About

Edwin M. Munro, PhD, is a Professor of Molecular Genetics and Cell Biology at The University of Chicago. His research focuses on understanding how embryos integrate biochemical signaling, cytoskeletal dynamics, and cell mechanics to orchestrate complex cell and tissue behaviors. He combines live imaging, genetic perturbations, biophysical analysis, and computer simulations to study the dynamic control of actomyosin contractility, cell polarization in C. elegans, and tissue morphogenesis in ascidians. His work investigates how contractile networks of actin filaments, myosin motors, and cross-linking proteins are remodeled by embryonic cells to polarize, move, change shape, and divide. He uses C. elegans embryos as a model system to explore cell polarity formation and stabilization in response to transient cues, uncovering a network of biochemical and mechanical interactions involving PAR polarity proteins, Rho GTPases, and the actomyosin cytoskeleton. Additionally, he studies how ascidians organize force production to shape tissues and organs, focusing on neural tube closure through experiments and computer simulations. Dr. Munro's background includes a PhD in Cell and Developmental Biology from the University of Washington and postdoctoral training at the Fred Hutchinson Cancer Research Center. His contributions advance understanding of the fundamental principles governing cell polarity, contractility, and morphogenesis during embryonic development.

Research topics

• Biology
• Computer Science
• Cell biology
• Genetics
• Biochemistry
• Biophysics
• Classical mechanics
• Nanotechnology
• Cognitive science
• Materials science
• Mechanical engineering
• Anatomy
• Engineering
• Physics

Selected publications

• Actomyosin contractility drives apical polarization and membrane transport during tubulogenesis

  Research Square · 2026-03-25

  preprintOpen accessSenior author
  PublisherDOI

• Oligomerization and positive feedback on membrane binding stabilize PAR-3 asymmetries in the C. elegans zygote

  Current Biology · 2026-03-01 · 1 citations

  articleSenior author
  PublisherDOI

• Actin network heterogeneity tunes activator-inhibitor dynamics at the cell cortex

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-07-30

  preprintOpen accessSenior author

  Abstract Biological systems can display diverse patterns of self-organization, even when built on conserved networks of interaction between molecular species. In these cases, reaction-diffusion equations provide a valuable tool to learn how new dynamics could emerge from quantitative tuning of parameters. Bringing these models into quantitative correspondence with biological data remains an outstanding challenge, especially when the data manifest heterogeneities that are difficult to account for mathematically. One particular example occurs in cell biology, where the membrane-bound regulatory protein RhoA interacts with the filamentous actin cortex in an activator-inhibitor loop. Though this core biochemical circuit is conserved across multiple cell types in different organisms, it produces different patterns of RhoA activity in different contexts, from traveling waves in starfish to transient pulses in C. elegans . To understand how this variation emerges, we develop an activator-inhibitor model that accounts explicitly for actin assembly and heterogeneity. By fitting the model to summary statistics of experimental data, subject to known parameter constraints, we show that F-actin assembly dynamics tune the spatiotemporal patterns of RhoA activity. A minimal representation of these dynamics reveals how directional transport (via polymerization) combines with stochasticity in F-actin number and orientation to produce the observed patterns. This work sheds light on how phenotypic diversity arises from heterogeneity and anisotropy, with important implications for the next generation of activator-inhibitor models. Significance To divide, move, and polarize, cells must self-organize their constituent proteins into large-scale patterns with varied spatiotemporal character. The design principles of this process remain poorly understood, primarily because quantitatively matching mathematical models to experimental data is difficult. Here we consider pattern formation from two constituents on the cell cortex: the regulatory protein RhoA and actin filaments. Using a mathematical model, constrained quantitatively by data from multiple organisms, we show how diversity in RhoA activity can arise from intra- and inter-organismal changes in actin filament architecture and assembly dynamics. Our results reveal general principles for pattern formation at the cortex, and our combination of data analysis, modeling, and parameter inference provides a broadly-applicable, interdisciplinary methodology to unravel mechanisms of self-organization.

