Biology subjects

Cho, Y.

Publications and source records attributed to Cho, Y..

64 records · Page 4Linked to original sources

bioRxiv2020

Viscous medium-based crystal support in sample holder for fixed-target serial femtosecond crystallography

Serial femtosecond crystallography (SFX) enables the determination of a room-temperature crystal structure of macromolecules without causing radiation damage, as well as provides time-resolved molecular dynamics data in pump-probe experiments. Fixed-target SFX (FT-SFX) can minimize sample consumption and physical effects to crystals during sample delivery. Various types of sample holders have been developed and applied in FT-SFX; however, no sample holder has been developed that can universally mount crystals of various sizes and shapes. Here, we introduce a viscous media-based crystal support in a sample holder for FT-SFX. Crystal samples were embedded in viscous media such as gelatin and agarose, which were enclosed in a polyimide film. In the vertically placed sample holder, the viscous medium stably supported crystals between the two polyimide films without crystal sinking due to gravity. Using this method, we performed FT-SFX experiments with glucose isomerase and lysozyme embedded in gelatin and agarose, respectively. The room-temperature crystal structures of glucose isomerase and lysozyme were successfully determined at 1.75 and 1.80 [A] resolutions, respectively. Viscous media used in this experiment showed negligible background scattering in data processing. This method is useful for delivering crystal samples of various sizes and shapes in FT-SFX experiments.

biophysics↗

bioRxiv2019

Noncoding de novo mutations contribute to autism spectrum disorder via chromatin interactions

Three-dimensional chromatin structures regulate gene expression across genome. The significance of de novo mutations (DNMs) affecting chromatin interactions in autism spectrum disorder (ASD) remains poorly understood. We generated 931 whole-genome sequences for Korean simplex families to detect DNMs and identified target genes dysregulated by noncoding DNMs via long-range chromatin interactions between regulatory elements. Notably, noncoding DNMs that affect chromatin interactions exhibited transcriptional dysregulation implicated in ASD risks. Correspondingly, target genes were significantly involved in histone modification, prenatal brain development, and pregnancy. Both noncoding and coding DNMs collectively contributed to low IQ in ASD. Indeed, noncoding DNMs resulted in alterations, via chromatin interactions, in target gene expression in primitive neural stem cells derived from human induced pluripotent stem cells from an ASD subject. The emerging neurodevelopmental genes, not previously implicated in ASD, include CTNNA2, GRB10, IKZF1, PDE3B, and BACE1. Our results were reproducible in 517 probands from MSSNG cohort. This work demonstrates that noncoding DNMs contribute to ASD via chromatin interactions.

neuroscience↗

bioRxiv2019

HeALTH: An Automated Platform for Long-term Longitudinal Studies of Whole Organisms under Precise Environmental Control

Health and longevity in all organisms are strongly influenced by the environment. To fully understand how environmental factors interact with genetic and stochastic factors to modulate the aging process, it is crucial to precisely control environmental conditions for long-term studies. In the commonly used model organism Caenorhabditis elegans, existing assays for healthspan and lifespan have inherent limitations, making it difficult to perform large-scale, longitudinal aging studies under precise environmental control. To address this constraint, we developed the Health and Lifespan Testing Hub (HeALTH), an automated, microfluidic-based system for robust, long-term, longitudinal behavioral monitoring. Our system provides spatiotemporal environmental control. We demonstrate health and lifespan studies under a variety of genetic and environmental perturbations while observing how individuality plays a role in the aging process. This system is generalizable beyond aging research for C. elegans, particularly for short- or long-term behavioral assays, and is also possible to be adapted for other model systems.

animal behavior and cognition↗

bioRxiv2019

High specificity of widely used phospho-tau antibodies validated using a quantitative whole-cell based assay

Antibodies raised against defined phosphorylation sites of the microtubule-associated protein tau are widely used in scientific research and being applied in clinical assays. However, recent studies have revealed an alarming degree of non-specific binding found in these antibodies. In order to quantify and compare the specificity phospho-tau antibodies and other post-translational modification site-specific antibodies in general, a measure of specificity is urgently needed. Here we report a robust flow cytometry assay using human embryonic kidney (HEK) cells that enables the determination of a specificity parameter termed {Phi}, which measures the fraction of non-specific signal in antibody binding. We validate our assay using anti-tau antibodies with known specificity profiles, and apply it to measure the specificity of 7 widely used phospho-tau antibodies (AT270, AT8, AT100, AT180, PHF-6, TG-3, and PHF-1) among others. We successfully determined the {Phi} values for all antibodies except AT100, which did not show detectable binding in our assay. Our results show that antibodies AT8, AT180, PHF-6, TG-3, and PHF-1 have {Phi} values near 1, which indicates no detectable non-specific binding. AT270 showed {Phi} value around 0.8, meaning that approximately 20% of the binding signal originates from non-specific binding. Further analyses using immunocytochemistry and western blotting confirmed the presence of non-specific binding of AT270 to non-tau proteins found in HEK cells and the mouse hippocampus. We anticipate that the quantitative approach and parameter introduced here will be widely adopted as a standard for reporting the specificity for phospho-tau antibodies, and potentially for post-translational modification targeting antibodies in general.

