Evidence map›Paper›PMID 39466814›Full record

ArticlePLoS computational biology2024

Tuning collective behaviour in zebrafish with genetic modification.

Yushi Yang, Abdelwahab Kawafi, Qiao Tong, Erika Kague, Chrissy L Hammond, C Patrick Royall

Abstract read
In one paragraph

Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yushi YangH. H. Wills Physics Laboratory, University of Bristol, Bristol, United Kingdom.
Abdelwahab KawafiDepartment of Physiology, Pharmacology, and Neuroscience, Medical Sciences, University of Bristol, Bristol, United Kingdom.
Qiao TongDepartment of Physiology, Pharmacology, and Neuroscience, Medical Sciences, University of Bristol, Bristol, United Kingdom.
Erika KagueDepartment of Physiology, Pharmacology, and Neuroscience, Medical Sciences, University of Bristol, Bristol, United Kingdom.
Chrissy L HammondDepartment of Physiology, Pharmacology, and Neuroscience, Medical Sciences, University of Bristol, Bristol, United Kingdom.
C Patrick RoyallGulliver UMR CNRS 7083, ESPCI Paris, Université PSL, Paris, France.ORCID 0009-0006-5735-5365

Funding

China Scholarship CouncilEuropean Research Council 617266Versus Arthritis (Career Development Award) 23115
6 · The paper itself

Abstract

Zebrafish collective behaviour is widely used to assess their physical and mental state, serving as a valuable tool to assess the impact of ageing, disease genetics, and the effect of drugs. The essence of these macroscopic phenomena can be represented by active matter models, where the individuals are abstracted as interactive self-propelling agents. The behaviour of these agents depends on a set of parameters in a manner reminiscent of those between the constituents of physical systems. In a few cases, the system may be controlled at the level of the individual constituents such as the interactions between colloidal particles, or the enzymatic behaviour of de novo proteins. Usually, however, while the collective behaviour may be influenced by environmental factors, it typically cannot be changed at will. Here, we challenge this scenario in a biological context by genetically modifying zebrafish. We thus demonstrate the potential of genetic modification in the context of controlling the collective behaviour of biological active matter systems at the level of the constituents, rather than externally. In particular, we probe the effect of the lack of col11a2 gene in zebrafish, which causes the early onset of osteoarthritis. The resulting col11a2 -/- zebrafish exhibited compromised vertebral column properties, bent their body less while swimming, and took longer to change their orientations. Surprisingly, a group of 25 mutant fish exhibited more orderly collective motion than the wildtype. We show that the collective behaviour of wildtype and col11a2 -/- zebrafish are captured with a simple active matter model, in which the mutant fish are modelled by self-propelling agents with a higher orientational noise on average. In this way, we demonstrate the possibility of tuning a biological system, changing the state space it occupies when interpreted with a simple active matter model.

Indexed as

Behavior, AnimalZebrafishAnimalsAnimals, Genetically ModifiedComputational BiologyModels, BiologicalSwimmingZebrafish ProteinsZebrafish Proteins

Identifiers

PMID39466814
PMCPMC11542821

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.