Biology subjects

Sun, J.

Publications and source records attributed to Sun, J..

At least 163 records · Page 9Linked to original sources

bioRxiv2024

A CRISPR/SpCas9M-reporting system for efficient and rapid genome editing in Caulobacter crescentus

As members of the -proteobacteria group, Caulobacter crescentus and its relatives are known for their asymmetric life cycle and comprehensive applications in gene delivery, agricultural biotechnology, and the production of high-value compounds. However, genetic manipulations of these bacteria are often time-consuming and labor-intensive due to the lack of efficient genome editing tools. Here, we report a practical CRISPR/SpCas9M-reporting system that overcomes the limitations of SpCas9 expression, enabling efficient, markerless, and rapid genome editing in C. crescentus. As a demonstration, we successfully knocked out two genes encoding the scaffold proteins, achieving apparent editing efficiencies up to 80%. Key components, including the Cas protein, Cas inducer, sgRNA, homologous arms, and reporter, were systematically analyzed and optimized to enhance the editing efficiency or decrease the cell lethality. A nearly zero off-target ratio was observed after the curing of the editor plasmid in editing strains. Furthermore, we applied the CRISPR/SpCas9M-reporting system to two C. crescentus relatives, Agrobacterium fabrum and Sinorhizobium meliloti, establishing it as an efficient and reliable editing strategy. We anticipate that this system could be applied to other hard-to-edit organisms, accelerating both basic and applied research in -proteobacteria.

bioengineering↗

bioRxiv2024

The Alzheimers Disease Risk Genes MS4A4A And MS4A6A Cooperate to Negatively Regulate Trem2 and Microglia states

Genetic variations in MS4A4A and MS4A6A are linked to the regulation of cerebrospinal fluid soluble TREM2 (sTREM2) levels and are associated with Alzheimers disease (AD) risk and progression. Using CRISPR knockout and MS4A4A-degrading antibodies in primary human microglia, non-human primates (NHP), and a xenotransplantation model of amyloid pathology, we provide evidence that MS4A4A and MS4A6A are negative regulators of both the transmembrane and soluble TREM2 proteins. They also negatively regulate microglia proliferation, survival, metabolism, lysosomal function, energetics, phagocytosis, and disease-fighting states. Mechanistically, we find that MS4A4A exerts negative regulation by interacting with MS4A6A and protecting it from degradation. MS4A6A in turn forms a complex with and blocks the co-receptor DAP12, which is required for the stability, cell surface localization, and signaling of TREM2 and other receptors. Taken together, the data indicate that MS4A4A and MS4A6A are cooperating, post-transcriptional negative regulators of TREM2 and microglial function, and potential drug targets for AD.

neuroscience↗

bioRxiv2024

Structural insights into cholesterol sensing by the LYCHOS-mTORC1 pathway

The mechanistic target of rapamycin complex 1 (mTORC1) pathway regulates cellular metabolism and growth by coordinating nutrient resources, including cholesterol, and its aberrant activation is linked to various age-related diseases. LYCHOS is a cholesterol sensor on the lysosome and bound to the GATOR1 complex, a GTPase-activating protein for the Rag GTPase, at high cholesterol concentrations, thereby activating the protein kinase mTORC1. However, how LYCHOS senses cholesterol and transduces signal to GATOR1 remain largely unknown. Here we report six cryo-electron microscopy structures of human LYCHOS, depicting five distinct states. These are categorized into a contracted state when complexed with a sufficient amount of the cholesterol analogue cholesteryl hemisuccinate (CHS), and an expanded state when CHS is deficient. The structure forms a homodimer, within each monomer the transmembrane region is divided into a permease-like domain (PLD) and a GPCR-like domain (GLD) with two clearly defined adjacent cholesterol binding sites between them. The PLD shares a conserved Na+/H+ antiporter (NhaA) fold, which much resembles plant auxin transporter PINs. Cholesterol locates between PLD and GLD and cholesterol binding induces a translation of GLD towards PLD and exposes the cytosolic extension of transmembrane 15, which mediates the interaction between LYCHOS and GATOR1. Strikingly, structure-guided mutations of Gly702 in GLD of LYCHOS increase its affinity for cholesterol, leading to sustained mTORC1 activation in cells. This indicates that LYCHOSs moderate affinity for cholesterol is crucial as a cholesterol sensor. Our results not only showed a solute carrier mechanistically coordinates a GPCR domain, elucidating the structural mechanism of cholesterol sensing by the mTORC1 pathway on the lysosome; but also provides a structural basis for developing inhibitors that selectively target to mTORC1 pathway to treat age-related diseases by blocking LYCHOS in its expanded state.

