Unique Cell Research Articles

Optimized protocol for the multiomics processing of cryopreserved human kidney tissue.

Biobanking of tissue from clinically obtained kidney biopsies for later analysis with multiomic approaches, such as single-cell technologies, proteomics, metabolomics, and the different types of imaging, is an inevitable step to overcome the need of disease model systems and toward translational medicine. Hence, collection protocols that ensure integration into daily clinical routines by the usage of preservation media that do not require liquid nitrogen but instantly preserve kidney tissue for both clinical and scientific analyses are necessary. Thus, we modified a robust single-nucleus dissociation protocol for kidney tissue stored snap-frozen or in the preservation media RNAlater and CellCover. Using at first porcine kidney tissue as a surrogate for human kidney tissue, we conducted single-nucleus RNA sequencing with the widely recognized Chromium 10X Genomics platform. The resulting datasets from each storage condition were analyzed to identify any potential variations in transcriptomic profiles. Furthermore, we assessed the suitability of the preservation media for additional analysis techniques such as proteomics, metabolomics, and the preservation of tissue architecture for histopathological examination including immunofluorescence staining. In this study, we show that in daily clinical routines, the preservation medium RNAlater facilitates the collection of highly preserved human kidney biopsies and enables further analysis with cutting-edge techniques like single-nucleus RNA sequencing, proteomics, and histopathological evaluation. Only metabolome analysis is currently restricted to snap-frozen tissue. This work will contribute to build tissue biobanks with well-defined cohorts of the respective kidney disease that can be deeply molecularly characterized, opening up new horizons for the identification of unique cells, pathways and biomarkers for the prevention, early identification, and targeted therapy of kidney diseases.NEW & NOTEWORTHY In this study, we addressed challenges in integrating clinically obtained kidney biopsies into everyday clinical routines. Using porcine kidneys, we evaluated preservation media (RNAlater and CellCover) versus snap freezing for multi-omics processing. Our analyses highlighted RNAlater's suitability for single-nucleus RNA sequencing, proteome analysis and histopathological evaluation. Only metabolomics are currently restricted to snap-frozen biopsies. Our research established a cryopreservation protocol that facilitates tissue biobanking for advancing precision medicine in nephrology.

Peripheral immune landscape of pediatric fulminant myocarditis revealed by single-cell sequencing

Abstract Fulminant myocarditis (FM) is one of the most feared diseases in children because of its fulminant nature and high mortality rate. However, the precise pathological immune subsets and molecular changes in FM are unknown. Here, we present the first comprehensive cellular and transcriptomic profiling of the peripheral blood mononuclear cells of children in FM acute and recovery phases using Single-cell RNA sequencing. 21 cell clusters are identified among 79542 cells. The proportion of T cells and NK cells increase, while myeloid cells and B cells reduce in acute phase, which were consistent with our flow cytometry data of 35 FM patients. Several unique cell types in peripheral blood are identified, including regulatory B cells, MAIT cells, adaptive NK cells and CD8+Tpex cells. The transcriptomic analysis exhibited elevated expression levels of chemokine receptor CXCR4 and S100A family genes almost in all cell types in FM acute phase, as well as MHC-II molecules in antigen-presenting cells. TCR and BCR exhibit remarkable amplification and obvious skewed usages of V genes in FM. Ligand receptor analysis show myeloid cells maintained active communication with other immune cells. Considering that CXCR4 may play an important role in myocarditis, we designed experiments to explore its function in mouse model. Vital myocarditis (VMC) mouse model was constructed using Coxsackie virus type3（CVB3）.We found that myocardial inflammation and myocardial injury of VMC mice were alleviated when treated with CXCR4 blocker. CXCR4 may be a potential therapeutic target for myocarditis. Our study will provide useful insights into key immune cell subsets and transcriptomic profiles implicated in pediatric fulminant myocarditis acute phase and recovery phase, thus providing several potential diagnostic and therapeutic targets for this disease.

