Biology subjects

Tillman, H.

Publications and source records attributed to Tillman, H..

6 recordsLinked to original sources

bioRxiv2023

Diet-induced obesity impacts influenza disease severity and transmission dynamics in ferrets

Obesity, and the associated metabolic syndrome, is a risk factor for increased disease severity with a variety of infectious agents, including influenza virus. Yet the mechanisms are only partially understood. As the number of people, particularly children, living with obesity continues to rise, it is critical to understand the role of host status on disease pathogenesis. In these studies, we use a novel diet-induced obese ferret model and new tools to demonstrate that like humans, obesity resulted in significant changes to the lung microenvironment leading to increased clinical disease and viral spread to the lower respiratory tract. The decreased antiviral responses also resulted in obese animals shedding higher infectious virus for longer making them more likely to transmit to contacts. These data suggest the obese ferret model may be crucial to understanding obesitys impact on influenza disease severity and community transmission, and a key tool for therapeutic and intervention development for this high-risk population. TeaserA new ferret model and tools to explore obesitys impact on respiratory virus infection, susceptibility, and community transmission.

microbiology↗

bioRxiv2022

A murine model of hnRNPH2-related neurodevelopmental disorder recapitulates clinical features of human disease and reveals a mechanism for genetic compensation of HNRNPH2

Mutations in HNRNPH2 cause an X-linked neurodevelopmental disorder with a phenotypic spectrum that includes developmental delay, intellectual disability, language impairment, motor function deficits, and seizures. More than 90% of patients with this disorder have a missense mutation within or adjacent to the nuclear localization signal (NLS) of hnRNPH2, although the specific pathogenic consequences of these mutations have not been examined. Here we found that hnRNPH2 NLS mutations result in reduced interaction with the nuclear transport receptor Kap{beta}2 in vitro and in cultured human cells. These mutations also cause modest accumulation of hnRNPH2 in the cytoplasm, suggesting that mislocalization of the protein might contribute to pathogenesis. We generated two knock-in mouse models with human-equivalent mutations in the endogenous mouse gene Hnrnph2, as well as Hnrnph2 knockout (KO) mice, and subjected them to extensive phenotyping. Mutant knock-in mice displayed a spectrum of phenotypes that recapitulated aspects of the human disorder, including reduced survival in males, craniofacial abnormalities, impaired motor and cognitive functions, and increased susceptibility to audiogenic seizures. Mutant knock-in male mice developed more severe phenotypes than female mice, likely due to differences in X-chromosome gene dosage. In contrast, two independent lines of Hnrnph2 KO mice showed no detectable phenotypes. Notably, KO mice had upregulated expression of Hnrnph1, a close paralog of Hnrnph2, whereas mutant Hnrnph2 knock-in mice failed to upregulate Hnrnph1. Thus, genetic compensation by Hnrnph1 might be sufficient to counteract the loss of hnRNPH2. These findings suggest that the pathogenesis of HNRNPH2-related disorder in humans may be driven by a toxic gain of function or a complex loss of HNRNPH2 function with impaired compensation by HNRNPH1. The mutant knock-in mice described here are an important resource for preclinical studies to assess the potential benefit of either gene replacement or therapeutic knockdown of mutant hnRNPH2.

neuroscience↗

bioRxiv2021

Jointly leveraging spatial transcriptomics and deep learning models for pathology image annotation improves cell type identification over either approach alone.

Spatial transcriptomics technologies have recently emerged as a powerful tool for measuring spatially resolved gene expression directly in tissues sections, revealing cell types and their dysfunction in unprecedented detail. However, spatial transcriptomics technologies are limited in their ability to separate transcriptionally similar cell types and can suffer further difficulties identifying cell types in slide regions where transcript capture is low. Here, we describe a conceptually novel methodology that can computationally integrate spatial transcriptomics data with cell-type-informative paired tissue images, obtained from, for example, the reverse side of the same tissue section, to improve inferences of tissue cell type composition in spatial transcriptomics data. The underlying statistical approach is generalizable to any spatial transcriptomics protocol where informative paired tissue images can be obtained. We demonstrate a use case leveraging cell-type-specific immunofluorescence markers obtained on mouse brain tissue sections and a use case for leveraging the output of AI annotated H&E tissue images, which we used to markedly improve the identification of clinically relevant immune cell infiltration in breast cancer tissue. Thus, combining spatial transcriptomics data with paired tissue images has the potential to improve the identification of cell types and hence to improve the applications of spatial transcriptomics that rely on accurate cell type identification.

