Biology subjects

Liu, Y.

Publications and source records attributed to Liu, Y..

At least 1,315 records · Page 73Linked to original sources

bioRxiv2024

Whole-Genome Analysis of Stress Resistance-Related Genes in Listeria monocytogenes

Listeria monocytogenes is a crucial foodborne pathogen with significant public health implications. This study analyzed whole-genome sequences (WGS) of L. monocytogenes strains from public databases, examining associations between resistance genes, lineage, strain type, isolation source, and geography. Results revealed that after eliminating duplicates and strains with incomplete WGS, a total of 316 strains were deemed suitable for subsequent analyses. Within these strains, lineages I and II were extensively distributed, predominantly isolated from clinical and food sources. 56.65% of these strains fell into seven major Clonal Complexes (CC), identified by Multilocus Sequence Typing (MLST), correlating significantly with isolation information. Analysis of 46 resistance-related genes showed a high consistency of resistance genes in the same type of strains, hinting at a potential causal chain of habits-foods-environments evolutions. Moreover, the standard strains exhibit similar gene carriage rates as the sample strains, with multiple variations observed in acid-resistance genes. In conclusion, through a comprehensive analysis of the L. monocytogenes genome sequences, this study deepens our understanding of the differences and associations between its lineage, strain typing, isolation sources, geographical distribution, and resistance genes. It has also explored the potential impact of environmental noise on the expression of these genes, offering a scientific foundation for devising more effective prevention and control strategies against L. monocytogenes. Future endeavors should further dissect the functions of stress resistance genes and the variations in their expression, with the aim of gaining a deeper insight into the risks posed by L. monocytogenes to public health safety.

bioinformatics↗

bioRxiv2024

Mimicking the breast metastatic microenvironment: characterization of a novel syngeneic model of HER2+ breast cancer

Preclinical murine models in which primary tumors spontaneously metastasize to distant organs are valuable tools to study metastatic progression and novel cancer treatment combinations. Here, we characterize a novel syngeneic murine breast tumor cell line, NT2.5-lung metastasis (- LM), that provides a model of spontaneously metastatic neu-expressing breast cancer with quicker onset of widespread metastases after orthotopic mammary implantation in immune-competent NeuN mice. Within one week of orthotopic implantation of NT2.5-LM in NeuN mice, distant metastases can be observed in the lungs. Within four weeks, metastases are also observed in the bones, spleen, colon, and liver. Metastases are rapidly growing, proliferative, and responsive to HER2-directed therapy. We demonstrate altered expression of markers of epithelial-to-mesenchymal transition (EMT) and enrichment in EMT-regulating pathways, suggestive of their enhanced metastatic potential. The new NT2.5-LM model provides more rapid and spontaneous development of widespread metastases. Besides investigating mechanisms of metastatic progression, this new model may be used for the rationalized development of novel therapeutic interventions and assessment of therapeutic responses targeting distant visceral metastases SUMMARY STATEMENTWe characterize a new syngeneic, immune-competent murine model of breast cancer (NT2.5-LM) that yields rapid and widespread metastases, preserves spontaneous metastasis, and provides a model for studying novel therapeutic interventions.

cancer biology↗

bioRxiv2024

Optimizing Accuracy and Efficiency in Analyzing Non-UMI Liquid Biopsy Datasets Using the Sentieon ctDNA Pipeline

Sequencing clinical liquid biopsy, especially circulating tumor DNA (ctDNA), provides a valuable method for identifying low allele frequency tumor variants, opening novel clinical applications, particularly in treatment selection for late-stage cancer patients. Despite advancements, challenges in assay development persist, primarily due to limited sample volumes and insufficiency of reads supporting low allele frequency variants. The allele frequencies of clinically significant variants often hover close to the threshold of errors introduced by PCR and sequencing processes. Therefore, more sophisticated analysis methods are crucial to further reduce base error rates, enabling accurate discrimination between background errors and genuine somatic variants. While several ctDNA analysis pipelines have been published and adopted, there is room for improvement in terms of accuracy and run efficiency. In this study, we introduce Sentieons innovative consensus-based ctDNA pipeline - a rapid and precise solution for calling small somatic variants from non-UMI ctDNA sequencing data. The pipeline comprises four core modules: alignment, consensus generation, variant calling, and variant filtering. Through benchmarking with in-vitro and real clinical datasets, we observed that the Sentieon ctDNA pipeline exhibits higher accuracy compared to alternative methods.

