Recapitulation and Modulation of the Cellular Architecture of a User-Chosen Cell of Interest Using Cell-Derived, Biomimetic Patterning

cytoNet: Spatiotemporal network analysis of cell communities

We introduce cytoNet, a cloud-based tool to characterize cell populations from microscopy images. cytoNet quantifies spatial topology and functional relationships in cell communities using principles of network science. Capturing multicellular dynamics through graph features, cytoNet also evaluates the effect of cell-cell interactions on individual cell phenotypes. We demonstrate cytoNet’s capabilities in four case studies: 1) characterizing the temporal dynamics of neural progenitor cell communities during neural differentiation, 2) identifying communities of pain-sensing neurons in vivo, 3) capturing the effect of cell community on endothelial cell morphology, and 4) investigating the effect of laminin α4 on perivascular niches in adipose tissue. The analytical framework introduced here can be used to study the dynamics of complex cell communities in a quantitative manner, leading to a deeper understanding of environmental effects on cellular behavior. The versatile, cloud-based format of cytoNet makes the image analysis framework accessible to researchers across domains.

Fabrication and Implementation of a Reference-Free Traction Force Microscopy Platform

Quantifying cell-induced material deformation provides useful information concerning how cells sense and respond to the physical properties of their microenvironment. While many approaches exist for measuring cell-induced material strain, here we provide a methodology for monitoring strain with sub-micron resolution in a reference-free manner. Using a two-photon activated photolithographic patterning process, we demonstrate how to generate mechanically and bio-actively tunable synthetic substrates containing embedded arrays of fluorescent fiducial markers to easily measure three-dimensional (3D) material deformation profiles in response to surface tractions. Using these substrates, cell tension profiles can be mapped using a single 3D image stack of a cell of interest. Our goal with this methodology is to make traction force microscopy a more accessible and easier to implement tool for researchers studying cellular mechanotransduction processes, especially newcomers to the field.

TISMorph: A tool to quantify texture, irregularity and spreading of single cells

A number of recent studies have shown that cell shape and cytoskeletal texture can be used as sensitive readouts of the physiological state of the cell. However, utilization of this information requires the development of quantitative measures that can describe relevant aspects of cell shape. In this paper we develop a toolbox, TISMorph, that calculates a set of quantitative measures to address this need. Some of the measures introduced here have been used previously, while others are new and have desirable properties for shape and texture quantification of cells. These measures, broadly classifiable into the categories of textural, irregularity and spreading measures, are tested by using them to discriminate between osteosarcoma cell lines treated with different cytoskeletal drugs. We find that even though specific classification tasks often rely on a few measures, these are not the same between all classification tasks, thus requiring the use of the entire suite of measures for classification and discrimination. We provide detailed descriptions of the measures, as well as the TISMorph package to implement them. Quantitative morphological measures that capture different aspects of cell morphology will help enhance large-scale image-based quantitative analysis, which is emerging as a new field of biological data.

Reference-Free Traction Force Microscopy Platform Fabricated via Two-Photon Laser Scanning Lithography Enables Facile Measurement of Cell-Generated Forces

Cells sense and respond to the physical nature of their microenvironment by mechanically probing their surroundings via cytoskeletal contractions. The material response to these stresses can be measured via traction force microscopy (TFM). Traditional TFM platforms present several limitations including variable spatial resolution, difficulty in attaining the full three-dimensional (3D) deformation/stress profile, and the requirement to remove or relax the cells being measured to determine the zero-stress state. To overcome these limitations, we developed a two-photon, photochemical coupling approach to fabricate a new TFM platform that provides high-resolution control over the 3D placement of fluorescent fiducial markers for facile measurement of cell-generated shear and normal components of traction forces. The highly controlled placement of the 3D marker array provides a built-in, zero stress state eliminating the need to perturb the cells being measured while also providing increased throughput. Using this platform, we discovered that the magnitude of cell-generated shear and normal force components are linked both spatially and temporally. The facile nature and increased throughput of measuring cell-generated forces afforded by this new platform will be useful to the mechanotransduction community and others.

