Biology subjects

Nam, H.

Publications and source records attributed to Nam, H..

At least 19 recordsLinked to original sources

bioRxiv2026

Targeting DNMT1 augments anti-tumor CD8⁺ T cell function

Chronic stimulation of CD8 T cells within the tumor microenvironment (TME) induces a hypofunctional state characterized by diminished cytotoxicity and functionally impaired anti-tumor function, known as exhaustion. Exhaustion is associated with epigenetic changes that remain relatively stable despite interventions like immune checkpoint inhibition (ICI). Although epigenetic changes are potentially reversible, reports of therapeutic strategies to effectively restore function in exhausted CD8 T cells remain limited. Here, we report DNA methyltransferase 1 (DNMT1) inhibition (DNMT1i) in counteracting CD8+ T cell dysfunction during the anti-tumor response. We show that DNMT1i synergizes with ICI to rescue the tumor cell killing activity of chronically stimulated CD8 T cells in a melanoma model. DNMT1i mitigates transcriptional features of exhaustion while inducing a divergent effector program. DNMT1i attenuates the global increase in chromatin accessibility associated with exhaustion and enables epigenetic remodeling of the exhausted chromatin landscape upon restimulation. Finally, DNMT1i enhances the effector function of melanoma patient-derived tumor infiltrating lymphocytes after prolonged ex vivo expansion. These studies establish DNMT1 targeting as a promising strategy to counteract CD8 T cell exhaustion and potentiate ICI efficacy.

immunology↗

bioRxiv2026

A novel mechanism of ceftolozane-tazobactam resistance in Pseudomonas aeruginosa mediated by L2 β-lactamase

The prevalance of non-susceptibility to ceftolozane-tazobactam (C/T) among Pseudomonas aeruginosa remains low but novel mechanisms of C/T resistance are of concern. Herein, we describe a novel Pseudomonas aeruginosa genotype associated with high-level C/T resistance (>256/4 {micro}g/mL) in a single patient. Whole genome sequencing of the isolate was compared to that of a susceptible isolate cultured from the same patient two months earlier. Analysis of the sequences revealed two different P. aeruginosa high-risk clones: ST111 followed by ST235. The C/T-resistant ST235 isolate contained five copies of a genetic element comprised of an L2 {beta}-lactamase gene (blaL2) and a truncated ampRL2 transcriptional regulator gene, which are commonly found together in Stenotrophomonas maltophilia strains and have not been reported to mediate resistance to C/T. Comparative genomic analysis with other P. aeruginosa isolates failed to identify alternative explanations for the observed C/T resistance. We found that exogenous expression of blaL2 modestly increased C/T MICs in genetically distinct P. aeruginosa strains. A screen of our archived isolates identified two P. aeruginosa clinical isolates, PS2045 and PS2046, with one and two copies, respectively, of the genetic element containing blaL2 and truncated ampRL2. Interestingly, disruption of the gene blaL2 but not the truncated ampRL2 in PS2045 led to a significant decrease in C/T MIC. Thus, we report a novel mechanism of C/T resistance in P. aeruginosa mediated by an L2 {beta}-lactamase independently of its canonical regulator AmpRL2.

microbiology↗

bioRxiv2025

AI-Guided Discovery and Optimization of Antimicrobial Peptides Through Species-Aware Language Model

The rise of antibiotic-resistant bacteria drives an urgent need for novel antimicrobial agents. Antimicrobial peptides (AMPs) show promise solutions due to their multiple mechanisms of action and reduced propensity for resistance development. This study introduces LLAMP (Large Language model for AMP activity prediction), a target species-aware AI model that leverages pre-trained language models to predict minimum inhibitory concentration (MIC) values of AMPs. Analysis of attention values allowed us to pinpoint critical amino acid residues (e.g., Trp, Lys, and Phe). Our work demonstrates the potential of AI to expedite the discovery of peptide-based antibiotics to combat antibiotic resistance.

