Biology subjects

Ahn, E. H.

Publications and source records attributed to Ahn, E. H..

9 recordsLinked to original sources

bioRxiv2026

Splanchnic-spinal transmission of gut-initiated α-synucleinopathy

Gut-initiated -synucleinopathy is proposed to spread from the gastrointestinal tract to the CNS, contributing to Parkinson's disease (PD), but whether routes beyond the vagus nerve are involved remains unclear. Using complementary intracolonic rotenone and gastroduodenal -synuclein PFF models, we combined pathway-specific surgical interruption with longitudinal behavioral analysis and anatomical mapping of pathological -synuclein. In the intracolonic rotenone model, interruption of the prevertebral ganglia/splanchnic-spinal axis more strongly attenuated behavioral deficits and -synuclein pathology than vagotomy. In the gastroduodenal PFF model, both vagal and splanchnic-spinal pathways contributed to pathology propagation. Early after PFF inoculation, pathological -synuclein was detected in peripheral neural structures associated with both routes. Consistent with these findings, spinal pathology was evident in human PD. Together, these results identify the splanchnic-spinal pathway as a key component of body-first Parkinson's disease, broadening current models of peripheral-to-central disease progression and informing efforts to target early peripheral disease progression.

neuroscience↗

bioRxiv2026

Label-free quantitative 3D mapping of collagen architecture by holotomography

Fibrillar collagen architecture regulates tissue mechanics and cell-matrix interactions, but following how collagen-rich matrices assemble and remodel in three dimensions requires non-destructive measurements that can link structure to matrix-associated mass without exogenous labels. Here we present holotomography (HT) as a label-free platform for volumetric imaging and quantitative profiling of reconstituted fibrillar collagen. Volumetric RI tomograms resolved fibrillar collagen networks without exogenous labels, and co-registration with second-harmonic generation (SHG) microscopy supported the correspondence between HT-resolved RI structures and SHG-positive fibrillar collagen. Curvelet-transform-based segmentation of representative axial sections converted the tomograms into fiber-level descriptors, including morphology, orientation and RI-derived fiber-associated dry mass. At the matched 0.8 mg/mL condition, HT resolved distinct network organization, with type I forming thicker, more sparsely distributed fibers and type III a finer, denser network, while mean fiber-associated RI remained comparable between subtypes. Across the concentration series, type I showed stronger increases in fiber width and RI-derived mass, whereas type III remained comparatively fine. Time-lapse HT further captured RI dynamics during type I fibrillogenesis and visualized local cell-matrix reorganization in HT1080 cell-embedded gels, capturing cells and surrounding matrix in a single label-free measurement. Together, these results position HT as a complementary label-free approach for volumetric visualization and RI-based quantification of collagen-rich extracellular matrices.

cell biology↗

bioRxiv2026

Deep-learning-enabled morphodynamic analysis of drug responses in a biomimetic fibrin-based 3D glioblastoma invasion model

Glioblastoma (GBM) lethality arises from aggressive invasion and diffuse infiltration of brain tissue. Conventional GBM preclinical models often fail to predict clinical therapeutic efficacy because they do not recapitulate the pathological extracellular matrix (ECM) cues that drive tumor invasion. Here, we present an ECM mimetic 3D platform using a fibrin scaffold to recapitulate the hemorrhagic, pro-thrombotic tumor microenvironment characteristic of high-grade gliomas. This fibrin scaffold induces a pro-invasive phenotype in GBM spheroids by upregulating proliferation/cell cycle- (MYC, FOXOM1, CCND1) and invasion-associated-(CTSS, FOXM1, CCND1) genes. Traditional cell morphology quantification methods (e.g., circularity) distil complex shapes into singular metrics and cannot capture the nuances of invasion. To address this limitation, we have applied a deep-learning segmentation pipeline (MARS-Net) and high-content morphodynamic descriptors. By using the Preserving Heterogeneity (PHet) algorithm, the 3D platform accurately classifies invasiveness levels and captures the invasion-inhibitory effects of potential repurposable drug candidates. We demonstrate that our model can predict a spheroids long-term invasive fate with high accuracy using only partial image sets from early time-points, rather than the complete time-course images. Our work presents an in vivo-like, scalable 3D platform integrated with a quantitative high-throughput pipeline to elucidate GBM invasion mechanisms and to evaluate anti-invasive compounds.

bioengineering↗

bioRxiv2022

Mutational Changes and Enhanced Cell Migration during Transformation of Breast Non-tumorigenic Cells to Tumorigenic Cells

