Biology subjects

Davis, S.

Publications and source records attributed to Davis, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Spatial Tumour Tissue Distribution Dynamics of a Bicycle Peptide-MMAE Toxin Conjugate Profiled by Targeted Mass Spectrometry

A highly specific-NECTIN-4 binding bicyclic peptide covalently linked to the cytotoxin monomethyl auristatin E (MMAE) via a valine-citrulline cleavable linker (zelenectide pevedotin, BT8009) is a promising modality to treat cancer patients with solid tumours. Although the pharmacokinetics and biodistribution of zelenectide pevedotin have been well characterised, a more precise view of tumour delivery and intra-tumoural distribution of its released payload is lacking. To address this, we have developed an approach to profile the spatial tumour and healthy tissue distribution of this anti-cancer agent using laser capture microdissection coupled to targeted liquid chromatography parallel reaction monitoring (LCM-LC-PRM) mass spectrometry. This LCM-assisted spatial pharmacology workflow enables the precise isolation of specific tissue regions, followed by high-resolution analysis of MMAE distribution at sub-tissue-specific levels. By identifying and optimising MS/MS-specific fragmentation ions for accurate and sensitive detection and quantitation of MMAE released from zelenectide pevedotin within tumour tissues, we observed progressive accumulation and sustained retention of MMAE in mouse tumour tissues over a period of 24 h. Conversely, in plasma, liver and muscle tissues, MMAE levels generally declined following early exposure, although inter-animal variability was observed. LCM-based intra-tumour spatial profiling revealed heterogeneous MMAE distribution between tumour cell-rich and stroma-rich regions, with distinct temporal patterns across compartments. Together, our spatial targeted MS method provided valuable insights into zelenectide pevedotin's payload distribution dynamics in vivo, thereby enhancing our understanding of its therapeutic potential and guiding the development of next-generation Bicycle Drug Conjugate (BDC).

cancer biology↗

bioRxiv2026

A synthetic PGC1α co-activator reprograms microglial immunometabolism to preserve cone function in retinal degeneration

Retinitis pigmentosa (RP) is genetically heterogeneous, yet initiating mutations converge on primary rod degeneration followed by cone dysfunction and loss. Activated microglia are implicated in this secondary phase, but whether selective immunometabolic reprogramming of microglia preserves retinal function remains unknown. In human iPSC-derived microglia and retinal CD11b cells, PGC1 induction suppressed LPS-driven interferon signaling and cytokine release, yet Seahorse analysis and isotopologue tracing showed that energy metabolism remained altered. We therefore fused PGC1 to a multivalent p65-HSF1 module, yielding ~2.5-fold higher nuclear receptor output than native PGC1 and coordinated engagement of oxidative and anti-inflammatory programs in mouse retinal CD11b cells. Microglia-restricted expression in humanized RHOP347L mice preserved photopic responses through six months, increased retinal thickness and promoted ramified subretinal IBA1 morphology. Microglial immunometabolism thus represents a potentially genotype-independent neuroprotective target in RP, and engineered PGC1 co-activators provide a means to sustain oxidative metabolism under inflammatory pressure.

immunology↗

bioRxiv2026

A platform for deep topographic multiomic mapping of the bone marrow environment in multiple myeloma

Multiple myeloma is a genetically complex plasma cell malignancy in which profound intratumoral heterogeneity shapes disease progression and therapeutic resistance. Genomic subclones dynamically emerge and evolve under treatment pressure, yet their spatial organization within intact bone marrow remains poorly defined. We hypothesized that genetically distinct myeloma subclones occupy spatially discrete ecological niches associated with unique molecular and microenvironmental states. To test this, we here demonstrate a proof-of-concept spatial tri-omics workflow combining laser capture microdissection-based genomics and deep LC-MS/MS proteomics with single-cell spatial transcriptomics, integrated by digital co-registration of adjacent tissue sections. Applied to a myeloma bone marrow trephine, this approach enabled coordinated profiling of matched anatomical regions demonstrating that genomic, transcriptomic and proteomic profiles converged to define clone-specific microenvironmental programmes. We show that genetically distinct myeloma subclones occupy mutually exclusive regions of the same bone marrow biopsy. Remarkably, an aggressive del(17p) clone and a gain(12q) clone occupied defined anatomical territories within the same trephine-biopsied section, each clone exhibiting distinct genomic, transcriptomic, proteomic and cellular ecosystems. The del(17p) clone localized to a fibrotic, osteolytic and angiogenic niche enriched for activated stromal cells, osteoblasts, osteoclasts and immunoregulatory myeloid populations, whereas the gain(12q) clone occupied a comparatively quiescent marrow niche with limited stromal remodelling. Together, these findings demonstrate that genetically distinct myeloma subclones establish spatially and biologically discrete ecological niches through coordinated remodelling of stromal, immune and bone compartments, providing a framework for understanding clonal evolution within the bone marrow microenvironment.

