Engineering a Model Cell for Rational Tuning of GPCR Signaling.

G protein-coupled receptor (GPCR) signaling is the primary method eukaryotes use to respond to specific cues in their environment. However, the relationship between stimulus and response for each GPCR is difficult to predict due to diversity in natural signal transduction architecture and expression. Using genome engineering in yeast, we constructed an insulated, modular GPCR signal transduction system to study how the response to stimuli can be predictably tuned using synthetic tools. We delineated the contributions of a minimal set of key components via computational and experimental refactoring, identifying simple design principles for rationally tuning the dose response. Using five different GPCRs, we demonstrate how this enables cells and consortia to be engineered to respond to desired concentrations of peptides, metabolites, and hormones relevant to human health. This work enables rational tuning of cell sensing while providing a framework to guide reprogramming of GPCR-based signaling in other systems.

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.

LlamaTags: A Versatile Tool to Image Transcription Factor Dynamics in Live Embryos.

Embryonic cell fates are defined by transcription factors that are rapidly deployed, yet attempts to visualize these factors in vivo often fail because of slow fluorescent protein maturation. Here, we pioneer a protein tag, LlamaTag, which circumvents this maturation limit by binding mature fluorescent proteins, making it possible to visualize transcription factor concentration dynamics in live embryos. Implementing this approach in the fruit fly Drosophila melanogaster, we discovered stochastic bursts in the concentration of transcription factors that are correlated with bursts in transcription. We further used LlamaTags to show that the concentration of protein in a given nucleus heavily depends on transcription of that gene in neighboring nuclei; we speculate that this inter-nuclear signaling is an important mechanism for coordinating gene expression to delineate straight and sharp boundaries of gene expression. Thus, LlamaTags now make it possible to visualize the flow of information along the central dogma in live embryos.

Migrasome biogenesis: when biochemistry meets biophysics on membranes.

Migrasomes, newly identified organelles, play crucial roles in intercellular communication, contributing to organ development and angiogenesis. These vesicles, forming on retraction fibers of migrating cells, showcase a sophisticated architecture. Recent research reveals that migrasome biogenesis is a complicated and highly regulated process. This review summarizes the mechanisms governing migrasome formation, proposing a model in which biogenesis is understood through the lens of membrane microdomain assembly. It underscores the critical interplay between biochemistry and biophysics. The biogenesis unfolds in three distinct stages: nucleation, maturation, and expansion, each characterized by unique morphological, biochemical, and biophysical features. We also explore the broader implications of migrasome research in membrane biology and outline key unanswered questions that represent important directions for future investigation.

Nitrogen signaling factor triggers a respiration-like gene expression program in fission yeast.

Microbes have evolved intricate communication systems that enable individual cells of a population to send and receive signals in response to changes in their immediate environment. In the fission yeast Schizosaccharomyces pombe, the oxylipin nitrogen signaling factor (NSF) is part of such communication system, which functions to regulate the usage of different nitrogen sources. Yet, the pathways and mechanisms by which NSF acts are poorly understood. Here, we show that NSF physically interacts with the mitochondrial sulfide:quinone oxidoreductase Hmt2 and that it prompts a change from a fermentation- to a respiration-like gene expression program without any change in the carbon source. Our results suggest that NSF activity is not restricted to nitrogen metabolism alone and that it could function as a rheostat to prepare a population of S. pombe cells for an imminent shortage of their preferred nutrients.

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.

CPPLS-MLP: a method for constructing cell-cell communication networks and identifying related highly variable genes based on single-cell sequencing and spatial transcriptomics data.

In the growth and development of multicellular organisms, the immune processes of the immune system and the maintenance of the organism's internal environment, cell communication plays a crucial role. It exerts a significant influence on regulating internal cellular states such as gene expression and cell functionality. Currently, the mainstream methods for studying intercellular communication are focused on exploring the ligand-receptor-transcription factor and ligand-receptor-subunit scales. However, there is relatively limited research on the association between intercellular communication and highly variable genes (HVGs). As some HVGs are closely related to cell communication, accurately identifying these HVGs can enhance the accuracy of constructing cell communication networks. The rapid development of single-cell sequencing (scRNA-seq) and spatial transcriptomics technologies provides a data foundation for exploring the relationship between intercellular communication and HVGs. Therefore, we propose CPPLS-MLP, which can identify HVGs closely related to intercellular communication and further analyze the impact of Multiple Input Multiple Output cellular communication on the differential expression of these HVGs. By comparing with the commonly used method CCPLS for constructing intercellular communication networks, we validated the superior performance of our method in identifying cell-type-specific HVGs and effectively analyzing the influence of neighboring cell types on HVG expression regulation. Source codes for the CPPLS_MLP R, python packages and the related scripts are available at 'CPPLS_MLP Github [https://github.com/wuzhenao/CPPLS-MLP]'.

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.

Tipifarnib Reduces Extracellular Vesicles and Protects From Heart Failure.

