% of cPRC1 complexes in DMG, CBX4/PCGF4-containing complexes predominate as gene repressors. Our findings link the altered distribution of H3K27me3 with imbalanced cPRC1 function, promoting oncogenic gene repression in DMG cells, revealing new disease mechanisms and highlighting potential therapeutic opportunities in this incurable childhood brain tumour.

cancer biology↗

bioRxiv2023

Interdependence of cellular and network properties in respiratory rhythmogenesis

How breathing is generated by the preBotzinger Complex (preBotC) remains divided between two ideological frameworks, and the persistent sodium current (INaP) lies at the heart of this debate. Although INaP is widely expressed, the pacemaker hypothesis considers it essential because it endows a small subset of neurons with intrinsic bursting or "pacemaker" activity. In contrast, burstlet theory considers INaP dispensable because rhythm emerges from "pre-inspiratory" spiking activity driven by feed-forward network interactions. Using computational modeling, we discover that changes in spike shape can dissociate INaP from intrinsic bursting. Consistent with many experimental benchmarks, conditional effects on spike shape during simulated changes in oxygenation, development, extracellular potassium, and temperature alter the prevalence of intrinsic bursting and pre-inspiratory spiking without altering the role of INaP. Our results support a unifying hypothesis where INaP and excitatory network interactions, but not intrinsic bursting or pre-inspiratory spiking, are critical interdependent features of preBotC rhythmogenesis. SIGNIFICANCE STATEMENTBreathing is a vital rhythmic process originating from the preBotzinger complex. Since its discovery in 1991, there has been a spirited debate about whether respiratory rhythm generation emerges as a network property or is driven by a subset of specialized neurons with rhythmic bursting capabilities, endowed by intrinsic currents. Here, using computational modeling, we propose a unifying data-driven model of respiratory rhythm generation which bridges the gap between these competing theories. In this model, both intrinsic cellular properties (a persistent sodium current) and network properties (recurrent excitation), but not intrinsic bursting, are essential and interdependent features of respiratory rhythm generation.

neuroscience↗

bioRxiv2023

Mechanistic implications of the ternary complex structural models for the photoenzyme protochlorophyllide oxidoreductase.

The photoenzyme protochlorophyliide oxidoreductase (POR) is an important enzyme for understanding biological H-transfer mechanisms. It uses light to catalyse the reduction of protochlorophyllide (Pchlide) to chlorophyllide, a key step in chlorophyll biosynthesis. Although a wealth of spectroscopic data have provided crucial mechanistic insight about the light-driven reaction chemistry, a structural rationale for POR photocatalysis has proved more challenging and remains hotly debated. Recent structural models of the ternary enzyme-substrate complex, derived from crystal and electron microscopy data, show differences in the orientation of the Pchlide substrate and the architecture of the POR active site that have significant implications for the catalytic mechanism of Pchlide reduction. Here, we have used a combination of computational and experimental approaches to investigate the compatibility of each of these structural models with the hypothesised reaction mechanisms and propose an alternative structural model for the cyanobacterial POR-Pchlide-NADPH ternary complex based on these findings. Through detailed site-directed mutagenesis studies we show that a strictly conserved Tyr residue, which has previously been proposed to act as the proton donor in POR photocatalysis, is not likely to be involved in this step of the reaction but is crucial for Pchlide binding. Instead, an active site Cys residue is important for both hydride and proton transfer reactions in POR and is proposed to act as the proton donor, either directly or through a water-mediated network. Moreover, a conserved Gln residue is found to be important for Pchlide binding and ensuring efficient photochemistry by tuning its electronic properties, likely by interacting with the central Mg atom of the substrate. This optimal binding pose for the POR ternary enzyme-substrate complex illustrates how light energy can be harnessed to facilitate enzyme catalysis by this unique enzyme.

