Spatiotemporal NF-κB dynamics encodes the position, amplitude, and duration of local immune inputs

High cell throughput, programmable fixation reveals the RNA and protein co-regulation with spatially resolved NFκB pseudo-signaling

RNA translation to protein is paramount to creating life, yet RNA and protein correlations vary widely across tissues, cells, and species. To investigate these perplexing results, we utilize a time-series fixation method that combines static stimulation and a programmable formaldehyde perfusion to map pseudo-Signaling with Omics signatures (pSigOmics) of single-cell data from hundreds of thousands of cells. Using the widely studied nuclear factor kappa B (NFκB) mammalian signaling pathway in mouse fibroblasts, we discovered a novel asynchronous pseudotime regulation (APR) between RNA and protein levels in the quintessential NFκB p65 protein using single molecule spatial imaging. Prototypical NFκB dynamics are successfully confirmed by the rise and fall of NFκB response as well as A20 negative inhibitor activity by 90 min. The observed p65 translational APR is evident in both statically sampled timepoints and dynamic response gradients from programmable formaldehyde fixation, which successfully creates continuous response measurements. Finally, we implement a graph neural network model capable of predicting APR cell subpopulations from GAPDH RNA spatial expression, which is strongly correlated with p65 RNA signatures. Successful decision tree classifiers on Potential of Heat-diffusion for Affinity-based Trajectory Embedding embeddings of our data, which illustrate partitions of APR cell subpopulations in latent space, further confirm the APR patterns. Together, our data suggest an RNA-protein regulatory framework in which translation adapts to signaling events and illuminates how immune signaling is timed across various cell subpopulations.

TLR9-dependent dendritic cell maturation promotes IL-6-mediated upregulation of cathepsin X

Cysteine cathepsins are lysosomal proteases subject to dynamic regulation within antigen-presenting cells during the immune response and associated diseases. To investigate the regulation of cathepsin X, a carboxy-mono-exopeptidase, during maturation of dendritic cells (DCs), we exposed immortalized mouse DCs to various Toll-like receptor agonists. Using a cathepsin X-selective activity-based probe, sCy5-Nle-SY, we observed a significant increase in cathepsin X activation upon TLR-9 agonism with CpG, and to a lesser extent with Pam3 (TLR1/2), FSL-1 (TLR2/6) and LPS (TLR4). Despite clear maturation of DCs in response to Poly I:C (TLR3), cathepsin X activity was only slightly increased by this agonist, suggesting differential regulation of cathepsin X downstream of TLR activation. We demonstrated that cathepsin X was upregulated at the transcriptional level in response to CpG. This occurred at late time points and was not dampened by NF-κB inhibition. Factors secreted from CpG-treated cells were able to provoke cathepsin X upregulation when applied to naïve cells. Among these factors was IL-6, which on its own was sufficient to induce transcriptional upregulation and activation of cathepsin X. IL-6 is highly secreted by DCs in response to CpG but much less so in response to poly I:C, and inhibition of the IL-6 receptor subunit glycoprotein 130 prevented CpG-mediated cathepsin X upregulation. Collectively, these results demonstrate that cathepsin X is differentially transcribed during DC maturation in response to diverse stimuli, and that secreted IL-6 is critical for its dynamic regulation.

Single-nucleus proteomics identifies regulators of protein transport

The physiological response of a cell to stimulation depends on its proteome configuration. Therefore, the abundance variation of regulatory proteins across unstimulated single cells can be associatively linked with their response to stimulation. Here we developed an approach that leverages this association across individual cells and nuclei to systematically identify potential regulators of biological processes, followed by targeted validation. Specifically, we applied this approach to identify regulators of nucleocytoplasmic protein transport in macrophages stimulated with lipopolysaccharide (LPS). To this end, we quantified the proteomes of 3,412 individual nuclei, sampling the dynamic response to LPS treatment, and linking functional variability to proteomic variability. Minutes after the stimulation, the protein transport in individual nuclei correlated strongly with the abundance of known protein transport regulators, thus revealing the impact of natural protein variability on functional cellular response. We found that simple biophysical constraints, such as the quantity of nuclear pores, partially explain the variability in LPS-induced nucleocytoplasmic transport. Among the many proteins newly identified to be associated with the response, we selected 16 for targeted validation by knockdown. The knockdown phenotypes confirmed the inferences derived from natural protein and functional variation of single nuclei, thus demonstrating the potential of (sub-)single-cell proteomics to infer functional regulation. We expect this approach to generalize to broad applications and enhance the functional interpretability of single-cell omics data.

