Olivier Witteveen, Samuel J Rosen, Ryan S Lach, Maxwell Z Wilson, Marianne Bauer
{"title":"Optimizing information transmission in optogenetic Wnt signaling.","authors":"Olivier Witteveen, Samuel J Rosen, Ryan S Lach, Maxwell Z Wilson, Marianne Bauer","doi":"10.1103/f7qj-f7qy","DOIUrl":"10.1103/f7qj-f7qy","url":null,"abstract":"<p><p>Populations of cells regulate gene expression in response to external signals, but their ability to make reliable collective decisions is limited by both intrinsic noise in molecular signaling and variability between individual cells. In this work, we use optogenetic control of the canonical Wnt pathway as an example to study how reliably information about an external signal is transmitted to a population of cells, and determine an optimal encoding strategy to maximize information transmission from Wnt signals to gene expression. We find that it is possible to reach an information capacity beyond 1 bit only through an appropriate, discrete encoding of signals: using no Wnt, a short Wnt pulse, or a sustained Wnt signal. By averaging over an increasing number of outputs, we systematically vary the effective noise in the pathway. As the effective noise decreases, the optimal encoding comprises more discrete input signals. These signals do not need to be fine-tuned to achieve near-optimal information transmission. The optimal code transitions into a continuous code in the small-noise limit, which can be shown to be consistent with the Jeffreys prior. We visualize the performance of different signal encodings using decoding maps. Our results suggest that optogenetic Wnt signaling allows for regulatory control beyond a simple binary switch and provide a framework to apply ideas from information processing to single-cell <i>in vitro</i> experiments.</p>","PeriodicalId":520315,"journal":{"name":"Physical review research","volume":"8 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13048778/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147625338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Gene expression cycles drive non-exponential bacterial growth.","authors":"Arianna Cylke, Shiladitya Banerjee","doi":"10.1103/24rx-sxcw","DOIUrl":"10.1103/24rx-sxcw","url":null,"abstract":"<p><p>Bacterial populations typically exhibit exponential growth under resource-rich conditions, yet individual cells often deviate from this pattern. Recent work has shown that the elongation rates of <i>Escherichia coli</i> and <i>Caulobacter crescentus</i> increase throughout the cell cycle (super-exponential growth), while <i>Bacillus subtilis</i> displays a mid-cycle minimum (convex growth), and <i>Mycobacterium tuberculosis</i> grows linearly. Here, we develop a single-cell model linking gene expression, proteome allocation, and mass growth to explain these diverse growth trajectories. By calibrating model parameters with experimental data, we show that DNA-proportional mRNA transcription produces near-exponential growth, whereas deviations from this proportionality yield the observed non-exponential growth patterns. Analysis of gene expression perturbations reveals that ribosome expression primarily controls dry mass growth rate, whereas cell envelope protein expression more strongly affects cell elongation rate. We show that cell-cycle-dependent transcription dynamics give rise to convex, super-exponential, and linear modes of cell elongation observed experimentally, demonstrating how the timing of cell envelope and ribosomal protein expressions drive cell-cycle-specific behaviors. These findings provide a mechanistic basis for non-exponential single-cell growth and offer insights into how bacterial cells dynamically regulate elongation rates within each generation.</p>","PeriodicalId":520315,"journal":{"name":"Physical review research","volume":"7 3","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12700632/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145759340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Physical review researchPub Date : 2025-04-01Epub Date: 2025-04-04DOI: 10.1103/physrevresearch.7.023014
David Frost, Keisha Cook, Hugo Sanabria
{"title":"Time heterogeneity of the Förster radius from dipole orientational dynamics impacts single-molecule Förster resonance energy transfer experiments.","authors":"David Frost, Keisha Cook, Hugo Sanabria","doi":"10.1103/physrevresearch.7.023014","DOIUrl":"https://doi.org/10.1103/physrevresearch.7.023014","url":null,"abstract":"<p><p>Förster resonance energy transfer (FRET) is a quantum mechanical process governing the nonradiative energy transfer between coupled electric dipoles. Its strong distance dependence makes it a widely used as a \"molecular ruler\" in biology, chemistry, and physics. In single-molecule FRET (smFRET) experiments employing time-resolved confocal microscopy, deviations from the theoretical Förster relationship between FRET efficiency and donor fluorescence lifetime-termed dynamic shifts-provide insight into underlying molecular conformational dynamics. A key challenge in interpreting these shifts is disentangling contributions from the intrinsic motion of the fluorescent dyes from those of the biomolecular system under study. We present a novel theoretical framework based on Langevin dynamics to model the stochastic translational and rotational motion of dye linkers, incorporating first-principles physics and chemical constraints consistent with molecular dynamics simulations. Our results demonstrate that the dominant factor influencing dynamic shifts in smFRET is the relative orientational fluctuations of the dyes' electric dipole moments, rather than their accessible spatial volumes. These findings refine the theoretical foundations of FRET and provide the most precise estimates of FRET efficiency to date, enhancing its utility as a molecular-scale probe of dynamic processes.</p>","PeriodicalId":520315,"journal":{"name":"Physical review research","volume":"7 2","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13098721/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147794665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Physical review researchPub Date : 2025-04-01Epub Date: 2025-05-21DOI: 10.1103/physrevresearch.7.023174
