The morpho-kinetic landscape of macrophage modes during wound healing in zebrafish

Macrophages play an essential role in wound healing due to their dynamic nature and functional plasticity, exhibiting highly heterogeneous morpho-kinetic behaviors depending on their activation states. However, quantitative analysis of macrophage behavior in in vivo settings remains limited, largely due to the complexity of their diverse morphologies and motility patterns over time. In this study, we present an analytic workflow to investigate macrophage dynamics in zebrafish. By computing a comprehensive set of morpho-kinetic features, we observe that M1-like (pro-inflammatory) and M2-like (anti-inflammatory) macrophages exhibit distinct behaviors, such as reduced shape elongation, more directed movement, and less random-like motion in M1-like compared to M2-like macrophages. Based on these features, we classify macrophages in the transition period into cM1-like (classified M1-like) and cM2-like (classified M2-like) groups. We compare and analyze their behaviors, which allows us to estimate the timing of the phenotypic switch. In addition, macrophages not expressing Tumor Necrosis Factor (TNF) are located significantly farther from the wound compared to M1-like macrophages. While macrophages unstimulated by wound signaling exhibit some cM2-like features, they differ notably in shape elongation and migration speed. In summary, this study provides a quantitative analysis of macrophage behavior during wound healing and suggests distinct behavioral landscapes across different macrophage activation states.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-01-28
DOI
https://doi.org/10.1038/s41598-026-36624-w
Primary Topic
Zebrafish Biomedical Research Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The morpho-kinetic landscape of macrophage modes during wound healing in zebrafish

Michal Kollár, Aneta A. Ožvat, Resul Özbilgiç, Giulia Lupi et al.
Scientific Reports
Zebrafish Biomedical Research Applications
article

The morpho-kinetic landscape of macrophage modes during wound healing in zebrafish

Michal Kollár, Aneta A. Ožvat, Resul Özbilgiç, Giulia Lupi, Mai Nguyen‐Chi, Seol Ah Park, Karol Mikula
article en

Abstract

Macrophages play an essential role in wound healing due to their dynamic nature and functional plasticity, exhibiting highly heterogeneous morpho-kinetic behaviors depending on their activation states. However, quantitative analysis of macrophage behavior in in vivo settings remains limited, largely due to the complexity of their diverse morphologies and motility patterns over time. In this study, we present an analytic workflow to investigate macrophage dynamics in zebrafish. By computing a comprehensive set of morpho-kinetic features, we observe that M1-like (pro-inflammatory) and M2-like (anti-inflammatory) macrophages exhibit distinct behaviors, such as reduced shape elongation, more directed movement, and less random-like motion in M1-like compared to M2-like macrophages. Based on these features, we classify macrophages in the transition period into cM1-like (classified M1-like) and cM2-like (classified M2-like) groups. We compare and analyze their behaviors, which allows us to estimate the timing of the phenotypic switch. In addition, macrophages not expressing Tumor Necrosis Factor (TNF) are located significantly farther from the wound compared to M1-like macrophages. While macrophages unstimulated by wound signaling exhibit some cM2-like features, they differ notably in shape elongation and migration speed. In summary, this study provides a quantitative analysis of macrophage behavior during wound healing and suggests distinct behavioral landscapes across different macrophage activation states.

Scientific ReportsVol. 16(1)
Slovak University of Technology in Bratislava (SK), Centre National de la Recherche Scientifique (FR), Inserm (FR), Université de Montpellier (FR)
Agence Nationale de la Recherche, Université de Montpellier
Openalex Percentile: Top 76%
Zebrafish Biomedical Research Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.