cancer biology↗

bioRxiv2026

Scalable spatial DNA sequencing from archival tissue maps copy number subclones

Spatially resolved DNA sequencing holds promise due to its potential utility in understanding cancer intra-tumour heterogeneity and tumour evolution in relation to tissue architecture. However, it has so far been used to a limited extent due to technical challenges and high cost of existing methods. Hence we aimed to develop a high throughput spatial genomic assay to obtain copy number alteration (CNA) information at user-defined spatial resolution. We derived CNA profiles from ultra-low coverage whole genome sequencing at sub-millimetre resolution from archival samples using a novel method called Adaptive Resolution Multiscale Spatial DNA sequencing (ARMS DNAseq). We used it to profile CNAs from more than 766 regions (tiles) from 3 patients, covering a total area of over 300 mm2, with 1.2-2.6 million mapped reads per tile and tile sizes of 0.1-0.99mm2. Using ARMS DNAseq, we delineate tumour evolution in a spatial context, and identify more tumour subclones that were obscured or incompletely represented in bulk multi-region whole genome sequencing. Next, we show associations between tumour subclones and morphology, and prediction of subclone identity from deep learning-derived image representations. Finally, we demonstrate multi-omic integration by alignment with spatial transcriptomic data, showing subclone-specific immune cell co-occurrence as well as transcriptional programmes cutting across subclone boundaries. ARMS DNAseq converts low-throughput, region-by-region profiling into a scalable and adaptable workflow for direct spatial copy number profiling from archival tissue sections.

genomics↗

bioRxiv2026

Progranulin deficiency perturbs lipid metabolism in white matter microglia

Progranulin (PGRN) deficiency is a common hallmark in frontotemporal dementia (FTD) patients with granulin (GRN) mutations (FTD-GRN). Previous studies by our group and others have observed that reduced PGRN perturbs lysosomal function and microglial activation, which is believed to accelerate neurodegeneration in FTD-GRN patients. Lysosomal function is intrinsically linked to lipid metabolism, and evidence suggests that GRN deficiency can alter lipid profiles in the brain. Unfortunately, studies to date have focused on whole brain or cortical extracts, limiting our ability to assess cell type-dependent changes in lipid metabolism under disease conditions. Here, we employed lipidomic analysis specifically within the pontine microglia of Grn knock-out (KO) mice, a cell population that was previously linked to disease phenotypes in this model. We observed a significant reduction in the endolysosomal lipid bis(monoacylglycero)phosphate (BMP) and the lipid metabolite phosphatidylethanolamine (PE); these microglial-specific lipid alterations mirror previous whole-brain findings, suggesting that similar changes may occur across multiple cell types in the brain. We also detected a significant increase in the myelin-composing factor galactosylceramide (GalCer), which may reflect an aberrant accumulation of myelin debris within microglia that arises due to defective lysosomal clearance. Notably, lipid perturbations were exacerbated with age within Grn KO microglia, suggesting that changes in lipid metabolism are both age- and genotype-dependent in this model. Together, our results support our hypothesis that PGRN acts as a master regulator of critical microglial processes - including lysosomal function, lipid metabolism, and the regulation of myelination - in an age-dependent manner.

neuroscience↗

bioRxiv2026

A mobile optical coherence microscope for studying aquatic organisms in- and outside the laboratory

