Organizational metrics of interchromatin speckle factor domains: integrative classifier for stem cell adhesion & lineage signaling

High-Throughput Routes to Biomaterials Discovery

Many existing clinical treatments are limited in their ability to completely restore decreased or lost tissue and organ function, an unenviable situation only further exacerbated by a globally aging population. As a result, the demand for new medical interventions has increased substantially over the past 20 years, with the burgeoning fields of gene therapy, tissue engineering, and regenerative medicine showing promise to offer solutions for full repair or replacement of damaged or aging tissues. Success in these fields, however, inherently relies on biomaterials that are engendered with the ability to provide the necessary biological cues mimicking native extracellular matrixes that support cell fate. Accelerating the development of such "directive" biomaterials requires a shift in current design practices toward those that enable rapid synthesis and characterization of polymeric materials and the coupling of these processes with techniques that enable similarly rapid quantification and optimization of the interactions between these new material systems and target cells and tissues. This manuscript reviews recent advances in combinatorial and high-throughput (HT) technologies applied to polymeric biomaterial synthesis, fabrication, and chemical, physical, and biological screening with targeted end-point applications in the fields of gene therapy, tissue engineering, and regenerative medicine. Limitations of, and future opportunities for, the further application of these research tools and methodologies are also discussed.

Cigarette Smoke and E-Cigarette Vapor Dysregulate Osteoblast Interaction With Titanium Dental Implant Surface

The purpose of this study was to determine the possible deleterious effects of e-cigarette vapor on osteoblast interaction with dental implant material. Osteoblasts were cultured onto Ti6Al4V titanium implant disks and were then exposed or not to whole cigarette smoke (CS), as well as to nicotine-rich (NR) or nicotine-free (NF) e-vapor for 15 or 30 minutes once a day for 1, 2, or 3 days, after which time various analyses were performed. Osteoblast growth on the titanium implant disks was found to be significantly (P < .001) reduced following exposure to CS and to the NR and NF e-vapors. Osteoblast attachment to the dental implant material was also dysregulated by CS and the NR and NF e-vapors through a decreased production of adhesion proteins such as F-actin. The effects of CS and e-cigarette vapor on osteoblast growth and attachment were confirmed by reduced alkaline phosphatase (ALP) activity and tissue mineralization. The adverse effects of CS and the NR and NF e-vapors on osteoblast interaction with dental implant material also involved the caspase-3 pathway, as the caspase-3 protein level increased following exposure of the osteoblasts to CS or e-vapor. It should be noted that the adverse effects of CS on osteoblast growth, attachment, ALP, and mineralized degradation were greater than those of the NR and NF e-vapors, although the latter did downregulate osteoblast interaction with the dental implant material. Overall results suggest the need to consider e-cigarettes as a possible contributor to dental implant failure and/or complications.

Engineering Lineage Potency and Plasticity of Stem Cells using Epigenetic Molecules

Stem cells are considered as a multipotent regenerative source for diseased and dysfunctional tissues. Despite the promise of stem cells, the inherent capacity of stem cells to convert to tissue-specific lineages can present a major challenge to the use of stem cells for regenerative medicine. We hypothesized that epigenetic regulating molecules can modulate the stem cell’s developmental program, and thus potentially overcome the limited lineage differentiation that human stem cells exhibit based on the source and processing of stem cells. In this study, we screened a library of 84 small molecule pharmacological agents indicated in nucleosomal modification and identified a sub-set of specific molecules that influenced osteogenesis in human mesenchymal stem cells (hMSCs) while maintaining cell viability in-vitro. Pre-treatment with five candidate hits, Gemcitabine, Decitabine, I-CBP112, Chidamide, and SIRT1/2 inhibitor IV, maximally enhanced osteogenesis in-vitro. In contrast, five distinct molecules, 4-Iodo-SAHA, Scriptaid, AGK2, CI-amidine and Delphidine Chloride maximally inhibited osteogenesis. We then tested the role of these molecules on hMSCs derived from aged human donors and report that small epigenetic molecules, namely Gemcitabine and Chidamide, can significantly promote osteogenic differentiation by 5.9- and 2.3-fold, respectively. Taken together, this study demonstrates new applications of identified small molecule drugs for sensitively regulating the lineage plasticity fates of bone-marrow derived mesenchymal stem cells through modulating the epigenetic profile of the cells.

