Biology subjects

Lee, B.

Publications and source records attributed to Lee, B..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Latent brain state dynamics predict early amyloid accumulation and cognitive impairment

Amyloid-{beta} (A{beta}) accumulation is a continuous process central to pathological aging that begins decades before cognitive impairment emerges. While subthreshold A{beta} levels have been linked to future decline in cognitive control, the neural mechanisms connecting this early accumulation to its neurocognitive impact are poorly understood. Brain circuit dynamics, which are essential for cognitive function, may offer a sensitive lens into these initial pathological changes. Here, we tested whether brain state dynamics could serve as sensitive markers for cognitive impairment at an early stage of A{beta} burden. Using the Bayesian Switching Dynamic System (BSDS) model, we identified 4 distinct latent brain states from high-temporal-resolution (800 ms) fMRI data acquired from 116 older adults, including 72 cognitively normal (CN) individuals and 44 with mild cognitive impairment (MCI), during an N-back working-memory task. Adopting a dimensional approach, we examined how latent brain state dynamics relate to early amyloid burden, cognitive performance, and clinical symptoms. While A{beta} levels failed to differentiate clinical groups or predict clinical symptoms and task performance, the dynamics of latent brain states proved highly sensitive to both early A{beta} accumulation and cognition. Canonical correlation analysis revealed a significant relationship between brain state dynamics and early A{beta} burden. Furthermore, the temporal properties of brain states were significantly predictive of working memory performance in CN individuals, a relationship that was selectively disrupted in the MCI group. The features of brain dynamics can also successfully predict cognitive impairment. Our findings establish brain state dynamics as sensitive neural markers of initial A{beta} accumulation and early cognitive impairment, offering a new framework for developing predictive models to identify individuals at risk for future cognitive decline.

neuroscience↗

bioRxiv2026

Who Formed All That Iron?: A Novel Antarctic Chemolithotroph Drives Iron Biomineralization

Iron mineralization has profoundly influenced Earths biogeochemical history1,2, yet the specific mechanisms underlying banded iron formation (BIF) remain unresolved3-5. Here we profile the microbiomes of Holocene sediments beneath the Larsen C Ice Shelf (LCIS), Antarctica6-8, through stratigraphic analysis of sedimentary ancient DNA combined with metagenomics. Distinct microbial phases aligned with glacial facies boundaries, with sub-ice shelf communities dominated by chemolithoautotrophs including an uncultured Thermodesulfovibrionia. This bacterium, visualized by fluorescence in situ hybridization and designated Candidatus Mariimomonas ferrooxydans (phylum Nitrospirota), emerged as a keystone taxon with high network centrality. Its genome encodes Cyc2, a fused porin-cytochrome outer membrane protein implicated in Fe(II) oxidation. Heterologous expression of Cyc2 in Escherichia coli confirmed its ability to catalyze iron oxidation, supporting iron precipitation under dark, anoxic conditions. These pristine LCIS sediments, unaltered since the last glacial maximum, provide a modern analogue for synglacial BIFs deposited during Neoproterozoic Snowball Earth events. Our findings deliver direct genomic and functional evidence for chemolithotrophic iron oxidation, challenge phototroph-centric models of BIF genesis, and highlight microbial iron cycling as a recurring force in Earths geochemical evolution. Beyond Earth, these insights inform interpretations of iron deposits on other planetary bodies.

microbiology↗

bioRxiv2026

PARG inhibition sequesters nuclear PAR-binding proteins, including XRCC1 and its partners, into nuclear condensates to elicit cytotoxicity

