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Chung, T.

Publications and source records attributed to Chung, T..

14 recordsLinked to original sources

Human meningiomas arise from developmental meningeal mosaicism

Meningioma is the most common primary intracranial tumour, yet its genetic origin and the temporal sequence of mutational events remain poorly defined. Here, we analysed 80 triple-matched tumour, histologically normal meninges, and blood samples from 22 patients. NF2 or TRAF7 driver mutations are detectable in phenotypically normal meninges in 81.8% of cases (95% CI: 59.7-94.8%; VAF [~]0.02%), corroborated by high-depth sequencing, single-cell cloning, and phylogenetic analysis. By distinguishing developmental mosaic mutations from postnatal tumour-private mutations, we revealed distinct mutational signatures and resolved the temporal sequence of meningioma evolution. The developmental origin was further underscored in patients with multiple meningiomas, where identical driver mutations were shared across genomically distinct tumours and meninges, and in intraventricular meningiomas (IVM), where driver mutations were detected in distant cranial dura. Reconstruction of mutational timing revealed lineage-specific trajectories, linking mosaicism to diverse disease presentations including solitary meningioma, IVM, meningiomatosis, and NF2-related schwannomatosis. Together, these findings reveal an early origin of human meningioma, in which developmental mosaicism establishes a pre-neoplastic field within the meninges, providing a developmental framework for adult tumourigenesis.

Cancer Biology↗

Chronic activation of a key exercise signal transducer, CaMKII, drives skeletal muscle aging and sarcopenia

Sarcopenia, the age-related loss of muscle strength and mass, contributes to adverse health outcomes in older adults. While exercise mitigates sarcopenia by transiently activating calcium (Ca2+)- and reactive oxygen species (ROS)-dependent signaling pathways that enhance muscle performance and adaptation, these same signals become chronically elevated in aged skeletal muscle and promote functional decline. Ca2+/calmodulin-dependent protein kinase II (CaMKII) is a key transducer of both Ca2+ and ROS signals during exercise. Here we show that CaMKII is chronically activated in aged muscles, promoting muscle dysfunction. Muscle-specific expression of a constitutively active CaMKII construct in young mice recapitulates features of aging muscles, including impaired contractility, progressive atrophy, mitochondrial disorganization, formation of tubular aggregates, and an older transcriptional profile characterized by the activation of inflammatory and stress response pathways. Mediation analysis identified altered heme metabolism as a potential mechanism of CaMKII-induced weakness, independent of muscle atrophy. Conversely, partial inhibition of CaMKII in aged muscle improved contractile function and shifted the transcriptome toward a more youthful state without inducing hypertrophy. These findings identify chronic CaMKII activation as a driver of functional and molecular muscle aging and support the concept that CaMKII exemplifies antagonistic pleiotropy, whereby its beneficial roles in promoting muscle performance and adaptation during youth may incur deleterious consequences in aging. We propose that persistent CaMKII activation in aged skeletal muscle reflects unresolved cellular stress and promotes maladaptive remodeling. Enhancing physiological reserve capacity through exercise, in combination with temporally targeted CaMKII inhibition, may help restore adaptive CaMKII signaling dynamics and preserve muscle function in aging.

physiology↗

Optimization of connectome weights for a neural network model generating both forward and backward locomotion in C. elegans.

Previous studies tracking the relationship between manipulations of C. elegans neurons and the resulting behavioral changes have called for the development of a connectome-constrained neural network model that describes the cascade from neurons to behavior. However, the model using anatomical connectome weights as they are did not achieve that. Here, we introduce a concept of learning the synaptic weights in our connectome-constrained neural network model based on the leaky-integrator equation while preserving the structural proportions of anatomical synapses. In this process, the weights of gap junctions and chemical synapses in C. elegans neurons are optimized. As a result, our neural network model generates plausible C. elegans behavior mediated by activity changes in forward and backward command neurons, even without the introduction of pacemaker neurons with intrinsic oscillatory activity. Additionally, we identified necessary or sufficient neurons for maintaining oscillatory patterns on muscular activity that could serve as clues for the central pattern generator in our neural network model. Finally, we provide 10 optimized synaptic weights sets of C. elegans that reproduce the results of manipulation experiments on the SMD neurons. This study will facilitate the future study for unraveling the multiscale relationship of "from synapse to behavior" in nervous system. Significance StatementIn the anatomical connectome of C. elegans, synaptic weights have been considered less important than network topology in designing neural network models for behavior generation. In this study, we introduce an advanced process that optimizes the synaptic weights of C. elegans based on the anatomical connectome weights through machine learning. Our neural network model, incorporating the optimized connectome weights, successfully reproduced both forward and backward locomotion in response to the on/off transitions of command neurons. Through this model, we were able to evaluate how manipulations of specific neurons translate into behavioral changes and to what extent they manifest. This study sets a foundation for exploring the intricate links between neural network structure, neuronal activity, and behavior in living systems.