Although cancer stem cells (CSCs) play a major role in tumorigenesis and metastasis, the role of genetic alterations in invasiveness of CSCs is still unclear. Tumor microenvironment signals, such as extracellular matrix (ECM) composition, significantly influence cell behaviors. Unfortunately, these signals are often lost in in vitro cell culture. This study determines putative CSC populations, examines genetic changes during tumorigenesis of human breast epithelial stem cells, and investigates single-cell migration properties on ECM-mimetic platforms. Whole exome sequencing data indicate that tumorigenic cells have a higher somatic mutation burden than non-tumorigenic cells, and that mutations exclusive to tumorigenic cells exhibit higher predictive deleterious scores. Tumorigenic cells exhibit distinct somatic copy number variations (CNVs) including gain of duplications in chromosomes 5 and 8. ECM-mimetic topography selectively enhances migration speed of tumorigenic cells, but not of non-tumorigenic cells, and results in a wide distribution of tumorigenic single-cell migration speeds, suggesting heterogeneity in cellular sensing of contact guidance cues. This study identifies mutations and CNVs acquired during breast tumorigenesis, which can be associated with enhanced migration of breast tumorigenic cells, and demonstrates that a nanotopographically-defined platform can be applied to recapitulate an ECM structure for investigating cellular migration in the simulated tumor microenvironment.

cancer biology↗

bioRxiv2019

The Norepinephrine Metabolite DOPEGAL Confers Locus Coeruleus Tau Vulnerability and Propagation via Asparagine Endopeptidase

Aberrant Tau inclusions in the locus coeruleus (LC) are the earliest detectable Alzheimers disease (AD)-like neuropathology in the human brain; however, why LC neurons are selectively vulnerable to developing early Tau pathology and degenerating later in disease and whether the LC might seed the stereotypical spread of Tau pathology to the rest of the brain remain unclear. Here we show that 3,4-dihydroxyphenylglycolaldehyde (DOPEGAL), which is produced exclusively in noradrenergic neurons by monoamine oxidase A (MAO-A) metabolism of norepinephrine (NE), activates asparagine endopeptidase (AEP) that cleaves Tau at residue N368 into aggregation- and propagation-prone forms, thereby leading to LC degeneration and the spread of Tau pathology. DOPEGAL triggers AEP-cleaved Tau aggregation in vitro and in intact cells, resulting in LC neurotoxicity and propagation of pathology to the forebrain. Thus, our findings reveal a novel molecular mechanism underlying the selective vulnerability of LC neurons in AD.

neuroscience↗

bioRxiv2019

Unexpectedly High Subclonal Mutational Diversity in Human Colorectal Cancer and Its Significance

Human colorectal cancers (CRC) contain both clonal and subclonal mutations. Clonal mutations are positively selected, present in most cells and drive malignant progression. Subclonal mutations are randomly dispersed throughout the genome; they provide a vast reservoir of mutant cells that can expand, repopulate the tumor and result in the rapid emergence of resistance, as well as being a major contributor to tumor heterogeneity. Here, we apply Duplex Sequencing (DS) methodology to quantify subclonal mutations in CRC tumor with unprecedented depth (104) and accuracy (<10-7). We measured mutation frequencies in genes encoding replicative DNA polymerases and in genes frequently mutated in CRC, and found an unexpectedly high effective mutation rate, 7.1 x 10-7. The curve of subclonal mutation accumulation as a function of sequencing depth, using DNA obtained from five different tumors, is in accord with a neutral model of tumor evolution. We present a new theoretical approach to model neutral evolution independent of the infinite sites assumption (which states that a particular mutation arises only in one tumor cell at any given time). Our analysis indicates that the infinite sites assumption is not applicable once the number of tumor cells exceeds the reciprocal of the mutation rate, a circumstance relevant to even the smallest clinically diagnosable tumor. Our methods allow accurate estimation of the total mutation burden in clinical cancers. Our results indicate that no DNA locus is wild type in every malignant cell within a tumor at the time of diagnosis (probability of all cells wild type = 10-308).\n\nSignificance StatementCancers evolve many mutations. Clonal mutations are selected early. Subsequent evolution occurs in a branching fashion, possibly without selection (\"neutral evolution\"). Rarer mutations occur later on smaller branches of the evolutionary tree. Using a DNA sequencing method, duplex sequencing, with unprecedented accuracy and sensitivity, we quantified very rare unique subclonal mutations in diagnostic specimens from five human colorectal cancers. Rarer subclones probe later evolutionary timepoints than previously possible. We confirm neutral evolution at later times and find many more subclonal mutations than expected. A novel theoretical method allowed us to extrapolate further forward in time to diagnosis. At diagnosis, every base in DNA is mutated in at least one cancer cell. In particular any therapy resistance mutation would be present.

cancer biology↗

bioRxiv2019

Immortalization of different breast epithelial cell types results in distinct mitochondrial mutagenesis

