Biology subjects

Chung, K.

Publications and source records attributed to Chung, K..

29 records · Page 2Linked to original sources

bioRxiv2020

Human brain organoids reveal accelerated development of cortical neuron classes as a shared feature of autism risk genes

Genetic risk for autism spectrum disorder (ASD) has been associated with hundreds of genes spanning a wide range of biological functions. The phenotypic alterations in the human brain resulting from mutations in ASD risk genes remain unclear, and the level at which these alterations converge on shared disease pathology is poorly understood. Here, we leveraged reproducible organoid models of the human cerebral cortex to identify cell type-specific developmental abnormalities associated with haploinsufficiency in three ASD risk genes, SUV420H1 (KMT5B), PTEN, and CHD8. We performed comprehensive single-cell RNA-sequencing (scRNA-seq) of over 400,000 cells, and proteomic analysis on individual organoids sampled at different developmental stages to investigate phenotypic convergence among these genes. We find that within a defined period of early cortical development, each of the three mutations demonstrates accelerated development of cortical neurons. Notably, they do so by affecting different neuronal populations: excitatory deep layer (SUV420H1) and callosal (PTEN) neurons, and inhibitory interneurons (CHD8). This work shows that haploinsufficiency in ASD risk genes converge on early developmental defects in the generation of neurons of the cortical microcircuit.

developmental biology↗

bioRxiv2019

Brain-wide mapping of contextual fear memory engram ensembles supports the dispersed engram complex hypothesis

GRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=145 SRC=\"FIGDIR/small/668483v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (34K):\norg.highwire.dtl.DTLVardef@1957e90org.highwire.dtl.DTLVardef@1a83d79org.highwire.dtl.DTLVardef@5bd5d5org.highwire.dtl.DTLVardef@133c879_HPS_FORMAT_FIGEXP M_FIG C_FIG SUMMARYNeuronal ensembles that hold specific memory (memory engrams) have been identified in the hippocampus, amygdala, and cortex. It has been hypothesized that engrams for a specific memory are distributed among multiple brain regions that are functionally connected. Here, we report the hitherto most extensive engram map for contextual fear memory by characterizing activity-tagged neurons in 409 regions using SHIELD-based tissue phenotyping. The mapping was aided by a novel engram index, which identified cFos+ brain regions holding engrams with a high probability. Optogenetic manipulations confirmed previously known engrams and revealed new engrams. Many of these engram holding-regions were functionally connected to the CA1 or amygdala engrams. Simultaneous chemogenetic reactivation of multiple engrams, which mimics natural memory recall, conferred a greater level of memory recall than reactivation of a single engram ensemble. Overall, our study supports the hypothesis that a memory is stored in functionally connected engrams distributed across multiple brain regions.

neuroscience↗

bioRxiv2019

Ultrafast immunostaining of organ-scale tissues for scalable proteomic phenotyping

Studying the function and dysfunction of complex biological systems necessitates comprehensive understanding of individual cells. Advancements in three-dimensional (3D) tissue processing and imaging modalities have enabled rapid visualization and phenotyping of cells in their spatial context. However, system-wide interrogation of individual cells within large intact tissue remains challenging, low throughput, and error-prone owing to the lack of robust labeling technologies. Here we introduce a rapid, versatile, and scalable method, eFLASH, that enables complete and uniform labeling of organ-scale tissue within one day. eFLASH dynamically modulates chemical transport and reaction kinetics to establish system-wide uniform labeling conditions throughout the day-long labeling period. This unique approach enables the same protocol to be compatible with a wide range of tissue types and probes, enabling combinatorial molecular phenotyping across different organs and species. We applied eFLASH to generate quantitative maps of various cell types in mouse brains. We also demonstrated multidimensional cell profiling in a marmoset brain block. We envision that eFLASH will spur holistic phenotyping of emerging animal models and disease models to help assess their functions and dysfunctions.

bioengineering↗

bioRxiv2019

The oncogenic Kaposi sarcoma-associated herpesvirus encodes a mimic of the tumor suppressive miR-15/16 miRNA family

Many tumor viruses encode oncogenes of cellular origin. Here, we report the first instance of an oncoviral mimic of a cellular tumor suppressor. The Kaposis sarcoma-associated herpesvirus (KSHV) miRNA miR-K6-5p shares sequence similarity to the tumor suppressive cellular miR-15/16 miRNA family. We show that miR-K6-5p inhibits cell cycle progression, a hallmark function of miR-16. miR-K6-5p regulates conserved miR-15/16 targets, including many cell cycle regulators. Inhibition of miR-K6-5p in KSHV-transformed B cells conferred a significant growth advantage. Altogether, our data show that KSHV encodes a functional mimic of the miR-15/16 miRNA family. While it is exceedingly well established that oncogenic viruses encode oncogenes of cellular origin, this is the first example of an oncogenic virus that encodes a viral mimic of a cellular tumor suppressor. Encoding a tumor suppressive miRNA could help KSHV balance viral oncogene expression and thereby avoid severe pathogenesis in the healthy host.