biochemistry↗

bioRxiv2023

Flexibility and sensitivity in gene regulation out of equilibrium

Cells adapt to environments and tune gene expression by controlling the concentrations of proteins and their kinetics in regulatory networks. In both eukaryotes and prokaryotes, experiments and theory increasingly attest that these networks can and do consume bio-chemical energy. How does this dissipation enable cellular behaviors unobtainable in equilibrium? This open question demands quantitative models that transcend thermodynamic equilibrium. Here we study the control of a simple, ubiquitous gene regulatory motif to explore the consequences of departing equilibrium in kinetic cycles. Employing graph theory, we find that dissipation unlocks nonmonotonicity and enhanced sensitivity of gene expression with respect to a transcription factors concentration. These features allow a single transcription factor to act as both a repressor and activator at different levels or achieve outputs with multiple concentration regions of locally-enhanced sensitivity. We systematically dissect how energetically-driving individual transitions within regulatory networks, or pairs of transitions, generates more adjustable and sensitive phenotypic responses. Our findings quantify necessary conditions and detectable consequences of energy expenditure. These richer mathematical behaviors--feasibly accessed using biological energy budgets and rates--may empower cells to accomplish sophisticated regulation with simpler architectures than those required at equilibrium. Significance StatementGrowing theoretical and experimental evidence demonstrates that cells can (and do) spend biochemical energy while regulating their genes. Here we explore the impact of departing from equilibrium in simple regulatory cycles, and learn that beyond increasing sensitivity, dissipation can unlock more flexible input-output behaviors that are otherwise forbidden without spending energy. These more complex behaviors could enable cells to perform more sophisticated functions using simpler systems than those needed at equilibrium.

biophysics↗

bioRxiv2023

Major axes of variation in tree demography across global forests

The future trajectory of global forests is closely intertwined with tree demography, and a major fundamental goal in ecology is to understand the key mechanisms governing spatial-temporal patterns in tree population dynamics. While historical research has made substantial progress in identifying the mechanisms individually, their relative importance among forests remains unclear mainly due to practical limitations. One approach is to group mechanisms according to their shared effects on the variability of tree vital rates and to quantify patterns therein. We developed a conceptual and statistical framework (variance partitioning of Bayesian multilevel models) that attributes the variability in tree growth, mortality, and recruitment to variation in species, space, and time, and their interactions, categories we refer to as organising principles (OPs). We applied the framework to data from 21 forest plots covering more than 2.9 million trees of approximately 6,500 species. We found that differences among species, the species OP, proved a major source of variability in tree vital rates, explaining 28-33% of demographic variance alone, and in interaction with space 14-17%, totalling 40-43%. The average variability among species declined with species richness across forests, indicating that diverse forests featured smaller interspecific differences in vital rates supporting the theory that the range of vital rates is similar across global forests. Decomposing the variance in vital rates into the proposed OPs showed that taxonomy is crucial to predicting and understanding tree demography on large forest plots. A focus on how variance is organized in forests can facilitate the construction of more targeted models with clearer expectations of which covariates might drive a vital rate. This study therefore highlights the most promising avenues for future research, both in terms of understanding the relative contributions of groups of mechanisms to forest demography and diversity, and for improving projections of forest ecosystems.

ecology↗

bioRxiv2022

Data-driven model of glycolysis identifies the role of allostery in maintaining ATP homeostasis

Glycolysis is a conserved metabolic pathway that produces ATP and biosynthetic precursors. Here, we use mathematical modeling to investigate how the control of mammalian glycolytic enzymes through allostery and mass action accomplishes various tasks of ATP homeostasis, such as controlling the rate of ATP production, maintaining high and stable ATP levels, and ensuring that ATP hydrolysis generates a net excess of energy. Our model uses data-derived enzyme rate equations, recapitulates the key tasks of glycolytic ATP homeostasis, and accurately predicts absolute concentrations of glycolytic intermediates and isotope tracing kinetics in live cells. We find that allosteric regulation of hexokinase (HK) and phosphofructokinase (PFK) by ATP, ADP, inorganic phosphate and glucose-6-phosphate (G6P), the surplus of lower glycolysis enzymes, and a large non-adenine phosphate pool are essential to robustly maintain high ATP levels and to prevent uncontrolled accumulation of phosphorylated intermediates of upper glycolysis. Meanwhile, mass action alone is sufficient to control ATP production rate and maintain high energy of ATP hydrolysis. Our results suggest a revision of the textbook view that the function of allosteric regulation of HK, PFK and PK is to control the net flux through glycolysis in response to variable ATP demand.

