Systems Biology Analysis of Heterocellular Signaling

Single cell lipid biology

Lipids are major cell constituents endowed with astonishing structural diversity. The pathways responsible for the assembly and disposal of different lipid species are energetically demanding, and genes encoding lipid metabolic factors and lipid-related proteins comprise a sizable fraction of our coding genome. Despite the importance of lipids, the biological significance of lipid structural diversity remains largely obscure. Recent technological developments have enabled extensive lipid analysis at the single cell level, revealing unexpected cell-cell variability in lipid composition. This new evidence suggests that lipid diversity is exploited in multicellularity and that lipids have a role in the establishment and maintenance of cell identity. In this review, we highlight the emerging concepts and technologies in single cell lipid analysis and the implications of this research for future studies.

Exploring the cell interactome: deciphering relative impacts of cell-cell communication in cell co-culture using a novel microfluidic device

The human body is made up of approximately 40 trillion cells in close contact, with the cellular density of individual tissues varying from 1 million to 1 billion cells per cubic centimetre. Interactions between different cell types (termed heterotypic) are thus common in vivo. Communication between cells can take the form of direct cell-cell contact mediated by plasma membrane proteins or through paracrine signalling mediated through the release, diffusion, and receipt of soluble factors. There is currently no systematic method to investigate the relative contributions of these mechanisms to cell behaviour. In this paper, we detail the conception, development and validation of a microfluidic device that allows cell-cell contact and paracrine signalling in defined areas and over a variety of biologically relevant length scales, referred to as the interactome-device or 'I-device'. Importantly, by intrinsic device design features, cells in different regions in the device are exposed to four different interaction types, including a) no heterotypic cell interaction, b) only paracrine signalling, c) only cell-cell direct contact, or d) both forms of interaction (paracrine and cell-cell direct contact) together. The device design was validated by both mathematical modelling and experiments. Perfused stem cell culture over the medium term and the formation of direct contact between cells in the culture chambers was confirmed. The I-device offers significant flexibility, being able to be applied to any combination of adherent cells to determine the relative contributions of different communication mechanisms to cellular outcomes.

Investigating the cytotoxic redox mechanism of PFOS within Hep G2 by hyperspectral-assisted scanning electrochemical microscopy

Perfluorooctane sulfonate (PFOS) is one of the most lethal per- and poly-fluoroalkyl substances (PFAS). Generally, exposure effects are studied through case-controlled studies, cohort studies, or cell assays. Unfortunately, most studies involving two-dimensional cell cultures require cell lysis or fixation. For in vitro studies, fluorescence microscopy has been useful, but methods to simultaneously discern phototoxic effects during an experiment are limited. Here, we use hepatocarcinoma (Hep G2) cells to examine the redox mechanism of PFOS cytotoxicity in vitro, while using hyperspectral-assisted scanning electrochemical microscopy (SECM) to differentiate between PFOS and redox mediator induced stress. Specifically, we correlate an increase in the electrochemical response of ferrocenemethanol oxidation with an increase in intracellular reactive oxygen species. Corresponding hyperspectral images of redox indicative-fluorophores implicate superoxide in the cytotoxic redox mechanism.

A universal microfluidic approach for integrated analysis of temporal homocellular and heterocellular signaling and migration dynamics

Microfluidics offers precise and dynamic control of microenvironments for the study of temporal cellular responses. However, recent research focusing solely on either homocellular (single-cell, population) or heterocellular response may yield insufficient output, which possibly leads to partial comprehension about the underlying mechanisms of signaling events and corresponding cellular behaviors. Here, a universal microfluidic approach is developed for integrated analysis of temporal signaling and cell migration dynamics in multiple cellular contexts (single-cell, population and coculture). This approach allows to confine the desired number or mixture of specific cell sample types in a single device. Precise single cell seeding was achieved manually with bidirectional controllability. Coupled with time-lapse imaging, temporal cellular responses can be observed with single-cell resolution. Using NIH3T3 cells stably expressing signal transducer and activator of transcription 1/2 (STAT1/2) activity biosensors, temporal STAT1/2 activation and cell migration dynamics were explored in isolated single cells, populations and cocultures stimulated with temporal inputs, such as single-pulse and continuous signals of interferon γ (IFNγ) or lipopolysaccharide (LPS). We demonstrate distinct dynamic responses of fibroblasts in different cellular contexts. Our presented approach facilitates a multi-dimensional understanding of STAT signaling and corresponding migration behaviors.

