A systems perspective of heterocellular signaling

Bridging systems biology and tissue engineering: Unleashing the full potential of complex 3D in vitro tissue models of disease

Rapid advances in tissue engineering have resulted in more complex and physiologically relevant 3D in vitro tissue models with applications in fundamental biology and therapeutic development. However, the complexity provided by these models is often not leveraged fully due to the reductionist methods used to analyze them. Computational and mathematical models developed in the field of systems biology can address this issue. Yet, traditional systems biology has been mostly applied to simpler in vitro models with little physiological relevance and limited cellular complexity. Therefore, integrating these two inherently interdisciplinary fields can result in new insights and move both disciplines forward. In this review, we provide a systematic overview of how systems biology has been integrated with 3D in vitro tissue models and discuss key application areas where the synergies between both fields have led to important advances with potential translational impact. We then outline key directions for future research and discuss a framework for further integration between fields.

Reconstructing the cell-cell interaction network among mouse immune cells

Intercellular interactions and cell-cell communication are critical to regulating cell functions, especially in normal immune cells and immunotherapies. Ligand-receptor pairs mediating these cell-cell interactions can be identified using diverse experimental and computational approaches. Here, we reconstructed the intercellular interaction network between Mus musculus immune cells using publicly available receptor-ligand interaction databases and gene expression data from the immunological genome project. This reconstructed network accounts for 50,317 unique interactions between 16 cell types between 731 receptor-ligand pairs. Analysis of this network shows that cells of hematopoietic lineages use fewer communication pathways for interacting with each other, while nonhematopoietic stromal cells use the most network communications. We further observe that the WNT, BMP, and LAMININ pathways are the most significant contributors to the overall number of cell-cell interactions among the various pathways in the reconstructed communication network. This resource will enable the systematic analysis of normal and pathologic immune cell interactions, along with the study of emerging immunotherapies.

SPROUT: spectral sparsification helps restore the spatial structure at single-cell resolution

Single-cell RNA sequencing thoroughly quantifies the individual cell transcriptomes but renounces the spatial structure. Conversely, recently emerged spatial transcriptomics technologies capture the cellular spatial structure but skimp cell or gene resolutions. Ligand-receptor interactions reveal the potential of cell proximity since they are spatially constrained. Cell–cell affinity values estimated by ligand–receptor interaction can partially represent the structure of cells but falsely include the pseudo affinities between distant or indirectly interacting cells. Here, we develop a software package, SPROUT, to reconstruct the single-cell resolution spatial structure from the transcriptomics data through diminished pseudo ligand–receptor affinities. For spatial data, SPROUT first curates the representative single-cell profiles for each spatial spot from a candidate library, then reduces the pseudo affinities in the intercellular affinity matrix by partial correlation, spectral graph sparsification, and spatial coordinates refinement. SPROUT embeds the estimated interactions into a low-dimensional space with the cross-entropy objective to restore the intercellular structures, which facilitates the discovery of dominant ligand–receptor pairs between neighboring cells at single-cell resolution. SPROUT reconstructed structures achieved shape Pearson correlations ranging from 0.91 to 0.97 on the mouse hippocampus and human organ tumor microenvironment datasets. Furthermore, SPROUT can solely de novo reconstruct the structures at single-cell resolution, i.e., reaching the cell-type proximity correlations of 0.68 and 0.89 between reconstructed and immunohistochemistry-informed spatial structures on a human developing heart dataset and a tumor microenvironment dataset, respectively.

Lung Models to Evaluate Silver Nanoparticles’ Toxicity and Their Impact on Human Health

Nanomaterials (NMs) solve specific problems with remarkable results in several industrial and scientific areas. Among NMs, silver nanoparticles (AgNPs) have been extensively employed as drug carriers, medical diagnostics, energy harvesting devices, sensors, lubricants, and bioremediation. Notably, they have shown excellent antimicrobial, anticancer, and antiviral properties in the biomedical field. The literature analysis shows a selective cytotoxic effect on cancer cells compared to healthy cells, making its potential application in cancer treatment evident, increasing the need to study the potential risk of their use to environmental and human health. A large battery of toxicity models, both in vitro and in vivo, have been established to predict the harmful effects of incorporating AgNPs in these numerous areas or those produced due to involuntary exposure. However, these models often report contradictory results due to their lack of standardization, generating controversy and slowing the advances in nanotoxicology research, fundamentally by generalizing the biological response produced by the AgNP formulations. This review summarizes the last ten years’ reports concerning AgNPs’ toxicity in cellular respiratory system models (e.g., mono-culture models, co-cultures, 3D cultures, ex vivo and in vivo). In turn, more complex cellular models represent in a better way the physical and chemical barriers of the body; however, results should be used carefully so as not to be misleading. The main objective of this work is to highlight current models with the highest physiological relevance, identifying the opportunity areas of lung nanotoxicology and contributing to the establishment and strengthening of specific regulations regarding health and the environment.

