A Quantitative Multivariate Model of Human Dendritic Cell-T Helper Cell Communication.

Cell-cell communication involves a large number of molecular signals that function as words of a complex language whose grammar remains mostly unknown. Here, we describe an integrative approach involving (1) protein-level measurement of multiple communication signals coupled to output responses in receiving cells and (2) mathematical modeling to uncover input-output relationships and interactions between signals. Using human dendritic cell (DC)-T helper (Th) cell communication as a model, we measured 36 DC-derived signals and 17 Th cytokines broadly covering Th diversity in 428 observations. We developed a data-driven, computationally validated model capturing 56 already described and 290 potentially novel mechanisms of Th cell specification. By predicting context-dependent behaviors, we demonstrate a new function for IL-12p70 as an inducer of Th17 in an IL-1 signaling context. This work provides a unique resource to decipher the complex combinatorial rules governing DC-Th cell communication and guide their manipulation for vaccine design and immunotherapies.

Mechanisms of Virulence Reprogramming in Bacterial Pathogens.

Bacteria are single-celled organisms that carry a comparatively small set of genetic information, typically consisting of a few thousand genes that can be selectively activated or repressed in an energy-efficient manner and transcribed to encode various biological functions in accordance with environmental changes. Research over the last few decades has uncovered various ingenious molecular mechanisms that allow bacterial pathogens to sense and respond to different environmental cues or signals to activate or suppress the expression of specific genes in order to suppress host defenses and establish infections. In the setting of infection, pathogenic bacteria have evolved various intelligent mechanisms to reprogram their virulence to adapt to environmental changes and maintain a dominant advantage over host and microbial competitors in new niches. This review summarizes the bacterial virulence programming mechanisms that enable pathogens to switch from acute to chronic infection, from local to systemic infection, and from infection to colonization. It also discusses the implications of these findings for the development of new strategies to combat bacterial infections.

The phc Quorum-Sensing System in Ralstonia solanacearum Species Complex.

Ralstonia solanacearum species complex (RSSC) strains are devastating plant pathogens distributed worldwide. The primary cell density-dependent gene expression system in RSSC strains is phc quorum sensing (QS). It regulates the expression of about 30% of all genes, including those related to cellular activity, primary and secondary metabolism, pathogenicity, and more. The phc regulatory elements encoded by the phcBSRQ operon and phcA gene play vital roles. RSSC strains use methyl 3-hydroxymyristate (3-OH MAME) or methyl 3-hydroxypalmitate (3-OH PAME) as the QS signal. Each type of RSSC strain has specificity in generating and receiving its QS signal, but their signaling pathways might not differ significantly. In this review, I describe the genetic and biochemical factors involved in QS signal input and the regulatory network and summarize control of the phc QS system, new cell-cell communications, and QS-dependent interactions with soil fungi.

Biogenesis, secretion, and intercellular interactions of exosomes and other extracellular vesicles.

In the 1980s, exosomes were described as vesicles of endosomal origin secreted from reticulocytes. Interest increased around these extracellular vesicles, as they appeared to participate in several cellular processes. Exosomes bear proteins, lipids, and RNAs, mediating intercellular communication between different cell types in the body, and thus affecting normal and pathological conditions. Only recently, scientists acknowledged the difficulty of separating exosomes from other types of extracellular vesicles, which precludes a clear attribution of a particular function to the different types of secreted vesicles. To shed light into this complex but expanding field of science, this review focuses on the definition of exosomes and other secreted extracellular vesicles. Their biogenesis, their secretion, and their subsequent fate are discussed, as their functions rely on these important processes.

The Making of a Heterocyst in Cyanobacteria.