Oxct1 regulates cardiomyocyte PANoptosis in acute myocardial infarction via succinylating Tfam

Abstract Background Myocardial ischemia leads to various forms of programmed cell death in cardiomyocytes, resulting in acute myocardial infarction (AMI) and the development of heart failure in the long term. PANoptosis is a unique cell death regulatory mechanism orchestrated by the PANoptosome complex, which regulates and intersects multiple forms of programmed cell death. Oxct1 has been demonstrated to play crucial roles in tumors, pressure-overloaded hearts, and cardiac endothelial cells. However, whether Oxct1 is involved in the regulation of PANoptosis and correlated mechanisms during AMI remains unclear. Purpose To elucidate the role of Oxct1 in cardiomyocytes during AMI and uncover the potential mechanisms. Methods The myocardial infarction model induced by anterior descending branch ligation and the primary cardiomyocytes hypoxia model were employed in our experiments. Small interfering RNA (siRNA) and adenovirus were constructed to knock down and overexpress Oxct1 for altering its expression in cardiomyocytes in vitro. Cardiomyocyte-specific knockout mice were constructed to alter Oxct1 expression in vivo. PANoptosis characteristic measurement, including Z-DNA binding protein 1(Zbp1), pyroptosis markers, apoptosis markers, necroptosis markers, ROS, and mitochondrial morphology, were performed to verify the ability of Oxct1 to regulate the PANoptosis of cardiomyocytes. Cardiac morphological, structural, and functional changes were measured to assess the effect of Oxct1 on AMI. RNA sequencing was performed to identify downstream pathways. Immunoprecipitation +Mass spectrometry and co-immunoprecipitation were performed to identify the specific binding factors of Oxct1. Results We found that the expression of Oxct1 was significantly elevated after AMI. Besides, gain- and loss-of-function experiments were constructed both in vitro and in vivo. Functionally, Oxct1 knockdown significantly enhanced cardiomyocyte vitality, reduced ROS production and mtDNA cytoplasmic release in hypoxic cardiomyocytes. In vivo, Oxct1cko mice manifested reduced infarct size, improved cardiac function and alleviated cardiac fibrosis by mitigating PANoptosis. However, Oxct1 overexpression resulted in the opposite effects. Afterwards, RNA-seq analysis results showed that cytosolic DNA-sensing pathway was significantly enriched in Oxct1 knockdown cardiomyocytes. Mechanistically, Oxct1 could bind to mitochondrial transcription factor A(Tfam) and increased its succinylation, promoting Tfam degradation. Downregulation of Tfam resulted in ROS production and mtDNA damage, while mtDNA released into cytoplasm could activate Zbp1 and induce cascade reaction of PANoptosis. Conclusion This study demonstrates that Oxct1 promotes Tfam degradation through succinylation, exacerbating ROS production, mtDNA damage and cytoplasmic release, ultimately leading to cardiomyocyte PANoptosis in AMI.

Defining the transcriptome of PIK3CA-altered cells in a human capillary malformation using single cell long-read sequencing

PIK3CA-related overgrowth spectrum (PROS) disorders are caused by somatic mosaic variants that result in constitutive activation of the phosphatidylinositol-3-kinase/AKT/mTOR pathway. Promising responses to molecularly targeted therapy have been reported, although identification of an appropriate agent can be hampered by the mosaic nature and corresponding low variant allele frequency of the causal variant. Moreover, our understanding of the molecular consequences of these variants—for example how they affect gene expression profiles—remains limited. Here we describe in vitro expansion of a human capillary malformation followed by molecular characterization using exome sequencing, single cell gene expression, and targeted long-read single cell RNA-sequencing in a patient with clinical features consistent with Megalencephaly-Capillary Malformation Syndrome (MCAP, a PROS condition). These approaches identified a targetable PIK3CA variant with expression restricted to PAX3+ fibroblast and undifferentiated keratinocyte populations. This study highlights the innovative combination of next-generation single cell sequencing methods to better understand unique transcriptomic profiles and cell types associated with MCAP, revealing molecular intricacies of this genetic syndrome.

Machine-guided design of cell-type-targeting cis-regulatory elements.

Cis-regulatory elements (CREs) control gene expression, orchestrating tissue identity, developmental timing and stimulus responses, which collectively define the thousands of unique cell types in the body1-3. While there is great potential for strategically incorporating CREs in therapeutic or biotechnology applications that require tissue specificity, there is no guarantee that an optimal CRE for these intended purposes has arisen naturally. Here we present a platform to engineer and validate synthetic CREs capable of driving gene expression with programmed cell-type specificity. We take advantage of innovations in deep neural network modelling of CRE activity across three cell types, efficient in silico optimization and massively parallel reporter assays to design and empirically test thousands of CREs4-8. Through large-scale in vitro validation, we show that synthetic sequences are more effective at driving cell-type-specific expression in three cell lines compared with natural sequences from the human genome and achieve specificity in analogous tissues when tested in vivo. Synthetic sequences exhibit distinct motif vocabulary associated with activity in the on-target cell type and a simultaneous reduction in the activity of off-target cells. Together, we provide a generalizable framework to prospectively engineer CREs from massively parallel reporter assay models and demonstrate the required literacy to write fit-for-purpose regulatory code.

