Integrated proteomic and transcriptomic landscape of macrophages in mouse tissues

ZNF143 is a transcriptional regulator of nuclear-encoded mitochondrial genes that acts independently of looping and CTCF

Gene expression is orchestrated by transcription factors, which function within the context of a three-dimensional genome. Zinc-finger protein 143 (ZNF143/ZFP143) is a transcription factor that has been implicated in both gene activation and chromatin looping. To study the direct consequences of ZNF143/ZFP143 loss, we generated a ZNF143/ZFP143 depletion system in mouse embryonic stem cells. Our results show that ZNF143/ZFP143 degradation has no effect on chromatin looping. Systematic analysis of ZNF143/ZFP143 occupancy data revealed that a commonly used antibody cross-reacts with CTCF, leading to its incorrect association with chromatin loops. Nevertheless, ZNF143/ZFP143 specifically activates nuclear-encoded mitochondrial genes, and its loss leads to severe mitochondrial dysfunction. Using an in vitro embryo model, we find that ZNF143/ZFP143 is an essential regulator of organismal development. Our results establish ZNF143/ZFP143 as a conserved transcriptional regulator of cell proliferation and differentiation by safeguarding mitochondrial activity.

Single-cell analysis identified key macrophage subpopulations associated with atherosclerosis

Background

Atherosclerosis is a lipid-driven inflammatory disease characterized by plaque formation in major arteries. These plaques contain lipid-rich macrophages that accumulate through monocyte recruitment, local macrophage differentiation, and proliferation.

Objective

We identify the macrophage subsets that are closely related to atherosclerosis and reveal the key pathways in the progression of atherosclerotic disease.

Materials and methods

In this study, we characterize the single-cell landscape of atherosclerosis, identifying macrophage subsets closely related to the disease and revealing key pathways in its progression. Using analytical methods like CytoTRACE, Monocle2, Slingshot, and CellChat, we study macrophage differentiation and infer cell trajectory.

Results

The 8,417 macrophages were divided into six subtypes, macrophages: C0 C1QC+ macrophages, C1 SPP1+ macrophages, C2 FCN1+ macrophages, C3 IGKC+ macrophages, C4 FCER1A+ macrophages, C5CALD1+ macrophages. The results of gene set enrichment analysis, Monocle2, and Slingshot suggest that C2 FCN1+ macrophages may play an important role in the progression of atherosclerosis. C2 FCN1+ macrophages interact with endothelial cells via CCL, CXCL, APP, and other pathways to regulate the progression of atherosclerosis.

Conclusion

We identify a key macrophage subgroup (C2 FCN1+ macrophages) associated with atherosclerosis, which interacts with endothelial cells via CCL, CXCL, APP, and other pathways to regulate disease progression.

Umbilical cord-derived mesenchymal stem cells preferentially modulate macrophages to alleviate pulmonary fibrosis

BACKGROUND

Idiopathic Pulmonary Fibrosis (IPF) is a type of interstitial lung disease characterized by chronic inflammation due to persistent lung damage. Mesenchymal stem cells (MSCs), including those derived from the umbilical cord (UCMSCs) and placenta (PLMSCs), have been utilized in clinical trials for IPF treatment. However, the varying therapeutic effectiveness between these two MSC types remains unclear.

METHODS

In this study, we examined the therapeutic differences between UCMSCs and PLMSCs in treating lung damage using a bleomycin (BLM)-induced pulmonary injury mouse model.

RESULTS

We showed that UCMSCs had a superior therapeutic impact on lung damage compared to PLMSCs. Upon cytokine stimulation, UCMSCs expressed higher levels of inflammation-related genes and more effectively directed macrophage polarization towards the M2 phenotype than PLMSCs, both in vitro and in vivo. Furthermore, UCMSCs showed a preference for expressing CC motif ligation 2 (CCL2) and C-X-C motif chemokine ligand 1 (CXCL1) compared to PLMSCs. The expression of secreted phosphoprotein 1 (SPP1), triggering receptor expressed on myeloid cells 2 (Trem2), and CCAAT enhancer binding protein beta (Cebpb) in macrophages from mice with the disease treated with UCMSCs was significantly reduced compared to those treated with PLMSCs.

