Biology subjects

Moon, K.

Publications and source records attributed to Moon, K..

7 recordsLinked to original sources

bioRxiv2026

Spatially resolved transcriptomic and proteomic profiling reveals cell interaction programs that predict Barrett's esophagus progression

Barretts esophagus (BE) is the precursor lesion of esophageal adenocarcinoma (EAC). It affects approximately 5% of adults in the United States and significantly increases the risk of developing EAC. However, current surveillance strategies cannot reliably distinguish patients who will progress from those who will remain stable. Direct studies of progressor BE are extremely limited due to availability of tissue with known progression outcomes, and have largely been restricted to genomic profiling approaches. The premalignant cellular landscape of progressor BE remains poorly understood. Here, we used complementary spatial transcriptomic and proteomic imaging to profile 34 non-dysplastic BE patients under endoscopic surveillance, including those who subsequently progressed to dysplasia or EAC, termed "Progressors" and those who remained stable, termed "Non-progressors". Transcriptomics based Xenium analysis captured 974,604 cells across 70 whole-biopsy regions, while protein based imaging mass cytometry profiled 372,242 cells across 119 selected regions. FUME-TCRseq further quantified T cell clonotypes from matched tissues scrolls. Cellular composition was generally similar between Progressors and Non-progressors. However, Progressors showed increased intestinal Barretts columnar cells, B cells and gastric progenitor-like cells, together with enhanced immune-epithelial interactions, whereas Non-progressors retained coordinated stromal organization. Spatial interaction features strongly outperformed cell composition and density for progression prediction. Combined spatial interaction model achieved an area under the curve (AUC) of 0.97, compared with 0.62 and 0.68 for comparison and density alone. Complementary imaging mass cytometry further resolved the underlying immune programs, identifying cytotoxic and antigen presenting myeloid features enriched in progressors, and CD56 associated memory T cell interactions enriched in non progressors. Together, these findings support a model that BE progression is driven by progressive remodeling of epithelial-immune-stromal architecture rather than emergence of distinct dysplasia-like cell subsets. Increased T cell clonal diversity and recruitment of cytotoxic and antigen-presenting immune niches may also reflect an evolving response to genomic alteration prior to dysplasia. These results establish spatial tissue architecture, rather than specific cell types, captures progression associated microenvironmental states in BE and provides a framework for spatially informed patient stratification and early cancer risk assessment.

systems biology↗

bioRxiv2026

Why Boolean network control tools disagree: a taxonomy of control problems

Boolean networks are discrete dynamical models that use Boolean states and logical functions to represent the dynamics of biological systems. A primary application of Boolean networks is to identify controls (e.g., genetic mutations or knockouts) that drive the system toward a desired phenotype. However, existing computational tools often produce inconsistent results because they rely on differing modeling assumptions. To better understand these differences, we survey existing tools and propose a taxonomy of control problems. Our taxonomy unveils hidden coverage relationships among their solutions that arise from these modeling assumptions. We provide a computational framework to empirically assess these relationships by comparing their predicted controls on a suite of artificial and biological models. Finally, we develop a coverage-consistent metric, the mutation co-occurrence score, to prioritize mutations based on their predicted impact on the phenotype. A case study on T-LGL leukemia highlights how an ensemble prediction of the score across multiple tools identifies key mutations associated with apoptosis. Author summaryBoolean networks let us model gene and protein regulation with simple on/off logic. That simplicity makes them useful for asking a practical question: which controls (e.g., genetic interventions, knockouts, or forced activations) can guarantee a desired cellular phenotype such as survival or apoptosis. In practice, different software tools often return inconsistent control sets, creating a practical barrier to reproducibility and reliability of predictions. Here we provide a comprehensive survey to navigate this landscape. We provide a comparison framework to assess coverage relationships, both theoretically and empirically, among the solutions of control tools. We classify the tools based on our new taxonomy that highlights the core differences among them. For many tools, we can theoretically determine their coverage relationships based on which components are fixed together to drive the phenotype. These new findings clearly explain subtle differences among solutions produced by various tools. We then develop a coverage-consistent metric for mutations called the mutation co-occurrence score. This new metric helps prioritize control targets based on their predicted impact on the phenotype. We also demonstrate that averaging scores from multiple tools gives reliable predictions. Our code is extensible to future tools and will facilitate the comparison of Boolean network control tools in biological research.