Multiplexed single-cell analysis of organoid signaling networks

Organoids are biomimetic tissue models comprising multiple cell types and cell states. Post-translational modification (PTM) signaling networks control cellular phenotypes and are frequently dysregulated in diseases such as cancer. Although signaling networks vary across cell types, there are limited techniques to study cell type-specific PTMs in heterocellular organoids. Here, we present a multiplexed mass cytometry (MC) protocol for single-cell analysis of PTM signaling and cell states in organoids and organoids co-cultured with fibroblasts and leukocytes. We describe how thiol-reactive organoid barcoding in situ (TOBis) enables 35-plex and 126-plex single-cell comparison of organoid cultures and provide a cytometry by time of flight (CyTOF) signaling analysis pipeline (CyGNAL) for computing cell type-specific PTM signaling networks. The TOBis MC protocol takes ~3 d from organoid fixation to data acquisition and can generate single-cell data for >40 antibodies from millions of cells across 126 organoid cultures in a single MC run.

Deciphering Organoids: High-Dimensional Analysis of Biomimetic Cultures

Organoids are self-organising stem cell-derived ex vivo cultures widely adopted as biomimetic models of healthy and diseased tissues. Traditional low-dimensional experimental methods such as microscopy and bulk molecular analysis have generated remarkable biological insights from organoids. However, as complex heterocellular systems, organoids are especially well-positioned to take advantage of emerging high-dimensional technologies. In particular, single-cell methods offer considerable opportunities to analyse organoids at unprecedented scale and depth, enabling comprehensive characterisation of cellular processes and spatial organisation underpinning organoid heterogeneity. This review evaluates state-of-the-art analytical methods applied to organoids, discusses the latest advances in single-cell technologies, and speculates on the integration of these two rapidly developing fields.

Intra- and intercellular signaling pathways associated with drug-induced cardiac pathophysiology

Cardiac physiology and homeostasis are maintained by the interaction of multiple cell types, via both intra- and intercellular signaling pathways. Perturbations in these signaling pathways induced by oncology therapies can reduce cardiac function, ultimately leading to heart failure. As cancer survival increases, related cardiovascular complications are becoming increasingly prevalent, thus identifying the perturbations and cell signaling drivers of cardiotoxicity is increasingly important. Here, we discuss the homotypic and heterotypic cellular interactions that form the basis of intra- and intercellular cardiac signaling pathways, and how oncological agents disrupt these pathways, leading to heart failure. We also highlight the emerging systems biology techniques that can be applied, enabling a deeper understanding of the intra- and intercellular signaling pathways across multiple cell types associated with cardiovascular toxicity.

Tumour microenvironment 3D-modelling: simplicity to complexity and back again

Tumours are surrounded by a host of noncancerous cells that fulfil both supportive and suppressive roles within the tumour microenvironment (TME). The drive to understand the biology behind each of these components has led to a rapid expansion in the number and use of 3D in vitro models, as researchers find ways to incorporate multiple cell types into physiomimetic configurations. The use and increasing complexity of these models does however demand many considerations. In this review we discuss approaches adopted to recapitulate complex tumour biology in tractable 3D models. We consider how these cell types can be sourced and combined and examine methods for the deconvolution of complex multicellular models into manageable and informative outputs.

Can mechanical forces attune heterotypic cell-cell communications?