Alireza Alemi, Emre R F Aksay, Mark S Goldman
{"title":"Lyapunov theory demonstrating a fundamental limit on the speed of systems consolidation.","authors":"Alireza Alemi, Emre R F Aksay, Mark S Goldman","doi":"10.1103/physrevresearch.7.023174","DOIUrl":"10.1103/physrevresearch.7.023174","url":null,"abstract":"<p><p>The nervous system reorganizes memories from an early site to a late site, a commonly observed feature of learning and memory systems known as systems consolidation. Previous work has suggested learning rules by which consolidation may occur. Here, we provide conditions under which such rules are guaranteed to lead to stable convergence of learning and consolidation. We use the theory of Lyapunov functions, which enforces stability by requiring learning rules to decrease an energy-like (Lyapunov) function. We present the theory in the context of a simple circuit architecture motivated by classic models of cerebellum-mediated learning and consolidation. Stability is only guaranteed if the learning rate in the late stage is not faster than the learning rate in the early stage. Further, the slower the learning rate at the late stage, the larger the perturbation the system can tolerate with a guarantee of stability. We provide intuition for this result by mapping a simple example consolidation model to a damped driven oscillator system and showing that the ratio of early- to late-stage learning rates in the consolidation model can be directly identified with the oscillator's damping ratio. We then apply the theory to modeling the tuning by the cerebellum of a well-characterized analog short-term memory system, the oculomotor neural integrator, and find similar stability conditions. This work suggests the power of the Lyapunov approach to provide constraints on nervous system function.</p>","PeriodicalId":520315,"journal":{"name":"Physical review research","volume":"7 2","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12392100/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144985697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Physical review researchPub Date : 2025-04-01Epub Date: 2025-04-02DOI: 10.1103/physrevresearch.7.023005
Anna Posfai, David M McCandlish, Justin B Kinney
{"title":"Symmetry, gauge freedoms, and the interpretability of sequence-function relationships.","authors":"Anna Posfai, David M McCandlish, Justin B Kinney","doi":"10.1103/physrevresearch.7.023005","DOIUrl":"https://doi.org/10.1103/physrevresearch.7.023005","url":null,"abstract":"<p><p>Quantitative models that describe how biological sequences encode functional activities are ubiquitous in modern biology. One important aspect of these models is that they commonly exhibit gauge freedoms, i.e., directions in parameter space that do not affect model predictions. In physics, gauge freedoms arise when physical theories are formulated in ways that respect fundamental symmetries. However, the connections that gauge freedoms in models of sequence-function relationships have to the symmetries of sequence space have yet to be systematically studied. Here we study the gauge freedoms of models that respect a specific symmetry of sequence space: the group of position-specific character permutations. We find that gauge freedoms arise when model parameters transform under redundant irreducible matrix representations of this group. Based on this finding, we describe an \"embedding distillation\" procedure that enables analytic calculation of the number of independent gauge freedoms, as well as efficient computation of a sparse basis for the space of gauge freedoms. We also study how parameter transformation behavior affects parameter interpretability. We find that in many (and possibly all) nontrivial models, the ability to interpret individual model parameters as quantifying intrinsic allelic effects requires that gauge freedoms be present. This finding establishes an incompatibility between two distinct notions of parameter interpretability. Our work thus advances the understanding of symmetries, gauge freedoms, and parameter interpretability in sequence-function relationships.</p>","PeriodicalId":520315,"journal":{"name":"Physical review research","volume":"7 2","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12363380/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144985627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xing‐Liang Dong, Fuli Li, Zongping Gong, Franco Nori
