Microarray Embedding/Sectioning for Parallel Analysis of 3D Cell Spheroids.

Three-dimensional cell spheroid models can be used to predict the effect of drugs and therapeutics and to model tissue development and regeneration. The utility of these models is enhanced by high throughput 3D spheroid culture technologies allowing researchers to efficiently culture numerous spheroids under varied experimental conditions. Detailed analysis of high throughput spheroid culture is much less efficient and generally limited to narrow outputs, such as metabolic viability. We describe a microarray approach that makes traditional histological embedding/sectioning/staining feasible for large 3D cell spheroid sample sets. Detailed methodology to apply this technology is provided. Analysis of the technique validates the potential for efficient histological analysis of up to 96 spheroids in parallel. By integrating high throughput 3D spheroid culture technologies with advanced immunohistochemical techniques, this approach will allow researchers to efficiently probe expression of multiple biomarkers with spatial localization within 3D structures. Quantitative comparison of staining will have improved inter- and intra-experimental reproducibility as multiple samples are collectively processed, stained, and imaged on a single slide

Transfer learning in a biomaterial fibrosis model identifies in vivo senescence heterogeneity and contributions to vascularization and matrix production across species and diverse pathologies

Cellular senescence is a state of permanent growth arrest that plays an important role in wound healing, tissue fibrosis, and tumor suppression. Despite senescent cells’ (SnCs) pathological role and therapeutic interest, their phenotype in vivo remains poorly defined. Here, we developed an in vivo–derived senescence signature (SenSig) using a foreign body response–driven fibrosis model in a p16-CreERT2;Ai14 reporter mouse. We identified pericytes and “cartilage-like” fibroblasts as senescent and defined cell type–specific senescence-associated secretory phenotypes (SASPs). Transfer learning and senescence scoring identified these two SnC populations along with endothelial and epithelial SnCs in new and publicly available murine and human data single-cell RNA sequencing (scRNAseq) datasets from diverse pathologies. Signaling analysis uncovered crosstalk between SnCs and myeloid cells via an IL34–CSF1R–TGFβR signaling axis, contributing to tissue balance of vascularization and matrix production. Overall, our study provides a senescence signature and a computational approach that may be broadly applied to identify SnC transcriptional profiles and SASP factors in wound healing, aging, and other pathologies.</p

Transfer learning in a biomaterial fibrosis model identifies in vivo senescence heterogeneity and contributions to vascularization and matrix production across species and diverse pathologies

Cellular senescence is a state of permanent growth arrest that plays an important role in wound healing, tissue fibrosis, and tumor suppression. Despite senescent cells’ (SnCs) pathological role and therapeutic interest, their phenotype in vivo remains poorly defined. Here, we developed an in vivo–derived senescence signature (SenSig) using a foreign body response–driven fibrosis model in a p16-CreERT2;Ai14 reporter mouse. We identified pericytes and “cartilage-like” fibroblasts as senescent and defined cell type–specific senescence-associated secretory phenotypes (SASPs). Transfer learning and senescence scoring identified these two SnC populations along with endothelial and epithelial SnCs in new and publicly available murine and human data single-cell RNA sequencing (scRNAseq) datasets from diverse pathologies. Signaling analysis uncovered crosstalk between SnCs and myeloid cells via an IL34–CSF1R–TGFβR signaling axis, contributing to tissue balance of vascularization and matrix production. Overall, our study provides a senescence signature and a computational approach that may be broadly applied to identify SnC transcriptional profiles and SASP factors in wound healing, aging, and other pathologies.</p

Transfer learning in a biomaterial fibrosis model identifies in vivo senescence heterogeneity and contributions to vascularization and matrix production across species and diverse pathologies

Cellular senescence is a state of permanent growth arrest that plays an important role in wound healing, tissue fibrosis, and tumor suppression. Despite senescent cells’ (SnCs) pathological role and therapeutic interest, their phenotype in vivo remains poorly defined. Here, we developed an in vivo–derived senescence signature (SenSig) using a foreign body response–driven fibrosis model in a p16-CreERT2;Ai14 reporter mouse. We identified pericytes and “cartilage-like” fibroblasts as senescent and defined cell type–specific senescence-associated secretory phenotypes (SASPs). Transfer learning and senescence scoring identified these two SnC populations along with endothelial and epithelial SnCs in new and publicly available murine and human data single-cell RNA sequencing (scRNAseq) datasets from diverse pathologies. Signaling analysis uncovered crosstalk between SnCs and myeloid cells via an IL34–CSF1R–TGFβR signaling axis, contributing to tissue balance of vascularization and matrix production. Overall, our study provides a senescence signature and a computational approach that may be broadly applied to identify SnC transcriptional profiles and SASP factors in wound healing, aging, and other pathologies.</p

Transfer learning in a biomaterial fibrosis model identifies in vivo senescence heterogeneity and contributions to vascularization and matrix production across species and diverse pathologies

