Unraveling cell-to-cell signaling networks with chemical biology

Noninvasive in vivo microscopy of single neutrophils in the mouse brain via NIR-II fluorescent nanomaterials

In vivo microscopy of single cells enables following pathological changes in tissues, revealing signaling networks and cell interactions critical to disease progression. However, conventional intravital microscopy at visible and near-infrared wavelengths <900 nm (NIR-I) suffers from attenuation and is typically performed following the surgical creation of an imaging window. Such surgical procedures cause the alteration of the local vasculature and induce inflammation in skin, muscle and skull, inevitably altering the microenvironment in the imaging area. Here, we detail the use of near-infrared fluorescence (NIR-II, 1,000-1,700 nm) for in vivo microscopy to circumvent attenuation in living tissues. This approach enables the noninvasive visualization of cell migration in deep tissues by labeling specific cells with NIR-II lanthanide downshifting nanoparticles exhibiting high physicochemical stability and photostability. We further developed a NIR-II fluorescence microscopy setup for in vivo imaging through the intact skull with high spatiotemporal resolution, which we use for the real-time dynamic visualization of single-neutrophil behavior in the deep brain of a mouse model of ischemic stroke. The labeled downshifting nanoparticle synthesis takes 5-6 d, the imaging system setup takes 1-2 h, the in vivo cell labeling takes 1-3 h, the in vivo NIR-II microscopic imaging takes 3-5 h and the data analysis takes 3-8 h. The procedures can be performed by users with standard laboratory training in nanomaterials research and appropriate animal handling.

Identifying potential ligand-receptor interactions based on gradient boosted neural network and interpretable boosting machine for intercellular communication analysis

Cell-cell communication is essential to many key biological processes. Intercellular communication is generally mediated by ligand-receptor interactions (LRIs). Thus, building a comprehensive and high-quality LRI resource can significantly improve intercellular communication analysis. Meantime, due to lack of a "gold standard" dataset, it remains a challenge to evaluate LRI-mediated intercellular communication results. Here, we introduce CellGiQ, a high-confident LRI prediction framework for intercellular communication analysis. Highly confident LRIs are first inferred by LRI feature extraction with BioTriangle, LRI selection using LightGBM, and LRI classification based on ensemble of gradient boosted neural network and interpretable boosting machine. Subsequently, known and identified high-confident LRIs are filtered by combining single-cell RNA sequencing (scRNA-seq) data and further applied to intercellular communication inference through a quartile scoring strategy. To validation the predictions, CellGiQ exploited several evaluation strategies: using AUC and AUPR, it surpassed six competing LRI prediction models on four LRI datasets; through Venn diagrams and molecular docking, its predicted LRIs were validated by five other popular intercellular communication inference methods; based on the overlapping LRIs, it computed high Jaccard index with six other state-of-the-art intercellular communication prediction tools within human HNSCC tissues; by comparing with classical models and literature retrieve, its inferred HNSCC-related intercellular communication results was further validated. The novelty of this study is to identify high-confident LRIs based on machine learning as well as design several LRI validation ways, providing reference for computational LRI prediction. CellGiQ provides an open-source and useful tool to decompose LRI-mediated intercellular communication at single cell resolution. CellGiQ is freely available at https://github.com/plhhnu/CellGiQ.

Chemical biology tools for protein labelling: insights into cell-cell communication

Multicellular organisms require carefully orchestrated communication between and within cell types and tissues, and many unicellular organisms also sense their context and environment, sometimes coordinating their responses. This review highlights contributions from chemical biology in discovering and probing mechanisms of cell-cell communication. We focus on chemical tools for labelling proteins in a cellular context and how these can be applied to decipher the target receptor of a signalling molecule, label a receptor of interest in situ to understand its biology, provide a read-out of protein activity or interactions in downstream signalling pathways, or discover protein-protein interactions across cell-cell interfaces.

Engineering Tissue-Scale Properties with Synthetic Cells: Forging One from Many

In metazoans, living cells achieve capabilities beyond individual cell functionality by assembling into multicellular tissue structures. These higher-order structures represent dynamic, heterogeneous, and responsive systems that have evolved to regenerate and coordinate their actions over large distances. Recent advances in constructing micrometer-sized vesicles, or synthetic cells, now point to a future where construction of synthetic tissue can be pursued, a boon to pressing material needs in biomedical implants, drug delivery systems, adhesives, filters, and storage devices, among others. To fully realize the potential of synthetic tissue, inspiration has been and will continue to be drawn from new molecular findings on its natural counterpart. In this review, we describe advances in introducing tissue-scale features into synthetic cell assemblies. Beyond mere complexation, synthetic cells have been fashioned with a variety of natural and engineered molecular components that serve as initial steps toward morphological control and patterning, intercellular communication, replication, and responsiveness in synthetic tissue. Particular attention has been paid to the dynamics, spatial constraints, and mechanical strengths of interactions that drive the synthesis of this next-generation material, describing how multiple synthetic cells can act as one.