systems biology↗

bioRxiv2022

Wildebeest Herds on Rolling Hills: Flocking on Arbitrary Curved Surfaces

The collective behavior of active agents, whether herds of wildebeest or microscopic actin filaments propelled by molecular motors, is an exciting frontier in biological and soft matter physics. Almost three decades ago, Toner and Tu developed a hydrodynamic theory of the collective action of flocks, or herds, that helped launch the modern field of active matter. One challenge faced when applying continuum active matter theories to living phenomena is the complex geometric structure of biological environments. Both macroscopic and microscopic herds move on asymmetric curved surfaces, like undulating grass plains or the surface layers of cells or embryos, which can render problems analytically intractable. In this work, we present a formulation of the Toner-Tu flocking theory that uses the finite element method to solve the governing equations on arbitrary curved surfaces. First, we test the developed formalism and its numerical implementation in channel flow with scattering obstacles and on cylindrical and spherical surfaces, comparing our results to analytical solutions. We then progress to surfaces with arbitrary curvature, moving beyond previously accessible problems to explore herding behavior on a variety of landscapes. Our approach allows the investigation of transients and dynamic solutions not revealed by analytic methods. It also enables versatile incorporation of new geometries and boundary conditions and efficient sweeps of parameter space. Looking forward, the work presented here lays the groundwork for a dialogue between Toner-Tu theory and data on collective motion in biologically-relevant geometries, from drone footage of migrating animal herds to movies of microscopic cytoskeletal flows within cells.

biophysics↗

bioRxiv2022

Emergent Actin Flows Explain Diverse Parasite Gliding Modes

During host infection, single-celled apicomplexan parasites like Plasmodium and Toxoplasma use a motility mechanism called gliding, which differs fundamentally from other known mechanisms of eukaryotic cell motility. Gliding is thought to be powered by a thin layer of flowing filamentous (F)-actin1- 3 sandwiched between the plasma membrane and a myosin-coated4,5 inner membrane complex. How this surface actin layer drives the diverse apicomplexan gliding modes observed experimentally - helical, circular, and twirling6,7, and patch8, pendulum9, or rolling2 - presents a rich biophysical puzzle. Here, we use single-molecule imaging to track individual actin filaments and myosin complexes in live Toxoplasma gondii. Based on these data, we hypothesize that F-actin flows arise by self-organization, rather than following a microtubule-based template as previously believed. We develop a continuum model of emergent F-actin flow within the unusual confines provided by parasite geometry. In the presence of F-actin turnover, our model predicts the emergence of a steady-state mode in which actin transport is largely rearward. Removing actin turnover leads to actin patches that recirculate up and down the cell, a "cyclosis" that we observe experimentally for drug-stabilized actin bundles in live parasites. These findings provide a mechanism by which actin turnover governs a transition between distinct self-organized F-actin states, whose properties can account for the diverse gliding modes known to occur. More broadly, we illustrate how different forms of gliding motility can emerge as an intrinsic consequence of the self-organizing properties of F-actin flow in a confined geometry.

biophysics↗

bioRxiv2022

Modeling and mechanical perturbations reveal how spatially regulated anchorage gives rise to spatially distinct mechanics across the mammalian spindle

During cell division, the spindle generates force to move chromosomes. In mammals, microtubule bundles called kinetochore-fibers (k-fibers) attach to and segregate chromosomes. To do so, k-fibers must be robustly anchored to the dynamic spindle. We previously developed microneedle manipulation to mechanically challenge k-fiber anchorage, and observed spatially distinct response features revealing the presence of heterogeneous anchorage (Suresh et al. 2020). How anchorage is precisely spatially regulated, and what forces are necessary and sufficient to recapitulate the k-fibers response to force remain unclear. Here, we develop a coarse-grained k-fiber model and combine with manipulation experiments to infer underlying anchorage using shape analysis. By systematically testing different anchorage schemes, we find that forces solely at k-fiber ends are sufficient to recapitulate unmanipulated k-fiber shapes, but not manipulated ones for which lateral anchorage over a 3 m length scale near chromosomes is also essential. Such anchorage robustly preserves k-fiber orientation near chromosomes while allowing pivoting around poles. Anchorage over a shorter length scale cannot robustly restrict pivoting near chromosomes, while anchorage throughout the spindle obstructs pivoting at poles. Together, this work reveals how spatially regulated anchorage gives rise to spatially distinct mechanics in the mammalian spindle, which we propose are key for function.

