Sebastian Sensale, Ph.D.

Research

Our research focuses on developing computational and theoretical approaches to understand and engineer micro- and nano-scale biological systems. We combine statistical mechanics, molecular dynamics simulations, and machine learning to investigate how biological molecules and living organisms behave under confinement and external forces, with applications ranging from biosensing to synthetic biology and toxicology.

Research Areas

• Computational Biophysics
• DNA Nanotechnology
• Nanopore Sensing
• Active Matter

DNA Nanotechnology and Nanodevice Design

A central theme of our work involves understanding the dynamics of DNA origami nanostructures (programmable molecular devices assembled from DNA). We develop theoretical models and computational tools to predict and optimize the behavior of these nanodevices, including their communication speeds, binding kinetics, and response to external stimuli such as electric fields. Our goal is to enable rational design principles for DNA-based sensors, actuators, and computing elements at the molecular scale.

We are currently investigating how confinement and electromagnetic fields can be leveraged to enhance the performance of DNA walkers and origami hinges. This work combines coarse-grained molecular dynamics with analytical theories to bridge timescales from nanoseconds to seconds, providing insights that guide experiments in optimizing these systems for applications in signal amplification and molecular diagnostics.

Nanopore Sensing Technologies

This effort addresses the challenge of characterizing single molecules as they pass through nanoscale pores. We have developed analytical theories that predict the electrical signatures generated during molecular translocation events, enabling the design of next-generation biosensors with improved resolution and specificity.

Our approach integrates non-equilibrium electrokinetics with molecular modeling to understand how ion clouds deform around translocating molecules, creating distinctive resistive signals. These insights have led to optimized impedance-based sensors capable of detecting and characterizing exosomes, nucleic acids, and nanoparticles in microfluidic devices. Current work extends these principles to insulator-based electrokinetic platforms for rapid screening of biological nanocarriers.

Biological Active Matter and Colony Dynamics

Our newest research direction applies concepts from statistical physics and complexity theory to understand collective behavior in biological systems. We are developing multifractal analysis techniques combined with machine learning to characterize pattern formation in C. elegans colonies, seeking universal physical principles that govern self-organization in active matter.

This work involves building agent-based models that connect individual organism behavior to emergent population-level patterns. By integrating microfluidics, automated image analysis, and computational modeling, we aim to develop C. elegans as a living biosensor platform for environmental monitoring applications.

Cytoskeletal Dynamics and Post-Translational Modifications

In collaboration with experimental groups, we investigate the stochastic processes governing microtubule modifications. We developed hybrid Brownian-Monte Carlo models to predict how enzyme activity patterns create spatial heterogeneity in microtubule detyrosination,a key regulator of cellular functions. This multiscale modeling approach connects single-molecule kinetics to cellular-scale organization, providing mechanistic insights into how cells spatially organize their cytoskeleton.

Education

• 2022 Post Doctorate, Mechanical Engineering and Materials Science, Duke University, Durham, NC
• 2020 Ph.D., Bioengineering, University of Notre Dame, Notre Dame, IN
• 2014 B.S., Mathematics, Universidad de la República, Montevideo, Uruguay

Publications & Professional Activity

Selected Publications

Tang Q, Sensale S, Bond C, et al. (2023)
Interplay Between Stochastic Enzyme Activity and Microtubule Stability Drives Detyrosination Enrichment on Microtubule Subsets.
Current Biology 33:1-6.

Wang Y, Sensale S, Pedrozo M, et al. (2023)
Reversible Communication in DNA Origami Devices via Steric Interactions.
ACS Nano 17:9.

Wang C, Sensale S, Pan Z, Senapati S, Chang HC (2021)
Slowing down DNA translocation through solid-state nanopores by edge-field leakage.
Nature Communications 12:1 (Editor's Pick).

Sensale S, Ramshani Z, Senapati S, Chang HC (2021)
Universal Features of Non-equilibrium Ionic Currents through Perm-Selective Membranes: Gating by Charged Nanoparticles/Macromolecules for Robust Biosensing Applications.
J. Phys. Chem. B 125:7 (Cover Article).

Sensale S, Peng Z, Chang HC (2019)
Biphasic signals during nanopore translocation of DNA and nanoparticles due to strong ion cloud deformation.
Nanoscale 11:47.

Professional Activity

• Chair-Elect, American Physical Society Eastern Great Lakes Section (APS EGLS), 2025-Present
• Vice-Chair, American Physical Society Eastern Great Lakes Section (APS EGLS), 2024-2025
• Co-Host and Chair, APS EGLS Fall Meeting 2023
• Reviewer for: Soft Matter, Lab on a Chip, Nanoscale, Langmuir, Physical Biology, National Science Foundation, Maryland Industrial Partnerships Program