CONCLUSIONS

Therefore, UCMSCs demonstrated superior anti-fibrotic abilities in treating lung damage, potentially through inducing a more robust M2 polarization of macrophages than PLMSCs.

A pan-family screen of nuclear receptors in immunocytes reveals ligand-dependent inflammasome control

Ligand-dependent transcription factors of the nuclear receptor (NR) family regulate diverse aspects of metazoan biology, enabling communications between distant organs via small lipophilic molecules. Here, we examined the impact of each of 35 NRs on differentiation and homeostatic maintenance of all major immunological cell types in vivo through a "Rainbow-CRISPR" screen. Receptors for retinoic acid exerted the most frequent cell-specific roles. NR requirements varied for resident macrophages of different tissues. Deletion of either Rxra or Rarg reduced frequencies of GATA6+ large peritoneal macrophages (LPMs). Retinoid X receptor alpha (RXRα) functioned conventionally by orchestrating LPM differentiation through chromatin and transcriptional regulation, whereas retinoic acid receptor gamma (RARγ) controlled LPM survival by regulating pyroptosis via association with the inflammasome adaptor ASC. RARγ antagonists activated caspases, and RARγ agonists inhibited cell death induced by several inflammasome activators. Our findings provide a broad view of NR function in the immune system and reveal a noncanonical role for a retinoid receptor in modulating inflammasome pathways.

Application of Macrophage Subtype Analysis in Acute Lung Injury/Acute Respiratory Distress Syndrome

Acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) is a common critical illness. Supportive therapy is still the main strategy for ALI/ARDS. Macrophages are the predominant immune cells in the lungs and play a pivotal role in maintaining homeostasis, regulating metabolism, and facilitating tissue repair. During ALI/ARDS, these versatile cells undergo polarization into distinct subtypes with significant variations in transcriptional profiles, developmental trajectory, phenotype, and functionality. This review discusses developments in the analysis of alveolar macrophage subtypes in the study of ALI/ARDS, and the potential value of targeting new macrophage subtypes in the diagnosis, prognostic evaluation, and treatment of ALI/ARDS.

Linking signal input, cell state, and spatial context to inflammatory responses

Signal integration is central to a causal understanding of appropriately scaled inflammatory responses. Here, we discuss recent progress in our understanding of the stimulus-response linkages downstream of pro-inflammatory inputs, with special attention to (1) the impact of cell state on the specificity of evoked gene expression and (2) the critical role of the spatial context of stimulus exposure. Advances in these directions are emerging from new tools for inferring cell-cell interactions and the activities of cytokines and transcription factors in complex microenvironments, enabling analysis of signal integration in tissue settings. Building on data-driven elucidation of factors driving inflammatory outcomes, mechanistic modeling can then contribute to a quantitative understanding of regulatory events that balance protective versus pathological inflammation.

Proteomic profiling of gliomas unveils immune and metabolism-driven subtypes with implications for anti-nucleotide metabolism therapy

Gliomas exhibit high heterogeneity and poor prognosis. Despite substantial progress has been made at the genomic and transcriptomic levels, comprehensive proteomic characterization and its implications remain largely unexplored. In this study, we perform proteomic profiling of gliomas using 343 formalin-fixed and paraffin-embedded tumor samples and 53 normal-appearing brain samples from 188 patients, integrating these data with genomic panel information and clinical outcomes. The proteomic analysis uncovers two distinct subgroups: Subgroup 1, the metabolic neural subgroup, enriched in metabolic enzymes and neurotransmitter receptor proteins, and Subgroup 2, the immune subgroup, marked by upregulation of immune and inflammatory proteins. These proteomic subgroups show significant differences in prognosis, tumorigenesis, microenvironment dysregulation, and potential therapeutics, highlighting the critical roles of metabolic and immune processes in glioma biology and patient outcomes. Through a detailed investigation of metabolic pathways guided by our proteomic findings, dihydropyrimidine dehydrogenase (DPYD) and thymidine phosphorylase (TYMP) emerge as potential prognostic biomarkers linked to the reprogramming of nucleotide metabolism. Functional validation in patient-derived glioma stem cells and animal models highlights nucleotide metabolism as a promising therapy target for gliomas. This integrated multi-omics analysis introduces a proteomic classification for gliomas and identifies DPYD and TYMP as key metabolic biomarkers, offering insights into glioma pathogenesis and potential treatment strategies.