Ligand-receptor promiscuity enables cellular addressing

In multicellular organisms, secreted ligands selectively activate, or "address," specific target cell populations to control cell fate decision-making and other processes. Key cell-cell communication pathways use multiple promiscuously interacting ligands and receptors, provoking the question of how addressing specificity can emerge from molecular promiscuity. To investigate this issue, we developed a general mathematical modeling framework based on the bone morphogenetic protein (BMP) pathway architecture. We find that promiscuously interacting ligand-receptor systems allow a small number of ligands, acting in combinations, to address a larger number of individual cell types, defined by their receptor expression profiles. Promiscuous systems outperform seemingly more specific one-to-one signaling architectures in addressing capability. Combinatorial addressing extends to groups of cell types, is robust to receptor expression noise, grows more powerful with increases in the number of receptor variants, and is maximized by specific biochemical parameter relationships. Together, these results identify design principles governing cellular addressing by ligand combinations.

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.

Data-driven learning how oncogenic gene expression locally alters heterocellular networks

Developing drugs increasingly relies on mechanistic modeling and simulation. Models that capture causal relations among genetic drivers of oncogenesis, functional plasticity, and host immunity complement wet experiments. Unfortunately, formulating such mechanistic cell-level models currently relies on hand curation, which can bias how data is interpreted or the priority of drug targets. In modeling molecular-level networks, rules and algorithms are employed to limit a priori biases in formulating mechanistic models. Here we combine digital cytometry with Bayesian network inference to generate causal models of cell-level networks linking an increase in gene expression associated with oncogenesis with alterations in stromal and immune cell subsets from bulk transcriptomic datasets. We predict how increased Cell Communication Network factor 4, a secreted matricellular protein, alters the tumor microenvironment using data from patients diagnosed with breast cancer and melanoma. Predictions are then tested using two immunocompetent mouse models for melanoma, which provide consistent experimental results.

While mechanistic models play increasing roles in immuno-oncology, hand network curation is current practice. Here the authors use a Bayesian data-driven approach to infer how expression of a secreted oncogene alters the cellular landscape within the tumor.

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.

Human physiomimetic model integrating microphysiological systems of the gut, liver, and brain for studies of neurodegenerative diseases

Slow progress in the fight against neurodegenerative diseases (NDs) motivates an urgent need for highly controlled in vitro systems to investigate organ-organ- and organ-immune-specific interactions relevant for disease pathophysiology. Of particular interest is the gut/microbiome-liver-brain axis for parsing out how genetic and environmental factors contribute to NDs. We have developed a mesofluidic platform technology to study gut-liver-cerebral interactions in the context of Parkinson's disease (PD). It connects microphysiological systems (MPSs) of the primary human gut and liver with a human induced pluripotent stem cell-derived cerebral MPS in a systemically circulated common culture medium containing CD4⁺ regulatory T and T helper 17 cells. We demonstrate this approach using a patient-derived cerebral MPS carrying the PD-causing A53T mutation, gaining two important findings: (i) that systemic interaction enhances features of in vivo-like behavior of cerebral MPSs, and (ii) that microbiome-associated short-chain fatty acids increase expression of pathology-associated pathways in PD.

Stereotactic ablative radiotherapy for colorectal cancer liver metastasis

Survival improvement of colorectal liver metastasis (CRLM) benefits from systemic therapy and metastasis-directed local therapy. Stereotactic ablative body radiotherapy (SABR), as a new efficient metastasis-directed local therapy with a systematic impact, plays a vital role in CRLM multidisciplinary treatment. SABR leads to a dramatic immunological change in the tumor microenvironment (TME) via differential activation of cytoprotective and cytotoxic pathways in malignant and non-malignant cells, in addition to direct tumor cell death. The synergy of SABR and immunotherapy might increase the abscopal response rate of out-field lesions by targeting different steps of the immune-mediated response, in addition to direct intratumoral cell death. The clinical treatment and efficacy of SABR, its influence on TME, and potential molecular underpinnings of which are the topic of this review.