Biology subjects

Magnuson, M. A.

Publications and source records attributed to Magnuson, M. A..

10 recordsLinked to original sources

bioRxiv2026

QuantEM: An optimized platform of vision transformer-based models for segmentation and analysis of electron microscopy data

Electron microscopy (EM) is essential for resolving cellular ultrastructure, yet quantitative analysis remains limited by labor-intensive segmentation and the scarcity of generalizable models. Here we present QuantEM, an open-source platform for segmentation and analysis of EM data across imaging modalities, tissues, and species. We assembled the largest curated collection of intracellular EM datasets to date, comprising over 15,000 two-dimensional images and 1,700 three-dimensional acquisitions from more than 600 datasets, including nearly 4,000 newly released acquisitions. Using this resource, we trained an EM-specific vision transformer foundation model and systematically optimized adaptation strategies for organelle segmentation. QuantEM provides pretrained models for mitochondria, endoplasmic reticulum, nuclei, and lipid droplets, integrated with interactive proofreading and downstream quantitative analyses through standalone and napari interfaces. Across diverse naive datasets, QuantEM consistently matches or exceeds existing models on zero-shot segmentation while requiring less data for finetuning. We further demonstrate its utility by revealing previously unrecognized subcellular compartmentation of hepatic glucokinase using immuno-electron microscopy.

cell biology↗

bioRxiv2025

Molecular dynamics driving phenotypic divergence among KRAS mutants in pancreatic tumorigenesis

Inflammation in the pancreas drives acinar-to-ductal metaplasia (ADM), a progenitor-like state that can be hijacked by mutant Kras in the formation of pancreatic cancer (PDAC). How these cell fate decisions vary according to KRAS mutation remains poorly understood. To define mutation-specific lineage reversion and tumor initiation, we implement novel Ptf1a-TdTomato mice and multiple KRAS mutants across an array of genetic, pharmacologic, and inflammatory perturbations in vivo. Whereas KRASG12D co-opts injury to enable lineage reversion, enhancer reprogramming, and tumor initiation, KRASG12R/V can initiate but not sustain dedifferentiated and neoplastic transcriptional and epigenetic programs. We find the KRASG12R/V defects consist of a failure to invoke robust EGFR signaling and activate Rac1/Vav1, with constitutive Akt activation in vivo sufficient to rescue the tumorigenic potential of KRASG12R. As the marked heterogeneity among KRAS variants begins early in tumorigenesis, these data are crucial to understanding mutation-specific oncogenic trajectories and directing the implementation of KRAS-directed therapeutics. SIGNIFICANCEDefining how KRAS mutants drive distinct outcomes in human pancreatic cancer is critical for developing allele-specific therapeutic approaches. This study unveils a hierarchy among KRASG12D, KRASG12V, and KRASG12R to drive tumor initiation, owing to heterogeneous activation of EGFR, PI3K/AKT, and RAC1 signaling, thus revealing mutation-specific evolutionary paths in pancreatic tumorigenesis.

cancer biology↗

bioRxiv2025

Genetic background influences the heterogeneous phenotypes driven by the MAFAS64F MODY variant in male mice

Pancreatic {beta}-cells require the coordinated expression of transcription factors such as MAFA to dynamically secrete insulin to maintain euglycemia. A naturally occurring mutation in MAFA (MAFAS64F) produces a long-lived variant protein which predisposes carriers to dichotomous conditions of either maturity (adult)-onset diabetes of the young (MODY) or hypoglycemia in a sex-dependent manner. Here we show that genetic background modulates disease penetrance in MafAS64F/+ male mice. Specifically, MafAS64F/+ males backcrossed to a C57/Bl6J ("C57") background prevented dysglycemia, while C57 MafAS64F/+ males bred one generation to an SJL/J background ("mixed") manifested overt diabetes, impaired insulin secretion, and accelerated {beta}-cell senescence. MafA protein levels, phosphorylation status, and target gene expression in C57 MafAS64F/+ male islets were more comparable to wildtype males. RNA sequencing of C57 MafAS64F/+ male islets revealed fewer differentially expressed genes than mixed background male islets, including transcriptional signatures of {beta}-cell senescence. In addition, retinoic acid signaling, another signature of cellular aging, was uniquely downregulated in C57 MafAS64F/+ male islets. Indeed, core retinoic acid signaling receptor RAR and known target genes were downregulated in C57 MafAS64F/+ male islets. CUT&RUN mapping revealed that MafA directly impacted retinoic acid receptor alpha Rara expression. In sum, these data show that genetic factors can impact unique pathways to modulate disease penetrance in mice modeling MAFA-MODY. Article HighlightsO_LIGenetic background in mice or ancestry in humans can profoundly influence diabetes susceptibility. C_LIO_LIWe asked whether diabetes penetrance in our robust mouse model of MAFA-MODY on a mixed genetic background was impacted when backcrossed to C57/Bl6J ("C57"). C_LIO_LIHere we show that C57 MafAS64F/+ males have wildtype glucose-sensing properties, compared to overt diabetes which could be reproducibly re-created on a mixed background. Further analysis disclosed more muted gene expression changes in C57 MafAS64F/+ male islets including unique downregulation of senescence and retinoic acid signaling. C_LIO_LIThese results illustrate the influence of genetic landscape on {beta}-cell function in response to a pathogenic MODY variant. C_LI