Integrative analysis of transcriptomic and immunoproteomic data reveals stress response mechanisms in Listeria monocytogenes

Listeria monocytogenes is a significant concern in the food industry due to its association with outbreaks of listeriosis, particularly affecting vulnerable populations. High-throughput technologies such as RNA sequencing (RNA-seq) and proteomics offer valuable insights into the molecular responses of L. monocytogenes to stress environments. In this study, a combined transcriptomic and immunoproteomic approach was applied to explore the stress response mechanisms of the L. monocytogenes strain ST7, which was responsible for an outbreak in central Italy. The bacterium was exposed to both optimal conditions and a stress environment representative of pork product matrices (pH 5.5; 7 % NaCl) and thermal abuse prior to consumption (12 °C).Transcriptomic analysis revealed variations in gene expression related to pathogenesis, stress responses, and virulence factors under different environmental conditions. Transcriptomic analysis of Listeria involves studying the complete set of RNA transcripts produced by the bacterium under various conditions or during different stages of its lifecycle. It can provide insights into its pathogenicity and virulence mechanisms. Immunoproteomic analysis identified proteins involved in stress response pathways, including oxidoreductases and DNA repair enzymes, uniquely expressed under stress conditions. Furthermore, the study highlighted proteins linked to antibiotic resistance and cell wall biosynthesis. By delineating specific proteins crucial in the stress response pathways, these findings not only deepen our comprehension of L. monocytogenes biology but also pave the way for designing more targeted mitigation strategies to safeguard food safety and public health effectively.

Role of Peptidyl Arginine Deiminase 4-Dependent Macrophage Extracellular Trap Formation in Type 1 Diabetes Pathogenesis

Excessive formation of macrophage extracellular trap (MET) has been implicated in several autoimmune disease pathogeneses; however, its impact on type 1 diabetes (T1D) and related mechanisms remains enigmatic. We demonstrated the pivotal role of peptidyl arginine deiminase 4 (PAD4) in driving profuse MET formation and macrophage M1 polarization in intestinal inflammation in NOD mice. Genetic knockout of PAD4 or adoptive transfer of METs altered the proportion of proinflammatory T cells in the intestine, subsequently influencing their migration to the pancreas. Combining RNA sequencing and CUT&Tag analysis, we found activated PAD4 transcriptionally regulated CXCL10 expression. This study comprehensively investigated how excessive PAD4-mediated MET formation in the colon increases the aggravation of intestinal inflammation and proinflammatory T-cell migration and finally is involved in T1D progression, suggesting that inhibition of MET formation may be a potential therapeutic target in T1D.

ARTICLE HIGHLIGHTS

Tissue-Resident Macrophages in Cancer: Friend or Foe?

INTRODUCTION

Macrophages are essential in maintaining homeostasis, combating infections, and influencing the process of various diseases, including cancer. Macrophages originate from diverse lineages: Notably, tissue-resident macrophages (TRMs) differ from hematopoietic stem cells and circulating monocyte-derived macrophages based on genetics, development, and function. Therefore, understanding the recruited and TRM populations is crucial for investigating disease processes.

METHODS

By searching literature databses, we summarized recent relevant studies. Research has shown that tumor-associated macrophages (TAMs) of distinct origins accumulate in tumor microenvironment (TME), with TRM-derived TAMs closely resembling gene signatures of normal TRMs.

RESULTS

Recent studies have revealed that TRMs play a crucial role in cancer progression. However, organ-specific effects complicate TRM investigations. Nonetheless, the precise involvement of TRMs in tumors is unclear. This review explores the multifaceted roles of TRMs in cancer, presenting insights into their origins, proliferation, the latest research methodologies, their impact across various tumor sites, their potential and strategies as therapeutic targets, interactions with other cells within the TME, and the internal heterogeneity of TRMs.

CONCLUSIONS

We believe that a comprehensive understanding of the multifaceted roles of TRMs will pave the way for targeted TRM therapies in the treatment of cancer.