Low-frequency ERK and Akt activity dynamics are predictive of stochastic cell division events

Understanding the dynamics of intracellular signaling pathways, such as ERK1/2 (ERK) and Akt1/2 (Akt), in the context of cell fate decisions is important for advancing our knowledge of cellular processes and diseases, particularly cancer. While previous studies have established associations between ERK and Akt activities and proliferative cell fate, the heterogeneity of single-cell responses adds complexity to this understanding. This study employed a data-driven approach to address this challenge, developing machine learning models trained on a dataset of growth factor-induced ERK and Akt activity time courses in single cells, to predict cell division events. The most predictive models were developed by applying discrete wavelet transforms (DWTs) to extract low-frequency features from the time courses, followed by using Ensemble Integration, a data integration and predictive modeling framework. The results demonstrated that these models effectively predicted cell division events in MCF10A cells (F-measure=0.524, AUC=0.726). ERK dynamics were found to be more predictive than Akt, but the combination of both measurements further enhanced predictive performance. The ERK model`s performance also generalized to predicting division events in RPE cells, indicating the potential applicability of these models and our data-driven methodology for predicting cell division across different biological contexts. Interpretation of these models suggested that ERK dynamics throughout the cell cycle, rather than immediately after growth factor stimulation, were associated with the likelihood of cell division. Overall, this work contributes insights into the predictive power of intra-cellular signaling dynamics for cell fate decisions, and highlights the potential of machine learning approaches in unraveling complex cellular behaviors.

Multi-organ single-cell transcriptomics of immune cells uncovered organ-specific gene expression and functions

Despite the wealth of publicly available single-cell datasets, our understanding of distinct resident immune cells and their unique features in diverse human organs remains limited. To address this, we compiled a meta-analysis dataset of 114,275 CD45+ immune cells sourced from 14 organs in healthy donors. While the transcriptome of immune cells remains relatively consistent across organs, our analysis has unveiled organ-specific gene expression differences (GTPX3 in kidney, DNTT and ACVR2B in thymus). These alterations are linked to different transcriptional factor activities and pathways including metabolism. TNF-α signaling through the NFkB pathway was found in several organs and immune compartments. The presence of distinct expression profiles for NFkB family genes and their target genes, including cytokines, underscores their pivotal role in cell positioning. Taken together, immune cells serve a dual role: safeguarding the organs and dynamically adjusting to the intricacies of the host organ environment, thereby actively contributing to its functionality and overall homeostasis.

Beyond microtubules: The cellular environment at the endoplasmic reticulum attracts proteins to the nucleus, enabling nuclear transport

All proteins are translated in the cytoplasm, yet many, including transcription factors, play vital roles in the nucleus. While previous research has concentrated on molecular motors for the transport of these proteins to the nucleus, recent observations reveal perinuclear accumulation even in the absence of an energy source, hinting at alternative mechanisms. Here, we propose that structural properties of the cellular environment, specifically the endoplasmic reticulum (ER), can promote molecular transport to the perinucleus without requiring additional energy expenditure. Specifically, physical interaction between proteins and the ER impedes their diffusion and leads to their accumulation near the nucleus. This result explains why larger proteins, more frequently interacting with the ER membrane, tend to accumulate at the perinucleus. Interestingly, such diffusion in a heterogeneous environment follows Chapman's law rather than the popular Fick's law. Our findings suggest a novel protein transport mechanism arising solely from characteristics of the intracellular environment.

