Biology subjects

Park, D. K.

Publications and source records attributed to Park, D. K..

7 recordsLinked to original sources

bioRxiv2025

Systematic yeast two-hybrid screening identifies novel functions for SET1C/COMPASS

Set1 is the catalytic subunit of SET1C or COMPASS, which methylates histone H3K4 and serves as a scaffold for the association of seven tightly bound polypeptides. We have employed yeast two-hybrid screenings to determine the interactome of Set1 and each subunit, providing a unique resource for exploring known and novel roles of the complex. Our screenings identified a multitude of potential interactors involved in chromatin regulation, DNA replication, meiotic breaks, and Ty transposition, processes previously associated with SET1C. Consistent with Set1 being an RNA-binding protein, the screens link SET1C to multiple aspects of RNA biogenesis, including pre-mRNA splicing and polyadenylation. The results reveal that several importins are candidate interactors of Set1, along with RGG motif-containing proteins, providing insights into the mechanisms by which Set1 moves between cytoplasmic and nuclear compartments. We further reveal that reconstituted SET1C interacts with the AT hook domain of the chromatin remodeler Snf2 and methylates multiple arginines within this domain. In vivo, we report that the ARTSTRGR AT-hook motif is methylated in a Set1-dependent manner revealing new interplay between lysine and arginine methylation.

molecular biology↗

bioRxiv2024

Quantum-classical hybrid approach for codon optimizationand its practical applications

Codon optimization is crucial for gene expression in heterologous hosts with varying genetic codes and codon usage, potentially resulting in enhanced protein expression and stability. Traditionally, the codon optimization problem has been solved using classical numerical techniques; however, with recent advancements, quantum algorithms deployed on quantum computers have been adopted for this purpose. This study proposes a codon sequence search protocol tailored to host preferences. Specifically, codon optimization is formulated as a constrained quadratic binary problem and solved using a quantum-classical hybrid approach, integrating quantum annealing with the Lagrange multiplier method. The proposed methodology is then applied to two real-world scenarios: optimizing the codon sequence of the severe respiratory syndrome coronavirus 2 spike protein in human hosts and insulin in Escherichia coli (E. coli) hosts. Finally, evaluations of several biological metrics demonstrate the effectiveness of our protocol, offering insights into the codon usage patterns governing translational efficiency and adaptation to the genetic code preferences of the host organisms.

bioinformatics↗

bioRxiv2024

D-Serine inhibits non-ionotropic NMDA receptor signaling

NMDA-type glutamate receptors (NMDARs) are widely recognized as master regulators of synaptic plasticity, most notably for driving long-term changes in synapse size and strength that support learning. NMDARs are unique among neurotransmitter receptors in that they require binding of both neurotransmitter (glutamate) and co-agonist (e.g. O_SCPLOWDC_SCPLOW-serine) to open the receptor channel, which leads to the influx of calcium ions that drive synaptic plasticity. Over the past decade, evidence has accumulated that NMDARs also support synaptic plasticity via ion flux-independent (non-ionotropic) signaling upon the binding of glutamate in the absence of co-agonist, although conflicting results have led to significant controversy. Here, we hypothesized that a major source of contradictory results can be attributed to variable occupancy of the co-agonist binding site under different experimental conditions. To test this hypothesis, we manipulated co-agonist availability in acute hippocampal slices from mice of both sexes. We found that enzymatic scavenging of endogenous co-agonists enhanced the magnitude of LTD induced by non-ionotropic NMDAR signaling in the presence of the NMDAR pore blocker, MK801. Conversely, a saturating concentration of O_SCPLOWDC_SCPLOW-serine completely inhibited both LTD and spine shrinkage induced by glutamate binding in the presence of MK801. Using a FRET-based assay in cultured neurons, we further found that O_SCPLOWDC_SCPLOW-serine completely blocked NMDA-induced conformational movements of the GluN1 cytoplasmic domains in the presence of MK801. Our results support a model in which O_SCPLOWDC_SCPLOW-serine inhibits ion flux-independent NMDAR signaling and plasticity, and thus O_SCPLOWDC_SCPLOW-serine availability could serve to modulate NMDAR signaling even when the NMDAR is blocked by magnesium. Significance StatementNMDARs are glutamate-gated cation channels that are key regulators of neurodevelopment and synaptic plasticity and unique in their requirement for binding of a co-agonist (e.g. O_SCPLOWDC_SCPLOW-serine) in order for the channel to open. NMDARs have been found to drive synaptic plasticity via non-ionotropic (ion flux-independent) signaling upon the binding of glutamate in the absence of co-agonist, though conflicting results have led to controversy. Here, we found that O_SCPLOWDC_SCPLOW-serine inhibits non-ionotropic NMDAR-mediated LTD and LTD-associated spine shrinkage. Thus, a major source of the contradictory findings might be attributed to experimental variability in O_SCPLOWDC_SCPLOW-serine availability. In addition, the developmental regulation of O_SCPLOWDC_SCPLOW-serine levels suggests a role for non-ionotropic NMDAR plasticity during critical periods of plasticity.

neuroscience↗

bioRxiv2022

Overestimated Polygenic Prediction due to Overlapping Subjects in Genetic Datasets

