Biology subjects

Kim, G.

Publications and source records attributed to Kim, G..

At least 109 records · Page 6Linked to original sources

bioRxiv2021

Abrupt remapping in human CA3/dentate gyrus signals resolution of memory interference

Remapping refers to a decorrelation of hippocampal representations of similar spatial environments. While it has been speculated that remapping may contribute to the resolution of episodic memory interference in humans, direct evidence is surprisingly limited. Here, we tested this idea using high-resolution, pattern-based fMRI analyses. We show that activity patterns in human CA3/dentate gyrus exhibit an abrupt, temporally-specific decorrelation of highly similar memory representations that is precisely coupled with behavioral expressions of successful learning. Strikingly, the magnitude of this learning-related decorrelation was predicted by the amount of pattern overlap during initial stages of learning, with greater initial overlap leading to stronger decorrelation. Finally, we show that remapped activity patterns carry relatively more information about learned episodic associations compared to competing associations, further validating the learning-related significance of remapping. Collectively, these findings establish a critical link between hippocampal remapping and episodic memory interference and provide novel insight into why remapping occurs.

neuroscience↗

bioRxiv2021

DRscDB: A single-cell RNA-seq resource for data mining and data comparison across species

With the advent of single-cell RNA sequencing (scRNA-seq) technologies, there has been a spike in studies involving scRNA-seq of several tissues across diverse species including Drosophila. Although a few databases exist for users to query genes of interest within the scRNA-seq studies, search tools that enable users to find orthologous genes and their cell type-specific expression patterns across species are limited. Here, we built a new search database, called DRscDB (https://www.flyrnai.org/tools/single_cell/web/) to address this need. DRscDB serves as a comprehensive repository for published scRNA-seq datasets for Drosophila and the relevant datasets from human and other model organisms. DRscDB is based on manual curation of Drosophila scRNA-seq studies of various tissue types and their corresponding analogous tissues in vertebrates including zebrafish, mouse, and human. Of note, our search database provides most of the literature-derived marker genes, thus preserving the original analysis of the published scRNA-seq datasets. DRscDB serves as a web-based user interface that allows users to mine, utilize and compare gene expression data pertaining to scRNA-seq datasets from the published literature.

bioinformatics↗

bioRxiv2021

Using Bayesian Optimization to Identify Optimal Exoskeleton Parameters Targeting Propulsion Mechanics: A Simulation Study

In this study, we determined the feasibility of modeling the relationship between robot control parameters and propulsion mechanics as a Gaussian process. Specifically, we used data obtained in a previous experiment that used pulses of torque applied at the hip and knee joint, at early and late stance, to establish the relationship a 3D control parameter space and the resulting changes in hip extension and propulsive impulse. We estimated Gaussian models both at the group level and for each subject. Moreover, we used the estimated subject-specific models to simulate virtual human-in-the-loop optimization (HIL) experiments based on Bayesian optimization to establish their convergence under multiple combinations of acquisition functions and seed point selection methods. Results of the group-level model are in agreement with those obtained with linear mixed effect model, thus establishing the feasibility of Gaussian process modeling. The estimated subject-specific optimal conditions have large between-subject variability in the metric of propulsive impulse, with only 31% of subjects featuring a subject-specific optimal point in the surrounding of the group-level optimal point. Virtual HIL experiments indicate that expected improvement is the most effective acquisition method, while no significant effect of seed point selection method was observed. Our study may have practical effects on the adoption of HIL robot-assisted training methods focused on propulsion.

bioengineering↗

bioRxiv2020

A genome-scale yeast library with inducible expression of individual genes

The ability to switch a gene from off to on and monitor dynamic changes provides a powerful approach for probing gene function and elucidating causal regulatory relationships, including instances of feedback control. Here, we developed and characterized YETI (Yeast Estradiol strains with Titratable Induction), a collection in which 5,687 yeast genes are engineered for transcriptional inducibility with single-gene precision at their native loci and without plasmids. Each strain contains Synthetic Genetic Array (SGA) screening markers and a unique molecular barcode, enabling high-throughput yeast genetics. We characterized YETI using quantitative growth phenotyping and pooled BAR-seq screens, and we used a YETI allele to characterize the regulon of ROF1, showing that it is a transcriptional repressor. We observed that strains with inducible essential genes that have low native expression can often grow without inducer. Analysis of data from other eukaryotic and prokaryotic systems shows that low native expression is a critical variable that can bias promoter-perturbing screens, including CRISPRi. We engineered a second expression system, Z3EB42, that gives lower expression than Z3EV, a feature enabling both conditional activation and repression of lowly expressed essential genes that grow without inducer in the YETI library.