bioinformatics↗

bioRxiv2024

Discovery of orally active SARS-CoV-2 papain-like protease (PLpro) inhibitors

Vaccines and first-generation antiviral therapeutics have provided important protection against coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there remains a need for additional therapeutic options that provide enhanced efficacy and protection against potential viral resistance. The SARS-CoV-2 papain-like protease (PLpro) is one of two essential cysteine proteases involved in viral replication. While inhibitors of the SARS-CoV-2 main protease (Mpro) have demonstrated clinical efficacy, known PLpro inhibitors have to date lacked the inhibitory potency and requisite pharmacokinetics to demonstrate that targeting PLpro translates to in vivo efficacy in a preclinical setting. Herein, we report the machine learning-driven discovery of potent, selective, and orally available SARS-CoV-2 PLpro inhibitors, with lead compound PF-07957472 (4) providing robust efficacy in a mouse-adapted model of COVID-19 infection.

microbiology↗

bioRxiv2024

Increased regional P2X7R expression detected by GSK1482160 PET in a tauopathy mouse model

Neuroinflammation plays an important role in Alzheimers disease and primary tauopathies. The aim of the current study was to map [18F]GSK1482160 for imaging of purinergic P2X7R in Alzheimers disease and primary tauopathy mouse models. MicroPET was performed using [18F]GSK1482160 in widely used mouse models of Alzheimers disease (APP/PS1, 5xFAD and 3xTg), 4-repeat tauopathy (rTg4510) mice and age-matched wild-type mice. Increased uptake of [18F]GSK1482160 was observed in the cortex and basal forebrain of 7-month-old rTg4510 mice compared to age-matched wild-type mice and compared to 3-month-old rTg4510 mice. Nonparametric Spearmans rank analysis revealed a positive correlation between tau [18F]APN-1607 uptake and [18F]GSK1482160 in the hippocampus of rTg4510 mice. No significant differences in the uptake of [18F]GSK1482160 were observed between wild-type mice and APP/PS1 mice (5, 10 months), 5xFAD mice (3, 7 months) or 3xTg mice (10 months). Immunofluorescence staining further indicated the distribution of P2X7Rs in the brains of 7-month-old rTg4510 mice with accumulation of tau inclusion compared to wild-type mice. These findings provide in vivo imaging evidence for increased P2X7R in the brains of tauopathy model mice.

neuroscience↗

bioRxiv2024

PI3Kγ promotes neutrophil extracellular trap formation by noncanonical pyroptosis in abdominal aortic aneurysm

BackgroundAbdominal aortic aneurysm (AAA) is one of the most life-threatening cardiovascular diseases while currently lacks effective drug treatment. NETs formation has been proved to be crucial trigger of AAA, so finding its upstream regulatory targets is the key to discovering therapeutic agents for AAA. Methods and Resultswe reveal that PI3Kgmma (PI3K{gamma}) is an upstream signal that regulates NETs formation. Inhibition of PI3K{gamma} reduces the expression of NETs and reduces inflammation in the aortic wall, thereby significantly ameliorating AAA. However, the mechanism of NETs formation regulated by PI3K{gamma} has not been fully elucidated. Using isolated bone marrow neutrophils, we show that PI3K{gamma} deficiency inactivates the noncanonical pyroptosis pathway (Capase11/GSDMD) to inhibit NETs expression, and subsequently found that PI3K{gamma} regulation of noncanonical pyroptosis via anchoring PKA is dependent on cAMP/PKA signaling, but not on classical PI3K/AKT signaling. ConclusionsOur research uncovers the role and mechanism of PI3K{gamma} in AAA development and provides insights into AAA therapy from the perspective of NETs formation.

cell biology↗

bioRxiv2024

Multifaceted Roles of Histone Lysine Lactylation in Meiotic Gene Dynamics and Recombination

Male germ cells, which are responsible for producing millions of genetically diverse sperm through meiosis in the testis, rely on lactate as their central energy metabolite. Recent study has revealed that lactate induces epigenetic modification in cells through histone lactylation, a post-translational modification involving the addition of lactyl groups to lysine residues on histones. Here we report dynamic histone lactylation at histone H4-lysine 5 (K5), -K8, and -K12 during meiosis prophase I in mouse spermatogenesis. By profiling genome-wide occupancy of histone H4-K8 lactylation (H4K8la), which peaks at zygotene, our data show that H4K8la mark is observed at the promoters of genes exhibiting active expression with Gene Ontology (GO) functions enriched for meiosis. Notably, our data also demonstrate that H4K8la is closely associated with recombination hotspots, where machinery involved in the processing DNA double-stranded breaks (DSBs), such as SPO11, DMC1, RAD51, and RPA2, is engaged. In addition, H4K8la was also detected at the meiosis-specific cohesion sites (marked by RAD21L and REC8) flanking the recombination hotspots. Collectively, our findings suggest that histone lactylation serves as a novel mechanism through which lactate regulates germ cell meiosis.