Sequential Control of Cellular Interactions Using Dynamic DNA Displacement

Intercellular interactions play a significant role in various complex biological processes, and their dysregulation promotes disease progression. To reveal the mechanisms of intercellular interactions without destroying basic life processes, it is necessary to mimic multicellular behaviors in vitro. However, the precise control of multicellular systems remains technically challenging owing to dynamic interactions. Here, we used DNA as a molecular lock and key to sequentially assemble and disassemble different cell clusters in a programmed way, regulating intercellular interactions. Tagging the surface of live cells with cholesterol-modified DNA enabled dynamical intercellular assemblies. By consecutively adding corresponding metaphorical locks (attaching DNA strands) and keys (detaching DNA strands), clusters of different cells could be sequentially formed. This strategy improved the capability of natural killer NK-92 cells to target tumor cells, improving the antitumor therapy efficacy. Our suggested approach allows dynamic regulation of intercellular interactions in complex cell systems and increases understanding of intercellular communication networks.

Recent Advances in DNA-Based Cell Surface Engineering for Biological Applications

Due to its excellent programmability and biocompatibility, DNA molecule has unique advantages in cell surface engineering. Recent progresses provide a reliable and feasible way to engineer cell surfaces with diverse DNA molecules and DNA nanostructures. The abundant form of DNA nanostructures has greatly expanded the toolbox of DNA-based cell surface engineering and gave rise to a variety of novel and fascinating applications. In this review, we summarize recent advances in DNA-based cell surface engineering and its biological applications. We first introduce some widely used methods of immobilizing DNA molecules on cell surfaces and their application features. Then we discuss the approaches of employing DNA nanostructures and dynamic DNA nanotechnology as elements for creating functional cell surfaces. Finally, we review the extensive biological applications of DNA-based cell surface engineering and discuss the challenges and prospects of DNA-based cell surface engineering.

DNA Nanotechnology-Empowered Live Cell Measurements

The systematic analysis and precise manipulation of a variety of biomolecules should lead to unprecedented findings in fundamental biology. However, conventional technology cannot meet the current requirements. Despite this, there has been progress as DNA nanotechnology has evolved to generate DNA nanostructures and circuits over the past four decades. Many potential applications of DNA nanotechnology for live cell measurements have begun to emerge owing to the biocompatibility, nanometer addressability, and stimulus responsiveness of DNA. In this review, the DNA nanotechnology-empowered live cell measurements which are currently available are summarized. The stability of the DNA nanostructures, in a cellular microenvironment, which is crucial for accomplishing precise live cell measurements, is first summarized. Thereafter, measurements in the extracellular and intracellular microenvironment, in live cells, are introduced. Finally, the challenges that are innate to, and the further developments that are possible in this nascent field are discussed.

Cell-Based Ambient Venturi Autosampling and Matrix-Assisted Laser Desorption Ionization Mass Spectrometric Imaging of Secretory Products

A cell-based ambient Venturi autosampling device was established for the monitoring of dynamic cell secretions in response to chemical stimulations in real time with temporal resolution on the order of a second. Detection of secretory products of cells and screening of bioactive compounds are primarily performed on an ambient autosampling probe and matrix-assisted laser desorption ionization (MALDI) mass spectrometry. It takes advantage of the Venturi effect in which the fluid flowing through an inlet capillary tube is automatically fed into a parallel array of multiple outlet capillaries. Cells are incubated inside the inlet capillary tube that is connected with either a syringe pump or liquid chromatography (LC) for the transfer of single compounds or mixtures, respectively. Secretory products were continuously pushed into the outlet capillaries and then spotted into a compressed thin film of the matrix material 9-aminoacridine for MALDI mass spectrometric imaging. In physiological pH, without the use of high voltages and without the use of chemical derivatizations, this platform can be applied to the direct assay of neurotransmitters or other secretory products released from cells in response to the stimulation of individual compounds or LC-separated eluates of natural mixtures. It provides a new way to identify bioactive compounds with a detection limit down to 0.04 fmol/pixel.

Magnetophoretic Micro-Distributor for Controlled Clustering of Cells

Cell clustering techniques are important to produce artificial cell clusters for in vitro models of intercellular mechanisms at the single-cell level. The analyses considering physical variables such as the shape and size of cells have been very limited. In addition, the precise manipulation of cells and control of the physical variables are still challenging. In this paper, a magnetophoretic device consisting of a trampoline micromagnet and active elements that enable the control of individual selective jumping motion and positioning of a micro-object is proposed. Based on a numerical simulation under various conditions, automatic separation or selective clustering of micro-objects according to their sizes is performed by parallel control and programmable manipulation. This method provides efficient control of the physical variables of cells and grouping of cells with the desired size and number, which can be a milestone for a better understanding of the intercellular dynamics between clustered cells at the single-cell level for future cell-on-chip applications.