Hierarchical Design of Tissue Regenerative Constructs

The worldwide shortage of organs fosters significant advancements in regenerative therapies. Tissue engineering and regeneration aim to supply or repair organs or tissues by combining material scaffolds, biochemical signals, and cells. The greatest challenge entails the creation of a suitable implantable or injectable 3D macroenvironment and microenvironment to allow for ex vivo or in vivo cell-induced tissue formation. This review gives an overview of the essential components of tissue regenerating scaffolds, ranging from the molecular to the macroscopic scale in a hierarchical manner. Further, this review elaborates about recent pivotal technologies, such as photopatterning, electrospinning, 3D bioprinting, or the assembly of micrometer-scale building blocks, which enable the incorporation of local heterogeneities, similar to most native extracellular matrices. These methods are applied to mimic a vast number of different tissues, including cartilage, bone, nerves, muscle, heart, and blood vessels. Despite the tremendous progress that has been made in the last decade, it remains a hurdle to build biomaterial constructs in vitro or in vivo with a native-like structure and architecture, including spatiotemporal control of biofunctional domains and mechanical properties. New chemistries and assembly methods in water will be crucial to develop therapies that are clinically translatable and can evolve into organized and functional tissues.

Shrinkage Clustering: a fast and size-constrained clustering algorithm for biomedical applications

Background

Many common clustering algorithms require a two-step process that limits their efficiency. The algorithms need to be performed repetitively and need to be implemented together with a model selection criterion. These two steps are needed in order to determine both the number of clusters present in the data and the corresponding cluster memberships. As biomedical datasets increase in size and prevalence, there is a growing need for new methods that are more convenient to implement and are more computationally efficient. In addition, it is often essential to obtain clusters of sufficient sample size to make the clustering result meaningful and interpretable for subsequent analysis.

Results

We introduce Shrinkage Clustering, a novel clustering algorithm based on matrix factorization that simultaneously finds the optimal number of clusters while partitioning the data. We report its performances across multiple simulated and actual datasets, and demonstrate its strength in accuracy and speed applied to subtyping cancer and brain tissues. In addition, the algorithm offers a straightforward solution to clustering with cluster size constraints.

Conclusions

Given its ease of implementation, computing efficiency and extensible structure, Shrinkage Clustering can be applied broadly to solve biomedical clustering tasks especially when dealing with large datasets.

Fundamentals of Laser-Based Hydrogel Degradation and Applications in Cell and Tissue Engineering

The cell and tissue engineering fields have profited immensely through the implementation of highly structured biomaterials. The development and implementation of advanced biofabrication techniques have established new avenues for generating biomimetic scaffolds for a multitude of cell and tissue engineering applications. Among these, laser-based degradation of biomaterials is implemented to achieve user-directed features and functionalities within biomimetic scaffolds. This review offers an overview of the physical mechanisms that govern laser-material interactions and specifically, laser-hydrogel interactions. The influences of both laser and material properties on efficient, high-resolution hydrogel degradation are discussed and the current application space in cell and tissue engineering is reviewed. This review aims to acquaint readers with the capability and uses of laser-based degradation of biomaterials, so that it may be easily and widely adopted.

Fabrication and characterization of cell sheets using methylcellulose and PNIPAAm thermoresponsive polymers: A comparison Study

Culturing cells on thermoresponsive polymers enables cells to be harvested as an intact cell sheet without disrupting the extracellular matrix or compromising cell-cell junctions. Previously, cell sheet fabrication methods using methylcellulose (MC) gel and PNIPAAm were independently demonstrated. In this study, MC and PNIPAAm fabrication methods are detailed and the resulting cell sheets characterized in parallel studies for direct comparison of human adipose derived stromal/stem cell (hASCs) sheet formation, cell morphology, viability, proliferation, and osteogenic potential over 21 days. A cell viability study revealed that hASCs in MC and PNIPAAm cell sheets remained viable for 21 days and proliferated until confluency. Osteogenic cell sheets exhibited upregulation of alkaline phosphatase (ALP) at day 7, as well as calcium deposition at 21 days. Additionally, expression of osteocalcin (OCN), a late-stage marker of osteogenesis, was quantified at days 14 and 21 using RT-PCR. OCN was upregulated in MC cell sheets at day 14 and PNIPAAm cell sheets at days 14 and 21. These results indicate that hASCs formed into cell sheets commit to an osteogenic lineage when cultured in osteogenic conditions. Cell sheets composed of hASCs may be used for further studies of hASC differentiation or surgical delivery of undifferentiated cells to defect sites. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 105A: 1346-1354, 2017.