genetics↗

bioRxiv2024

Oscillatory Hypoxia Induced Unfolded Protein Folding Response Gene Expression Predicts Low Survival in Human Breast Cancer Patients

Hypoxia is one of the key factors in the tumor microenvironment regulating nearly all steps in the metastatic cascade in many cancers, including in breast cancer. The hypoxic regions can however be dynamic with the availability of oxygen fluctuating or oscillating. The canonical response to hypoxia is relayed by transcription factor HIF-1, which is stabilized in hypoxia and acts as the master regulator of a large number of downstream genes. However, HIF-1 transcriptional activity can also fluctuate either due to unstable hypoxia, or by lactate mediated non-canonical degradation of HIF-1. Our understanding of how oscillatory hypoxia or HIF-1 activity specifically influence cancer malignancy is very limited. Here, using MDA-MB-231 cells as a model of triple negative breast cancer characterized by severe hypoxia, we measured the gene expression changes induced specifically by oscillatory hypoxia. We found that oscillatory hypoxia can specifically regulate gene expression differently, and at times opposite to stable hypoxia. Using The Cancer Genome Atlas (TCGA) RNAseq data of human cancer samples, we show that the oscillatory specific gene expression signature in MDA-MB-231 is enriched in most human cancers, and prognosticate low survival in breast cancer patients. In particular, we found that oscillatory hypoxia, unlike stable hypoxia, induces unfolded protein folding response (UPR) in cells resulting in gene expression predicting reduced survival.

cancer biology↗

bioRxiv2024

Identifying new cancer genes based on the integration of annotated gene sets via hypergraph neural networks

MotivationIdentifying cancer genes remains a significant challenge in cancer genomics research. Annotated gene sets encode functional associations among multiple genes, and cancer genes have been shown to cluster in hallmark signaling pathways and biological processes. The knowledge of annotated gene sets is critical for discovering cancer genes but remains to be fully exploited. ResultsHere, we present the DIsease-Specific Hypergraph neural network (DISHyper), a hypergraph-based computational method that integrates the knowledge from multiple types of annotated gene sets to predict cancer genes. First, our benchmark results demonstrate that DISHyper outperforms the existing state-of-the-art methods and highlight the advantages of employing hypergraphs for representing annotated gene sets. Second, we validate the accuracy of DISHyper-predicted cancer genes using functional validation results and multiple independent functional genomics data. Third, our model predicts 44 novel cancer genes, and subsequent analysis shows their significant associations with multiple types of cancers. Overall, our study provides a new perspective for discovering cancer genes and reveals previously undiscovered cancer genes. AvailabilityDISHyper is freely available for download at https://github.com/genemine/DISHyper. Contactjxwang@mail.csu.edu.cn

systems biology↗

bioRxiv2024

3D genomic analysis reveals novel enhancer-hijacking caused by complex structural alterations that drive oncogene overexpression

Cancer genomes are composed of many complex structural alterations on chromosomes and extrachromosomal DNA (ecDNA), making it difficult to identify non-coding enhancer regions that are hijacked to activate oncogene expression. Here, we describe a 3D genomics-based analysis called HAPI (Highly Active Promoter Interactions) to characterize enhancer hijacking. HAPI analysis of HiChIP data from 34 cancer cell lines identified enhancer hijacking events that activate both known and potentially novel oncogenes such as MYC, CCND1, ETV1, CRKL, and ID4. Furthermore, we found enhancer hijacking among multiple oncogenes from different chromosomes, often including MYC, on the same complex amplicons such as ecDNA. We characterized a MYC-ERBB2 chimeric ecDNA, in which ERBB2 heavily hijacks MYCs enhancers. Notably, CRISPRi of the MYC promoter led to increased interaction of ERBB2 with MYC enhancers and elevated ERBB2 expression. Our HAPI analysis tool provides a robust strategy to detect enhancer hijacking and reveals novel insights into oncogene activation.

cancer biology↗

bioRxiv2024

Rbpms2 promotes female fate upstream of the nutrient sensing Gator2 complex component, Mios