Different phenotypes of normal cells might influence genetic profiles, epigenetic profiles, and tumorigenicities of their transformed derivatives. In this study, we investigated whether the whole mitochondrial genome of immortalized cells can be attributed to different phenotypes (stem vs non-stem) of their normal epithelial cell originators. To accurately determine mutations, we employed Duplex Sequencing, which exhibits the lowest error rates among currently available DNA sequencing methods. Our results indicate that the vast majority of observed mutations of the whole mitochondrial DNA occur at low-frequency (rare mutations). The most prevalent rare mutation types are C[->]T/G[->]A and A[->]G/T[->]C transitions. Frequencies and spectra of homoplasmic point mutations are virtually identical between stem cell-derived immortalized (SV1) cells and non-stem cell-derived immortalized (SV22) cells, verifying that both cell types were derived from the same woman. However, frequencies of rare point mutations are significantly lower in SV1 cells (5.79x10-5) than in SV22 cells (1.16x10-4). Additionally, the predicted pathogenicity for rare mutations in the mitochondrial tRNA genes is significantly lower (by 2.5-fold) in SV1 cells than in SV22 cells. Our findings suggest that the immortalization of normal cells with stem cell features leads to decreased mitochondrial mutagenesis, particularly in noncoding RNA regions. The mutation spectra and mutations specific to stem cell-derived immortalized cells (vs non-stem cell derived) have implications in characterizing heterogeneity of tumors and understanding the role of mitochondrial mutations in immortalization and transformation of human cells.

genomics↗

bioRxiv2018

Detection of low-frequency mutations and removal of heat-induced artifactual mutations using Duplex Sequencing

We present a genome-wide comparative and comprehensive analysis of three different sequencing methods (conventional next generation sequencing (NGS), tag-based single strand sequencing (eg. SSCS), and Duplex Sequencing for investigating mitochondrial mutations in human breast epithelial cells. Duplex Sequencing produces a single strand consensus sequence (SSCS) and a duplex consensus sequence (DCS) analysis, respectively. Our study validates that although high-frequency mutations are detectable by all the three sequencing methods with the similar accuracy and reproducibility, rare (low-frequency) mutations are not accurately detectable by NGS and SSCS. Even with conservative bioinformatical modification to overcome the high error rate of NGS, the NGS frequency of rare mutations is 7.0x10-4. The frequency is reduced to 1.3x10-4 with SSCS and is further reduced to 1.0x10-5 using DCS. Rare mutation context spectra obtained from NGS significantly vary across independent experiments, and it is not possible to identify a dominant mutation context. In contrast, rare mutation context spectra are consistently similar in all independent DCS experiments. We have systematically identified heat-induced artifactual mutations and corrected the artifacts using Duplex Sequencing. All of these artifacts are stochastically occurring rare mutations. C>A/G>T, a signature of oxidative damage, is the most increased (170-fold) heat-induced artifactual mutation type. Our results strongly support the claim that Duplex Sequencing accurately detects low-frequency mutations and identifies and corrects artifactual mutations introduced by heating during DNA preparation.

genomics↗

bioRxiv2018

NanoMEA: a versatile platform for high-throughput analysis of structure-function relationships in human stem cell-derived excitable cells and tissues

Somatic cells derived from human pluripotent stem cell (hPSC) sources hold significant potential as a means to improve current in vitro screening assays. However, their inconsistent ability to recapitulate the structural and functional characteristics of native cells has raised questions regarding their ability to accurately predict the functional behavior of human tissues when exposed to chemical or pathological insults. In addition, the lack of cytoskeletal organization within conventional culture platforms prevents analysis of how structural changes in human tissues affect functional performance. Using cation-permeable hydrogels, we describe the production of multiwell nanotopographically-patterned microelectrode arrays (nanoMEAs) for studying the effect of structural organization on hPSC-derived cardiomyocyte and neuronal function in vitro. We demonstrate that nanoscale topographic substrate cues promote the development of more ordered cardiac and neuronal monolayers while simultaneously enhancing cytoskeletal organization, protein expression patterns, and electrophysiological function in these cells. We then show that these phenotypic improvements act to alter the sensitivity of hPSC-derived cardiomyocytes to treatment with arrhythmogenic and conduction-blocking compounds that target structural features of the cardiomyocyte. Similarly, we demonstrate that neuron sensitivity to synaptic blockers is increased when cells are maintained on nanotopographically-patterned Nafion surfaces. The improved structural and functional capacity of hPSC-derived cardiomyocyte and neuronal populations maintained on nanoMEAs may have important implications for improving the predictive capabilities of cell-based electrophysiological assays used in preclinical screening applications.

bioengineering↗