Single-Cell Transcriptomics Unveils Skin Cell Specific Antifungal Immune Responses and IL-1Ra- IL-1R Immune Evasion Strategies of Emerging Fungal Pathogen Candida auris.

Candida auris is an emerging multidrug-resistant fungal pathogen that preferentially colonizes and persists in skin tissue, yet the host immune factors that regulate the skin colonization of C. auris in vivo are unknown. In this study, we employed unbiased single-cell transcriptomics of murine skin infected with C. auris to understand the cell type-specific immune response to C. auris. C. auris skin infection results in the accumulation of immune cells such as neutrophils, inflammatory monocytes, macrophages, dendritic cells, T cells, and NK cells at the site of infection. We identified fibroblasts as a major non-immune cell accumulated in the C. auris infected skin tissue. The comprehensive single-cell profiling revealed the transcriptomic signatures in cytokines, chemokines, host receptors (TLRs, C-type lectin receptors, NOD receptors), antimicrobial peptides, and immune signaling pathways in individual immune and non-immune cells during C. auris skin infection. Our analysis revealed that C. auris infection upregulates the expression of the IL-1RN gene (encoding IL-1R antagonist protein) in different cell types. We found IL-1Ra produced by macrophages during C. auris skin infection decreases the killing activity of neutrophils. Furthermore, C. auris uses a unique cell wall mannan outer layer to evade IL-1R-signaling mediated host defense. Collectively, our single-cell RNA seq profiling identified the transcriptomic signatures in immune and non-immune cells during C. auris skin infection. Our results demonstrate the IL-1Ra and IL-1R-mediated immune evasion mechanisms employed by C. auris to persist in the skin. These results enhance our understanding of host defense and immune evasion mechanisms during C. auris skin infection and identify potential targets for novel antifungal therapeutics.

Single cell transcriptional analysis of human adenoids identifies molecular features of airway microfold cells.

The nasal, oropharyngeal, and bronchial mucosa are primary contact points for airborne pathogens like Mycobacterium tuberculosis (Mtb), SARS-CoV-2, and influenza virus. While mucosal surfaces can function as both entry points and barriers to infection, mucosa-associated lymphoid tissues (MALT) facilitate early immune responses to mucosal antigens. MALT contains a variety of specialized epithelial cells, including a rare cell type called a microfold cell (M cell) that functions to transport apical antigens to basolateral antigen-presenting cells, a crucial step in the initiation of mucosal immunity. M cells have been extensively characterized in the gastrointestinal (GI) tract in murine and human models. However, the precise development and functions of human airway M cells is unknown. Here, using single-nucleus RNA sequencing (snRNA-seq), we generated an atlas of cells from the human adenoid and identified 16 unique cell types representing basal, club, hillock, and hematopoietic lineages, defined their developmental trajectories, and determined cell-cell relationships. Using trajectory analysis, we found that human airway M cells develop from progenitor club cells and express a gene signature distinct from intestinal M cells. Surprisingly, we also identified a heretofore unknown epithelial cell type demonstrating a robust interferon-stimulated gene signature. Our analysis of human adenoid cells enhances our understanding of mucosal immune responses and the role of M cells in airway immunity. This work also provides a resource for understanding early interactions of pathogens with airway mucosa and a platform for development of mucosal vaccines.