Inhibition of SIRT1 relieves hepatocarcinogenesis via alleviating autophagy and inflammation

Imbalanced Sirtuin 1 (SIRT1) levels may lead to liver diseases through abnormal regulation of autophagy, but the roles of SIRT1-regulated autophagy in hepatocellular carcinoma are still controversial. In this study, we found that SIRT1 mRNA and protein levels were upregulated in hepatocellular carcinoma, and high SIRT1 expression hinted an advanced stage and a poor prognosis. The differentially expressed proteins were significantly elevated in autophagy, cellular response to stress, and immune signaling pathways. In a thioacetamide-induced hepatocellular carcinoma mouse model, we found that SIRT1 expression was highly increased with increased autophagy and excessive macrophage inflammatory response. Next, we established a Hepa 1-6 cells and macrophage co-culture system in vitro to model the alteration of tumor microenvironment, and found that the medium from CCl4-treated or SIRT1-overexpressing Hepa 1-6 cells triggered the polarization of macrophage M1, and the culture medium derived from M1 macrophage promoted Hepa 1-6 cells growth and intracellular oxidative stress. The progression of liver fibrosis in the CCl4-induced liver fibrosis mouse model showed that inhibition of SIRT1 alleviated inflammatory response and ameliorated liver fibrosis. These findings suggest that SIRT1-regulated autophagy and inflammation are oncogenic in hepatocarcinogenesis.

Real time changes in the expression of eicosanoid synthesizing enzymes during inflammation

Immune responses during inflammation involve complex, well-coordinated lipid signaling pathways. Eicosanoids are a class of lipid signaling molecules derived from polyunsaturated fatty acids such as arachidonic acid and constitute a major network that controls inflammation and its subsequent resolution. Arachidonic acid is metabolized by enzymes in three different pathways to form a variety of lipid metabolites that can be either pro- or anti-inflammatory. Therefore, an understanding of the time-dependent gene expression, lipid metabolite profiles and cytokine profiles during the initial inflammatory response is necessary, as it will allow for the design of time-dependent therapeutics. Herein, we investigate the multi-level regulation of this process. After stimulating RAW 264.7 cells, a mouse-derived macrophage cell line commonly used to examine inflammatory responses, we examine the gene expression of 44 relevant lipid metabolizing enzymes from the different eicosanoid synthesizing classes. We also measure the formation of lipid metabolites and production of cytokines at selected time points. Results reveal a dynamic relationship between the time-course of inflammation dependent gene expression of the three eicosanoid synthesizing enzymes.

Integrative Analysis of Multi-Omics Data to Identify Deregulated Molecular Pathways and Druggable Targets in Chronic Lymphocytic Leukemia

Chronic Lymphocytic Leukemia (CLL) is the most common B-cell malignancy in the Western world, characterized by frequent relapses despite temporary remissions. Our study integrated publicly available proteomic, transcriptomic, and patient survival datasets to identify key differences between healthy and CLL samples. We exposed approximately 1000 proteins that differentiate healthy from cancerous cells, with 608 upregulated and 415 downregulated in CLL cases. Notable upregulated proteins include YEATS2 (an epigenetic regulator), PIGR (Polymeric immunoglobulin receptor), and SNRPA (a splicing factor), which may serve as prognostic biomarkers for this disease. Key pathways implicated in CLL progression involve RNA processing, stress resistance, and immune response deficits. Furthermore, we identified three existing drugs-Bosutinib, Vorinostat, and Panobinostat-for potential further investigation in drug repurposing in CLL. We also found limited correlation between transcriptomic and proteomic data, emphasizing the importance of proteomics in understanding gene expression regulation mechanisms. This generally known disparity highlights once again that mRNA levels do not accurately predict protein abundance due to many regulatory factors, such as protein degradation, post-transcriptional modifications, and differing rates of translation. These results demonstrate the value of integrating omics data to uncover deregulated proteins and pathways in cancer and suggest new therapeutic avenues for CLL.

Integration tools for scRNA-seq data and spatial transcriptomics sequencing data

Numerous methods have been developed to integrate spatial transcriptomics sequencing data with single-cell RNA sequencing (scRNA-seq) data. Continuous development and improvement of these methods offer multiple options for integrating and analyzing scRNA-seq and spatial transcriptomics data based on diverse research inquiries. However, each method has its own advantages, limitations and scope of application. Researchers need to select the most suitable method for their research purposes based on the actual situation. This review article presents a compilation of 19 integration methods sourced from a wide range of available approaches, serving as a comprehensive reference for researchers to select the suitable integration method for their specific research inquiries. By understanding the principles of these methods, we can identify their similarities and differences, comprehend their applicability and potential complementarity, and lay the foundation for future method development and understanding. This review article presents 19 methods that aim to integrate scRNA-seq data and spatial transcriptomics data. The methods are classified into two main groups and described accordingly. The article also emphasizes the incorporation of High Variance Genes in annotating various technologies, aiming to obtain biologically relevant information aligned with the intended purpose.

