About

Professor Jason Haugh leads a research group within the Department of Chemical and Biomolecular Engineering at NC State University. His lab employs a quantitative approach to investigate the molecular mechanisms that regulate the behavior and function of living cells, focusing on the field of signal transduction. The research conducted in the Haugh Lab encompasses several key areas including quantifying signaling networks with an emphasis on pathway crosstalk and feedback regulation, directed cell migration through the integration of signaling, adhesion, and cytoskeletal dynamics, biophysical modeling and simulation, as well as receptor endocytosis and compartmentalized intracellular signaling. Through these studies, Professor Haugh's group aims to deepen the understanding of cellular signaling processes that govern cell function and behavior.

Research topics

• Biology
• Cell biology
• Chemistry
• Biochemistry

Selected publications

• A phase field model with stochastic input simulates cellular gradient sensing, morphodynamics, and fidelity of haptotaxis

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-03-13

  articleOpen accessSenior authorCorresponding

  Haptotaxis is an understudied form of directed cell migration in which movements are biased by gradients of immobilized ligands. For example, fibroblasts and other mesenchymal cells sense and respond to gradients of extracellular matrix (ECM) composition, which is relevant during tissue morphogenesis and repair. As a step towards understanding how haptotactic gradients spatially bias cell adhesion, intracellular signal transduction, and cytoskeletal dynamics, we formulated a phase field model of whole-cell migration, in which the occupancy of potential adhesion sites changes stochastically with time. With careful assignment of parameter values, the model predicts significant haptotactic bias for adhesion-site gradient steepness of a few percent across the cell. We then used the model to predict how the cell's removal of surface-bound ECM ligand (as observed in experiment) and/or the presence of a competing, chemotactic gradient influence(s) haptotactic fidelity. An emergent principle is that gains in directional persistence naturally offset losses of directional bias, at the cost of greater cell-to-cell heterogeneity of the response. In the case of orthogonally oriented gradients, this offset manifests as a remarkable robustness of the multi-cue response.

  PublisherOA PDFDOI

• Optogenetic control of PLC-γ1 activity directs cell motility

  The Journal of Cell Biology · 2026-04-08

  articleSenior author

  Phospholipase C-γ1 (PLC-γ1) signaling is required for mesenchymal chemotaxis, but is it sufficient to bias motility? PLC-γ1 enzyme activity is basally autoinhibited, and light-controlled membrane recruitment of wild-type PLC-γ1 (OptoPLC-γ1) in Plcg1-null fibroblasts does not trigger lipid hydrolysis, complicating efforts to isolate its contribution. Utilizing cancer-associated mutations to investigate the regulatory logic of PLC-γ1, we demonstrate that a hallmark of enzyme activity, phosphorylated Tyr783, is not a proxy for activity level, but is rather a marker of dysregulated autoinhibition. Accordingly, OptoPLC-γ1 with a deregulating mutation (P867R, S345F, or D1165H) exhibits elevated phosphorylation, and membrane localization of such is sufficient to activate substrate hydrolysis and concomitant motility responses. In particular, local recruitment of OptoPLC-γ1 S345F polarizes cell motility and migration on demand. This response is spatially dose-sensitive and only partially reduced by blocking canonical PLC-γ1 signaling, yet is lipase-dependent. Our findings reframe the interpretation of PLC-γ1 regulation and demonstrate that local activation of PLC-γ1 is sufficient to direct cell motility.

  PublisherDOI

• In Memoriam: Robert M. Kelly (1953–2026)

  Applied and Environmental Microbiology · 2026-04-30

  articleOpen access

  ABSTRACT The chemical and biochemical engineering, microbiology, and biotechnology communities deeply mourn the passing of Dr. Robert M. Kelly, the Alcoa Professor of Chemical and Biomolecular Engineering and Director of the Biotechnology Program at NC State University. A towering pioneer in the biology of extremophiles, an esteemed educator and mentor, and a dedicated editor for Applied and Environmental Microbiology (AEM), Bob leaves behind an extraordinary legacy that reshaped our understanding of life at high temperatures.

