Biology subjects

Williams, A. S.

Publications and source records attributed to Williams, A. S..

5 recordsLinked to original sources

bioRxiv2026

A high-resolution mass spectrometry-based method for quantifying insulin-stimulated glucose uptake in mice following an intraperitoneal injection of tracer

ObjectiveA catheter-free, non-radiolabeled method that permits in vivo measurement of tissue-specific glucose uptake does not exist. To address this gap, we sought to develop and validate a new, higher throughput mass spectrometry (MS)-based method that combines an injection of insulin with a non-radiolabeled glucose tracer, 2-fluoro-2-deoxyglucose (2FDG), to determine insulin-stimulated tissue-specific glucose clearance in conscious, unrestrained mice. MethodsInjections of saline or insulin with 2FDG were coupled with LC-Q Exactive Hybrid Quadrupole-Orbitrap (LC) MS-based measures of plasma 2FDG and tissue (2-fluoro-2-deoxyglucose-6-phosphate) 2FDGP to determine glucose clearance in mice under several different conditions. ResultsThe newly developed method was first applied to a dose response experiment in mice. Next, the ability of this method to quantify changes in glucose clearance in response to an insulin stimulus was assessed, and glucose clearance was compared between chow and high fat fed mice. Results from these studies showed that insulin-stimulated skeletal muscle and heart glucose clearance can be estimated following a bolus injection of tracer, and these fluxes are blunted in diet-induced obese mice. The broad applicability of this approach was then demonstrated by assessing glucose clearance in a mouse model with anticipated changes in insulin-stimulated skeletal muscle glucose metabolism. ConclusionsThe results validated a new LC-MS method to quantify insulin-stimulated tissue-specific glucose clearance in vivo without the use of catheters or radiolabeled tracers. The method offers great potential because it is designed for application to pre-clinical studies seeking high throughput tests and/or assays that can be coupled with discovery technologies such as genomics, proteomics and metabolomics. HIGHLIGHTSO_LIIn vivo glucose clearance can be estimated by a new non-radiolabeled method. C_LIO_LIThe plasma tracer to tracee ratio is required to determine tissue tracer phosphorylation. C_LIO_LIMeasures of plasma glucose and tracer kinetics are critical for data interpretation. C_LIO_LIThe new method can be combined with omics technologies such as metabolomics. C_LI

physiology↗

bioRxiv2025

Discrete cytokine signaling networks instruct distinctsynovial pathotypes in inflammatory arthritis

Patients with rheumatoid arthritis (RA) display distinct patterns of synovitis. To define the inflammatory mechanisms driving this heterogeneity, we analyzed the inflamed synovium of wild-type (WT), Il6ra-/-, and Il27ra-/- mice with antigen-induced arthritis (AIA). Remarkably, each strain developed a joint pathology mirroring a major RA synovial pathotype: myeloid-rich (WT), fibroblast-rich/pauci-immune (Il6ra-/-), and lymphoid-rich (Il27ra-/-) synovitis. Histology confirmed minimal immune infiltration in Il6ra-/- joints, while WT and Il27ra-/- mice exhibited prominent immune involvement, including organized synovial lymphoid-like aggregates in Il27ra-/- mice. Transcriptomic and epigenomic profiling revealed both shared and distinct regulatory programs among genotypes. Il6ra-/- mice showed increased WNT, DKK, and AMPK signaling associated with fibroblast, chondrocyte, and osteoclast activation (e.g., Adamts19, Dkk1, Ecm1). Consistent with synovial ectopic lymphoid-like structures, Il27ra-/- mice showed enrichment of lymphocyte activation (e.g., Il17a, Il22, Bhlhe40). WT mice exhibited hallmarks of MAP kinase activation. These molecular signatures parallel those of fibroblast-, lymphoid-, and myeloid-rich synovitis in RA. Defining a STAT1-STAT3 regulatory interplay influencing transcriptional decisions in WT and Il27ra-/- mice, our findings offer insights into cytokine-driven disease heterogeneity. Together, these results establish a framework for mechanism-based classification of synovitis and introduce new mouse models to study the molecular drivers of synovial pathotypes and treatment response.

pathology↗

bioRxiv2024

Ketogenesis protects against MASLD-MASH progression through fat oxidation-independent mechanisms

