A single-cell atlas of the microenvironment of implanted biomaterials and computational analysis of the transcriptional signalling networks [bulk RNA-seq]
Ontology highlight
ABSTRACT: The understanding of the foreign-body responses to implanted biomaterials would benefit from the reconstruction of intracellular and intercellular signalling networks in the microenvironment surrounding the implant. Here, by leveraging single-cell RNA-sequencing data from 42,156 cells harvested from the site of implantation of either polycaprolactone or an extracellular-matrix-derived scaffold in a mouse model of volumetric muscle loss, we report a computational analysis of intercellular-signalling networks reconstructed from data of transcription-factor activation. We found that intercellular signalling networks can be clustered into modules associated with specific cell subsets, and that biomaterial-specific responses can be characterized by interactions between signalling modules for immune, fibroblast and tissue-specific cells. In a Il17ra–/¬– knockout mouse model, we validated that predicted IL-17-linked transcriptional targets led to concomitant changes in gene expression. Moreover, we identified cell subsets that had not been implicated in the responses to implanted biomaterials. Single-cell atlases of the cellular responses to implanted biomaterials will facilitate the design of implantable biomaterials and the understanding of the ensuing cellular responses.
Project description:The understanding of the foreign-body responses to implanted biomaterials would benefit from the reconstruction of intracellular and intercellular signalling networks in the microenvironment surrounding the implant. Here, by leveraging single-cell RNA-sequencing data from 42,156 cells harvested from the site of implantation of either polycaprolactone or an extracellular-matrix-derived scaffold in a mouse model of volumetric muscle loss, we report a computational analysis of intercellular-signalling networks reconstructed from data of transcription-factor activation. We found that intercellular signalling networks can be clustered into modules associated with specific cell subsets, and that biomaterial-specific responses can be characterized by interactions between signalling modules for immune, fibroblast and tissue-specific cells. In a Il17ra–/¬– knockout mouse model, we validated that predicted IL-17-linked transcriptional targets led to concomitant changes in gene expression. Moreover, we identified cell subsets that had not been implicated in the responses to implanted biomaterials. Single-cell atlases of the cellular responses to implanted biomaterials will facilitate the design of implantable biomaterials and the understanding of the ensuing cellular responses.
Project description:A single-cell atlas of the microenvironment of implanted biomaterials and computational analysis of the transcriptional signalling networks
Project description:A single-cell atlas of the microenvironment of implanted biomaterials and computational analysis of the transcriptional signalling networks [bulk RNA-seq]
Project description:A single-cell atlas of the microenvironment of implanted biomaterials and computational analysis of the transcriptional signalling networks [single-cell RNA-seq]
Project description:B cells are an adaptive immune target of biomaterials development in vaccine research but despite their role in wound healing have not been studied tissue engineering and regenerative medicine. We evaluated the B cell response to biomaterial scaffold materials implanted in a muscle wound; a biological extracellular matrix (ECM) and synthetic polyester polycaprolactone. In the local muscle tissue, small numbers of B cells are recruited in response to tissue injury and biomaterial implantation. ECM materials induced plasmablasts in lymph nodes and antigen presentation in the spleen while the synthetic PCL implants delayed B cell migration and induced an antigen presenting phenotype. In muMt- mice lacking B cells, the fibrotic response to the synthetic biomaterials decreased. Immunofluorescence confirmed antigen presenting B cells in fibrotic tissue surrounding silicone breast implants. In sum, the adaptive B cell immune response to biomaterial depends on composition and induces local, regional and systemic immunological changes.
