A gated relaxation oscillator mediated by FrzX controls morphogenetic movements in Myxococcus xanthus

Guzzo, Mathilde; Murray, Séan; Martineau, Eugénie; Lhospice, Sébastien; Baronian, Grégory; My, Lætitia; Zhang, Yong; Espinosa, Léon; Vincentelli, Renaud; Bratton, Benjamin P.; Shaevitz, Joshua W.; Molle, Virginie; Howard, Martin; Mignot, Tâm

doi:10.1038/s41564-018-0203-x

Cited by 51 publications

(154 citation statements)

References 39 publications

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“…20 Recent studies based on cell tracking have provided unprecedented detail of cell 21 movement during development [7]. In combination with mathematical modeling, these 22 datasets unambiguously identified individual cell behaviors that are essential for 23 42 help of A-motility system that uses a novel molecular motor and focal adhesion 43 complexes [9,21]. However, most S-system mutants fail to develop because they cannot 44 produce an extracellular matrix (ECM) that is both essential for S-motility and vital for 45 development.…”

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confidence: 99%

“…It is frequently difficult to ascertain which of 8 the behavioral changes are deleterious to development and which can be tolerated. Here 9 we develop a new approach that leverages data-driven modeling to determine whether a 10 statistically significant trend in cell behavior results in biologically significant alteration 11 of the multicellular program. We demonstrate this approach by focusing on full or aggregation [7,34].…”

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confidence: 99%

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Data-driven models reveal mutant cell behaviors important for myxobacterial aggregation

Zhang

Cotter²,

Lyu³

et al. 2020

Preprint

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Single mutations frequently alter several aspects of cell behavior but it is often not clear whether a particular statistically significant change is biologically significant. To determine which behavioral changes are most important for multicellular self-organization, we devised a new methodology using Myxococcus xanthus as a model system. During development, myxobacteria coordinate their movement to aggregate into spore-filled fruiting bodies. We investigate how aggregation is restored in two mutants, csgA and pilC, that cannot aggregate unless mixed with wild type (WT) cells. To this end, we use cell tracking to follow movement of fluorescently labeled cells in combination with data-driven agent-based modeling. The results indicate that just like WT cells, both mutants bias their movement toward aggregates and reduce motility inside aggregates. However, several aspects of mutant behavior remain uncorrected by WT demonstrating that perfect recreation of WT behavior is unnecessary. In fact, synergies between errant behaviors can make aggregation robust. 12 partial rescue of the mutants during multicellular development of Myxococcus xanthus 13 biofilms. 14 Myxococcus xanthus is a rod-shaped member of the delta-Protobacteria with a 15 lifecycle centered around surface motility of cells in a biofilm. M. xanthus has evolved 16 1/20multiple social mechanisms such as S-motility [11] and C-signaling [5, 17, 26] to achieve 17 coordinated group behaviors such as predation [25], rippling [3,12,28] and 18 development [28,35]. Upon amino acid limitation, M. xanthus cells move into 19 three-dimensional aggregates called fruiting bodies where they sporulate [14,18,23]. 20 Recent studies based on cell tracking have provided unprecedented detail of cell 21 movement during development [7]. In combination with mathematical modeling, these 22 datasets unambiguously identified individual cell behaviors that are essential for 23 42 help of A-motility system that uses a novel molecular motor and focal adhesion 43 complexes [9,21]. However, most S-system mutants fail to develop because they cannot 44 produce an extracellular matrix (ECM) that is both essential for S-motility and vital for 45 development. The ECM is required for some types of chemotaxis [15,16] as well as for 46 cell cohesion, which could play a role in the inhibition of motility inside the 47 65 2/20 1 Results 66 1.1 Quantifying aggregation dynamics in mixtures of wild-type 67 and mutant strains 68 Fluorescence microscopy was used to quantify the behavior of mutant cells at both 69 single cell and population levels. A small fraction of cells expressing the fluorescent 70 protein tdTomato were mixed with cells expressing eYFP. Each cell expressing 71 tdTomato is bright enough to be segmented and tracked, allowing quantification of their 72 behaviors, whereas the weaker eYFP signal was used to quantify cell density during 73 aggregate growth [7]. 74 When either pilC or csgA cells are mixed with differentially labeled cells of their 75 own genotype, no aggregates were o...