NF-κB in biology and targeted therapy: new insights and translational implications

NF-κB signaling has been discovered for nearly 40 years. Initially, NF-κB signaling was identified as a pivotal pathway in mediating inflammatory responses. However, with extensive and in-depth investigations, researchers have discovered that its role can be expanded to a variety of signaling mechanisms, biological processes, human diseases, and treatment options. In this review, we first scrutinize the research process of NF-κB signaling, and summarize the composition, activation, and regulatory mechanism of NF-κB signaling. We investigate the interaction of NF-κB signaling with other important pathways, including PI3K/AKT, MAPK, JAK-STAT, TGF-β, Wnt, Notch, Hedgehog, and TLR signaling. The physiological and pathological states of NF-κB signaling, as well as its intricate involvement in inflammation, immune regulation, and tumor microenvironment, are also explicated. Additionally, we illustrate how NF-κB signaling is involved in a variety of human diseases, including cancers, inflammatory and autoimmune diseases, cardiovascular diseases, metabolic diseases, neurological diseases, and COVID-19. Further, we discuss the therapeutic approaches targeting NF-κB signaling, including IKK inhibitors, monoclonal antibodies, proteasome inhibitors, nuclear translocation inhibitors, DNA binding inhibitors, TKIs, non-coding RNAs, immunotherapy, and CAR-T. Finally, we provide an outlook for research in the field of NF-κB signaling. We hope to present a stereoscopic, comprehensive NF-κB signaling that will inform future research and clinical practice.

Open questions in the NF-κB field

A variety of stress signals leads to activation of the inducible transcription factor NF-κB, one of the master regulators of the innate immune response. Despite a wealth of information available on the NF-κB core components and its control by different activation pathways and negative feedback loops, several levels of complexity hamper our understanding of the system. This has also contributed to the limited success of NF-κB inhibitors in the clinic and explains some of their unexpected effects. Here we consider the molecular and cellular events generating this complexity at all levels and point to a number of unresolved questions in the field. We also discuss potential future experimental and computational strategies to provide a deeper understanding of NF-κB and its coregulatory signaling networks.

Processing stimulus dynamics by the NF-κB network in single cells

Cells at the site of an infection experience numerous biochemical signals that vary in amplitude, space, and time. Despite the diversity of dynamic signals produced by pathogens and sentinel cells, information-processing pathways converge on a limited number of central signaling nodes to ultimately control cellular responses. In particular, the NF-κB pathway responds to dozens of signals from pathogens and self, and plays a vital role in processing proinflammatory inputs. Studies addressing the influence of stimulus dynamics on NF-κB signaling are rare due to technical limitations with live-cell measurements. However, recent advances in microfluidics, automation, and image analysis have enabled investigations that yield high temporal resolution at the single-cell level. Here, we summarize the recent research which measures and models the NF-κB response to pulsatile and fluctuating stimulus concentrations, as well as different combinations and sequences of signaling molecules. Collectively, these studies show that the NF-κB network integrates external inflammatory signals and translates these into downstream transcriptional responses.

Emerging role and therapeutic implications of p53 in intervertebral disc degeneration

Lower back pain (LBP) is a common degenerative musculoskeletal disease that imposes a huge economic burden on both individuals and society. With the aggravation of social aging, the incidence of LBP has increased globally. Intervertebral disc degeneration (IDD) is the primary cause of LBP. Currently, IDD treatment strategies include physiotherapy, medication, and surgery; however, none can address the root cause by ending the degeneration of intervertebral discs (IVDs). However, in recent years, targeted therapy based on specific molecules has brought hope for treating IDD. The tumor suppressor gene p53 produces a transcription factor that regulates cell metabolism and survival. Recently, p53 was shown to play an important role in maintaining IVD microenvironment homeostasis by regulating IVD cell senescence, apoptosis, and metabolism by activating downstream target genes. This study reviews research progress regarding the potential role of p53 in IDD and discusses the challenges of targeting p53 in the treatment of IDD. This review will help to elucidate the pathogenesis of IDD and provide insights for the future development of precision treatments.