DNA breaks activate PARP1/2 to synthesize poly(ADP-ribose) (PAR), which relaxes chromatin and recruits DNA repair factors. Normally, PAR is short-lived, rapidly degraded by poly(ADP-ribose) glycohydrolase (PARG). While PARP1/2 inhibitors are established therapies for homologous recombination (HR)-deficient cancers, predictive biomarkers for PARG inhibition (PARGi) remain undefined. Using parallel genome-wide CRISPR screens with PARP and PARG inhibitors, we show that PARGi is synthetically lethal with loss of several PAR-binding factors, including XRCC1-LIG3, POLB, ALC1/CHD1L, ARH3, and PARG itself, but notably not with HR deficiency. Conversely, loss of PARP1, NMNAT1 (required for nuclear NAD synthesis), or UNG (upstream of APE1 cleavage and PARP1 activation), confers PARGi resistance. Mechanistically, PARGi induces time- and dose-dependent formation of PARP1-and PAR-dependent nuclear condensates containing XRCC1 and associated repair factors in otherwise undamaged cells. These condensates do not harbor active DNA breaks but instead sequester PAR-binding repair proteins, depleting their available nuclear pool and impairing their recruitment to genuine DNA breaks. While our analysis focused on XRCC1, PARG inhibition likely sequesters additional PAR- and PARP1-binding proteins. Thus, we propose that PARGi sequesters PAR-binding proteins to elicit toxicity, explaining the essentiality of PARG (but not PARP1) and identifying the loss of PAR-binding factors as candidate predictive biomarkers for PARG-targeted therapy.

molecular biology↗

bioRxiv2026

A Pan-Cancer Single-Cell Atlas to Evaluate Tumor Identity, Cell Line Concordance, and Dependency Mapping

Bulk RNA sequencing enables pan-cancer transcriptional analyses, but obscures cancer cell-specific programs due to admixture with nonmalignant cells, thereby limiting direct comparison between experimental models and primary tumors. Single-cell RNA sequencing (scRNA-seq) overcomes these limitations; however, the biological interpretability of public datasets is often compromised by variable data quality, inconsistent annotation, and atlas-scale aggregation strategies that prioritize data volume over biological coherence. We therefore developed a stringent integration framework that prioritizes representative malignant transcriptional states. Using Mahalanobis distance-based selection within batch-corrected latent space, we constructed a pan-cancer atlas comprising 135,424 high-quality malignant cells from 499 samples across 36 adult and pediatric cancers. Atlas-derived cancer signatures were used to determine tumor-cell line concordance and project ElasticNet models trained on DepMap CRISPR screens to infer cancer-specific gene dependencies. The scTumor Atlas establishes a scalable framework for tumor identity inference, cancer cell line benchmarking, and systematic identification of genetic vulnerabilities.

cancer biology↗

bioRxiv2026

Temporal dynamics of microbiome communities within urban compost piles undergoing the heat process

Urban composting supports soil health but also intersects with food safety, where compost is produced near farms and communities. Here, we profiled temporal microbiome dynamics across a 6-week heat compost cycle from the urban compost piles using paired physicochemical panels and long-read metagenomics. Nutrient composition and pH shifted with compost age, coinciding with stage-structured microbial succession, including temperature-linked turnover of compost communities from mesophilic to thermotolerant taxa. Bacterial profiles included the presence of antimicrobial resistance genes and foodborne-associated genera early in the cycle, with reduced representation during the thermophilic phase. Analysis of previously unclassified long reads reveals an extensive repertoire of putative bacteriophages, including several complete genomes and candidates linked to foodborne bacteria, and their abundance is coupled to the host abundance. Together, these results support thermophilic composting as a key mitigation step for microbiological hazards in urban-adjacent systems and identify compost piles as a promising reservoir for discovering candidate lytic phages for downstream isolation and host-range testing.

microbiology↗

bioRxiv2026

Borrelia Burgdorferi binds Serum Amyloid A and Modulates Subcutaneous Adipose Tissue Immune Signaling