biophysics↗

bioRxiv2022

Anthroponumbers.org: A Quantitative Database Of Human Impacts on Planet Earth

The Human Impacts Database (www.anthroponumbers.org) is a curated searchable resource housing quantitative data relating to the diverse anthropogenic impacts on our planet, with topics ranging from sea level rise, to livestock populations, greenhouse gas emissions, fertilizer use, and beyond. Each entry in the database relates a quantitative value (or a time-series of values) along with clear referencing of the primary source, the method of measurement or estimation, an assessment of uncertainty, links to the underlying data, as well as a permanent identifier called an Human Impacts ID ("HuID"). While there are other databases that house some of these values, they are typically focused on a single topic area like energy usage or greenhouse gas emissions. The Human Impacts Database provides centralized access to quantitative information about the myriad ways in which humans impact the Earth, giving links to more specialized databases for interested readers. Here, we outline the structure of the database and describe our curation procedures. Finally, we use this database to generate a graphical summary of the current state of human impacts on the Earth, illustrating both their numerical values and their dense interconnections. The Bigger PictureOver the last 10,000 years, human activities have transformed the Earth through farming, forestry, mining and industry. The complex results of these activities are now observed and quantified as "human impacts" on Earths atmosphere, oceans, biosphere and geochemistry. While myriad studies have explored facets of human impacts on the planet, they are necessarily technical and often tightly-focused. Thus, finding reliable quantitative information requires a significant investment of time to assess each quantity, its methods of determination, and associated uncertainty. We present the Human Impacts Database (www.anthroponumbers.org), which houses a diverse array of such quantities. We review a subset of these values and how they help build intuition for understanding the Earth-human system. While collation alone does not tell us how to best ameliorate human impacts, we contend that any future plans should be made in light of a quantitative understanding of the interconnected ways in which humans impact the planet.

ecology↗

bioRxiv2021

Motor processivity and speed determine structure and dynamics of microtubule-motor assemblies

1Active matter systems can generate highly ordered structures, avoiding equilibrium through the consumption of energy by individual constituents. How the microscopic parameters that characterize the active agents are translated to the observed mesoscopic properties of the assembly has remained an open question. These active systems are prevalent in living matter; for example, in cells, the cytoskeleton is organized into structures such as the mitotic spindle through the coordinated activity of many motor proteins walking along microtubules. Here, we investigate how the microscopic motor-microtubule interactions affect the coherent structures formed in a reconstituted motor-microtubule system. This question is of deeper evolutionary significance as we suspect motor and microtubule type contribute to the shape and size of resulting structures. We explore key parameters experimentally and theoretically, using a variety of motors with different speeds, proces-sivities, and directionalities. We demonstrate that aster size depends on the motor used to create the aster, and develop a model for the distribution of motors and microtubules in steady-state asters that depends on parameters related to motor speed and processivity. Further, we show that network contraction rates scale linearly with the single-motor speed in quasi one-dimensional contraction experiments. In all, this theoretical and experimental work helps elucidate how microscopic motor properties are translated to the much larger scale of collective motor-microtubule assemblies.

