Biology subjects

Ackerman, D.

Publications and source records attributed to Ackerman, D..

10 recordsLinked to original sources

bioRxiv2025

Optical genome mapping identifies a novel PSIP1::TBL1X fusion in metastatic pancreatic neuroendocrine tumors

Background and aimsEffective treatment of metastatic neuroendocrine tumors (NETs) is limited by a lack of targeted therapies and clinically useful predictive biomarkers. We applied complementary genomic profiling technologies to identify genomic alterations that could lead to actionable drug targets and biomarkers. MethodsOptical genome mapping (OGM) and whole exome sequencing (WES) were performed on 70 liver metastases of neuroendocrine tumors from multiple anatomical primary sites. PacBio Iso-Seq long read sequencing and western blotting was used to confirm fusion gene expression. Findings were validated by rtPCR and western blotting on a separate cohort of 17 resection specimens from 14 pancreatic NET cases. ResultsSomatic variant calling from OGM data detected recurrent fusions involving TBL1X (PSIP1::TBL1X) and BEND2 (CHD7::BEND2 and NEO1::BEND2) in pancreatic neuroendocrine tumors (pNETs). BEND2 fusions were associated with high grade tumors, as previously described. The novel PSIP1::TBL1X fusion was confirmed to result in fusion transcript expression by both long-read sequencing and nested rtPCR. Presence of the PSIP1::TBL1X fusion transcript was also confirmed in a second cohort of pNET resection specimens and fusion protein expression was established by western blotting. Both TBL1X and BEND2 fusions are mutually exclusive with ATRX/DAXX mutations. ConclusionThis study underscores the importance of structural variants, including fusion genes as both prognostic biomarkers and potential therapeutic targets, especially in ATRX/DAXX negative pNETs. BEND2 fusion positivity may be a clinically useful biomarker for aggressive disease. As all TBL1X fusion isoforms contain the entire TBL1X coding sequence, TBL1X inhibition could be explored as a novel treatment for TBL1X fusion positive pNETs.

cancer biology↗

bioRxiv2025

MSI.EAGLE: An Open-Source GUI for Streamlined Mass Spectrometry Imaging Analysis

Mass Spectrometry Imaging (MSI) is an emergent tool for analyzing spatial molecular distributions, yet data complexity often hinders effective analysis. MSI.EAGLE, an open-source R-Shiny application, makes analysis accessible for non-specialists by integrating advanced tools in a user-friendly interface. The workflow leverages tools from the Cardinal MSI package, with enhanced phenotyping, segmentation, statistical analysis and visualization. The application addresses a gap in spatial biology research by empowering a broader scientific community.

pathology↗

bioRxiv2024

Synaptic Specializations at Dopamine Release Sites Orchestrate Efficient and Precise Neuromodulatory Signaling

Neuromodulators are generally understood to act through expansive projections that broadcast signals relatively indiscriminately, in stark contrast to the precise, synapse-bound organization of fast neurotransmitters like glutamate and GABA. This dichotomy has left the local architecture of neuromodulatory release and receptor engagement largely obscure. Here, using dopamine as a model system, we reveal that neuromodulatory signaling can be guided by precise molecular specificity. We show that dopamine axons exhibit a fundamental tropism for neurons expressing D1 or D2 receptors in the striatum and amygdala, a targeting principle that is conserved in dissociated co-cultures. Importantly, single-bouton-resolved optical imaging of release shows that dopamine is not broadcast broadly but is highly localized to varicosities that form direct, synapse-like appositions with receptor-expressing somata and dendrites. In contrast, varicosities lacking such appositions, or contacting receptor-negative neurons, are largely quiescent, indicating that local interactions with receptor-expressing targets help specify dopamine release competence. To directly visualize receptor organization relative to release sites at endogenous expression levels, we generated ALFA-tag knock-in mice (ALFADoR mice) in which the N-termini of D1 and D2 dopamine receptors are epitope-tagged. Combining these mice with immunolabeling and expansion microscopy in dissociated culture and intact tissue, we show that both D1 and D2 receptors are organized into discrete puncta rather than diffuse membrane distributions. Across major terminal fields of midbrain dopamine neurons, including striatum, amygdala, and prefrontal cortex, these receptor nanoclusters are preferentially positioned near dopamine varicosities at distances far smaller than expected from spatial shuffling controls. Moreover, receptor clusters apposed to dopamine varicosities were observed to be larger than non-apposed clusters, consistent with specialized receptor microdomains that may enhance signaling efficacy. Together, our data demonstrate that dopaminergic signaling is spatially organized by receptor-specific targeting and subcellular microdomain specialization. This structured framework challenges the canonical dichotomy between precise fast transmission and diffuse neuromodulation. It reveals that principles of synaptic organization extend to and define a previously hidden layer of specificity in neuromodulatory systems, opening new frontiers in understanding cell-type specific neuromodulation, axon guidance, and subcellular GPCR organization.