Heterotypic cell lineages relentlessly exchange biomechanical signals among themselves in metazoan organs. Hence, cell-cell communications are pivotal for organ physiology and pathogenesis. Every cell lineage of an organ responds differently to a specific signal due to its unique receptibility and signal interpretation capacity. These distinct cellular responses generate a system-scale signaling network that helps in generating a specific organ phenotype. Although the reciprocal biochemical signal exchange between non-identical neighboring cells is known to be an essential factor for organ functioning, if, then how, mechanical cues incite these signals is not yet quite explored. Cells within organ tissues experience multiple mechanical forces, such as stretching, bending, compression, and shear stress. Forms and magnitudes of mechanical forces influence biochemical signaling in a cell-specific manner. Additionally, the biophysical state of acellular extracellular matrix (ECM) can transmit exclusive mechanical cues to specific cells of an organ. As it scaffolds heterotypic cells and tissues in close proximities, therefore, ECM can easily be contemplated as a mechanical conduit for signal exchange among them. However, force-stimulated signal transduction is not always physiological, aberrant force sensing by tissue-resident cells can transduce anomalous signals to each other, and potentially can promote pathological phenotypes. Herein, I attempt to put forward a perspective on how mechanical forces may influence signal transductions among heterotypic cell populations and how they feedback each other to achieve a transient or perpetual alteration in metazoan organs. A mechanistic insight of organ scale mechanotransduction can emanate the possibility of finding potential biomarkers and novel therapeutic strategies to deal with pathogenesis and organ regeneration.

Understanding cell-cell communication and signaling in the colorectal cancer microenvironment

Carcinomas are complex heterocellular systems containing epithelial cancer cells, stromal fibroblasts, and multiple immune cell-types. Cell-cell communication between these tumor microenvironments (TME) and cells drives cancer progression and influences response to existing therapies. In order to provide better treatments for patients, we must understand how various cell-types collaborate within the TME to drive cancer and consider the multiple signals present between and within different cancer types. To investigate how tissues function, we need a model to measure both how signals are transferred between cells and how that information is processed within cells. The interplay of collaboration between different cell-types requires cell-cell communication. This article aims to review the current in vitro and in vivo mono-cellular and multi-cellular cultures models of colorectal cancer (CRC), and to explore how they can be used for single-cell multi-omics approaches for isolating multiple types of molecules from a single-cell required for cell-cell communication to distinguish cancer cells from normal cells. Integrating the existing single-cell signaling measurements and models, and through understanding the cell identity and how different cell types communicate, will help predict drug sensitivities in tumor cells and between- and within-patients responses.

The tissue proteome in the multi-omic landscape of kidney disease

Kidney research is entering an era of 'big data' and molecular omics data can provide comprehensive insights into the molecular footprints of cells. In contrast to transcriptomics, proteomics and metabolomics generate data that relate more directly to the pathological symptoms and clinical parameters observed in patients. Owing to its complexity, the proteome still holds many secrets, but has great potential for the identification of drug targets. Proteomics can provide information about protein synthesis, modification and degradation, as well as insight into the physical interactions between proteins, and between proteins and other biomolecules. Thus far, proteomics in nephrology has largely focused on the discovery and validation of biomarkers, but the systematic analysis of the nephroproteome can offer substantial additional insights, including the discovery of mechanisms that trigger and propagate kidney disease. Moreover, proteome acquisition might provide a diagnostic tool that complements the assessment of a kidney biopsy sample by a pathologist. Such applications are becoming increasingly feasible with the development of high-throughput and high-coverage technologies, such as versatile mass spectrometry-based techniques and protein arrays, and encourage further proteomics research in nephrology.

A systems biology approach to discovering pathway signaling dysregulation in metastasis

Total metastatic burden is the primary cause of death for many cancer patients. While the process of metastasis has been studied widely, much remains to be understood. Moreover, few agents have been developed that specifically target the major steps of the metastatic cascade. Many individual genes and pathways have been implicated in metastasis but a holistic view of how these interact and cooperate to regulate and execute the process remains somewhat rudimentary. It is unclear whether all of the signaling features that regulate and execute metastasis are yet fully understood. Novel features of a complex system such as metastasis can often be discovered by taking a systems-based approach. We introduce the concepts of systems modeling and define some of the central challenges facing the application of a multidisciplinary systems-based approach to understanding metastasis and finding actionable targets therein. These challenges include appreciating the unique properties of the high-dimensional omics data often used for modeling, limitations in knowledge of the system (metastasis), tumor heterogeneity and sampling bias, and some of the issues key to understanding critical features of molecular signaling in the context of metastasis. We also provide a brief introduction to integrative modeling that focuses on both the nodes and edges of molecular signaling networks. Finally, we offer some observations on future directions as they relate to developing a systems-based model of the metastatic cascade.