biochemistry↗

bioRxiv2019

Within-family studies for Mendelian randomization: avoiding dynastic, assortative mating, and population stratification biases

Mendelian randomization (MR) is a widely-used method for causal inference using genetic data. Mendelian randomization studies of unrelated individuals may be susceptible to bias from family structure, for example, through dynastic effects which occur when parental genotypes directly affect offspring phenotypes. Here we describe methods for within-family Mendelian randomization and through simulations show that family-based methods can overcome bias due to dynastic effects. We illustrate these issues empirically using data from 61,008 siblings from the UK Biobank and Nord-Trondelag Health Study. Both within-family and population-based Mendelian randomization analyses reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while MR estimates from population-based samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects largely disappeared in within-family MR analyses. We found differences between population-based and within-family based estimates, indicating the importance of controlling for family effects and population structure in Mendelian randomization studies.

genetics↗

bioRxiv2018

MR-TRYX: Exploiting horizontal pleiotropy to infer novel causal pathways

In Mendelian randomization (MR) analysis, variants that exert horizontal pleiotropy are typically treated as a nuisance. However, they could be valuable in identifying novel pathways to the traits under investigation. Here, we developed the MR-TRYX framework, following the advice of William Bateson to \"TReasure Your eXceptions\". We begin by detecting outliers in a single exposure-outcome MR analysis, hypothesising they are due to horizontal pleiotropy. We search across thousands of complete GWAS summary datasets in the MR-Base database to systematically identify other (\"candidate\") traits that associate with the outliers. We developed a multi-trait pleiotropy model of the heterogeneity in the exposure-outcome analysis due to pathways through candidate traits. Through detailed investigation of several causal relationships, many pleiotropic pathways were uncovered with already established causal effects, validating the approach, but also novel putative causal pathways. Adjustment for pleiotropic pathways reduced the heterogeneity across the analyses.

bioinformatics↗

bioRxiv2018

Instant Automated Inference of Perceived Mental Stress through Smartphone PPG and Thermal Imaging

BackgroundA smartphone is a promising tool for daily cardiovascular measurement and mental stress monitoring. Photoplethysmography (PPG) and low-cost thermography can be used to create cheap, convenient and mobile systems. However, to achieve robustness, a person has to remain still for several minutes while a measurement is being taken. This is very cumbersome, and limits the usage in applications such producing instant measurements of stress.\n\nObjectiveWe propose to use smartphone-based mobile PPG and thermal imaging to provide a fast binary measure of stress responses to an event using dynamical physiological changes which occur within 20 seconds of the event finishing.\n\nMethodsWe propose a system that uses a smartphone and its physiological sensors to reliably and continuously measure over a short window of time a persons blood volume pulse, the time interval between heartbeats (R-R interval) and the 1D thermal signature of the nose tip. 17 healthy participants, involved in a series of stress-inducing mental activities, measured their physiological response to stress in the 20 second-window immediately following each activity. A 10-cm Visual Analogue Scale was used by them to self-report their level of mental stress. As a main labeling strategy, normalized K-means clustering is used to better treat interpersonal differences in ratings. By taking an array of the R-R intervals and thermal directionality as a low-level feature input, we mainly use an artificial neural network to enable the automatic feature learning and the machine learning inference process. To compare the automated inference performance, we also extracted widely used high level features from HRV (e.g., LF/HF ratio) and the thermal signature and input them to a k-nearest neighbor to infer perceived stress levels.\n\nResultsFirst, we tested the physiological measurement reliability. The measured cardiac signals were considered highly reliable (signal goodness probability used, Mean=0.9584, SD=0.0151). The proposed 1D thermal signal processing algorithm effectively minimized the effect of respiratory cycles on detecting the apparent temperature of the nose tip (respiratory signal goodness probability Mean=0.8998 to Mean=0). Second, we tested the 20 seconds instant perceived stress inference performance. The best results were obtained by using automatic feature learning and classification using artificial neural networks rather than using pre-crafted features. The combination of both modalities produced higher accuracy on the binary classification task using 17-fold leave-one-subject-out (LOSO) cross-validation (accuracy: HRV+Thermal: 76.96%; HRV: 60.29%; Thermal: 61.37%). The results are comparable with the state of the art automatic stress recognition methods requiring long term measurements (a minimum of 2 minutes for up to around 80% accuracy from LOSO). Lastly, we explored the impact of different data labeling strategies used in the field on the sensitivity of our inference methods and the need for normalization within individual.\n\nConclusionsResults demonstrate the capability of smartphone biomedical imaging in instant mental stress recognition. Given that this approach does not require long measurements requiring attention and reduced mobility, it is more feasible for mobile mental healthcare solution in the wild.