The Alteration of Microglial Calcium Homeostasis in Central Nervous System Disorders: A Comprehensive Review

Microglia, the unique and motile immune cells of the central nervous system (CNS), function as a security guard in maintaining CNS homeostasis, primarily through calcium signaling. The calcium dynamics in microglia control important functions such as phagocytosis, cytokine release, and migration. Calcium dysregulation in microglia has been linked to several CNS disorders, like Alzheimer’s disease (AD), Parkinson’s disease (PD), multiple sclerosis (MS), and ischemic stroke (IS). Calcium entering through channels such as voltage-gated calcium channels (VGCCs), store-operated calcium entry (SOCE), and transient receptor potential (TRP) channels is essential for microglial activation and pro-inflammatory responses. Under pathological conditions, like the formation of amyloid-β plaques in AD, aggregation of α-synuclein in PD, and oxidative stress in MS, calcium dysregulation exacerbates neuroinflammation, mitochondrial dysfunction, and neurodegeneration. Therapeutic strategies targeting calcium signaling pathways, using calcium channel blockers and antioxidant interventions, show promise for alleviating microglial activation and slowing down disease progression. This review summarizes the underlying mechanisms of microglial calcium dysregulation and potential therapeutic benefits for restoring microglial calcium balance in CNS disorders.

Cell-cycle phase progression analysis identifies three unique phenotypes in soft tissue sarcoma

PurposeLoddo et al. (Br J Cancer 100:959–70, 2009) established the prognostic significance of cell cycle markers and "Cell-Cycle Phenotypes" in breast carcinoma. This study aims to 1) identify prognostic cell-cycle markers in sarcoma, and 2) assess the prognostic potential of specific cell-cycle phenotypes in sarcoma.MethodsTissue samples from 128 soft tissue sarcomas were stained for four cell cycle-specific markers: Mcm2, Geminin, Plk1, and H3S10ph. Only primary soft tissue tumors (liposarcoma, leiomyosarcoma, synovial sarcoma, and undifferentiated pleomorphic sarcoma) were included in the analysis. Any tumor coming from a recurrent or metastatic lesion were excluded from the analysis. Three cell-cycle phenotypes (I, II, III) were derived from marker expression patterns. Prognostic significance was evaluated in a subset of primary soft tissue sarcomas using Cox regression for survival analysis.ResultsCompared to phenotype I, the phenotype III tumors had a decreased 5-year overall survival (HR 6.81 [2.36–19.61]; p = < 0.001), 5-year disease-free survival (HR 1.07 (1.02–1.18); p = 0.004), and 5-year metastasis-free survival (HR 4.34 [1.58–11.93]; p = 0.004).High expression of Plk1 was associated with decreased 5-year overall survival (HR: 4.04 CI [1.21–6.67; p = 0.02) and 5-year metastasis-free survival (HR: 2.91 CI [1.15–7.37]; p = 0.03). Geminin was also found to have a decreased 5-year overall survival (HR:2.84 CI [1.21–6.67]; p = 0.02). No statistical difference in prognostication were noted between phenotypes and the AJCC system.ConclusionsWe identified three unique sarcoma cell cycle phenotypes that have prognostic significance. This performs similarly to the AJCC staging system.

Neuropeptide signalling orchestrates T cell differentiation.

The balance between T helper type 1 (TH1) cells and other TH cells is critical for antiviral and anti-tumour responses1-3, but how this balance is achieved remains poorly understood. Here we dissected the dynamic regulation of TH1 cell differentiation during in vitro polarization, and during in vivo differentiation after acute viral infection. We identified regulators modulating T helper cell differentiation using a unique TH1-TH2 cell dichotomous culture system and systematically validated their regulatory functions through multiple in vitro and in vivo CRISPR screens. We found that RAMP3, a component of the receptor for the neuropeptide CGRP (calcitonin gene-related peptide), has a cell-intrinsic role in TH1 cell fate determination. Extracellular CGRP signalling through the receptor RAMP3-CALCRL restricted the differentiation of TH2 cells, but promoted TH1 cell differentiation through the activation of downstream cAMP response element-binding protein (CREB) and activating transcription factor 3 (ATF3). ATF3 promoted TH1 cell differentiation by inducing the expression of Stat1, a key regulator of TH1 cell differentiation. After viral infection, an interaction between CGRP produced by neurons and RAMP3 expressed on T cells enhanced the anti-viral IFNγ-producing TH1 and CD8+ T cell response, and timely control of acute viral infection. Our research identifies a neuroimmune circuit in which neurons participate in T cell fate determination by producing the neuropeptide CGRP during acute viral infection, which acts on RAMP3-expressing T cells to induce an effective anti-viral TH1 cell response.

Identification of LRP1+CD13+ human periosteal stem cells that require LRP1 for bone repair.

