Dynamics of Complex Biological Systems

At the convergence of physics with biology, our group is motivated both by the desire to gain fundamental insights into the behavior of living systems and by the drive to contribute to the pressing challenges associated with the explosion of quantitative information in medical research.

Our analysis of shape dynamics of migrating cells has led us to discover mechanical waves as a ubiquitous underlying motor in many fast-migrating cells. Another project in the Biodynamics lab is to elucidate how surface chemistry and topography affects migratory machinery, and how internal waves may be harnessed to control cell behavior. We also develop new tools to control the arrangement and dynamics of cell groups via holographic laser tweezers and to investigate the mechanical properties of models of circulating tumor cells. Other projects apply Complex Systems approaches to investigate cancer related biological processes as part of a Cancer Technology interaction between the University of Maryland and the National Cancer Institute. Examples of the many ways studying complex systems provides insight into biological systems are available on this page.

Contact Guidance of Migrating Human Neutrophils on Nanotopographies

Satarupa Das, Previous Postdoctoral Research Associate

We broadly focus on how cells orchestrate diverse chemical and physical signals and forces to control directed migration, a mechanism essential to regulating development, wound healing, and immune cell surveillance. To reach their proper destinations, cells must coordinate with multiple distinct guidance cues, including protrusions, adhesions and retractions. Specifically, our lab focuses on feedback signaling mechanisms that control highly polarized responses to external chemical gradients. Current interests include understanding the mechanism behind how physical forces and biochemical signaling events interact to guide cell movement on nanotopographic surfaces that mimic the extracellular matrix in natural tissue environments.

One of the challenging facets for a cell inside the human body is its ability to travel long distances through changing environments to reach a final destination. Intrinsic to this process are decisions about when to migrate, the paths to be taken, and when to stop: an operation known as “Directional Cell Migration”. The spatial patterning and timing of many intracellular signaling events decide the fate of directed migration. Two important factors that guide cells through different tissue substrates are adhesion structures and the actin cytoskeleton. By combining the expertise of different groups, we expect to develop novel, highly quantitative approaches for the study of dynamic molecular interactions between these factors on different, changing surfaces. We expect that these innovative methods could be readily translated to a diverse array of signaling pathways important to human health.

Supported by the National Institutes of Health

Patterns in Biological Systems
Neutrophils moving along sawtooth nanoridges.

Unidirectional Cell Guidance promoted by Asymmetric Nanotopography

Xiaoyu Sun, Postdoctoral Research Associate
Meghan Driscoll, Former Postdoc

with J. Fourkas (University of Maryland)

Many biological and physiological processes depend upon directed migration of cells, which is typically mediated by chemical gradients, physical gradients, and signal relay. My work focuses on the effect that local topographic asymmetries on the nano/micro-scale have on attempting to guide Dictyostelium discoideum and lamellipod-driven human neutrophils to migrate in single, preferred directions. Given that these asymmetries can be repeated we can thereby attempt to provide directional guidance over arbitrarily large areas. We are currently studying the relationship between the direction and strength of the guidance and the details of the nano/microtopography. We have thus far demonstrated that asymmetric nano/microtopography guides the direction of internal actin polymerization waves and that cells move in the same direction as these waves. The conservation of this mechanism across cell types and the asymmetric shape of many natural scaffolds suggests that actin-wave-based guidance is important in biology and physiology.

X. Sun, et al., "Asymmetric nanotopography biases cytoskeletal dynamics and promotes unidirectional cell guidance", Proceedings of the National Academy of Sciences, 112(41), pp. 12557-12562, 2015.

Supported by the National Institutes of Health

Left: Sixty-frame (2.55-min) space/time plot of actin waves along a ridge composed of asymmetric sawteeth. Top, right: Actin-wave directionality angle histogram. Bottom, right: Average actin flux around a sawtooth.

Contact Guidance of Migrating Human Neutrophils on Nanotopographies

Song Chen, Ph.D. student, Biophysics

Tumor metastasis is the primary cause of cancer-related deaths. The cellular microenvironment, and in particular the extracellular matrix (ECM), has been shown to be important for the dissemination pattern of metastatic cancer cells. The question we aim to address is whether nanotopographic surfaces can trigger changes in cytoskeletal dynamics and induce cancer cells to exhibit distinct dissemination patterns. Inspired by discoveries of texture sensing by neutrophils and Dictyostelium, we hypothesize that contact guidance regulates cancer dissemination by fostering directional cell migration and changing collective cell behavior toward more invasive phenotypes. We study nanotopography-induced contact guidance using a breast cancer progression model and preliminary results indicate that nanoridges can change collective cell migration patterns in a guided way.