synthetic biology↗

bioRxiv2020

Heterogeneous Mediation Analysis for Causal Inference

DNA methylation (DNAm) has been suggested to play a critical role in post-traumatic stress disorder (PTSD), through mediating the relationship between trauma and PTSD. However, this underlying mechanism of PTSD for African Americans still remains unknown. To fill this gap, in this paper, we investigate how DNAm mediates the effects of traumatic experiences on PTSD symptoms in the Detroit Neighborhood Health Study (DNHS) (2008-2013) which involves primarily African Americans adults. To achieve this, we develop a new mediation analysis approach for high-dimensional potential DNAm mediators. A key novelty of our method is that we consider heterogeneity in mediation effects across sub-populations. Specifically, mediators in different sub-populations could have opposite effects on the outcome, and thus could be difficult to identify under a traditional homogeneous model framework. In contrast, the proposed method can estimate heterogeneous mediation effects and identifies sub-populations in which individuals share similar effects. Simulation studies demonstrate that the proposed method outperforms existing methods for both homogeneous and heterogeneous data. We also present our mediation analysis results of a dataset with 125 participants and more than 450, 000 CpG sites from the DNHS study. The proposed method finds three sub-groups of subjects and identifies DNAm mediators corresponding to genes such as HSP90AA1 and NFATC1 which have been linked to PTSD symptoms in literature. Our finding could be useful in future finer-grained investigation of PTSD mechanism and in the development of new treatments for PTSD.

bioinformatics↗

bioRxiv2020

Live imaging of breast tumors shows macrophage-dependent induction and TMEM-mediated enrichment of cancer stem cells during metastatic dissemination

Cancer stem cells (CSCs) play an important role during metastasis, but the dynamic behavior and induction mechanisms of CSCs are not well understood. We employed high-resolution intravital microscopy using a CSC biosensor to directly observe CSCs in live mice with mammary tumors. CSCs display the slow-migratory, invadopod-rich phenotype that is the hallmark of disseminating tumor cells. CSCs are enriched near macrophages, particularly near macrophage-containing intravasation sites called Tumor Microenvironment of Metastasis (TMEM) doorways. A dramatic enrichment of CSCs occurs on association with TMEM doorways, contributing to the finding that CSCs represent [~]>60% of circulating tumor cells. Mechanistically, stemness is induced in non-stem cancer cells upon their direct contact with macrophages via Notch signaling. In breast cancers from patients, the density of TMEM doorways correlates strongly with the proportion of cancer cells expressing stem cell markers, indicating that in human breast cancer TMEM doorways are not only cancer cell intravasation portals but also CSC programming sites. One Sentence SummaryIntravital imaging reveals macrophage-mediated induction of cancer stem cells in vivo and their dramatic enrichment on dissemination through TMEM doorways.

cancer biology↗

bioRxiv2020

Data-driven multiplexed microtomography of endogenous subcellular dynamics

Simultaneous imaging of various facets of intact biological systems across multiple spatiotemporal scales would be an invaluable tool in biomedicine. However, conventional imaging modalities have stark tradeoffs precluding the fulfilment of all functional requirements. Here we propose the refractive index (RI), an intrinsic quantity governing light-matter interaction, as a means for such measurement. We show that major endogenous subcellular structures, which are conventionally accessed via exogenous fluorescence labeling, are encoded in 3D RI tomograms. We decode this information in a data-driven manner, thereby achieving multiplexed microtomography. This approach inherits the advantages of both high-specificity fluorescence imaging and label-free RI imaging. The performance, reliability, and scalability of this technology have been extensively characterized, and its application within single-cell profiling at unprecedented scales has been demonstrated.

bioengineering↗

bioRxiv2020

Double Emulsion Picoreactors for High-Throughput Single-Cell Encapsulation and Phenotyping via FACS

