Biology subjects

Lu, E.

Publications and source records attributed to Lu, E..

11 recordsLinked to original sources

bioRxiv2026

Engineering Persistent and Rewritable Genetic Memory in Bacteria through Multiscale Plasmid Competition

Genetic memory enables bacteria to record transient stimuli as persistent genetic states, providing a foundation for cellular information storage, sensing, and computation. Recombinase-based memories encode discrete states through rewritable DNA rearrangements, but these states can continue to evolve after stimulus removal as cells proliferate. Here, we show that the long-term stability of reversible recombinase-based memory can be engineered by controlling post-switching dynamics. We identify a temporal hierarchy in which heterogeneous states arising from imperfect recombinase orthogonality are first resolved through intracellular competition between incompatible plasmids and subsequently reshaped by fitness differences between cells carrying alternative states. Reducing DNA copy number accelerates intracellular state resolution and decreases expression-associated fitness costs, while tuning state-specific gene expression balances the relative fitness of alternative memory states. Using these principles, we engineer a reversible memory device that maintains its two states for up to two weeks while retaining rewritability after prolonged maintenance. Our results establish a framework for engineering persistent and rewritable genetic memory through control of intracellular competition and population-level fitness.

synthetic biology↗

bioRxiv2026

Time-Resolved Phenotypic and Transcriptomic Responses of Primary Canine Dermal Fibroblasts to Prolonged Hypothermic Stress

Prolonged low-temperature exposure may extend the preservation window of mammalian cells but can also disrupt cellular homeostasis and ultimately compromise cell viability. This study investigated the time-dependent phenotypic and transcriptomic responses of primary canine dermal fibroblasts to sustained hypothermic stress. Passage-three fibroblasts were continuously maintained at 15 for up to 15 days, with samples collected on Days 0, 3, 6, 9, 12, and 15. Cellular morphology, metabolic activity and viability, and apoptosis were evaluated using bright-field microscopy, Cell Counting Kit-8 assays, and Annexin V-FITC/propidium iodide flow cytometry, respectively. RNA sequencing was performed to characterize dynamic transcriptional changes throughout the exposure period. Early low-temperature exposure was associated with relatively preserved cellular morphology and viability, suggesting a transient adaptive response. With increasing exposure duration, fibroblasts exhibited progressive morphological deterioration, reduced metabolic activity, loss of adhesion, and increased apoptosis. Time-series transcriptomic analysis further revealed temporally coordinated and stage-dependent gene-expression programs associated with metabolic regulation, cellular stress responses, structural homeostasis, and cell survival. Integration of phenotypic and transcriptomic data demonstrated that the response of primary canine dermal fibroblasts to 15 was dynamic rather than linear, progressing from early adaptation to cumulative dysfunction during prolonged exposure. These findings provide a framework for defining the low-temperature tolerance of primary canine dermal fibroblasts and may inform the optimization of protocols for their short- to medium-term preservation and transportation.

cell biology↗

bioRxiv2026

A Systematic Approach Toward Implementing Machine Learning Techniques to Analyze Gut Microbiome Data

This study investigates the relationship between the gut microbiota and specific diseases. Data was collected from the Human Gut Microbiome Atlas, which examines regional variations across 20 countries on five continents, categorizing microbial species by taxonomy, from genus to species. The Atlas provides color-coded phylum classifications, numerical species counts within the same genus, and an analysis of dysbiosis-related associations with 23 diseases, as well as region-enriched species. The data stratified samples into distinct categories such as westernized, non-westernized, cancerous, and non-cancerous. The findings demonstrate that tree-based ensemble methods, such as Bagging and Boosting prediction methods, achieved the highest accuracies across all categories due to their robustness in handling the complex, high-dimensional data. The XGBoost model yielded the strongest predictive performance, achieving 91% accuracy for westernized cancer-associated samples, 84% accuracy for non-westernized cancer-associated samples, 92% accuracy for westernized samples, and 78% for non-westernized samples. Additionally, advanced topological data analysis was used to assess the global structure and underlying patterns within the dataset. ImportanceThis research aims to connect gut microbiome composition to diseases using global datasets from the Human Gut Microbiome Atlas. The goal was to evaluate how accurately different machine learning algorithms could classify microbiota species and diseases and predict disease associations by comparing westernized and non-westernized populations, including both cancerous and noncancerous groups. These findings can contribute to the future creation of population-specific and disease-specific microbial models.

