Biology subjects

Ahn, E.

Publications and source records attributed to Ahn, E..

13 recordsLinked to original sources

bioRxiv2025

From minutes to bounds: A probabilistic UV-C control and a shape-only morphological fingerprint for postharvest Colletotrichum

Postharvest losses in high-value horticultural crops such as cacao and coffee are often driven by Colletotrichum spp. and other latent fruit pathogens. Ultraviolet-C (UV-C) is increasingly deployed as a chemical-free postharvest technology, yet prescriptions remain framed in minutes rather than in probabilistic guarantees of disease control and safety. We present a dual framework that (1) establishes conservative confidence bounds on survival and (2) validates a "shape-only" morphological fingerprint. This approach addresses the biological complexity of host-pathogen interactions by quantifying isolate-specific heterogeneity, rather than averaging it away. We utilized a large Colletotrichum dataset (n = 5,363) from cacao and coffee, spanning diverse treatments including UV-C, UV-B, and sonication. First, focusing on the Coffee UV-C cohort ([~]10 min), we quantified this heterogeneity; the most conservative Clopper-Pearson upper 95% bound on survival reached 1.000, highlighting partial survival events (e.g., isolate P24-88) under otherwise high-efficacy conditions. This probabilistic framework captures the "tail-risk" of biological resilience instead of assuming complete kill. Second, we trained machine learning models on the full dataset using only geometric features (e.g., aspect ratio, asymmetry), explicitly excluding all primary size metrics. Serving as a rapid physiological indicator of UV-induced stress, these "shape-only" models successfully predicted pathogen host-origin (Accuracy {approx} 0.93) and post-treatment survival (R{superscript 2} {approx} 0.74). The signals ability to generalize across UV-B and sonication confirms that geometry, not just growth reduction, carries a robust and transferable physiological stress signature. This work provides a device-agnostic, probabilistic control platform, replacing time-based heuristics with quantitative guarantees and a generalizable, shape-based diagnostic. HighlightsO_LIA conservative upper 95 % confidence bound (on survival = 1.000) was observed for the Coffee UV-C ([~]10 min) cohort, revealing strong isolate-specific heterogeneity rather than a universal kill guarantee C_LIO_LIIsolate-specific heterogeneity (e.g., localized P24-88 survival) was quantified rather than averaged away. C_LIO_LIA size-free morphological fingerprint predicted host-origin (Accuracy {approx} 0.93) and survival (R{superscript 2} {approx} 0.74). C_LIO_LIThe shape-only signal generalized across diverse stressors, including UV-C, UV-B, and sonication. C_LIO_LIA probabilistic, device-agnostic control framework replaces traditional time-based heuristics. C_LI

microbiology↗

bioRxiv2025

Decoding pathogen ecological memory from chemical-stress phenotypes

Can standardized chemical stress reveal a reproducible, taxonomy-agnostic stress-response fingerprint that is predictive of sample-source labels (crop-of-isolation) in fungal isolates? Six coffee{square}associated Colletotrichum isolates were profiled using four phenolic{square}branched compounds and compared them with a previously characterized cacao panel. Quantitative morphology, hyperspectral imaging (HSI), and supervised machine learning (ML) yielded panel-specific fingerprints under uniform, isotropic in vitro conditions. Circularity, a measure of edge symmetry, was the most informative morphological feature, and ML classified the crop-of-isolation label (coffee vs cacao, in this panel) with 86.7% accuracy in within-panel cross-validation. HSI detected dose-dependent spectral shifts in a targeted subset of isolates and compounds, including changes near 1930 nm in the short-wave infrared, a moisture-sensitive region that warrants robustness checks (e.g., band masking or preprocessing sensitivity) prior to biochemical attribution. Multi{square}locus phylogeny showed the coffee isolates are polyphyletic, so the predictive signal should be interpreted conservatively as a taxonomy-agnostic phenotype fingerprint associated with crop background in this mixed-lineage panel, acknowledging that crop labels are partially confounded with phylogenetic structure. We propose a "chemical priors" framework as a working hypothesis, in which long-term environmental exposure may imprint stress-response pathways that become legible under simple, standardized probes. This integrative workflow supports scalable screening of eco-friendly antifungals and sensor-driven decision support for high-throughput phenotype-based screening workflows. HighlightsO_LITaxonomy-agnostic workflow integrates hyperspectral imaging and morphology. C_LIO_LIMachine learning predicts crop-source labels with 86.7% accuracy in mixed lineages. C_LIO_LISystem exhibits robustness, maintaining >86% accuracy even after feature ablation. C_LIO_LINon-linear ML captures structure missed by linear stats (1.7% variance). C_LIO_LIEnables rapid, sensor-driven antifungal screening without prior DNA sequencing. C_LI

