In vitro inflammatory multi-cellular model of osteoarthritis.

Objective: Osteoarthritis (OA) is a chronic joint disease, with limited treatment options, characterized by inflammation and matrix degradation, and resulting in severe pain or disability. Progressive inflammatory interaction among key cell types, including chondrocytes and macrophages, leads to a cascade of intra- and inter-cellular events which culminate in OA induction. In order to investigate these interactions, we developed a multi-cellular in vitro OA model, to characterize OA progression, and identify and evaluate potential OA therapeutics in response to mediators representing graded levels of inflammatory severity. Methods: We compared macrophages, chondrocytes and their co-culture responses to "low" Interleukin-1 (IL-1) or "high" IL-1/tumor necrosis factor (IL-1/TNF) levels of inflammation. We also investigated response changes following the administration of dexamethasone (DEX) or mesenchymal stromal cell (MSC) treatment via a combination of gene expression and secretory changes, reflecting not only inflammation, but also chondrocyte function. Results: Inflamed chondrocytes presented an osteoarthritic-like phenotype characterized by high gene expression of pro-inflammatory cytokines and chemokines, up-regulation of ECM degrading proteases, and down-regulation of chondrogenic genes. Our results indicate that while MSC treatment attenuates macrophage inflammation directly, it does not reduce chondrocyte inflammatory responses, unless macrophages are present as well. DEX however, can directly attenuate chondrocyte inflammation. Conclusions: Our results highlight the importance of considering multi-cellular interactions when studying complex systems such as the articular joint. In addition, our approach, using a panel of both inflammatory and chondrocyte functional genes, provides a more comprehensive approach to investigate disease biomarkers, and responses to treatment.

Differentiation of monocytes and polarized M1/M2 macrophages from human induced pluripotent stem cells.

Here, we present a protocol to differentiate induced pluripotent stem cell (iPSC) into adherent hematopoietic progenitors that release floating CD14+ CD45+ monocytes into the culture medium. We describe steps for iPSC expansion, embryoid body (EB) formation, suspension culture, plating EBs, and recurring harvests of monocytes, a.k.a. "monocyte factory." We then describe detailed procedures for freezing/thawing of monocytes and differentiation into polarized M1 and M2 macrophages. This protocol provides foundation to study iPSC monocytes and their progenies such as macrophages, microglial, and dendritic cells. For complete details on the use and execution of this protocol, please refer to Karlson et al.1 and Panicker et al.2.

A biologically validated mathematical model for decoding epithelial apical, basolateral, and paracellular electrical properties.

Epithelial tissues form selective barriers to ions, nutrients, waste products, and infectious agents throughout the body. Damage to these barriers is associated with conditions such as celiac disease, cystic fibrosis, diabetes, and age-related macular degeneration. Conventional electrophysiology measurements like transepithelial resistance can quantify epithelial tissue maturity and barrier integrity but are limited in differentiating between apical, basolateral, and paracellular transport pathways. To overcome this limitation, a combination of mathematical modeling, stem cell biology, and cell physiology led to the development of 3 P-EIS, a novel mathematical model and measurement technique. 3 P-EIS employs an intracellular pipette and extracellular electrochemical impedance spectroscopy to accurately measure membrane-specific properties of epithelia, without the constraints of prior models. 3 P-EIS was validated using electronic circuit models of epithelia with known resistances and capacitances, confirming a median error of 19% (interquartile range: 14%-26%) for paracellular and transcellular resistances and capacitances (n = 5). Patient stem cell-derived retinal pigment epithelium tissues were measured using 3 P-EIS, successfully isolating the cellular responses to adenosine triphosphate. 3 P-EIS enhances quality control in epithelial cell therapies and has extensive applicability in drug testing and disease modeling, marking a significant advance in epithelial physiology.NEW & NOTEWORTHY This interdisciplinary paper integrates mathematics, biology, and physiology to measure epithelial tissue's apical, basolateral, and paracellular transport pathways. A key advancement is the inclusion of intracellular voltage recordings using a sharp pipette, enabling precise quantification of relative impedance changes between apical and basolateral membranes. This enhanced electrochemical impedance spectroscopy technique offers insights into epithelial transport dynamics, advancing disease understanding, drug interactions, and cell therapies. Its broad applicability contributes significantly to epithelial physiology research.

Protocol to generate endothelial cells, pericytes, and fibroblasts in one differentiation round from human-induced pluripotent stem cells.

Here, we present a protocol for differentiating human-induced pluripotent stem cells into three distinct mesodermal cell types: vascular endothelial cells (ECs), pericytes, and fibroblasts. We describe steps for using monolayer serum-free differentiation and isolating ECs (CD31+) and mesenchymal pre-pericytes (CD31-) from a single differentiation set. We then differentiate pericytes into fibroblasts using a commercial fibroblast culture medium. The three cell types differentiated in this protocol are useful for vasculogenesis, drug testing, and tissue engineering applications. For complete details on the use and execution of this protocol, please refer to Orlova et al. (2014).1.

A computational pipeline for functional gene discovery.

Many computational pipelines exist for the detection of differentially expressed genes. However, computational pipelines for functional gene detection rarely exist. We developed a new computational pipeline for functional gene identification from transcriptome profiling data. Key features of the pipeline include batch effect correction, clustering optimization by gap statistics, gene ontology analysis of clustered genes, and literature analysis for functional gene discovery. By leveraging this pipeline on RNA-seq datasets from two mouse retinal development studies, we identified 7 candidate genes involved in the formation of the photoreceptor outer segment. The expression of top three candidate genes (Pde8b, Laptm4b, and Nr1h4) in the outer segment of the developing mouse retina were experimentally validated by immunohistochemical analysis. This computational pipeline can accurately predict novel functional gene for a specific biological process, e.g., development of the outer segment and synapses of the photoreceptor cells in the mouse retina. This pipeline can also be useful to discover functional genes for other biological processes and in other organs and tissues.