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Muscle transcriptomics of alpha-sarcoglycanopathy highlights inflammatory pathways driving disease
No full textMuscular dystrophies are a heterogeneous group of genetic disorders associated with an aberrant inflammatory response, that contributes to disease progression impairing regeneration and inducing fibrosis. Sarcoglycanopathies are recessively inherited limb-girdle muscular dystrophies (LGMDRs), in which the role of inflammation and its association with disease severity remains poorly understood, particularly in alpha-sarcoglycanopathy (LGMDR3). This study characterizes skeletal muscle and peripheral inflammatory signatures in sixteen LGMDR3 patients and eight unaffected individuals through bulk RNA sequencing with additional validation in Sgca-null mice. Patients were classified into mild and severe groups based on SGCA expression in muscle biopsy. Peripheral immunophenotype was assessed via flow cytometry analysis of peripheral blood mononuclear cells (PBMC). Principal Component Analysis showed a clear separation of severe LGMDR3 from mild LGMDR3 and unaffected individuals, with the latter two groups overlapping. Unsupervised hierarchical clustering analysis of the most variable genes identified distinct gene expression profiles between severe and mild LGMDR3 samples. Severe LGMD3 showed overexpression of innate immune system and T-cell activation pathways, with higher abundance of inflammatory infiltrate, mainly monocytes, cytotoxic T and dendritic cells. Notably, severe LGMD3 was characterised by polarized monocytes predominated in mild cases. Similar inflammatory profiles were observed in Sgca-null mice. PBMC analysis revealed significantly increased CD8+, TH1 CD4+ lymphocytes and activated monocytes in LGMDR3 patients compared to controls. Severe LGMDR3 patients additionally showed overexpression of genes governing fibrosis and muscle tissue regeneration and exhibited clustering pattern similar to Duchenne Muscular Dystrophy patients. In conclusion, this study represents the first comprehensive characterization of LGMDR3 immunological profiles and demonstrated that inflammation plays a significant role in severe disease pathogenesis. The distinct immune signatures separating severe from mild cases provide a foundation for developing targeted anti-inflammatory therapies that may benefit for severe LGMDR3 patients with severe phenotype
Cellular dynamics and epidermal specialization during Arabidopsis floral development at single-cell resolution
No full textCellular specialization underlies the functional diversification of floral organs, yet the regulatory networks driving epidermal differentiation remain poorly understood. Here, we constructed a single-nucleus transcriptomic atlas of developing Arabidopsis thaliana flowers by profiling over 70,000 nuclei. For annotation of single-cell identities and differentiation status, we additionally generated tissue- and stage-specific transcriptomic datasets using nine fluorescent marker lines spanning four floral developmental stages. Guided by this integrative approach, we focused specifically on the floral epidermis at single-cell resolution and resolved 22 transcriptionally distinct epidermal cell populations. Gene regulatory network analyses identified key transcription factors essential for epidermal differentiation, highlighting MYB16 as a central regulator within the petal epidermis. Developmental trajectory and chromatinbinding analyses demonstrated that MYB16 dynamically orchestrates gene expression programs involved in epidermal identity establishment, cuticle biosynthesis, and stress resilience. Moreover, we demonstrate MYB16 interacts with DRMY1, a regulator of organ growth robustness. Complementation assays confirmed the non-redundant role of MYB16 in epidermal cell fate specification, distinct from other MYB transcription factors. This study provides a comprehensive cellular and regulatory framework for floral epidermal specialization, advancing our understanding of how temporal transcriptional dynamics integrate with spatial cell fate decisions during flower development
AI-powered spatial cell phenomics enhances risk stratification in non-small cell lung cancer
Get PDFRisk stratification remains a critical challenge in non-small cell lung cancer patients for optimal therapy selection. In this study, we develop an artificial intelligence-powered spatial cellomics approach that combines histology, multiplex immunofluorescence imaging and multimodal machine learning to characterize the complex cellular relationships of 43 cell phenotypes in the tumor microenvironment in a real-world retrospective cohort of 1168 non-small cell lung cancer patients from two large German cancer centers. The model identifies cell niches associated with survival and achieves a 14% and 47% improvement in risk stratification in the two main non-small cell lung cancer subtypes, lung adenocarcinoma and squamous cell carcinoma, respectively, combining niche patterns with conventional cancer staging. Our results show that complex immune cell niche patterns identify potentially undertreated high-risk patients qualifying for adjuvant therapy. Our approach highlights the potential of artificial intelligence powered multiplex imaging analyses to better understand the contribution of the tumor microenvironment to cancer progression and to improve risk stratification and treatment selection in non-small cell lung cancer