biochemistry↗

bioRxiv2024

Clonal analysis of murine HSC self-renewal and differentiation in native hematopoiesis

Hematopoietic stem cells (HSC) maintain lifelong hematopoiesis. However, in current clonal analyses with unbiased "barcoding" approaches, steady-state hematopoietic clones in young and middle-aged adults rarely have detectable HSCs, which precludes comprehensive interrogation of HSC clonal behaviors. In the current study, we used the previously described Sleeping Beauty transposon model to investigate HSC self-renewal and differentiation at a clonal level following a lifelong chase that significantly enriched HSC-derived clones. From seventeen mice, we detected over seventy thousand clones in native hematopoiesis that reflected the known HSC differentiation biases observed in transplantation. Our data indicated an intimate connection between megakaryocytic-restricted differentiation and HSC self-renewal expansion. By comparing the differentiation patterns of clones derived from transplanted HSCs, we further demonstrated the abilities of HSCs to preserve their cell fates towards self-renewal or multilineage differentiation. Unlike HSCs, clonal expansion in multipotent progenitors was associated with either a differentiation-active or differentiation-indolent state. Moreover, the clonal expansion events in the more differentiated stem and progenitor cells, but not the most primitive HSCs, drove clonal expansion in the megakaryocyte and myeloid cell lineages. Our study provided a comprehensive portrait of native hematopoiesis at a clonal level and revealed the general patterns in which HSCs maintained self-renewal and multi-lineage differentiation.

developmental biology↗

bioRxiv2024

Complex regulation of Cav2.2 N-type Ca2+ channels by Ca2+ and G-proteins

G-protein coupled receptors inhibit Cav2.2 N-type Ca2+ channels by a fast, voltage-dependent pathway mediated by Gi/ G{beta}{gamma} and a slow, voltage-independent pathway mediated by Gq-dependent reductions in phosphatidylinositol 4,5-bisphosphate (PIP2) or increases in arachidonic acid. Studies of these forms of regulation generally employ Ba2+ as the permeant ion, despite that Ca2+ -dependent pathways may impinge upon G-protein modulation. To address this possibility, we compared tonic G-protein inhibition of currents carried by Ba2+ (IBa) and Ca2+ (ICa) in HEK293T cells transfected with Cav2.2. Both IBa and ICa exhibited voltage-dependent facilitation (VDF), consistent with G{beta}{gamma} unbinding from the channel. Compared to that for IBa, VDF of ICawas less sensitive to an inhibitor of G proteins (GDP-{beta}-S) and an inhibitor of G{beta}{gamma} (C-terminal construct of G-protein coupled receptor kinase 2). While insensitive to high intracellular Ca2+ buffering, VDF of ICa that remained in GDP-{beta}-S was blunted by reductions in PIP2. We propose that when G-proteins are inhibited, Ca2+ influx through Cav2.2 promotes a form of VDF that involves PIP2. Our results highlight the complexity whereby Cav2.2 channels integrate G-protein signaling pathways, which may enrich the information encoding potential of chemical synapses in the nervous system.

neuroscience↗

bioRxiv2024

Exploring the Hypothetical Role of Bacteroides Species in Depression Progression: Insights from Metagenomic Analysis

Depression, a psychiatric disorder with significant morbidity and mortality, has a complex etiology. Recent advances in microbiome research have highlighted the potential role of gut microbiota in depression pathogenesis. This study utilized shotgun metagenomic sequencing to compare the fecal microbiota of 28 depression patients and 26 healthy individuals. Significant differences in gut microbiota composition were observed between the two groups. We generated 350 non-redundant high-quality metagenome-assembled Genomes (MAGs) by binning and conducted comparisons between the depression and control groups. Notably, we found that the MAGs enriched in people with depression mostly belonged to Bactendicating a close link between Bacteroides abundance and the development of depression, suggesting that Bacteroides might be a potential culprit for deroides, ipression. In the depression group, we found that the module of nitric oxide synthesis was remarkably enriched, and all Bacteroides MAGs were annotated to nitric oxide synthase, suggesting that increased levels of Bacteroides may contribute to elevated nitric oxide synthesis. Specifically, the mean relative abundance about the genomes of Bacteroides xylanisolvens, Bacteroides caccae, Bacteroides fragilis, Bacteroides stercoris and Bacteroides ovatus showed strong discriminatory power in distinguishing depressed patients from healthy individuals (AUC=0.834). This research shed light on the potential role of gut microbiota in depression and highlights specific metabolic pathways and microbial markers for further investigation. ImprotanceThis research highlighted significant differences in the composition and function of gut microbiota between individuals with depression and healthy individuals, particularly the enrichment of Bacteroides MAGs in depression patients. The upregulation of the nitric oxide synthesis pathway associated with these MAGs belong to Bacteroides in the gut of depression patients had also been observed. The mean relative abundance of a specific set of Bacteroides MAGs had been identified, which could accurately classify individuals with depression from healthy individuals (AUC=0.834). Our results suggest the importance of exploring microbial markers as potential diagnostic and therapeutic targets in managing depression.