Heterocyst differentiation that occurs in some filamentous cyanobacteria, such as Anabaena sp. PCC 7120, provides a unique model for prokaryotic developmental biology. Heterocyst cells are formed in response to combined-nitrogen deprivation and possess a microoxic environment suitable for nitrogen fixation following extensive morphological and physiological reorganization. A filament of Anabaena is a true multicellular organism, as nitrogen and carbon sources are exchanged among different cells and cell types through septal junctions to ensure filament growth. Because heterocysts are terminally differentiated cells and unable to divide, their activity is an altruistic behavior dedicated to providing fixed nitrogen for neighboring vegetative cells. Heterocyst development is also a process of one-dimensional pattern formation, as heterocysts are semiregularly intercalated among vegetative cells. Morphogens form gradients along the filament and interact with each other in a fashion that fits well into the Turing model, a mathematical framework to explain biological pattern formation.

Formation of recurring transient Ca2+-based intercellular communities during Drosophila hematopoiesis.

Tissue development occurs through a complex interplay between many individual cells. Yet, the fundamental question of how collective tissue behavior emerges from heterogeneous and noisy information processing and transfer at the single-cell level remains unknown. Here, we reveal that tissue scale signaling regulation can arise from local gap-junction mediated cell-cell signaling through the spatiotemporal establishment of an intermediate-scale of transient multicellular communication communities over the course of tissue development. We demonstrated this intermediate scale of emergent signaling using Ca2+ signaling in the intact, ex vivo cultured, live developing Drosophila hematopoietic organ, the lymph gland. Recurrent activation of these transient signaling communities defined self-organized signaling "hotspots" that gradually formed over the course of larva development. These hotspots receive and transmit information to facilitate repetitive interactions with nonhotspot neighbors. Overall, this work bridges the scales between single-cell and emergent group behavior providing key mechanistic insight into how cells establish tissue-scale communication networks.

MetalinksDB: a flexible and contextualizable resource of metabolite-protein interactions.

From the catalytic breakdown of nutrients to signaling, interactions between metabolites and proteins play an essential role in cellular function. An important case is cell-cell communication, where metabolites, secreted into the microenvironment, initiate signaling cascades by binding to intra- or extracellular receptors of neighboring cells. Protein-protein cell-cell communication interactions are routinely predicted from transcriptomic data. However, inferring metabolite-mediated intercellular signaling remains challenging, partially due to the limited size of intercellular prior knowledge resources focused on metabolites. Here, we leverage knowledge-graph infrastructure to integrate generalistic metabolite-protein with curated metabolite-receptor resources to create MetalinksDB. MetalinksDB is an order of magnitude larger than existing metabolite-receptor resources and can be tailored to specific biological contexts, such as diseases, pathways, or tissue/cellular locations. We demonstrate MetalinksDB's utility in identifying deregulated processes in renal cancer using multi-omics bulk data. Furthermore, we infer metabolite-driven intercellular signaling in acute kidney injury using spatial transcriptomics data. MetalinksDB is a comprehensive and customizable database of intercellular metabolite-protein interactions, accessible via a web interface (https://metalinks.omnipathdb.org/) and programmatically as a knowledge graph (https://github.com/biocypher/metalinks). We anticipate that by enabling diverse analyses tailored to specific biological contexts, MetalinksDB will facilitate the discovery of disease-relevant metabolite-mediated intercellular signaling processes.

Revealing cell-cell communication pathways with their spatially coupled gene programs.

Inference of cell-cell communication (CCC) provides valuable information in understanding the mechanisms of many important life processes. With the rise of spatial transcriptomics in recent years, many methods have emerged to predict CCCs using spatial information of cells. However, most existing methods only describe CCCs based on ligand-receptor interactions, but lack the exploration of their upstream/downstream pathways. In this paper, we proposed a new method to infer CCCs, called Intercellular Gene Association Network (IGAN). Specifically, it is for the first time that we can estimate the gene associations/network between two specific single spatially adjacent cells. By using the IGAN method, we can not only infer CCCs in an accurate manner, but also explore the upstream/downstream pathways of ligands/receptors from the network perspective, which are actually exhibited as a new panoramic cell-interaction-pathway graph, and thus provide extensive information for the regulatory mechanisms behind CCCs. In addition, IGAN can measure the CCC activity at single cell/spot resolution, and help to discover the CCC spatial heterogeneity. Interestingly, we found that CCC patterns from IGAN are highly consistent with the spatial microenvironment patterns for each cell type, which further indicated the accuracy of our method. Analyses on several public datasets validated the advantages of IGAN.