From transcriptomics to digital twins of organ function

Cell level functions underlie tissue and organ physiology. Gene expression patterns offer extensive views of the pathways and processes within and between cells. Single cell transcriptomics provides detailed information on gene expression within cells, cell types, subtypes and their relative proportions in organs. Functional pathways can be scalably connected to physiological functions at the cell and organ levels. Integrating experimentally obtained gene expression patterns with prior knowledge of pathway interactions enables identification of networks underlying whole cell functions such as growth, contractility, and secretion. These pathways can be computationally modeled using differential equations to simulate cell and organ physiological dynamics regulated by gene expression changes. Such computational systems can be thought of as parts of digital twins of organs. Digital twins, at the core, need computational models that represent in detail and simulate how dynamics of pathways and networks give rise to whole cell level physiological functions. Integration of transcriptomic responses and numerical simulations could simulate and predict whole cell functional outputs from transcriptomic data. We developed a computational pipeline that integrates gene expression timelines and systems of coupled differential equations to generate cell-type selective dynamical models. We tested our integrative algorithm on the eicosanoid biosynthesis network in macrophages. Converting transcriptomic changes to a dynamical model allowed us to predict dynamics of prostaglandin and thromboxane synthesis and secretion by macrophages that matched published lipidomics data obtained in the same experiments. Integration of cell-level system biology simulations with genomic and clinical data using a knowledge graph framework will allow us to create explicit predictive models that mechanistically link genomic determinants to organ function. Such integration requires a multi-domain ontological framework to connect genomic determinants to gene expression and cell pathways and functions to organ level phenotypes in healthy and diseased states. These integrated scalable models of tissues and organs as accurate digital twins predict health and disease states for precision medicine.

Imidacloprid-induced lung injury in mice: Activation of the PI3K/AKT/NF-κB signaling pathway via TLR4 receptor engagement

Significant impairment of pulmonary function has been demonstrated through long-term exposure to neonicotinoid insecticides, such as imidacloprid (IMI). However, the underlying mechanisms of lung injury induced by IMI remain unclear. In this study, a mouse model of IMI-induced pulmonary injury was established, and the toxicity and lung damage were assessed through mouse body weight, organ index, hematological parameters, and histopathological analysis of lung tissues. Furthermore, metabolomics and transcriptomics techniques were employed to explore the mechanistic aspects. Results from the toxicity assessments indicated that mouse body weight was significantly reduced by IMI, organ index was disturbed, and hematological parameters were disrupted, resulting in pulmonary injury. The mechanistic experimental results indicate that the differences in metabolites and gene expression in mouse lungs could be altered by IMI. Validation of the results through combined analysis of metabolomics and transcriptomics revealed that the mechanism by which IMI induces lung injury in mice might be associated with the activation of the TLR4 receptor, thereby activating the PI3K/AKT/NF-κB signaling pathway to induce inflammation in mouse lungs. This study provided valuable insights into the mechanisms underlying IMI-induced pulmonary damage, potentially contributing to the development of safer pest control strategies. The knowledge gained served as a robust scientific foundation for the prevention and treatment of IMI-related pulmonary injuries.

Proteomics Analysis of Polyphyllin D-Treated Triple-Negative Breast Cancer Cells Reveal the Anticancer Mechanisms of Polyphyllin D