Borrelia burgdorferi causes over 470,000 infections annually [1]. Following a tick bite, Borrelia spirochetes replicate in human skin and disseminate through tissues, including subcutaneous adipose tissue. Adipose tissue is a complex organ containing non-immune and immune cells that play a significant role in the immune response [2], yet little is known about adipose tissue signaling after Borrelia infection. We investigated the landscape of immune signaling within adipose tissue-resident cells during Borrelia infection in human tissue (skin and adipose tissue) ex vivo. Immune pathways overall were downregulated in adipose tissue during Borrelia infection. Despite this, adipose stem/progenitor cells exhibited increased pro-inflammatory and extracellular matrix (ECM)-related signaling (IL-6, MIF, collagen, laminin, fibronectin), positioning them as key hubs of intercellular communication during infection. Myeloid lineage cells showed cluster-specific upregulation of immune genes such as IL1B and TNF. Network analyses highlighted laminin, and strong outgoing MIF signals in all adipose-resident cell clusters. Among the identified genes modulated after Borrelia infection, we observed reduced expression levels of serum amyloid A in adipose tissue-resident cells, a marker typically elevated in Lyme disease patient serum during acute infection. Here, we show that human serum amyloid A1 and serum amyloid A2 directly bind B. burgdorferi spirochetes, using flow cytometry. Functionally, serum amyloid A2 reduces spirochete viability in vitro in a dose-dependent manner and enhances opsonization and phagocytosis by macrophages. Together, these findings show that adipose tissue is a site of active immune signaling in the setting of Borrelia infection and identifies SAA as a host defense factor against Borrelia.

immunology↗

bioRxiv2026

msmu: a Python toolkit for modular and traceable LC-MS proteomics data analysis based on MuData

Computational workflows for MS-based proteomics remain comparatively fragmented, with heterogeneous data formats and analysis pipelines that hinder their reproducibility, interoperability, and reuse of processed data. We present msmu, an open-source Python package that implements a flexible and reproducible end-to-end pipeline for post-search data preprocessing and statistical analysis. At its core, msmu leverages the highly structured MuData format, empowering comprehensive data provenance, transparency in data sharing and reuse, and interoperability with broader Python ecosystem. Together, msmu represents a unique and significant step toward realizing the FAIR (Findable, Accessible, Interoperable, and Reusable) principles in computational proteomics.

bioinformatics↗

bioRxiv2025

Multidimensional Single-Cell Transcriptomic Profiling of Uterine Leiomyosarcomas Identifies Molecular Subtypes with Distinct Therapeutic Vulnerabilities

Uterine leiomyosarcoma (ULMS) is an orphan disease that frequently recurs and metastasizes, with patients undergoing multiple lines of chemotherapy due to lack of effective therapeutic targets. To address this gap, we used single-cell RNA sequencing and spatial transcriptomic analysis to comprehensively profile ULMS. We uncovered multiple states of tumor cells, including tumor cells with mesenchyme-like features, ischemic tumor cells defined by a MYC program, inflammatory tumor cells with active interferon signaling, and stem cell-like hormone receptor-positive cells. The inferred spatial correlates of these tumor cell states demonstrated unique localization patterns. By correlating these signatures to bulk RNA sequencing data, we demonstrate the relevance of these findings to clinical outcomes. Finally, using the single-cell integration and drug response prediction algorithm (scIDUC), we propose drug predictions that may target specific tumor states. Our findings suggest new avenues for further exploration of individualized and multifaceted therapeutic strategies to treat ULMS.

cancer biology↗

bioRxiv2025

10,239 whole genomes with multiomic and clinical health information as the Korean population multiomic reference dataset

We present Korea10K, the largest genomic dataset of the Korean population, comprising 10,239 high-coverage whole genomes (mean depth 30x) with matched multiomic profiles and phenotype data. Korea10K achieves complete and near-complete discovery of very rare and ultra-rare alleles, respectively, at 9,000 Korean genomes. This dataset provides the high-quality population-specific imputation panel, enabling accurate inference of low-frequency variants. Admixture analyses confirm the genetic homogeneity of the Korean population, despite its diverse Y-chromosomal, mitochondrial, and HLA repertoires. This pattern reflects a long and continuous lineage history characterized by persistent internal admixture and genomic homogenization over thousands of years on the Korean peninsula. We also identified 16.8 million genomic variants that directly modify CG sites by creating or abolishing CG dinucleotides, providing the population-scale evidence of coordinated genomic-epigenomic regulatory mechanism in Koreans.