Recently, polygenic risk score (PRS) has gained significant attention in studies involving complex genetic diseases and traits. PRS is often derived from summary statistics, from which the independence between discovery and replication sets cannot be monitored. Prior studies, in which the independence is strictly observed, report a relatively low gain from PRS in predictive models of binary traits. We hypothesize that the independence assumption may be compromised when using the summary statistics, and suspect an overestimation bias in the predictive accuracy. To demonstrate the overestimation bias in the replication dataset, prediction performances of PRS models are compared when overlapping subjects are either present or removed. We consider the task of Alzheimers disease (AD) prediction across genetics datasets, including the International Genomics of Alzheimers Project (IGAP), AD Sequencing Project (ADSP), and Accelerating Medicine Partnership - Alzheimers Disease (AMP-AD). PRS is computed from either sequencing studies for ADSP and AMP-AD (denoted as rPRS) or the summary statistics for IGAP (sPRS). Two variables with the high heritability in UK Biobank, hypertension, and height, are used to derive an exemplary scale effect of PRS. Based on the scale effect, the expected performance of sPRS is computed for AD prediction. Using ADSP as a discovery set for rPRS on AMP-AD, {Delta}AUC and {Delta}R2 (performance gains in AUC and R2 by PRS) record 0.069 and 0.11, respectively. Both drop to 0.0017 and 0.0041 once overlapping subjects are removed from AMP-AD. sPRS is derived from IGAP, which records {Delta}AUC and {Delta}R2 of 0.051{+/-}0.013 and 0.063{+/-}0.015 for ADSP and 0.060 and 0.086 for AMP-AD, respectively. On UK Biobank, rPRS performances for hypertension assuming a similar size of discovery and replication sets are 0.0036{+/-}0.0027 ({Delta}AUC) and 0.0032{+/-}0.0028 ({Delta}R2). For height, {Delta}R2 is 0.029{+/-}0.0037. Considering the high heritability of hypertension and height of UK Biobank, we conclude that sPRS results from AD databases are inflated. The higher performances relative to the size of the discovery set were observed in PRS studies of several diseases. PRS performances for binary traits, such as AD and hypertension, turned out unexpectedly low. This may, along with the difference in linkage disequilibrium, explain the high variability of PRS performances in cross-nation or cross-ethnicity applications, i.e., when there are no overlapping subjects. Hence, for sPRS, potential duplications should be carefully considered within the same ethnic group.

genomics↗

bioRxiv2021

Non-ionotropic NMDA receptor signaling alters structural plasticity of dendritic spines in a mouse model of schizophrenia

Schizophrenia is a psychiatric disorder that affects over 20 million people globally. Notably, schizophrenia is associated with decreased density of dendritic spines and decreased levels of D-serine, a co-agonist required for opening of the N-methyl-D-aspartate receptor (NMDAR). We hypothesized that lowered D-serine levels associated with schizophrenia would enhance ion flux-independent signaling by the NMDAR, driving destabilization and loss of dendritic spines. We tested our hypothesis using the serine racemase knockout (SRKO) mouse model, which lacks the enzyme for D-serine production. We show that activity-dependent spine growth is impaired in SRKO mice, but can be acutely rescued by exogenous D-serine. Moreover, we find a significant bias of synaptic plasticity toward spine shrinkage in the SRKO mice as compared to wild-type littermates. Notably, we demonstrate that enhanced ion flux-independent signaling through the NMDAR contributes to this bias toward spine destabilization, which is exacerbated by an increase in synaptic NMDARs in hippocampal synapses of SRKO mice. Our results support a model in which lowered D-serine levels associated with schizophrenia enhance ion flux-independent NMDAR signaling and bias toward spine shrinkage and destabilization.

neuroscience↗

bioRxiv2020

Non-ionotropic NMDA receptor signaling gates bidirectional structural plasticity of dendritic spines

Experience-dependent refinement of neuronal connections is critically important for brain development and learning. Here we show that ion flow-independent NMDAR signaling is required for the long-term dendritic spine growth that is a vital component of brain circuit plasticity. We found that inhibition of p38 MAPK, shown to be downstream of non-ionotropic NMDAR signaling in LTD and spine shrinkage, blocked LTP-induced spine growth but not LTP. We hypothesized that non-ionotropic NMDAR signaling drives the cytoskeletal changes that support bidirectional spine structural plasticity. Indeed, we found that key signaling components downstream of non-ionotropic NMDAR function in LTD-induced spine shrinkage also are necessary for LTP-induced spine growth. Furthermore, NMDAR conformational signaling with coincident Ca2+ influx is sufficient to drive CaMKII-dependent long-term spine growth, even when Ca2+ is artificially driven through voltage-gated Ca2+ channels. Our results support a model in which non-ionotropic NMDAR signaling gates the bidirectional spine structural changes vital for brain plasticity.

neuroscience↗

bioRxiv2020

Molecular Mechanisms of Non-ionotropic NMDA Receptor Signaling

Structural plasticity of dendritic spines is a key component of the refinement of synaptic connections during learning. Recent studies highlight a novel role for the NMDA receptor (NMDAR), independent of ion flow, in driving spine shrinkage and LTD. Yet little is known about the molecular mechanisms that link conformational changes in the NMDAR to changes in spine size and synaptic strength. Here, using two-photon glutamate uncaging to induce plasticity in hippocampal CA1 neurons from mice and rats, we demonstrate that p38 MAPK is required downstream of conformational NMDAR signaling to drive both spine shrinkage and LTD at individual dendritic spines. In a series of pharmacological and molecular genetic experiments, we identify key components of the non-ionotropic NMDAR signaling pathway driving dendritic spine shrinkage, including the interaction between NOS1AP and nNOS, nNOS enzymatic activity, activation of MK2 and cofilin, and signaling through CaMKII. Our results represent a large step forward in delineating the molecular mechanisms of non-ionotropic NMDAR signaling that drive the shrinkage and elimination of dendritic spines during synaptic plasticity.

neuroscience↗