Biology subjects

Lee, C. H.

Publications and source records attributed to Lee, C. H..

25 records · Page 2Linked to original sources

bioRxiv2022

Peroxiredoxin 5 regulates osteogenic differentiation via interaction with hnRNPK during bone regeneration

Peroxiredoxin 5 (Prdx5) is involved in pathophysiological regulation via the stress-induced cellular response. However, the function of Prdx5 in the bone remains largely unknown. Here, we show that Prdx5 is involved in osteoclast and osteoblast differentiation, resulting in osteoporotic phenotypes in Prdx5 knockout (Prdx5Ko) mice. Through immunoprecipitation and liquid chromatography combined with tandem mass spectrometry analysis, heterogeneous nuclear ribonucleoprotein K (hnRNPK) was identified as a potential binding partner of Prdx5 during osteoblast differentiation in vitro. We found that Prdx5 acts as a negative regulator of hnRNPK-mediated osteocalcin (Ocn) expression. In addition, transcriptomic analysis revealed that in vitro differentiated osteoclasts from the bone marrow-derived macrophages of Prdx5Ko mice showed enhanced expression of several osteoclast-related genes. These findings indicate that Prdx5 might contribute to the maintenance of bone homeostasis by regulating osteoblast differentiation. This study proposes a new function of Prdx5 in bone remodeling that may be used in developing therapeutic strategies for bone diseases.

cell biology↗

bioRxiv2022

Deep Learning Guided Diffusion MRI Tractography in the Mouse Brain

Diffusion MRI (dMRI) tractography is the only tool for non-invasive mapping of macroscopic structural connectivity over the entire brain. Although it has been successfully used to reconstruct large white matter tracts in the human and animal brains, the sensitivity and specificity of dMRI tractography remained limited. Especially, the fiber orientation distributions (FODs) estimated from dMRI signals, key to tractography, may deviate from histologically measured fiber orientation in crossing fibers and gray matter regions. In this study, we demonstrated that a deep learning network, trained using mesoscopic tract-tracing data from the Allen Mouse Brain Connectivity Atlas, was able to improve the estimation of FODs from mouse brain dMRI data. Tractography results based on the network generated FODs showed improved specificity while maintaining sensitivity comparable to results based on FOD estimated using a conventional spherical deconvolution method. Our result is a proof-of-concept of how mesoscale tract-tracing data can guide dMRI tractography and enhance our ability to characterize brain connectivity.

bioengineering↗

bioRxiv2021

Oxo-M and 4-PPBP Delivery via Multi-Domain Peptide Hydrogel Toward Tendon Regeneration

We have recently identified novel small molecules, Oxo-M and 4-PPBP, which specifically stimulates endogenous tendon stem/progenitor cells (TSCs) leading to potential regenerative healing of fully-transected tendons. Here we investigated an injectable, multi-domain peptide (MDP) hydrogel providing a controlled delivery of the small molecules for regenerative tendon healing. We investigated the release kinetics of Oxo-M and 4-PPBP from MDP hydrogels and the effect of MDP-released small molecules on tenogenic differentiation of TSCs and in vivo tendon healing. In vitro, MDP showed a sustained release of Oxo-M and 4-PPBP and a slower degradation compared to fibrin. In addition, tenogenic gene expression was significantly increased in TSC with MDP-released Oxo-M and 4-PPBP as compared to the fibrin-released. In vivo, MDP releasing Oxo-M and 4-PPBP significantly improved tendon healing, likely associated with prolonged effects of Oxo-M and 4-PPBP on suppression of M1 macrophages and promotion of M2 macrophages. Comprehensive analyses including histomorphology, digital image processing, and modulus mapping with nanoindentation consistently suggested that Oxo-M and 4-PPBP delivered via MDP further improved tendon healing as compared to fibrin-based delivery. In conclusion, MDP delivered with Oxo-M and 4-PPBP may serve as an efficient regenerative therapeutic for in situ tendon regeneration and healing.

bioengineering↗

bioRxiv2020

A method to map and interpret pleiotropic loci using summary statistics of multiple traits

1The identification of pleiotropic loci and the interpretation of the associations at these loci are essential to understand the shared etiology of related traits. A common approach to map pleiotropic loci is to use an existing meta-analysis method to combine summary statistics of multiple traits. This strategy does not take into account the complex genetic architectures of traits such as genetic correlations and heritabilities. Furthermore, the interpretation is challenging because phenotypes often have different characteristics and units. We propose PLEIO, a summary-statistic-based framework to map and interpret pleiotropic loci in a joint analysis of multiple traits. Our method maximizes power by systematically accounting for the genetic correlations and heritabilities of the traits in the association test. Any set of related phenotypes, binary or quantitative traits with differing units, can be combined seamlessly. In addition, our framework offers interpretation and visualization tools to help downstream analyses. Using our method, we combined 18 traits related to cardiovascular disease and identified 20 novel pleiotropic loci, which showed five different patterns of associations. Our method is available at https://github.com/hanlab-SNU/PLEIO.