biophysics↗

bioRxiv2021

Fatigue, Alertness and Risk Prediction for Shift Workers

Executive summaryO_LIThis report describes the principal outcomes of an Impact Acceleration Account project (grant number EP/I000992/1) between the University of Surrey and Transport for London carried out between Oct. 2019 and Mar. 2020. C_LIO_LIThe aim of the project was to compare the Health and Safety Executive (HSE) Fatigue Risk tool with SAFTE and other more recent models of fatigue, where fatigue here primarily means a reduced ability to function effectively and efficiently as a result of inadequate sleep. C_LIO_LIWe have not sought to discuss the useability of the HSE Fatigue Risk tool or SAFTE since this has been discussed comprehensively elsewhere (e.g. [1, 2]). We have instead focussed on the fundamental principles underlying the models. C_LIO_LIAll current biomathematical models have limitations and make asumptions that are not always evident from the accompanying documentation. Since full details of the HSE Fatigue Risk tool and the SAFTE model are not publicly available, Sections 1 and 2 give a mathematical description of the equations that we believe underlie each of these models. C_LIO_LIA comparison of predictions made by our versions of the HSE and SAFTE equations for one particular shift schedule of relevance to the UK and global tunnelling and construction industries is shown in Section 3. In this comparison, we use data collected durings TfLs Crossrail project by Dragados1. Essentially, both models give broadly the same message for the schedule we looked at, but the ability to display fatigue as it develops within a shift is a strength of SAFTE. C_LIO_LIA summary of the strengths and limitations of the use of these kind of scheduling tools is given in the final Section 4. Limitations include: O_LIModels do not describe fatigue during times when people are not in shift (e.g. driving home). However, they could readily be extended to do so. C_LIO_LIModels assume people start well-rested. This is not always a good assumption and can lead to an under-estimate of fatigue. C_LIO_LIMost models are currently based on population averages, but there are large individual different. It would be possible to further develop models to include uncertainty in fatigue predictions associated with individual differences. C_LIO_LIFew mdels include the light environment, which is important both to promote short-term alertness and facilitate circadian alignment. C_LIO_LIModels are not transparent, which makes them hard to independently validate. C_LIO_LIIt is hard to relate the outputs of current models to measureable outcomes in the field. C_LI C_LIO_LIWe also discuss briefly recent developments in mathematical modelling of fatigue and possible future directions. These include O_LIGuidance on scheduling and education on sleep and fatigue should be considered at least as important as current biomathematical models. C_LIO_LIOnly by analysing and integrating high quality individual data on sleep, fatigue, performance, near misses, accidents, actual shift patterns with models can we develop better models and management systems to reduce fatigue and associated risks. Wearables combined with apps present a great opportunity to collect data at scale but need to be used appropriately. C_LIO_LIThe importance of making time for sleep is not always recognised. Education, early diagnosis of sleep disorders such as sleep apnea, and self-monitoring all have a role to play in reducing fatigue-related risk in the work-place. C_LI C_LIO_LISection 3 and Section 4 may be understood without reading the intermediate more mathematical sections. C_LI

neuroscience↗

bioRxiv2020

Fundamental limits on the rate of bacterial growth

Recent years have seen an experimental deluge interrogating the relationship between bacterial growth rate, cell size, and protein content, quantifying the abundance of proteins across growth conditions with unprecedented resolution. However, we still lack a rigorous understanding of what sets the scale of these quantities and when protein abundances should (or should not) depend on growth rate. Here, we seek to quantitatively understand this relationship across a collection of Escherichia coli proteomic data covering {approx} 4000 proteins and 36 growth rates. We estimate the basic requirements for steady-state growth by considering key processes in nutrient transport, cell envelope biogenesis, energy generation, and the central dogma. From these estimates, ribosome biogenesis emerges as a primary determinant of growth rate. We expand on this assessment by exploring a model of proteomic regulation as a function of the nutrient supply, revealing a mechanism that ties cell size and growth rate to ribosomal content.

systems biology↗

bioRxiv2020

Reconciling Kinetic and Equilibrium Models of Bacterial Transcription

The study of transcription remains one of the centerpieces of modern biology with implications in settings from development to metabolism to evolution to disease. Precision measurements using a host of different techniques including fluorescence and sequencing readouts have raised the bar for what it means to quantitatively understand transcriptional regulation. In particular our understanding of the simplest genetic circuit is sufficiently refined both experimentally and theoretically that it has become possible to carefully discriminate between different conceptual pictures of how this regulatory system works. This regulatory motif, originally posited by Jacob and Monod in the 1960s, consists of a single transcriptional repressor binding to a promoter site and inhibiting transcription. In this paper, we show how seven distinct models of this so-called simple-repression motif, based both on equilibrium and kinetic thinking, can be used to derive the predicted levels of gene expression and shed light on the often surprising past success of the equilibrium models. These different models are then invoked to confront a variety of different data on mean, variance and full gene expression distributions, illustrating the extent to which such models can and cannot be distinguished, and suggesting a two-state model with a distribution of burst sizes as the most potent of the seven for describing the simple-repression motif.

biophysics↗

bioRxiv2020

Proofreading through spatial gradients

Key enzymatic processes in biology use the nonequilibrium error correction mechanism called kinetic proofreading to enhance their specificity. Kinetic proofreading typically requires several dedicated structural features in the enzyme, such as a nucleotide hydrolysis site and multiple enzyme-substrate conformations that delay product formation. Such requirements limit the applicability and the adaptability of traditional proofreading schemes. Here, we explore an alternative conceptual mechanism of error correction that achieves delays between substrate binding and subsequent product formation by having these events occur at distinct physical locations. The time taken by the enzyme-substrate complex to diffuse from one location to another is leveraged to discard wrong substrates. This mechanism does not require dedicated structural elements on the enzyme, making it easier to overlook in experiments but also making proofreading tunable on the fly. We discuss how tuning the length scales of enzyme or substrate concentration gradients changes the fidelity, speed and energy dissipation, and quantify the performance limitations imposed by realistic diffusion and reaction rates in the cell. Our work broadens the applicability of kinetic proofreading and sets the stage for the study of spatial gradients as a possible route to specificity.