bioinformatics↗

bioRxiv2024

Mechanistic genotype-phenotype translation using hierarchical transformers

Genome-wide association studies have linked millions of genetic variants to biomedical phenotypes, but their utility has been limited by lack of mechanistic understanding and widespread epistatic interactions. Recently, Transformer models have emerged as powerful machine learning architectures with potential to address these and other challenges. Here we introduce the Genotype-to-Phenotype Transformer (G2PT), a framework for modeling hierarchical information flow among variants, genes, multigenic systems, and phenotypes. As proof-of-concept, we train G2PT to model the genetics of metabolic traits including insulin resistance (serum triglycerides-to-HDL ratio), LDL and type-2 diabetes. G2PT predicts these traits with accuracy exceeding state-of-the-art and, unlike other polygenic models, extends to distinct populations not used for training. Predictions of insulin resistance are based on >1,395 variants within 20 systems and include epistatic interactions among variants, e.g. between APOA4 and CETP in phospholipid transfer. This work positions hierarchical graph transformers as a next-generation approach to polygenic risk.

bioinformatics↗

bioRxiv2024

Transformation of meiotic drive into hybrid sterility in Drosophila

Hybrid male sterility is one of the fastest evolving intrinsic reproductive barriers between recently isolated populations. A leading explanation for the evolution of hybrid male sterility involves genomic conflicts with meiotic drivers in the male germline. There are, however, few examples directly linking meiotic drive to hybrid sterility. Here, we report that the Sex-Ratio chromosome of Drosophila pseudoobscura, which causes X-chromosome drive within the USA subspecies, causes near complete male sterility when moved into the genetic background of the Bogota subspecies. In addition, we show that this new form of sterility is genetically distinct from the sterility of F1 hybrid males in crosses between USA males and Bogota females. Our observations provide a tractable study system where non-cryptic drive within species is transformed into strong hybrid sterility between very young subspecies.

genetics↗

bioRxiv2024

PIEZO acts in an intestinal valve to regulate swallowing in C. elegans

Sensations of the internal state of the body play crucial roles in regulating the physiological processes and maintaining homeostasis of an organism. However, our understanding of how internal signals are sensed, processed, and integrated to generate appropriate biological responses remains limited. Here, we show that the C. elegans PIEZO channel, encoded by pezo-1, regulates food movement in the intestine by detecting food accumulation in the anterior part of the intestinal lumen, thereby triggering rhythmical movement of the pharynx, referred to as the pharyngeal plunge. pezo-1 deletion mutants exhibit defects in the pharyngeal plunge, which is rescued by PEZO-1 or mouse PIEZO1 expression, but not by PIEZO2, in a single isolated non-neuronal tissue of the digestive tract, the pharyngeal-intestinal valve. Genetic ablation or optogenetic activation of this valve inhibits or induces the pharyngeal plunge, respectively. Moreover, pressure built in the anterior lumen of the intestine results in a pezo-1-dependent pharyngeal plunge, which is driven by head muscle contraction. These findings illustrate how interoceptive processes in a digestive organ regulate swallowing through the PIEZO channel, providing insights into how interoception coordinates ingestive processes in higher animals, including humans.

neuroscience↗

bioRxiv2024

Rapid and label-free exosome analysis by surface-enhanced Raman spectroscopy using silver nanoparticle substrate based on selective laser ablation and melting of silver nanowire

Early diagnostics of breast cancer is crucial to reduce the risk of cancer metastasis and late relapse. Exosome, which contains distinct information of its origin, can be the target object as a liquid biopsy. However, its low sensitivity and inadequate diagnostic tools interfere with the point-of-care testing (POCT) of the exosome. Recently, Surface-enhanced Raman spectroscopy (SERS), which enables the detection of Raman scattering, has been proved as a promising tool for exosome detection but the fabrication process of SERS probe or substrate is still inefficient and far from large-scale production. This study proposes rapid and label-free detection of breast cancer-derived exosomes by statistical analysis of Raman spectra using silver nanoparticle SERS substrate fabricated by selective laser ablation and melting. Employing silver nanowire and optimizing pulse repetition rate power enable rapid and energy-efficient fabrication of SERS substrate. The functionality including sensitivity, reproducibility, stability, and renewability was evaluated using rhodamine 6G as a probe molecule. Then, the feasibility of POCT was examined by the statistical analysis of Raman spectra of exosomes from malignant breast cancer cells and non-tumorigenic breast epithelial cells. The presented framework is anticipated to be utilized in other biomedical applications, facilitating cost-effective and large-scale production performance.