Cellular senescence is a state of permanent growth arrest that plays an important role in wound healing, tissue fibrosis, and tumor suppression. Despite senescent cells’ (SnCs) pathological role and therapeutic interest, their phenotype in vivo remains poorly defined. Here, we developed an in vivo–derived senescence signature (SenSig) using a foreign body response–driven fibrosis model in a p16-CreERT2;Ai14 reporter mouse. We identified pericytes and “cartilage-like” fibroblasts as senescent and defined cell type–specific senescence-associated secretory phenotypes (SASPs). Transfer learning and senescence scoring identified these two SnC populations along with endothelial and epithelial SnCs in new and publicly available murine and human data single-cell RNA sequencing (scRNAseq) datasets from diverse pathologies. Signaling analysis uncovered crosstalk between SnCs and myeloid cells via an IL34–CSF1R–TGFβR signaling axis, contributing to tissue balance of vascularization and matrix production. Overall, our study provides a senescence signature and a computational approach that may be broadly applied to identify SnC transcriptional profiles and SASP factors in wound healing, aging, and other pathologies.</p

Evolution of Autologous Chondrocyte Repair and Comparison to Other Cartilage Repair Techniques

Articular cartilage defects have been addressed using microfracture, abrasion chondroplasty, or osteochondral grafting, but these strategies do not generate tissue that adequately recapitulates native cartilage. During the past 25 years, promising new strategies using assorted scaffolds and cell sources to induce chondrocyte expansion have emerged. We reviewed the evolution of autologous chondrocyte implantation and compared it to other cartilage repair techniques. Methods. We searched PubMed from 1949 to 2014 for the keywords “autologous chondrocyte implantation” (ACI) and “cartilage repair” in clinical trials, meta-analyses, and review articles. We analyzed these articles, their bibliographies, our experience, and cartilage regeneration textbooks. Results. Microfracture, abrasion chondroplasty, osteochondral grafting, ACI, and autologous matrix-induced chondrogenesis are distinguishable by cell source (including chondrocytes and stem cells) and associated scaffolds (natural or synthetic, hydrogels or membranes). ACI seems to be as good as, if not better than, microfracture for repairing large chondral defects in a young patient’s knee as evaluated by multiple clinical indices and the quality of regenerated tissue. Conclusion. Although there is not enough evidence to determine the best repair technique, ACI is the most established cell-based treatment for full-thickness chondral defects in young patients

Photomodulation of Cellular Gene Expression in Hydrogels

Biomaterials are designed to mimic aspects of various extracellular matrix environments, through chemical modifications to input biological or chemical signals. However, the dynamic nature and timing of gene expression during cellular events is much more difficult to mimic and control in these synthetic environments. Here, we utilized concepts of photochemistry combined with click chemistry for synthetic biology applications to modulate cellular gene expression in poly­(ethylene glycol) (PEG) hydrogels. Specifically, a genetic inducer, isopropyl β-d-1-thiogalactopyranoside (IPTG), is covalently linked to PEG via a biocompatible and easy to synthesize 2-(2-azido-6-nitrophenyl)­ethoxycarbonyl (ANPEOC) photocleavable moiety that, on a short exposure to UV light, effectively releases IPTG and activates gene expression of enhanced green fluorescence protein (EGFP). We anticipate that combining concepts of material chemistry with synthetic biology will further enable the construction of highly defined engineered niches that are capable of controlling both intrinsic and extrinsic cellular events

Tissue-Derived Biological Particles Restore Cornea Properties in an Enzyme-Mediated Corneal Ectatic Model

Purpose: To investigate the impact of tissue derived biological particles on enzyme-mediated weakened corneas. Methods: Rabbit corneas were treated with enzymes to create an ex vivo ectatic model that simulated representative characteristics of keratoconus (KC). Porcine cornea, cartilage, and lymph node tissues were processed to remove most cellular components and cryomilled into microparticles. The KC corneas were cultured in medium containing the tissue-derived biological particles (TDP) overnight. The mechanical, thermal, ultrastructural changes, and gene expressions of corneal stromal cells were characterized to evaluate the effects of the TDP treatment. Results: The enzyme treatment significantly reduced corneal mechanics and thermal stability, and also disrupted the extracellular matrix ultrastructure. After culturing with TDP medium, the Young&rsquo;s modulus of the modeled KC corneas increased by ~50%, comparable to normal cornea controls. Similarly, the thermal denaturation temperature of the corneas was restored. These findings also corresponded to a significant increase in collagen fibril density after TDP treatment. Furthermore, corneas cultured in TDP medium significantly downregulated expression of the pro-inflammatory gene Tnf&alpha;, and restored the expression of the key keratocyte markers Aldh, keratocan, and biglycan. Conclusions: Tissue-derived biological particles reinforce mechanical and thermal properties of corneal tissue in an ex vivo model of KC. Through this study, we demonstrate and characterize the previously unexplored impact of tissue-derived biological scaffolds on corneal biomechanics, thermal stability, and gene expression, presenting a potential new therapy for ocular disease