Multi-scale cellular engineering: From molecules to organ-on-a-chip.

Recent technological advances in cellular and molecular engineering have provided new insights into biology and enabled the design, manufacturing, and manipulation of complex living systems. Here, we summarize the state of advances at the molecular, cellular, and multi-cellular levels using experimental and computational tools. The areas of focus include intrinsically disordered proteins, synthetic proteins, spatiotemporally dynamic extracellular matrices, organ-on-a-chip approaches, and computational modeling, which all have tremendous potential for advancing fundamental and translational science. Perspectives on the current limitations and future directions are also described, with the goal of stimulating interest to overcome these hurdles using multi-disciplinary approaches

Dissecting tumor cell heterogeneity in 3D cell culture systems by combining imaging and next generation sequencing technologies

Three-dimensional (3D) in vitro cell culture systems have advanced the modeling of cellular processes in health and disease by reflecting physiological characteristics and architectural features of in vivo tissues. As a result, representative patient-derived 3D culture systems are emerging as advanced pre-clinical tumor models to support individualized therapy decisions. Beside the additional progress that has been achieved in molecular and pathological analyses towards personalized treatments, a remaining problem in both primary lesions and in vitro cultures is our limited understanding of functional tumor cell heterogeneity. This phenomenon is increasingly recognized as key driver of tumor progression and treatment resistance. Recent technological advances in next generation sequencing (NGS) have enabled unbiased identification of gene expression in low-input samples and single cells (scRNA-seq), thereby providing the basis to reveal cellular subtypes and drivers of cell state transitions. However, these methods generally require dissociation of tissues into single cell suspensions, which consequently leads to the loss of multicellular context. Thus, a direct or indirect combination of gene expression profiling with in situ microscopy is necessary for single cell analyses to precisely understand the association between complex cellular phenotypes and their underlying genetic programs. In this thesis, I will present two complementing strategies based on combinations of NGS and microscopy to dissect tumor cell heterogeneity in 3D culture systems. First, I will describe the development and application of the new method ‘pheno-seq’ for integrated high-throughput imaging and transcriptomic profiling of clonal tumor spheroids derived from models of breast and colorectal cancer (CRC). By this approach, we revealed characteristic gene expression that is associated with heterogeneous invasive and proliferative behavior, identified transcriptional regulators that are missed by scRNA-seq, linked visual phenotypes and associated transcriptional signatures to inhibitor response and inferred single-cell regulatory states by deconvolution. Second, by applying scRNA-seq to 12 patient-derived CRC spheroid cultures, we identified shared expression programs that relate to intestinal lineages and revealed metabolic signatures that are linked to cancer cell differentiation. In addition, we validated and complemented sequencing results by quantitative microscopy using live-dyes and multiplexed RNA fluorescence in situ hybridization, thereby revealing metabolic compartmentalization and potential cell-cell interactions. Taken together, we believe that our approaches provide a framework for translational research to dissect heterogeneous transcriptional programs in 3D cell culture systems which will pave the way for a deeper understanding of functional tumor cell heterogeneity

Automated four-dimensional long term imaging enables single cell tracking within organotypic brain slices to study neurodevelopment and degeneration.

Current approaches for dynamic profiling of single cells rely on dissociated cultures, which lack important biological features existing in tissues. Organotypic slice cultures preserve aspects of structural and synaptic organisation within the brain and are amenable to microscopy, but established techniques are not well adapted for high throughput or longitudinal single cell analysis. Here we developed a custom-built, automated confocal imaging platform, with improved organotypic slice culture and maintenance. The approach enables fully automated image acquisition and four-dimensional tracking of morphological changes within individual cells in organotypic cultures from rodent and human primary tissues for at least 3 weeks. To validate this system, we analysed neurons expressing a disease-associated version of huntingtin (HTT586Q138-EGFP), and observed that they displayed hallmarks of Huntington's disease and died sooner than controls. By facilitating longitudinal single-cell analyses of neuronal physiology, our system bridges scales necessary to attain statistical power to detect developmental and disease phenotypes

Evolution and Impact of High Content Imaging

Abstract/outline: The field of high content imaging has steadily evolved and expanded substantially across many industry and academic research institutions since it was first described in the early 1990′s. High content imaging refers to the automated acquisition and analysis of microscopic images from a variety of biological sample types. Integration of high content imaging microscopes with multiwell plate handling robotics enables high content imaging to be performed at scale and support medium- to high-throughput screening of pharmacological, genetic and diverse environmental perturbations upon complex biological systems ranging from 2D cell cultures to 3D tissue organoids to small model organisms. In this perspective article the authors provide a collective view on the following key discussion points relevant to the evolution of high content imaging:• Evolution and impact of high content imaging: An academic perspective• Evolution and impact of high content imaging: An industry perspective• Evolution of high content image analysis• Evolution of high content data analysis pipelines towards multiparametric and phenotypic profiling applications• The role of data integration and multiomics• The role and evolution of image data repositories and sharing standards• Future perspective of high content imaging hardware and softwar

Resolving Metabolic Heterogeneity in Experimental Models of the Tumor Microenvironment from a Stable Isotope Resolved Metabolomics Perspective

The tumor microenvironment (TME) comprises complex interactions of multiple cell types that determines cell behavior and metabolism such as nutrient competition and immune suppression. We discuss the various types of heterogeneity that exist in solid tumors, and the complications this invokes for studies of TME. As human subjects and in vivo model systems are complex and difficult to manipulate, simpler 3D model systems that are compatible with flexible experimental control are necessary for studying metabolic regulation in TME. Stable Isotope Resolved Metabolomics (SIRM) is a valuable tool for tracing metabolic networks in complex systems, but at present does not directly address heterogeneous metabolism at the individual cell level. We compare the advantages and disadvantages of different model systems for SIRM experiments, with a focus on lung cancer cells, their interactions with macrophages and T cells, and their response to modulators in the immune microenvironment. We describe the experimental set up, illustrate results from 3D cultures and co-cultures of lung cancer cells with human macrophages, and outline strategies to address the heterogeneous TME

Getting the whole picture: High content screening using three-dimensional cellular model systems and whole animal assays

Phenotypic or High Content Screening (HCS) is becoming more widely used for primary screening campaigns in drug discovery. Currently the vast majority of HCS campaigns are using cell lines grown in well-established monolayer cultures (2D tissue culture). There is widespread recognition that the more biologically relevant 3D tissue culture technologies such as spheroids and organoids and even whole animal assays will eventually be run as primary HCS. Upgrading the IT infrastructure to cope with the increase in data volumes requires investments in hardware (and software) and this will be manageable. However, the main bottleneck for the effective adoption and use of 3D tissue culture and whole animal assays in HCS is anticipated to be the development of software for the analysis of 3D images. In this review we summarize the current state of the available software and how they may be applied to analyzing 3D images obtained from a HCS campaign