Biology subjects

Park, D. J.

Publications and source records attributed to Park, D. J..

12 recordsLinked to original sources

bioRxiv2026

TOX enforces the immunosuppressive program of tumor-infiltrating regulatory T cells

Regulatory T (Treg) cells accumulate in the tumor microenvironment (TME) to suppress anti-tumor immunity, but the transcriptional regulators stabilizing their immunosuppressive state remain poorly defined. Here we show that transcriptional factor TOX is selectively upregulated in tumor-infiltrating (TI) Treg cells across human cancers and mouse tumor models, while remaining low in peripheral and naive Treg populations. Treg-specific deletion of TOX reduced tumor burden, impaired TI Treg-mediated immune suppression, and enhanced effector functions of CD8 and CD4 T cells. In mosaic mice, TOX-deficient Tregs were selectively depleted from tumors, accompanied by increased apoptosis. Single-cell RNA sequencing and TCR clonotype analysis linked TOX expression to an effector-like TI Treg state with clonal expansion, whereas TOX loss shifted cells toward a TCF7-associated progenitor-like phenotype. ATAC-seq revealed enrichment of AP-1 motifs in TOX-sufficient TI Tregs. In contrast, TCF7, LEF1, and FOXO1 motifs in TOX-deficient counterparts, uncovering the opposing transcriptional networks downstream of TOX. Furthermore, TOX deficiency augmented CD8 T cell responses to PD-1 blockade. Together, these findings establish TOX as a key regulator of TI Treg fitness and stability, and identify it as a potential therapeutic target to enhance the efficacy of PD-1-based immunotherapy.

immunology↗

bioRxiv2025

Radiosensitizers in Cancer Therapy: A Global Bibliometric Analysis

Background/ObjectivesRadiosensitizers are compounds given concurrently with radiotherapy to enhance the killing of cancer cells while sparing healthy tissue. Radiosensitization research has involved a diverse range of therapeutic agents. In the present study, we aimed to investigate international trends in the development of radiosensitizers across the most common cancer types. MethodsA bibliometric analysis was performed of the field of radiosensitizer research from 1956 to 2024. Individual author impacts and trends, collaborations between and productivity of countries, and themes/keywords were analyzed. ResultsOur search yielded 12,690 results. The most highly represented countries were the United States of America, China, and Germany. Radiosensitizer studies for breast cancers demonstrated the highest rate of annual growth in record count by comparison with other cancer types, while publications for gynecological cancers showed the slowest growth. The most common radiosensitizers investigated included ATM kinase inhibitors, chemotherapies, gold nanoparticles, mTOR inhibitors, natural compounds such as caffeine or curcumin, and poly (ADP-ribose) polymerase inhibitors. ConclusionsThe United States, Germany, and China were the most productive countries during the study period, with China demonstrating the greatest increase in annual publication rate. Additionally, pre-clinical studies primarily investigated gold particles and targeted therapies. By comparison, clinical studies focused on radiosensitizing chemotherapies.

cancer biology↗

bioRxiv2025

Delphy: scalable, near-real-time Bayesian phylogenetics for outbreaks

Pathogen genomic analysis is central to tracking, understanding, and containing outbreaks, but complexity and high costs of state-of-the-art (SOTA) phylogenetic tools limit global access and impact. We introduce Delphy, an exact reformulation of Bayesian phylogenetics designed to transform its speed, scalability and accessibility while retaining SOTA accuracy. Delphys central data structure, an Explicit Mutation Annotated Tree, exploits the high sequence similarity in large-scale epidemic datasets for efficient tree exploration and convergence. By reproducing key analyses from recent major epidemics (Ebola, Zika, SARS-CoV-2, mpox, and H5N1), we demonstrate SOTA accuracy with up to 1,000x speedups. Assessing Delphys scalability, we show that a simulated dataset of 100,000 sequences can be analyzed in under a day-the largest such computation to date. We distribute Delphy as a client-side web application, enabling users worldwide to turn raw data into interactive results within minutes, without the data ever leaving the users machine. Delphy automatically identifies key viral lineages and mutations, as well as their emergence and prevalence through time, all with quantified uncertainties derived from a solid theoretical foundation. Delphy shows the power of Bayesian phylogenetics as a fast, accessible frontline tool for tackling future outbreaks.