systems biology↗

bioRxiv2025

Tool-use brain representations are independent of the acting body part and motor experience

The sensorimotor system is broadly organized somatotopically. However, an action-type organization has also been found: a division based on action-type independent of acting body parts has been shown for reaching and grasping actions. Does this generalization extend to non-ethological actions? Here, we examined fMRI responses for tool-use actions that participants performed with their hands or feet. We additionally tested individuals born without hands to control for hand motor imagery when performing foot actions. We show that the primary sensorimotor cortices have hand and foot selectivity, consistent with a somatotopic organization. In contrast, higher-level motor areas within the tool-use network, such as the premotor cortex, supplementary motor area, and superior parietal cortices, showed a shared preference for tool-use independent of the executing body part and sensorimotor experience. Multivariate decoding of action-type in these areas generalized between controls hand and foot and was successful in individuals born without hands. Finally, the temporal dynamics pattern in primary and association areas carried effector-specific and action-type information, respectively. Altogether, we show that the tool-use network in motor association areas represents higher-order action information beyond concrete motor parameters associated with specific effectors, and regardless of hand motor experience. This suggests that an action-type, effector-independent organization extends beyond ethological actions, supporting a hierarchical organization in the action domain. Further, it shows that functional organization in congenital handlessness is based on the hierarchical organization of the intact cortex.

neuroscience↗

bioRxiv2024

A highly conserved sRNA downregulates multiple genes, including a sigma54 transcriptional activator, in the virulence mode of Bordetella pertussis

Bacterial sRNAs together with the RNA chaperone Hfq post-transcriptionally regulate gene expression by affecting ribosome binding or mRNA stability. In the human pathogen Bordetella pertussis, the causative agent of whooping cough, hundreds of sRNAs have been identified, but their roles in B. pertussis biology are mostly unknown. Here we characterize a Hfq-dependent sRNA (S17), whose level is dramatically higher in the virulence (Bvg+) mode. We show that transcription from a {sigma}A-dependent promoter yields a long form of 190 nucleotides (nts) that is processed by RNase E to generate a shorter, more stable form (S17S) of 67 nts. Using RNA-seq and RT-qPCR, we identify 92 genes whose expression significantly increases in the absence of S17. Of these genes, 70 contain sequences at/near their ribosome binding sites (RBSs) that are complementary to single-stranded (ss) regions (Sites 1 or 2) of S17S. The identified genes include those encoding multiple transporters and 3 transcriptional regulators. Using a lacZ translational reporter system, we demonstrate that S17S directly represses one of these genes, BP2158, a {sigma}54- dependent transcriptional regulator, suggesting the repression of a {sigma}54 regulon in the Bvg+ mode. We find that the S17S region containing Sites 1 and 2 is 100% conserved throughout various Betaproteobacteria species, and the S17S target sites are often conserved in the homologs of the B. pertussis target genes. We speculate that S17S regulation represents a highly conserved process that fine-tunes gene expression in the Bvg+ mode of B. pertussis and perhaps under other conditions in related bacteria. IMPORTANCERegulation of gene expression involves controlling transcription, translation, and transcript degradation. sRNAs with short sequences complementary to an mRNA sequence are involved in post-transcriptional regulation by aiding or interfering with either ribosome binding or nuclease attack. In the human pathogen Bordetella pertussis, the causative agent of whooping cough, hundreds of sRNA have been identified, but their functions remain largely unknown. We have characterized a sRNA that is abundant in the virulence mode of B. pertussis and serves to down-regulate multiple genes including transcriptional regulators and various transporters. We demonstrate that this sRNA directly represses a transcriptional factor, suggesting that it influences the regulation of specific B. pertussis regulons. The high conservation of this sRNA and its targets within Betaproteobacteria suggests a conserved pathway for gene regulation.