High-resolution, three-dimensional imaging of live organisms has largely depended on laboratory-bound microscopes, limiting quantitative analysis of morphology and dynamics to species that survive transport and thrive under lab-controlled conditions. Here we present a mobile optical coherence microscopy (OCM) platform that overcomes this constraint, delivering [~]2.5 {micro}m axial resolution, label-free, volumetric imaging of live aquatic organisms in both laboratory and remote field environments. We demonstrate the platform across a broad range of aquatic organisms from the lab and field, spanning multiple phyla - including cnidarians, poriferans, annelids, arthropods and echinoderms - resolving internal anatomy, tissue boundaries and organismal morphology at micrometer scale without fixation, fluorescent labeling, or specialized sample preparation. High-speed acquisition, with up to 250 kHz A-line rate and 7.7 Hz volume rate, further enabled morphodynamic imaging of live biological processes, including cellular aggregate motility, embryonic cell division, and organ-level peristaltic dynamics in intact, living animals. To demonstrate field deployability, the platform was operated during the EMBL TREC pan-European expedition, enabling on-site, label-free imaging of marine organisms and plankton immediately upon collection. By decoupling high-resolution volumetric imaging from fixed laboratory settings, mobile OCM opens a path toward field-ready quantitative morphological and dynamic phenotyping of aquatic life.

bioengineering↗

bioRxiv2026

Single-cell multi-omics analysis reveals heterogeneity and plasticity of neutrophil states in response to immunotherapies

BackgroundTumor-associated neutrophils (TANs) are emerging as functionally heterogeneous and plastic cells in the tumor microenvironment. In immunologically cold tumors, elevated neutrophil abundance correlates with poor prognosis and resistance to immune checkpoint inhibition (ICI). Whether distinct anti-tumoral neutrophil states can be induced by different immunotherapies and how they relate to treatment efficacy remains unclear. MethodsUsing the syngeneic MOC2-huEGFR (M2h) mouse model of head and neck squamous cell cancer (HNSCC), we treated tumor-bearing mice with agonistic anti-CD40 monoclonal antibody (mAb) (aCD40), TNF, Cetuximab, or a combination of all three, designated Neutrophil Activating Therapy (NAT). In addition to evaluating anti-tumor efficacy, we performed single-cell multiomics RNA and protein sequencing, followed by bioinformatics analyses and flow cytometry validation. NAT-induced anti-tumor efficacy and related neutrophil states were also assessed in another cold tumor model, 9464D-GD2 neuroblastoma. Murine treatment-induced neutrophil gene signatures were then evaluated using clinical, proteomic, and transcriptomic data from HNSCC patients. ResultsFive transcriptionally distinct neutrophil states (N0-N4), including precursor state CD49d+ N4, were identified using the M2h model. N0 neutrophils (immunosuppressive/quiescent) dominated untreated tumors, but not in successful treatments. ISG+ N1 neutrophils and CCR3+ N3 neutrophils expanded by aCD40, TNF, and NAT treatment with anti-tumoral gene signatures and found more interacting with CD8+ T cells from bioinformatics analysis. N2 neutrophils reflected a recently established hypoxia-adapted state found in all treatments. ICAM1 (CD54) emerged as a marker of treatment-induced neutrophil activation, discriminating N1, N2, and N3 neutrophils from N0 neutrophils, validated by flow cytometry. In the 9464D-GD2 neuroblastoma model, NAT treatment also reduced the N0 dominance seen in untreated tumors in the HNSCC model but failed to induce anti-tumoral neutrophil states. In 23 HNSCC patients who received ICI therapy, ICAM1 protein expression in neutrophils trended toward association with responder status (TMA-level p=0.029), and ICAM1 neutrophil gene expression also trended toward association with improved overall survival in TCGA data (HR=0.75, p=0.059). ConclusionsDistinct immunotherapy-induced neutrophil states are defined by transcriptional profiles enriched in different functional pathways, associated with both anti-tumor and pro-tumor signatures. ICAM1 identifies activated neutrophils and potentially serves as a biomarker of ICI response in HNSCC, warranting further clinical validation. WHAT IS ALREADY KNOWN ON THIS TOPICNeutrophil heterogeneity has received increasing attention, with studies identifying antitumoral neutrophil populations, either at baseline or induced by treatment. Several effective treatment regimens involve an anti-CD40 agonist (aCD40) antibody, among them Neutrophil Activating Therapy (NAT), which combines aCD40, TNF, and a tumor antigen binding antibody designed to reprogram neutrophils. NAT could thus be particularly effective in cold, myeloid-rich tumors that are largely unresponsive to conventional immunotherapies such as checkpoint blockade, enacting these anti-tumoral effects through similar and different mechanisms; however, this has not been tested. WHAT THIS STUDY ADDSThis study adds a single-cell multi-omics framework for defining treatment-induced neutrophil heterogeneity in MOC2-huEGFR and 9464D-GD2 tumors, two immunologically cold models. It highlights ICAM1/CD54 and interferon-stimulated genes as markers of a dominant antitumor neutrophil state, while showing that neutrophil state composition variy across tumor models. HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE, OR POLICYThese results support the efficacy of a myeloid-modulating therapy built around aCD40 and TNF in a cold murine head and neck cancer model, and to a lesser extent in a cold murine neuroblastoma model. ICAM1/CD54 expression in neutrophils was also identified as a promising marker of antitumor activity and treatment response. More broadly, this work suggests that incorporating aCD40 and/or TNF into existing treatment regimens could improve outcomes, while ICAM1/CD54-high neutrophils may serve as a useful therapeutic readout.