Melatonin ameliorates atherosclerosis by suppressing S100a9-mediated vascular inflammation

Atherosclerosis (AS)-associated cardiovascular diseases are predominant causes of morbidity and mortality worldwide. Melatonin, a circadian hormone with anti-inflammatory activity, may be a novel therapeutic intervention for AS. However, the exact mechanism is unclear. This research intended to investigate the mechanism of melatonin in treating AS. Melatonin (20 mg/kg/d) was intraperitoneally administered in a high-fat diet (HFD)-induced AS model using apolipoprotein E-deficient (ApoE-/-) mice for 12 weeks. Immunohistochemical and immunofluorescence analyses, data-independent acquisition (DIA)-based protein profiling, ingenuity pathway analysis (IPA), and western blotting were employed to investigate the therapeutic effects of melatonin in treating HFD-induced AS. An adeno-associated virus (AAV) vector was further used to confirm the antiatherosclerotic mechanism of melatonin. Melatonin treatment markedly attenuated atherosclerotic lesions, induced stable phenotypic sclerotic plaques, inhibited macrophage infiltration, and suppressed the production of proinflammatory cytokines in ApoE-/- mice with HFD-induced AS. Notably, DIA-based quantitative proteomics together with IPA identified S100a9 as a pivotal mediator in the protective effects of melatonin. Moreover, melatonin significantly suppressed HFD-induced S100a9 expression at both the mRNA and protein levels. The overexpression of S100a9 significantly activated the NF-κB signaling pathway and markedly abolished the antagonistic effect of melatonin on HFD-induced vascular inflammation during atherogenesis. Melatonin exerts a significant antiatherogenic effect by inhibiting S100a9/NF-κB signaling pathway-mediated vascular inflammation. Our findings reveal a novel antiatherosclerotic mechanism of melatonin and underlie its potential clinical use in modulating AS with good availability and affordability.

Quantifying dynamic pro-inflammatory gene expression and heterogeneity in single macrophage cells

Macrophages must respond appropriately to pathogens and other pro-inflammatory stimuli in order to perform their roles in fighting infection. One way in which inflammatory stimuli can vary is in their dynamics-that is, the amplitude and duration of stimulus experienced by the cell. In this study, we performed long-term live cell imaging in a microfluidic device to investigate how the pro-inflammatory genes IRF1, CXCL10, and CXCL9 respond to dynamic interferon-gamma (IFNγ) stimulation. We found that IRF1 responds to low concentration or short duration IFNγ stimulation, whereas CXCL10 and CXCL9 require longer or higherconcentration stimulation to be expressed. We also investigated the heterogeneity in the expression of each gene and found that CXCL10 and CXCL9 have substantial cell-to-cell variability. In particular, the expression of CXCL10 appears to be largely stochastic with a subpopulation of nonresponding cells across all the stimulation conditions tested. We developed both deterministic and stochastic models for the expression of each gene. Our modeling analysis revealed that the heterogeneity in CXCL10 can be attributed to a slow chromatin-opening step that is on a similar timescale to that of adaptation of the upstream signal. In this way, CXCL10 expression in individual cells can remain stochastic in response to each pulse of repeated stimulation, which we also validated by experiments. Together, we conclude that pro-inflammatory genes in the same signaling pathway can respond to dynamic IFNγ stimulus with very different response features and that upstream signal adaptation can contribute to shaping heterogeneous gene expression.

Engineering global and local signal generators for probing temporal and spatial cellular signaling dynamics

Cells constantly encounter a wide range of environmental signals and rely on their signaling pathways to initiate reliable responses. Understanding the underlying signaling mechanisms and cellular behaviors requires signal generators capable of providing diverse input signals to deliver to cell systems. Current research efforts are primarily focused on exploring cellular responses to global or local signals, which enable us to understand cellular signaling and behavior in distinct dimensions. This review presents recent advancements in global and local signal generators, highlighting their applications in studying temporal and spatial signaling activity. Global signals can be generated using microfluidic or photochemical approaches. Local signal sources can be created using living or artificial cells in combination with different control methods. We also address the strengths and limitations of each signal generator type, discussing challenges and potential extensions for future research. These approaches are expected to continue to facilitate on-going research to discover novel and intriguing cellular signaling mechanisms.

Signaling is the pathway to macrophage function

Tissue and inflammatory contexts are well appreciated to shape macrophage function to promote health or disease. However, there has been minimal progress towards understanding how these contexts modify signaling-to-transcription networks. Integration of mechanistic modeling and data-driven approaches will be crucial for investigating how cell state impacts macrophage decision-making.