bioinformatics↗

bioRxiv2021

The Myogenesis Program Drives Clonal Selection and Drug Resistance in Rhabdomyosarcoma

Rhabdomyosarcoma (RMS) is a pediatric cancer with features of skeletal muscle; patients with unresectable or metastatic RMS fare poorly due to high rates of disease recurrence. Here, we use single cell and single nucleus RNA-sequencing to show that RMS tumors recapitulate the spectrum of embryonal myogenesis. Using matched patient samples from a clinical trial and orthotopic patient-derived xenografts (O-PDXs), we show chemotherapy eliminates the most proliferative component with features of myoblasts; after treatment, the quiescent immature population with features of paraxial mesoderm expands to reconstitute the developmental hierarchy of the original tumor. We discovered that this paraxial mesoderm population is dependent on EGFR signaling and is sensitive to EGFR inhibitors. Taken together, this data serves as a proof-of-concept that targeting each developmental state in RMS is an effective strategy for improving outcomes by preventing disease recurrence.

cancer biology↗

bioRxiv2019

Geldanamycin inhibits Jumonji histone lysine demethylase KDM4 and targets chimeric transcription factor PAX3-FOXO1

Histone lysine demethylases (KDMs) are emerging as therapeutic targets in cancer. Development of potent KDM inhibitors may provide additional options for epigenomics-oriented therapies. Using a Time-Resolved Fluorescence Resonance Energy Transfer (TR-FRET) functional demethylation assay, in combination with a high-content immunofluorescence imaging phenotypic screen, Matrix-Assisted Laser Desorption/Ionization-Fourier Transform Ion Cyclotron Resonance mass spectrometry (MALDI-FTICR MS) and Amplified Luminescent Proximity Homogeneous Assay (ALPHA), we identified geldanamycin, an inhibitor of heat shock protein 90 (Hsp90), as a novel inhibitor of JmjC-domain containing demethylases such as KDM4B. We further found that geldanamycin can destabilize the PAX3-FOXO1 fusion oncoprotein, an Hsp90 client, which is a driver of clinically unfavorable alveolar rhabdomyosarcoma (aRMS). We then hypothesized that dual inhibition of PAX3-FOXO1 and epigenetic modifiers of aRMS would have synergistic antitumor activity. We repurposed the geldanamycin analog 17-DMAG to target aRMS and found that 17-DMAG significantly delays tumor growth, extends survival in xenograft mouse models, and inhibits expression of PAX3-FOXO1 targets and multiple oncogenic pathways including MYC, E2F and NOTCH. In addition, the combination of 17-DMAG with conventional chemotherapy or the bromodomain inhibitor JQ1 significantly enhances therapeutic efficacy. In summary, we have identified geldanamycin and 17-DMAG as dual KDM/Hsp90 inhibitors and 17-DMAG is efficacious against PAX3-FOXO1-driven rhabdomyosarcoma.

cancer biology↗

bioRxiv2018

Unc 51-like autophagy-activating kinase (ULK1) mediates clearance of free {alpha}-globin in {beta}-thalassemia

Erythroid maturation is coordinated to maximize the production of hemoglobin A heterotetramers (2{beta}2) and minimize the accumulation of potentially toxic free - or {beta}-globin subunits. In {beta}-thalassemia, mutations in the {beta}-globin gene cause a build-up of free -globin, which forms intracellular precipitates that impair erythroid cell maturation and viability. Protein quality-control systems mitigate {beta}-thalassemia pathophysiology by degrading toxic free -globin. We show that loss of the Unc 51-like autophagy-activating kinase gene Ulk1 in {beta}-thalassemic mice reduces autophagic clearance of -globin in red cell precursors and exacerbates disease phenotypes, whereas inactivation of the canonical autophagy gene Atg5 has minimal effects. Systemic treatment with rapamycin to inhibit the ULK1 inhibitor mTORC1 reduces -globin precipitates and lessens pathologies in {beta}-thalassemic mice, but not in those lacking Ulk1. Similarly, rapamycin reduces free -globin accumulation in erythroblasts derived from {beta}-thalassemic patient CD34+ hematopoietic progenitors. Our findings identify a new, drug-regulatable pathway for ameliorating {beta}-thalassemia.\n\nOne Sentence SummaryRapamycin alleviates {beta}-thalassemia by stimulating ULK1-dependent autophagy of toxic free -globin.

cell biology↗