cancer biology↗

bioRxiv2026

MetaHarmonizer: robust biomedical metadata harmonization and a contamination control for inflated LLM performance on public benchmarks

Public biomedical repositories hold substantial reuse potential, but inconsistent metadata routinely blocks integration across studies. Recent LLM-based harmonization approaches address scale but suffer from non-determinism, hallucinated ontology terms, and, in their highest-accuracy configurations, dependence on proprietary APIs or labeled fine-tuning data. A more fundamental concern is that LLM accuracies on widely-used public benchmarks may substantially inflate transferable capability: under a contamination-controlled evaluation protocol we developed, the apparent LLM-only advantage on the GDC schema-mapping benchmark is inverted and three out of five LLMs recovers 80-100% of GDC identifiers from zero-schema context, suggesting direct memorization. Building on this insight, we present MetaHarmonizer, an automated metadata harmonization system designed to be robust by construction: SchemaMapper aligns attribute names across schemas, and OntologyMapper standardizes values to controlled vocabularies. Both modules implement a multi-stage cascade that escalates to more resource-intensive methods only when earlier stages fall short, with all candidates grounded in pre-defined controlled vocabularies to preclude hallucinated outputs and LLMs used only as bounded preprocessing components rather than inference-time dependencies. On the GDC schema-matching benchmark, SchemaMapper with the deployment-optimized LLM-generated alias dictionary achieved 71.6% Top-1 accuracy and the higher Recall@GT than Magneto bipartite variants, recovering significantly more ground-truth mappings; with the best performing alias dictionary, it reached the highest Top-1/Top-5/Recall@GT, and also matched the best Magneto reranker (fine-tuned LLM-reranker) on MRR; and it also outperforms LLM-only performance under contamination-controlled conditions. On four EFO benchmarks, OntologyMapper achieved 77.9-95.5% Top-1 accuracy, outperforming text2term by up to 16.4 pp and direct LLM inference (against the smaller corpus) by 19.2 pp because memorization is not a viable shortcut for this task. Across both modules, calibrated confidence scores separate correct from incorrect predictions (AUC 0.73-0.94), enabling principled human-in-the-loop triage. Inference is fully local, deterministic, and computationally efficient - seconds on schema mapping and under a minute for ontology mapping of up to [~]7,000 terms against the pre-indexed 33,230-term corpus. Released as a Python package with a domain-agnostic architecture, MetaHarmonizer provides a scalable foundation for improving the FAIRness of biomedical data and enabling cross-study integration, alongside an evaluation methodology applicable to any LLM-augmented bioinformatics benchmark built on public benchmarks.

bioinformatics↗

bioRxiv2026

Spatially patterned, spectral single-molecule microscopy

Multicolour and spectrally resolved single-molecule microscopy can reveal molecular interactions, nanoscale environments and dynamics, but usually depends on experimentally complex detection architectures based on beam splitting, spectral dispersion or engineered point spread functions. Here we show that spatially patterned detectors offer a conceptually simpler route to spectral single-molecule imaging. By replacing a conventional monochrome camera with a commercially available colour CMOS detector and fitting the raw detector response directly, we recover both molecular position and spectral fingerprint from a single image without optical splitting, channel registration or demosaicing. We term this approach spatial spectral single-molecule microscopy, or S3M. We show that S3M retains single-molecule sensitivity across the visible spectrum, enables robust spectral multiplexing, and supports applications spanning multicolour single-molecule tracking, single-molecule F&oumlrster resonance energy transfer, multicolour localisation microscopy and spectral PAINT. Although spatial patterning necessarily trades photon efficiency for spectral information, current low noise detectors already provide sufficient performance for a broad range of experiments. Spatially patterned detection therefore establishes a widely accessible strategy for simplified spectral microscopy and single-molecule spectroscopy, and points towards a new class of detector informed photonic measurement schemes for nanoscale imaging.