genomics↗

bioRxiv2024

Reproductive modes of polyploid Ludwigia grandiflora subsp. hexapetala in western Europe: the effects of a late-acting self-incompatibility system and its absence on genetic diversity within populations

Reproductive mode, i.e., the proportion of individuals produced by clonality, selfing and outcrossing in populations, determines how hereditary material is transmitted through generations. It shapes genetic diversity and its structure over time and space, which can be used to infer reproductive modes. Ludwigia grandiflora subsp. hexapetala (Lgh) is a partially clonal, polyploid, hermaphroditic, and heteromorphic plant that recently colonized multiple countries worldwide. In western Europe, individuals are either self-incompatible caused by a late-acting self-incompatibility (LSI) system developing long-styled flowers, or self-compatible (SC), with short-styled flowers. In this study, we genotyped 53 long- and short-styled populations newly colonizing France and northern Spain using SNPs to estimate rates of clonality, selfing and outcrossing. We found that populations reproduced mainly clonally but with a high diversity of genotypes along with rates of sexuality ranging from 10% up to 40%. We also found evidence for local admixture between long- and short-styled populations in a background of genetic structure between floral morphs that was twice the level found within morphs. Long- and short-styled populations showed similar rates of clonality but short-styled populations presented significantly higher rates of selfing, as expected considering their breeding system, and despite the small rates of failure of the LSI system. Within the 53 studied populations, the 13 short-styled populations had fewer effective alleles, lower observed heterozygosity, and higher inbreeding coefficients, linkage disequilibrium and estimates of selfing than what was found in long-styled populations. These results emphasize the necessity to consider the variation of reproductive modes when managing invasive plant species. The overall maintenance of higher genetic diversity with the possibility of maintaining populations clonally in the absence of compatible partners may explain why long-styled individuals seem to be more prevalent in all newly expanding populations worldwide. Beyond Lgh, our methodological approach may inspire future studies to assess the reproductive modes in other autopolyploid populations.

evolutionary biology↗

bioRxiv2023

Functional implication of the homotrimeric multidomain vacuolar sorting receptor 1 (VSR1) from Arabidopsis thaliana

The vacuolar sorting receptors (VSRs) are specific to plants and are responsible for sorting and transporting particular proteins from the trans-Golgi network to the vacuole. This process is critically important for various cellular functions, including storing nutrients during seed development. Despite many years of intense studies on VSRs, a complete relation between function and structure has not yet been revealed. For the first time, the crystal structure of the full-length luminal part of glycosylated VSR1 from Arabidopsis thaliana (AtVSR1) has been determined. The structure provides insights into the tertiary and quaternary structures of VSR1, which are composed of an N-terminal protease-associated (PA) domain, a unique central region, and one epidermal growth factor (EGF) domain followed by two disordered EGF domains. The structure of VSR1 exhibits unique characteristics, the significance of which is yet to be fully understood.

plant biology↗

bioRxiv2021

DNA spike-ins enable confident interpretation of SARS-CoV-2 genomic data from amplicon-based sequencing

The rapid global spread and continued evolution of SARS-CoV-2 has highlighted an unprecedented need for viral genomic surveillance and clinical viral sequencing. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine lab processes and results. This challenge will only increase with expanding global production of sequences by diverse research groups for epidemiological and clinical interpretation. We present an approach which uses synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination through a sequencing workflow. Applying this approach to the ARTIC Consortiums amplicon design, we define a series of best practices for Illumina-based sequencing and provide a detailed characterization of approaches to increase sensitivity for low-viral load samples incorporating the SDSIs. We demonstrate the utility and efficiency of the SDSI method amidst a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases.

molecular biology↗

bioRxiv2020

Enhanced virus detection and metagenomic sequencing in patients with meningitis and encephalitis