  PublisherDOI

• Topologically-based parameter inference for agent-based model selection from spatiotemporal cellular data

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-06-15

  preprintOpen access

  Abstract Advances in spatiotemporal single-cell imaging have enabled detailed observations of cell population dynamics and intercellular interactions. However, translating these rich data sets into mechanistic insight remains a significant challenge. Agent-based models (ABMs) are a bottom-up computational framework for investigating the emergent behavior of cell populations that can arise from rules defining the interactions between individual neighboring cells, while topological data analysis (TDA) provides robust descriptors of spatial organization. We present TOPAZ (TOpologically-based Parameter inference for Agent-based model optimiZation), a computational pipeline that integrates TDA with approximate Bayesian computation (ABC), approximate approximate Bayesian computation (AABC), and Bayesian model selection to identify biologically plausible ABMs from spatiotemporal cellular data. TOPAZ uses persistent homology to quantify spatial features of cell trajectories and combines this topological information with parameter inference via ABC and AABC and model comparison using the Bayesian information criterion. We validate TOPAZ using simulations of collective fibroblast movement, demonstrating its ability to accurately recover model parameters and distinguish between a baseline ABM and an extended model that incorporates alignment interactions. Our results and open-source code demonstrate the utility of TOPAZ as a extensible framework for mechanistic inference and model discrimination in spatial single-cell analysis. Author summary Understanding how individual cells coordinate to produce complex collective behaviors is a major challenge in computational biology, especially with the increasing availability of high-resolution, spatiotemporal single-cell data. While agent-based models (ABMs) offer a flexible framework for simulating cell behaviors and interactions, they are often difficult to calibrate and compare. Topological data analysis (TDA), on the other hand, captures spatial organization in a robust and scale-invariant way but lacks mechanistic interpretability. In this work, we present TOPAZ (TOpologically-based Parameter inference for Agent-based model optimiZation), a novel computational pipeline that integrates TDA with approximate Bayesian computation, approximate approximate Bayesian computation, and Bayesian model selection to infer biologically meaningful parameters and identify the most plausible ABM from spatiotemporal cellular data. We benchmark TOPAZ using synthetic data from ABMs of collective cell movement in dense fibroblast populations. Our results show that TOPAZ can distinguish between competing mechanistic hypotheses, namely the presence or absence of alignment interactions among neighboring cells. This approach provides a powerful and extensible framework for model inference and selection with the potential to enable deeper insights into the mechanisms driving complex emergent behaviors in cell populations.

  PublisherDOI

• CD44 and Ezrin restrict EGF receptor mobility to generate a novel spatial arrangement of cytoskeletal signaling modules driving bleb-based migration

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-01-01 · 4 citations

  preprintOpen access

  Cells under high confinement form highly polarized hydrostatic pressure-driven, stable leader blebs that enable efficient migration in low adhesion, environments. Here we investigated the basis of the polarized bleb morphology of metastatic melanoma cells migrating in non-adhesive confinement. Using high-resolution time-lapse imaging and specific molecular perturbations, we found that EGF signaling via PI3K stabilizes and maintains a polarized leader bleb. Protein activity biosensors revealed a unique EGFR/PI3K activity gradient decreasing from rear-to-front, promoting PIP3 and Rac1-GTP accumulation at the bleb rear, with its antagonists PIP2 and RhoA-GTP concentrated at the bleb tip, opposite to the front-to-rear organization of these signaling modules in integrin-mediated mesenchymal migration. Optogenetic experiments showed that disrupting this gradient caused bleb retraction, underscoring the role of this signaling gradient in bleb stability. Mathematical modeling and experiments identified a mechanism where, as the bleb initiates, CD44 and ERM proteins restrict EGFR mobility in a membrane-apposed cortical actin meshwork in the bleb rear, establishing a rear-to-front EGFR-PI3K-Rac activity gradient. Thus, our study reveals the biophysical and molecular underpinnings of cell polarity in bleb-based migration of metastatic cells in non-adhesive confinement, and underscores how alternative spatial arrangements of migration signaling modules can mediate different migration modes according to the local microenvironment.