biophysics↗

bioRxiv2026

TimeTraits: extracting functional traits from biological time-series in R

SummaryTimeTraits provides a series of functions to enable the extraction of parameters from time series data using Functional Data Analysis methods. We demonstrate its utility in dissecting the changes in curve shape of a circadian clock bioluminescence marker, following a photoperiod shift in wildtype and phyB Arabidopsis. Availability and ImplementationTimeTraits is available in CRAN: https://cran.r-project.org/web/packages/TimeTraits/readme/README.html

plant biology↗

bioRxiv2026

SoftHybrid: A Hybrid Imputation Algorithm Optimised for Single-Cell Proteomics Data

Missing values (MVs) remain a significant barrier to reliable proteomics analysis, particularly in single-cell proteomics, where small amounts of starting material and limits in detection drive Missing-Not-At-Random (MNAR) sparsity. Existing imputation methods typically target either Missing-At-Random (MAR) or MNAR mechanisms, resulting in a trade-off between replicate consistency and preservation of biological variation, and are largely designed for bulk data. Here, we introduce SoftHybrid, a data-driven imputation framework that jointly models missingness and protein abundance to estimate the probability of MNAR, enabling continuous weighting between MAR- and MNAR-oriented strategies. SoftHybrid requires no external priors (cell type labels, group annotations, predefined missingness assumptions, etc.), enabling fully unsupervised applications. Across ground truth benchmarks and real single-cell proteomics datasets, SoftHybrid outperforms existing methods at low input and matches or exceeds their performance at the mini-bulk level. By preserving proteomic structure and abundance accuracy, it enhances the recovery of biologically meaningful signals. SoftHybrid is implemented as an R package and is freely available on GitHub.

bioinformatics↗

bioRxiv2025

Large-scale Manual Curation and Harmonization of Metadata from Metagenomic and Cancer Genomic Repositories: Challenges and Solutions

Public omics repositories contain vast amounts of valuable data, but their metadata suffers from extreme heterogeneity, unstandardized terminologies, and quality issues that severely limit data reusability and cross-study integration. While prospective metadata standards exist, the majority of published omics data remain in non-standardized formats requiring retrospective curation. We performed comprehensive manual curation and harmonization of clinical metadata from 212,027 samples across 468 studies in two major repositories: curatedMetagenomicData (93 studies, 22,588 samples) and cBioPortal (375 studies, 189,438 samples). Through systematic ontology mapping, we consolidated redundant, dispersed information into much fewer harmonized columns, reduced unique values, and increased the completeness of major attributes. This curation process revealed common metadata quality issues, including typos, inconsistent terminologies, misplaced values, conflicting annotations, and inappropriately merged information across attributes. We document the challenges, decisions, and solutions encountered during large-scale metadata harmonization across two distinct omics domains. The harmonized metadata, accessible through the OmicsMLRepoR Bioconductor package, enables repository-wide queries and cross-study analyses previously challenging with heterogeneous metadata. Our experience provides practical guidance for similar curation efforts and demonstrates the value of investing in retrospective metadata improvement for existing public omics resources.

bioinformatics↗

bioRxiv2025

Generating Hybrid Proteins with the MSA-Transformer

Protein superfamilies display extensive sequence and functional divergence, providing a rich landscape for engineering functionally enhanced variants. We present a stochastic, iterative framework that leverages the MSA-Transformer to generate intermediate sequences between a homologous pair of user-specified "source" and "target" proteins in sequence space. Sequence sites to "mask" is either selected by embedding-based dissimilarity or by row-attention information, while beam search concurrently explores multiple mutational pathways. Pre-trained sparse autoencoders combined with sequence and structural analyses are used to trace the inheritance and exchange of features across the "mutational pathway", revealing "hybrid" sequences that integrate properties of both source and target proteins. Applied across diverse protein families, the framework produces sequences that occupy biologically meaningful regions of sequence space and achieve higher consistency and plausibility scores than random baselines according to in silico metrics. In the B1/B2 metallo-{beta}-lactamase family, hybrids largely retain their core fold recombining structural and active-site motifs from both subclasses, demonstrating the models capacity to preserve catalytic features while exploring novel structural permutations. Code availabilityThe implementation is available via GitHub at https://github.com/santule/protmixy.