microbiology↗

bioRxiv2019

Scalable image processing techniques for quantitative analysis of volumetric biological images from light-sheet microscopy

Here we describe an image processing pipeline for quantitative analysis of terabyte-scale volumetric images of SHIELD-processed mouse brains imaged with light-sheet microscopy. The pipeline utilizes open-source packages for destriping, stitching, and atlas alignment that are optimized for parallel processing. The destriping step removes stripe artifacts, corrects uneven illumination, and offers over 100x speed improvements compared to previously reported algorithms. The stitching module builds upon Terastitcher to create a single volumetric image quickly from individual image stacks with parallel processing enabled by default. The atlas alignment module provides an interactive web-based interface that automatically calculates an initial alignment to a reference image which can be manually refined. The atlas alignment module also provides summary statistics of fluorescence for each brain region as well as region segmentations for visualization. The expected runtime of our pipeline on a whole mouse brain hemisphere is 1-2 d depending on the available computational resources and the dataset size.

bioengineering↗

bioRxiv2018

Predicting One-Year Outcome in First Episode Psychosis using Machine Learning

Lay SummaryO_ST_ABSEvidence before this studyC_ST_ABSOur knowledge of factors which predict outcome in first episode psychosis (FEP) is incomplete. Poor premorbid adjustment, history of developmental disorder, symptom severity at baseline and duration of untreated psychosis are the most replicated predictors of poor clinical, functional, cognitive, and biological outcomes. Yet, such group level differences are not always replicated in individuals, nor can observational results be clearly equated with causation. Advanced machine learning techniques have potential to revolutionise medicine by looking at causation and the prediction of individual patient outcome. Within psychiatry, Koutsouleris et al employed machine learning to predict 4- and 52-week functional outcome in FEP to a 75% and 73.8% test-fold balanced accuracy on repeated nested internal cross-validation. The authors suggest that before employing a machine learning model \"into real-world care, replication is needed in external first episode samples\".\n\nAdded value of this studyWe believe our study to be the first externally validated evidence, in a temporally and geographically independent cohort, for predictive modelling in FEP at an individual patient level. Our results demonstrate the ability to predict both symptom remission and functioning (in employment, education or training (EET)) at one-year. The performance of our EET model was particularly robust, with an ability to accurately predict the one-year EET outcome in more than 85% of patients. Regularised regression results in sparse models which are uniquely interpretable and identify meaningful predictors of recovery including specific individual PANSS items, and social support. This builds on existing studies of group-level differences and the elegant work of Koutsouleris et al.\n\nImplications of all the available evidenceWe have demonstrated the externally validated ability to accurately predict one-year symptomatic and functional status in individual patients with FEP. External validation in a plausibly related temporally and geographically distinct population assesses model transportability to an untested situation rather than simply reproducibility alone. We propose that our results represent important and exciting progress in unlocking the potential of predictive modelling in psychiatric illness. The next step prior to implementation into routine clinical practice would be to establish whether, by the accurate identification of individuals who will have poor outcomes, we can meaningful intervene to improve their prognosis.\n\nAbstractO_ST_ABSBackgroundC_ST_ABSEarly illness course correlates with long-term outcome in psychosis. Accurate prediction could allow more focused intervention. Earlier intervention corresponds to significantly better symptomatic and functional outcomes.\n\nWe use routinely collected baseline demographic and clinical characteristics to predict employment, education or training (EET) status, and symptom remission in patients with first episode psychosis (FEP) at 1 year.\n\nMethods83 FEP patients were recruited from National Health Service (NHS) Glasgow between 2011 and 2014 to a 24-month prospective cohort study with regular assessment of demographic and psychometric measures. An external independent cohort of 79 FEP patients were recruited from NHS Glasgow and Edinburgh during a 12-month study between 2006 and 2009.\n\nElastic net regularised logistic regression models were built to predict binary EET status, period and point remission outcomes at 1 year on 83 Glasgow patients (training dataset). Models were externally validated on an independent dataset of 79 patients from Glasgow and Edinburgh (validation dataset). Only baseline predictors shared across both cohorts were made available for model training and validation.\n\nOutcomesAfter excluding participants with missing outcomes, models were built on the training dataset for EET status, period and point remission outcomes and externally validated on the validation dataset. Models predicted EET status, period and point remission with ROC area under curve (AUC) performances of 0.876 (95%CI: 0.864, 0.887), 0.630 (95%CI: 0.612, 0.647) and 0.652 (95%CI: 0.635, 0.670) respectively. Positive predictors of EET included baseline EET and living with spouse/children. Negative predictors included higher PANSS suspiciousness, hostility and delusions scores. Positive predictors for symptom remission included living with spouse/children, and affective symptoms on the Positive and Negative Syndrome Scale (PANSS). Negative predictors of remission included passive social withdrawal symptoms on PANSS.\n\nInterpretationUsing advanced statistical machine learning techniques, we provide the first externally validated evidence for the ability to predict 1-year EET status and symptom remission in FEP patients.\n\nFundingThe authors acknowledge financial support from NHS Research Scotland, the Chief Scientist Office, the Wellcome Trust, and the Scottish Mental Health Research Network.