Reconstructing Soma-Soma Synapse-like Vesicular Exocytosis with DNA Origami

Cell-cell communications exhibit distinct physiological functions in immune responses and neurotransmitter signaling. Nevertheless, the ability to reconstruct a soma-soma synapse-like junction for probing intercellular communications remains difficult. In this work, we develop a DNA origami nanostructure-based method for establishing cell conjugation, which consequently facilitates the reconstruction of a soma-soma synapse-like junction. We demonstrate that intercellular communications including small molecule and membrane vesicle exchange between cells are maintained in the artificially designed synapse-like junction. By inserting the carbon fiber nanometric electrodes into the soma-soma synapse-like junction, we accomplish the real-time monitoring of individual vesicular exocytotic events and obtain the information on vesicular exocytosis kinetics via analyzing the parameters of current spikes. This strategy provides a versatile platform to study synaptic communications.

Nanoscale Catalyst Chemotaxis Can Drive the Assembly of Functional Pathways

Recent experiments demonstrate molecular chemotaxis or altered diffusion rates of enzymes in the presence of their own substrates. We show here an important implication, namely, that if a nanoscale catalyst A produces a small-molecule ligand product L which is the substrate of another catalyst B, the two catalysts will attract each other. We explore this nonequilibrium producer recruitment force (ProRec) in a reaction-diffusion model. The predicted cat-cat association will be the strongest when A is a fast producer of L and B is a tight binder to it. ProRec is a force that could drive a mechanism (the catpath mechanism) by which catalysts could become spatially localized into functional pathways, such as in the biochemical networks in cells, which can achieve complex goals.

A Chemical Approach for Programmable Protein Outputs Based on Engineered Cell Interactions

Cell-cell interactions and communication are crucial to the proper function of complex mammalian physiology including neurocognitive and immune system functions. While many tools are available for observing and perturbing intracellular processes, relatively few exist to probe intercellular processes. Current techniques for studying interactions often rely on direct protein contact, and few can manipulate diverse, functional outputs with tunable protein expression. To address these limitations, we have developed a small-molecule approach based on a trimethoprim prodrug-enzyme pair capable of reporting the presence of two different engineered cell populations with programmable protein outputs. The approach relies on bacterial nitroreductase enzyme catalysis, which is orthogonal to normal mammalian biology, and diffusion of trimethoprim from "activator" cells to "receiver" cells. We test this strategy, which can theoretically regulate many different types of proteins, using biochemical and in vitro culture assays with optical and cytokine protein readouts. This describes the first small-molecule approach capable of detecting and controlling engineered cell-cell outputs, and we anticipate future applications that are especially relevant to the field of immuno-oncology.

FunRes: resolving tissue-specific functional cell states based on a cell-cell communication network model

The functional specialization of cell types arises during development and is shaped by cell-cell communication networks determining a distribution of functional cell states that are collectively important for tissue functioning. However, the identification of these tissue-specific functional cell states remains challenging. Although a plethora of computational approaches have been successful in detecting cell types and subtypes, they fail in resolving tissue-specific functional cell states. To address this issue, we present FunRes, a computational method designed for the identification of functional cell states. FunRes relies on scRNA-seq data of a tissue to initially reconstruct the functional cell-cell communication network, which is leveraged for partitioning each cell type into functional cell states. We applied FunRes to 177 cell types in 10 different tissues and demonstrated that the detected states correspond to known functional cell states of various cell types, which cannot be recapitulated by existing computational tools. Finally, we characterize emerging and vanishing functional cell states in aging and disease, and demonstrate their involvement in key tissue functions. Thus, we believe that FunRes will be of great utility in the characterization of the functional landscape of cell types and the identification of dysfunctional cell states in aging and disease.

CellTalkDB: a manually curated database of ligand-receptor interactions in humans and mice

Cell-cell communications in multicellular organisms generally involve secreted ligand-receptor (LR) interactions, which is vital for various biological phenomena. Recent advancements in single-cell RNA sequencing (scRNA-seq) have effectively resolved cellular phenotypic heterogeneity and the cell-type composition of complex tissues, facilitating the systematic investigation of cell-cell communications at single-cell resolution. However, assessment of chemical-signal-dependent cell-cell communication through scRNA-seq relies heavily on prior knowledge of LR interaction pairs. We constructed CellTalkDB (http://tcm.zju.edu.cn/celltalkdb), a manually curated comprehensive database of LR interaction pairs in humans and mice comprising 3398 human LR pairs and 2033 mouse LR pairs, through text mining and manual verification of known protein-protein interactions using the STRING database, with literature-supported evidence for each pair. Compared with SingleCellSignalR, the largest LR-pair resource, CellTalkDB includes not only 2033 mouse LR pairs but also 377 additional human LR pairs. In conclusion, the data on human and mouse LR pairs contained in CellTalkDB could help to further the inference and understanding of the LR-interaction-based cell-cell communications, which might provide new insights into the mechanism underlying biological processes.