Polyphyllin D (PD), one of the important steroid saponins in traditional medicinal herb Paris polyphylla, has been demonstrated to have anticancer activity both in vitro and in vivo. However, the mechanisms through which PD exerts its anticancer effects in triple-negative breast cancer (TNBC) remain unclear. Our study was presented to evaluate the anticancer effect and the potential mechanisms of PD in two TNBC cell lines, BT-549 and MDA-MB-231. Through comprehensively comparing the liquid chromatography-tandem mass spectrometry (LC-MS/MS) data of PD-treated and untreated BT-549 and MDA-MB-231 cells, we found that PD could induce apoptosis of TNBC cells by activating oxidative phosphorylation pathway in BT-549 cells, as well as inhibiting spliceosome function alteration in MDA-MB-231 cells. These results suggested that the mechanisms underlying the pro-apoptotic effect of PD on TNBC may be cell type-specificity-dependent. Moreover, we found that nodal modulator 2/3 (NOMO2/3) were downregulated both in PD-treated BT-549 and MDA-MB-231 cells, suggesting that NOMO2/3 may be the potential target of PD. Verification experiments revealed that PD deceased NOMO2/3 expression at protein level, rather than mRNA level. Whether NOMO2/3 are the upstream modulators of oxidative phosphorylation pathway and spliceosome needs further validation. In conclusion, a comprehensive proteomics study was performed on PD-treated or untreated TNBC cells, revealing the anticancer mechanisms of PD.

Brucella Manipulates Host Cell Ferroptosis to Facilitate Its Intracellular Replication and Egress in RAW264.7 Macrophages

Brucella virulence relies on its successful intracellular life cycle. Modulating host cell death is a strategy for Brucella to survive and replicate intracellularly. Ferroptosis is a novel regulated cell death characterized by iron-triggered excessive lipid peroxidation, which has been proven to be associated with pathogenic bacteria infection. Thus, we attempted to explore if smooth-type Brucella infection triggers host cell ferroptosis and what role it plays in Brucella infection. We assessed the effects of Brucella infection on the lactate dehydrogenase release and lipid peroxidation levels of RAW264.7 macrophages; subsequently, we determined the effect of Brucella infection on the expressions of ferroptosis defense pathways. Furthermore, we determined the role of host cell ferroptosis in the intracellular replication and egress of Brucella. The results demonstrated that Brucella M5 could induce ferroptosis of macrophages by inhibiting the GPX4-GSH axis at the late stage of infection but mitigated ferroptosis by up-regulating the GCH1-BH4 axis at the early infection stage. Moreover, elevating host cell ferroptosis decreased Brucella intracellular survival and suppressing host cell ferroptosis increased Brucella intracellular replication and egress. Collectively, Brucella may manipulate host cell ferroptosis to facilitate its intracellular replication and egress, extending our knowledge about the underlying mechanism of how Brucella completes its intracellular life cycle.

Efferocytosis-Inspired Biomimetic Nanoplatform for Targeted Acute Lung Injury Therapy

Acute lung injury (ALI) is a serious inflammatory disease that causes impairment of pulmonary function. Phenotypic modulation of macrophage in the lung using fibroblast growth factor 21 (FGF21) may be a potential strategy to alleviate lung inflammation. Consequently, achieving specific delivery of FGF21 to the inflamed lung and subsequent efficient FGF21 internalization by macrophages within the lung becomes critical for effective ALI treatment. Here, an apoptotic cell membrane-coated zirconium-based metal-organic framework UiO-66 is reported for precise pulmonary delivery of FGF21 (ACM@U-FGF21) whose design is inspired by the process of efferocytosis. ACM@U-FGF21 with apoptotic signals is recognized and internalized by phagocytes in the blood and macrophages in the lung, and then the intracellular ACM@U-FGF21 can inhibit the excessive secretion of pro-inflammatory cytokines by these cells to relieve the inflammation. Utilizing the homologous targeting properties inherited from the source cells and the spontaneous recruitment of immune cells to inflammatory sites, ACM@U-FGF21 can accumulate preferentially in the lung after injection. The results prove that ACM@U-FGF21 effectively reduces inflammatory damage to the lung by modulating lung macrophage polarization and suppressing the excessive secretion of pro-inflammatory cytokines by activated immune cells. This study demonstrates the usefulness of efferocytosis-inspired ACM@U-FGF21 in the treatment of ALI.

