Biology subjects

SoRelle, E. D.

Publications and source records attributed to SoRelle, E. D..

7 recordsLinked to original sources

bioRxiv2025

HIV-associated non-Hodgkin lymphoma tumor-microenvironment axes differ by EBV status across cellular origins

Non-Hodgkin Lymphoma (NHL) is the main cancer-related mortality for people living with HIV (PLWH). NHL genetic and molecular classifications have been intensely studied and correlated with clinical outcomes, but critical unanswered questions relevant to malignancy persist. For example, tumors positive for Epstein-Barr virus (EBV) are aggressive and account for 30-50% of HIV-associated NHLs, yet insights on the nature of EBV in NHL pathogenesis or potential therapeutic vulnerabilities have been limited. Here, we examined HIV-associated NHLs stratified by histopathologic classification, cell of origin (COO), molecular subtype, and EBV status using genome-wide spatial transcriptomic analyses. Tumor tissues in EBV+ HIV-NHLs displayed enriched expression of mitochondrial respiration and purine metabolism signatures versus EBV- tumors. Immune infiltration of EBV+ tumors was limited, and immune and stromal regions of EBV+ HIV-NHLs displayed upregulation of the gene for the iron exporter ferroportin (SLC40A1), indicating immunosuppressive macrophage polarization. An immunosuppressive SPP1-CD44 axis and oncogenic GAS6-AXL interaction between tumor and stroma were specifically predicted for EBV+ HIV-NHLs with plasmablastic features. Tumor microenvironment (TME) similarities to secondary lymphoid tissues such as inverse CXCL12-CXCL13 gradients and evidence of matching between tumor B cell phenotypes and reticular cell signatures were also observed. Finally, we developed a simple yet flexible approach to quantify expression gradients and cell proximity to annotated regions. Thus, this study highlights potential avenues for NHL therapy tailored by EBV status and provides a unique resource to examine tumor-TME interactions in the HIV-immunocompromised context. Key PointsO_LISpatial transcriptomic landscapes resolve cell-of-origin- and EBV-associated HIV-NHL heterogeneity including immunosuppressive myeloid responses to EBV+ tumors C_LIO_LISpatial gradients including CXCL12 and CXCL13 indicate that tumor-stromal interactions mimic lymphoid tissue organization and depend on B cell development stage C_LIO_LIDevelopment of a direction-agnostic method to calculate spatial expression gradients relative to annotated tissue and cell types of interest C_LIO_LIPredicted pharmacologic vulnerabilities in clinical samples are replicated in vitro and confirmed by small molecule screening C_LI

cancer biology↗

bioRxiv2025

Reconstructing EBV reactivation and DNA damage response kinetics in morphologic pseudotime

Epstein-Barr virus (EBV) lytic infection contributes to virus-associated cancers and autoimmunity and depends on viral subversion of host DNA damage responses (DDR). Here, we use high-content screening (HCS) for morphologic and pseudotemporal profiling of single-cell EBV reactivation and DDR dynamics spanning seven lytic induction treatments in nine B cell lymphoma models. We generated an atlas (>750,000 cells) of spatiotemporally distinct phenotypes of immediate-early (IE) and late lytic proteins, viral and cellular DNA replication, and double-stranded break (DSB) DDR factors. Single-cell segmentation, feature extraction, and clustering identify treatment- and model-dependent cell responses and lytic induction. Notably, genotoxin-induced DDR profiles differ in lytic versus latent cells, and lytic protein localization varies across pharmacologic and physiologic stimuli. Pseudotime trajectories of physiologic reactivation reveal viral replication compartment (VRC) nucleation and expansion alongside concomitant host DDR localization. The early DDR marker {gamma}H2AX is depleted from VRCs but widespread across host chromatin throughout reactivation. Surprisingly, the lytic-essential late DDR protein 53BP1 is present in lytic cells prior to viral genome replication but subsequently absent from VRCs and host chromatin, indicating spatial and kinetic DDR dysregulation during EBV reactivation. Collectively, these data support a model wherein EBV transiently employs host DSB DDR mediators to initiate genome replication while a host-targeted DDR is initiated but impaired. We further demonstrate biological generalizability and utility of the method across confocal and epifluorescence systems. Thus, this work demonstrates a powerful technique to recover host-virus dynamics from static timepoints and will support future high-throughput single-cell virology applications.

microbiology↗

bioRxiv2022

Fate-resolved gene regulatory signatures of individual B lymphocytes in the early stages of Epstein-Barr Virus infection