Cell-type-specific signaling networks in heterocellular organoids

Despite the widespread adoption of organoids as biomimetic tissue models, methods to comprehensively analyze cell-type-specific post-translational modification (PTM) signaling networks in organoids are absent. Here, we report multivariate single-cell analysis of such networks in organoids and organoid cocultures. Simultaneous analysis by mass cytometry of 28 PTMs in >1 million single cells derived from small intestinal organoids reveals cell-type- and cell-state-specific signaling networks in stem, Paneth, enteroendocrine, tuft and goblet cells, as well as enterocytes. Integrating single-cell PTM analysis with thiol-reactive organoid barcoding in situ (TOBis) enables high-throughput comparison of signaling networks between organoid cultures. Cell-type-specific PTM analysis of colorectal cancer organoid cocultures reveals that shApc, KrasG12D and Trp53R172H cell-autonomously mimic signaling states normally induced by stromal fibroblasts and macrophages. These results demonstrate how standard mass cytometry workflows can be modified to perform high-throughput multivariate cell-type-specific signaling analysis of healthy and cancerous organoids.

Dissecting intercellular signaling with mass spectrometry-based proteomics

Physiological functions depend on a coordinated interplay of numerous different cell types. Proteins serve as major signaling molecules between cells; however, their comprehensive investigation in physiologically relevant settings has remained challenging. Mass spectrometry (MS)-based shotgun proteomics is emerging as a powerful technology for the systematic analysis of protein-mediated intercellular signaling and regulated post-translational modifications. Here, we discuss recent advancements in cell biological, chemical, and biochemical MS-based approaches for the profiling of cellular messengers released by sending cells, receptors expressed on the cell surface, and their interactions. We highlight methods tailored toward the mapping of dynamic signal transduction mechanisms at cellular interfaces and approaches to dissect communication cell specifically in heterocellular systems. Thereby, MS-based proteomics contributes a unique systems biology perspective for the identification of intercellular signaling pathways deregulated in disease.

Systems Biology of Cancer Metastasis

Cancer metastasis is no longer viewed as a linear cascade of events but rather as a series of concurrent, partially overlapping processes, as successfully metastasizing cells assume new phenotypes while jettisoning older behaviors. The lack of a systemic understanding of this complex phenomenon has limited progress in developing treatments for metastatic disease. Because metastasis has traditionally been investigated in distinct physiological compartments, the integration of these complex and interlinked aspects remains a challenge for both systems-level experimental and computational modeling of metastasis. Here, we present some of the current perspectives on the complexity of cancer metastasis, the multiscale nature of its progression, and a systems-level view of the processes underlying the invasive spread of cancer cells. We also highlight the gaps in our current understanding of cancer metastasis as well as insights emerging from interdisciplinary systems biology approaches to understand this complex phenomenon.

Systems biology: perspectives on multiscale modeling in research on endocrine-related cancers