Architecture in 3D cell culture: An essential feature for in vitro toxicology

Three-dimensional cell culture has the potential to revolutionize toxicology studies by allowing human-based reproduction of essential elements of organs. Beyond the study of toxicants on the most susceptible organs such as liver, kidney, skin, lung, gastrointestinal tract, testis, heart and brain, carcinogenesis research will also greatly benefit from 3D cell culture models representing any normal tissue. No tissue function can be suitably reproduced without the appropriate tissue architecture whether mimicking acini, ducts or tubes, sheets of cells or more complex cellular organizations like hepatic cords. In this review, we illustrate the fundamental characteristics of polarity that is an essential architectural feature of organs for which different 3D cell culture models are available for toxicology studies in vitro. The value of tissue polarity for the development of more accurate carcinogenesis studies is also exemplified, and the concept of using extracellular gradients of gaseous or chemical substances produced with microfluidics in 3D cell culture is discussed. Indeed such gradients-on-a-chip might bring unprecedented information to better determine permissible exposure levels. Finally, the impact of tissue architecture, established via cell-matrix interactions, on the cell nucleus is emphasized in light of the importance in toxicology of morphological and epigenetic alterations of this organelle.

Optimization of Polymer-ECM Composite Scaffolds for Tissue Engineering: Effect of Cells and Culture Conditions on Polymeric Nanofiber Mats

The design of composite tissue scaffolds containing an extracellular matrix (ECM) and synthetic polymer fibers is a new approach to create bioactive scaffolds that can enhance cell function. Currently, studies investigating the effects of ECM-deposition and decellularization on polymer degradation are still lacking, as are data on optimizing the stability of the ECM-containing composite scaffolds during prolonged cell culture. In this study, we develop fibrous scaffolds using three polymer compositions, representing slow (E0000), medium (E0500), and fast (E1000) degrading materials, to investigate the stability, degradation, and mechanics of the scaffolds during ECM deposition and decellularization, and during the complete cellularization-decell-recell cycle. We report data on percent molecular weight (% Mw) retention of polymeric fiber mats, changes in scaffold stiffness, ECM deposition, and the presence of fibronectin after decellularization. We concluded that the fast degrading E1000 (Mw retention ≤ 50% after 28 days) was not sufficiently stable to allow scaffold handling after 28 days in culture, while the slow degradation of E0000 (Mw retention ≥ 80% in 28 days) did not allow deposited ECM to replace the polymer support. The scaffolds made from medium degrading E0500 (Mw retention about 60% at 28 days) allowed the gradual replacement of the polymer network with cell-derived ECM while maintaining the polymer network support. Thus, polymers with an intermediate rate of degradation, maintaining good scaffold handling properties after 28 days in culture, seem best suited for creating ECM-polymer composite scaffolds.

High-content image informatics of the structural nuclear protein NuMA parses trajectories for stem/progenitor cell lineages and oncogenic transformation

Stem and progenitor cells that exhibit significant regenerative potential and critical roles in cancer initiation and progression remain difficult to characterize. Cell fates are determined by reciprocal signaling between the cell microenvironment and the nucleus; hence parameters derived from nuclear remodeling are ideal candidates for stem/progenitor cell characterization. Here we applied high-content, single cell analysis of nuclear shape and organization to examine stem and progenitor cells destined to distinct differentiation endpoints, yet undistinguishable by conventional methods. Nuclear descriptors defined through image informatics classified mesenchymal stem cells poised to either adipogenic or osteogenic differentiation, and oligodendrocyte precursors isolated from different regions of the brain and destined to distinct astrocyte subtypes. Nuclear descriptors also revealed early changes in stem cells after chemical oncogenesis, allowing the identification of a class of cancer-mitigating biomaterials. To capture the metrology of nuclear changes, we developed a simple and quantitative "imaging-derived" parsing index, which reflects the dynamic evolution of the high-dimensional space of nuclear organizational features. A comparative analysis of parsing outcomes via either nuclear shape or textural metrics of the nuclear structural protein NuMA indicates the nuclear shape alone is a weak phenotypic predictor. In contrast, variations in the NuMA organization parsed emergent cell phenotypes and discerned emergent stages of stem cell transformation, supporting a prognosticating role for this protein in the outcomes of nuclear functions.