bioinformatics↗

bioRxiv2025

Differentiation-Dependent Proximity Proteomics Identifies Novel Host Factors Linked to HPV16 E2 Function

Human papillomavirus 16 (HPV16) is a causative agent of oropharyngeal, cervical and anogenital cancers. The viral E2 protein is essential for viral genome replication, transcriptional regulation, episome maintenance, and activation of the host DNA damage response. Despite its central role, the full network of HPV16 E2 interactions with host proteins remains incompletely defined, particularly under differentiating conditions which support the complete viral life cycle. In this study, we used TurboID-based proximity labeling to characterize the interactome of HPV16 E2 and known host partner protein TOPBP1, in both undifferentiated monolayer and differentiating keratinocytes. We generated stable keratinocyte lines expressing doxycycline-inducible TurboID-tagged HPV16 E2 and confirmed that the tagged protein retained transcriptional, replicative, and DNA damage-inducing functions. Mass spectrometry analysis of streptavidin-enriched proteins identified both known and novel E2-associated host factors, including chromatin regulators, DNA repair proteins, and nucleolar components. Comparative analysis revealed a substantial overlap between E2 and TOPBP1 interactomes, and in situ validation by proximity ligation assay identified nucleolin (NCL) as a differentiation-dependent factor whose interaction with E2 is stabilized by TOPBP1. Functional studies demonstrated that NCL is required for episomal genome maintenance, highlighting a cooperative E2-TOPBP1- NCL axis critical for viral genome stability during differentiation. These findings provide a comprehensive view of the E2-associated protein landscape in stratified epithelial cells and reveal a mechanistic pathway through which HPV16 co-opts host factors to support genome maintenance, productive replication, and persistence. ImportanceHuman papillomaviruses (HPVs) establish persistent infections in stratified epithelia and rely on host DNA damage and repair factors to support their replication. The E2 protein is central to viral genome replication and maintenance, and depends heavily on its interaction with the host factor TOPBP1 for these functions. Here, we define the E2 and TOPBP1 interactomes in differentiating keratinocytes, and identify nucleolin (NCL) a critical differentiation- and TOPBP1-dependent E2 partner required for episomal genome stability. These findings expand the understanding of how HPV16 coordinates viral replication with host chromatin and DNA repair networks, uncovering a cooperative E2-TOPBP1-NCL axis that may represent a new target for antiviral intervention.

cancer biology↗

bioRxiv2025

Lateral Hypothalamic Glutamate and GABA Neurons Cooperatively Shape Striatum-Wide Dopamine Dynamics During Consumption

The lateral hypothalamic area (LHA) contains GABAergic and glutamatergic neurons that converge on the midbrain dopamine system and exert opposing influences on consummatory feeding behavior. However, the activity dynamics of these populations during consumption and their impact on striatal dopamine release remain poorly understood. Here, we show that LHA GABAergic and glutamatergic neurons independently scale their activity during the consumption of rewarding and aversive solutions while cooperatively regulating dopamine release along the anterior-posterior axis of the striatum in mice. Dopamine release exhibited widespread modulation during consumption, with anterior striatal regions showing stronger representation of solution value and its recent history--an effect dependent on LHA activity. These findings suggest that the LHA acts as a central regulator of striatal dopamine release during consumption, providing a mechanism through which hypothalamic circuits influence motivational and consummatory behaviors.

