Biology subjects

Weldon, K. C.

Publications and source records attributed to Weldon, K. C..

9 recordsLinked to original sources

bioRxiv2026

A Dynamic Stem Cell State Links Environmental Cues to Skeletal and Regenerative Fates

Stem cells faithfully generate tissue architecture during development, yet how their identity and regenerative output are reshaped as anatomical niches mature and environmental signals change with aging and injury remains poorly understood. Rare skeletal stem cells (SSCs) across diverse skeletal sites are defined by combinations of cell-surface markers, precluding their genetic interrogation in vivo. Here, using spatially informed single cell transcriptomics, we identify Pannexin-3 (Panx3) to mark a dynamic functional state within bona fide SSCs and establish Panx3-CreERT2 mice for its longitudinal interrogation. Panx3 SSCs exhibit long-term clonal persistence, self-renewal and multipotency, whereas Panx3- SSCs can acquire this state. Successive SSC cohorts engage the Panx3 state during skeletal development, osteoanabolic stimulation expands pre-existing Panx3 SSC clones and injury induces it locally in previously unlabeled progenitors. Thus, anatomically distinct progenitors can converge on a common stem cell state in response to different environmental inputs. Three-dimensional reconstruction of chondrogenic niches further identifies signals that redirect Panx3-lineage cells towards stable cartilage, enabling durable regeneration in aged and osteoarthritic joints and with human SSCs. These findings establish anatomical origin, stem cell state and lineage fate as separable dimensions of stem cell identity and provide genetic access for interrogating and directing endogenous SSC function.

cell biology↗

bioRxiv2026

Bioorthogonal Tethering of FGF18 to Annealed Microgel Scaffolds Enhances Cartilage Repair

Articular cartilage damage often progresses to osteoarthritis (OA), a degenerative joint disease characterized by chronic pain, limited mobility, and reduced quality of life. Tissue engineering approaches using poly (ethylene glycol) (PEG)-based hydrogels offer tunable mechanical properties and bioactive functionalization, yet the influence of surface charge on cartilage regeneration remains underexplored. Moreover, recombinant fibroblast growth factor 18 (FGF18) has successfully improved cartilage tissue thickness in clinical trials, but required high dosages and recurring injections may limit compliance. Here, we developed a granular microgel-based platform with bioorthogonally tethered FGF18 to evaluate the interplay of microgel surface charge and growth factor presentation on chondrogenesis. Azide groups were incorporated onto the microgel surfaces to enable site specific FGF18 conjugation across microgel scaffolds with distinct surface charges. When seeded with mesenchymal stromal cells, microgel scaffolds functionalized with FGF18 outperformed their unmodified counterparts, evidenced by higher GAG content, collagen content, and compressive modulus. In a murine microfracture model, anionic and zwitterionic microgel scaffolds tethered with FGF18 increased cartilage regeneration compared to nonionic microgels. We detected increased collagen II content within defects treated with tethered FGF18 microgel scaffolds. This work demonstrates the role of surface charge and growth factor presentation in directing cell behavior and tissue repair, advancing the design of biomaterials for cartilage regeneration. HIGHLIGHTSO_LICovalent tethering of FGF18 to microgel surface enables localized bioactivity C_LIO_LIFGF18 tethered microgel scaffolds enhance extracellular matrix deposition and chondrogenic differentiation of murine mesenchymal stromal cells in vitro C_LIO_LILocalized FGF18 presentation improves cartilage tissue formation and mechanical properties in vivo, with anionic and zwitterionic microgel scaffolds outperforming nonionic scaffolds C_LIO_LIFGF18 presentation is a more potent stimulus than microgel surface charge for cartilage regeneration C_LI

bioengineering↗

bioRxiv2025

Basigin Links Altered Skeletal Stem Cell Lineage Dynamics with Glucocorticoid-induced Bone Loss and Impaired Angiogenesis