Epstein-Barr Virus (EBV) infection of B lymphocytes elicits diverse host responses via complex, well-adapted transcriptional control dynamics. Consequently, this host-pathogen interaction provides a powerful system to explore fundamental cellular processes that contribute to consensus fate decisions including cell cycle arrest, apoptosis, proliferation, and differentiation. Here we capture these responses and fates with matched single-cell transcriptomics and chromatin accessibility, from which we construct a genome-wide multistate model of early infection dynamics. Notably, our model captures a previously uncharacterized EBV+ analog of a multipotent activated precursor state that can yield early memory B cells. We also find that a marked global reduction in host chromatin accessibility occurs during the first stages of infection in subpopulations of EBV+ cells that display senescent and pre-apoptotic hallmarks induced by innate antiviral sensing and proliferation-linked DNA damage. However, cells in proliferative infection trajectories exhibit greater accessibility at select host sites linked to B cell activation and survival genes as well as key regions within the viral genome. To further investigate such loci, we implement a bioinformatic workflow (crisp-ATAC) to identify phenotype-resolved regulatory signatures. This customizable method applies user-specified logical criteria to produce genome-wide single-cell ATAC-and ChIP-seq range intersections that are used as inputs for cis-linkage prediction and ontology tools. The resulting tri-modal data yield exquisitely detailed hierarchical perspectives of the transforming regulatory landscape during critical stages of an oncogenic viral infection that simulates antigen-induced B cell activation and differentiation. We anticipate these resources will guide investigations of gene regulatory modules controlling EBV-host dynamics, B cell effector fates, and lymphomagenesis. To demonstrate the utility of this resource, this work concludes with the discovery of EBV infection dynamics in FCRL4+ / TBX21+ Tissue-Like Memory B cells, an unconventional subset with notable associations to numerous immune disorders.

immunology↗

bioRxiv2021

Comparing instance segmentation methods for analyzing clonal growth of single cells in microfluidic chips

Appropriately tailored segmentation techniques can extract detailed quantitative information from biological image datasets to characterize and better understand sample distributions. Practically, high-resolution characterization of biological samples such as cell populations can provide insights into the sources of variance in biomarker expression, drug resistance, and other phenotypic aspects, but it is still unclear what is the best method for extracting this information from large image-based datasets. We present a software pipeline and comparison of multiple image segmentation methods to extract single-cell morphological and fluorescence quantitation from time lapse images of clonal growth rates using a recently reported microfluidic system. The inputs in all pipelines consist of thousands of unprocessed images and the outputs are the detection of cell counts, chamber identifiers, and individual morphological properties of each clone over time detected through multi-channel fluorescence and bright field imaging. Our conclusion is that unsupervised learning methods for cell segmentation substantially outperform supervised statistical methods with respect to accuracy and have key advantages including individual cell instance detection and flexibility through model training. We expect this system and software to have broad utility for researchers interested in high-throughput single-cell biology.

bioengineering↗

bioRxiv2020

Massively parallel quantification of phenotypic heterogeneity in single cell drug responses

Single cell analysis tools have made significant advances in characterizing genomic heterogeneity, however tools for measuring phenotypic heterogeneity have lagged due to the increased difficulty of handling live biology. Here, we report a single cell phenotyping tool capable of measuring image-based clonal properties at scales approaching 100,000 clones per experiment. These advances are achieved by exploiting a novel flow regime in ladder microfluidic networks that, under appropriate conditions, yield a mathematically perfect cell trap. Machine learning and computer vision tools are used to control the imaging hardware and analyze the cellular phenotypic parameters within these images. Using this platform, we quantified the responses of tens of thousands of single cell-derived acute myeloid leukemia (AML) clones to targeted therapy, identifying rare resistance and morphological phenotypes at frequencies down to 0.05%. This approach can be extended to higher-level cellular architectures such as cell pairs and organoids and on-chip live-cell fluorescence assays.

bioengineering↗

bioRxiv2018

Real-time detection of circulating tumor cells in living animals using functionalized large gold nanorods

Optical coherence tomography (OCT) with significant speckle reduction can be used with highly-scattering contrast agents for noninvasive, contrast-enhanced imaging of living tissue at the cellular scale. The advantages of reduced speckle noise and improved targeted contrast can be harnessed to track objects as small as 2 m in vivo, with the potential for cell tracking and counting in living subjects. Here we demonstrate the use of Large Gold Nanorods (LGNRs) as contrast agents for detecting individual micron-sized polystyrene beads and single myeloma cells in blood circulation using speckle modulating-OCT (SM-OCT). This is the first time that OCT has been used to image at the individual cell scale in vivo. This technical capability presents an exciting opportunity for the dynamic detection and quantification of tumor cells circulating in living subjects.

bioengineering↗

bioRxiv2017

Wide-field dynamic monitoring of immune cell trafficking in murine models of glioblastoma

Leukocyte populations, especially tumor-associated macrophages (TAMs), are capable of mediating both anti- and pro-tumor processes and play significant roles in the tumor microenvironment. Moreover, TAMs have been shown to exert substantial influence on the efficacy of various cancer immunotherapy treatment strategies. Laboratory investigation into the behavior of TAMs has been limited by a lack of methods capable of resolving the in vivo distribution and dynamics of this cell population across wide fields of view. Recent studies have employed magnetic resonance imaging and intravital microscopy in conjunction with nanoparticle labeling methods to detect TAMs and observe their responses to therapeutic agents. Here we describe a novel method to enable high-resolution, wide-field, longitudinal imaging of leukocytes based on contrast-enhanced Speckle-Modulating Optical Coherence Tomography (SM-OCT), which substantially reduces imaging noise. We were able to specifically label TAMs and activated microglia in vivo with large gold nanorod contrast agents (LGNRs) in an orthotopic murine glioblastoma model. After labeling, we demonstrated near real-time tracking of leukocyte migration and distribution within the tumors. The intrinsic resolution, imaging depth, and sensitivity of this method may facilitate detailed studies of the fundamental behaviors of TAMs in vivo, including their intratumoral distribution heterogeneity and the roles they play in modulating cancer proliferation. In future studies, the method described herein may also provide the necessary means to characterize TAM responses to immunotherapeutic regimens in a range of solid tumors.

bioengineering↗