Image-guided, Laser-based Fabrication of Vascular-derived Microfluidic Networks

This detailed protocol outlines the implementation of image-guided, laser-based hydrogel degradation for the fabrication of vascular-derived microfluidic networks embedded in PEGDA hydrogels. Here, we describe the creation of virtual masks that allow for image-guided laser control; the photopolymerization of a micromolded PEGDA hydrogel, suitable for microfluidic network fabrication and pressure head-driven flow; the setup and use of a commercially available laser scanning confocal microscope paired with a femtosecond pulsed Ti:S laser to induce hydrogel degradation; and the imaging of fabricated microfluidic networks using fluorescent species and confocal microscopy. Much of the protocol is focused on the proper setup and implementation of the microscope software and microscope macro, as these are crucial steps in using a commercial microscope for microfluidic fabrication purposes that contain a number of intricacies. The image-guided component of this technique allows for the implementation of 3D image stacks or user-generated 3D models, thereby allowing for creative microfluidic design and for the fabrication of complex microfluidic systems of virtually any configuration. With an expected impact in tissue engineering, the methods outlined in this protocol could aid in the fabrication of advanced biomimetic microtissue constructs for organ- and human-on-a-chip devices. By mimicking the complex architecture, tortuosity, size, and density of in vivo vasculature, essential biological transport processes can be replicated in these constructs, leading to more accurate in vitro modeling of drug pharmacokinetics and disease.

Fabrication of 3D Biomimetic Microfluidic Networks in Hydrogels

A laser-based hydrogel degradation technique is developed that allows for local control over hydrogel porosity, fabrication of 3D vascular-derived, biomimetic, hydrogel-embedded microfluidic networks, and generation of two intertwining, yet independent, microfluidic networks in a single construct.

Biomimetic Surface Patterning Promotes Mesenchymal Stem Cell Differentiation

Both chemical and mechanical stimuli can dramatically influence cell behavior. By optimizing the signals cells experience, it may be possible to control the behavior of therapeutic cell populations. In this work, biomimetic geometries of adhesive ligands, which recapitulate the morphology of mature cells, are used to direct human mesenchymal stem cell (HMSC) differentiation toward a desired lineage. Specifically, adipocytes cultured in 2D are imaged and used to develop biomimetic virtual masks used in laser scanning lithography to form patterned fibronectin surfaces. The impact of adipocyte-derived pattern geometry on HMSC differentiation is compared to the behavior of HMSCs cultured on square and circle geometries, as well as adipocyte-derived patterns modified to include high stress regions. HMSCs on adipocyte mimetic geometries demonstrate greater adipogenesis than HMSCs on the other patterns. Greater than 45% of all HMSCs cultured on adipocyte mimetic patterns underwent adipogenesis as compared to approximately 19% of cells on modified adipocyte patterns with higher stress regions. These results are attributed to variations in cytoskeletal tension experienced by cells on the different protein micropatterns. The effects of geometry on adipogenesis are mitigated by the incorporation of a cytoskeletal protein inhibitor; exposure to this inhibitor leads to increased adipogenesis on all patterns examined.

Progeny Clustering: A Method to Identify Biological Phenotypes

Estimating the optimal number of clusters is a major challenge in applying cluster analysis to any type of dataset, especially to biomedical datasets, which are high-dimensional and complex. Here, we introduce an improved method, Progeny Clustering, which is stability-based and exceptionally efficient in computing, to find the ideal number of clusters. The algorithm employs a novel Progeny Sampling method to reconstruct cluster identity, a co-occurrence probability matrix to assess the clustering stability, and a set of reference datasets to overcome inherent biases in the algorithm and data space. Our method was shown successful and robust when applied to two synthetic datasets (datasets of two-dimensions and ten-dimensions containing eight dimensions of pure noise), two standard biological datasets (the Iris dataset and Rat CNS dataset) and two biological datasets (a cell phenotype dataset and an acute myeloid leukemia (AML) reverse phase protein array (RPPA) dataset). Progeny Clustering outperformed some popular clustering evaluation methods in the ten-dimensional synthetic dataset as well as in the cell phenotype dataset, and it was the only method that successfully discovered clinically meaningful patient groupings in the AML RPPA dataset.