Human periosteal skeletal stem cells (P-SSCs) are critical for cortical bone maintenance and repair. However, their in vivo identity, molecular characteristics, and specific markers remain unknown. Here, single-cell sequencing revealed human periosteum contains SSC clusters expressing known SSC markers, PDPN and PDGFRA. Notably, human P-SSCs, but not bone marrow SSCs (BM-SSCs), selectively expressed newly identified markers, LRP1 and CD13. These LRP1+CD13+ human P-SSCs were perivascular cells with high osteochondrogenic but minimal adipogenic potential. Upon transplantation into bone injuries in mice, they preserved self-renewal capability in vivo. Single-cell analysis of mouse periosteum further supported the preferential expression of LRP1 and CD13 in Prx1+ P-SSCs. When Lrp1 was conditionally deleted in Prx1-lineage cells, it led to severe bone deformity, short statue, and periosteal defects. By contrast, local treatment with a LRP1 agonist at the injury sites induced early P-SSC proliferation and bone healing. Thus, human and mouse periosteum contains unique osteochondrogenic stem cell subsets, and these P-SSCs express specific markers, LRP1 and CD13, with regulatory mechanism through LRP1 that enhances P-SSC function and bone repair.

Attentive graph neural network models for the prediction of blood brain barrier permeability.

The blood brain barrier's (BBB) unique endothelial cells and tight junctions selectively regulate passage of molecules to the central nervous system (CNS) to prevent pathogen entry and maintain neural homeostasis. Various neurological conditions and neurodegenerative diseases benefit from small molecules capable of BBB penetration (BBBP) to elicit a therapeutic effect. Predicting BBBP often involves in silico assessment of molecular properties such as lipophilicity (log P ) and polar surface area (PSA) using the CNS multiparameter optimization (MPO) method. This study curated an open-source dataset to benchmark rigorously machine learning (ML) and neural network (NN) models with each other and with MPO for predicting BBBP. Our analysis demonstrated that AI models, especially attentive NNs using stereochemical features, significantly outperform MPO in predicting BBBP. An attentive graph neural network (GNN), we refer to as CANDID-CNS™, achieved a 0.23-0.26 higher AUROC score than MPO on full test sets, and a 0.17-0.19 higher score on stereoisomers filtered subsets. Regarding stereoisomers that differ in BBBP, which MPO cannot distinguish, attentive GNNs correctly classify these with AUROC and MCC metrics comparable to or better than MPO's AUROC and MCC on less difficult test molecules. These findings suggest that integrating attentive GNN models into pharmaceutical drug discovery processes can substantially improve prediction rates, and thereby reduce the timeline, cost, and increase probability of success of designing brain penetrant therapeutics for the treatment of a wide variety of neurological and neurodegenerative diseases.

A multi-task graph deep learning model to predict drugs combination of synergy and sensitivity scores

BackgroundDrug combination treatments have proven to be a realistic technique for treating challenging diseases such as cancer by enhancing efficacy and mitigating side effects. To achieve the therapeutic goals of these combinations, it is essential to employ multi-targeted drug combinations, which maximize effectiveness and synergistic effects.ResultsThis paper proposes ‘MultiComb’, a multi-task deep learning (MTDL) model designed to simultaneously predict the synergy and sensitivity of drug combinations. The model utilizes a graph convolution network to represent the Simplified Molecular-Input Line-Entry (SMILES) of two drugs, generating their respective features. Also, three fully connected subnetworks extract features of the cancer cell line. These drug and cell line features are then concatenated and processed through an attention mechanism, which outputs two optimized feature representations for the target tasks. The cross-stitch model learns the relationship between these tasks. At last, each learned task feature is fed into fully connected subnetworks to predict the synergy and sensitivity scores.The proposed model is validated using the O’Neil benchmark dataset, which includes 38 unique drugs combined to form 17,901 drug combination pairs and tested across 37 unique cancer cells. The model’s performance is tested using some metrics like mean square error (MSE\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$MSE$$\\end{document}), mean absolute error (MAE\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$MAE$$\\end{document}), coefficient of determination (R2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${R}^{2}$$\\end{document}), Spearman, and Pearson scores. The mean synergy scores of the proposed model are 232.37, 9.59, 0.57, 0.76, and 0.73 for the previous metrics, respectively. Also, the values for mean sensitivity scores are 15.59, 2.74, 0.90, 0.95, and 0.95, respectively.ConclusionThis paper proposes an MTDL model to predict synergy and sensitivity scores for drug combinations targeting specific cancer cell lines. The MTDL model demonstrates superior performance compared to existing approaches, providing better results.

