Cross-inhibition of Turing patterns explains the self-organized regulatory mechanism of planarian fission

Herath, Samantha; Lobo, Daniel

doi:10.1016/j.jtbi.2019.110042

Cited by 16 publications

(9 citation statements)

References 85 publications

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“…Ding et al [55], Hammoudi et al [56], Herath and Lobo [59], Cole [62] Higher temperature (25-33°C) The regeneration speed increased. The movement is slow, and the velocity is not stable.…”

Section: Inhibit Rosmentioning

confidence: 97%

“…According to literatures showing that the fission of planarian flatworms correlates with the length and area size of worms [57], the fission frequency increased with the body size; when the body length is shorter than 4-5 mm, they cannot fission again [58]. Subsequent researchers reported that environmental stress can impact the process, such as increased temperature would decrease the fission length and increase the frequency of fission [59]. Hammoudi et al showed that the spontaneous fission frequency multiplied significantly at 26°C and 28°C than at 19°C [56].…”

Section: Physiological Effects Of Temperature and Oxygenmentioning

confidence: 99%

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Extreme Environmental Stress-Induced Biological Responses in the Planarian

Cao

Liu

Zhao

et al. 2020

BioMed Research International

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Planarians are bilaterally symmetric metazoans of the phylum Platyhelminthes. They have well-defined anteroposterior and dorsoventral axes and have a highly structured true brain which consists of all neural cell types and neuropeptides found in a vertebrate. Planarian flatworms are famous for their strong regenerative ability; they can easily regenerate any part of the body including the complete neoformation of a functional brain within a few days and can survive a series of extreme environmental stress. Nowadays, they are an emerging model system in the field of developmental, regenerative, and stem cell biology and have offered lots of helpful information for these realms. In this review, we will summarize the response of planarians to some typical environmental stress and hope to shed light on basic mechanisms of how organisms interact with extreme environmental stress and survive it, such as altered gravity, temperature, and oxygen, and this information will help researchers improve the design in future studies.

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“…Ding et al [55], Hammoudi et al [56], Herath and Lobo [59], Cole [62] Higher temperature (25-33°C) The regeneration speed increased. The movement is slow, and the velocity is not stable.…”

Section: Inhibit Rosmentioning

confidence: 97%

Section: Physiological Effects Of Temperature and Oxygenmentioning

confidence: 99%

Extreme Environmental Stress-Induced Biological Responses in the Planarian

Cao

Liu

Zhao

et al. 2020

BioMed Research International

View full text Add to dashboard Cite

show abstract

“…In the first session, metabolic models were developed to rationalise strategies for (i) the optimisation of energy use, such as to identify alternative sources of reactive oxygen species, (ii) to optimise proteomic allocation, integrate different sources of information and (iii) to identify a reduced genome for functional optimisation ( Szeliova et al , 2020 ). The second session on organism-level models included presentations on (i) a scalable model for prokaryote and human cells using a modular pipeline, (ii) a cross-inhibited Turing reaction-diffusion system to model the regeneration and homeostasis in planaria ( Herath and Lobo, 2020 ) and (iii) the first mathematical model of cell cycle control in budding yeast that can exhibit sustained, autonomous oscillations through previously unknown network designs ( Mondeel et al , 2020 ). These talks described the role of modelling in revealing underlying mechanistic insights by predicting novel molecular regulations.…”

Section: Annual Meetingsmentioning

confidence: 99%

SysMod: the ISCB community for data-driven computational modelling and multi-scale analysis of biological systems

et al. 2021

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Computational models of biological systems can exploit a broad range of rapidly developing approaches, including novel experimental approaches, bioinformatics data analysis, emerging modelling paradigms, data standards and algorithms. A discussion about the most recent advances among experts from various domains is crucial to foster data-driven computational modelling and its growing use in assessing and predicting the behaviour of biological systems. Intending to encourage the development of tools, approaches and predictive models, and to deepen our understanding of biological systems, the Community of Special Interest (COSI) was launched in Computational Modelling of Biological Systems (SysMod) in 2016. SysMod’s main activity is an annual meeting at the Intelligent Systems for Molecular Biology (ISMB) conference, which brings together computer scientists, biologists, mathematicians, engineers, computational and systems biologists. In the five years since its inception, SysMod has evolved into a dynamic and expanding community, as the increasing number of contributions and participants illustrate. SysMod maintains several online resources to facilitate interaction among the community members, including an online forum, a calendar of relevant meetings and a YouTube channel with talks and lectures of interest for the modelling community. For more than half a decade, the growing interest in computational systems modelling and multi-scale data integration has inspired and supported the SysMod community. Its members get progressively more involved and actively contribute to the annual COSI meeting and several related community workshops and meetings, focusing on specific topics, including particular techniques for computational modelling or standardisation efforts.

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“…Mechanistic models-specifically, those based on mathematical descriptions of the underlying causes-have been proposed for explaining the planarian body patterning during homeostasis and regeneration. These dynamic models can provide mechanistic hypotheses for the formation of the planarian poles and AP patterning by reaction-diffusion (Meinhardt, 1982;Schiffmann, 2011), including the rescaling of head and tail patterns (Werner et al, 2015) as well as the location of fission planes (Herath & Lobo, 2020). Conversely, inhibitory signals diffusing from the worm AP-ML border can produce the planarian midline gradient forming from the ML axis (Meinhardt, 2004).…”

Section: Introductionmentioning

confidence: 99%

Mechanistic Regulation of Planarian Shape During Growth and Degrowth

Ko,

Reginato,

Lobo

2023

Preprint

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Adult planarians can grow when fed and degrow (shrink) when starved while maintaining their whole-body shape with correct proportions. Different planarian morphogens are expressed at the anterior-posterior poles, medio-lateral border, and midline to provide positional information signals for the specification of different tissues at the right locations. However, it is currently unknown how these signals are coordinated together during feeding or starvation and how they modulate the differential tissue growth or degrowth necessary to form correct whole-body shapes. Here we investigate the dynamics of planarian shape during growth and degrowth together with a theoretical study to evaluate the mechanisms that regulate whole-body proportions and shape. We found that the planarian body proportions scale isometrically following similar linear rates during growth and degrowth, but that fed worms are significantly wider than starved worms. By combining a descriptive model of planarian shape and size with a mechanistic model of anterior-posterior and medio-lateral signaling calibrated with a novel machine learning methodology, we demonstrate that the feedback loop between these positional information signals and the shape they control can regulate the planarian whole-body shape during growth. Furthermore, the model can predict the correct shape and size dynamics during degrowth due to an increase in apoptosis rate and pole signal during starvation. These results offer mechanistic insights into planarian shape and size dynamics and the regulation of whole-body morphologies.

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Cross-inhibition of Turing patterns explains the self-organized regulatory mechanism of planarian fission

Cited by 16 publications

References 85 publications

Extreme Environmental Stress-Induced Biological Responses in the Planarian

Extreme Environmental Stress-Induced Biological Responses in the Planarian

SysMod: the ISCB community for data-driven computational modelling and multi-scale analysis of biological systems

Mechanistic Regulation of Planarian Shape During Growth and Degrowth

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