New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data

For multicellular organisms, cell-cell communication is essential to numerous biological processes. Drawing upon the latest development of single-cell RNA-sequencing (scRNA-seq), high-resolution transcriptomic data have deepened our understanding of cellular phenotype heterogeneity and composition of complex tissues, which enables systematic cell-cell communication studies at a single-cell level. We first summarize a common workflow of cell-cell communication study using scRNA-seq data, which often includes data preparation, construction of communication networks, and result validation. Two common strategies taken to uncover cell-cell communications are reviewed, e.g., physically vicinal structure-based and ligand-receptor interaction-based one. To conclude, challenges and current applications of cell-cell communication studies at a single-cell resolution are discussed in details and future perspectives are proposed.

CIRCOAST: a statistical hypothesis test for cellular colocalization with network structures

Motivation

Colocalization of structures in biomedical images can lead to insights into biological behaviors. One class of colocalization problems is examining an annular structure (disk-shaped such as a cell, vesicle or molecule) interacting with a network structure (vascular, neuronal, cytoskeletal, organellar). Examining colocalization events across conditions is often complicated by changes in density of both structure types, confounding traditional statistical approaches since colocalization cannot be normalized to the density of both structure types simultaneously. We have developed a technique to measure colocalization independent of structure density and applied it to characterizing intercellular colocation with blood vessel networks. This technique could be used to analyze colocalization of any annular structure with an arbitrarily shaped network structure.

Results

We present the circular colocalization affinity with network structures test (CIRCOAST), a novel statistical hypothesis test to probe for enriched network colocalization in 2D z-projected multichannel images by using agent-based Monte Carlo modeling and image processing to generate the pseudo-null distribution of random cell placement unique to each image. This hypothesis test was validated by confirming that adipose-derived stem cells (ASCs) exhibit enriched colocalization with endothelial cells forming arborized networks in culture and then applied to show that locally delivered ASCs have enriched colocalization with murine retinal microvasculature in a model of diabetic retinopathy. We demonstrate that the CIRCOAST test provides superior power and type I error rates in characterizing intercellular colocalization compared to generic approaches that are confounded by changes in cell or vessel density.

Availability and implementation

CIRCOAST source code available at: https://github.com/uva-peirce-cottler-lab/ARCAS.

Supplementary information

Supplementary data are available at Bioinformatics online.

Designing azobenzene-based tools for controlling neurotransmission

Chemical and electrical signaling at the synapse is a dynamic process that is crucial to neurotransmission and pathology. Traditional pharmacotherapy has found countless applications in both academic labs and the clinic; however, diffusible drugs lack spatial and temporal precision when employed in heterogeneous tissues such as the brain. In the field of photopharmacology, chemical attachment of a synthetic photoswitch to a bioactive ligand allows cellular signaling to be controlled with light. Azobenzenes have remained the go-to photoswitch for biological applications due to their tunable photophysical properties, and can be leveraged to achieve reversible optical control of numerous receptors and ion channels. Here, we discuss the most recent advances in photopharmacology which will improve the use of azobenzene-based probes for neuroscience applications.

In proteins, the structural responses of a position to mutation rely on the Goldilocks principle: not too many links, not too few

A disease has distinct genetic and molecular hallmarks such as sequence variants that are likely to produce the alternative protein structures accountable for individual responses to drugs and disease development.

Design of biomimetic cellular scaffolds for co-culture system and their application

The extracellular matrix of most natural tissues comprises various types of cells, including fibroblasts, stem cells, and endothelial cells, which communicate with each other directly or indirectly to regulate matrix production and cell functionality. To engineer multicellular interactions in vitro, co-culture systems have achieved tremendous success achieving a more realistic microenvironment of in vivo metabolism than monoculture system in the past several decades. Recently, the fields of tissue engineering and regenerative medicine have primarily focused on three-dimensional co-culture systems using cellular scaffolds, because of their physical and biological relevance to the extracellular matrix of actual tissues. This review discusses several materials and methods to create co-culture systems, including hydrogels, electrospun fibers, microfluidic devices, and patterning for biomimetic co-culture system and their applications for specific tissue regeneration. Consequently, we believe that culture systems with appropriate physical and biochemical properties should be developed, and direct or indirect cell-cell interactions in the remodeled tissue must be considered to obtain an optimal tissue-specific microenvironment.