A GAN-based stepwise full-field mechanical prediction model for architected metamaterials

The exploration of mechanical metamaterials, characterized by unique unit cells with significant macroscopic mechanical properties, is of crucial importance. Traditional methods relying on bioinspired structures lack broad design space and controllability to some extent, especially when practical requirements have no biological counterparts. Hence, there is a pressing need to advance methodologies for the expansive design of unit cells, catering to diverse practical demands. Inspired by architected material, a latent design paradigm gains prominence for its extensive possibilities and unique distribution. However, wide design space faces challenges in accurately assessing the deformation history and stress states of diverse units, requiring validation through experiments or simulations, and imposing efficiency constraints on design. Using patterns generated by a mimetic corrosion algorithm and computational simulations, a GAN-based machine learning surrogate model is constructed to predict the history of deformation and stress fields of architected unit cells with accuracy and efficiency, in which a stepwise mapping strategy is proposed to augment comprehension of mechanical information in image processing. In distinct cases covering both explored domains and several unexplored domains, the model achieves effective predictions, demonstrating the robustness and adaptability of the model in extrapolating predictions of both time domain and design space. The proposed method demonstrates efficacy, stability, and generalizability, pioneering a solution for the mechanical history prediction of architected metamaterials in a sparse data setting, thereby overcoming the limitations of the training set.

Identification and validation of diagnostic markers related to immunogenic cell death and infiltration of immune cells in diabetic nephropathy

IntroductionImmunogenic cell death (ICD) is a unique cell death triggered by chemotherapy. However, studies elucidating the potential therapeutic role of ICD and the underlying mechanism in diabetic nephropathy (DN) are limited. MethodsWGCNA was conducted on the human kidney biopsy data linked to DN, analyzing gene sets associated with ICD. Gene Set Enrichment Analysis and Gene Set Variation Analysis were utilized to examine the discrepancy in biological function. We used Gene Ontology, the Kyoto Encyclopedia of Genes and Genomes, and the GeneMANIA database to investigate the function of the signature genes. An analysis using the receiver operating characteristic (ROC) was conducted to validate the diagnostic value of hub genes. Additionally, immune infiltration-related analyses were also performed. In conclusion, we examined the association between the glomerular filtration rate, serum creatinine, and hub genes. Hub genes were validated by immunohistochemistry using db/db mice kidneys. ResultsWGCNA revealed that the targets in the turquoise unit (1674 genes) exhibited the highest positive correlation with ICD. Furthermore, 4222 statistically significant DEGs were identified when comparing the DN and healthy control groups. Significantly, the KEGG pathway enrichment analysis indicated a connection between ICD and the nuclear factor-kappa B signaling pathway and the synthesis of cytokines (tumor necrosis factor superfamily). ROC analysis revealed that 16 hub genes exhibited strong discriminatory potential as biomarkers for DN. Therefore, immunohistochemical validation, with the potential involvement of chemokines (CCL11, CCR2, CCR7, CX3CR1, CXCL10, CXCL12, and CXCR5) and immune cells (CD3G, CD5, and CD247) may be crucial for the diagnosis and therapy of DN. ConclusionsDKK3, NR4A1, NR4A2, VEGFA, and DUSP1 may be associated with the development of DN. The pathogenesis of DN may specifically involve chemokines (CCL11, CCR2, CCR7, CX3CR1, CXCL10, CXCL12, and CXCR5) and immune cells (CD3G, CD5, and CD247), with LCP2 playing a significant role.