genomics↗

bioRxiv2024

Unbiased profiling of multipotency landscapes reveals spatial modulators of clonal fate biases

The proportion of cell types varies systematically across the body, but it remains unclear how individual progenitor cells integrate positional information to establish patterns of cellular composition. In this study we profile the clonal landscape of the embryo, using single-cell lineage tracing of mouse embryos from neurulation until mid-gestation. To analyze the complex clonal patterns derived from highly multipotent progenitors, we developed clone2vec, which uses unsupervised learning to categorize individual clones into lineages based on shared transcriptional context. This revealed a body-wide gradient of clonal fate biases, in which anatomical position and clonal composition are mutually predictive. Comparison of clonal lineages revealed spatial transcription factor programs associated with dynamic cell biasing towards skeletal versus non-skeletal fates. Mosaic combinatorial perturbations targeting the Hedgehog pathway generated clones in which positional identity was mismatched with clonal composition, suggesting a potential signaling influence on somite patterning. We explore the effects of position and heterochrony on fate biases in cranial, trunk, and caudal neural crest clones. Altogether, our work demonstrates an effective practical approach for dissecting mechanisms of lineage specification.

developmental biology↗

bioRxiv2024

Pathway Specific Unbinding Free Energy Profiles of Ritonavir Dissociation From HIV-1 Protease

Investigation of protein-drug recognition is key in understanding drug selectivity and binding affinity. In combination, binding/unbinding free energy landscape and intermolecular interactions can be used to understand the drug binding/unbinding mechanisms. This information is vital for the development of drugs with improved efficacy and explanation of mutation effects. This study investigated the dissociation processes of ritonavir unbinding from HIV protease (HIVp). Analyzing unbinding trajectories modeled by accelerated molecular dynamics (MD) simulations, three distinct pathways, Pathways A, B, and C, were characterized. Using reduced dimensionality strategy with the principal component analysis, we carried out short classical MD runs with explicit water to sample local fluctuation during ritonavir dissociation and applied the milestoning theory to construct unbinding free energy landscape. We found that each pathway showed similar values of binding free energy, albeit Pathway A accounts for over 50 percent of dissociation trajectories. Interesting, residue-residue correlation network analysis showed that in Pathway A, a broad correlation network outside the flap region governs protein motions during ritonavir unbinding which includes residues with reported mutation effects. However, the other two pathways showed limited correlation networks where no reported mutated residues were involved, explaining the favorability of Pathway A. Guided by the free energy profile, we investigated how and why of an energy barrier and minimum and demonstrated that hydrogen bonding governed the movement of the flap regions, directly impacting the calculated energy. Our study provided a new strategy to estimate ligand binding free energy and demonstrated the importance of the transient interactions during ligand-protein dissociation pathways in understanding drug unbinding.

biochemistry↗

bioRxiv2024

Language model generates cis-regulatory elements across prokaryotes

Deep learning had succeeded in designing Cis-regulatory elements (CREs) for certain species, but necessitated training data derived from experiments. Here, we present Promoter-Factory, a protocol that leverages language models (LM) to design CREs for prokaryotes without experimental prior. Millions of sequences were drawn from thousands of prokaryotic genomes to train a suite of language models, named PromoGen2, and achieved the highest zero-shot promoter strength prediction accuracy among tested LMs. Artificial CREs designed with Promoter-Factory achieved a 100% success rate to express gene in Escherichia coli, Bacillus subtilis, and Bacillus licheniformis. Furthermore, most of the promoters designed targeting Jejubacter sp. L23, a halophilic bacterium without available CREs, were active and successfully drove lycopene overproduction. The generation of 2 million putative promoters across 1,757 prokaryotic genera, along with the Promoter-Factory protocol, will significantly expand the sequence space and facilitate the development of an extensive repertoire of prokaryotic CREs.