physiology↗

bioRxiv2023

Temporal recording of mammalian development and precancer

Key to understanding many biological phenomena is knowing the temporal ordering of cellular events, which often require continuous direct observations [1, 2]. An alternative solution involves the utilization of irreversible genetic changes, such as naturally occurring mutations, to create indelible markers that enables retrospective temporal ordering [3-8]. Using NSC-seq, a newly designed and validated multi-purpose single-cell CRISPR platform, we developed a molecular clock approach to record the timing of cellular events and clonality in vivo, while incorporating assigned cell state and lineage information. Using this approach, we uncovered precise timing of tissue-specific cell expansion during murine embryonic development and identified new intestinal epithelial progenitor states by their unique genetic histories. NSC-seq analysis of murine adenomas and single-cell multi-omic profiling of human precancers as part of the Human Tumor Atlas Network (HTAN), including 116 scRNA-seq datasets and clonal analysis of 418 human polyps, demonstrated the occurrence of polyancestral initiation in 15-30% of colonic precancers, revealing their origins from multiple normal founders. Thus, our multimodal framework augments existing single-cell analyses and lays the foundation for in vivo multimodal recording, enabling the tracking of lineage and temporal events during development and tumorigenesis.

developmental biology↗

bioRxiv2023

The MODY-associated TALK-1 L114P mutation causes islet α-cell overactivity and β-cell inactivity resulting in transient neonatal diabetes and glucose dyshomeostasis in adults

The gain-of-function mutation in the TALK-1 K+ channel (p.L114P) is associated with maturity-onset diabetes of the young (MODY). TALK-1 is a key regulator of {beta}-cell electrical activity and glucose-stimulated insulin secretion. The KCNK16 gene encoding TALK-1 is the most abundant and {beta}-cell-restricted K+ channel transcript. To investigate the impact of KCNK16 L114P on glucose homeostasis and confirm its association with MODY, a mouse model containing the Kcnk16 L114P mutation was generated. Heterozygous and homozygous Kcnk16 L114P mice exhibit increased neonatal lethality in the C57BL/6J and the CD-1(ICR) genetic background, respectively. Lethality is likely a result of severe hyperglycemia observed in the homozygous Kcnk16 L114P neonates due to lack of glucose-stimulated insulin secretion and can be reduced with insulin treatment. Kcnk16 L114P increased whole-cell {beta}-cell K+ currents resulting in blunted glucose-stimulated Ca2+ entry and loss of glucose-induced Ca2+ oscillations. Thus, adult Kcnk16 L114P mice have reduced glucose-stimulated insulin secretion and plasma insulin levels, which significantly impairs glucose homeostasis. Taken together, this study shows that the MODY-associated Kcnk16 L114P mutation disrupts glucose homeostasis in adult mice resembling a MODY phenotype and causes neonatal lethality by inhibiting islet insulin secretion during development. These data suggest that TALK-1 is an islet-restricted target for the treatment for diabetes. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC="FIGDIR/small/545631v3_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@19031e9org.highwire.dtl.DTLVardef@1bccc49org.highwire.dtl.DTLVardef@803e1org.highwire.dtl.DTLVardef@36c584_HPS_FORMAT_FIGEXP M_FIG Graphical Summary C_FIG

physiology↗

bioRxiv2022

Species-specific roles for the MAFA and MAFB transcription factors in regulatingislet β cell identity

Type 2 diabetes (T2D) is associated with compromised identity of insulin-producing pancreatic islet beta ({beta}) cells, characterized by inappropriate production of other islet cell-enriched hormones. Here we examined how hormone misexpression was influenced by the MAFA and MAFB transcription factors, closely related proteins that maintain islet cell function. Mice specifically lacking MafA in {beta} cells demonstrated broad, population-wide changes in hormone gene expression with an overall gene signature closely resembling islet gastrin (Gast)-positive cells generated under conditions of chronic hyperglycemia and obesity. A human {beta} cell line deficient in MAFB, but not one lacking MAFA, also produced a gastrin (GAST)-positive gene expression pattern. In addition, GAST was detected in human T2D {beta} cells with low levels of MAFB. Moreover, evidence is provided that human MAFB can directly repress GAST gene transcription. These results support a novel, species-specific role for MafA and MAFB in maintaining adult mouse and human {beta} cell identity, respectively, by repressing expression of Gast/GAST and other non-{beta} cell hormones.