  PublisherOA PDFDOI

• Information bounds the robustness of self-organized systems

  ArXiv.org · 2025-11-03

  preprintOpen access

  Self-organized systems, from synthetic nanostructures to developing organisms, are composed of fluctuating units capable of forming robust functional structures despite noise. Here, we ask: are there fundamental bounds on the robustness of noisy self-organized systems? By viewing self-organization as noisy encoding, we prove that the positional information capacity of short-range classical systems with discrete states obeys a bound reminiscent of area laws for quantum information. We illustrate this principle with lattice models whose dynamics is captured by continuum models derived using exact coarse-graining techniques and validated through Dynamical Renormalization Group calculations. The universal bound is saturated by fine-tuning transport coefficients, which can be rationalized in the continuum limit upon considering the effects of boundaries on domain wall dynamics. We illustrate how this limit can be bypassed when long-range correlations are present by investigating a wave-pinning model motivated by biological mechanisms. In this class of models, global constraints reduce the need for fine-tuning by providing effective integral feedback. Our work identifies fundamental limits for the ability of natural and synthetic microsystems to self-assemble into patterns and rationalizes them on purely information-theoretic grounds.

  PublisherOA PDFDOI

• Spectral decomposition unlocks ascidian morphogenesis

  eLife · 2025-05-19

  articleOpen access

  Describing morphogenesis generally consists in aggregating the multiple high-resolution spatiotemporal processes involved into reproducible low-dimensional morphological processes consistent across individuals of the same species or group. In order to achieve this goal, biologists often have to submit movies issued from live imaging of developing embryos either to a qualitative analysis or to basic statistical analysis. These approaches, however, present noticeable drawbacks as they can be time consuming, hence unfit for scale, and often lack standardization and a firm foundation. In this work, we leverage the power of a continuum mechanics approach and flexibility of spectral decompositions to propose a standardized framework for automatic detection and timing of morphological processes. First, we quantify whole-embryo scale shape changes in developing ascidian embryos by statistically estimating the strain rate tensor field of its time-evolving surface without the requirement of cellular segmentation and tracking. We then apply to this data spectral decomposition in space using spherical harmonics and in time using wavelets transforms. These transformations result in the identification of the principal dynamical modes of ascidian embryogenesis and the automatic unveiling of its blueprint in the form of scalograms that tell the story of development in ascidian embryos.

  PublisherDOI

• Actin network heterogeneity tunes activator–inhibitor dynamics at the cell cortex

  Proceedings of the National Academy of Sciences · 2025-12-08 · 1 citations

  articleOpen accessSenior author

  Biological systems can display diverse patterns of self-organization, even when built on conserved networks of interaction between molecular species. In these cases, reaction–diffusion equations provide a valuable tool to learn how new dynamics could emerge from quantitative tuning of parameters. Bringing these models into quantitative correspondence with biological data remains an outstanding challenge, especially when the data manifest heterogeneities that are difficult to account for mathematically. One particular example occurs in cell biology, where the membrane-bound regulatory protein RhoA interacts with the filamentous actin cortex in an activator–inhibitor loop. Though this core biochemical circuit is conserved across multiple cell types in different organisms, it produces different patterns of RhoA activity in different contexts, from traveling waves in starfish to transient pulses in Caenorhabditis elegans . To understand how this variation emerges, we develop an activator–inhibitor model that accounts explicitly for actin assembly and heterogeneity. By fitting the model to summary statistics of experimental data, subject to known parameter constraints, we show that F-actin assembly dynamics tune the spatiotemporal patterns of RhoA activity. A minimal representation of these dynamics reveals how directional transport (via polymerization) combines with stochasticity in F-actin number and orientation to produce the observed patterns. This work sheds light on how phenotypic diversity arises from heterogeneity and anisotropy, with important implications for the next generation of activator–inhibitor models.

  PublisherOA PDFDOI

• Microscopic Control of Cortical Flows in Polarized <i>C. elegans</i> Zygotes

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-01-13 · 1 citations

  preprintSenior author

  Abstract Cell polarization, migration, and cytokinesis rely on flows of the cell cortex, a network of actin filaments, cross-linkers, and motors beneath the plasma membrane of animal cells. While actin network architecture, assembly dynamics, and motor activity are known to be important for cortical flows, how their modulation tunes macroscopic flow dynamics remains poorly quantified in vivo . Here, we use quantitative microscopy to constrain agent-based simulations that account for filament assembly, crosslinking, and motor activity. We calibrate the model to reproduce steady-state flows in polarized C. elegans zygotes and then challenge it to predict the results of RNA interference (RNAi) experiments. Our model predicts, and experiments largely confirm, a biphasic dependence of flow speed on microscopic rates of actin filament assembly and crosslinking. This biphasic dependence reflects a competition between the tendencies of perturbations to disrupt both transmission of and resistance to cortical forces. Our results provide new insights into how variations in microscopic features shape the emergent dynamics of the cell cortex. By establishing a well-calibrated model of cortical flow in a highly tractable model cell, we also provide a foundation for future studies of microscopic origins and biological control of cortical contractility and flow in vivo .