Glucocorticoid (GC) induced osteoporosis (GIOP) and osteonecrosis remain a significant health issue with few approved therapies that can treat the bone loss and dysfunction of skeletal vasculature. Therefore, we aimed to investigate the cellular and molecular processes by which GCs affect osteogenesis and angiogenesis, as well as how treatment with parathyroid hormone (hPTH 1-34) modifies these effects in a mouse model of GIOP. GC treatment reduced bone mass through decreased bone formation by skeletal stem cells (SSCs) while also increasing osteoclast mediated resorption. Concomitantly, endothelial cells were increased in numbers but displayed distorted phenotypical features. However, hPTH treatment reversed GC induced changes in osteogenesis and angiogenesis to control levels. Transplantation studies of SSCs combined with molecular analysis by single cell RNA-sequencing and functional testing of primary human cells tied GC-induced skeletal changes to altered stem and progenitor cell differentiation dynamics. This in turn perpetuated reduced osteogenesis and vascular malformation through direct SSC-endothelial crosstalk mediated at least in part by Basigin. Intriguingly, antibody-mediated blockade of Basigin during GC treatment prevented detrimental bone loss. In addition, when administered to aged mice, anti-Basigin therapy reinstated bone remodeling to significantly improve bone mass independent of sex. These findings, while helping to explain the cellular and molecular basis of how hPTH treatment can mitigate GC induced bone loss, provide new therapeutic vantage points for GIOP and other conditions associated with bone loss.

cell biology↗

bioRxiv2024

Metabolomic Profiling Reveals Potential of Fatty Acids as Regulators of Stem-like Exhausted CD8 T Cells During Chronic Viral Infection

Chronic infections drive a CD8 T cell program termed T cell exhaustion, characterized by reduced effector functions. While cell-intrinsic mechanisms underlying CD8 T cell exhaustion have been extensively studied, the impact of the metabolic environment in which exhausted CD8 T cells (Tex) operate remains less clear. Using untargeted metabolomics and the murine lymphocytic choriomeningitis virus infection model we investigated systemic metabolite changes early and late following acute versus chronic viral infections. We identified distinct short-term and persistent metabolite shifts, with the most significant differences occurring transiently during the acute phase of the sustained infection. This included nutrient changes that were independent of viral loads and partially associated with CD8 T cell-induced anorexia and lipolysis. One remarkable observation was the elevation of medium- and long-chain fatty acid (FA) and acylcarnitines during the early phase after chronic infection. During this time, virus-specific CD8 T cells from chronically infected mice exhibited increased lipid accumulation and uptake compared to their counterparts from acute infection, particularly stem-like Tex (TexSTEM), a subset that generates effector-like TexINT which directly limit viral replication. Notably, only TexSTEM increased oxidative metabolism and ATP production upon FA exposure. Consistently, short-term reintroduction of FA during late chronic infection exclusively improved TexSTEM mitochondrial fitness, percentages and numbers. This treatment, however, also reduced TexINT, resulting in compromised viral control. Our study offers a valuable resource for investigating the role of specific metabolites in regulating immune responses during acute and chronic viral infections and highlights the potential of long-chain FA to influence TexSTEM and viral control during a protracted infection. SignificanceThis study examines systemic metabolite changes during acute and chronic viral infections. Notably, we identified an early, transient nutrient shift in chronic infection, marked by an increase in medium- and long-chain fatty acid related species. Concomitantly, a virus-specific stem-like T cell population, essential for maintaining other T cells, displayed high lipid avidity and was capable of metabolizing exogenous fatty acids. Administering fatty acids late in chronic infection, when endogenous lipid levels had normalized, expanded this stem-like T cell population and enhanced their mitochondrial fitness. These findings highlight the potential role of fatty acids in regulating stem-like T cells in chronic settings and offer a valuable resource for studying other metabolic signatures in both acute and persistent infections.

immunology↗

bioRxiv2024

Urinary Metabolomic Profile is Minimally Impacted by Common Storage Conditions and Additives

Metabolomics reflects the molecular communications within a biological system. Urine can be obtained non-invasively and is rich in metabolites that are potential biomarkers for human health and disease. The optimal urine storage conditions for metabolomic analysis are unknown. We measured the impact of common storage conditions and the presence of a DNA-stabilizer, AssayAssure(R) (Thermo Scientific), on metabolite content of voided human urine. Urinary metabolite composition was not altered across storage conditions. Although addition of AssayAssure(R) significantly alters metabolic profile by adduct addition, this does not preclude the identification of parent metabolites or overshadow biological differences. These data suggest biobanked urine stored in any of the tested conditions for metabolomic studies may be considered for metabolomic analysis.

molecular biology↗

bioRxiv2022

Open Access Repository-Scale Propagated Nearest Neighbor Suspect Spectral Library for Untargeted Metabolomics

Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of public MS/MS spectra. Annotations were propagated based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimers brain phenotype. The nearest neighbor suspect spectral library is openly available through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

bioinformatics↗

bioRxiv2021

Non-Invasive Skin Sampling Detects Systemically Administered Drugs in Humans

Clinical testing typically relies on invasive blood draws and biopsies. Alternative methods of sample collection are continually being developed to improve patient experience; swabbing the skin is one of the least invasive sampling methods possible. To show that skin swabs in combination with untargeted mass spectrometry (metabolomics) can be used for non-invasive monitoring of an oral drug, we report the kinetics and metabolism of diphenhydramine in healthy volunteers (n=10) over the course of 24 hours in blood and three regions of the skin. Diphenhydramine and its metabolites were observed on the skin after peak plasma levels, varying by compound and skin location, and is an illustrative example of how systemically administered molecules can be detected on the skin surface. The observation of diphenhydramine directly from the skin supports the hypothesis that both parent drug and metabolites can be qualitatively measured from a simple non-invasive swab of the skin surface. The mechanism of the drug and metabolites pathway to the skins surface remains unknown.

pharmacology and toxicology↗

bioRxiv2019

Protocol for Community-created Public MS/MS Reference Library Within the GNPS Infrastructure

RationaleA major hurdle in identifying chemicals in mass spectrometry experiments is the availability of MS/MS reference spectra in public databases. Currently, scientists purchase databases or use public databases such as GNPS. The MSMS-Chooser workflow empowers the creation of MS/MS reference spectra directly in the GNPS infrastructure.\n\nMethodsAn MSMS-Chooser sample template was completed with the required information and sequence tables were generated programmatically. Standards in methanol-water (1:1) solution (1 M) were placed into wells individually. An LC-MS/MS system using data-dependent acquisition in positive and negative modes was used. Species that may be generated under typical ESI conditions are chosen. The MS/MS spectra and MSMS-Chooser sample template were subsequently uploaded to MSMS-Chooser in GNPS for automatic MS/MS spectral annotation.\n\nResultsData acquisition quickly and effectively collected MS/MS spectra. MSMS-Chooser was able to accurately annotate 99.2% of the manually validated MS/MS scans that were generated from the chemical standards. The output of MSMS-Chooser includes a table ready for inclusion in the GNPS library (after inspection) as well as the ability to directly launch searches via MASST. Altogether, the data acquisition, processing, and upload to GNPS took ~2 hours for our proof-of-concept results.\n\nConclusionsThe MSMS-Chooser workflow enables the rapid data acquisition, analysis, and annotation of chemical standards, and uploads the MS/MS spectra to community-driven GNPS. MSMS-Chooser democratizes the creation of MS/MS reference spectra in GNPS which will improve annotation and strengthen the tools which use the annotation information.

bioinformatics↗

bioRxiv2019

Metabolome-informed microbiome analysis refines metadata classifications and reveals unexpected medication transfer in captive cheetahs

Structured AbstractEven high-quality collection and reporting of study metadata in microbiome studies can lead to various forms of inadvertently missing or mischaracterized information that can alter the interpretation or outcome of the studies, especially with non-model organisms. Metabolomic profiling of fecal microbiome samples can provide empirical insight into unanticipated confounding factors that are not possible to obtain even from detailed care records. We illustrate this point using data from cheetahs from the San Diego Zoo Safari Park. The metabolomic characterization indicated that one cheetah had to be moved from the non-antibiotic-exposed to the antibiotic-exposed group. The detection of the antibiotic in this second cheetah was likely due to grooming interactions with the cheetah that was administered antibiotics. Similarly, because transit time for stool is variable, early fecal samples within the first few days of antibiotic prescription do not all contain detectable antibiotics. Therefore, the microbiome is not affected by the antibiotics at those time points. These insights significantly altered the way the samples were grouped for analysis (antibiotic vs no antibiotic), and the subsequent understanding of the effect of the antibiotics on the cheetah microbiome. Metabolomics also revealed information about numerous other medications, and provided unexpected dietary insights that in turn improved our understanding of the molecular patterns on the impact on the community microbial structure. These results suggest that untargeted metabolomics data provide empirical evidence to correct records of non-model organisms in captivity, although we also expect these methods will be appropriate for experimental conditions typical in human studies.\n\nImportanceMetabolome-informed analyses can enhance omics studies by enabling the correct partitioning of samples by identifying hidden confounders inadvertently misrepresented or omitted from carefully curated metadata. We demonstrate the utility of metabolomics in a study characterizing the microbiome associated with liver disease in cheetahs. Metabolome-informed reinterpretation of metagenome and metabolome profiles factored in an unexpected transfer of antibiotics preventing misinterpretation of the data. Our work suggests that untargeted metabolomics can be used to verify, augment, and correct sample metadata to support improved grouping of sample data for microbiome analyses, here for non-model organisms in captivity. However, the techniques also suggest a path forward for correcting clinical information in human studies to enable higher-precision analyses.

systems biology↗