Topographical depth reveals contact guidance mechanism distinct from focal adhesion confinement.

Cellular response to the topography of their environment, known as contact guidance, is a crucial aspect to many biological processes yet remains poorly understood. A prevailing model to describe cellular contact guidance involves the lateral confinement of focal adhesions (FA) by topography as an underlying mechanism governing how cells can respond to topographical cues. However, it is not clear how this model is consistent with the well-documented depth-dependent contact guidance responses in the literature. To investigate this model, we fabricated a set of contact guidance chips with lateral dimensions capable of confining focal adhesions and relaxing that confinement at various depths. We find at the shallowest depth of 330 nm, the model of focal adhesion confinement is consistent with our observations. However, the cellular response at depths of 725 and 1000 nm is inadequately explained by this model. Instead, we observe a distinct reorganization of F-actin at greater depths in which topographically induced cell membrane deformation alters the structure of the cytoskeleton. These results are consistent with an alternative curvature-hypothesis to explain cellular response to topographical cues. Together, these results indicate a confluence of two molecular mechanisms operating at increased induced membrane curvature that govern how cells sense and respond to topography.

Automated cell segmentation for reproducibility in bioimage analysis.

Live-cell imaging is extremely common in synthetic biology research, but its ability to be applied reproducibly across laboratories can be hindered by a lack of standardized image analysis. Here, we introduce a novel cell segmentation method developed as part of a broader Independent Verification & Validation (IV&V) program aimed at characterizing engineered Dictyostelium cells. Standardizing image analysis was found to be highly challenging: the amount of human judgment required for parameter optimization, algorithm tweaking, training and data pre-processing steps forms serious challenges for reproducibility. To bring automation and help remove bias from live-cell image analysis, we developed a self-supervised learning (SSL) method that recursively trains itself directly from motion in live-cell microscopy images without any end-user input, thus providing objective cell segmentation. Here, we highlight this SSL method applied to characterizing the engineered Dictyostelium cells of the original IV&V program. This approach is highly generalizable, accepting images from any cell type or optical modality without the need for manual training or parameter optimization. This method represents an important step toward automated bioimage analysis software and reflects broader efforts to design accessible measurement technologies to enhance reproducibility in synthetic biology research.

Self-supervised machine learning for live cell imagery segmentation.

Segmenting single cells is a necessary process for extracting quantitative data from biological microscopy imagery. The past decade has seen the advent of machine learning (ML) methods to aid in this process, the overwhelming majority of which fall under supervised learning (SL) which requires vast libraries of pre-processed, human-annotated labels to train the ML algorithms. Such SL pre-processing is labor intensive, can introduce bias, varies between end-users, and has yet to be shown capable of robust models to be effectively utilized throughout the greater cell biology community. Here, to address this pre-processing problem, we offer a self-supervised learning (SSL) approach that utilizes cellular motion between consecutive images to self-train a ML classifier, enabling cell and background segmentation without the need for adjustable parameters or curated imagery. By leveraging motion, we achieve accurate segmentation that trains itself directly on end-user data, is independent of optical modality, outperforms contemporary SL methods, and does so in a completely automated fashion-thus eliminating end-user variability and bias. To the best of our knowledge, this SSL algorithm represents a first of its kind effort and has appealing features that make it an ideal segmentation tool candidate for the broader cell biology research community.

Robust optical flow algorithm for general single cell segmentation.

Cell segmentation is crucial to the field of cell biology, as the accurate extraction of single-cell morphology, migration, and ultimately behavior from time-lapse live cell imagery are of paramount importance to elucidate and understand basic cellular processes. In an effort to increase available segmentation tools that can perform across research groups and platforms, we introduce a novel segmentation approach centered around optical flow and show that it achieves robust segmentation of single cells by validating it on multiple cell types, phenotypes, optical modalities, and in-vitro environments with or without labels. By leveraging cell movement in time-lapse imagery as a means to distinguish cells from their background and augmenting the output with machine vision operations, our algorithm reduces the number of adjustable parameters needed for manual optimization to two. We show that this approach offers the advantage of quicker processing times compared to contemporary machine learning based methods that require manual labeling for training, and in most cases achieves higher quality segmentation as well. This algorithm is packaged within MATLAB, offering an accessible means for general cell segmentation in a time-efficient manner.

Interfacing Live Cells with Surfaces: A Concurrent Control Technique for Quantifying Surface Ligand Activity.

