Megan E. Brasch

Automated, contour-based tracking and analysis of cell behaviour over long time scales in environments of varying complexity and cell density

Understanding single and collective cell motility in model environments is foundational to many current research efforts in biology and bioengineering. To elucidate subtle differences in cell behaviour despite cell-to-cell variability, we introduce an algorithm for tracking large numbers of cells for long time periods and present a set of physics-based metrics that quantify differences in cell trajectories. Our algorithm, termed automated contour-based tracking for in vitro environments (ACTIVE), was designed for adherent cell populations subject to nuclear staining or transfection. ACTIVE is distinct from existing tracking software because it accommodates both variability in image intensity and multi-cell interactions, such as divisions and occlusions. When applied to low-contrast images from live-cell experiments, ACTIVE reduced error in analysing cell occlusion events by as much as 43% compared with a benchmark-tracking program while simultaneously tracking cell divisions and resulting daughter–daughter cell relationships. The large dataset generated by ACTIVE allowed us to develop metrics that capture subtle differences between cell trajectories on different substrates. We present cell motility data for thousands of cells studied at varying densities on shape-memory-polymer-based nanotopographies and identify several quantitative differences, including an unanticipated difference between two ‘control’ substrates. We expect that ACTIVE will be immediately useful to researchers who require accurate, long-time-scale motility data for many cells.

How Escherichia coli lands and forms cell clusters on a surface: a new role of surface topography.

Bacterial response to surface topography during biofilm formation was studied using 5 μm tall line patterns of poly (dimethylsiloxane) (PDMS). Escherichia coli cells attached on top of protruding line patterns were found to align more perpendicularly to the orientation of line patterns when the pattern narrowed. Consistently, cell cluster formation per unit area on 5 μm wide line patterns was reduced by 14-fold compared to flat PDMS. Contrasting the reduced colony formation, cells attached on narrow patterns were longer and had higher transcriptional activities, suggesting that such unfavorable topography may present a stress to attached cells. Results of mutant studies indicate that flagellar motility is involved in the observed preference in cell orientation on narrow patterns, which was corroborated by the changes in cell rotation pattern before settling on different surface topographies. These findings led to a set of new design principles for creating antifouling topographies, which was validated using 10 μm tall hexagonal patterns.

How Bacteria Respond to Material Stiffness during Attachment: A Role of Escherichia coli Flagellar Motility

Material stiffness has been shown to have potent effects on bacterial attachment and biofilm formation, but the mechanism is still unknown. In this study, response to material stiffness by Escherichia coli during attachment was investigated with biofilm assays and cell tracking using the Automated Contour-base Tracking for in Vitro Environments (ACTIVE) computational algorithm. By comparing the movement of E. coli cells attached on poly(dimethylsiloxane) (PDMS) surfaces of different Youngs moduli (0.1 and 2.6 MPa, prepared by controlling the degree of cross-linking) using ACTIVE, attached cells on stiff surfaces were found more motile during early stage biofilm formation than those on soft surfaces. To investigate if motility is important to bacterial response to material stiffness, we compared E. coli RP437 and its isogenic mutants of flagellar motor (motB) and synthesis of flagella (fliC) and type I fimbriae (fimA) for attachment on 0.1 and 2.6 MPa PDMS surfaces. The motB mutant exhibited defects in response to PDMS stiffness (based on cell counting and tracking with ACTIVE), which was recovered by complementing the motB gene. Unlike motB results, mutants of fliC and fimA did not show significant defects on both face-up and face-down surfaces. Collectively, these findings suggest that E. coli cells can actively respond to material stiffness during biofilm formation, and motB is involved in this response.

Contour-Based Algorithm for Tracking Cells and Cell-Material Analyses

Cellular tracking has been employed to investigate complex cell-cell and cell-material interactions that play critical roles in tissue development and disease progression. Tracking is often performed manually, however limitations associated with manual tracking make it impractical for tracking dense populations of cells. To address these limitations, several automated tracking algorithms have been developed, buy most of these algorithms are incapable of tracking cells after occlusion events or cell divisions. Here we have developed a custom algorithm in MATLAB that employs a contour-based segmentation approach to identify and track cell divisions and occlusion events. The algorithm further analyzes cell tracks during occlusion events using a cost analysis to detect and relabel mislabeled cells.

Shape memory activation can affect cell seeding of shape memory polymer scaffolds designed for tissue engineering and regenerative medicine

The ability of a three-dimensional scaffold to support cell seeding prior to implantation is a critical criterion for many scaffold-based tissue engineering and regenerative medicine strategies. Shape memory polymer functionality may present important new opportunities and challenges in cell seeding, but the extent to which shape memory activation can positively or negatively affect cell seeding has yet to be reported. The goal of this study was to determine whether shape memory activation can affect cell seeding. The hypothesis was that shape memory activation of porous scaffolds during cell seeding can affect both the number of cells seeded in a scaffold and the distribution (in terms of average infiltration distance) of cells following seeding. Here, we used a porous shape memory foam scaffold programmed to expand when triggered to study cell number and average cell infiltration distance following shape memory activation. We found that shape memory activation can affect both the number of cells and the average cell infiltration distance. The effect was found to be a function of rate of shape change and scaffold pore interconnectivity. Magnitude of shape change had no effect. Only reductions in cell number and infiltration distance (relative to control and benchmark) were observed. The findings suggest that strategies for tissue engineering and regenerative medicine that involve shape memory activation in the presence of a cell-containing medium in vitro or in vivo should consider how recovery rate and scaffold pore interconnectivity may ultimately impact cell seeding.Graphical abstract

Active surface wrinkling influences cell migration behavior and control

Dynamic reorganization of a cells local microenvironment has been shown to critically alter migration, adhesion, and morphological behaviors in vivo during development, wound healing, and disease. While static microenvironments with patterned topographies, stiffness variations, or chemical gradients have been used to characterize cell responses in vitro, they are incapable of capturing the dynamic functionality of extracellular matrix naturally seen in the body. Here, we use a thermally responsive class of materials, shape memory polymers (SMPs), to dynamically manipulate the topographical environment cells experience. By providing physical manipulation of the microenvironment, we demonstrate the ability to control cell migratory behavior in response to a dynamic topographical change provided by SMPs.

A contour-based particle tracking system for the study of cell migratory behavior

Due to a recent focus on cell based therapies in biomedical applications, the ability to accurately track cellular behavior has become an increasingly crucial research tool. Cell motility is of particular importance as it influences basic cellular interactions, effecting macroscale processes such as general tissue development, wound healing, and disease progression. Traditional particle tracking systems focus on intensity thresholds as a means of identifying particles and removing noise. This work presents a contour-based particle tracking algorithm capable of identifying and sorting cells based on nuclear stained images. The two functions presented act cohesively to accurately identify individual cells as particles, capitalizing on a new technique for more accurate depiction of variably stained cells. Based on full-width half maximum theorem fitting, preliminary results demonstrate that this tool has strong potential for use in cell based biomedical applications.