Systematic inference identifies a major source of heterogeneity in cell signaling dynamics: The rate-limiting step number

Kim, Dae Wook; Hong, Hyukpyo; Kim, Jae Kyoung

doi:10.1126/sciadv.abl4598

Cited by 20 publications

(21 citation statements)

References 82 publications

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“…Importantly, the cascades of complex biochemical/biophysical processes 17,18 needed to transform signal perception into a navigational reaction inevitably result in retarded interactions upon coarsegraining 19 (cf. supplementary Table S1).…”

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confidence: 99%

Spontaneous vortex formation by microswimmers with retarded attractions

et al. 2023

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Collective states of inanimate particles self-assemble through physical interactions and thermal motion. Despite some phenomenological resemblance, including signatures of criticality, the autonomous dynamics that binds motile agents into flocks, herds, or swarms allows for much richer behavior. Low-dimensional models have hinted at the crucial role played in this respect by perceived information, decision-making, and feedback, implying that the corresponding interactions are inevitably retarded. Here we present experiments on spherical Brownian microswimmers with delayed self-propulsion toward a spatially fixed target. We observe a spontaneous symmetry breaking to a transiently chiral dynamical state and concomitant critical behavior that do not rely on many-particle cooperativity. By comparison with the stochastic delay differential equation of motion of a single swimmer, we pinpoint the delay-induced effective synchronization of the swimmers with their own past as the key mechanism. Increasing numbers of swimmers self-organize into layers with pro- and retrograde orbital motion, synchronized and stabilized by steric, phoretic, and hydrodynamic interactions. Our results demonstrate how even most simple retarded interactions can foster emergent complex adaptive behavior in small active-particle ensembles.

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confidence: 99%

Spontaneous vortex formation by microswimmers with retarded attractions

et al. 2023

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“…A simulation-based MCMC method can be developed for other dynamical models as long as a likelihood function is available. While we used a continuous-time Markov Chain, which efficiently explains a biochemical reaction network with a low copy number of molecules, one can also use a stochastic differential equation (Calderazzo et al ., 2018; Ruttor and Opper, 2009) which is accurate when the copy numbers are higher, an agent-based model (Grazzini et al, 2017), or a delay differential equation (Kim et al ., 2022). Thus, we expect that our framework can be extended to various stochastic models of non-Markovian GRNs, and thus characterize the dynamics of a variety of systems from partial observations.…”

Section: Discussionmentioning

confidence: 99%

“…Recently, inference methods have been proposed based on the assumption that the unobserved processes are sequential, and thus can be modeled by introducing a delay (Jiang et al ., 2021; Heron et al ., 2007; Calderazzo et al ., 2018; Choi et al ., 2020; Cortez et al ., 2022; Barrio et al ., 2013; Leier et al ., 2014; Gomez et al ., 2016; Kim et al ., 2022). The resulting models are non-Markovian, as system dynamics depends not only on the present, but also past states.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, inference methods have been proposed based on the assumption that the unobserved processes are sequential, and thus can be modeled by introducing a delay (Jiang et al, 2021;Heron et al, 2007;Calderazzo et al, 2018;Choi et al, 2020;Cortez et al, 2022; Barrio i i "output" -2022/11/27 -13:34 -page 2 -#2 i i i i i i 2 Hong et al et al, 2013;Leier et al, 2014;Gomez et al, 2016;Kim et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Inferring delays in partially observed gene regulatory networks

Hong

Cortez

Cheng

et al. 2022

Preprint

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Motivation: Cell function is regulated by gene regulatory networks (GRNs) defined by protein-mediated interaction between constituent genes. Despite advances in experimental techniques, we can still measure only a fraction of the processes that govern GRN dynamics. To infer the properties of GRNs using partial observation, unobserved sequential processes can be replaced with distributed time delays, yielding non- Markovian models. Inference methods based on the resulting model suffer from the curse of dimensionality. Results: We develop a simulation-based Bayesian MCMC method for the efficient and accurate inference of GRN parameters when only some of their products are observed. We illustrate our approach using a two-step activation model: An activation signal leads to the accumulation of an unobserved regulatory protein, which triggers the expression of observed fluorescent proteins. With prior information about observed fluorescent protein synthesis, our method successfully infers the dynamics of the unobserved regulatory protein. We can estimate the delay and kinetic parameters characterizing target regulation including transcription, translation, and target searching of an unobserved protein from experimental measurements of the products of its target gene. Our method is scalable and can be used to analyze non-Markovian models with hidden components. Availability: Accompanying code in R is available at https://github.com/Mathbiomed/SimMCMC.

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“…Furthermore, since directly simulating spatiotemporal dynamics during the cytoplasmic trafficking of thousands of PER molecules is computationally intractable, we describe the process with a distributed time delay (𝜏) [48][49][50][51] . This time delay 𝜏 is assumed to be gammadistributed, which is similar to the distribution of time spent during the cytoplasmic trafficking of proteins 33 .…”

Section: Bistable Phosphorylation Of Per Allows Sharp Transcriptional...mentioning

confidence: 99%

Spatially coordinated collective phosphorylation filters spatiotemporal noises for precise circadian timekeeping

Chae

Kim

Lee

et al. 2022

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The mammalian circadian (~24h) clock is based on a self-sustaining transcriptional-translational negative feedback loop (TTFL) centered around the PERIOD protein (PER), which is translated in the cytoplasm and then enters the nucleus to repress its own transcription at the right time of day. How such precise nucleus entry, critical for generating circadian rhythms, occurs is mysterious because thousands of PER molecules transit through crowded cytoplasm and arrive at the perinucleus across several hours. Here, we investigate this by developing a mathematical model that effectively describes the complex spatiotemporal dynamics of PER as a single random time delay. We find that the spatially coordinated bistable phosphoswitch of PER, which triggers the phosphorylation of accumulated PER at the perinucleus, can lead to the synchronous and precise nuclear entry of PER, and thus to precise transcriptional repression despite the heterogenous PER arrival times at the perinucleus. In particular, even when cell crowdedness, cell size, and transcriptional activator level change, and thus PER arrival times at the perinucleus are greatly perturbed, the bistable phosphoswitch allows the TTFL to maintain robust circadian rhythms. These results provide fundamental insight into how the circadian clock compensates for spatiotemporal noise from various intracellular sources.

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Systematic inference identifies a major source of heterogeneity in cell signaling dynamics: The rate-limiting step number

Cited by 20 publications

References 82 publications

Spontaneous vortex formation by microswimmers with retarded attractions

Spontaneous vortex formation by microswimmers with retarded attractions

Inferring delays in partially observed gene regulatory networks

Spatially coordinated collective phosphorylation filters spatiotemporal noises for precise circadian timekeeping

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