neuroscience↗

bioRxiv2024

Data Release: High-Resolution Imaging and Segmentation of P7 Mouse Tissue Microarchitecture Using FIB-SEM and Machine Learning

This report presents a comprehensive data release exploring the tissue microarchitecture of P7 aged mice using Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) combined with machine learning-based segmentations of nuclei. The study includes high-resolution 3D volumes and nucleus segmentations for seven vital tissues--pancreas, liver, kidney, heart, thymus, hippocampus, and skin--from a single mouse. The detailed datasets are openly accessible onOpenOrganelle.org, providing a valuable resource for the scientific community to support further research and collaboration.

cell biology↗

bioRxiv2024

Transport and Organization of Individual Vimentin Filaments Within Dense Networks Revealed by Single Particle Tracking and 3D FIB-SEM

Vimentin intermediate filaments (VIFs) form complex, tight-packed networks; due to this density, traditional ensemble labeling and imaging approaches cannot accurately discern single filament behavior. To address this, we introduce a sparse vimentin-SunTag labeling strategy to unambiguously visualize individual filament dynamics. This technique confirmed known long-range dynein and kinesin transport of peripheral VIFs and uncovered extensive bidirectional VIF motion within the perinuclear vimentin network, a region we had thought too densely bundled to permit such motility. To examine the nanoscale organization of perinuclear vimentin, we acquired high-resolution electron microscopy volumes of a vitreously frozen cell and reconstructed VIFs and microtubules within a [~]50 {micro}m3 window. Of 583 VIFs identified, most were integrated into long, semi-coherent bundles that fluctuated in width and filament packing density. Unexpectedly, VIFs displayed minimal local co-alignment with microtubules, save for sporadic cross-over sites that we predict facilitate cytoskeletal crosstalk. Overall, this work demonstrates single VIF dynamics and organization in the cellular milieu for the first time SummarySingle-particle tracking demonstrates that individual filaments in bundles of vimentin intermediate filaments are transported in the cytoplasm by motor proteins along microtubules. Furthermore, using 3D FIB-SEM the authors showed that vimentin filament bundles are loosely packed and co-aligned with microtubules.

cell biology↗

bioRxiv2022

Architecture and dynamics of a novel desmosome-endoplasmic reticulum organelle

The endoplasmic reticulum (ER) forms a dynamic network that contacts other cellular membranes to regulate stress responses, calcium signaling, and lipid transfer. Using high-resolution volume electron microscopy, we find that the ER forms a previously unknown association with keratin intermediate filaments and desmosomal cell-cell junctions. Peripheral ER assembles into mirror image-like arrangements at desmosomes and exhibits nanometer proximity to keratin filaments and the desmosome cytoplasmic plaque. ER tubules exhibit stable associations with desmosomes, and perturbation of desmosomes or keratin filaments alters ER organization and mobility. These findings indicate that desmosomes and the keratin cytoskeleton pattern the distribution of the ER network. Overall, this study reveals a previously unknown subcellular architecture defined by the structural integration of ER tubules with an epithelial intercellular junction. One-Sentence SummaryThe desmosome adhesive junction regulates the organization and dynamics of the endoplasmic reticulum network.