{"title":"Waveguide QED with dissipative light-matter couplings","authors":"Xing‐Liang Dong, Fuli Li, Zongping Gong, Franco Nori","doi":"10.1103/physrevresearch.7.l012036","DOIUrl":"https://doi.org/10.1103/physrevresearch.7.l012036","url":null,"abstract":"Dissipative light-matter coupling plays a vital role in non-Hermitian physics, but it remains largely unexplored in waveguide QED systems. In this work, we find that by employing pseudo-Hermitian symmetry rather than anti-<a:math xmlns:a=\"http://www.w3.org/1998/Math/MathML\"><a:mi mathvariant=\"script\">PT</a:mi></a:math> symmetry, the concept of dissipative coupling could be generalized and applied to the field of waveguide QED. This leads to a series of intriguing results, such as spontaneous breaking of pseudo-Hermitian symmetry across the exceptional points (EPs), level attraction between the bound states, and critical transition across the EPs for the population of quantum emitters in the bound state. Thanks to the tunability of photonic bands in crystal waveguides, we also demonstrate that dissipative light-matter coupling leads to the emergence of nonstandard third-order exceptional points with chiral spatial profiles in a topological waveguide QED system. This work provides a promising paradigm for studying non-Hermitian quantum phenomena in waveguide QED systems.","PeriodicalId":520315,"journal":{"name":"Physical review research","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"http://link.aps.org/pdf/10.1103/PhysRevResearch.7.L012036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147381964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Physical review researchPub Date : 2024-11-01Epub Date: 2024-11-15DOI: 10.1103/physrevresearch.6.043148
Andris Berzins, Maziar Saleh Ziabari, Yaser Silani, Ilja Fescenko, Joshua T Damron, John F Barry, Andrey Jarmola, Pauli Kehayias, Bryan A Richards, Janis Smits, Victor M Acosta
{"title":"Impact of microwave phase noise on diamond quantum sensing.","authors":"Andris Berzins, Maziar Saleh Ziabari, Yaser Silani, Ilja Fescenko, Joshua T Damron, John F Barry, Andrey Jarmola, Pauli Kehayias, Bryan A Richards, Janis Smits, Victor M Acosta","doi":"10.1103/physrevresearch.6.043148","DOIUrl":"10.1103/physrevresearch.6.043148","url":null,"abstract":"<p><p>Precision optical measurements of the electron-spin precession of nitrogen-vacancy (NV) centers in diamond form the basis of numerous applications. The most sensitivity-demanding applications, such as femtotesla magnetometry, require the ability to measure changes in GHz spin transition frequencies at the sub-millihertz level, corresponding to a fractional resolution of better than 10<sup>-12</sup>. Here we study the impact of microwave (MW) phase noise on the response of an NV sensor. Fluctuations of the phase of the MW waveform cause undesired rotations of the NV spin state. These fluctuations are imprinted in the optical readout signal and, left unmitigated, are indistinguishable from magnetic-field noise. We show that the phase noise of several common commercial MW generators results in an effective <math><mtext>pT</mtext> <mspace></mspace> <msup><mrow><mtext>s</mtext></mrow> <mrow><mn>1</mn> <mo>/</mo> <mn>2</mn></mrow> </msup> </math> -range noise floor that varies with the MW carrier frequency and the detection frequency of the pulse sequence. The data are described by a frequency-domain model incorporating the MW phase-noise spectrum and the filter-function response of the sensing protocol. For controlled injection of white and random-walk phase noise, the observed NV magnetic noise floor is described by simple analytic expressions that accurately capture the scaling with pulse sequence length and the number of <math><mi>π</mi></math> pulses. We outline several strategies to suppress the impact of MW phase noise and implement a version, based on gradiometry, that realizes a > 10-fold suppression. Our study highlights an important challenge in the pursuit of sensitive diamond quantum sensors and is applicable to other qubit systems with a large transition frequency.</p>","PeriodicalId":520315,"journal":{"name":"Physical review research","volume":"6 4","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12524190/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145310577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Physical review researchPub Date : 2024-10-01Epub Date: 2024-11-20DOI: 10.1103/physrevresearch.6.043179
Shivang Rawat, Stefano Martiniani
{"title":"Element-wise and Recursive Solutions for the Power Spectral Density of Biological Stochastic Dynamical Systems at Fixed Points.","authors":"Shivang Rawat, Stefano Martiniani","doi":"10.1103/physrevresearch.6.043179","DOIUrl":"https://doi.org/10.1103/physrevresearch.6.043179","url":null,"abstract":"<p><p>Stochasticity plays a central role in nearly every biological process, and the noise power spectral density (PSD) is a critical tool for understanding variability and information processing in living systems. In steady-state, many such processes can be described by stochastic linear time-invariant (LTI) systems driven by Gaussian white noise, whose PSD is a complex rational function of the frequency that can be concisely expressed in terms of their Jacobian, dispersion, and diffusion matrices, fully defining the statistical properties of the system's dynamics at steady-state. Here, we arrive at compact element-wise solutions of the rational function coefficients for the auto- and cross-spectrum that enable the explicit analytical computation of the PSD in dimensions <i>n</i> = 2, 3, 4. We further present a recursive Leverrier-Faddeev-type algorithm for the exact computation of the rational function coefficients. Crucially, both solutions are free of matrix inverses. We illustrate our element-wise and recursive solutions by considering the stochastic dynamics of neural systems models, namely Fitzhugh-Nagumo (<i>n</i> = 2), Hindmarsh-Rose (<i>n</i> = 3), Wilson-Cowan (<i>n</i> = 4), and the Stabilized Supralinear Network (<i>n</i> = 22), as well as an evolutionary game-theoretic model with mutations (<i>n</i> = 5, 31). We extend our approach to derive a recursive method for calculating the coefficients in the power series expansion of the integrated covariance matrix for interacting spiking neurons modeled as Hawkes processes on arbitrary directed graphs.