Reproductive success relies on proper establishment and maintenance of biological sex. In many animals, including mammals, the primary gonad is initially ovary in character. We previously showed the RNA binding protein (RNAbp), Rbpms2, is required for ovary fate in zebrafish. Here, we identified Rbpms2 targets in oocytes (Rbpms2-bound oocyte RNAs; rboRNAs). We identify Rbpms2 as a translational regulator of rboRNAs, which include testis factors and ribosome biogenesis factors. Further, genetic analyses indicate that Rbpms2 promotes nucleolar amplification via the mTorc1 signaling pathway, specifically through the mTorc1-activating Gap activity towards Rags 2 (Gator2) component, Missing oocyte (Mios). Cumulatively, our findings indicate that early gonocytes are in a dual poised, bipotential state in which Rbpms2 acts as a binary fate-switch. Specifically, Rbpms2 represses testis factors and promotes oocyte factors to promote oocyte progression through an essential Gator2-mediated checkpoint, thereby integrating regulation of sexual differentiation factors and nutritional availability pathways in zebrafish oogenesis.

developmental biology↗

bioRxiv2024

Integrative Omics Uncovers Low Tumorous Magnesium Content as A Driver Factor of Colorectal Cancer

Magnesium (Mg) deficiency is associated with increased risk and malignancy of colorectal cancer (CRC), yet the underlying mechanisms remain elusive. Here we used genomic, proteomic, and phosphoproteomic data to elucidate the impact of Mg deficiency on CRC. Genomic analysis identified 160 genes with higher mutation frequencies in Low-Mg tumors, including key driver genes such as KMT2C and ERBB3. Unexpectedly, initiation driver genes of CRC, such as TP53 and APC, displayed higher mutation frequencies in High-Mg tumors. Additionally, proteomics and phosphoproteomics indicated that low tumorous Mg content may activate epithelial-mesenchymal transition (EMT) by modulating inflammation or remodeling the phosphoproteome of cancer cells. Notably, we observed a negative correlation between the phosphorylation of DBN1 at S142 (DBN1S142p) and Mg content. A mutation in S142 to D (DBN1S142D) mimicking DBN1S142p upregulated MMP2 and enhanced cell migration, while treatment with MgCl2 reduced DBN1S142p, thereby reversing this phenotype. Mechanistically, Mg2+ attenuated the DBN1-ACTN4 interaction by decreasing DBN1S142p, which, in turn, enhanced the binding of ACTN4 to F-actin and promoted F-actin polymerization, ultimately reducing MMP2 expression. These findings shed new light on the crucial role of Mg deficiency in CRC progression and suggest that Mg supplementation may offer a promising preventive and therapeutic strategy for CRC.

cancer biology↗

bioRxiv2024

ZNF827 pleiotropic cardiovascular risk locus involves regulation by Nuclear factor-1

IntroductionSCAD (spontaneous coronary artery dissection) is a form of myocardial infarction that disproportionately affects young women. SCAD is caused by the formation of a hematoma within coronary artery wall, resulting in its blockage. Sixteen SCAD susceptibility loci are currently known, including ZNF827 gene locus on chromosome 4. Several common genetic variations within ZNF827 are also linked to coronary artery disease (CAD), systolic blood pressure (SBP), and ascending aortic diameter. The molecular processes driving these genetic connections, however, are unknown. MethodsWe performed fine-mapping and genetic colocalization analysis at ZNF827 locus on multiple GWAS signals and quantitative expression traits. We explored the regulatory function of sequences of interest using a luciferase reporter system in rat smooth muscle cells. We used siRNA to knockdown the expression of gene and assessed transcriptomic changes through bulk RNA-Seq. ResultsThe genetic association signals for SCAD, CAD, blood pressure, and aorta dimensions could all be explained by a single causal variant. We identified rs13128814 as the most likely causative variant. This variant overlaps epigenetic regulatory markers specifically active in vascular SMCs and fibroblasts. A 1kb region containing the SCAD-risk allele (A) of rs13128814 variant had a transcriptional activation impact, while the protective allele (G) had no effect. In silico predictions found nuclear factor 1 (NF1) transcription factors preferentially bind to the A allele of rs13128814. We found that overexpressing NFIA (Nuclear Factor 1 A-Type) activated transcription in this area. SCAD association and ZNF827 eQTL colocalization in various vascular tissues suggested the latter as a plausible target gene in this locus. Knockdown of ZNF827 in iPSC-derived SMCs and fibroblasts, followed by RNA-seq, identified a large number of dysregulated genes, including multiple genes involved in cardiovascular disease. ConclusionOur findings in ZNF827 locus support the hypothesis that the rs13128814 variant, which may affect the binding of NF1 family transcription factors and cause ZNF827 expression to be deregulated, is the molecular mechanism underpinning the relationship of the ZNF827 locus with numerous cardiovascular disorders. ZNF827 acts as a regulator of gene expression in vascular SMCs and fibroblasts. Further investigation of ZNF827 function in vascular tissue will be required to understand the implications of its dysregulation on cardiovascular physiopathology.