neuroscience↗

bioRxiv2018

Initial Characterization of the Two ClpP Paralogs of Chlamydia trachomatis Suggests Unique Functionality for Each

Chlamydia is an obligate intracellular bacterium that differentiates between two distinct functional and morphological forms during its developmental cycle: elementary bodies (EBs) and reticulate bodies (RBs). EBs are non-dividing, small electron dense forms that infect host cells. RBs are larger, non-infectious replicative forms that develop within a membrane-bound vesicle, termed an inclusion. Given the unique properties of each developmental form of this bacterium, we hypothesized that the Clp protease system plays an integral role in proteomic turnover by degrading specific proteins from one developmental form or the other. Chlamydia has five uncharacterized clp genes: clpX, clpC, two clpP paralogs, and clpB. In other bacteria, ClpC and ClpX are ATPases that unfold and feed proteins into the ClpP protease to be degraded, and ClpB is a deaggregase. Here, we focused on characterizing the ClpP paralogs. Transcriptional analyses and immunoblotting determined these genes are expressed mid-cycle. Bioinformatic analyses of these proteins identified key residues important for activity. Over-expression of inactive clpP mutants in Chlamydia suggested independent function of each ClpP paralog. To further probe these differences, we determined interactions between the ClpP proteins using bacterial two-hybrid assays and native gel analysis of recombinant proteins. Homotypic interactions of the ClpP proteins, but not heterotypic interactions between the ClpP paralogs, were detected. Interestingly, ClpP2, but not ClpP1, protease activity was detected in vitro. This activity was stimulated by antibiotics known to activate ClpP, which also blocked chlamydial growth. Our data suggest the chlamydial ClpP paralogs likely serve distinct and critical roles in this important pathogen.\n\nImportanceChlamydia trachomatis is the leading cause of preventable infectious blindness and of bacterial sexually transmitted infections worldwide. Chlamydiae are developmentally regulated, obligate intracellular pathogens that alternate between two functional and morphologic forms with distinct repertoires of proteins. We hypothesize that protein degradation is a critical aspect to the developmental cycle. A key system involved in protein turnover in bacteria is the Clp protease system. Here, we characterized the two chlamydial ClpP paralogs by examining their expression in Chlamydia, their ability to oligomerize, and their proteolytic activity. This work will help understand the evolutionarily diverse Clp proteases in the context of intracellular organisms, which may aid in the study of other clinically relevant intracellular bacteria.

microbiology↗

bioRxiv2018

DNMT1 in Six2 progenitor cells is essential for transposable element silencing and kidney development

Cytosine methylation (5mC) plays a key role in maintaining progenitor cell self-renewal and differentiation. Here, we analyzed the role of 5mC in kidney development by genome-wide methylation, expression profiling, and by systematic genetic targeting of DNA methyltransferases (Dnmt) and Ten-eleven translocation methylcytosine hydroxylases (Tet).\n\nIn mice, nephrons differentiate from Six2+ progenitor cells, therefore we created animals with genetic deletion of Dnmt1, 3a, 3b, Tet1, and Tet2 in the Six2+ population (Six2Cre/Dnmt1flox/flox, Six2Cre/Dnmt3aflox/flox, Six2Cre/Dnmt3bflox/flox, Six2Cre/Tet2flox/flox and Tet1-/-). Animals with conditional deletion of Dnmt3a, 3b, Tet1 and Tet2 showed no significant structural or functional renal abnormalities. On the other hand, Six2Cre/Dnmt1flox/flox mice died within 24hrs of birth. Dnmt1 knock-out animals had small kidneys and significantly reduced nephron number. Genome-wide methylation analysis indicated marked loss of methylation mostly on transposable elements. RNA sequencing detected endogenous retroviral (ERV) gene transcripts and early embryonic genes. Increase in levels of interferon (and RIG-I signaling) and apoptosis (Trp53) in response to ERV activity likely contributed to the phenotype development. Once epithelial differentiation was established, loss of Dnmt1, 3a, 3b, Tet1 or Tet2 in glomerular epithelial cells did not lead to functional or structural differences at baseline or following toxic glomerular injury.\n\nGenome-wide cytosine methylation and gene expression profiling showed that Dnmt1-mediated DNA methylation is essential for kidney development by preventing regression of progenitor cells into a primitive undifferentiated state and demethylation of transposable elements.\n\nSignificanceCytosine methylation of regulatory regions (promoters and enhancers) has been proposed to play a key role in establishing gene expression and thereby cellular phenotype. DNMT1 is the key enzyme responsible for maintaining methylation patterns during DNA replication. While the role of Dnmt1 has been described in multiple organs, here we identified a novel, critically important mechanism how Dnmt1 controls tissue progenitors. The greatest methylation difference in Dnmt1 knock-out mice was observed on transposable elements (TE), which resulted in increase of endogenous retroviruses and cell death. We believe that release of TE was a critically overlooked component of phenotype development in previous studies that our comprehensive genome wide methylation analysis allowed us to identify.\n\nCompeting interestsThe Susztak lab receives research support from Biogen, Boehringer Ingelheim, Celgene, GSK, Merck, Regeneron and ONO Pharma for work not related to this manuscript.