Drawing on concepts from experimental biology, computer science, informatics, mathematics and statistics, systems biologists integrate data across diverse platforms and scales of time and space to create computational and mathematical models of the integrative, holistic functions of living systems. Endocrine-related cancers are well suited to study from a systems perspective because of the signaling complexities arising from the roles of growth factors, hormones and their receptors as critical regulators of cancer cell biology and from the interactions among cancer cells, normal cells and signaling molecules in the tumor microenvironment. Moreover, growth factors, hormones and their receptors are often effective targets for therapeutic intervention, such as estrogen biosynthesis, estrogen receptors or HER2 in breast cancer and androgen receptors in prostate cancer. Given the complexity underlying the molecular control networks in these cancers, a simple, intuitive understanding of how endocrine-related cancers respond to therapeutic protocols has proved incomplete and unsatisfactory. Systems biology offers an alternative paradigm for understanding these cancers and their treatment. To correctly interpret the results of systems-based studies requires some knowledge of how in silico models are built, and how they are used to describe a system and to predict the effects of perturbations on system function. In this review, we provide a general perspective on the field of cancer systems biology, and we explore some of the advantages, limitations and pitfalls associated with using predictive multiscale modeling to study endocrine-related cancers.

Harnessing the innate immune system and local immunological microenvironment to treat colorectal cancer

Significant progress in the development of new immunotherapies has led to successful clinical trials for malignant melanoma and non-small cell lung cancer; however, for the majority of solid tumours of the gastrointestinal tract, little or no progress has been seen. The efficacy of immunotherapies is limited by the complexities of a diverse set of immune cells, and interactions between the tumour cells and all other cells in the local microenvironment of solid tumours. A large fraction of immune cells present in and around solid tumours derive from the innate arm of the immune system and using these cells against tumours offers an alternative immunotherapeutic option, especially as current strategies largely harness the adaptive arm of the immune system. This option is currently being investigated and attempts at using the innate immune system for gastrointestinal cancers are showing initial results. Several important factors, including cytokines, chemotherapeutics and the microbiome, influence the plasticity and functionality of innate (myeloid) cells in the microenvironment, and this complexity of regulation has limited translation into successful trials so far. In this review, current concepts of the immunobiology of the innate arm in the tumour microenvironment are presented in the context of clinical translation.

A systems perspective of heterocellular signaling

Signal exchange between different cell types is essential for development and function of multicellular organisms, and its dysregulation is causal in many diseases. Unfortunately, most cell-signaling work has employed single cell types grown under conditions unrelated to their native context. Recent technical developments have started to provide the tools needed to follow signaling between multiple cell types, but gaps in the information they provide have limited their usefulness in building realistic models of heterocellular signaling. Currently, only targeted assays have the necessary sensitivity, selectivity, and spatial resolution to usefully probe heterocellular signaling processes, but these are best used to test specific, mechanistic models. Decades of systems biology research with monocultures has provided a solid foundation for building models of heterocellular signaling, but current models lack a realistic description of regulated proteolysis and the feedback processes triggered within and between cells. Identification and understanding of key regulatory processes in the extracellular environment and of recursive signaling patterns between cells will be essential to building predictive models of heterocellular systems.

Topography of cancer-associated immune cells in human solid tumors

Lymphoid and myeloid cells are abundant in the tumor microenvironment, can be quantified by immunohistochemistry and shape the disease course of human solid tumors. Yet, there is no comprehensive understanding of spatial immune infiltration patterns (‘topography’) across cancer entities and across various immune cell types. In this study, we systematically measure the topography of multiple immune cell types in 965 histological tissue slides from N = 177 patients in a pan-cancer cohort. We provide a definition of inflamed (‘hot’), non-inflamed (‘cold’) and immune excluded patterns and investigate how these patterns differ between immune cell types and between cancer types. In an independent cohort of N = 287 colorectal cancer patients, we show that hot, cold and excluded topographies for effector lymphocytes (CD8) and tumor-associated macrophages (CD163) alone are not prognostic, but that a bivariate classification system can stratify patients. Our study adds evidence to consider immune topographies as biomarkers for patients with solid tumors.

The Heterocellular Emergence of Colorectal Cancer

Tissues contain multiple different cell types and can be considered to be heterocellular systems. Signaling between different cells allows tissues to achieve phenotypes that no cell type can achieve in isolation. Such emergent tissue-level phenotypes can be said to 'supervene upon' heterocellular signaling. It is proposed here that cancer is also an emergent phenotype that supervenes upon heterocellular signaling. Using colorectal cancer (CRC) as an example, I review how heterotypic cells differentially communicate to support emergent malignancy. Studying tumors as integrated heterocellular systems - rather than as solitary expansions of mutated cells - may reveal novel ways to treat cancer.