Meningitis and encephalitis are leading causes of central nervous system (CNS) disease and often result in severe neurological compromise or death. Traditional diagnostic workflows largely rely on pathogen-specific diagnostic tests, sometimes over days to weeks. Metagenomic next-generation sequencing (mNGS) is a high-throughput platform that profiles all nucleic acid in a sample. We prospectively enrolled 68 patients from New England with known or suspected CNS infection and performed mNGS from both RNA and DNA to identify potential pathogens. Using a computational metagenomic classification pipeline based on KrakenUniq and BLAST, we detected pathogen nucleic acid in cerebrospinal fluid (CSF) from 22 subjects. This included some pathogens traditionally diagnosed by serology or not typically identified in CSF, including three transmitted by Ixodes scapularis ticks (Powassan virus, Borrelia burgdorferi, Anaplasma phagocytophilum). Among 24 subjects with no clinical diagnosis, we detected enterovirus in two subjects and Epstein Barr virus in one subject. We also evaluated two methods to enhance detection of viral nucleic acid, hybrid capture and methylated DNA depletion. Hybrid capture nearly universally increased viral read recovery. Although results for methylated DNA depletion were mixed, it allowed detection of varicella zoster virus DNA in two samples that were negative by standard mNGS. Overall, mNGS is a promising approach that can test for multiple pathogens simultaneously, with similar efficacy to pathogen-specific tests, and can uncover geographically relevant infectious CNS disease, such as tick-borne infections in New England. With further laboratory and computational enhancements, mNGS may become a mainstay of workup for encephalitis and meningitis. ImportanceMeningitis and encephalitis are leading global causes of central nervous system (CNS) disability and mortality. Current diagnostic workflows remain inefficient, requiring costly pathogen-specific assays and sometimes invasive surgical procedures. Despite intensive diagnostic efforts, 40-60% of people with meningitis or encephalitis have no clear cause of their CNS disease identified. As diagnostic uncertainty often leads to costly inappropriate therapies, the need for novel pathogen detection methods is paramount. Metagenomic next-generation sequencing (mNGS) offers the unique opportunity to circumvent these challenges using unbiased laboratory and computational methods. Here, we performed comprehensive mNGS from 68 patients with suspected CNS infection, and define enhanced methods to improve the detection of CNS pathogens, including those not traditionally identified in the CNS by nucleic acid detection. Overall, our work helps elucidate how mNGS can become a mainstay in the diagnostic toolkit for CNS infections.

neuroscience↗

bioRxiv2020

Deployable CRISPR-Cas13a diagnostic tools to detect and report Ebola and Lassa virus cases in real-time

Viral hemorrhagic fevers (VHFs) remain some of the most devastating human diseases, and recent outbreaks of Ebola virus disease (EVD) 1,2 and Lassa fever (LF) 3,4 highlight the urgent need for sensitive, field-deployable tests to diagnose them 5,6. Here we develop CRISPR-Cas13a-based (SHERLOCK) diagnostics targeting Ebola virus (EBOV) and Lassa virus (LASV), with both fluorescent and lateral flow readouts. We demonstrate on laboratory and clinical samples the sensitivity of these assays and the capacity of the SHERLOCK platform to handle virus-specific diagnostic challenges. Our EBOV diagnostic detects both the L and NP genes, thereby eliminating the potential for false positive results caused by the rVSV{Delta}G-ZEBOV-GP live attenuated vaccine. Our two LASV diagnostics together capture 90% of known viral diversity and demonstrate that CRISPR-RNAs (crRNAs) can be effectively multiplexed to provide greater coverage of known viral diversity. We performed safety testing to demonstrate the efficacy of our HUDSON protocol in heat-inactivating and chemically treating VHF viruses before SHERLOCK testing, eliminating the need for an extraction. We developed a user-friendly field protocol and mobile application (HandLens) to report results, facilitating SHERLOCKs use in endemic regions. Finally, we successfully deployed our tests in Sierra Leone and Nigeria in response to recent outbreaks.

