Integrated Multiparametric High-Content Profiling of Endothelial Cells

High content Image Analysis to study phenotypic heterogeneity in endothelial cell monolayers

Endothelial cells (EC) are heterogeneous across and within tissues, reflecting distinct, specialised functions. EC heterogeneity has been proposed to underpin EC plasticity independently from vessel microenvironments. However, heterogeneity driven by contact-dependent or short-range cell-cell crosstalk cannot be evaluated with single cell transcriptomic approaches as spatial and contextual information is lost. Nonetheless, quantification of EC heterogeneity and understanding of its molecular drivers is key to developing novel therapeutics for cancer, cardiovascular diseases and for revascularisation in regenerative medicine. Here, we developed an EC profiling tool (ECPT) to examine individual cells within intact monolayers. We used ECPT to characterise different phenotypes in arterial, venous and microvascular EC populations. In line with other studies, we measured heterogeneity in terms of cell cycle, proliferation, and junction organisation. ECPT uncovered a previously under-appreciated single-cell heterogeneity in NOTCH activation. We correlated cell proliferation with different NOTCH activation states at the single cell and population levels. The positional and relational information extracted with our novel approach is key to elucidating the molecular mechanisms underpinning EC heterogeneity.

Comparative Analysis of Blood-Derived Endothelial Cells for Designing Next-Generation Personalized Organ-on-Chips

Background

Organ‐on‐chip technology has accelerated in vitro preclinical research of the vascular system, and a key strength of this platform is its promise to impact personalized medicine by providing a primary human cell–culture environment where endothelial cells are directly biopsied from individual tissue or differentiated through stem cell biotechniques. However, these methods are difficult to adopt in laboratories, and often result in impurity and heterogeneity of cells. This limits the power of organ‐chips in making accurate physiological predictions. In this study, we report the use of blood‐derived endothelial cells as alternatives to primary and induced pluripotent stem cell–derived endothelial cells.

Methods and Results

Here, the genotype, phenotype, and organ‐chip functional characteristics of blood‐derived outgrowth endothelial cells were compared against commercially available and most used primary endothelial cells and induced pluripotent stem cell–derived endothelial cells. The methods include RNA‐sequencing, as well as criterion standard assays of cell marker expression, growth kinetics, migration potential, and vasculogenesis. Finally, thromboinflammatory responses under shear using vessel‐chips engineered with blood‐derived endothelial cells were assessed. Blood‐derived endothelial cells exhibit the criterion standard hallmarks of typical endothelial cells. There are differences in gene expression profiles between different sources of endothelial cells, but blood‐derived cells are relatively closer to primary cells than induced pluripotent stem cell–derived. Furthermore, blood‐derived endothelial cells are much easier to obtain from individuals and yet, they serve as an equally effective cell source for functional studies and organ‐chips compared with primary cells or induced pluripotent stem cell–derived cells.

Conclusions

Blood‐derived endothelial cells may be used in preclinical research for developing more robust and personalized next‐generation disease models using organ‐on‐chips.

Biofunctionalization of bioactive ceramic scaffolds to increase the cell response for bone regeneration

Biofunctionalization was investigated for polymers and metals considering their scarce integration ability. On the contrary few studies dealt with ceramic biofunctionalization because the bioactive and bioresorbable surfaces of ceramics are able to positively interact with biological environment. In this study the cell-response improvement on biofunctionalized wollastonite and diopside-based scaffolds was demonstrated. The ceramics were first obtained by heat treatment of a silicone embedding reactive oxide fillers and then biofunctionalized with adhesive peptides mapped on vitronectin. The most promisingin vitroresults, in terms of h-osteoblast proliferation and bone-related gene expression, were reached anchoring selectively a peptide stable toward proteolytic degradation induced by serum-enriched medium. Inin vivoassays the anchoring of this protease-stable adhesive peptide was combined with self-assembling peptides, for increasing cell viability and angiogenesis. The results demonstrated external and internal cell colonization of biofunctionalized scaffolds with formation of new blood vessels (neoangiogenesis) and stimulation of ectopic mineralization.

An integrated pipeline for high-throughput screening and profiling of spheroids using simple live image analysis of frame to frame variations

High-throughput imaging methods can be applied to relevant cell culture models, fostering their use in research and translational applications. Improvements in microscopy, computational capabilities and data analysis have enabled high-throughput, high-content approaches from endpoint 2D microscopy images. Nonetheless, trade-offs in acquisition, computation and storage between content and throughput remain, in particular when cells and cell structures are imaged in 3D. Moreover, live 3D phase contrast microscopy images are not often amenable to analysis because of the high level of background noise. Cultures of Human induced pluripotent stem cells (hiPSC) offer unprecedented scope to profile and screen conditions affecting cell fate decisions, self-organisation and early embryonic development. However, quantifying changes in the morphology or function of cell structures derived from hiPSCs over time presents significant challenges. Here, we report a novel method based on the analysis of live phase contrast microscopy images of hiPSC spheroids. We compare self-renewing versus differentiating media conditions, which give rise to spheroids with distinct morphologies; round versus branched, respectively. These cell structures are segmented from 2D projections and analysed based on frame-to-frame variations. Importantly, a tailored convolutional neural network is trained and applied to predict culture conditions from time-frame images. We compare our results with more classic and involved endpoint 3D confocal microscopy and propose that such approaches can complement spheroid-based assays developed for the purpose of screening and profiling. This workflow can be realistically implemented in laboratories using imaging-based high-throughput methods for regenerative medicine and drug discovery.