cell biology↗

bioRxiv2024

Transcranial Photobiomodulation on the Left Prefrontal Cortex Enhances Mandarin Chinese L1 and L2 Complex Sentence Processing Performances

This study investigated the causal effect of transcranial photobiomodulation (tPBM) over the left prefrontal cortex (LPFC) on syntactically complex Mandarin Chinese first language (L1) and second language (L2) sentence processing performances. Two (L1 and L2) groups of participants (thirty per group) were recruited to receive the double-blind, sham-controlled tPBM intervention, followed by the sentence processing, the verbal working memory (WM), and the visual WM tasks. Results revealed a consistent pattern for both groups: (a) tPBM enhanced sentence processing performance but not verbal WM and visual WM performance; (b) Participants with lower sentence processing performances under sham tPBM benefited more from active tPBM. Taken together, the current study substantiated that tPBM enhanced L1 and L2 sentence processing ability directly without verbal WM interference, and would serve as a promising and cost-effective noninvasive brain stimulation (NIBS) tool for future applications on upregulating the human language faculty. HighlightsO_LIThe first study that applies tPBM to (complex) sentence processing. C_LIO_LItPBM enhances sentence processing performances in both Mandarin L1 & L2 speakers. C_LIO_LItPBM directly enhances sentence processing without the interference of verbal WM. C_LIO_LIA causal role of LPFC for sentence processing through active tPBM. C_LIO_LIOpening up the promising application prospect for tPBM on sentence processing. C_LI

neuroscience↗

bioRxiv2024

Self-inspired learning to denoise for live-cell super-resolution microscopy

Every collected photon is precious in live-cell super-resolution (SR) fluorescence microscopy for contributing to breaking the diffraction limit with the preservation of temporal resolvability. Here, to maximize the utilization of accumulated photons, we propose SN2N, a Self-inspired Noise2Noise engine with self-supervised data generation and self-constrained learning process, which is an effective and data-efficient learning-based denoising solution for high-quality SR imaging in general. Through simulations and experiments, we show that the SN2Ns performance is fully competitive to the supervised learning methods but circumventing the need for large training-set and clean ground-truth, in which a single noisy frame is feasible for training. By one-to-two orders of magnitude increased photon efficiency, the direct applications on various confocal-based SR systems highlight the versatility of SN2N for allowing fast and gentle 5D SR imaging. We also integrated SN2N into the prevailing SR reconstructions for artifacts removal, enabling efficient reconstructions from limited photons. Together, we anticipate our SN2N and its integrations could inspire further advances in the rapidly developing field of fluorescence imaging and benefit subsequent precise structure segmentation irrespective of noise conditions.

bioengineering↗

bioRxiv2024

Bleomycin induced EBV-specific gastric epithelial cell death is enhanced by LMP2A

Epstein-Barr virus (EBV) infects more than 90% of the global population, leading to EBV-related cancers, such as EBV-associated gastric cancer and nasopharyngeal carcinoma. Despite the rarity of p53 mutations in tumor cells, there is a lack of specific therapies targeting EBV-associated gastric cancers. Our study demonstrated that EBV-infected gastric epithelial cells exhibited high sensitivity to the bleomycin family, encompassing bleomycin and zeocin, compared to uninfected cells. Zeocin treatment induces a DNA damage response (DDR) and promotes the expression of BZLF1, triggering the expression of EBV lytic genes. This cascade leads to apoptosis via a p53 dependent pathway, coinciding with the activation of caspase-3. Cells infected with the BZLF1-deficient virus could not induce apoptosis by zeocin treatment, and the cells maintained a tight latent infection but initiated a robust DDR. Conversely, neither lytic infection nor DDR was induced by zeocin treatment in cells infected with LMP2A-deficient virus. These findings indicate that LMP2A augments DDR in EBV-infected gastric epithelial cells, facilitating the transition from latent to lytic infection, and consequently inducing cell death. Bleomycin derivatives are expected to serve as fundamental components in the development of specific anticancer drugs targeting EBV-positive epithelial cancer cells. IMPORTANCEBecause of its ubiquitous infection in the human population, the number of patients suffering from EBV-related diseases, including malignant tumors and severe active infections, is substantial. Previous research has reported the potential of drugs such as HDAC inhibitors and poly ADP-ribose polymerase inhibitors to induce cell death in EBV-infected cells. However, a clinical therapeutic agent specifically reducing EBV-infected cells has not yet been available. In this study, we report that bleomycin, or its derivative, which has been used for over half a century, induces apoptotic cell death in EBV-infected cells by triggering lytic viral replication associated with DNA damage response. Particularly, we discovered that the viral latent gene LMP2A unexpectedly enhances bleomycin-induced EBV-infected epithelial cell death by promoting DDR.