In the past five years, droplet microfluidic techniques have unlocked new opportunities for the high-throughput genome-wide analysis of single cells, transforming our understanding of cellular diversity and function. However, the field lacks an accessible method to screen and sort droplets based on cellular phenotype upstream of genetic analysis, particularly for large and complex cells. To meet this need, we developed Dropception, a robust, easy-to-use workflow for precise single-cell encapsulation into picoliter-scale double emulsion droplets compatible with high-throughput phenotyping via fluorescence-activated cell sorting (FACS). We demonstrate the capabilities of this method by encapsulating five standardized mammalian cell lines of varying size and morphology as well as a heterogeneous cell mixture of a whole dissociated flatworm (5 - 25 m in diameter) within highly monodisperse double emulsions (35 m in diameter). We optimize for preferential encapsulation of single cells with extremely low multiple-cell loading events (<2% of cell-containing droplets), thereby allowing direct linkage of cellular phenotype to genotype. Across all cell lines, cell loading efficiency approaches the theoretical limit with no observable bias by cell size. FACS measurements reveal the ability to discriminate empty droplets from those containing cells with good agreement to single-cell occupancies quantified via microscopy, establishing robust droplet screening at single-cell resolution. High-throughput FACS phenotyping of cellular picoreactors has the potential to shift the landscape of single-cell droplet microfluidics by expanding the repertoire of current nucleic acid droplet assays to include functional screening. ABSTRACT FIGURE O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=85 SRC="FIGDIR/small/139311v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@9d2028org.highwire.dtl.DTLVardef@1aa55b3org.highwire.dtl.DTLVardef@1e05eb3org.highwire.dtl.DTLVardef@1695a88_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2020

Novel Immunoassay for Diagnosis of Ongoing Clostridioides difficile Infections Using Serum and Medium Enriched for Newly Synthesized Antibodies (MENSA)

BACKGROUNDClostridioides difficile infections (CDI) have been a challenging and increasing serious concern in recent years. While early and accurate diagnosis is crucial, available assays have frustrating limitations OBJECTIVEDevelop a simple, blood-based immunoassay to accurately diagnose patients suffering from active CDI. MATERIALS AND METHODSUninfected controls (n=95) and CDI patients (n=167) were recruited from Atlanta area hospitals. Blood samples were collected from patients within twelve days of a positive CDI test and processed to yield serum and PBMCs cultured to yield medium enriched for newly synthesized antibodies (MENSA). Multiplex immunoassays measured Ig responses to ten recombinant C. difficile antigens. RESULTSSixty-six percent of CDI patients produced measurable responses to C. difficile antigens in their serum or MENSA within twelve days of a positive CDI test. Fifty-two of the 167 CDI patients (31%) were detectable in both serum and MENSA, but 32/167 (19%) were detectable only in MENSA, and 27/167 (16%) were detectable only in serum. DISCUSSIONWe describe the results of a multiplex immunoassay for the diagnosis of ongoing CDI in hospitalized patients. Our assay resolved patients into four categories: MENSA-positive only, serum-positive only, MENSA- and serum-positive, and MENSA- and serum-negative. The MENSA positive-only patients accounted for 30% and may be attributed to nascent antibody secretion in MENSA prior to seroconversion. Conversely, the serum positive-only subset may have been more advanced in their disease course. Immunocompromise and misdiagnosis may have contributed to the 34% of CDI patients who were not identified using MENSA or serum immunoassays. IMPORTANCEWhile there was considerable overlap between patients identified through MENSA and serum, both methods detected additional, unique patients. The combined use of both MENSA and serum to detect CDI patients resulted in the greatest identification of CDI patients. Together, longitudinal analysis of MENSA and serum will provide a more accurate evaluation of successful host humoral immune responses in CDI patients.

microbiology↗

bioRxiv2020

Genetic dissection of glutamatergic neuron subpopulations and developmental trajectories in the cerebral cortex

Diverse types of glutamatergic pyramidal neurons (PyNs) mediate the myriad processing streams and output channels of the cerebral cortex, yet all derive from neural progenitors of the embryonic dorsal telencephalon. Here, we establish genetic strategies and tools for dissecting and fate mapping PyN subpopulations based on their developmental and molecular programs. We leverage key transcription factors and effector genes to systematically target the temporal patterning programs in progenitors and differentiation programs in postmitotic neurons. We generated over a dozen temporally inducible mouse Cre and Flp knock-in driver lines to enable combinatorial targeting of major progenitor types and projection classes. Intersectional converter lines confer viral access to specific subsets defined by developmental origin, marker expression, anatomical location and projection targets. These strategies establish an experimental framework for understanding the hierarchical organization and developmental trajectory of PyN subpopulations that assemble cortical processing networks and output channels.

neuroscience↗

bioRxiv2020

Reliable data collection in participatory trials to assess digital healthcare apps.