Targeting formyl peptide receptor 1 reduces brain inflammation and neurodegeneration
No full textMultiple sclerosis (MS) progresses through brain region–specific inflammation and degeneration, with poorly defined mechanisms. In individuals with MS, we identified increased expression of formyl peptide receptor 1 (FPR1) in central nervous system (CNS)–resident microglia and CNS-infiltrating macrophages. Blood amounts of N-formylated peptides, which are endogenous agonists of FPR1, correlated with disease progression in patients with MS. In MS mouse models, signaling through FPR1 promoted microglial mitochondrial dysfunction, causing axonal loss and apoptosis. FPR1-expressing microglia sustained the clonal expansion of myelin-reactive CD4+ T cells in the CNS. A CNS-penetrating small molecule FPR1 antagonist, T0080, mitigated autoimmune responses and axonal degeneration. Our study identifies FPR1 signaling as a potential mechanism for MS progression and suggests antagonizing FPR1 as a therapeutic approach
Innovative in vivo imaging and single cell expression from tumor bulk and corpus callosum reveal glioma stem cells with unique regulatory programs
Get PDFBACKGROUND/OBJECTIVES: High-grade gliomas (HGGs), including glioblastomas, are among the most aggressive brain tumors due to their high intratumoral heterogeneity and extensive infiltration. Glioma stem-like cells (GSCs) frequently invade along white matter tracts such as the corpus callosum, but the molecular programs driving this region-specific invasion remain poorly defined. The aim of this study was to identify transcriptional signatures associated with GSC infiltration into the corpus callosum. METHODS: We established an orthotopic xenograft model by implanting fluorescently labeled human GSCs into nude mouse brains. Tumor growth and invasion patterns were assessed using tissue clearing, light-sheet fluorescence microscopy, and histological analyses. To characterize region-specific molecular profiles, we performed microfluidic-based single-cell RNA expression analysis of 48 invasion- and stemness-related genes in cells isolated from the tumor bulk (TB) and corpus callosum (CC). RESULTS: By six weeks post-implantation, GSCs displayed marked tropism for the corpus callosum, with distinct infiltration patterns captured by three-dimensional imaging. Single-cell gene expression profiling revealed significant differences in 7 of the 48 genes (14.6%) between TB- and CC-derived GSCs. These genes—NES, CCND1, GUSB, NOTCH1, E2F1, EGFR, and TGFB1—collectively defined a “corpus callosum invasion signature” (CC-Iv). CC-derived cells showed a unimodal, high-expression profile of CC-Iv genes, whereas TB cells exhibited bimodal distributions, suggesting heterogeneous transcriptional states. Importantly, higher CC-Iv expression correlated with worse survival in patients with low-grade gliomas. CONCLUSIONS: This multimodal approach identified a corpus callosum-specific invasion signature in glioma stem-like cells, revealing how local microenvironmental cues shape transcriptional reprogramming during infiltration. These findings provide new insights into the spatial heterogeneity of gliomas and highlight potential molecular targets for therapies designed to limit tumor spread through white matter tracts
Ongoing genome doubling shapes evolvability and immunity in ovarian cancer
Get PDFWhole-genome doubling (WGD) is a common feature of human cancers and is linked to tumour progression, drug resistance, and metastasis1,2,3,4,5,6. Here we examine the impact of WGD on somatic evolution and immune evasion at single-cell resolution in patient tumours. Using single-cell whole-genome sequencing, we analysed 70 high-grade serous ovarian cancer samples from 41 patients (30,260 tumour genomes) and observed near-ubiquitous evidence that WGD is an ongoing mutational process. WGD was associated with increased cell–cell diversity and higher rates of chromosomal missegregation and consequent micronucleation. We developed a mutation-based WGD timing method called doubleTime to delineate specific modes by which WGD can drive tumour evolution, including early fixation followed by considerable diversification, multiple parallel WGD events on a pre-existing background of copy-number diversity, and evolutionarily late WGD in small clones and individual cells. Furthermore, using matched single-cell RNA sequencing and high-resolution immunofluorescence microscopy, we found that inflammatory signalling and cGAS-STING pathway activation result from ongoing chromosomal instability, but this is restricted to predominantly diploid tumours (WGD-low). By contrast, predominantly WGD tumours (WGD-high), despite increased missegregation, exhibited cell-cycle dysregulation, STING1 repression, and immunosuppressive phenotypic states. Together, these findings establish WGD as an ongoing mutational process that promotes evolvability and dysregulated immunity in high-grade serous ovarian cancer
