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Rust, M.

Publications and source records attributed to Rust, M..

4 recordsLinked to original sources

The Phenotypic Landscape of a Circadian Clock

Circadian clocks produce near-24-hour oscillations through biochemical feedback loops. To study their architecture, we developed a deep sequencing assay that measures the phenotypes of thousands of mutant clocks in parallel. We reveal a landscape where oscillator properties are factorized: mutations change period without decreasing amplitude and while maintaining a balanced waveform. Mutations that either shorten or lengthen period localize to specific protein-protein interaction surfaces, while a particularly sensitive region near the KaiC interdomain linker can cause extreme effects. After entrainment, high amplitude mutant oscillators form a tunable low-dimensional manifold in the period-phase plane, suggesting that most period mutations leave the coupling to the environment unchanged. In contrast, mutations that reduce amplitude are concentrated in a specific long period phenotype. This correlation structure may support the evolvability of this dynamical molecular system and is a powerful constraint on underlying mechanism.

biophysics↗

Information theory for data-driven model reduction in physics and biology

Model reduction is the construction of simple yet predictive descriptions of the dynamics of many-body systems in terms of a few relevant variables. A prerequisite to model reduction is the identification of these relevant variables, a task for which no general method exists. Here, we develop a systematic approach based on the information bottleneck to identify the relevant variables, defined as those most predictive of the future. We elucidate analytically the relation between these relevant variables and the eigenfunctions of the transfer operator describing the dynamics. Further, we show that in the limit of high compression, the relevant variables are directly determined by the slowest-decaying eigenfunctions. Our information-based approach indicates when to optimally stop increasing the complexity of the reduced model. Furthermore, it provides a firm foundation to construct interpretable deep learning tools that perform model reduction. We illustrate how these tools work in practice by considering uncurated videos of atmospheric flows from which our algorithms automatically extract the dominant slow collective variables, as well as experimental videos of cyanobacteria colonies in which we discover an emergent synchronization order parameter. Significance StatementThe first step to understand natural phenomena is to intuit which variables best describe them. An ambitious goal of artificial intelligence is to automate this process. Here, we develop a framework to identify these relevant variables directly from complex datasets. Very much like MP3 compression is about retaining information that matters most to the human ear, our approach is about keeping information that matters most to predict the future. We formalize this insight mathematically and systematically answer the question of when to stop increasing the complexity of minimal models. We illustrate how interpretable deep learning tools built on these ideas reveal emergent collective variables in settings ranging from satellite recordings of atmospheric fluid flows to experimental videos of cyanobacteria colonies.

biophysics↗

Optimizing Oscillators for Specific Tasks Predicts Preferred Biochemical Implementations

Oscillatory processes are used throughout cell biology to control time-varying physiology including the cell cycle, circadian rhythms, and developmental patterning. It has long been understood that free-running oscillations require feedback loops where the activity of one component depends on the concentration of another. Oscillator motifs have been classified by the positive or negative net logic of these loops. However, each feedback loop can be implemented by regulation of either the production step or the removal step. These possibilities are not equivalent because of the underlying structure of biochemical kinetics. By computationally searching over these possibilities, we find that certain molecular implementations are much more likely to produce stable oscillations. These preferred molecular implementations are found in many natural systems, but not typically in artificial oscillators, suggesting a design principle for future synthetic biology. Finally, we develop an approach to oscillator function across different reaction networks by evaluating the biosynthetic cost needed to achieve a given phase coherence. This analysis predicts that phase drift is most efficiently suppressed by delayed negative feedback loop architectures that operate without positive feedback. PACS numbers47.15.-x

systems biology↗

A cooperative switch within the KaiC hexamer revealed by cryo-EM

The circadian clock of cyanobacteria is based on an approximately 24h rhythm in the phosphorylation level of KaiC, a hexameric ATPase. This oscillation can be reconstituted in vitro by incubating three proteins together with ATP. Like all chemical oscillators, this system must include a nonlinear, or switch-like, feedback loop, whose nature has been unclear. Here, by using single particle cryo-EM at near-atomic resolution we identified two major conformational states of KaiC subunits, denoted as the exposed state and the buried state, which may provide a structural basis of how the KaiC hexamer changes its conformation during the (day-night) phosphorylation-dephosphorylation cycle. We classify the abundance and pattern of exposed and buried states within hexamers for more than 160,000 KaiC particles. The statistics of the spatial arrangement of the two states in hexamers can be quantitatively fit by a simple statistical physics model with an interaction energy between neighboring subunits and a local field that depends on phosphorylation state. Our study shows that phosphorylation shifts the probability of each conformation and reveals that there is substantial cooperativity between neighboring subunits, which can allow a KaiC hexamer to respond in an ultrasensitive, switch-like manner to changes in the phosphorylation level.

biophysics↗