Profiling stem cell states in three-dimensional biomaterial niches using high content image informatics

A predictive framework for the evolution of stem cell biology in 3-D is currently lacking. In this study we propose deep image informatics of the nuclear biology of stem cells to elucidate how 3-D biomaterials steer stem cell lineage phenotypes. The approach is based on high content imaging informatics to capture minute variations in the 3-D spatial organization of splicing factor SC-35 in the nucleoplasm as a marker to classify emergent cell phenotypes of human mesenchymal stem cells (hMSCs). The cells were cultured in varied 3-D culture systems including hydrogels, electrospun mats and salt leached scaffolds. The approach encompasses high resolution 3-D imaging of SC-35 domains and high content image analysis (HCIA) to compute quantitative 3-D nuclear metrics for SC-35 organization in single cells in concert with machine learning approaches to construct a predictive cell-state classification model. Our findings indicate that hMSCs cultured in collagen hydrogels and induced to differentiate into osteogenic or adipogenic lineages could be classified into the three lineages (stem, adipogenic, osteogenic) with ⩾80% precision and sensitivity, within 72h. Using this framework, the augmentation of osteogenesis by scaffold design exerted by porogen leached scaffolds was also profiled within 72h with ∼80% high sensitivity. Furthermore, by employing 3-D SC-35 organizational metrics, differential osteogenesis induced by novel electrospun fibrous polymer mats incorporating decellularized matrix could also be elucidated and predictably modeled at just 3days with high precision. We demonstrate that 3-D SC-35 organizational metrics can be applied to model the stem cell state in 3-D scaffolds. We propose that this methodology can robustly discern minute changes in stem cell states within complex 3-D architectures and map single cell biological readouts that are critical to assessing population level cell heterogeneity.

STATEMENT OF SIGNIFICANCE

The sustained development and validation of bioactive materials relies on technologies that can sensitively discern cell response dynamics to biomaterials, while capturing cell-to-cell heterogeneity and preserving cellular native phenotypes. In this study, we illustrate the application of a novel high content image informatics platform to classify emergent human mesenchymal stem cell (hMSC) phenotypes in a diverse range of 3-D biomaterial scaffolds with high sensitivity and precision, and track cell responses to varied external stimuli. A major in silico innovation is the proposed image profiling technology based on unique three dimensional textural signatures of a mechanoreporter protein within the nuclei of stem cells cultured in 3-D scaffolds. This technology will accelerate the pace of high-fidelity biomaterial screening.

Convergence of Highly Resolved and Rapid Screening Platforms with Dynamically Engineered, Cell Phenotype-Prescriptive Biomaterials

Biophysical and biochemical cues from the cellular microenvironment initiate intracellular signaling through cellular membrane receptors and trigger specific cell developmental programs. Extracellular substrates and matrix scaffolds engineered to mimic cell's native physiological environment must incorporate the multifactorial parameters (composition, micro and nanoscale organization and topography) of the extracellular matrix as well as the dynamic nature of the matrix. The design of such engineered biomaterials is challenged by the inherent complexity and dynamic nature of the cell-extracellular matrix reciprocity, while the validation of robust microenvironments requires a deeper, higher content phenotypic resolution of cell-matrix interactions alongside a rapid screening capability. To this end, high-throughput platforms are integral to facilitating the screening and optimization of complex engineered microenvironments for directing desired cell developmental pathway. This review highlights the recent advances in biomaterial platforms that present dynamic cues and enable high throughput screening of cell's response to a combination of micro-environmental factors. We also address some newer techniques involving high content image informatics to elucidate emergent cellular behaviors with a focus on stem cell regenerative endpoints.

Time series modeling of live-cell shape dynamics for image-based phenotypic profiling

Live-cell imaging can be used to capture spatio-temporal aspects of cellular responses that are not accessible to fixed-cell imaging. As the use of live-cell imaging continues to increase, new computational procedures are needed to characterize and classify the temporal dynamics of individual cells. For this purpose, here we present the general experimental-computational framework SAPHIRE (Stochastic Annotation of Phenotypic Individual-cell Responses) to characterize phenotypic cellular responses from time series imaging datasets. Hidden Markov modeling is used to infer and annotate morphological state and state-switching properties from image-derived cell shape measurements. Time series modeling is performed on each cell individually, making the approach broadly useful for analyzing asynchronous cell populations. Two-color fluorescent cells simultaneously expressing actin and nuclear reporters enabled us to profile temporal changes in cell shape following pharmacological inhibition of cytoskeleton-regulatory signaling pathways. Results are compared with existing approaches conventionally applied to fixed-cell imaging datasets, and indicate that time series modeling captures heterogeneous dynamic cellular responses that can improve drug classification and offer additional important insight into mechanisms of drug action. The software is available at http://saphire-hcs.org.