How to avoid missing a diagnosis of neuromyelitis optica spectrum disorder
No full textRecognizing neuromyelitis optica spectrum disorder (NMOSD) and differentiating NMOSD from multiple sclerosis (MS) and other disorders can be challenging yet it is extremely important to prevent misdiagnosis, defined in this review as the incorrect diagnosis of patients who truly have NMOSD, particularly in aquaporin-4-IgG (AQP4-IgG)-seronegative cases. The heterogeneity of clinical presentations and wide range of differential diagnoses often lead to missed diagnoses of NMOSD. Misapplication of the 2015 NMOSD criteria and misinterpretation of clinical and neuroradiological findings are relevant factors associated with misdiagnosis in clinical practice. Despite the presence of a specific biomarker for NMOSD (AQP4-IgG), misdiagnosis rates have been reported as high as 35%. Studies indicate that misdiagnosed patients often undergo unnecessary prolonged immunotherapy, leading to health risks and increased morbidity. Accurate definitive diagnosis is crucial as long-term outcomes and treatment approaches differ based on the correct diagnosis, and inappropriate immunotherapy can lead to disability in NMOSD patients. This review outlines factors linked to NMOSD misdiagnosis and briefly discusses strategies to reduce misdiagnosis
Systematic mapping of antibiotic cross-resistance and collateral sensitivity with chemical genetics
Get PDFBy acquiring or evolving resistance to one antibiotic, bacteria can become cross-resistant to a second antibiotic, which further limits therapeutic choices. In the opposite scenario, initial resistance leads to collateral sensitivity to a second antibiotic, which can inform cycling or combinatorial treatments. Despite their clinical relevance, our knowledge of both interactions is limited. We used published chemical genetics data of the Escherichia coli single-gene deletion library in 40 antibiotics and devised a metric that discriminates between known cross-resistance and collateral-sensitivity antibiotic interactions. Thereby we inferred 404 cases of cross-resistance and 267 of collateral-sensitivity, expanding the number of known interactions by over threefold. We further validated 64/70 inferred interactions using experimental evolution. By identifying mutants driving these interactions in chemical genetics, we demonstrated that a drug pair can exhibit both interactions depending on the resistance mechanism. Finally, we applied collateral-sensitive drug pairs in combination to reduce antibiotic-resistance development in vitro
Alzheimer’s disease risk gene SORL1 promotes receptiveness of human microglia to pro-inflammatory stimuli
Get PDFSorting protein-related receptor containing class A repeats (SORLA) is an intracellular trafficking receptor encoded by the Alzheimer's disease (AD) gene SORL1 (sortilin-related receptor 1). Recent findings argue that altered expression in microglia may underlie the genome-wide risk of AD seen with some SORL1 gene variants, however, the functional significance of the receptor in microglia remains poorly explained. Using unbiased omics and targeted functional analyses in iPSC-based human microglia, we identified a crucial role for SORLA in sensitizing microglia to pro-inflammatory stimuli. We show that SORLA acts as a sorting factor for the pattern recognition receptor CD14, directing CD14 exposure on the cell surface and priming microglia to stimulation by pro-inflammatory factors. Loss of SORLA in gene-targeted microglia impairs proper CD14 sorting and blunts pro-inflammatory responses. Our studies indicate an important role for SORLA in shaping the inflammatory brain milieu, a biological process important to local immune responses in AD
Antibiotic-perturbed microbiota and the role of probiotics
No full textThe disruptive effect of antibiotics on the composition and function of the human microbiota is well established. However, the hypothesis that probiotics can help restore the antibiotic-disrupted microbiota has been advanced, with little consideration of the strength of evidence supporting it. Some clinical data suggest that probiotics can reduce antibiotic-related side effects, including Clostridioides difficile-associated diarrhoea, but there are no data that causally link these clinical effects to microbiota protection or recovery. Substantial challenges hinder attempts to address this hypothesis, including the absence of consensus on the composition of a ‘normal’ microbiota, non-standardized and evolving microbiome measurement methods, and substantial inter-individual microbiota variation. In this Review, we explore these complexities. First, we review the known benefits and risks of antibiotics, the effect of antibiotics on the human microbiota, the resilience and adaptability of the microbiota, and how microbiota restoration might be defined and measured. Subsequently, we explore the evidence for the efficacy of probiotics in preventing disruption or aiding microbiota recovery post-antibiotic treatment. Finally, we offer insights into the current state of research and suggest directions for future research