bioengineering↗

bioRxiv2023

TESOGENASE, An Engineered Nuclease Editor for Enhanced Targeted Genome Integration

Summary/AbstractNon-viral DNA donor template has been widely used for targeted genomic integration by homologous recombination (HR). This process has become more efficient with RNA guided endonuclease editor system such as CRISPR/Cas9. Circular single stranded DNA (cssDNA) has been harnessed previously as a genome engineering catalyst (GATALYST) for efficient and safe targeted gene knock-in. However, the engineering efficiency is bottlenecked by the nucleoplasm trafficking and genomic tethering of cssDNA donor, especially for extra-large transgene integration. Here we developed enGager, enhanced GATALYST associated genome editor system by fusion of nucleus localization signal (NLS) peptide tagged Cas9 with various single stranded DNA binding protein modules through a GFP reporter Knock-in screening. The enGager system assembles an integrative genome integration machinery by forming tripartite complex for engineered nuclease editors, sgRNA and ssDNA donors, thereby facilitate the nucleus trafficking of DNA donors and increase their active local concentration at the targeted genomic site. When applied for genome integration with cssDNA donor templates to diverse genomic loci in various cell types, these enGagers outperform unfused editors. The enhancement of integration efficiency ranges from 1.5- to more than 6-fold, with the effect being more prominent for > 4Kb transgene knock-in in primary cells. We further demonstrated that enGager mediated enhancement for genome integration is ssDNA, but less dsDNA dependent. Using one of the mini-enGagers, we demonstrated large chimeric antigen receptor (CAR) transgene integration in primary T cells with exceptional efficiency and anti-tumor function. These tripartite editors with ssDNA optimized genome engineering system (TESOGENASETM) add a set of novel endonuclease editors into the gene-editing toolbox for potential cell and gene therapeutic development based on ssDNA mediated non-viral genome engineering. HighlightO_LIA reporter Knock-in screening establishes enGager system to identify TESOGENASE editor to improving ssDNA mediated genome integration C_LIO_LIMini-TESOGENASEs developed by fusing Cas9 nuclease with novel ssDNA binding motifs C_LIO_LImRNA mini-TESOGENASEs enhance targeted genome integration via various non-viral delivery approaches C_LIO_LIEfficient functional CAR-T cell engineering by mini-TESOGENASE C_LI

bioengineering↗

bioRxiv2022

IMPASTO: Multiplexed cyclic imaging without signal removal via self-supervised neural unmixing

Spatially resolved proteomics requires a highly multiplexed imaging modality. Cyclic imaging techniques, which repeat staining, imaging, and signal erasure, have been adopted for this purpose. However, due to tissue distortion, it is challenging to obtain high fluorescent signal intensities and complete signal erasure in thick tissue with cyclic imaging techniques. Here, we propose an "erasureless" cyclic imaging method named IMPASTO. In IMPASTO, specimens are iteratively stained and imaged without signal erasure. Then, images from two consecutive rounds are unmixed to retrieve the images of single proteins through self-supervised machine learning without any prior training. Using IMPASTO, we demonstrate 30-plex imaging from brain slices in 10 rounds, and when used in combination with spectral unmixing, in five rounds. We show that IMPASTO causes negligible tissue distortion and demonstrate 3D multiplexed imaging of brain slices. Further, we show that IMPASTO can shorten the signal removal processes of existing cyclic imaging techniques.