molecular biology↗

bioRxiv2018

Co-circulating mumps lineages at multiple geographic scales

Despite widespread vaccination, eleven thousand mumps cases were reported in the United States (US) in 2016-17, including hundreds in Massachusetts, primarily in college settings. We generated 203 whole genome mumps virus (MuV) sequences from Massachusetts and 15 other states to understand the dynamics of mumps spread locally and nationally, as well as to search for variants potentially related to vaccination. We observed multiple MuV lineages circulating within Massachusetts during 2016-17, evidence for multiple introductions of the virus to the state, and extensive geographic movement of MuV within the US on short time scales. We found no evidence that variants arising during this outbreak contributed to vaccine escape. Combining epidemiological and genomic data, we observed multiple co-circulating clades within individual universities as well as spillover into the local community. Detailed data from one well-sampled university allowed us to estimate an effective reproductive number within that university significantly greater than one. We also used publicly available small hydrophobic (SH) gene sequences to estimate migration between world regions and to place this outbreak in a global context, but demonstrate that these short sequences, historically used for MuV genotyping, are inadequate for tracing detailed transmission. Our findings suggest continuous, often undetected, circulation of mumps both locally and nationally, and highlight the value of combining genomic and epidemiological data to track viral disease transmission at high resolution.

genomics↗

bioRxiv2018

Capturing diverse microbial sequence with comprehensive and scalable probe design

Metagenomic sequencing has the potential to transform microbial detection and characteri zation, but new tools are needed to improve its sensitivity. We developed CATCH (Compact Aggregation of Targets for Comprehensive Hybridization), a computational method to enhance nucleic acid capture for enrichment of diverse microbial taxa. CATCH designs compact probe sets that achieve full coverage of known sequence diversity and that scale well with this diversity. To illustrate applications of CATCH, we focused on capturing viral genomes. We designed, synthesized, and validated multiple probe sets, including one that targets whole genomes of the 356 viral species known to infect humans. Capture with these probe sets enriched unique viral content on average 18x and allowed us to assemble genomes that we could not otherwise recover, while accurately preserving within-sample diversity. We used this approach to recover genomes from the 2018 Lassa fever outbreak in Nigeria and to improve detection of viral infections in samples with unknown content. Together, this work demonstrates a path toward more sensitive, cost-effective metagenomic sequencing.

genomics↗

bioRxiv2017

Genome sequencing reveals Zika virus diversity and spread in the Americas

Despite great attention given to the recent Zika virus (ZIKV) epidemic in the Americas, much remains unknown about its epidemiology and evolution, in part due to a lack of genomic data. We applied multiple sequencing approaches to generate 110 ZIKV genomes from clinical and mosquito samples from 10 countries and territories, greatly expanding the observed viral genetic diversity from this outbreak. We analyzed the timing and patterns of introductions into distinct geographic regions; our phylogenetic evidence suggests rapid expansion of the outbreak in Brazil and multiple introductions of outbreak strains into Puerto Rico, Honduras, Colombia, other Caribbean islands, and the continental US. We find that ZIKV circulated undetected in multiple regions for many months before the first locally transmitted cases were confirmed, highlighting the importance of viral surveillance. We identify mutations with possible functional implications for ZIKV biology and pathogenesis, as well as those potentially relevant to the effectiveness of diagnostic tests.

genomics↗

bioRxiv2017

Multiple introductions of Zika virus into the United States revealed through genomic epidemiology

Zika virus (ZIKV) is causing an unprecedented epidemic linked to severe congenital syndromes1,2. In July 2016, mosquito-borne ZIKV transmission was first reported in the continental United States and since then, hundreds of locally-acquired infections have been reported in Florida3. To gain insights into the timing, source, and likely route(s) of introduction of ZIKV into the continental United States, we tracked the virus from its first detection in Miami, Florida by direct sequencing of ZIKV genomes from infected patients and Aedes aegypti mosquitoes. We show that at least four distinct ZIKV introductions contributed to the outbreak in Florida and that local transmission likely started in the spring of 2016 - several months before its initial detection. By analyzing surveillance and genetic data, we discovered that ZIKV moved among transmission zones in Miami. Our analyses show that most introductions are phylogenetically linked to the Caribbean, a finding corroborated by the high incidence rates and traffic volumes from the region into the Miami area. By comparing mosquito abundance and travel flows, we describe the areas of southern Florida that are especially vulnerable to ZIKV introductions. Our study provides a deeper understanding of how ZIKV initiates and sustains transmission in new regions.

epidemiology↗