Visualizing cell-cell communication using synthetic notch activated MRI.

Cell-cell communication plays a fundamental role in multicellular organisms. Cell-based cancer immunotherapies rely on the ability of innate or engineered receptors on immune cells to engage specific antigens on cancer cells to induce tumor kill. To improve the development and translation of these therapies, imaging tools capable of noninvasively and spatiotemporally visualizing immune-cancer cell interactions would be highly valuable. Using the synthetic Notch (SynNotch) system, we engineered T cells that upon interaction with a chosen antigen (CD19) on neighboring cancer cells induce the expression of optical reporter genes and the human-derived, magnetic resonance imaging (MRI) reporter gene organic anion transporting polypeptide 1B3 (OATP1B3). Administration of engineered T cells induced the antigen-dependent expression of all our reporter genes in mice bearing CD19-positive tumors but not CD19-negative tumors. Notably, due to the high spatial resolution and tomographic nature of MRI, contrast-enhanced foci within CD19-positive tumors representing OATP1B3-expressing T cells were clearly visible and their distribution was readily mapped. We then extended this technology onto human natural killer-92 (NK-92) cells, observing similar CD19-dependent reporter activity in tumor-bearing mice. Furthermore, we show that when delivered intravenously, engineered NK-92 cells can be detected via bioluminescence imaging in a systemic cancer model. With continued work, this highly modular imaging strategy could aid in the monitoring of cell therapies in patients and, beyond this, augment our understanding of how different cell populations interact within the body during normal physiology or disease.

Decoding functional cell-cell communication events by multi-view graph learning on spatial transcriptomics.

Cell-cell communication events (CEs) are mediated by multiple ligand-receptor (LR) pairs. Usually only a particular subset of CEs directly works for a specific downstream response in a particular microenvironment. We name them as functional communication events (FCEs) of the target responses. Decoding FCE-target gene relations is: important for understanding the mechanisms of many biological processes, but has been intractable due to the mixing of multiple factors and the lack of direct observations. We developed a method HoloNet for decoding FCEs using spatial transcriptomic data by integrating LR pairs, cell-type spatial distribution and downstream gene expression into a deep learning model. We modeled CEs as a multi-view network, developed an attention-based graph learning method to train the model for generating target gene expression with the CE networks, and decoded the FCEs for specific downstream genes by interpreting trained models. We applied HoloNet on three Visium datasets of breast cancer and liver cancer. The results detangled the multiple factors of FCEs by revealing how LR signals and cell types affect specific biological processes, and specified FCE-induced effects in each single cell. We conducted simulation experiments and showed that HoloNet is more reliable on LR prioritization in comparison with existing methods. HoloNet is a powerful tool to illustrate cell-cell communication landscapes and reveal vital FCEs that shape cellular phenotypes. HoloNet is available as a Python package at https://github.com/lhc17/HoloNet.

A Bacterial Tower of Babel: Quorum-Sensing Signaling Diversity and Its Evolution.

Quorum sensing is a process in which bacteria secrete and sense a diffusible molecule, thereby enabling bacterial groups to coordinate their behavior in a density-dependent manner. Quorum sensing has evolved multiple times independently, utilizing different molecular pathways and signaling molecules. A common theme among many quorum-sensing families is their wide range of signaling diversity-different variants within a family code for different signal molecules with a cognate receptor specific to each variant. This pattern of vast allelic polymorphism raises several questions-How do different signaling variants interact with one another? How is this diversity maintained? And how did it come to exist in the first place? Here we argue that social interactions between signaling variants can explain the emergence and persistence of signaling diversity throughout evolution. Finally, we extend the discussion to include cases where multiple diverse systems work in concert in a single bacterium.

Predicting intercellular communication based on metabolite-related ligand-receptor interactions with MRCLinkdb.