genomics↗

bioRxiv2025

High-throughput plasma proteomic platforms: Insights from a multi-ethnic Asian cohort

We compared three leading affinity-based and mass-spectrometry-based proteomic platforms (SomaScan11K, Olink Explore HT, Orbitrap Astral with Seer Proteograph [MS-Seer]) in a multi-ethnic Asian cohort, to inform biomarker discovery and functional genomic studies of global populations. We found limited overlap (1,740 proteins) across the three platforms, with modest correlations (0.34-0.10). SomaScan had lower missingness (<1%) and CV (<10%), compared to Olink (51%, 23%) and MS-Seer (12%, 19%). The new assays in Olink Explore HT (absent in Explore3072) primarily drove its higher missingness and CV. The number of phenotypic associations varied by trait, while the number of genetic associations (cis-pQTLs at P<5e-08) were similar for Olink and SomaScan. Protein levels differed between ethnicities, with SomaScan identifying more ethnicity-differentiated proteins than Olink (FDR<0.05). Finally, SomaScan ANML normalization attenuated biologically relevant associations in our study. These findings underscore the importance of platform evaluation and data normalization strategies for application in large-scale, diverse population cohorts.

bioinformatics↗

bioRxiv2025

De novo recovery of Ghana virus, an African bat Henipavirus, reveals differential tropism and attenuated pathogenicity compared to Nipah virus

Henipaviruses (HNVs) like Nipah (NiV) and Hendra (HeV) viruses represent severe zoonotic threats. Ghana virus (GhV), identified in 2012, is the only African bat henipavirus with a near-complete genome assembly. However, without isolates in culture, GhV biology, pathogenicity, and zoonotic potential remain poorly understood. Using reverse genetics, we recovered a full-length infectious clone of GhV at BSL-4 following rational reconstruction of its incomplete 3' leader and modification of a non-canonical transcriptional initiation site. GhV demonstrated restricted receptor tropism (ephrin-B2 but not ephrin-B3) and distinct innate immune antagonism. Replication was attenuated in primary human cells, but was enhanced in bat cells. In Syrian golden hamsters, GhV infection caused no disease or mortality. Furthermore, a chimeric NiV encoding the GhV receptor-binding protein was completely attenuated in vivo, implicating ephrin-B3 receptor usage as a critical determinant of HNV pathogenesis. These findings elucidate GhV zoonotic potential and inform strategies for virus surveillance and control. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/679836v1_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@1e5addcorg.highwire.dtl.DTLVardef@1f96850org.highwire.dtl.DTLVardef@12f842eorg.highwire.dtl.DTLVardef@8f013c_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

A validated set of neural gene reporter mice and chemical tracers tools for mapping knee innervating neurons

Joint pain is an increasing concern for our aging population, as current therapies to slow joint disease progression or reduce pain are largely ineffective and often carry significant health and dependency risks. Age and joint disease induce changes to all tissues that make up the joint, including the dense neural network that innervates the joint. Several studies have correlated joint innervation changes in diseases such as osteoarthritis or rheumatoid arthritis, but little is known about their respective functional consequences. How subtypes of knee-innervating neurons affect pain experience remains relatively uncharacterized. A few studies focused on a single neural subtype due to the limited availability of validated tools to study joint innervation. To better understand the relationship between aging, joint disease, and pain, systematic characterization of nociceptors and other neural subtypes regulating joint homeostasis and pain is urgently needed. This studys objective was to establish a validated molecular and genetic toolbox for accurate mapping of the neuro-architecture in the murine knee. We screened genetic reporter mice, containing different combinations of Cre and Flp recombinase alleles along with recombinase responsive reporter alleles to either highlight peripheral nociceptors or post-ganglionic sympathetic neurons for their specificity and accuracy in labeling specific neural subtypes in the dorsal root ganglia, sympathetic ganglia, and the knee joint. Additionally, we compared the performance of a series of conventional retrograde tracers for effective labelling of sensory and sympathetic neurons innervating the knee joint. The validated molecular and genetic tools identified in this study will facilitate the creation of comprehensive joint innervation maps in physiological and pathological contexts, setting the stage for identifying the cellular and molecular changes responsible for mediating joint pain, a necessary goal for improved therapeutic interventions. Lay summaryJoint diseases, such as Rheumatoid Arthritis and Osteoarthritis significantly affect the neural landscape in joints, impacting pain, balance, and joint health. Understanding these nerve changes can provide insights into the drivers of joint pain and potential treatments. Our study evaluated genetic and conventional neural tracer tools to visualize and track knee innervating nerve fibers. We found two genetic mouse lines that specifically highlight sensory and sympathetic nerves, making them suitable models for knee joint studies. Additionally, the fluorescent tracer True Blue, effectively marks cell bodies of knee-innervating neurons. These tools will help researchers better understand nerve changes in painful joint pathologies.