BACKGROUND: Heart failure (HF) is one of the leading causes of mortality worldwide. Extracellular vesicles, including small extracellular vesicles or exosomes, and their molecular cargo are known to modulate cell-to-cell communication during multiple cardiac diseases. However, the role of systemic extracellular vesicle biogenesis inhibition in HF models is not well documented and remains unclear. METHODS: We investigated the role of circulating exosomes during cardiac dysfunction and remodeling in a mouse transverse aortic constriction (TAC) model of HF. Importantly, we investigate the efficacy of tipifarnib, a recently identified exosome biogenesis inhibitor that targets the critical proteins (Rab27a [Ras associated binding protein 27a], nSMase2 [neutral sphingomyelinase 2], and Alix [ALG-2-interacting protein X]) involved in exosome biogenesis for this mouse model of HF. In this study, 10-week-old male mice underwent TAC surgery were randomly assigned to groups with and without tipifarnib treatment (10 mg/kg 3 times/wk) and monitored for 8 weeks, and a comprehensive assessment was conducted through performed echocardiographic, histological, and biochemical studies. RESULTS: TAC significantly elevated circulating plasma exosomes and markedly increased cardiac left ventricular dysfunction, cardiac hypertrophy, and fibrosis. Furthermore, injection of plasma exosomes from TAC mice induced left ventricular dysfunction and cardiomyocyte hypertrophy in uninjured mice without TAC. On the contrary, treatment of tipifarnib in TAC mice reduced circulating exosomes to baseline and remarkably improved left ventricular functions, hypertrophy, and fibrosis. Tipifarnib treatment also drastically altered the miRNA profile of circulating post-TAC exosomes, including miR 331-5p, which was highly downregulated both in TAC circulating exosomes and in TAC cardiac tissue. Mechanistically, miR 331-5p is crucial for inhibiting the fibroblast-to-myofibroblast transition by targeting HOXC8, a critical regulator of fibrosis. Tipifarnib treatment in TAC mice upregulated the expression of miR 331-5p that acts as a potent repressor for one of the fibrotic mechanisms mediated by HOXC8. CONCLUSIONS: Our study underscores the pathological role of exosomes in HF and fibrosis in response to pressure overload. Tipifarnib-mediated inhibition of exosome biogenesis and cargo sorting may serve as a viable strategy to prevent progressive cardiac remodeling in HF.

A PDLP-NHL3 complex integrates plasmodesmal immune signaling cascades.

The plant immune system relies on the perception of molecules that signal the presence of a microbe threat. This triggers signal transduction that mediates a range of cellular responses via a collection of molecular machinery including receptors, small molecules, and enzymes. One response to pathogen perception is the restriction of cell-to-cell communication by plasmodesmal closure. We previously found that while chitin and flg22 trigger specialized immune signaling cascades in the plasmodesmal plasma membrane, both execute plasmodesmal closure via callose synthesis at the plasmodesmata. Therefore, the signaling pathways ultimately converge at or upstream of callose synthesis. To establish the hierarchy of signaling at plasmodesmata and characterize points of convergence in microbe elicitor-triggered signaling, we profiled the dependence of plasmodesmal responses triggered by different elicitors on a range of plasmodesmal signaling machinery. We identified that, like chitin, flg22 signals via RESPIRATORY BURST OXIDASE HOMOLOGUE D (RBOHD) to induce plasmodesmal closure. Further, we found that PLASMODESMATA-LOCATED PROTEIN 1 (PDLP1), PDLP5, and CALLOSE SYNTHASE 1 (CALS1) are common to microbe- and salicylic acid (SA)-triggered responses, identifying PDLPs as a candidate signaling nexus. To understand how PDLPs relay a signal to CALS1, we screened for PDLP5 interactors and found NON-RACE SPECIFIC DISEASE RESISTANCE/HIN1 HAIRPIN-INDUCED-LIKE protein 3 (NHL3), which is also required for chitin-, flg22- and SA-triggered plasmodesmal responses and PDLP-mediated activation of callose synthesis. We conclude that a PDLP-NHL3 complex acts as an integrating node of plasmodesmal signaling cascades, transmitting multiple immune signals to activate CALS1 and plasmodesmata closure.

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.

Peering into tunneling nanotubes-The path forward.

The identification of Tunneling Nanotubes (TNTs) and TNT-like structures signified a critical turning point in the field of cell-cell communication. With hypothesized roles in development and disease progression, TNTs' ability to transport biological cargo between distant cells has elevated these structures to a unique and privileged position among other mechanisms of intercellular communication. However, the field faces numerous challenges-some of the most pressing issues being the demonstration of TNTs in vivo and understanding how they form and function. Another stumbling block is represented by the vast disparity in structures classified as TNTs. In order to address this ambiguity, we propose a clear nomenclature and provide a comprehensive overview of the existing knowledge concerning TNTs. We also discuss their structure, formation-related pathways, biological function, as well as their proposed role in disease. Furthermore, we pinpoint gaps and dichotomies found across the field and highlight unexplored research avenues. Lastly, we review the methods employed to date and suggest the application of new technologies to better understand these elusive biological structures.

'Neighbourhood watch' model: embryonic epiblast cells assess positional information in relation to their neighbours.

In many developing and regenerating systems, tissue pattern is established through gradients of informative morphogens, but we know little about how cells interpret these. Using experimental manipulation of early chick embryos, including misexpression of an inducer (VG1 or ACTIVIN) and an inhibitor (BMP4), we test two alternative models for their ability to explain how the site of primitive streak formation is positioned relative to the rest of the embryo. In one model, cells read morphogen concentrations cell-autonomously. In the other, cells sense changes in morphogen status relative to their neighbourhood. We find that only the latter model can account for the experimental results, including some counter-intuitive predictions. This mechanism (which we name the 'neighbourhood watch' model) illuminates the classic 'French Flag Problem' and how positional information is interpreted by a sheet of cells in a large developing system.

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.