bioinformatics↗

bioRxiv2024

Reliable prediction of protein-protein binding affinity changes upon mutations with Pythia-PPI

Protein-protein interactions are essential for numerous biological functions, and predicting binding affinity changes caused by mutations is crucial for understanding the impact of genetic variations and advancing protein engineering. Although machine learning-based methods show promise in improving the prediction accuracy, the scarcity of experimental data remains a significant bottleneck. Here, we utilized multi-task learning and self-distillation to overcome the data limitation and improved the accuracy of deep learning-based protein binding affinity prediction. By incorporating a mutation stability prediction task, the model achieved state-of-the-art accuracy on the SKEMPI dataset and was subsequently used to predict binding affinity changes for millions of mutations, generating an expanded dataset for self-distillation. Compared with prevalent methods, Pythia-PPI increased the Pearson correlation between predictions and experimental data from 0.6447 to 0.7850 on the SKEMPI dataset, and from 0.3654 to 0.6051 on the virial-receptor dataset. These findings demonstrated Pythia-PPI to be a valuable tool for analyzing the fitness landscape of protein-protein interactions. We provided a web server at https://pythiappi.wulab.xyz for easy access to Pythia-PPI.

bioinformatics↗

bioRxiv2024

Decipher Fundamental Atomic Interactions to Unify Generative Molecular Docking and Design

Understanding molecular interactions is essential to structural biology and drug discovery. Despite the progress of AI models in revealing and exploiting the interaction mechanisms for various applications, they are predominantly tailored to specific tasks without fully exploiting the underlying transferability across molecular data and tasks. Here, we present PocketXMol, an atom-level generative foundation model to decipher fundamental atomic interactions for general protein-pocket-interacting molecular tasks. It adopts a novel unified generative framework with an innovative task prompt mechanism and an exclusive atom-level representation, making it applicable to diverse tasks covering structure prediction and design of small molecules and peptides, without requiring fine-tuning. PocketXMol was compared to 55 baseline models across 13 typical tasks, achieving state-of-the-art performance in 11 tasks and remaining competitive in the others. We successfully utilized PocketXMol to design novel small molecules that inhibit caspase-9 with efficacy comparable to that of commercial pan-caspase inhibitors. Furthermore, we employed PocketXMol to design PD-L1-binding peptides, demonstrating a success rate substantially higher than random library screening. Three representative peptides underwent further experiments, which validated the cellular specificity and confirmed their potential for molecular probing and therapeutics. PocketXMol presents a powerful and versatile tool with promising prospects for future applications and will have a profound impact on AI-aided drug discovery.

bioinformatics↗

bioRxiv2024

Unveiling the Gut Microbiome Network Fingerprint: A Deep Learning Approach to Predict Immunotherapy Response in Melanoma Patients.

Immune checkpoint inhibitors (ICI) are critical in cancer therapy, harnessing the immune system to fight tumors. The gut microbiome, a diverse ecosystem of trillions of microorganisms, has emerged as a key influencer of ICI efficacy. However, the specific gut bacteria linked to ICI response in melanoma patients remain unclear, with studies showing inconsistent findings across cohorts. Attributing the lack of consensus to multiple layers of non-linear interactions with host factors and within the microbial community, we developed DeepMicroNET, a novel deep neural network (DNN) model-driven network analysis method to identify and characterize the gut bacteria associated with treatment response. Utilizing data from five cohorts of advanced melanoma patients undergoing ICI therapies, we demonstrate how DeepMicroNET identifies gut bacteria consistently predicting immunotherapy responses (response-associated or RA bacteria). Further, DeepMicroNET revealed that these bacteria are associated with key immune pathways, such as antigen processing and presentation, offering novel insights into the molecular mechanisms that could be targeted to improve therapeutic outcomes. Altogether, by identifying gut bacteria robustly associated with immunotherapy response, DeepMicroNET opens the door to a new era of personalized medicine based on the gut microbiome profile.

microbiology↗

bioRxiv2024

Citrate synthase improves sepsis-induced lung injury by reconstructing the mitochondrial tricarboxylic acid cycle of macrophages