bioinformatics↗

bioRxiv2025

Characterization of Endogenous and Epitope-Tagged Ubiquitin Expression and Ubiquitination Patterns at Drosophila Neuromuscular Junctions

Ubiquitination is a highly regulated post-translational modification that controls protein stability, activity, localization, and interactions. Disruption of this process contributes to a broad range of human diseases, including cancer, neurodegeneration, and immune dysfunction. The genetic model organism Drosophila melanogaster offers powerful tools to study ubiquitination in vivo, where versatile systems such as GAL4/UAS, Split-GAL4, GeneSwitch, and MARCM can be combined with imaging and biochemical approaches to achieve precise spatial and temporal analyses. To fully exploit these advantages, experimental designs often require epitope-tagged UAS-Ubiquitin transgenes--both modified and unmodified--that accurately recapitulate the behavior of endogenous Ubiquitin. Here, we report the generation and validation of a panel of epitope-tagged UAS-Ubiquitin transgenes. We first characterize the endogenous ubiquitination pattern at larval neuromuscular junctions (NMJs), then compare that with transgenically expressed Ubiquitin in muscle. Our analysis showed that transgenic His-Myc-, HA-, and His-Biotin-tagged Ubiquitin proteins accurately reproduce endogenous postsynaptic ubiquitination patterns. These validated transgenes provide versatile resources for investigating ubiquitination dynamics across diverse cellular and developmental contexts.

genetics↗

bioRxiv2025

Matrix metalloproteinase-3 promotes arteriovenous fistula failure by regulating FAK-AKT signaling

Objective- Surgically created upper extremity arteriovenous fistulae (AVF) are the preferred vascular access for patients requiring dialysis. It is estimated, however, that 50% of AVF fail within one year due to aggressive neointimal hyperplasia, which significantly increases morbidity and mortality. Matrix metalloproteinase-3 (MMP-3), also known as stromelysin-1, is a member of the metalloproteinase family that plays a critical role in the pathogenesis of many human disorders by degrading extracellular matrix and regulating molecular signaling pathways. The role of MMP- 3 in AVF neointimal failure has not been explored. Approach and Results- We observed that MMP-3 was induced in a time-dependent fashion by fetal bovine serum (FBS) and the growth factor PDGF-BB in cultured venous SMC. MMP-3 was also highly expressed in the neointimal SMCs of the outflow veins and the juxta-anastomotic area in an AVF mouse model, as well as in human AVF specimens. Knockdown of MMP-3 significantly suppressed venous SMC proliferation, whereas overexpression of MMP-3 facilitated cell growth in vitro. Importantly, deficiency of global and SMC-specific MMP-3 significantly reduced neointimal hyperplasia and improved patency after AVF creation. Mechanistic studies showed that MMP-3-mediated SMC proliferation and AVF neointimal hyperplasia were regulated via the FAK-AKT signaling pathway. Conclusions- These data suggest that MMP-3 is a key mediator of AVF neointimal failure. Targeting local MMP-3 activity may be a novel therapeutic strategy to prevent AVF neointimal failure and improve outcomes in patients requiring hemodialysis.

cell biology↗

bioRxiv2025

A pivotal role for Wnt antagonists in constraining Wnt activity to promote digit joint specification.

Bmps and Wnts play opposing roles in several contexts during chondrogenesis and joint formation. Using genetic and genomic approaches, we found instead that canonical Wnts can cooperate with Bmps to enhance pSmad1/5 activity and initiate chondrogenic commitment in digit tip progenitors. 5Hoxd{Delta}/{Delta} mutant digits are characterized by elevated Bmp and pSmad1/5 activity and subsequent joint loss. We show that expressing stabilized {beta}catenin ({beta}catCA) in interdigit mesenchyme rescues 5Hoxd{Delta}/{Delta} digit joint loss non-autonomously, by inducing secreted Wnt antagonists and normalizing digit tip pSmad1/5 levels. Indeed, genetic removal of Dkk2 in 5Hoxd{Delta}/{Delta} prevented joint rescue by {beta}catCA. Furthermore, elevating Wnt activity with Gsk3{beta} antagonists in limb bud culture stabilized pSmad1/5 levels and enhanced Bmp activity. Elevated pSmad1/5, as seen in 5Hoxd{Delta}/{Delta}, accelerates chondrogenic commitment, impeding a switch of phalanx forming region (PFR) cells in the digit tip to interzone (joint progenitor) fate. We propose that, before progenitors transit into PFR, Wnt antagonists cooperate with Fgfs to prevent precocious pSmad1/5 accumulation by stabilizing Gsk3{beta} to promote Smad-linker phosphorylation and Smad1/5 degradation. Consequently, Wnt antagonists play a key role in modulating the pace of initial commitment of digit progenitors to chondrogenesis, together with Fgfs, and maintain mesenchymal plasticity to balance digit phalanx and joint formation.