microbiology↗

bioRxiv2025

An Eligibility-Aware Pipeline for Robust ITS Diagnostics in Fungi: A Cacao Case Study with Generalizable Rules

Accurate fungal ITS diagnostics rely on public sequence archives, but heterogeneous record lengths, especially frequent truncation before the LSU/28S segment, cause naive in silico benchmarking to conflate primer performance with database incompleteness. To resolve this persistent "denominator error," we present an open and fully reproducible "eligibility-aware" framework. Our pipeline first establishes eligibility by confirming both primer sites are present before applying bench-realistic performance rules, including a strict penalty for 3-terminal mismatches. It further provides mechanistic insights by analyzing binding-site conservation and uses a rarefaction-based approach to guide efficient quality control as databases grow. We demonstrate the frameworks utility using the cacao pathosystem, a context where rapid differentiation of the fungal pathogen Moniliophthora from symptomatically similar oomycetes is critical. The result is a robust, field-ready diagnostic decision tree operable under a single touchdown (TD) PCR program. By providing a transparent and barcode-agnostic template, our eligibility-aware approach offers a significant methodological advance for designing and validating molecular assays in mycology and beyond.

microbiology↗

bioRxiv2025

Genomic Prediction and SNP Importance Analysis for Agronomic Traits in Two Coffea canephora Populations

This study reveals that distinct breeding populations of Coffea canephora can achieve agronomic success through fundamentally different biological strategies. To uncover this, we performed a comparative genomic analysis of two populations ( Premature and Intermediate), integrating single-SNP association, machine learning (Bootstrap Forest), and Gene Ontology (GO) pathway analysis. The genetic architecture of the Premature population was linked to specialized metabolic pathways, including lipid modification and processes within the organelle lumen, a finding supported by the identification of a putative caffeine synthase 3 gene. In contrast, traits in the Intermediate population were governed by variation in core cellular machinery, with significant enrichment for pathways related to actin cytoskeleton regulation and salicylic acid signaling. This discovery provides a new biological context for important candidate genes involved in disease resistance (e.g., RPP13-like, NB-ARC, CERK1). These findings demonstrate that population-specific biological routes underpin agronomic performance, providing a powerful foundation for designing more targeted breeding programs in coffee. We release population-specific, ranked SNP lists and GO gene sets as a reusable resource to enable meta-analyses and benchmarking in coffee and perennial crops.

genetics↗

bioRxiv2025

Unveiling differential responses to UVB (305 nm) and UVC (275 nm) in cacao-infecting Colletotrichum gloeosporioides and Pestalotiopsis sp.