  PublisherDOI

• Optogenetic control of PLC-γ1 activity directs cell motility

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-10-11

  preprintOpen accessSenior authorCorresponding

  ABSTRACT Phospholipase C-γ1 (PLC-γ1) signaling is required for mesenchymal chemotaxis, but is it sufficient to bias motility? PLC-γ1 enzyme activity is basally autoinhibited, and light-controlled membrane recruitment of wild-type PLC-γ1 (OptoPLC-γ1) in Plcg1- null fibroblasts does not trigger lipid hydrolysis, complicating efforts to isolate its contribution. Utilizing cancer-associated mutations to investigate the regulatory logic of PLC-γ1, we demonstrate that a hallmark of enzyme activity, phosphorylated Tyr783 (pTyr783), is not a proxy for activity level, but is rather a marker of dysregulated autoinhibition. Accordingly, OptoPLC-γ1 with a deregulating mutation (P867R, S345F, or D1165H) exhibits elevated phosphorylation, and membrane localization of such is sufficient to activate substrate hydrolysis and concomitant motility responses. In particular, local recruitment of OptoPLC-γ1 S345F polarizes cell motility and migration on demand. This response is spatially dose-sensitive and only partially reduced by blocking canonical PLC-γ1 signaling yet is lipase-dependent. Our findings reframe the interpretation of PLC-γ1 regulation and demonstrate that local activation of PLC-γ1 is sufficient to direct cell motility.

  PublisherOA PDFDOI

• Quantifying collective motion patterns in mesenchymal cell populations using topological data analysis and agent-based modeling

  Mathematical Biosciences · 2024-02-17 · 9 citations

  articleOpen access
  PublisherOA PDFDOI

• G-actin diffusion is insufficient to achieve F-actin assembly in fast-treadmilling protrusions

  Biophysical Journal · 2023-08-28 · 3 citations

  articleOpen accessSenior authorCorresponding
  PublisherOA PDFDOI

• Semi-autonomous wound invasion via matrix-deposited, haptotactic cues

  Journal of Theoretical Biology · 2023-04-22 · 1 citations

  articleOpen accessSenior authorCorresponding
  PublisherOA PDFDOI

• On the inference of ERK signaling dynamics from protein biosensor measurements

  Molecular Biology of the Cell · 2023-03-08 · 8 citations

  articleOpen accessSenior author

  The extracellular signal-regulated kinase (ERK) signaling pathway plays prominent roles in cell growth, proliferation, and differentiation. ERK signaling is dynamic, involving phosphorylation/dephosphorylation, nucleocytoplasmic shuttling, and interactions with scores of protein substrates in the cytosol and in the nucleus. Live-cell fluorescence microscopy using genetically encoded ERK biosensors offers the potential to infer those dynamics in individual cells. In this study, we have monitored ERK signaling using four commonly used translocation- and Förster resonance energy transfer-based biosensors in a common cell stimulation context. Consistent with previous reports, we found that each biosensor responds with unique kinetics; it is clear that there is not a single dynamic signature characterizing the complexity of ERK phosphorylation, translocation, and kinase activity. In particular, the widely adopted ERK Kinase Translocation Reporter (ERKKTR) gives a readout that reflects ERK activity in both compartments. Mathematical modeling offers an interpretation of the measured ERKKTR kinetics, in relation to cytosolic and nuclear ERK activity, and suggests that biosensor-specific dynamics substantially influence the measured output.

  PublisherOA PDFDOI

Recent grants

• Metastability of Cell Migration Polarity

  NSF · $340k · 2011–2015

• Signaling Vector Analysis of Cell Migration

  NSF · $300k · 2008–2012

• Multi-cue Guidance of Mesenchymal Cell Migration

  NIH · $1.2M · 2021–2027

• NC State Molecular Biotechnology Training Program (MBTP)

  NIH · $2.3M · 2020–2030

• NIH Grant R21GM074711

  NIH · $351k · 2010

Frequent coauthors

• James E. Bear

  University of North Carolina at Chapel Hill

  45 shared

• Sreeja B. Asokan

  23 shared

• Heath E. Johnson

  Princeton University

  15 shared

• Jeremy D. Rotty

  Unifor

  12 shared

• Tobias Meyer

  Cornell University

  11 shared

• I Schneider

  Iowa State University

  10 shared

• Douglas A. Lauffenburger

  Massachusetts Institute of Technology

  10 shared

• Erik S. Welf

  The University of Texas Southwestern Medical Center

  10 shared

Education

• PhD, Chemical Engineering

  Massachusetts Institute of Technology

  1999

• BS, Chemical Engineering

  North Carolina State University

  1994