neuroscience↗

bioRxiv2025

Cytokine control of systemic hypoxia tolerance in Drosophila.

Systemic hypoxia--reduction in oxygen supply to all tissues and organs--occurs in both physiological and pathological conditions in animals. Under these conditions, organisms must adapt their physiology to ensure proper functioning and survival. While extensive research has characterized how individual cells sense and adapt to low oxygen conditions, the mechanisms that coordinate whole-body responses to systemic hypoxia remain poorly understood. In this study, we uncover an interorgan signaling response mediated by the cytokine Unpaired-3 (upd3) that is important for systemic hypoxia tolerance in Drosophila. We demonstrate that hypoxia rapidly induces upd3 expression and activates JAK/STAT signaling in both larvae and adults. Interestingly, we discovered a sex-specific requirement for this pathway, with females requiring upd3 for hypoxia survival while males do not. We also identify the intestine as a critical source of hypoxia-induced upd3 and show that gut-derived upd3 signals to the fat body and oenocytes to mediate hypoxia tolerance by promoting nitric oxide synthase expression. Furthermore, we reveal an unexpected role for the canonical hypoxia response transcription factor HIF-1/sima as a molecular brake, preventing lethal upd3 overproduction, revealing that hypoxia survival requires precise cytokine dosage control. Our findings define a gut-to-fat/oenocyte signaling axis that coordinates systemic hypoxia adaptation, highlighting the complex interplay between classic hypoxia response pathways and cytokine signaling in maintaining organismal homeostasis during oxygen limitation. This work provides important insights into how organisms adapt to systemic hypoxia, with potential implications for understanding systemic hypoxia-related human pathologies such as respiratory disorders and sleep apnea.

physiology↗

bioRxiv2025

Back-projection improves inference from sparsely sampled genomic surveillance data

Highly transmissible SARS-CoV-2 variants have emerged throughout the COVID-19 pandemic, driving new waves of infections. Genomic surveillance data can provide insights into the viruss evolution and biology. However, delayed and limited regional data can introduce biases in epidemiological models, potentially obscuring transmission patterns. To address this issue, we used a novel, variant-specific back-projection model to estimate a distribution of likely infection times from sample collection times. We combined this approach with epidemiological modeling to estimate selection for increased transmission in a way that accounts for the uncertainty in infection times. Tests in simulations demonstrated that our method can make the inference of selection more reliable. We also applied our approach to SARS-CoV-2 data, where it excelled in smoothing and extending data from geographic regions or times with poor sampling. Overall, our method can aid in the reliable identification of mutations and variants with higher transmission rates.

evolutionary biology↗

bioRxiv2025

Optimization of Tissue Clearing Methods and Imaging Conditions for 3D Visualization of the Vasculature of the Adult Murine Knee