Sustainable control of microbial pathogens requires alternatives to chemicals, but physical methods like Ultraviolet-C (UVC) show variable efficacy linked to poorly understood pathogen-specific responses. Here, we investigate differential UVB/UVC responses in plant pathogenic fungi (Colletotrichum gloeosporioides, Pestalotiopsis sp.). Using hyperspectral imaging and machine learning, we dissect the physiological underpinnings of UV sensitivity. UVC proves more potent than UVB, with Pestalotiopsis sp. showing significantly higher resistance than C. gloeosporioides isolates. Crucially, hyperspectral signatures correlated with resistance, revealing UVC-induced photopigment changes, biochemical disruption, and oxidative stress markers in sensitive isolates, contrasting with minimal perturbation in the resistant isolate. Machine learning accurately decoded these complex phenotypes for classification. This understanding enabled enhanced inactivation via optimized pulsed UVC and synergistic sonication. We link distinct physiological states, non-invasively detected via hyperspectral imaging, to fungal UV resistance, demonstrating how integrating advanced phenotyping and machine learning provides a mechanistic basis for optimizing physical pathogen controls.

microbiology↗

bioRxiv2025

Genome-wide association mapping and predictive modeling of wet bean mass in a diverse cacao collection

Improving cacao yield, a key objective in post-domestication crop improvement, remains a primary goal for breeders, but progress is often hindered by the confounding effects of population structure. To overcome this, we analyzed 346 diverse cacao accessions using an ML-based association mapping framework (with and without population structure adjustment) and a phenotype-only ML prediction of yield. By correcting for population structure, our Bootstrap Forest-based GWAS revealed association signals that showed consistent enrichment for ribosome and protein-synthesis functions, and a recurrent subset of SNPs with high importance appeared across multiple yield components, including pod index and seed number. In parallel, a Neural Network model was utilized to identify cotyledon mass and length as the most powerful predictors for total wet bean mass (R{superscript 2} = 0.715 by repeated five-fold cross-validation), suggesting a practical, low-cost screening proxy for breeding). Collectively, this study delivers a robust genetic framework and a novel predictive tool to accelerate the development of high-yielding cacao varieties through the early identification of elite clones.

genomics↗

bioRxiv2025

The graphene-based affinity cryo-EM grid for the endogenous protein structure determination

Following recent advancements in cryo-electron microscopy (cryo-EM) instrumentation and software algorithms, the next bottleneck in achieving high-resolution cryo-EM structures arises from sample preparation. To overcome this, we developed a graphene-based affinity cryo-EM grid, the Graffendor (GFD) grid, to target low-abundance endogenous protein complexes. To maintain grid quality and consistency within a single batch of 36 grids, we established a one-step crosslinking batch-production method using genetically modified ALFA nanobody as affinity probe (GFD-A grid). Using low concentrations of {beta}-galactosidase-2xALFA, we demonstrated the GFD-A grids efficiency in capturing tagged proteins and resolving its cryo-EM structure at 2.71 [A]. To test its application for endogenous proteins, we engineered yeast cells with a C-terminal tandem affinity tag (3xALFA-Tev-3xFlag: ATF) at Pop6, a shared component of RNase MRP and RNase P. Cryo-EM structures of RNase MRP and RNase P were resolved at 3.3 [A] and 3.0 [A] from cell lysates, and 3.6 [A] and 3.9 [A] from anti-flag elution, respectively. Notably, additional densities were observed in the structures obtained from cell lysates, which were absent in those from the anti-FLAG eluate. These findings establish the GFD-A grid as a robust platform for investigating endogenous proteins, capable of capturing transient interactions and enhancing the resolution of challenging cryo-EM structures with greater efficiency.

biochemistry↗

bioRxiv2024

Contact Lens Wear Alters Transcriptional Responses to Pseudomonas aeruginosa in Both the Corneal Epithelium and the Bacteria