AbstractThe progression of metabolic-dysfunction-associated steatotic liver disease (MASLD) to metabolic-dysfunction-associated steatohepatitis (MASH) involves complex alterations in both liver-autonomous and systemic metabolism that influence the livers balance of fat accretion and disposal. Here, we quantify the relative contribution of hepatic oxidative pathways to liver injury in MASLD-MASH. Using NMR spectroscopy, UHPLC-MS, and GC-MS, we performed stable-isotope tracing and formal flux modeling to quantify hepatic oxidative fluxes in humans across the spectrum of MASLD-MASH, and in mouse models of impaired ketogenesis. We found in humans with MASH, that liver injury correlated positively with ketogenesis and total fat oxidation, but not with turnover of the tricarboxylic acid cycle. The use of loss-of-function mouse models demonstrated that disruption of mitochondrial HMG-CoA synthase (HMGCS2), the rate-limiting step of ketogenesis, impairs overall hepatic fat oxidation and induces a MASLD-MASH-like phenotype. Disruption of mitochondrial {beta}-hydroxybutyrate dehydrogenase (BDH1), the terminal step of ketogenesis, also impaired fat oxidation, but surprisingly did not exacerbate steatotic liver injury. Taken together, these findings suggest that quantifiable variations in overall hepatic fat oxidation may not be a primary determinant of MASLD-to-MASH progression, but rather, that maintenance of hepatic ketogenesis could serve a protective role through additional mechanisms that extend beyond quantified overall rates of fat oxidation.

biochemistry↗

bioRxiv2023

Evaluating cancer cell line and patient-derived xenograft recapitulation of tumor and non-diseased tissue gene expression profiles

Preclinical models like cancer cell lines and patient-derived xenografts (PDXs) are vital for studying disease mechanisms and evaluating treatment options. It is essential that they accurately recapitulate the disease state of interest to generate results that will translate in the clinic. Prior studies have demonstrated that preclinical models do not recapitulate all biological aspects of human tissues, particularly with respect to the tissue of origin gene expression signatures. Therefore, it is critical to assess how well preclinical model gene expression profiles correlate with human cancer tissues to inform preclinical model selection and data analysis decisions. Here we evaluated how well preclinical models recapitulate human cancer and non-diseased tissue gene expression patterns in silico with respect to the full gene expression profile as well as subsetting by the most variable genes, genes significantly correlated with tumor purity, and tissue-specific genes by using publicly available gene expression profiles across multiple sources. We found that using the full gene set improves correlations between preclinical model and tissue global gene expression profiles, confirmed that GBM PDX global gene expression correlation to GBM tumor global gene expression outperforms GBM cell line to GBM tumor global gene expression correlations, and demonstrated that preclinical models in our study often failed to reproduce tissue-specific expression. While including additional genes for global gene expression comparison between cell lines and tissues decreases the overall correlation, it improves the relative rank between a cell line and its tissue of origin compared to other tissues. Our findings underscore the importance of using the full gene expression set measured when comparing preclinical models and tissues and confirm that tissue-specific patterns are better preserved in GBM PDX models than in GBM cell lines. Future studies can build on these findings to determine the specific pathways and gene sets recapitulated by particular preclinical models to facilitate model selection for a given study design or goal.

genomics↗

bioRxiv2020

Range reduction of the Oblong Rocksnail, Leptoxis compacta, shapes riverscape genetic patterns

Many freshwater gastropod species face extinction, including 79% of species in the family Pleuroceridae. The Oblong Rocksnail, Leptoxis compacta, is a narrow range endemic pleurocerid from the Cahaba River basin in central Alabama that has seen rapid range contraction in the last 100 years. Such a decline is expected to negatively affect genetic diversity in the species. However, precise patterns of genetic variation and gene flow across the restricted range of L. compacta are unknown. This lack of information limits our understanding of human impacts on the Cahaba River system and Pleuroceridae. Here, we show that L. compacta has likely seen a species-wide decline in genetic diversity, but remaining populations have relatively high genetic diversity. We also report a contemporary range extension compared to the last published survey. Leptoxis compacta does not display an isolation by distance pattern, contrasting patterns seen in many riverine taxa. Our findings also indicate that historical range contraction has resulted in the absence of common genetic patterns seen in many riverine taxa like isolation by distance as the small distribution of L. compacta allows for relatively unrestricted gene flow across its remaining range despite limited dispersal abilities. Two collection sites had higher genetic diversity than others, and broodstock sites for future captive propagation and reintroduction efforts should utilize sites identified here as having the highest genetic diversity. Broadly, our results support the hypothesis that range contraction will result in the reduction of species-wide genetic diversity, and common riverscape genetic patterns cannot be assumed to be present in species facing extinction risk.

zoology↗