BACKGROUND: Metabolite-associated cell communications play critical roles in maintaining human biological function. However, most existing tools and resources focus only on ligand-receptor interaction pairs where both partners are proteinaceous, neglecting other non-protein molecules. To address this gap, we introduce the MRCLinkdb database and algorithm, which aggregates and organizes data related to non-protein L-R interactions in cell-cell communication, providing a valuable resource for predicting intercellular communication based on metabolite-related ligand-receptor interactions. RESULTS: Here, we manually curated the metabolite-ligand-receptor (ML-R) interactions from the literature and known databases, ultimately collecting over 790 human and 670 mouse ML-R interactions. Additionally, we compiled information on over 1900 enzymes and 260 transporter entries associated with these metabolites. We developed Metabolite-Receptor based Cell Link Database (MRCLinkdb) to store these ML-R interactions data. Meanwhile, the platform also offers extensive information for presenting ML-R interactions, including fundamental metabolite information and the overall expression landscape of metabolite-associated gene sets (such as receptor, enzymes, and transporter proteins) based on single-cell transcriptomics sequencing (covering 35 human and 26 mouse tissues, 52 human and 44 mouse cell types) and bulk RNA-seq/microarray data (encompassing 62 human and 39 mouse tissues). Furthermore, MRCLinkdb introduces a web server dedicated to the analysis of intercellular communication based on ML-R interactions. MRCLinkdb is freely available at https://www.cellknowledge.com.cn/mrclinkdb/ . CONCLUSIONS: In addition to supplementing ligand-receptor databases, MRCLinkdb may provide new perspectives for decoding the intercellular communication and advancing related prediction tools based on ML-R interactions.

Fibroblasts and macrophages: Collaborators in tissue homeostasis.

Fibroblasts and macrophages are universal cell types across all mammalian tissues. These cells differ in many ways including their cellular origins; dynamics of renewal, recruitment, and motility within tissues; roles in tissue structure and secretion of signaling molecules; and contributions to the activation and progression of immune responses. However, many of the features that make these two cell types unique are not opposing, but instead complementary. This review will present cell-cell communication in this context and discuss how complementarity makes fibroblasts and macrophages highly compatible partners in the maintenance of tissue homeostasis.

Dynamical hallmarks of cancer: Phenotypic switching in melanoma and epithelial-mesenchymal plasticity.

Phenotypic plasticity was recently incorporated as a hallmark of cancer. This plasticity can manifest along many interconnected axes, such as stemness and differentiation, drug-sensitive and drug-resistant states, and between epithelial and mesenchymal cell-states. Despite growing acceptance for phenotypic plasticity as a hallmark of cancer, the dynamics of this process remains poorly understood. In particular, the knowledge necessary for a predictive understanding of how individual cancer cells and populations of cells dynamically switch their phenotypes in response to the intensity and/or duration of their current and past environmental stimuli remains far from complete. Here, we present recent investigations of phenotypic plasticity from a systems-level perspective using two exemplars: epithelial-mesenchymal plasticity in carcinomas and phenotypic switching in melanoma. We highlight how an integrated computational-experimental approach has helped unravel insights into specific dynamical hallmarks of phenotypic plasticity in different cancers to address the following questions: a) how many distinct cell-states or phenotypes exist?; b) how reversible are transitions among these cell-states, and what factors control the extent of reversibility?; and c) how might cell-cell communication be able to alter rates of cell-state switching and enable diverse patterns of phenotypic heterogeneity? Understanding these dynamic features of phenotypic plasticity may be a key component in shifting the paradigm of cancer treatment from reactionary to a more predictive, proactive approach.

The Legionella autoinducer LAI-1 is delivered by outer membrane vesicles to promote interbacterial and interkingdom signaling.