bioengineering↗

bioRxiv2021

Distinct properties in ventral pallidum projection neuron subtypes

The ventral pallidum (VP) is central to reward seeking and withdrawal from drugs of abuse. A characteristic of the VP is the diversity of its projection targets. Yet, it remains unknown whether different VP projections also differ in other aspects, such as their transcriptome, physiology and relevance to drug reward. In this study we perform a multimodal dissection of four major projections of the VP - to the lateral hypothalamus (VP[->]LH), ventral tegmental area (VP[->]VTA), lateral habenula (VP[->]LHb) and mediodorsal thalamus (VP[->]MDT) - with physiological, anatomical, genetic and behavioral tools and show significant differences between projections in all aspects. Specifically, the VP[->]LH and VP[->]VTA projections show minimal overlap and stand out as having opposite properties - VP[->]LH neurons show higher excitability compared to VP[->]VTA neurons, different pattern of inputs and differentially expressed genes. Moreover, inhibition of VP[->]LH projections diminishes, while inhibition of VP[->]VTA enhances cocaine preference after cocaine withdrawal. This demonstrates that VP projections are heterogenous neuron populations with different roles in cocaine withdrawal.

neuroscience↗

bioRxiv2021

Activation of Npas1-neurons in the Ventral Pallidum Mediates Stress Susceptibility

AbstractAltered activity of the ventral pallidum (VP) underlies disrupted motivation in stress and drug exposure. The VP is a very heterogeneous structure comprised of many neuron types with distinct physiological properties and projections. Neuronal PAS 1-positive (Npas1+) VP neurons are thought to send projections to brain regions critical for motivational behavior. While Npas1+ neurons have been characterized in the globus pallidus external, there is limited information on these neurons in the VP. To address this limitation, we evaluated the projection targets of the VP Npas1+ neurons and performed RNA-seq on ribosome-associated mRNA from VP Npas1+ neurons to determine their molecular identity. Finally, we used a chemogenetic approach to manipulate VP Npas1+ neurons during social defeat stress (SDS) and behavioral tasks related to anxiety and motivation in Npas1-Cre mice. We employed a similar approach in females using the chronic witness defeat stress (CWDS). We identified VP Npas1+ projections to the nucleus accumbens, ventral tegmental area, medial and lateral habenula, lateral hypothalamus, thalamus, medial and lateral septum, and periaqueductal gray area. VP Npas1+ neurons displayed distinct transcriptomes representing distinct biological processes. Chemogenetic activation of VP Npas1+ neurons increased susceptibility to a subthreshold (S)SDS and anxiety-like behavior in the elevated plus maze and open field while the inhibition of VP Npas1+ neurons enhanced resilience to chronic (C)SDS and CWDS. Thus, the activity of VP Npas1+ neurons modulates susceptibility to social stressors and anxiety-like behavior. Our studies provide new information into VP Npas1+ neuron circuitry, molecular identity, and their role in stress response.

neuroscience↗

bioRxiv2021

Transcriptome profiling of the ventral pallidum reveals a role for pallido-thalamic neurons in cocaine reward

Psychostimulant exposure alters the activity of ventral pallidum (VP) projection-neurons. However, the molecular underpinnings of these circuit dysfunctions are unclear. We used RNA- sequencing to reveal alterations in the transcriptional landscape of the VP that are induced by cocaine self-administration in mice. We then probed gene expression in select VP neuronal subpopulations to isolate a circuit associated with cocaine intake. Finally, we used both overexpression and CRISPR-mediated knockdown to test the role of a gene target on cocaine- mediated behaviors as well as dendritic spine density. Our results showed that a large proportion (55%) of genes associated with structural plasticity were changed 24 hours following cocaine intake. Among them, the transcription factor Nr4a1 (Nuclear receptor subfamily 4, group A, member 1, or Nur77) showed high expression levels. We found that the VP to mediodorsal thalamus (VP[->]MDT) projection neurons specifically were recapitulating this increase in Nr4a1 expression. Overexpressing Nr4a1 in VP[->]MDT neurons enhanced drug-seeking and drug- induced reinstatement, while Nr4a1 knock down prevented self-administration acquisition and subsequent cocaine-mediated behaviors. Moreover, we showed that Nr4a1 negatively regulated spine dynamics in this specific cell subpopulation. Together, our study identifies for the first time the transcriptional mechanisms occurring in VP in drug exposure. Our study provides further understanding on the role of Nr4a1 in cocaine-related behaviors and identifies the crucial role of the VP[->]MDT circuit in drug intake and relapse-like behaviors.