NADPH metabolism: a survey of its theoretical characteristics and manipulation strategies in amino acid biosynthesis

Reduced nicotinamide adenine nucleotide phosphate (NADPH), which is one of the key cofactors in the metabolic network, plays an important role in the biochemical reactions, and physiological function of amino acid-producing strains. The manipulation of NADPH availability and form is an efficient and easy method of redirecting the carbon flux to the amino acid biosynthesis in industrial strains. In this review, we survey the metabolic mode of NADPH. Furthermore, we summarize the research developments in the understanding of the relationship between NADPH metabolism and amino acid biosynthesis. Detailed strategies to manipulate NADPH availability are addressed based on this knowledge. Finally, the uses of NADPH manipulation strategies to enhance the metabolic function of amino acid-producing strains are discussed.

Rational Design of Mouse Models for Cancer Research

The laboratory mouse is widely considered as a valid and affordable model organism to study human disease. Attempts to improve the relevance of murine models for the investigation of human pathologies led to the development of various genetically engineered, xenograft and humanized mouse models. Nevertheless, most preclinical studies in mice suffer from insufficient predictive value when compared with cancer biology and therapy response of human patients. We propose an innovative strategy to improve the predictive power of preclinical cancer models. Combining (i) genomic, tissue engineering and regenerative medicine approaches for rational design of mouse models with (ii) rapid prototyping and computational benchmarking against human clinical data will enable fast and nonbiased validation of newly generated models.

Integrated Strategies to Gain a Systems-Level View of Dynamic Signaling Networks

In order to survive and function properly in the face of an ever changing environment, cells must be able to sense changes in their surroundings and respond accordingly. Cells process information about their environment through complex signaling networks composed of many discrete signaling molecules. Individual pathways within these networks are often tightly integrated and highly dynamic, allowing cells to respond to a given stimulus (or, as is typically the case under physiological conditions, a combination of stimuli) in a specific and appropriate manner. However, due to the size and complexity of many cellular signaling networks, it is often difficult to predict how cellular signaling networks will respond under a particular set of conditions. Indeed, crosstalk between individual signaling pathways may lead to responses that are nonintuitive (or even counterintuitive) based on examination of the individual pathways in isolation. Therefore, to gain a more comprehensive view of cell signaling processes, it is important to understand how signaling networks behave at the systems level. This requires integrated strategies that combine quantitative experimental data with computational models. In this chapter, we first examine some of the progress that has recently been made toward understanding the systems-level regulation of cellular signaling networks, with a particular emphasis on phosphorylation-dependent signaling networks. We then discuss how genetically targetable fluorescent biosensors are being used together with computational models to gain unique insights into the spatiotemporal regulation of signaling networks within single, living cells.

Cell-selective proteomics for biological discovery

Cells alter the proteome to respond to environmental and developmental cues. Global analysis of proteomic responses is of limited value in heterogeneous environments, where there is no 'average' cell. Advances in sequencing, protein labeling, mass spectrometry, and data analysis have fueled recent progress in the investigation of specific subpopulations of cells in complex systems. Here we highlight recently developed chemical tools that enable cell-selective proteomic analysis of complex biological systems, from bacterial pathogens to whole animals.

Cell-Specific Labeling for Analyzing Bidirectional Signaling by Mass Spectrometry

Cell-specific proteome labeling enables global proteome-wide analysis of cell signaling in heterotypic co-cultures. Such approaches have provided unique insight in contact-initiated receptor tyrosine kinase signaling, transfer of proteomic material between heterotypic cells, and interactions between normal and oncogenic cells. Here we describe current methods for cell-specific labeling of heterotypic cells with isotopic labeled amino acids (e.g., SILAC and CTAP). We outline the advantages and disadvantages of individual approaches, describe typical experimental scenarios, and discuss where each experimental approach is optimally applied.