PurposeHealthy corneas resist colonization by virtually all microbes yet contact lens wear can predispose the cornea to sight-threatening infection with Pseudomonas aeruginosa. Here, we explored how lens wear changes corneal epithelium transcriptional responses to P. aeruginosa and its impact on bacterial gene expression. MethodsMale and female C57BL/6J mice were fitted with a contact lens on one eye for 24 h. After lens removal, corneas were immediately challenged for 4 h with P. aeruginosa. A separate group of naive mice were similarly challenged with bacteria. Bacteria-challenged eyes were compared to uninoculated naive controls as was lens wear alone. Total RNA-sequencing determined corneal epithelium and bacterial gene expression. ResultsPrior lens wear profoundly altered the corneal response to P. aeruginosa, including: upregulated pattern-recognition receptors (tlr3, nod1), downregulated lectin pathway of complement activation (masp1), amplified upregulation of tcf7, gpr55, ifi205, wfdc2 (immune defense) and further suppression of efemp1 (corneal stromal integrity). Without lens wear, P. aeruginosa upregulated mitochondrial and ubiquinone metabolism genes. Lens wear alone upregulated axl, grn, tcf7, gpr55 (immune defense) and downregulated Ca2+-dependent genes necab1, snx31 and npr3. P. aeruginosa exposure to prior lens wearing vs. naive corneas upregulated bacterial genes of virulence (popD), its regulation (rsmY, PA1226) and antimicrobial resistance (arnB, oprR). ConclusionPrior lens wear impacts corneal epithelium gene expression altering its responses to P. aeruginosa and how P. aeruginosa responds to it favoring virulence, survival and adaptation. Impacted genes and associated networks provide avenues for research to better understand infection pathogenesis.

microbiology↗

bioRxiv2023

Evidence for a Causal Dissociation of the McGurk Effect and Congruent Audiovisual Speech Perception via TMS

Congruent visual speech improves speech perception accuracy, particularly in noisy environments. Conversely, mismatched visual speech can alter what is heard, leading to an illusory percept known as the McGurk effect. This illusion has been widely used to study audiovisual speech integration, illustrating that auditory and visual cues are combined in the brain to generate a single coherent percept. While prior transcranial magnetic stimulation (TMS) and neuroimaging studies have identified the left posterior superior temporal sulcus (pSTS) as a causal region involved in the generation of the McGurk effect, it remains unclear whether this region is critical only for this illusion or also for the more general benefits of congruent visual speech (e.g., increased accuracy and faster reaction times). Indeed, recent correlative research suggests that the benefits of congruent visual speech and the McGurk effect reflect largely independent mechanisms. To better understand how these different features of audiovisual integration are causally generated by the left pSTS, we used single-pulse TMS to temporarily impair processing while subjects were presented with either incongruent (McGurk) or congruent audiovisual combinations. Consistent with past research, we observed that TMS to the left pSTS significantly reduced the strength of the McGurk effect. Importantly, however, left pSTS stimulation did not affect the positive benefits of congruent audiovisual speech (increased accuracy and faster reaction times), demonstrating a causal dissociation between the two processes. Our results are consistent with models proposing that the pSTS is but one of multiple critical areas supporting audiovisual speech interactions. Moreover, these data add to a growing body of evidence suggesting that the McGurk effect is an imperfect surrogate measure for more general and ecologically valid audiovisual speech behaviors.

neuroscience↗

bioRxiv2023

Mechanical force regulates ligand binding and function of PD-1

Immune checkpoint blockade targeting PD-1 shows great success in cancer therapy. However, the mechanism of how ligand binding initiates PD-1 signaling remains unclear. As prognosis markers of multiple cancers, soluble PD-L1 is found in patient sera and can bind PD-1, but fails to suppress T cell function. This and our previous observations that T cells exert endogenous forces on PD-1- PD-L2 bonds prompt the hypothesis that mechanical force might be critical to PD-1 triggering, which is missing in the soluble ligand case due to the lack of mechanical support afforded by surface-anchored ligand. Here we show that PD-1 function is eliminated or reduced when mechanical support on ligand is removed or dampened, respectively. Force spectroscopic analysis reveals that PD-1 forms catch bonds with both PD-Ligands <7 pN where force prolongs bond lifetime, but slip bonds >8 pN where force accelerates dissociation. Steered molecular dynamics finds PD-1-PD-L2 complex very sensitive to force due to the two molecules "side-to-side" binding via {beta} sheets. Pulling causes relative rotation and translation between the two molecules by stretching and aligning the complex along the force direction, yielding new atomic contacts not observed in the crystal structure. Compared to wild-type, PD-1 mutants targeting the force-induced new interactions maintain the same binding affinity but display lower rupture force, shorter bond lifetime, reduced tension, and most importantly, impaired capacity to suppress T cell activation. Our results uncover a mechanism for cells to probe the mechanical support of PD-1-PD-Ligand bonds using endogenous forces to regulate PD-1 triggering.