The number of digital healthcare mobile apps on the market is increasing exponentially owing to the development of the mobile network and widespread usage of smartphones. However, only a few of these apps have undergone adequate validation. As with many mobile apps, healthcare apps are generally considered safe to use, making them easy for developers and end-users to exchange them in the marketplace. The existing platforms are not suitable to collect reliable data for evaluating the effectiveness of the apps. Moreover, these platforms only reflect the perspectives of developers and experts, not of end-users. For instance, data collection methods typical of clinical trials are not appropriate for participant-driven assessment of healthcare apps because of their complexity and high cost. Thus, we identified a need for a participant-driven data collection platform for end-users that is interpretable, systematic, and sustainable --as a first step to validate the effectiveness of the apps. To collect reliable data in the participatory trial format, we defined distinct stages for data preparation, storage, and sharing. Interpretable data preparation consists of a protocol database system and semantic feature retrieval method to create a protocol without professional knowledge. Collected data reliability weight calculation belongs to the systematic data storage stage. For sustainable data collection, we integrated the weight method and the future reward distribution function. We validated the methods through statistical tests conducted on 718 human participants. The validation results demonstrate that the methods have significant differences in the comparative experiment and prove that the choice of the right method is essential for reliable data collection. Furthermore, we created a web-based system for our pilot platform to collect reliable data in an integrated pipeline. We validate the platform features with existing clinical and pragmatic trial data collection platforms. In conclusion, we show that the method and platform support reliable data collection, forging a path to effectiveness validation of digital healthcare apps.

bioinformatics↗

bioRxiv2019

Spontaneous generation of face recognition in untrained deep neural networks

Face-selective neurons are observed in the primate visual pathway and are considered the basis of facial recognition in the brain. However, it is debated whether this neuronal selectivity can arise spontaneously, or requires training from visual experience. Here, we show that face-selective neurons arise spontaneously in random feedforward networks in the absence of learning. Using biologically inspired deep neural networks, we found that face-selective neurons arise under three different network conditions: one trained using non-face natural images, one randomized after being trained, and one never trained. We confirmed that spontaneously emerged face-selective neurons show the biological view-point-invariant characteristics observed in monkeys. Such neurons suddenly vanished when feedforward weight variation declined to a certain level. Our results suggest that innate face-selectivity originates from statistical variation of the feedforward projections in hierarchical neural networks.

neuroscience↗

bioRxiv2019

Spontaneous generation of innate number sense in untrained deep neural networks

Number-selective neurons are observed in numerically naive animals, but it was not understood how this innate function emerges in the brain. Here, we show that neurons tuned to numbers can arise in random feedforward networks, even in the complete absence of learning. Using a biologically inspired deep neural network, we found that number tuning arises in three cases of networks: one trained to non-numerical natural images, one randomized after trained, and one never trained. Number-tuned neurons showed characteristics that were observed in the brain following the Weber-Fechner law. These neurons suddenly vanished when the feedforward weight variation decreased to a certain level. These results suggest that number tuning can develop from the statistical variation of bottom-up projections in the visual pathway, initializing innate number sense.

neuroscience↗

bioRxiv2019

Optimized double emulsion flow cytometry with high-throughput single droplet isolation

Droplet microfluidics has made large impacts in diverse areas such as enzyme evolution, chemical product screening, polymer engineering, and single-cell analysis. However, while droplet reactions have become increasingly sophisticated, phenotyping droplets by a fluorescent signal and sorting them to isolate variants-of-interest remains a field-wide bottleneck. Here, we present an optimized double emulsion workflow, sdDE-FACS, that enables high-throughput phenotyping, selection, and sorting of droplets using standard flow cytometers. Using a 130 m nozzle, we demonstrate robust post-sort recovery of intact droplets, with little to no shear-induced droplet breakage, at high sort frequency (12-14 kHz) across two industry-standard FACS instruments. We report the first quantitative plate statistics for double emulsion droplet isolation and demonstrate single droplet recovery with >70% efficiency. In addition, we establish complete downstream recovery of nucleic acids from single, sorted double emulsion droplets, an advance in droplet sorting comparable with the capabilities of single-cell FACS. This work resolves several hurdles in the field of high-throughput droplet analysis and paves the way for a variety of new droplet assays, including rare variant isolation and multiparameter single-cell analysis, marrying the full power of flow cytometry with droplet microfluidics.