cell biology↗

bioRxiv2022

The microtubule minus end-binding protein CAMSAP2 does not regulate microtubule dynamics in primary pancreatic β-cells but facilitates insulin secretion

Glucose stimulation induces the remodeling of microtubules in Islet {beta}-cells to potentiate glucose-stimulated insulin secretion. CAMSAP2 is a microtubule minus-end binding protein and is reported to stabilize and position microtubules in several non-{beta}-cells, such as human retinal pigment epithelium cells. In immortalized insulinoma MIN6 cells, CAMSAP2 binds to and forms short stretches at microtubule minus ends in the cytoplasm, which is consistent with the reported subcellular localization and functions of CAMSAP2 in non-{beta}-cells. Surprisingly, we found that CAMSAP2 expressed in primary islet {beta}-cells does not form short stretches in the cytoplasm, but instead is localized to the Golgi apparatus. This novel localization is specific to {beta}-but not -cells in islets and it is independent of MT-binding. Knockdown of CAMSAP2 by shRNA impairs Golgi-ER trafficking, reduces total insulin content, and attenuates GSIS without affecting the MT dynamics or releasability of insulin granules in islet {beta}-cells. Corresponding to these results, we found that primary islets and MIN6 cells express different CAMSAP2 isoforms. We propose that primary islet {beta} cells use a novel CAMSAP2 isoform for a MT-independent non-canonical function, which is to promote Golgi-ER trafficking that supports efficient production of insulin secretory granules.

cell biology↗

bioRxiv2020

Microtubules regulate pancreatic beta cell heterogeneity via spatiotemporal control of insulin secretion hot spots

Heterogeneity of glucose-stimulated insulin secretion (GSIS) in pancreatic islets is physiologically important but poorly understood. Here, we utilize whole mouse islets to determine how microtubules affect secretion toward the vascular extracellular matrix. Our data indicate that microtubule stability in the {beta}-cell population is heterogenous, and that cells with more stable microtubules secrete less in response to a stimulus. Consistently, microtubule hyper-stabilization prevents, and microtubule depolymerization promotes {beta}-cell activation. Analysis of spatiotemporal patterns of secretion events shows that microtubule depolymerization activates otherwise dormant {beta}-cells via initiation of secretion clusters (hot spots). Microtubule depolymerization also enhances secretion from individual cells, introducing both additional clusters and scattered events. Interestingly, without microtubules, the timing of clustered secretion is dysregulated, extending the first phase of GSIS. Our findings uncover a novel microtubule function in tuning insulin secretion hot spots, which leads to accurately measured and timed response to glucose stimuli and promotes functional {beta}-cell heterogeneity.

cell biology↗

bioRxiv2017

iterativeWGCNA: iterative refinement to improve module detection from WGCNA co-expression networks

Weighted-gene correlation network analysis (WGCNA) is frequently used to identify highly co-expressed clusters of genes (modules) within whole-transcriptome datasets. However, transcriptome-scale networks tend to be highly connected, making it challenging for the hierarchical clustering underlying the WGCNA-based classification to discriminate coherently expressed gene sets without significant information loss from either a priori filtering of the expression dataset or a posteriori pruning of the cluster dendrogram.\n\nHere we present iterativeWGCNA, a Python-wrapped extension for the WGCNA R software package that improves the robustness of detected modules and minimizes information loss. The method works by pruning poorly fitting genes from estimated modules and then re-running WGCNA to refine gene clusters. After refining, pruned genes are assembled into a new expression dataset to isolate overlapping modules and the process repeated. In doing so, iterativeWGCNA provides an unsupervised, non-biased filtering to generate a robust, comprehensive network-based classification of whole-transcriptome expression datasets.

bioinformatics↗

bioRxiv2017

FUCCI tracking shows that Neurog3 levels vary with cell-cycle phase in endocrine-biased pancreatic progenitors

Neurog3HI endocrine-committing cells are generated from a population of Sox9+ mitotic progenitors with only a low level of Neurog3 transcriptional activity (Neurog3TA.LO). Low-level Neurog3 protein, in Neurog3TA.LO cells, is required to maintain their mitotic endocrine-lineage-primed status. Herein, we describe a Neurog3-driven FUCCI cell-cycle reporter (Neurog3P2A.FUCCI) derived from a Neurog3 BAC transgenic reporter that functions as a loxed cassette acceptor (LCA). In cycling Sox9+ Neurog3TA.LO progenitors, the majority of cells in S-G2-M phases have undetectable levels of Neurog3 with increased expression of endocrine progenitor markers, while those in G1 have low Neurog3 levels with increased expression of endocrine differentiation markers. These findings support a model in which variations in Neurog3 protein levels are coordinated with cell-cycle phase progression in Neurog3TA.LO progenitors with entrance into G1 triggering a concerted effort, beyond increasing Neurog3 levels, to maintain an endocrine-lineage-primed state by initiating expression of the downstream endocrine differentiation program prior to endocrine-commitment.

cell biology↗