biophysics↗

bioRxiv2020

Multiplexed characterization of rationally designed promoter architectures deconstructs combinatorial logic for IPTG-inducible systems

A crucial step towards engineering biological systems is the ability to precisely tune the genetic response to environmental stimuli. In the case of Escherichia coli inducible promoters, our incomplete understanding of the relationship between sequence composition and gene expression hinders our ability to predictably control transcriptional responses. Here, we profile the expression dynamics of 8,269 rationally designed IPTG-inducible promoters that collectively explore the individual and combinatorial effects of RNA polymerase and LacI repressor binding site strengths. Using these data, we fit a statistical mechanics model that accurately models gene expression and reveals properties of theoretically optimal inducible promoters. Furthermore, we characterize three novel promoter architectures and show that repositioning binding sites within promoters influences the types of combinatorial effects observed between promoter elements. In total, this approach enables us to deconstruct relationships between inducible promoter elements and discover practical insights for engineering inducible promoters with desirable characteristics.

synthetic biology↗

bioRxiv2020

Deciphering the regulatory genome of Escherichiacoli, one hundred promoters at a time

Advances in DNA sequencing have revolutionized our ability to read genomes. However, even in the most well-studied of organisms, the bacterium Escherichia coli, for {approx} 65% of the promoters we remain completely ignorant of their regulation. Until we have cracked this regulatory Rosetta Stone, efforts to read and write genomes will remain haphazard. We introduce a new method (Reg-Seq) linking a massively-parallel reporter assay and mass spectrometry to produce a base pair resolution dissection of more than 100 promoters in E. coli in 12 different growth conditions. First, we show that our method recapitulates regulatory information from known sequences. Then, we examine the regulatory architectures for more than 80 promoters in the E. coli genome which previously had no known regulation. In many cases, we also identify which transcription factors mediate their regulation. The method introduced here clears a path for fully characterizing the regulatory genome of model organisms, with the potential of moving on to an array of other microbes of ecological and medical relevance.

biophysics↗

bioRxiv2019

Physiological Adaptability and Parametric Versatility in a Simple Genetic Circuit

The intimate relationship between the environment and cellular growth rate has remained a major topic of inquiry in bacterial physiology for over a century. Now, as it becomes possible to understand how the growth rate dictates the wholesale reorganization of the intracellular molecular composition, we can interrogate the biophysical principles underlying this adaptive response. Regulation of gene expression drives this adaptation, with changes in growth rate tied to the activation or repression of genes covering enormous swaths of the genome. Here, we dissect how physiological perturbations alter the expression of a circuit which has been extensively characterized in a single physiological state. Given a complete thermodynamic model, we map changes in physiology directly to the biophysical parameters which define the expression. Controlling the growth rate via modulating the available carbon source or growth temperature, we measure the level of gene expression from a LacI-regulated promoter where the LacI copy number is directly measured in each condition, permitting parameter-free prediction of the expression level. The transcriptional output of this circuit is remarkably robust, with expression of the repressor being largely insensitive to the growth rate. The predicted gene expression quantitatively captures the observations under different carbon conditions, indicating that the bio-physical parameters are indifferent to the physiology. Interestingly, temperature controls the expression level in ways that are inconsistent with the prediction, revealing temperature-dependent effects that challenge current models. This work exposes the strengths and weaknesses of thermodynamic models in fluctuating environments, posing novel challenges and utility in studying physiological adaptation. SignificanceCells adapt to changing environmental conditions by repressing or activating gene expression from enormous fractions of their genome, drastically changing the molecular composition of the cell. This requires the concerted adaptation of transcription factors to the environmental signals, leading to binding or releasing of their cognate sequences. Here, we dissect a well characterized genetic circuit in a number of physiological states, make predictions of the response, and measure how the copy number of a regulator and its gene target are affected. We find the parameters defining the regulators behavior are remarkably robust to changes in the nutrient availability, but are susceptible to temperature changes. We quantitatively explore these two effects and discuss how they challenge current models of transcriptional regulation.

biophysics↗