bioengineering↗

bioRxiv2019

Integration of locomotion and auditory signals in the mouse inferior colliculus

The inferior colliculus (IC) is the major midbrain auditory integration center, where virtually all ascending auditory inputs converge. Although the IC has been extensively studied for sound processing, little is known about the neural activity of the IC in moving subjects, as frequently happens in natural hearing conditions. Here we show, by recording the IC neural activity in walking mice, the activity of IC neurons is strongly modulated by locomotion in the absence of sound stimulus presentation. Similar modulation was also found in deafened mice, demonstrating that IC neurons receive non-auditory, locomotion-related neural signals. Sound-evoked activity was attenuated during locomotion, and the attenuation increased frequency selectivity across the population, while maintaining preferred frequencies. Our results suggest that during behavior, integrating movement-related and auditory information is an essential aspect of sound processing in the IC.

neuroscience↗

bioRxiv2019

Simultaneous development and periodic clustering of simple and complex cells in visual cortex

Neurons in the primary visual cortex (V1) are often classified as simple or complex cells, but it is debated whether they are discrete hierarchical classes of neurons developing sequentially, or if they represent a continuum of variation within a single class of cells developing simultaneously. Herein, we show that simple and complex cells may arise simultaneously from the universal process of retinal development. From analysis of the cortical receptive fields in cats, we show evidence that simple and complex cells originate from the periodic variation of ON-OFF segregation in the feedforward projection of retinal mosaics, by which they organize into periodic clusters in V1. Our key prediction that clusters of simple and complex cells correlate topographically with orientation maps was confirmed by data in cats. Our results suggest that simple and complex cells are not two distinct neural populations but arise from common retinal afferents, simultaneous with orientation tuning.\n\nHighlightsO_LISimple and complex cells arise simultaneously from retinal afferents.\nC_LIO_LISimple/complex cells are organized into periodic clusters across visual cortex.\nC_LIO_LISimple/complex clusters are topographically correlated with orientation maps.\nC_LIO_LIDevelopment of clustered cells in V1 is explained by the Paik-Ringach model.\nC_LI

neuroscience↗

bioRxiv2019

Multipotent radial glia progenitors and fate-restricted intermediate progenitors sequentially generate diverse cortical interneuron types

GABAergic interneurons deploy numerous inhibitory mechanisms that regulate cortical circuit operation, but the developmental programs that generate diverse interneuron types are not yet well understood. We carried out a comprehensive genetic fate mapping of the radial glial progenitors (RGs) and intermediate progenitors (IP) in the medial ganglionic eminence (MGE) in mice. We reveal that Nkx2.1+ RGs are multipotent and mediate two consecutive waves of neurogenesis, each sequentially generating different sets of interneuron types that laminate the neocortex in an inside-out-inside order. The first wave begins early and is restricted to the caudal MGE, has limited neurogenic window and capacity, and involves mostly apical IPs. The second wave begins later throughout the MGE, has an extended time course and large neurogenic capacity, and features a large set of fate-restricted basal IPs that amplify and diversify interneurons. Chandelier cells are generated toward the end of each wave and laminate in an outside-in order. Therefore, separate pools of multipotent RGs deploy temporal cohorts of IPs to sequentially generate diverse interneuron types.

neuroscience↗

bioRxiv2019

MAPPING TRANSCRIPTION FACTOR NETWORKS BY COMPARING TF BINDING LOCATIONS TO TF PERTURBATION RESPONSES

BackgroundA transcription-factor (TF) network map indicates the direct, functional targets of each TF -- the genes it regulates by binding to their cis-regulatory DNA. Data on the genomic binding locations of each TF and the transcriptional responses to perturbations of its activity, such as overexpressing it, could support TF network mapping. Systematic data sets of both types exist for yeast and for human K562 and HEK293 cells.\n\nResultsIn previous data, most TF binding sites appear to be non-functional, so one cannot take the genes in whose promoters a TF binds as its direct, functional (DF) targets. Taking the genes that are both bound by a TF and responsive to a perturbation of it as its DF targets (intersection algorithm) is also not safe, as we show by deriving a new lower bound on the expected false discovery rate of the intersection algorithm. When there are many non-functional binding sites and many indirect targets, non-functional sites are expected to occur in the cis-regulatory DNA of indirect targets by chance. Dual threshold optimization, a new method for setting significance thresholds on binding and response data, improves the intersection algorithm, as does post-processing perturbation-response data with NetProphet 2.0. A comprehensive new data set measuring the transcriptional response shortly after inducing overexpression of a TF also helps, as does transposon calling cards, a new method for identifying TF binding locations.\n\nConclusionsThe combination of dual threshold optimization and NetProphet greatly expands the high-confidence TF network map in both yeast and human. In yeast, measuring the response shortly after inducing TF overexpression and measuring binding locations by using transposon calling cards improve the network synergistically.

genomics↗