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confidence: 99%

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confidence: 99%

Data-driven models reveal mutant cell behaviors important for myxobacterial aggregation

Zhang

Cotter²,

Lyu³

et al. 2020

Preprint

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“…Such patterns can be manifested in both space and time, with perhaps the most widespread instance of the latter being provided by systems that exhibit relaxation oscillations (see, e.g., Refs. [3][4][5][6]). In the simplest scenarios, these can be understood as resulting from interactions between an activator component and an inhibitory (or inactivation) component that operate at fast and slow time-scales respectively [7].…”

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confidence: 99%

Lateral inhibition provides a unifying framework for spatiotemporal pattern formation in media comprising relaxation oscillators

et al. 2019

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The collective dynamics seen in a wide variety of chemical, biological and ecological systems involve interactions between relaxation oscillators that typically involve fast activation process coupled with a slower inactivation. In this paper, we show that systems of such oscillators having distinct kinetics governing local dynamical behavior and whose interactions are described by different connection topologies, can exhibit strikingly similar spatiotemporal patterns when diffusively coupled via their inactivation component. We explain the apparent universality of this global behavior by showing that relaxation oscillators interacting via lateral inhibition will generally yield two basic classes of patterns, viz., one comprising one or more clusters of synchronized oscillators while the other is a time-invariant spatially inhomogeneous state resulting from oscillation death. All observed collective states can be interpreted either as specific instances of these fundamental patterns or as resulting from their competition.

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“…1A), while it rapidly diffuses in the cytoplasm. This simplest scenario is a good approximation for the M. xanthus polarity system [21] and suffices to reveal general principles of signal-induced polarity switching, as we will see below. The distribution of A is then characterized by quantifying its abundance at pole '1' and '2', as well as in the cytoplasm, and the timedependent cell polarity can be defined as…”

Section: Resultsmentioning

confidence: 97%

“…Recently, Guzzo et al [21] identified the response regulator FrzX as a mediator of the Frz reversal signal to the Mgl system, and proposed a mechanism for how FrzX can interact with the three core polarity proteins to trigger polarity reversals. Here, we take this study as a starting point to explore the question of signal-induced polarity switching on a more general level.…”

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confidence: 99%

Four different mechanisms for switching cell polarity

Tostevin

Wigbers

Søgaard‐Andersen

et al. 2020

Preprint

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The mechanisms and design principles of regulatory systems establishing stable polarized protein patterns within cells are well studied. However, cells can also dynamically control their cell polarity.Here, we ask how an upstream signaling system can switch the orientation of a polarized pattern.We use a mathematical model of a core polarity system based on three proteins as the basis to study different mechanisms of signal-induced polarity switching. The analysis of this model reveals four general classes of switching mechanisms with qualitatively distinct behaviors: the transient oscillator switch, the reset switch, the prime-release switch, and the push switch. Each of these regulatory mechanisms effectively implements the function of a spatial toggle switch, however with different characteristics in their nonlinear and stochastic dynamics. We identify these characteristics and also discuss experimental signatures of each type of switching mechanism.1 Cell polarity is manifested in molecular and morphological asymmetries of the cell. From bacterial to mammalian cells, cell polarity is essential in a multitude of functional contexts, including cell migration, cell division and differentiation, cell-cell signaling, development and tissue homeostasis [1,2]. One fundamental question related to cell polarity is how an initially symmetrical cell can establish a polarized state and subsequently maintain it [3].However, cells are also known to dynamically change their polarity, e.g. reversing polarity in response to external or internal signals to control motility [4][5][6]. This raises a second fundamental question: Which mechanisms permit reliable switching of cell polarity?The first question, about establishing and maintaining cell polarity, is well studied, both on the conceptual level with theoretical approaches and on the experimental level by characterizing model systems. The polarization of an initially nonpolarized cell is a symmetry breaking phenomenon: In the case of essentially isotropic cells, e.g. budding yeast or epithelial cells [3], the continuous angular symmetry is broken by polarization, whereas discrete symmetry breaking occurs for rod-shaped bacterial cells [7]. Symmetry breaking can occur spontaneously [8], but is often controlled by upstream guiding cues [9]. While the detailed molecular mechanisms underlying cell polarization differ between organisms, they often incorporate conserved G-protein based signaling systems that use multiple feedback interactions to generate asymmetric distributions on the cell membrane via a Turing instability [10]. A class of simple networks that can achieve cell polarization was explored in a synthetic biology study [11], which first showed computationally that all such networks feature one or more of the three minimal motifs 'positive feedback', 'mutual inhibition', or 'inhibition with positive feedback', and that combinations of these motifs generally polarize more reliably. The study also corroborated the latter finding experimentally, recapitulating the basic ...

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A gated relaxation oscillator mediated by FrzX controls morphogenetic movements in Myxococcus xanthus

Cited by 51 publications

References 39 publications

Data-driven models reveal mutant cell behaviors important for myxobacterial aggregation

Data-driven models reveal mutant cell behaviors important for myxobacterial aggregation

Lateral inhibition provides a unifying framework for spatiotemporal pattern formation in media comprising relaxation oscillators

Four different mechanisms for switching cell polarity

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