High-Content Imaging to Phenotype Human Primary and iPSC-Derived Cells

Increasingly powerful microscopy, liquid handling, and computational techniques have enabled cell imaging in high throughput. Microscopy images are quantified using high-content analysis platforms linking object features to cell behavior. This can be attempted on physiologically relevant cell models, including stem cells and primary cells, in complex environments, and conceivably in the presence of perturbations. Recently, substantial focus has been devoted to cell profiling for cell therapy, assays for drug discovery or biomarker identification for clinical decision-making protocols, bringing this wealth of information into translational applications. In this chapter, we focus on two protocols enabling to (1) benchmark human cells, in particular human endothelial cells as a case study and (2) extract cells from blood for follow-up experiments including image-based drug testing. We also present concepts of high-content imaging and discuss the benefits and challenges, with the aim of enabling readers to tailor existing pipelines and bring such approaches closer to translational research and the clinic.

Induction of Neural Crest Stem Cells From Bardet-Biedl Syndrome Patient Derived hiPSCs

Neural crest cells arise in the embryo from the neural plate border and migrate throughout the body, giving rise to many different tissue types such as bones and cartilage of the face, smooth muscles, neurons, and melanocytes. While studied extensively in animal models, neural crest development and disease have been poorly described in humans due to the challenges in accessing embryonic tissues. In recent years, patient-derived human induced pluripotent stem cells (hiPSCs) have become easier to generate, and several streamlined protocols have enabled robust differentiation of hiPSCs to the neural crest lineage. Thus, a unique opportunity is offered for modeling neurocristopathies using patient specific stem cell lines. In this work, we make use of hiPSCs derived from patients affected by the Bardet-Biedl Syndrome (BBS) ciliopathy. BBS patients often exhibit subclinical craniofacial dysmorphisms that are likely to be associated with the neural crest-derived facial skeleton. We focus on hiPSCs carrying variants in the BBS10 gene, which encodes a protein forming part of a chaperonin-like complex associated with the cilium. Here, we establish a pipeline for profiling hiPSCs during differentiation toward the neural crest stem cell fate. This can be used to characterize the differentiation properties of the neural crest-like cells. Two different BBS10 mutant lines showed a reduction in expression of the characteristic neural crest gene expression profile. Further analysis of both BBS10 mutant lines highlighted the inability of these mutant lines to differentiate toward a neural crest fate, which was also characterized by a decreased WNT and BMP response. Altogether, our study suggests a requirement for wild-type BBS10 in human neural crest development. In the long term, approaches such as the one we describe will allow direct comparison of disease-specific cell lines. This will provide valuable insights into the relationships between genetic background and heterogeneity in cellular models. The possibility of integrating laboratory data with clinical phenotypes will move us toward precision medicine approaches.

Biofunctionalization of TiO2 Surfaces with Self-Assembling Layers of Oligopeptides Covalently Grafted to Chitosan

In the field of tissue engineering, a promising approach to obtain a bioactive, biomimetic, and antibiotic implant is the functionalization of a "classical" biocompatible material, for example, titanium, with appropriate biomolecules. For this purpose, we propose preparing self-assembling films of multiple components, allowing the mixing of different biofunctionalities "on demand". Self-assembling peptides (SAPs) are synthetic materials characterized by the ability to self-organize in nanostructures both in aqueous solution and as thin or thick films. Moreover, ordered layers of SAPs adhere on titanium surface as a scaffold coating to mimic the extracellular matrix. Chitosan is a versatile hydrophilic polysaccharide derived from chitin, with a broad antimicrobial spectrum to which Gram-negative and Gram-positive bacteria and fungi are highly susceptible, and is already known in the literature for the ability of its derivatives to firmly graft titanium alloys and show protective effects against some bacterial species, either alone or in combination with other antimicrobial substances such as antibiotics or antimicrobial peptides. In this context, we functionalized titanium surfaces with chitosan grafted to EAK16-II (a SAP), obtaining layer-by-layer structures of different degrees of order, depending on the preparative stoichiometry and path. The chemical composition, molecular structure, and arrangement of the obtained biofunctionalized surfaces were investigated by surface-sensitive techniques such as reflection-absorption infrared spectroscopy (RAIRS) and state-of-the-art synchrotron radiation-induced spectroscopies as X-ray photoemission spectroscopy (SR-XPS), and near-edge X-ray absorption fine structure (NEXAFS). Furthermore, was demonstrated that surfaces coated with EAK and Chit-EAK can support hNPs cell attachment and growth.