7574 Diabetes Stem Cells: A Common Target for Abnormal Insulin Secretion and Insulin Resistance

Abstract Disclosure: H. Kojima: None. M. Katagi: None. J. Okano: None. T. Nakagawa: None. Diabetes is based on chronic inflammation and cannot be cured using only drugs that lower blood glucose levels. A culprit was lurking there that was hindering healing. We discovered abnormal hematopoietic stem cells that caused persistent chronic inflammation in the bone marrow of diabetic model animals. The real culprit is born after several days of hyperglycemia, never dies, and each time glycemic control deteriorates, it moves its progeny in large numbers throughout the body, fusing with unique cells in various organs and producing TNF-α from the organ cells. We have named these worst stem cells, which resemble cancer stem cells, "diabetes stem cells," and attempted to induce complete remission in diabetic model animals by eliminating them with drugs. In this study, we used streptozotocin (STZ)-induced insulin-deficient diabetes model mice. "Diabetes stem cells" were included in the CD106-positive short-term hematopoietic stem cell fraction, in which progenitor cells that play an important role in the regeneration of the thymus and peripheral tissues, and were characterized by abnormal expression of proinsulin and TNF-α. Furthermore, like cancer cells, the expression of histone deacetylases (HDACs) increased, and once the cells were born, they would not disappear. Therefore, we aimed to eliminate diabetes by administering an HDAC inhibitor and subcutaneously injecting insulin pellets to temporarily correct blood glucose levels. We treated diabetic mice with HDAC inhibitor for 8 weeks, along with several weeks of insulin therapy. Insulin aims to prevent the formation of new abnormal cells in the bone marrow and to prevent the inhibition of pancreatic islet wasting due to the forced insulin secretion caused by hyperglycemia. The combination therapy allowed the beta cells to regenerate and produce enough insulin to normalize blood glucose levels and maintain them even after treatment was discontinued. It also solved the mystery of how the abnormal cell population evades attacks from the T cells. In STZ diabetes, the supply of normal CD106-positive progenitor cells from the bone marrow for thymic regeneration was completely blocked, resulting in marked thymic atrophy. As a result, the thymus, which had lost its progenitor cells, was unable to establish an immune surveillance system to eliminate mutated cells throughout the body. In other words, the combination therapy completely broke the vicious cycle caused by atrophies in both the islet and the thymus. Moreover, when the thymus was surgically removed along with the adventitia to prevent regeneration, diabetes remission was completely inhibited, supporting the importance of thymic normalization. Diabetes is a hematopoietic stem cell disease accompanied by thymic dysfunction, and the removal of "diabetes stem cells" paves the way for the cure of diabetes. Presentation: 6/2/2024

Lattice metamaterials with controllable mechanical properties inspired by projection of four-dimensional hypercubes

There has been an increasing interest among the material research community in the pursuit of enhancing the designability of mechanical properties. The existing approaches usually resorted to sophisticated algorithms (such as machine learning) for the reverse design of materials with specific properties. Different from these existing approaches, here we propose a new approach to create lattice metamaterials with continuously controllable mechanical properties by continuously adjusting the geometric parameters of a unique cell topology originated from the projection of four-dimensional hypercubes. The cells contain an inner region and an outer region, each with different deformation characteristics. For example, the inner region is a stretching-dominated simple cubic (SC) unit cell, while the outer region is a bending-dominated body-centered cubic (BCC) unit cell. Specifically, both stiffness and strength isotropy can be simultaneously realized. The proposed lattice metamaterial exhibits intriguing feature of dual stress plateaus. These plateaus can be effectively controlled by adjusting the geometric parameters of inner and outer regions, which enables these lattice metamaterials to hold promising application prospects in the energy absorption scenarios, such as vehicle and pedestrian protection. Such lattice metamaterial design can be used to realize the gradient distribution of mechanical properties through continuous transition of cell topology without introduction of inefficient interfaces, providing a new approach for the design of heterogeneous metamaterials used in the scenarios involving non-uniform stress distribution.

7908 GPNMB Promotes Tumor Growth And Is A Biomarker For Lymphangioleiomyomatosis (LAM)

Abstract Disclosure: E. Gibbons: None. M. Taya: None. H. Wu: None. S. Lopa: None. J. Moss: None. E.P. Henske: None. F.X. McCormack: None. S.R. Hammes: None. Lymphangioleiomyomatosis (LAM) is a rare, progressive cystic lung disease affecting almost exclusively female-sexed individuals. The cysts represent regions of lung destruction caused by smooth muscle tumors containing mutations in one of the two tuberous sclerosis (TSC) genes. mTORC1 inhibition slows but does not stop LAM advancement. Furthermore, monitoring disease progression is hindered by insufficient biomarkers. Therefore, new treatment options and biomarkers are needed. LAM cells express melanocytic markers, including Glycoprotein Non-Metastatic Melanoma Protein B (GPNMB). The function of GPNMB in LAM is currently unknown; however, GPNMB’s unique cell surface expression on tumor versus benign cells makes GPNMB a potential therapeutic target, and persistent release of its extracellular ectodomain suggests potential as a serum biomarker. Here we establish that GPNMB regulates TSC2-null tumor cell invasion as well as TSC2-null xenograft tumor growth, and that GPNMB expression is dependent on mTORC1 signaling. Further, we show that GPNMB’s ectodomain is released from the cell surface of TSC2-null cells by ADAM10 and 17 proteases, and we identify the protease target sequence on GPNMB. In fact, mutating this cleavage sequence so that the GPNMB ectodomain can no longer be shed results in cessation of TSC2-null tumor growth. Finally, we demonstrate that GPNMB’s ectodomain is present at higher levels in LAM patient serum compared to healthy controls, and that ectodomain levels decrease with mTORC1 inhibition, making it a potential LAM biomarker. Presentation: 6/3/2024