microbiology↗

bioRxiv2023

Mitochondrial genomes of Pleistocene megafauna retrieved from recent sediment layers of two Siberian lakes

Ancient environmental DNA (aeDNA) from lake sediments has yielded remarkable insights for the reconstruction of past ecosystems, including suggestions of late survival of extinct species. However, translocation and lateral inflow of DNA in sediments can potentially distort the stratigraphic signal of the DNA. Using three different approaches on two short lake sediment cores of the Yamal peninsula, West Siberia, with ages spanning only the past hundreds of years, we detect DNA and identified mitochondrial genomes of multiple mammoth and woolly rhinoceros individuals--both species that have been extinct for thousands of years on the mainland. The occurrence of clearly identifiable aeDNA of extinct Pleistocene megafauna (e.g., > 400K reads in one core) throughout these two short subsurface cores, along with specificities of sedimentology and dating, confirm that processes acting on regional scales, such as extensive permafrost thawing, can influence the aeDNA record and should be accounted for in aeDNA paleoecology.

molecular biology↗

bioRxiv2022

3D Graph Contrastive Learning for MolecularProperty Prediction

MotivationSelf-supervised learning (SSL) is a method that learns the data representation by utilizing supervision inherent in the data. This learning method is in the spotlight in the drug field, lacking annotated data due to time-consuming and expensive experiments. SSL using enormous unlabeled data has shown excellent performance for molecular property prediction, but a few issues exist. (1) Existing SSL models are large-scale; there is a limitation to implementing SSL where the computing resource is insufficient. (2) In most cases, they do not utilize 3D structural information for molecular representation learning. The activity of a drug is closely related to the structure of the drug molecule. Nevertheless, most current models do not use 3D information or use it partially. (3) Previous models that apply contrastive learning to molecules use the augmentation of permuting atoms and bonds. Therefore, molecules having different characteristics can be in the same positive samples. We propose a novel contrastive learning framework, small-scale 3D Graph Contrastive Learning (3DGCL) for molecular property prediction, to solve the above problems. Results3DGCL learns the molecular representation by reflecting the molecules structure through the pre-training process that does not change the semantics of the drug. Using only 1,128 samples for pre-train data and 0.5 million model parameters, we achieved state-of-the-art or comparable performance in six benchmark datasets. Extensive experiments demonstrate that 3D structural information based on chemical knowledge is essential to molecular representation learning for property prediction. AvailabilityData and codes are available in https://github.com/moonkisung/3DGCL. Contactsy.kwon@pusan.ac.kr

biochemistry↗

bioRxiv2019

In situ structures of periplasmic flagella in Borrelia reveals conformational changes essential for flagellar rotation

The bacterial flagellar motor is a molecular machine that rotates the flagellar filament at high speed. Torque is generated by the stator-rotor interaction coupled to an ion flux through the torque-generating stator. Here, we employed cryo-electron tomography to visualize the intact flagellar motor in the Lyme disease spirochete Borrelia burgdorferi. By analysis of the motor structures of wild-type and stator mutants, we localize the torque-generating units precisely and determine three-dimensional structure of the stator and its interactions with the rotor. Our study shows that the cytoplasmic domains of the stator are packed regularly around the circumference of the flagellar C-ring. The stator-rotor interaction induces a profound conformational change in the C-ring. Analysis of the motors of a less motile motB-D24E mutant and a non-motile motB-D24N mutant, in which the proton translocation is reduced and blocked, respectively, provides evidence that the conformational change of the C-ring is essential for flagellar rotation.

microbiology↗