</p>","PeriodicalId":520315,"journal":{"name":"Physical review research","volume":"6 4","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13105316/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147794681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Price of information in games of chance: A statistical physics approach.","authors":"Luca Gamberi, Alessia Annibale, Pierpaolo Vivo","doi":"10.1103/PhysRevResearch.6.033250","DOIUrl":"https://doi.org/10.1103/PhysRevResearch.6.033250","url":null,"abstract":"<p><p>Information in the form of <i>data</i>, which can be stored and transferred between users, can be viewed as an intangible commodity, which can be traded in exchange for money. Determining the fair price at which a string of data should be traded is an important and open problem in many settings. In this work we develop a statistical physics framework that allows one to determine analytically the fair price of information exchanged between players in a game of chance. For definiteness, we consider a game where <i>N</i> players bet on the binary outcome of a stochastic process and share the entry fees pot if successful. We assume that one player holds information about past outcomes of the game, which they may either use exclusively to improve their betting strategy or offer to sell to another player. We find a sharp transition as the number of players <i>N</i> is tuned across a critical value, between a phase where the transaction is always profitable for the seller and one where it may not be. In both phases, different regimes are possible, depending on the \"quality\" of information being put up for sale: we observe <i>symbiotic</i> regimes, where both parties collude effectively to rig the game in their favor, <i>competitive</i> regimes, where the transaction is unappealing to the data holder as it overly favors a competitor for scarce resources, and even <i>prey-predator</i> regimes, where an exploitative data holder could be giving away bad-quality data to undercut a competitor. Our analytical framework can be generalized to more complex settings and constitutes a flexible tool to address the rich and timely problem of pricing information in games of chance.</p>","PeriodicalId":520315,"journal":{"name":"Physical review research","volume":"6 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7616869/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142776296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gian Marco Visani, Michael N Pun, Arman Angaji, Armita Nourmohammad
{"title":"Holographic-(V)AE: An end-to-end SO(3)-equivariant (variational) autoencoder in Fourier space.","authors":"Gian Marco Visani, Michael N Pun, Arman Angaji, Armita Nourmohammad","doi":"10.1103/physrevresearch.6.023006","DOIUrl":"10.1103/physrevresearch.6.023006","url":null,"abstract":"<p><p>Group-equivariant neural networks have emerged as an efficient approach to model complex data, using generalized convolutions that respect the relevant symmetries of a system. These techniques have made advances in both the supervised learning tasks for classification and regression, and the unsupervised tasks to generate new data. However, little work has been done in leveraging the symmetry-aware expressive representations that could be extracted from these approaches. Here, we present <i>holographic</i>-(variational) autoencoder [H-(V)AE], a fully end-to-end SO(3)-equivariant (variational) autoencoder in Fourier space, suitable for unsupervised learning and generation of data distributed around a specified origin in 3D. H-(V)AE is trained to reconstruct the spherical Fourier encoding of data, learning in the process a low-dimensional representation of the data (i.e., a latent space) with a maximally informative rotationally invariant embedding alongside an equivariant frame describing the orientation of the data. We extensively test the performance of H-(V)AE on diverse datasets. We show that the learned latent space efficiently encodes the categorical features of spherical images. Moreover, the low-dimensional representations learned by H-VAE can be used for downstream data-scarce tasks. Specifically, we show that H-(V)AE's latent space can be used to extract compact embeddings for protein structure microenvironments, and when paired with a random forest regressor, it enables state-of-the-art predictions of protein-ligand binding affinity.</p>","PeriodicalId":520315,"journal":{"name":"Physical review research","volume":"6 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11661850/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142879570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}