developmental biology↗

bioRxiv2025

Chlamydia trachomatis restricts signaling through NOD2 until late in the pathogen's developmental cycle

Pathogenic chlamydial species restrict their peptidoglycan (PG) to the division septum of their replicative forms. PG is a microbe-associated molecular pattern (MAMP) and two of its major pattern recognition receptors in human cells are nucleotide-binding oligomerization domain-containing proteins 1 and 2 (NOD1 and NOD2, respectively). It has been proposed that this unique morphological feature is evidence of pathoadaptation by the microbe, permitting PG-dependent cell division while also reducing the bacteriums recognition by innate immune receptors. Chlamydia trachomatis-infected cells activate NOD1 signaling within 8-12 hours of exposure to the bacterium, roughly coinciding with the microbes transition from its infectious to replicative forms. Here we report that, unlike NOD1 signaling, Chlamydia-induced NOD2 signaling does not occur until later in the pathogens developmental cycle. Both C. trachomatis and the related murine pathogen Chlamydia muridarum signal late in infection in HEK293 reporter cell lines expressing either human or murine-derived NOD2 receptors. NOD2 signaling can be modulated by disruption of the chlamydial amidase enzyme, AmiACT, interrupting the microbes developmental cycle, and treatment with inhibitors of lipooligosaccharide or peptidoglycan biosynthesis / assembly. These results mirror prior observations with Chlamydia-induced TLR9 signaling, leading us to hypothesize that Chlamydia-induced NOD2 signaling results from lytic events that occur sporadically during the transition between the pathogens developmental forms. Given our finding that pre-treating cells with NOD2-stimulatory ligands reduces chlamydial inclusion size and delays the developmental cycle, we hypothesize that the microbe preferentially degrades its PG during development to reduce the generation of NOD2 ligands.

microbiology↗

bioRxiv2025

Ophiobolin A selectively alters mitochondria, metabolism and redox biology in breast cancer and mammary epithelial cells which have undergone epithelial to mesenchymal transition

Breast cancer progression is facilitated by the epithelial to mesenchymal transition (EMT), generating cancer cells with enhanced metastatic capacity and resistance to chemotherapeutics. EMT is known to impart changes in metabolic pathways and mitochondrial function. Here, we show a natural product possesses EMT-specific cytotoxic activity via alterations in metabolic and mitochondrial functions. The fungus-derived sesterterpenoid, ophiobolin A (OpA), possesses nanomolar cytotoxic activity and a high therapeutic index, although its target and mechanism of action remain unknown. Here, we utilized a model of mammary epithelial cells and breast cancer cell lines with and without EMT features to characterize the mechanism of selectivity towards EMT(+) cells by OpA and to identify novel targets for the treatment of EMT-enriched breast cancer. Proteins interacting with OpA in EMT(+) cells were identified through proteomic studies. We utilized trans-mitochondrial cybrids to determine that mitochondria mediate sensitivity to OpA. Furthermore, we report effects on glycolysis, oxidative metabolism, and disruption of metabolite abundance in the TCA cycle. Alterations to mitochondrial iron concentrations and glutathione production, mediated partly by OpA engagement with the metabolic proteins CISD3 and SLC25A40, were also detected in EMT(+) cells. Antioxidant mechanisms are activated by OpA in EMT(+) cells via the NRF2-ARE pathway, verified by decreased cytotoxicity in EMT(+) cells pretreated with the NRF2 activator CDDO. Collectively, we conclude that OpA selectivity toward EMT is mediated by the mitochondria, and at sub-cytotoxic levels, generates a metabolic shift leading to cell death countered by antioxidant mechanisms.

cancer biology↗