developmental biology↗

bioRxiv2018

Exploring Mechanisms of Inhibition of Amyloid Seeding of Transthyretin

Amyloid deposition of the hormone transporter transthyretin causes familial and sporadic amyloidoses. The current treatment for familial cases is gene-therapy by liver transplantation. However, this procedure is often insufficient to stop subsequent cardiac deposition. Our recent work has shown that preformed amyloid fibrils present in the heart by the time of surgery can template or seed further polymerization of native transthyretin. No drugs have been approved to stop or slow this seeding process; the only treatment option is heart transplantation. Here we explore two potential inhibitory mechanisms. Of clinical significance, we found that tetramer stabilization does not hinder amyloid seeding. In contrast, binding of the peptide inhibitor TabFH2 to ex-vivo fibrils efficiently inhibits amyloid seeding in a tissue-independent manner. Our findings point to inhibition of amyloid seeding by peptide inhibitors as a potential therapeutic approach to be further explored.

biochemistry↗

bioRxiv2017

NINJA-Associated ERF19 Negatively Regulates Arabidopsis Pattern-Triggered Immunity

Recognition of microbe-associated molecular patterns (MAMPs) derived from invading pathogens by plant pattern recognition receptors (PRRs) initiates defense responses known as pattern-triggered immunity (PTI). Transcription factors (TFs) orchestrate the onset of PTI through complex signaling networks. Here, we characterize the function of ERF19, a member of the Arabidopsis thaliana ethylene response factor (ERF) family. ERF19 was found to act as a negative regulator of PTI against Botrytis cinerea and Pseudomonas syringae pv. tomato DC3000 (Pst). Notably, overexpression of ERF19 increased plant susceptibility to these pathogens and repressed MAMP-induced PTI outputs. In contrast, expression of the chimeric dominant repressor ERF19-SRDX boosted PTI activation, conferred increased resistance to B. cinerea, and enhanced elf18-triggered immunity against Pst. Consistent with a negative role of ERF19 in PTI, MAMP-mediated growth inhibition was respectively weakened or augmented in lines overexpressing ERF19 or expressing ERF19-SRDX. Moreover, we demonstrate that the transcriptional repressor Novel INteractor of JAZ (NINJA) associates with and represses the function of ERF19. Our work reveals ERF19 as a key player in a buffering mechanism to avoid defects imposed by over-activation of PTI and a potential role for NINJA in fine-tuning ERF19-mediated regulation.

plant biology↗

bioRxiv2017

3D Mapping Reveals Network-specific Amyloid Progression and Subcortical Susceptibility.

Alzheimers disease is a progressive, neurodegenerative condition for which there is no cure. Prominent hypotheses posit that accumulation of beta-amyloid (A{beta}) peptides drives the neurodegeneration that underlies memory loss, however the spatial origins of the lesions remain elusive. Using SWITCH, we created a spatiotemporal map of A{beta} deposition in a mouse model of amyloidosis. We report that structures connected by the fornix show primary susceptibility to A{beta} accumulation and demonstrate that aggregates develop in increasingly complex networks with age. Notably, the densest early A{beta} aggregates occur in the mammillary body coincident with electrophysiological alterations. In later stages, the fornix itself also develops overt A{beta} burden. Finally, we confirm A{beta} in the mammillary body of postmortem patient specimens. Together, our data suggest that subcortical memory structures are particularly vulnerable to A{beta} deposition and that functional alterations within and physical propagation from these regions may underlie the affliction of increasingly complex networks.\n\nAuthor ContributionsRGC, KC, L-HT, ID conceived of the work and planned the experiments.\n\nRGC, HC, JW, LAW, CGY, FA, SMB performed experiments and analyzed data.\n\nHC built the custom microscope.\n\nRGC, L-HT, KC, ID wrote the manuscript.

neuroscience↗