Legionella pneumophila is an environmental bacterium, which replicates in amoeba but also in macrophages, and causes a life-threatening pneumonia called Legionnaires' disease. The opportunistic pathogen employs the α-hydroxy-ketone compound Legionella autoinducer-1 (LAI-1) for intraspecies and interkingdom signaling. LAI-1 is produced by the autoinducer synthase Legionella quorum sensing A (LqsA), but it is not known, how LAI-1 is released by the pathogen. Here, we use a Vibrio cholerae luminescence reporter strain and liquid chromatography-tandem mass spectrometry to detect bacteria-produced and synthetic LAI-1. Ectopic production of LqsA in Escherichia coli generated LAI-1, which partitions to outer membrane vesicles (OMVs) and increases OMV size. These E. coli OMVs trigger luminescence of the V. cholerae reporter strain and inhibit the migration of Dictyostelium discoideum amoeba. Overexpression of lqsA in L.pneumophila under the control of strong stationary phase promoters (PflaA or P6SRNA), but not under control of its endogenous promoter (PlqsA), produces LAI-1, which is detected in purified OMVs. These L. pneumophila OMVs trigger luminescence of the Vibrio reporter strain and inhibit D. discoideum migration. L. pneumophila OMVs are smaller upon overexpression of lqsA or upon addition of LAI-1 to growing bacteria, and therefore, LqsA affects OMV production. The overexpression of lqsA but not a catalytically inactive mutant promotes intracellular replication of L. pneumophila in macrophages, indicating that intracellularly produced LA1-1 modulates the interaction in favor of the pathogen. Taken together, we provide evidence that L. pneumophila LAI-1 is secreted through OMVs and promotes interbacterial communication and interactions with eukaryotic host cells.

Regulation of stomatal development by epidermal, subepidermal and long-distance signals.

Plant leaves consist of three layers, including epidermis, mesophyll and vascular tissues. Their development is meticulously orchestrated. Stomata are the specified structures on the epidermis for uptake of carbon dioxide (CO2) while release of water vapour and oxygen (O2), and thus play essential roles in regulation of plant photosynthesis and water use efficiency. To function efficiently, stomatal formation must coordinate with the development of other epidermal cell types, such as pavement cell and trichome, and tissues of other layers, such as mesophyll and leaf vein. This review summarizes the regulation of stomatal development in three dimensions (3D). In the epidermis, specific stomatal transcription factors determine cell fate transitions and also activate a ligand-receptor- MITOGEN-ACTIVATED PROTEIN KINASE (MAPK) signaling for ensuring proper stomatal density and patterning. This forms the core regulation network of stomatal development, which integrates various environmental cues and phytohormone signals to modulate stomatal production. Under the epidermis, mesophyll, endodermis of hypocotyl and inflorescence stem, and veins in grasses secrete mobile signals to influence stomatal formation in the epidermis. In addition, long-distance signals which may include phytohormones, RNAs, peptides and proteins originated from other plant organs modulate stomatal development, enabling plants to systematically adapt to the ever changing environment.

Utilizing human cerebral organoids to model breast cancer brain metastasis in culture.

BACKGROUND: Metastasis, the spread, and growth of malignant cells at secondary sites within a patient's body, accounts for over 90% of cancer-related mortality. Breast cancer is the most common tumor type diagnosed and the leading cause of cancer lethality in women in the United States. It is estimated that 10-16% breast cancer patients will have brain metastasis. Current therapies to treat patients with breast cancer brain metastasis (BCBM) remain palliative. This is largely due to our limited understanding of the fundamental molecular and cellular mechanisms through which BCBM progresses, which represents a critical barrier for the development of efficient therapies for affected breast cancer patients. METHODS: Previous research in BCBM relied on co-culture assays of tumor cells with rodent neural cells or rodent brain slice ex vivo. Given the need to overcome the obstacle for human-relevant host to study cell-cell communication in BCBM, we generated human embryonic stem cell-derived cerebral organoids to co-culture with human breast cancer cell lines. We used MDA-MB-231 and its brain metastatic derivate MDA-MB-231 Br-EGFP, other cell lines of MCF-7, HCC-1806, and SUM159PT. We leveraged this novel 3D co-culture platform to investigate the crosstalk of human breast cancer cells with neural cells in cerebral organoid. RESULTS: We found that MDA-MB-231 and SUM159PT breast cancer cells formed tumor colonies in human cerebral organoids. Moreover, MDA-MB-231 Br-EGFP cells showed increased capacity to invade and expand in human cerebral organoids. CONCLUSIONS: Our co-culture model has demonstrated a remarkable capacity to discern the brain metastatic ability of human breast cancer cells in cerebral organoids. The generation of BCBM-like structures in organoid will facilitate the study of human tumor microenvironment in culture.