The vasculature is an essential regulator of tissue oxygenation, metabolism, and immune surveillance under developmental and homeostatic conditions, as well as in regeneration and disease. Within the musculoskeletal system, blood vessels are involved in bone development and resorption, and they also mediate the inflammatory processes that contribute to diseases affecting the joints, including osteoarthritis. Historically, visualization of vascular networks in joints has been limited to conventional histological approaches due to technical limitations and the inherit structure of the skeletal muscle and bones. Recent advances in optical tissue clearing technologies and 3D fluorescence imaging approaches enabling three-dimensional analysis in whole, intact tissues offer an entree to interrogate musculoskeletal development and disease at a cellular resolution. However, these techniques were not originally developed to image hard mineralized tissues, such as the femur and tibias. To circumvent these challenges, we have optimized tissue decalcification conditions and systematically compared aqueous- and solvent-based tissue clearing approaches to establish an optimal pipeline for clearing and imaging of mineralized tissues with superior resolution of the vasculature. Collectively, this work shows that optical clearing and lightsheet microscopy presents a viable method for generating high-resolution images of the murine hindlimb vasculature, with potential applications in aging and disease modeling.

developmental biology↗

bioRxiv2025

Inferring fitness seascapes from evolutionary histories

Evolutionary dynamics are often conceptualized as walks on an adaptive landscape, with populations climbing toward optimal fitness peaks. However, environmental changes can transform static landscapes into dynamic "fitness seascapes" where natural selection fluctuates in time. Here, we used a path integral approach derived from statistical physics to reveal time-varying selection pressures from genetic sequence data. We found that constraints on the fitness seascape are determined by the screened Poisson equation, which also describes the screening of electric fields in media with mobile charge carriers. In our model, changes in mutation frequencies act as "charges" that reveal the underlying fitness seascape, which is analogous to an electrostatic potential. After validating our method in simulations, we applied it to study how HIV-1 evolves to escape immune control by T cells within individual hosts. Our analysis showed that the fitness benefit of immune escape declines as T cell responses approach their peak intensity, suggesting that functional exhaustion may impair the effectiveness of the immune response against HIV-1. Overall, our approach provides a general framework for capturing the complex dynamics of natural selection in rapidly evolving populations.

evolutionary biology↗

bioRxiv2025

A novel Hox gene promoter fuels the evolution of adaptive phenotypic plasticity

Adaptive phenotypic plasticity allows organisms to display distinct phenotypes in response to variable environments, but little is known about the genomic changes that promote the evolution of plasticity on a macroevolutionary scale. Combining spatial transcriptomics, comparative genomics, and genome editing, we show that temperature-mediated plasticity in the size of eyespot wing patterns in satyrid butterflies, a derived seasonal adaptation evolved [~]80 million years ago in this subfamily, is associated with the taxon-specific evolution of a novel promoter in the Hox gene Antennapedia (Antp). The promoter activates Antp expression specifically in satyrid eyespot center cells, sensitizes these cells to environmental temperatures, and plays a critical role in regulating satyrid eyespot size plasticity. Our study demonstrates that a taxon-specific cis-regulatory innovation in an ancestral developmental gene fueled the evolution of adaptive phenotypic plasticity across a clade of animals.

evolutionary biology↗

bioRxiv2025

H2O2-induced astrocytic collagen triggers neuronal death via fucosylation-dependent glial barrier formation upon ischemic stroke

The cascade of molecular and cellular events leading to neuronal death after a focal ischemic stroke remains enigmatic. Although astrocytes form glial barriers that may protect surrounding tissue, how barriers develop and contribute to neuronal death is unclear. Here, we show that H2O2 induces astrocytic type I collagen (COL1)-production via miR-29-mediated post-transcriptional and fucosylation-dependent post-translational regulations, leading to integrin activation and neuronal death. In photothrombosis (PT)-induced cortical stroke model, PT triggered H2O2-surge, astrogliosis, glial barrier formation, COL1 expression, fibrotic scarring, altered N-glycosylation, neuronal loss, and neurological deficits. Remarkably, these effects were reversed by astrocyte-specific COL1 or FUT8 gene-silencing or treatment with KDS12025, an H2O2-decomposing peroxidase enhancer. KDS12025s neuroprotective effects were also recapitulated in non-human primate stroke model. These findings delineate a previously unrecognized astrocyte-driven mechanism in which oxidative stress induces COL1 production, promoting neuronal death, and position H2O2 and astrocytic COL1 and FUT8 as promising therapeutic targets for ischemic stroke.

neuroscience↗