neuroscience↗

bioRxiv2025

Phenotypic pleiotropy of missense variants in human B cell-confinement receptor P2RY8

Missense variants can have pleiotropic effects on protein function and predicting these effects can be difficult. We performed near-saturation deep mutational scanning of P2RY8, a G-protein-coupled receptor that promotes germinal center B cell confinement. We assayed the effect of each variant on surface expression, migration, and proliferation. We delineated variants that affected both expression and function, affected function independently of expression, and discrepantly affected migration and proliferation. We also used cryo-electron microscopy to determine the structure of activated, ligand-bound P2RY8, providing structural insights into the effects of variants on ligand binding and signal transmission. We applied the deep mutational scanning results to both improve computational variant effect predictions and to characterize the phenotype of germline variants and lymphoma-associated variants. Together, our results demonstrate the power of integrating deep mutational scanning, structure determination, and in silico prediction to advance the understanding of a receptor important in human health.

genomics↗

bioRxiv2025

Neuron type-specific mRNA translation programs provide a gateway for memory consolidation.

Long-term memory consolidation is a dynamic process that requires a heterogeneous ensemble of neurons, each with a highly specialized molecular signature. Considerable effort has been devoted to identifying molecular changes that accompany the process of consolidation, but mostly hours or days after training, when memory consolidation is already complete. Studies have shown that protein synthesis is elevated during the early stages of consolidation, but how this increase impacts neuronal function remains unclear. We hypothesize that mRNAs translated during the early stages of consolidation could provide information on how diverse neurons involved in memory formation restructure their molecular signatures to support memory. Here, we generate a landscape of the translatome of three neuron types in the dorsal hippocampus during the first hour of contextual memory consolidation. Our results reveal that translation programs associated with consolidation are different among neurons, fueling the reconfiguration of specific biological processes. We further demonstrate the patterned translation of mRNAs in different neuron types during consolidation is explained by features hard-coded in the mRNA sequence, suggesting ubiquitous mechanisms controlling activity-induced neuronal translation. Altogether, our work uncovers previously unknown mechanisms controlling activity-induced translation in neurons and provides a large, readily available resource for scientists interested in the role of memory formation in health and disease.

neuroscience↗

bioRxiv2023

Identification of an allele-specific transcription factor binding interaction that regulates PLA2G2A gene expression

The secreted phospholipase A2 (sPLA2) isoform, sPLA2-IIA, has been implicated in a variety of diseases and conditions, including bacteremia, cardiovascular disease, COVID-19, sepsis, adult respiratory distress syndrome, and certain cancers. Given its significant role in these conditions, understanding the regulatory mechanisms impacting its levels is crucial. Genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs), including rs11573156, that are associated with circulating levels of sPLA2-IIA. Through Genotype-Tissue Expression (GTEx), 234 expression quantitative trait loci (eQTLs) were identified for the gene that encodes for sPLA2-IIA, PLA2G2A. SNP2TFBS (https://ccg.epfl.ch/snp2tfbs/) was utilized to ascertain the binding affinities between transcription factors (TFs) to both the reference and alternative alleles of identified SNPs. Subsequently, ChIP-seq peaks highlighted the TF combinations that specifically bind to the SNP, rs11573156. SP1 emerged as a significant TF/SNP pair in liver cells, with rs11573156/SP1 interaction being most prominent in liver, prostate, ovary, and adipose tissues. Further analysis revealed that the upregulation of PLA2G2A transcript levels through the rs11573156 variant was affected by tissue SP1 protein levels. By leveraging an ordinary differential equation, structured upon Michaelis-Menten enzyme kinetics assumptions, we modeled the PLA2G2A transcriptions dependence on SP1 protein levels, incorporating the SNPs influence. Collectively, these data strongly suggest that the binding affinity differences of SP1 for the different rs11573156 alleles can influence PLA2G2A expression. This, in turn, can modulate sPLA2-IIA levels, impacting a wide range of human diseases.