microbiology↗

bioRxiv2024

Quantifying Interpretation Reproducibility in Vision Transformer Models with TAVAC

The use of deep learning algorithms to extract meaningful diagnostic features from biomedical images holds the promise to improve patient care given the expansion of digital pathology. Among these deep learning models, Vision Transformer (ViT) models have been demonstrated to capture long-range spatial relationships with more robust prediction power for image classification tasks than regular convolutional neural network (CNN) models, and also better model interpretability. Model interpretation is important for understanding and elucidating how a deep learning model makes predictions, especially for developing transparent models for digital pathology. However, like other deep learning algorithms, with limited annotated biomedical imaging datasets, ViT models are prone to poor performance due to overfitting, which can lead to false predictions due to random noise. Overfitting affects model interpretation when predictions are made out of random noise. To address this issue, we introduce a novel metric - Training Attention and Validation Attention Consistency (TAVAC) - for evaluating ViT model degree of overfitting on imaging datasets and quantifying the reproducibility of interpretation. Specifically, the model interpretation is performed by comparing the high-attention regions in the image between training and testing. We test the method on four publicly available image classification datasets and two independent breast cancer histological image datasets. All overfitted models exhibited significantly lower TAVAC scores than the good-fit models. The TAVAC score quantitatively measures the level of generalization of model interpretation on a fine-grained level for small groups of cells in each H&E image, which cannot be provided by traditional performance evaluation metrics like prediction accuracy. Furthermore, the application of TAVAC extends beyond medical diagnostic AI models; it enhances the monitoring of model interpretative reproducibility at pixel-resolution in basic research, to reveal critical spatial patterns and cellular structures essential to understanding biological processes and disease mechanisms. TAVAC sets a new standard for evaluating the performance of deep learning model interpretation and provides a method for determining the significance of high-attention regions detected from the attention map of the biomedical images.

bioinformatics↗

bioRxiv2024

Defining cell type-specific immune responses in a mouse model of allergic contact dermatitis by single-cell transcriptomics

Allergic contact dermatitis (ACD), a prevalent inflammatory skin disease, is elicited upon repeated skin contact with protein-reactive chemicals through a complex and poorly characterized cellular network between immune cells and skin resident cells. Here, single-cell transcriptomic analysis of the murine hapten-elicited model of ACD reveals that upon elicitation of ACD, infiltrated CD4+ or CD8+ lymphocytes were primarily the IFN{gamma}-producing type 1 central memory phenotype. In contrast, type 2 cytokines (IL4 and IL13) were dominantly expressed by basophils, IL17A was primarily expressed by {delta}{gamma} T cells, and IL1{beta} was identified as the primary cytokine expressed by activated neutrophils/monocytes and macrophages. Furthermore, analysis of skin resident cells identified a sub-cluster of dermal fibroblasts with preadipocyte signature as a prominent target for IFN{gamma}+ lymphocytes and dermal source for key T cell chemokines CXCL9/10. IFN{gamma} treatment shifted dermal fibroblasts from collagen-producing to CXCL9/10-producing, which promoted T cell polarization toward the type-1 phenotype through a CXCR3-dependent mechanism. Furthermore, targeted deletion of Ifngr1 in dermal fibroblasts in mice reduced Cxcl9/10 expression, dermal infiltration of CD8+ T cell, and alleviated ACD inflammation in mice. Finally, we showed that IFN{gamma}+ CD8+ T cells and CXCL10-producing dermal fibroblasts co-enriched in the dermis of human ACD skin. Together, our results define the cell type-specific immune responses in ACD, and recognize an indispensable role of dermal fibroblasts in shaping the development of type-1 skin inflammation through the IFNGR-CXCR3 signaling circuit during ACD pathogenesis.

immunology↗