Supported by the National Institutes of Health

Cancer Cells on Nanotopographies
Cancer Cells moving on ridges (top) and on a flat surface (bottom).

Understanding Cell-Cell Interaction in Collective Cell Migration with Optical Manipulation Techniques

Chenlu Wang, Alumnus Ph.D. student, Biophysics
Sagar Chowdhury, Alumnus Ph.D. student, Mechanical Engineering

with S.K. Gupta (University of Maryland) and Dr. Carole Parent (National Cancer Institute)

Optical micromanipulation is well suited to study biological objects due to its ability to precisely control the object. The challenge to wide application of optical tweezers in biological micromanipulation is to avoid photodamage caused by high-intensity laser exposure to the manipulated living systems. To reduce photodamage, we have developed various approaches that integrate indirect optical manipulation with robotic planning techniques. By using these approaches, the probability of cell survival increases, so does the ability of cells to maintain shape and wiggle. In addition, our approaches also demonstrate that they allow cell–cell contacts to be formed in a controllable way, while retaining the ability of cells to change shape and move. This allows us to further investigate mechanical interaction through cell-cell contacts during collective cell migration and the interaction between extracellular mechanical guidance and intercellular biochemical signaling.


A. Thakur et al. submitted to IEEE Trans Biomed Eng 2013

S. Chowdhury et al. accepted to IEEE Trans Autom Sci Eng 2013

C. Wang, S. Chowdhury, S.K. Gupta, and W. Losert, J Biomed Opt 2013 [SPIE]

S. Chowdhury et al. IEEE Trans Autom Sci Eng 2012 [IEEE]

Supported by NSF - Cyber-Physical Systems

A,B: Transportation of a yeast cell using the synthesized gripper:
(A) at t = 0 s, the yeast cell is gripped by the gripper.
(B) The gripper ensemble avoids an obstacle by moving in a curved trajectory, while maintaining a safe distance from the obstacle, and then reaches the goal location at t = 21 s.

C,D: Indirect pushing of two Dictyostelium cells allows testing of cell–cell adhesion with controlled cell polarity.
(C) The upper cell is pushed indirectly by the trapped bead through the intermediate bead.
(D) The manipulation stops after 1 min, and the two Dictyostelium cells are able to form head-to-tail contact.

Collective Migration in Cancer Progression

Rachel Lee, Ph.D. student, Physics

with Dr. Carole Parent (National Cancer Institute)

In addition to playing a role in processes such as wound healing and development, collective migration is seen in the progression of diseases such as cancer. As tumor cells become more malignant, they gain the ability to migrate throughout the body; in addition to migrating as individual cells, they have been seen to migrate in vivo as sheets and stands (examples can be seen in the work by Alexander et al. 2008). The collective migration patterns of healthy and malignant cells show noticeable qualitative differences, but there are few tools currently available to quantify these differences.

Using automated image analysis techniques we are able to extract information such as velocities from images of migrating human epithelial cells. Inspired by tools developed to study fluid flows and moving grains of sand, we have quantified the motion of migrating epithelial sheets. We are currently using these tools to understand how the motion of epithelial cells is regulated and how changes in cell migration are linked to metastatic cancer.

R.M. Lee, D.H. Kelley, K.N. Nordstrom, N.T. Ouellette, and W. Losert, New J Phys 2013 [IOP]
R.M. Lee, C.H. Stuelten, C.A. Parent, W. Losert, CSPO 2016 [IOP]

Cell Sheet
A migrating sheet of MCF10A cells overlaid with velocity information derived using particle image velocimetry.

Determination of Cell Shape PhenoTypes Associated with Micro-Environmental Cues and Stem Cell Fates with Machine Learning Based Methodology

Desu Chen, Ph.D. student, Biophysics

with Julian Candia (National Institutes of Health) and Sumona Sarkar (National Institute of Standards and Technology)

Differentiation of stem cells can be guided by their mechanical responses to the environment. It has been found that human bone marrow stromal cells (hBMSCs) develop osteogenic lineage in some polymer scaffold structures in the absence of chemicals while staying in their original states on some other kinds of substrates (Kumar et al. 2011). Morphological responses of hBMSCs to different microenvironments may play a crucial roles in the early stage of this process despite the fact that the chemical signatures of differentiation usually appear much later. In order to understand the correlation between a cell's morphological response to its microenvironment and its differentiation, we quantify the morphological phenotypes of hBMSCs at early stages with multiple shape descriptors and introduce a machine learning algorithm to find the optimal set of shape descriptors for distinguishing cells in different microenvironments. This approach allows us to account for both multi-parametric complexity and biological heterogeneity. The algorithm also identifies individual representative cell shapes that could be used for cell shape templating to control cell function in current and future studies.