Project description:Escherichia coli is the leading cause of catheter-associated urinary tract infections, caused by biofilm formation on implanted biomaterial surfaces. Understanding the genes that cause cellular adhesion to diverse biomaterial surfaces may aid in the design of targeting anti-biofouling chemicals to prevent these biofilm infections, but our current knowledge on such surfaces is limited. Here, we incorporate a platform of six biomaterials of varying hydrophilicities and stiffnesses and a comprehensive genome-wide CRISPR interference (CRISPRi) library to elucidate genotype-phenotype relationships for cellular adhesion to physicochemically varied biomaterial surfaces in E. coli MG1655. After characterization of the biomaterials and CRISPRi tool, we designed a CRISPRi library of 34,315 unique designs targeting 99.0% of the genome in MG1655 (up to 8 designs per gene). We then performed pooled selections for adhesion to each biomaterial surface, elucidating over 400 novel gene hits to each biomaterial surface. Data analysis revealed greater correlations between biomaterials of the same hydrophilicity rather than stiffness, in addition to more gene hits associated with decreased adhesion across all six surfaces than increased adhesion. Monoclonal verification of select designs from the library exhibited strong correlations between results from the pooled selections and individual measurements for adhesion to each gel for most designs. The results from this study provide comprehensive gene sets for cellular adhesion to physicochemically diverse biomaterial surfaces that may be potential gene targets for the design of targeting anti-biofouling agents and offer insight that could be used for the design of “smart” biomaterials, both with potential to prevent biofilm infections.
Project description:During the past decades, there have been major advances in the field of biomaterials, thereby generating a vast variety of materials for a broad range of tissue engineering and regeneration applications. Although gene expression profiling has been used occasionally in biomaterial research, its usefulness for understanding cell-biomaterial interactions should be further explored for it to fulfill its promise as a tool to assess and improve material properties. Here, the transcriptional landscape induced by 23 materials is explored with a variety of properties within the scope of bone regeneration. An osteoblast cell line is used to identify the gene expression profiles that can be adopted in response to biophysical and chemical cues. It is shown that TGF-beta and WNT signaling may be involved in the cellular response to osteoinductive materials along with differential cell adhesion kinetics via attenuated FAK signaling. The previously reported effect of calcium and phosphate on BMP2 and TGF-beta signaling is confirmed and the biological effect of the addition of nanohydroxyapatite in poly (d,l-lactic acid) polymer particles is studied. Together with future applications, this approach will help researchers understand cellular responses in relation to material properties, which will promote the development of more effective biomaterials for applications in tissue regeneration.
Project description:The bone-defect-repair process involves complex interaction between mesenchymal stem cells (MSCs) and immune cells, while the heterogeneity of osteoimmune microenvironment around implanted biomaterials remains elusive. By combining analysis of scRNA-seq and spatial transcriptomics technologies, we revealed that MgphiMSCs subpopulation served as the pioneers during the early stage of biomaterials-mediated bone defect healing process. They performed efficient osteogenic differentiation potential and had close interactions with immune cells. Remarkably, the MgphiMSCs could response to biomaterials-mediated osteoimmune microenvironment, rewired the polarization and osteoclastic differentiation of macrophages via midkine (MDK) signaling pathway. The inhibition of MDK activated the pro-inflammatory programs of macrophages and osteoclastogenesis. Meanwhile, multiple innate and adaptive immune-cell subsets exhibited close crosstalk between MgphiMSCs via SPP1 signaling pathway. These cellular profiles and interactions characterized in this study could broaden our understanding of the functional MSCs subpopulations at the early stage of biomaterial-mediated bone regeneration and provide the basis for the materials-designed strategies that target osteoimmune modulation.
Project description:The bone-defect-repair process involves complex interaction between mesenchymal stem cells (MSCs) and immune cells, while the heterogeneity of osteoimmune microenvironment around implanted biomaterials remains elusive. By combining analysis of scRNA-seq and spatial transcriptomics technologies, we revealed that MgphiMSCs subpopulation served as the pioneers during the early stage of biomaterials-mediated bone defect healing process. They performed efficient osteogenic differentiation potential and had close interactions with immune cells. Remarkably, the MgphiMSCs could response to biomaterials-mediated osteoimmune microenvironment, rewired the polarization and osteoclastic differentiation of macrophages via midkine (MDK) signaling pathway. The inhibition of MDK activated the pro-inflammatory programs of macrophages and osteoclastogenesis. Meanwhile, multiple innate and adaptive immune-cell subsets exhibited close crosstalk between MgphiMSCs via SPP1 signaling pathway. These cellular profiles and interactions characterized in this study could broaden our understanding of the functional MSCs subpopulations at the early stage of biomaterial-mediated bone regeneration and provide the basis for the materials-designed strategies that target osteoimmune modulation.