  PublisherDOI

• Author response: Spectral decomposition unlocks ascidian morphogenesis

  2025-04-15

  peer-reviewOpen access

  Describing morphogenesis generally consists in aggregating the multiple high resolution spatiotemporal processes involved into reproducible low dimensional morphological processes consistent across individuals of the same species or group. In order to achieve this goal, biologists often have to submit movies issued from live imaging of developing embryos either to a qualitative analysis or to basic statistical analysis. These approaches, however, present noticeable drawbacks, as they can be time consuming, hence unfit for scale, and often lack standardisation and a firm foundation. In this work, we leverage the power of a continuum mechanics approach and flexibility of spectral decompositions to propose a standardised framework for automatic detection and timing of morphological processes. First, we quantify whole-embryo scale shape changes in developing ascidian embryos by statistically estimating the strain-rate tensor field of its time-evolving surface without the requirement of cellular segmentation and tracking. We then apply to this data spectral decomposition in space using spherical harmonics and in time using wavelets transforms. These transformations result in the identification of the principal dynamical modes of ascidian embryogenesis and the automatic unveiling of its blueprint in the form of scalograms that tell the story of development in ascidian embryos.

  PublisherDOI

• Author response: Spectral decomposition unlocks ascidian morphogenesis

  2025-06-16

  peer-reviewOpen access
  PublisherDOI

• Spectral decomposition unlocks ascidian morphogenesis

  eLife · 2025-04-15

  preprintOpen access

  Abstract Describing morphogenesis generally consists in aggregating the multiple high resolution spatiotemporal processes involved into reproducible low dimensional morphological processes consistent across individuals of the same species or group. In order to achieve this goal, biologists often have to submit movies issued from live imaging of developing embryos either to a qualitative analysis or to basic statistical analysis. These approaches, however, present noticeable drawbacks, as they can be time consuming, hence unfit for scale, and often lack standardisation and a firm foundation. In this work, we leverage the power of a continuum mechanics approach and flexibility of spectral decompositions to propose a standardised framework for automatic detection and timing of morphological processes. First, we quantify whole-embryo scale shape changes in developing ascidian embryos by statistically estimating the strain-rate tensor field of its time-evolving surface without the requirement of cellular segmentation and tracking. We then apply to this data spectral decomposition in space using spherical harmonics and in time using wavelets transforms. These transformations result in the identification of the principal dynamical modes of ascidian embryogenesis and the automatic unveiling of its blueprint in the form of scalograms that tell the story of development in ascidian embryos.

  PublisherDOI

Recent grants

• Mechanistic origins and dynamic control of epithelial zippering and neural tube closure

  NIH · $1.6M · 2016–2022

• Dynamics and regulation of actomyosin contractility in the C. elegans embryo

  NIH · $2.9M · 2011–2022

Frequent coauthors

• Pierre‐François Lenne

  Centre National de la Recherche Scientifique

  16 shared

• Margaret L. Gardel

  Chicago Institute for Psychoanalysis

  13 shared

• François Robin

  12 shared

• Patrick Lemaire

  Université de Montpellier

  9 shared

• Michael F. Staddon

  Max Planck Institute for the Physics of Complex Systems

  9 shared

• Samantha Stam

  University of Utah

  8 shared

• Shiladitya Banerjee

  Carnegie Mellon University

  7 shared

• Thomas Lecuit

  7 shared

Labs

• Munro LabPI

Education

• Ph.D., Cell and Developmental Biology

  University of Washington

  2000

• B.A., Mathematics and Biology

  Hampshire College

  1987

• Other, Cell Biology

  Fred Hutchison Cancer Research Center

  2002