Surface ligand activity is a key design parameter for successfully interfacing surfaces with cells─whether in the context of in vitro investigations for understanding cellular signaling pathways or more applied applications in drug delivery and medical implants. Unlike other crucial surface parameters, such as stiffness and roughness, surface ligand activity is typically based on a set of assumptions rather than directly measured, giving rise to interpretations of cell adhesion that can vary with the assumptions made. To fill this void, we have developed a concurrent control technique for directly characterizing in vitro ligand surface activity. Pairs of gold-coated glass chips were biofunctionalized with RGD ligand in a parallel workflow: one chip for in vitro applications and the other for surface plasmon resonance (SPR)-based RGD activity characterization. Recombinant αVß3 integrins were injected over the SPR chip surface as mimics of the cellular-membrane-bound receptors and the resulting binding kinetics parameterized to quantify surface ligand activity. These activity measurements were correlated with cell morphological features, measured by interfacing MDA-MB-231 cells with the in vitro chip surfaces on the live cell microscope. We demonstrate how the interpretation of a cell phenotype based on direct activity measurements can vary markedly from interpretations based on assumed activity. The SPR concurrent control approach has multiple advantages due to the fact that SPR is a standardized technique and has the sensitivity to measure ligand activity across the most relevant range of extracellular surface densities, while the in vitro chip design can be used with all commonly used light microscopy modalities (e.g., phase contrast, DIC, and fluorescence) so that a wide range of phenotypic and molecular markers can be correlated to the ligand surface activity.

Mechanisms of cell damage due to mechanical impact: an in vitro investigation.

The dynamic response of cells when subjected to mechanical impact has become increasingly relevant for accurate assessment of potential blunt injuries and elucidating underlying injury mechanisms. When exposed to mechanical impact, a biological system such as the human skin, brain, or liver is rapidly accelerated, which could result in blunt injuries. For this reason, an acceleration of greater than > 150 g is the most commonly used criteria for head injury. To understand the main mechanism(s) of blunt injury under such extreme dynamic threats, we have developed an innovative experimental method that applies a well-characterized and -controlled mechanical impact to live cells cultured in a custom-built in vitro setup compatible with live cell microscopy. Our studies using fibroblast cells as a model indicate that input acceleration ([Formula: see text]) alone, even when it is much greater than the typical injury criteria, e.g., [Formula: see text] g, does not result in cell damage. On the contrary, we have observed a material-dependent critical pressure value above which a sudden decrease in cell population and cell membrane damage have been observed. We have unambiguously shown that (1) this critical pressure is associated with the onset of cavitation bubbles in a cell culture chamber and (2) the dynamics of cavitation bubbles in the chamber induces localized compressive/tensile pressure cycles, with an amplitude that is considerably greater than the acceleration-induced pressure, to cells. More importantly, the rate of pressure change with time for cavitation-induced pressure is significantly faster (more than ten times) than acceleration-induced pressure. Our in vitro study on the dynamic response of biological systems due to mechanical impact is a crucial step towards understanding potential mechanism(s) of blunt injury and implementing novel therapeutic strategies post-trauma.

Problem of Diminished cRGD Surface Activity and What Can Be Done about It.

RGD peptides play a pivotal role in growing and diverse areas of biological research, ranging from in vitro experiments probing fundamental molecular mechanisms of cell adhesion to more applied in vivo strategies in medical imaging and cancer therapeutics. To better understand the outcomes of RGD-based approaches, we quantified the degree to which cyclic RGD (cRGD) activity is blocked by nonspecific binding of commonly used medium constituents. First, we show that recombinant αVß3 integrins can be used as a highly sensitive cell-free sensor to quantitatively and reliably characterize the activity of cRGD-functionalized surfaces via surface plasmon resonance (SPR). Next, SPR experiments were utilized to measure the extent of blocking of cRGD-functionalized surfaces by the commonly used agents BSA, PLL-g-PEG, and fetal calf serum (FCS)-supplemented media, using recombinant αVß3 integrin as a probe for cRGD binding activity in the presence of blocking agents. All three additives were highly efficient blockers of cRGD activity, as exemplified by cell culture media containing 1% FCS which reduced the cRGD activity by 33-fold. We then developed a strategy to combat these deleterious effects by employing the recombinant integrins as a protective cap. We show that the unblocked cRGD activity can be preserved in the presence of PLL-g-PEG by employing the αVß3 integrin as a removable protective cap, both in cell-free and in vitro experiments. In vitro studies with MDA-MB-231 cells cultured atop cRGD-functionalized surfaces found that cell adhesion and migration prevented by PLL-g-PEG were restored when this protective cap approach was used.

Small-angle light scattering to detect strain-directed collagen degradation in native tissue.

It has been demonstrated that there is a mechanochemical relationship between collagen and collagenolytic enzymes such that increased tensile mechanical strain reduces the enzymatic cutting rate. This mechanochemical relationship has the potential to permit directed remodelling of tissue-engineered constructs in vitro and to shed light on the generation of load-adapted collagen-based connective tissue. In this investigation, we demonstrate that small-angle light scattering (SALS) has the sensitivity to dynamically detect the preferential enzymatic degradation of a subset of unloaded collagen fibrils within differentially loaded native tissue. Detection of the difference in the relative degradation rate of unloaded fibrils versus loaded fibrils was manifested through changes in the spatial distribution of the SALS signal. Specifically, we found a linear increase in the eccentricity of the SALS data that was consistent with preferential retention of the collagen fibrils aligned with the applied tensile strain. We conclude that SALS is simple, inexpensive and may provide a useful optical screening method permitting real-time monitoring of strain-controlled tissue and construct remodelling.