Supported by the NIST-UMD Cooperative Agreement

From molecules to cells to organisms: understanding health and disease with multidimensional single-cell methods

Yang Shen, Ph.D. student, Chemical Physics
Julian Candia, Research Associate for the Cancer Technology Partnership

An amazing feature of living systems is that the behavior of organisms is based on the concerted action occurring on a wide range of scales from the molecular to the organismal level. Molecular properties control the function of a cell, and cell ensembles function as organisms. While some operations of a cell can be inferred from the study of its molecules one by one, the overall behavior of a cell is an emergent property that cannot be understood simply based on its components. Similarly, organs and organisms are expected to have emergent properties based on the collective action of the constituent cells that can best be inferred by studies of cell ensembles.

Our goal is to apply and develop a variety of computational and analytical tools to uncover the underlying emergent behavior that links molecules and cells to human health. Our different approaches include dimensional reduction based on singular value decomposition, the perceptron and other machine learning algorithms, and network theory applied to high-throughput multidimensional single-cell data. We expect to gain a better understanding of different disease phenotypes based on single-cell molecular markers (which would improve clinical diagnosis) and link those findings to overexpressed genes within specific disease-related cell subpopulations (which would improve clinical treatment).

Publication: J. Candia et al. PLoS Comput Biol 2013, in press [PLoS] [arXiv]

Supported by a joint appointment from the Department of Physics, University of Maryland (College Park) and the School of Medicine, University of Maryland (Baltimore)

Full-text access to all publications, CV, research interests, and contact information are available here.

(a) Due to cell heterogeneity, single-cell measurements often lead to highly overlapping populations. (b) The novel supercell framework, however, allows us to uncover molecular phenotypes that separate different diseases.

3D Structure Analysis in Biological Systems

Leonard Campanello, Ph.D. student, Physics

with Maria Traver (Postdoc, Uniformed Services University) and Brian Schaefer (Professor, Uniformed Services University)

My research focuses on the extraction, analysis, and visualization of complex, amorphous structures within three dimensional super-resolution images of various types of cells. I am currently studying the role of protein migration, degradation, and co-localization in activated T-cells and the roles that these proteins play in regulating antigen-mediated signaling from the T-cell receptor to the transcription factor, NF-kB. Performing the analysis, aside from the standard image processing, draws on concepts from combinatorics, topology, and graph theory.

Mathematical Modeling in Physics for the Life Sciences

Deborah Hemingway, Ph.D. student, Biophysics

with Joe Redish (University of Maryland)

I am investigating the barriers to using mathematical modeling in physics for the life sciences (IPLS) as part of an exploratory collaborative project with Joe Redish’s Physics Education Research Group. My focus is on researching pre-medical and biology student problem solving amongst a variety of other students; creating analytical tools for describing student resources in the context of the NEXUS/Physics interdisciplinary IPLS course; and developing a set of materials on mathematical modeling.

Cytoskeletal Responses in the Extravasation Stage of Metastasis

Eleanor Ory (EChO), Ph.D. student, Biophysics

with Stuart Martin (University of Maryland School of Medicine)

Although 90% of cancer fatalities are the result of metastasis, the vast majority of cancer research focuses on treating primary tumors. Perhaps the most critical step for successful colonization of a secondary site, extravasation, happens when a cell survives circulation, embeds, and invades new tissue. Extravasation requires that a cell has unbalanced cytoskeletal forces as shown in a phenomena called microtentacles in which tubulin protrusions cause the cell to get embedded in the capillary tubes. Using image analysis techniques and unique experimental approaches like optical stretchers, we aim to better understand the complex interactions between the actin cytoskeleton, myosin, and microtubules and how disruptions in these forces can contribute to metastasis.

Supported by the Department of Defense Breast Cancer Research Program’s Era of Hope Grant

Maryland Day: Welcome to Cells in Motion!

Lab Outreach

As part of the 2013 Maryland Day event, the Losert Lab prepared a video, "Cells in Motion," which was shown in the inflatable Biomolecular Discovery Dome. We also created an interactive demonstration of our cell tracking software where participants were able to track their motion while playing games such as follow the leader. To watch our video or to learn more, visit our Maryland Day page!

University of Maryland


Please contact ljcamp @ umd.edu for updates to this page (last updated December 4th, 2015) and wlosert @ umd.edu for questions about the Dynamics of Complex Systems lab.