cell biology↗

bioRxiv2020

Automatic whole cell organelle segmentation in volumetric electron microscopy

Cells contain hundreds of different organelle and macromolecular assemblies intricately organized relative to each other to meet any cellular demands. Obtaining a complete understanding of their organization is challenging and requires nanometer-level, threedimensional reconstruction of whole cells. Even then, the immense size of datasets and large number of structures to be characterized requires generalizable, automatic methods. To meet this challenge, we developed an analysis pipeline for comprehensively reconstructing and analyzing the cellular organelles in entire cells imaged by focused ion beam scanning electron microscopy (FIB-SEM) at a near-isotropic size of 4 or 8 nm per voxel. The pipeline involved deep learning architectures trained on diverse samples for automatic reconstruction of 35 different cellular organelle classes - ranging from endoplasmic reticulum to microtubules to ribosomes - from multiple cell types. Automatic reconstructions were used to directly quantify various previously inaccessible metrics about these structures, including their spatial interactions. We show that automatic organelle reconstructions can also be used to automatically register light and electron microscopy images for correlative studies. We created an open data and open source web repository, OpenOrganelle, to share the data, computer code, and trained models, enabling scientists everywhere to query and further reconstruct the datasets.

cell biology↗

bioRxiv2020

A Connectome and Analysis of the Adult Drosophila Central Brain

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the flys brain.

bioinformatics↗

bioRxiv2020

A Connectome of the Adult Drosophila Central Brain

The neural circuits responsible for behavior remain largely unknown. Previous efforts have reconstructed the complete circuits of small animals, with hundreds of neurons, and selected circuits for larger animals. Here we (the FlyEM project at Janelia and collaborators at Google) summarize new methods and present the complete circuitry of a large fraction of the brain of a much more complex animal, the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses, and proofread such large data sets; new methods that define cell types based on connectivity in addition to morphology; and new methods to simplify access to a large and evolving data set. From the resulting data we derive a better definition of computational compartments and their connections; an exhaustive atlas of cell examples and types, many of them novel; detailed circuits for most of the central brain; and exploration of the statistics and structure of different brain compartments, and the brain as a whole. We make the data public, with a web site and resources specifically designed to make it easy to explore, for all levels of expertise from the expert to the merely curious. The public availability of these data, and the simplified means to access it, dramatically reduces the effort needed to answer typical circuit questions, such as the identity of upstream and downstream neural partners, the circuitry of brain regions, and to link the neurons defined by our analysis with genetic reagents that can be used to study their functions. Note: In the next few weeks, we will release a series of papers with more involved discussions. One paper will detail the hemibrain reconstruction with more extensive analysis and interpretation made possible by this dense connectome. Another paper will explore the central complex, a brain region involved in navigation, motor control, and sleep. A final paper will present insights from the mushroom body, a center of multimodal associative learning in the fly brain.

neuroscience↗

bioRxiv2019

In vivo screen identifies LXR agonism potentiates sorafenib killing of hepatocellular carcinoma

Existing drug therapies for hepatocellular carcinoma (HCC), including sorafenib, extend patient survival by only three months. We sought to identify novel druggable targets for use in combination with sorafenib to increase its efficacy. We implemented an in vivo genetic screening paradigm utilizing a library of 43 genes-of-interest expressed in the context of repopulation of the injured livers of Fumarylacetoacetate Hydrolase-deficient (Fah-/-) mice, which led to highly penetrant HCC. We then treated mice with vehicle or sorafenib to discover genetic determinants of sensitivity and resistance. Liver X Receptor alpha (LXR) emerged as a potential target. To examine LXR agonism in combination with sorafenib treatment, we added varying concentrations of sorafenib and LXR agonist drugs to HCC cell lines. We performed transcriptomic analysis to elucidate the mechanisms of HCC death. Fah-/- mice injected with the screening library developed HCC tumor clones containing Myc cDNA plus various other cDNAs. Treatment with sorafenib resulted in sorafenib-resistant HCCs that were significantly depleted in Nr1h3 cDNA, encoding LXR, suggesting that LXR activation is incompatible with tumor growth in the presence of sorafenib treatment in vivo. The combination of sorafenib and LXR agonism led to enhanced cell death as compared to monotherapy in multiple HCC cell lines, due to reduced expression of cell cycle regulators and increased expression of genes associated with apoptosis. Combination therapy also enhanced cell death in a sorafenib-resistant primary human HCC cell line. Our novel in vivo screen led to the discovery that LXR agonist drugs potentiate the efficacy of sorafenib in treating HCC.

cancer biology↗