Tunneling nanotube-transmitted mechanical signal and its cellular response.

Tunneling nanotubes (TNTs) are elastic tubular structures that physically link cells, facilitating the intercellular transfer of organelles, chemical signals, and electrical signals. Despite TNTs serving as a multifunctional pathway for cell-cell communication, the transmission of mechanical signals through TNTs and the response of TNT-connected cells to these forces remain unexplored. In this study, external mechanical forces were applied to induce TNT bending between rat kidney (NRK) cells using micromanipulation. These forces, transmitted via TNTs, induced reduced curvature of the actin cortex and increased membrane tension at the TNT-connected sites. Additionally, TNT bending results in an elevation of intracellular calcium levels in TNT-connected cells, a response attenuated by gadolinium ions, a non-selective mechanosensitive calcium channel blocker. The degree of TNT deflection positively correlated with decreased actin cortex curvature and increased calcium levels. Furthermore, stretching TNT due to the separation of TNT-connected cells resulted in decreased actin cortex curvature and increased intracellular calcium in TNT-connected cells. The levels of these cellular responses depended on the length changes of TNTs. Moreover, TNT connections influence cell migration by regulating cell rotation, which involves the activation of mechanosensitive calcium channels. In conclusion, our study revealed the transmission of mechanical signals through TNTs and the subsequent responses of TNT-connected cells, highlighting a previously unrecognized communication function of TNTs. This research provides valuable insights into the role of TNTs in long-distance intercellular mechanical signaling.

Robustness and timing of cellular differentiation through population-based symmetry breaking.

During mammalian development and homeostasis, cells often transition from a multilineage primed state to one of several differentiated cell types that are marked by the expression of mutually exclusive genetic markers. These observations have been classically explained by single-cell multistability as the dynamical basis of differentiation, where robust cell-type proportioning relies on pre-existing cell-to-cell differences. We propose a conceptually different dynamical mechanism in which cell types emerge and are maintained collectively by cell-cell communication as a novel inhomogeneous state of the coupled system. Differentiation can be triggered by cell number increase as the population grows in size, through organisation of the initial homogeneous population before the symmetry-breaking bifurcation point. Robust proportioning and reliable recovery of the differentiated cell types following a perturbation is an inherent feature of the inhomogeneous state that is collectively maintained. This dynamical mechanism is valid for systems with steady-state or oscillatory single-cell dynamics. Therefore, our results suggest that timing and subsequent differentiation in robust cell-type proportions can emerge from the cooperative behaviour of growing cell populations during development.

circRAB3IP modulates cell proliferation by reorganizing gene expression and mRNA processing in a paracrine manner.

Circular RNAs are an endogenous long-lived and abundant noncoding species. Despite their prevalence, only a few circRNAs have been dissected mechanistically to date. Here, we cataloged nascent RNA-enriched circRNAs from primary human cells and functionally assigned a role to circRAB3IP in sustaining cellular homeostasis. We combined "omics" and functional experiments to show how circRAB3IP depletion deregulates hundreds of genes, suppresses cell cycle progression, and induces senescence-associated gene expression changes. Conversely, excess circRAB3IP delivered to endothelial cells via extracellular vesicles suffices for accelerating their division. We attribute these effects to an interplay between circRAB3IP and the general splicing factor SF3B1, which can affect transcript variant expression levels of cell cycle-related genes. Together, our findings link the maintenance of cell homeostasis to the presence of a single circRNA.