7908 GPNMB Promotes Tumor Growth and is a Biomarker for Lymphangioleiomyomatosis (LAM)

Abstract Disclosure: E. Gibbons: None. M. Taya: None. H. Wu: None. S. Lopa: None. J. Moss: None. E.P. Henske: None. F.X. McCormack: None. S.R. Hammes: None. Lymphangioleiomyomatosis (LAM) is a rare, progressive cystic lung disease affecting almost exclusively female-sexed individuals. The cysts represent regions of lung destruction caused by smooth muscle tumors containing mutations in one of the two tuberous sclerosis (TSC) genes. mTORC1 inhibition slows but does not stop LAM advancement. Furthermore, monitoring disease progression is hindered by insufficient biomarkers. Therefore, new treatment options and biomarkers are needed. LAM cells express melanocytic markers, including Glycoprotein Non-Metastatic Melanoma Protein B (GPNMB). The function of GPNMB in LAM is currently unknown; however, GPNMB’s unique cell surface expression on tumor versus benign cells makes GPNMB a potential therapeutic target, and persistent release of its extracellular ectodomain suggests potential as a serum biomarker. Here we establish that GPNMB regulates TSC2-null tumor cell invasion as well as TSC2-null xenograft tumor growth, and that GPNMB expression is dependent on mTORC1 signaling. Further, we show that GPNMB’s ectodomain is released from the cell surface of TSC2-null cells by ADAM10 and 17 proteases, and we identify the protease target sequence on GPNMB. In fact, mutating this cleavage sequence so that the GPNMB ectodomain can no longer be shed results in cessation of TSC2-null tumor growth. Finally, we demonstrate that GPNMB’s ectodomain is present at higher levels in LAM patient serum compared to healthy controls, and that ectodomain levels decrease with mTORC1 inhibition, making it a potential LAM biomarker. Presentation: 6/3/2024

9308 GPNMB Promotes Tumor Growth And Is A Biomarker For Lymphangioleiomyomatosis (LAM)

Abstract Disclosure: E. Gibbons: None. M. Taya: None. H. Wu: None. S. Lopa: None. J. Moss: None. E.P. Henske: None. F.X. McCormack: None. S.R. Hammes: None. Lymphangioleiomyomatosis (LAM) is a rare, progressive cystic lung disease affecting almost exclusively female-sexed individuals. The cysts represent regions of lung destruction caused by smooth muscle tumors containing mutations in one of the two tuberous sclerosis (TSC) genes. mTORC1 inhibition slows but does not stop LAM advancement. Furthermore, monitoring disease progression is hindered by insufficient biomarkers. Therefore, new treatment options and biomarkers are needed. LAM cells express melanocytic markers, including Glycoprotein Non-Metastatic Melanoma Protein B (GPNMB). The function of GPNMB in LAM is currently unknown; however, GPNMB’s unique cell surface expression on tumor versus benign cells makes GPNMB a potential therapeutic target, and persistent release of its extracellular ectodomain suggests potential as a serum biomarker. Here we establish that GPNMB regulates TSC2-null tumor cell invasion as well as TSC2-null xenograft tumor growth, and that GPNMB expression is dependent on mTORC1 signaling. Further, we show that GPNMB’s ectodomain is released from the cell surface of TSC2-null cells by ADAM10 and 17 proteases, and we identify the protease target sequence on GPNMB. In fact, mutating this cleavage sequence so that the GPNMB ectodomain can no longer be shed results in cessation of TSC2-null tumor growth. Finally, we demonstrate that GPNMB’s ectodomain is present at higher levels in LAM patient serum compared to healthy controls, and that ectodomain levels decrease with mTORC1 inhibition, making it a potential LAM biomarker. Presentation: 6/3/2024