neuroscience↗

bioRxiv2021

Reagent- and actuator-free analysis of individual erythrocytes using three-dimensional quantitative phase imaging and capillary microfluidics

Histopathological examination of blood cells plays a crucial role in the diagnosis of various diseases. However, it involves time-consuming and laborious staining procedures required for microscopic review by medical experts and is not directly applicable for point-of-care diagnosis in resource-limited locations. This study reports a dilution-, actuation- and label-free method for the analysis of individual red blood cells (RBCs) using a capillary microfluidic device and quantitative phase imaging. Blood, without any sample treatment, is directly loaded into a micrometer-thick channel such that it forms a quasi-monolayer inside the channel. The morphological and biochemical properties of RBCs, including hemoglobin concentration, hemoglobin content, and corpuscular volume, were retrieved using the refractive index tomograms of individual RBCs measured using 3D quantitative phase imaging. The deformability of individual RBCs was also obtained by measuring the dynamic membrane fluctuations. The proposed framework applies to other imaging modalities and biomedical applications, facilitating rapid and cost-effective diagnosis and prognosis of diseases.

bioengineering↗

bioRxiv2021

scMM: Mixture-of-experts multimodal deep generative model for single-cell multiomics data analysis.

AO_SCPLOWBSTRACTC_SCPLOWThe recent development in single-cell multiomics analysis has enabled simultaneous detection of multiple traits at the single-cell level, thus providing deeper insights into the cellular phenotypes and functions in diverse tissues. However, currently, it is challenging to infer the joint representations and learn relationships among multiple modalities from complex multimodal single-cell data. Herein, we present scMM, a novel deep generative model-based framework for the extraction of interpretable joint representations and cross-modal generation. scMM addresses the complexity of data by leveraging a mixture-of-experts multimodal variational autoencoder. The pseudocell generation strategy of scMM compensates for the limited interpretability of deep learning models and discovered multimodal regulatory programs associated with latent dimensions. Analysis of recently produced datasets validated that scMM facilitates high-resolution clustering with rich interpretability. Furthermore, we show that cross-modal generation by scMM leads to more precise prediction and data integration compared with the state-of-the-art and conventional approaches.

bioinformatics↗

bioRxiv2021

TGF-B signaling suppresses TCA cycle metabolism in renal cancer.

The Warburg effect is one of most-well studied metabolic phenomenon in cancer cells. For the most part, these studies have focused on enhanced rates of glycolysis observed in various models. The presumption has been that mitochondrial metabolism is suppressed. However, recent studies indicate that the extent of mitochondrial metabolism is far more heterogeneous in tumors than originally presumed. One tumor type with suppression of mitochondrial metabolism is renal cell carcinoma (RCC). Prior studies indicate that suppressed TCA cycle enzyme mRNA expression is associated with aggressive RCC. Yet, the mechanisms that regulate the TCA cycle in RCC remain uncharacterized. Here, we demonstrate that loss of TCA cycle enzyme expression is retained in RCC metastatic tissues. Moreover, proteomic analysis demonstrates that reduced TCA cycle enzyme expression is far more pronounced in RCC relative to other tumor types. Loss of TCA cycle enzyme expression is correlated with reduced expression of the transcription factor peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1) which is also lost in RCC tissues. PGC-1 re-expression in RCC cells restores the expression of TCA cycle enzymes in vitro and in vivo and leads to enhanced glucose carbon incorporation into TCA cycle intermediates. Mechanistically, TGF-{beta} signaling, in concert with histone deacetylase 7 (HDAC7), suppresses TCA cycle enzyme expression. In turn, pharmacologic inhibition of TGF-{beta} restores expression of TCA cycle enzyme expression and suppresses tumor growth in an orthotopic model of RCC. Taken together, our findings reveal a novel role for the TGF-{beta} /HDAC7 axis in global suppression of TCA cycle enzymes in RCC and provide novel insight into the molecular basis of altered mitochondrial metabolism in this malignancy.