bioinformatics↗

bioRxiv2022

Identifying Strong Modulators of Cellular Quiescence Depth Across Different Quiescent Cells and Conditions

The proper balance and transition between cellular quiescence and proliferation are critical to tissue homeostasis, repair, and regeneration. The likelihood of quiescence-to-proliferation transition is inversely correlated with quiescence depth, and deep quiescent cells are less likely to exit quiescence and reenter the cell cycle than shallow quiescent cells. The regulatory mechanisms of quiescence depth are poorly understood but essential for developing strategies against hypo- or hyper-proliferation diseases such as aging and cancer. Our earlier studies have demonstrated that the activation threshold of the bistable Rb-E2F gene network switch (ThE2F) controls quiescence depth. We have also identified coarse- and fine-tuning ThE2F modulators in rat embryonic fibroblasts. To examine whether other quiescent cells (including most adult stem and progenitor cells) under different environmental conditions use the same or different modulators of quiescence depth, here we studied the behaviors of 30,000 theoretical quiescent cell models that each support a functional Rb-E2F bistable switch with a unique parameter set. We found that although the vastly heterogeneous quiescent cell models exhibited no apparent parameter patterns, they converged at two alternative groups of strong quiescence-depth modulators (G1 cyclin/cdk-related and Rb/E2F complex-related). Our further machine learning (decision tree) analysis suggested that the Rb protein level and dephosphorylation rate in quiescent cells determine which modulator group to use to regulate quiescence depth.

systems biology↗

bioRxiv2021

The cardiac lncRNA Chantico directly regulates Cxcl1 chemokine transcription

Withdrawal StatementThe corresponding author has withdrawn this preprint owing to inability to reproduce some of the data, instances of inappropriate data exclusion, and loss of much of the primary experimental records/data. Specifically, Figures 2B,E,H; 3; 4; 5A,B,D; 6; S2A,C; S4A; S5; and S6A,B and attendant text contain analyses for which the primary record and/or raw data no longer exist; the analyses, where still available, suffer from inappropriate data exclusion and thus should not be construed to be an accurate reflection of the experiments. Attempts by others in the lab to repeat several of the experiments in these indicated panels have failed reproduce the presented effects, despite showing much greater precision. Therefore the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

molecular biology↗

bioRxiv2018

Hedgehog signaling controls progenitor differentiation timing during heart development

Heterochrony, defined as differences in the timing of developmental processes, impacts organ development, homeostasis, and regeneration. The molecular basis of heterochrony in mammalian tissues is poorly understood. We report that Hedgehog signaling activates a heterochronic pathway that controls differentiation timing in multiple lineages. A differentiation trajectory from second heart field cardiac progenitors to first heart field cardiomyocytes was identified by single-cell transcriptional profiling in mouse embryos. A survey of developmental signaling pathways revealed specific enrichment for Hedgehog signaling targets in cardiac progenitors. Removal of Hh signaling caused loss of progenitor and precocious cardiomyocyte differentiation gene expression in the second heart field in vivo. Introduction of active Hh signaling to mESC-derived progenitors, modelled by transient expression of the Hh-dependent transcription factor GLI1, delayed differentiation in cardiac and neural lineages in vitro. A shared GLI1-dependent network in both cardiac and neural progenitors was enriched with FOX family transcription factors. FOXF1, a GLI1 target, was sufficient to delay onset of the cardiomyocyte differentiation program in progenitors, by epigenetic repression of cardiomyocyte-specific enhancers. Removal of active Hh signaling or Foxf1 expression from second heart field progenitors caused precocious cardiac differentiation in vivo, establishing a mechanism for resultant Congenital Heart Disease. Together, these studies suggest that Hedgehog signaling directly activates a gene regulatory network that functions as a heterochronic switch to control differentiation timing across developmental lineages.

developmental biology↗