BackgroundThe destruction of mitochondrial function during sepsis-induced acute lung injury (sepsis-ALI) can lead to tissue cell damage and organ dysfunction. Citrate synthase (CS) may maintain cellular energy metabolism by enhancing the mitochondrial tricarboxylic acid cycle (TCA cycle) in macrophages. Methods76 healthy donors and 89 sepsis patients were included. The levels of CS were determined using ELISA. We established a cecal ligation and puncture (CLP) model of sepsis to evaluate the effects of CS on lung injury by lung macrophages-specific CS knockdown or CS inhibitors. Isolated mouse lung macrophages were stimulated with LPS to observe the impact of CS overexpression and knockdown on TCA cycle. ResultsIn sepsis patients, CS was expressed at low levels and positively correlates with lung function parameters. In sepsis mice, knockdown CS or inhibiting its expression exacerbated lung injury and oxidative stress. In macrophages, inhibiting CS expression affected TCA cycle and worsened cell apoptosis, while overexpressing CS promoted TCA cycle, alleviating cell apoptosis, enhancing cellular energy production, and reducing oxidative stress levels. The supplementation of citric acid (a downstream metabolite of CS) helped alleviate mitochondrial damage and promotes the TCA cycle. ConclusionsThese results suggest that targeting CS may be a promising therapeutic approach for treating sepsis.

cell biology↗

bioRxiv2024

The first near-complete genome assembly of pig: enabling more accurate genetic research

Pigs are crucial sources of meat and protein, valuable animal models, and potential donors for xenotransplantation. However, the existing reference genome for pigs is incomplete, with thousands of segments and missing centromeres and telomeres, which limits our understanding of the important traits in these genomic regions. To address this issue, we present a near complete genome assembly for the Jinhua pig (JH-T2T), constructed using PacBio HiFi and ONT long reads. This assembly includes all 18 autosomes and the X and Y sex chromosomes, with only six gaps. It features annotations of 46.90% repetitive sequences, 35 telomeres, 17 centromeres, and 23,924 high-confident genes. Compared to the Sscrofa11.1, JH-T2T closes nearly all gaps, extends sequences by 177 Mb, predicts more intact telomeres and centromeres, and gains 799 more genes and loses 114 genes. Moreover, it enhances the mapping rate for both Western and Chinese local pigs, outperforming Sscrofa11.1 as a reference genome. Additionally, this comprehensive genome assembly will facilitate large-scale variant detection and enable the exploration of genes associated with pig domestication, such as GPAM, CYP2C18, LY9, ITLN2, and CHIA. Our findings represent a significant advancement in pig genomics, providing a robust resource that enhances genetic research, breeding programs, and biomedical applications.

genomics↗

bioRxiv2024

Spatial organization of supercoil dynamics during DNA replication

Progression of DNA replication inevitably generates helical tension and resulting super-helical structures, or supercoils, that originate from the double helix of DNA. As DNA polymerases progress, negative supercoils accumulate in the wake of the replication fork, thereby impeding fork progression unless the supercoils are resolved topologically. Using super-resolution microscopy combined with spatial distribution analysis, here we describe that SMC5/6-mediated confinement of negative supercoils lies at the basis of releasing them by topoisomerase Top2A. Along with DNA replication, SMC5/6 progressively associates with chromatin and locally increases the density of supercoil clusters behind the fork, allowing Top2A to efficiently target and release the accumulated supercoils. These processes are essential to complete DNA replication prior to mitosis and therefore to ensure genome stability. Remarkably, we found that HeLa cells over-accumulate poorly confined negative supercoils beyond the processing capacity of cellular SMC5/6, which may exemplify the condition associated with genome instability of cancer cells.

cell biology↗

bioRxiv2024

Addressing domain shift in deep learning: Challenges and insights from plant disease diagnosis and flower recognition

Deep learning models have shown significant potential for plant pest and disease (PPD) diagnosis; however, their real-world effectiveness is often limited by variability between datasets, where models trained on one dataset perform poorly on others collected under different conditions. In this study, I evaluated the cross-dataset generalization of widely used deep learning architectures, including ResNet, EfficientNet, Inception, and MobileNet, across multiple tomato pest and disease datasets. As expected, models trained and tested on the same dataset achieved high performance. However, substantial performance degradation occurred when these models were tested on different datasets, highlighting the challenges posed by dataset variability. This trend was consistent across all evaluated architectures, indicating that changing the model architecture alone is insufficient to address these issues. The findings emphasize the need for more diverse and representative datasets to better capture variability in agricultural data and enhance the practical deployment of deep learning models for PPD diagnosis.

plant biology↗

bioRxiv2024

Latexin facilitates neointimal formation via promoting smooth muscle cell proliferation and macrophage migration