Radical-Generating Activity, Phagocytosis, and Mechanical Properties of Four Phenotypes of Human Macrophages

Macrophages are the major players and orchestrators of inflammatory response. Expressed proteins and secreted cytokines have been well studied for two polar macrophage phenotypes-pro-inflammatory M1 and anti-inflammatory regenerative M2, but little is known about how the polarization modulates macrophage functions. In this study, we used biochemical and biophysical methods to compare the functional activity and mechanical properties of activated human macrophages differentiated from monocyte with GM-CSF (M0_GM) and M-CSF (M0_M) and polarized into M1 and M2 phenotypes, respectively. Unlike GM-CSF, which generates dormant cells with low activity, M-CSF confers functional activity on macrophages. M0_M and M2 macrophages had very similar functional characteristics-high reactive oxygen species (ROS) production level, and higher phagocytosis and survival compared to M1, while M1 macrophages showed the highest radical-generating activity but the lowest phagocytosis and survival among all phenotypes. All phenotypes decreased their height upon activation, but only M1 and M2 cells increased in stiffness, which can indicate a decrease in the migration ability of these cells and changes in their interactions with other cells. Our results demonstrated that while mechanical properties differ between M0 and polarized cells, all four phenotypes of monocyte-derived macrophages differ in their functional activities, namely in cytokine secretion, ROS production, and phagocytosis. Within the broad continuum of human macrophages obtained in experimental models and existing in vivo, there is a diversity of phenotypes with varying combinations of both markers and functional activities.

Surface-Charge-Driven Ferroptosis and Mitochondrial Dysfunction Is Involved in Toxicity Diversity in the Marine Bivalve Exposed to Nanoplastics

Nanoplastics (NPs) pervade daily life, posing serious threats to marine ecosystems. Despite the crucial role that surface charge plays in NP effects, there is a substantial gap in our understanding of how surface charge influences NP toxicity. Herein, by exposing Ruditapes philippinarum (R. philippinarum) to both positively charged NPs (p-NPs) and negatively charged NPs (n-NPs) at environmentally relevant particle number levels for a duration of 35 days, we unequivocally demonstrate that both types of NPs had discernible impacts on the clams depending on their surface charge. Through transcriptomic and proteomic analyses, we unveiled the primary mechanisms behind p-NP toxicity, which stem from induced mitochondrial dysfunction and ferroptosis. In contrast, n-NPs predominantly stimulated innate immune responses, influencing salivary secretion and modulating the complement and coagulation cascades. Furthermore, in vitro tests on clam immune cells confirmed that internalized p-NPs triggered alterations in mitochondrial morphology, a decrease in membrane potential, and the initiation of ferroptosis. Conversely, n-NPs, to a certain extent, moderated the expression of genes related to immune responses, thus mitigating their adverse effects. Taken together, these findings indicate that the differential surface-charge-driven ferroptosis and mitochondrial dysfunction in clams play a critical role in the toxicity profile of NPs, providing an insightful reference for assessing the ecological toxicity associated with NPs.

Microglial Transcriptional Signatures in the Central Nervous System: Toward A Future of Unraveling Their Function in Health and Disease

Microglia, the resident immune cells of the central nervous system (CNS), are primarily derived from the embryonic yolk sac and make their way to the CNS during early development. They play key physiological and immunological roles across the life span, throughout health, injury, and disease. Recent transcriptomic studies have identified gene transcript signatures expressed by microglia that may provide the foundation for unprecedented insights into their functions. Microglial gene expression signatures can help distinguish them from macrophage cell types to a reasonable degree of certainty, depending on the context. Microglial expression patterns further suggest a heterogeneous population comprised of many states that vary according to the spatiotemporal context. Microglial diversity is most pronounced during development, when extensive CNS remodeling takes place, and following disease or injury. A next step of importance for the field will be to identify the functional roles performed by these various microglial states, with the perspective of targeting them therapeutically.

Metabolic adaption of mucosal macrophages: Is metabolism a driver of persistence across tissues?

Macrophages play essential roles in tissue homeostasis, defense, and repair. Their functions are highly tissue-specific, and when damage and inflammation stimulate repopulation by circulating monocytes, the incoming monocytes rapidly acquire the same, tissue-specific functions as the previous, resident macrophages. Several environmental factors are thought to guide the functional differentiation of recruited monocytes, including metabolic pressures imposed by the fuel sources available in each tissue. Here we discuss whether such a model of metabolic determinism can be applied to macrophage differentiation across barrier sites, from the lung to the skin. We suggest an alternative model, in which metabolic phenotype is a consequence of macrophage longevity rather than an early driver of tissue-specific adaption.

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.