Next-Generation Adjuvants: Applying Engineering Methods to Create and Evaluate Novel Immunological Responses

Adjuvants are a critical component of vaccines. Adjuvants typically target receptors that activate innate immune signaling pathways. Historically, adjuvant development has been laborious and slow, but has begun to accelerate over the past decade. Current adjuvant development consists of screening for an activating molecule, formulating lead molecules with an antigen, and testing this combination in an animal model. There are very few adjuvants approved for use in vaccines, however, as new candidates often fail due to poor clinical efficacy, intolerable side effects, or formulation limitations. Here, we consider new approaches using tools from engineering to improve next-generation adjuvant discovery and development. These approaches will create new immunological outcomes that will be evaluated with novel diagnostic tools. Potential improved immunological outcomes include reduced vaccine reactogenicity, tunable adaptive responses, and enhanced adjuvant delivery. Evaluations of these outcomes can leverage computational approaches to interpret "big data" obtained from experimentation. Applying engineering concepts and solutions will provide alternative perspectives, further accelerating the field of adjuvant discovery.

Overexpression of IκB⍺ modulates NF-κB activation of inflammatory target gene expression

Cells respond to inflammatory stimuli such as cytokines by activation of the nuclear factor-κB (NF-κB) signalling pathway, resulting in oscillatory translocation of the transcription factor p65 between nucleus and cytoplasm in some cell types. We investigate the relationship between p65 and inhibitor-κB⍺ (IκBα) protein levels and dynamic properties of the system, and how this interaction impacts on the expression of key inflammatory genes. Using bacterial artificial chromosomes, we developed new cell models of IκB⍺-eGFP protein overexpression in a pseudo-native genomic context. We find that cells with high levels of the negative regulator IκBα remain responsive to inflammatory stimuli and maintain dynamics for both p65 and IκBα. In contrast, canonical target gene expression is dramatically reduced by overexpression of IκBα, but can be partially rescued by overexpression of p65. Treatment with leptomycin B to promote nuclear accumulation of IκB⍺ also suppresses canonical target gene expression, suggesting a mechanism in which nuclear IκB⍺ accumulation prevents productive p65 interaction with promoter binding sites. This causes reduced target promoter binding and gene transcription, which we validate by chromatin immunoprecipitation and in primary cells. Overall, we show how inflammatory gene transcription is modulated by the expression levels of both IκB⍺ and p65. This results in an anti-inflammatory effect on transcription, demonstrating a broad mechanism to modulate the strength of inflammatory response.

High-throughput co-culture system for analysis of spatiotemporal cell-cell signaling

Study of spatial and temporal aspects of signaling between individual cells is essential in understanding development, the immune response, and host-pathogen interactions. We present an automated high-throughput microfluidic platform that chemically stimulates immune cells to initiate cytokine secretion, and controls the formation of signal gradients that activate neighboring cell populations. Furthermore, our system enables controlling the cell type and density based on distance, and retrieval of cells from different regions for gene expression analysis. Our device performs these tasks in 192 independent chambers to simultaneously test different co-culture conditions. We demonstrate these capabilities by creating various cellular communication scenarios between macrophages and fibroblasts in vitro. We find that spatial distribution of macrophages and heterogeneity in cytokine secretion determine spatiotemporal gene expression responses. Furthermore, we describe how gene expression dynamics depend on a cell's distance from the signaling source. Our device addresses key challenges in the study of cell-to-cell signaling, and provides high-throughput and automated analysis over a wide range of co-culture conditions.

NF-κB dynamics in the language of immune cells

Biological discovery has been driven by advances in throughput and resolution of analysis technologies. They have also created an indelible bias for snapshot-based knowledge. Even though recent methods such as multi-omics single-cell assays have empowered immunological investigations, they still provide snapshots of cellular behaviors and thus, have inherent limitations in reconstructing unsynchronized dynamic events across individual cells. Here, we present a rationale for how NF-κB may convey specificity of contextual information through subtle quantitative features of its signaling dynamics. The next frontier of predictive understanding should involve functional characterization of NF-κB signaling dynamics and their immunological implications. This may help solve the apparent paradox that a ubiquitously activated transcription factor can shape accurate responses to different immune challenges.