RationaleNeointimal formation is the major cause of cardiovascular diseases such as atherosclerosis and restenosis. Although restenosis rates are significantly reduced by the development of drug-eluting, the stent may not be implanted at all atherosclerotic sites, and long-term dual anti-platelet therapy is needed after stent implantation. Thus, it is essential to elucidate the detailed mechanisms underlying neointimal formation for developing novel therapies. Latexin (LXN), a previously identified pro-inflammatory protein, is highly expressed in vasculature and its expression is regulated by shear stress. Whether it plays a role in vascular remodeling, however, remains unknown. ObjectiveTo determine whether LXN is involved in neointimal formation, and if so, to define the molecular mechanisms involved. Methods and ResultsWe found that the expression of LXN was significantly increased in neointimal hyperplasia, as determined by western blot. Immunofluorescent staining indicated that increased LXN expression was predominantly localized in smooth muscle cells and macrophages. To determine the cell specific roles of LXN in neointimal formation after injury, we generated global, smooth muscle cell (SMC)-specific, endothelial specific-, and myeloid-specific LXN knockout (KO) mice. We found that global, SMC-, and myeloid-specific LXN deficiency markedly prevented neointimal hyperplasia in mice after carotid artery ligation, whereas LXN deficiency in endothelial cells had no effects. Mechanistically, we found that LXN deficiency in SMCs significantly attenuated SMC proliferation and migration, mainly through inhibiting the expression of platelet-derived growth factor (PDGF) receptors. Intriguely, LXN deficiency in macrophages inhibited monocyte chemoattractant protein-1 (MCP-1)-induced macrophage migration through inhibiting ERK phosphorylation. ConclusionsIn summary, we for the first time demonstrated that LXN is essentially involved in SMC proliferation and microphage migration. Specific inhibition of LXN signaling may provide a novel therapeutic strategy for the treatment of cardiovascular diseases, such as restenosis and atherosclerosis. Novelty and SignificanceO_ST_ABSWhat is known?C_ST_ABSO_LILatexin (LXN) is considered to be a novel pro-inflammatory protein and its expression is responsive to laminar shear stress. C_LIO_LIVascular inflammation, SMC proliferation, and macrophage migration are critical events in neointimal hyperplasia. C_LI What new information does this article contribute?O_LILXN is elevated in carotid artery ligation-induced neointimal hyperplasia in mice. C_LIO_LISMC-specific LXN deficiency prevents neointimal hyperplasia through inhibiting SMC proliferation migration via attenuating platelet-derived growth factor receptor expression. C_LIO_LIMyeloid-specific LXN deficiency prevents neointimal hyperplasia through inhibiting monocyte chemoattractant protein-1-induced macrophage migration and extracellular signal-regulated kinase phosphorylation. C_LI Neointimal formation is the major cause of cardiovascular disease such as atherosclerosis and restenosis after stenting or balloon angioplasty. Because of the development of drug-eluting stents, restenosis rates have been significantly reduced; however, it is still essential to explore the detailed mechanisms underlying neointimal hyperplasia. Latexin (LXN) is considered a novel pro-inflammatory protein that is ubiquitously expressed in vascular and immune cells. We found that LXN is elevated in neointimal hyperplasia, and its deficiency in SMCs and macrophages, but not in ECs, markedly prevents neointimal formation after carotid artery ligation in mice. Mechanistically, LXN deficiency in SMCs prevents SMC proliferation and migration via attenuation of platelet-derived growth factor receptor expression. Further, myeloid-specific LXN deficiency inhibits monocyte chemoattractant protein-1-induced macrophage migration via attenuation of extracellular signal-regulated kinase phosphorylation. For the first time, the present study demonstrated that LXN is a crucial mediator implicated in SMC biology and macrophage migration.

physiology↗

bioRxiv2024

Circulatory proteins shape microglia state and boost phagocytosis

Microglia, the brains immune cells, are highly responsive to their local environment. Given that circulatory proteins can enter the brain, we asked whether microglia are responsive to such proteins. Here, we identify a stable population of microglia specialized to take up circulatory proteins in a region-specific manner under physiological conditions; human hematopoietic stem cell-derived microglia replacing endogenous microglia in chimeric mice show similar regional specialization. Plasma-positive microglia are characterized by prominent expression of genes related to innate immunity and antigen presentation and exhibit high metabolic and phagocytic activity. This activity is dependent, in part, on microglial uptake and accumulation of circulatory Apolipoprotein AI (ApoA-I). Our findings thus identify a new model of communication between brain and periphery through specialized microglia.

neuroscience↗