immunology↗

bioRxiv2021

Batch Production of High-Quality Graphene Grids for Cryo-EM: Cryo-EM Structure of Methylococcus capsulatus Soluble Methane Monooxygenase Hydroxylase

Cryogenic electron microscopy (cryo-EM) has become a widely used tool for determining protein structure. Despite recent technology advances, sample preparation remains a major bottleneck for several reasons, including protein denaturation at the air/water interface, the presence of preferred orientations, nonuniform ice layers, etc. Graphene, a two-dimensional allotrope of carbon consisting of a single atomic layer, has recently gained attention as a near-ideal support film for cryo-EM that can overcome these challenges because of its superior properties, including mechanical strength and electrical conductivity. Here, we introduce a reliable, easily implemented, and reproducible method to produce 36 graphene-coated grids within 1.5 days. To demonstrate their practical application, we determined the cryo-EM structure of Methylococcus capsulatus soluble methane monooxygenase hydroxylase (sMMOH) at resolutions of 2.9 and 2.4 [A] using Quantifoil and graphene-coated grids, respectively. We found that the graphene-coated grid has several advantages, including less amount of protein required and avoiding protein denaturation at the air/water interface. By comparing the cryo-EM structure of sMMOH with its crystal structure, we identified subtle yet significant geometrical changes at the non-heme di-iron center, which may better indicate the active site configuration of sMMOH in the resting/oxidized state.

biochemistry↗

bioRxiv2021

Interleukin-33 coordinates a microglial phagocytic response and limits corticothalamic excitability and seizure susceptibility

Microglia are key remodelers of neuronal synapses during brain development, but the mechanisms that regulate this process and its ultimate impact on neural circuit function are not well defined. We previously identified the IL-1 family cytokine Interleukin-33 (IL-33) as a novel mediator of microglial synapse remodeling. Here we define the phagocytic program induced in microglia in response to IL-33. We find that IL-33 markedly alters the microglial enhancer landscape and exposes AP-1 transcription factor sites that promote target gene expression. We identify the scavenger receptor MARCO and the pattern recognition receptor TLR2 as downstream mediators of IL-33 dependent synapse engulfment. Conditional deletion of IL-33 in the CNS or its receptor on microglia results in increased numbers of excitatory synapses in the corticothalamic circuit and spontaneous epileptiform activity as well as increased seizure susceptibility by early adulthood. These findings define novel mechanisms through which IL-33 coordinates experience-dependent synaptic refinement to restrict hyperexcitability in the developing brain.

neuroscience↗

bioRxiv2021

Atmospheric plasma jet device for versatile electron microscope grid treatment

Atmospheric pressure plasmas have been widely applied in surface modification and biomedical treatment due to its ability to generate highly reactive radicals and charged particles. In negative-stain electron microscopy (Neg-EM) and cryogenic electron microscopy (cryo-EM), plasmas have been used in eliminating the surface contaminants as well as generating the hydrophilic surface to embed the specimen on grids. Plasma treatment is a prerequisite for negative stain and quantifoil grids, which are coated with hydrophobic carbon on the grid surface. Here we introduce a non-thermal atmospheric plasma jet system as an alternative new tool for surface treatment. Unlike the conventional glow discharger, we found that the plasma jet system successfully cleans the grid surface and introduces hydrophilicity on grids in the ambient environment without introducing a vacuum. Therefore, we anticipate the plasma jet system will be beneficial in many aspects, such as cost-effective, convenient, versatile, and potential applications in surface modification for both negative stain and cryo-EM grid treatment.

biochemistry↗