physiology↗

bioRxiv2018

Pharmacological modulation of AMPA receptor surface diffusion restores hippocampal synaptic plasticity and memory in Huntington’s disease

Impaired hippocampal synaptic plasticity is increasingly considered to play an important role in cognitive impairment in Huntingtons disease (HD). However, the molecular basis of synaptic plasticity defects is not fully understood. Combining live-cell nanoparticle tracking and super-resolution imaging, we show that dysregulation of AMPA receptors (AMPARs) surface diffusion represents a molecular basis underlying the aberrant hippocampal synaptic plasticity during HD. AMPARs surface diffusion is increased in various HD neuronal models, which results in the failure of AMPARs surface stabilization after long-term potentiation (LTP) stimuli. This appears to result from a defective brain-derived neurotrophic factor (BDNF) - tyrosine receptor kinase B (TrkB) - Ca2+/calmodulin-dependent protein kinase II (CaMKII) signaling pathway that impacts the interaction between the AMPAR auxiliary subunit stargazin and postsynaptic density protein 95 (PSD-95). Notably, the disturbed AMPAR surface diffusion is rescued, via BDNF signaling pathway and by the antidepressant tianeptine. Tianeptine also restores the impaired LTP and hippocampus-dependent memory as well as anxiety/depression-like behavior in different HD mouse models. We thus unveil a mechanistic framework underlying hippocampal synaptic and memory dysfunction and propose a new perspective in HD treatment by targeting AMPAR surface diffusion.

neuroscience↗

bioRxiv2017

Myotis rufoniger Genome Sequence and Analyses: M. rufoniger’s Genomic Feature and the Decreasing Effective Population Size of Myotis Bats

Myotis rufoniger is a vesper bat in the genus Myotis. Here we report the whole genome sequence and analyses of the M. rufoniger. We generated 124 Gb of short-read DNA sequences with an estimated genome size of 1.88 Gb at a sequencing depth of 66x fold. The sequences were aligned to M. brandtii bat reference genome at a mapping rate of 96.50% covering 95.71% coding sequence region at 10x coverage. The divergence time of Myotis bat family is estimated to be 11.5 million years, and the divergence time between M. rufoniger and its closest species M. davidii is estimated to be 10.4 million years. We found 1,239 function-altering M. rufoniger specific amino acid sequences from 929 genes compared to other Myotis bat and mammalian genomes. The functional enrichment test of the 929 genes detected amino acid changes in melanin associated DCT, SLC45A2, TYRP1, and OCA2 genes possibly responsible for the M. rufonigers red fur color and a general coloration in Myotis. N6AMT1 gene, associated with arsenic resistance, showed a high degree of function alteration in M. rufoniger. We further confirmed that M. rufoniger also has bat-specific sequences within FSHB, GHR, IGF1R, TP53, MDM2, SLC45A2, RGS7BP, RHO, OPN1SW, and CNGB3 genes that have already been published to be related to bats reproduction, lifespan, flight, low vision, and echolocation. Additionally, our demographic history analysis found that the effective population size of Myotis clade has been consistently decreasing since [~]30k years ago. M. rufonigers effective population size was the lowest in Myotis bats, confirming its relatively low genetic diversity.

genomics↗

bioRxiv2017

High-Throughput Controlled Mechanical Stimulation and Functional Imaging In Vivo

Understanding mechanosensation and other sensory behavior in genetic model systems such as C. elegans is relevant to many human diseases. These studies conventionally require immobilization by glue and manual delivery of stimuli, leading to low experimental throughput and high variability. Here we present a microfluidic platform that delivers precise mechanical stimuli robustly. The system can be easily used in conjunction with functional imaging and optical interrogation techniques, as well as other capabilities such as sorting or more sophisticated fluid delivery schemes. The platform is fully automated, thereby greatly enhancing the throughput and robustness of experiments. We show that behavior of the well-known gentle and harsh touch neurons and their receptive fields can be recapitulated in our system. Using calcium dynamics as a readout, we demonstrate the ability to perform a drug screen in vivo. Furthermore, using an integrated chip platform that can deliver both mechanical and chemical stimuli, we examine sensory integration in interneurons in response to multimodal sensory inputs. We envision that this system will be able to greatly accelerate the discovery of genes and molecules involved in mechanosensation and multimodal sensory behavior, as well as the discovery of therapeutics for related diseases.

bioengineering↗