cancer biology↗

bioRxiv2019

The Evolution of Placental Invasion and Cancer Metastasis are Causally Linked

Among mammals, the extent of placental invasion is correlated with vulnerability to malignancy. Animals with more invasive placentation (e.g. humans) are more vulnerable to malignancy, whereas animals with a non-invasive placenta (e.g. ruminants) are less likely to develop malignant cancer. To explain this correlation, we propose the hypothesis of Evolved Levels of Invasibility (ELI) positing that the permissiveness of stromal tissue to invasion is a unitary character affecting both placental and cancer invasion. We provide evidence for this hypothesis by contrasting invasion of human and bovine cancer and placental cells into a lawn of stromal cells from different species. We find that both bovine endometrial and skin fibroblasts are more resistant to invasion of placental and cancer cells than their human counterparts. Gene expression profiling identified genes with high expression in human but not bovine fibroblasts. Knocking down of a subset of them in human fibroblasts leads to significantly stronger resistance to cancer cell invasion. Comparative analysis of gene expression among mammals suggests that humans evolved higher vulnerability to malignancy than the eutherian ancestor, possibly as a correlate of more invasive placentation, and boroeutherians evolved to decrease stromal invasibility. Identifying the evolutionary determinants of stromal invasibility can provide significant insights to develop rational anti-metastatic therapeutics.

cancer biology↗

bioRxiv2018

Chemotaxis model for human breast cancer cells based on signal-to-noise ratio

Chemotaxis, a biased migration of cells under a chemical gradient, plays a significant role in diverse biological phenomena including cancer metastasis. Stromal cells release signaling proteins to induce chemotaxis, which further causes organ-specific metastasis. Epidermal growth factor (EGF) is an example of the chemical attractants, and its gradient stimulates metastasis of breast cancer cells. Hence, the interactions between EGF and breast cancer cells have long been a subject of interest for oncologists and clinicians. However, most current approaches do not systematically separate the effects of gradient and absolute concentration of EGF on chemotaxis of breast cancer cells. In this work, we develop a theoretical model based on signal-to-noise ratio to represent stochastic properties and report our microfluidic experiments to verify the analytical predictions from the model. The results demonstrate that even under the same EGF concentration gradients, breast cancer cells can reveal distinct chemotaxis patterns at different absolute concentrations. Moreover, we found that addition of EGF receptor antibody can promote chemotaxis at a low EGF level. This apparently counterintuitive finding suggests that EGF receptor-targeted therapy may stimulate metastasis of breast cancer at a particular condition, which should be considered in anticancer drug design.

biophysics↗

bioRxiv2017

Accurate detection of low-level somatic mutations with technical replication for next-generation sequencing

Accurate genome-wide detection of somatic mutations with low variant allele frequency (VAF, <1%) has proven difficult, for which generalized, scalable methods are lacking. Herein, we describe a new computational method, called RePlow that we developed to detect low-VAF somatic mutations based on simple, library-level replicates for next-generation sequencing on any platform. Through joint analysis of replicates, RePlow is able to remove prevailing background errors in next-generation sequencing analysis, facilitating remarkable improvement in the detection accuracy for low-VAF somatic mutations (up to [~]99% reduction in false positives). The method was validated in independent cancer panel and brain tissue sequencing data. Our study suggests a new paradigm with which to exploit an overwhelming abundance of sequencing data for accurate variant detection.

genomics↗