bioinformatics↗

bioRxiv2020

Inferring Maps of Cellular Structures from MRI Signals using Deep Learning

1H MRI maps brain structure and function non-invasively through versatile contrasts that exploit inhomogeneity in tissue micro-environments. Inferring histopathological information from MRI findings, however, remains challenging due to absence of direct links between MRI signals and cellular structures. Here, we show that deep convolutional neural networks, developed using co-registered multi-contrast MRI and histological data of the mouse brain, can estimate histological staining intensity directly from MRI signals at each pixel. The results provide three-dimensional maps of axons and myelin with tissue contrasts that closely mimics target histology and enhanced sensitivity and specificity compared to conventional MRI markers. Furthermore, the relative contribution of each MRI contrast within the networks can be used to optimize multi-contrast MRI acquisition. We anticipate our method to be a starting point for translation of MRI results into easy-to-understand virtual histology for neurobiologists and provide resources for validating novel MRI techniques.

bioengineering↗

bioRxiv2019

Slit/Robo signals prevent spinal motor neuron emigration by organizing the spinal cord basement membrane

The developing spinal cord builds a boundary between the CNS and the periphery, in the form of a basement membrane. The spinal cord basement membrane is a barrier that retains CNS neuron cell bodies, while being selectively permeable to specific axon types. Spinal motor neuron cell bodies are located in the ventral neural tube next to the floor plate and project their axons out through the basement membrane to peripheral targets. However, little is known about how spinal motor neuron cell bodies are retained inside the ventral neural tube, while their axons can exit. In previous work, we found that disruption of Slit/Robo signals caused motor neuron emigration outside the spinal cord. In the current study, we investigate how Slit/Robo signals are necessary to keep spinal motor neurons within the neural tube. Our findings show that when Slit/Robo signals were removed from motor neurons, they migrated outside the spinal cord. Furthermore, this emigration was associated with abnormal basement membrane protein expression in the ventral spinal cord. Using Robo2 and Slit2 conditional mutants, we found that motor neuron-derived Slit/Robo signals were required to set up a normal basement membrane in the spinal cord. Together, our results suggest that motor neurons produce Slit signals that are required for the basement membrane assembly to retain motor neuron cell bodies within the spinal cord.

developmental biology↗

bioRxiv2017

Decomposing the neural pathways mediating value-based choice

Understanding the neural implementation of value-based choice has been an important focus of neuroscience for several decades. Although a consensus has emerged regarding the brain regions involved, disagreement persists regarding precise regional functions and how value information flows between value-based choice regions.\n\nIn the current study, we isolate neural activity related to decision-making using a gambling task where expected gains and losses are dissociated from the received outcomes of choices. We apply multilevel modelling and mediation analysis to formally test whether brain regions identified as part of the value-based choice network mediate between perceptions of expected value and choices to take or pass a gamble.\n\nA critical function in decision-making is accruing and representing value information to drive choice. Several regions have been assigned this role, including ventromedial prefrontal (vmPFC) and posterior parietal cortex (PPC), and the ventral striatum (VStr). The implied chain of events is one where regions that support the process of gathering relevant information mediate the relationship between choice and representations of value in other brain regions. Here, we formally test whether distinct brain regions express interregional mediation consistent with this chain of processes.\n\nWe observe that activity in vmPFC does not predict choice, but rather is highly associated with outcome evaluation. By contrast, both PPC and VStr (bilaterally) mediate between expected value and choice. Interregional mediation analyses reveal that VStr fully mediates between PPC and choice. Together these results suggest that VStr, and not vmPFC nor PPC, functions as an important driver of late stage choice.\n\nSignificance StatementMaking choices that maximize gain and minimize loss is critical for success. Our paradigm and analytic approach allowed isolation of choice-related neural signals from outcome-related signals. The vmPFC is involved at outcome rather than at choice. Isolating choice-related neural activity, we formally demonstrate that VStr and PPC mediate between expected value and choice. Our approach adds significant innovation by using generalized multilevel modelling to predict behavior with concurrent neural activity and formally testing the fully mediated pathway from stimulus through neural activity to behavior. Applying interregional multilevel mediation analysis, we demonstrate that ventral striatum comprises a final, critical step in processing value-based choice, mediating the relationship between value representation and choice.

neuroscience↗