neuroscience↗

Single nucleotide polymorphisms associated with cytotoxicity of Bacillus cereus group strains in Caco-2 cells

Bacillus cereus sensu lato (s.l.) encompasses strains with diverse impacts, ranging from foodborne illness and anthrax to beneficial applications in agriculture and industry. While the risk of anthrax and emetic intoxication can be reliably predicted by the presence of specific virulence genes, predicting diarrheal foodborne illness risk based solely on enterotoxin gene presence has proven unreliable. In this study, we evaluated cytotoxicity against Caco-2 human gut cells using a diverse collection of B. cereus s.l. isolates representing all eight panC phylogenetic groups and conducted genomic analyses to identify predictive markers of cytotoxicity. Isolates from panC groups I, IV, and V exhibited significantly higher cytotoxicity compared to other groups, although individual isolates from other panC groups have also been linked to illness. Logistic and random forest regression models revealed that while the presence of enterotoxin genes was a sensitive indicator of cytotoxicity, it lacked specificity. Logistic regression analysis identified 21 nonsynonymous single nucleotide polymorphisms (SNPs) within enterotoxin (Nhe and Hbl) gene sequences that were more effective predictors of cytotoxicity, providing higher specificity with comparable sensitivity. These SNPs achieved accuracy and precision values exceeding 0.7. Random forest models highlighted the importance of panC group, enterotoxin gene SNPs, and the presence of the full hbl operon as key predictors of cytotoxicity. The strong sensitivity, specificity, and biological relevance of these SNPs position them as promising markers for improving strain-based risk assessment of B. cereus s.l. IMPORTANCEEnterotoxin genes have been associated with B. cereus sensu lato (s.l.) diarrheal foodborne illness; however, their mere presence in a genome is an unreliable predictor of an isolates cytotoxicity towards human gut epithelial cells. To improve food safety risk assessment, more specific markers of cytotoxicity are required. In this study, we identified nonsynonymous SNPs within the coding sequences of the enterotoxins Nhe and Hbl. These SNPs offer potential targets for rapid molecular tests to identify B. cereus s.l. isolates with an elevated food safety risk due to their capacity to inflict cytotoxic damage on human gut epithelial cells. Implementation of such markers upon validation could improve consumer safety while reducing food waste.

microbiology↗

Wavenumber-dependent transmission of subthreshold waves on electrical synapses network model of Caenorhabditis elegans

Recent experimental studies showed that electrically coupled neural networks like in mammalian inferior olive nucleus generate synchronized rhythmic activity by the subthreshold sinusoidal-like oscillations of the membrane voltage. Understanding the basic mechanism and its implication of such phenomena in the nervous system bears fundamental importance and requires preemptively the connectome information of a given nervous system. Inspired by these necessities of developing a theoretical and computational model to this end and, however, in the absence of connectome information for the inferior olive nucleus, here we investigated interference phenomena of the subthreshold oscillations in the reference system Caenorhabditis elegans for which the structural anatomical connectome was completely known recently. We evaluated how strongly the sinusoidal wave was transmitted between arbitrary two cells in the model network. The region of cell-pairs that are good at transmitting waves changed according to the wavenumber of the wave, for which we named a wavenumber-dependent transmission map. Also, we unraveled that 1) the transmission of all cell-pairs disappeared beyond a threshold wavenumber, 2) long-distance and regular patterned transmission existed in the body-wall muscles part of the model network, and 3) major hub cell-pairs of the transmission were identified for many wavenumber conditions. A theoretical and computational model presented in this study provided fundamental insight for understanding how the multi-path constructive/destructive interference of the subthreshold oscillations propagating on electrically coupled neural networks could generate wavenumber-dependent synchronized rhythmic activity.

biophysics↗

Comparison of the performance of multiple whole-genome sequence-based tools for the identification of Bacillus cereus sensu stricto biovar Thuringiensis

The Bacillus cereus sensu stricto (s.s.) species comprises strains of biovar Thuringiensis (Bt) known for their bioinsecticidal activity, as well as strains with foodborne pathogenic potential. Bt strains are identified (i) based on the production of insecticidal crystal proteins also known as Bt toxins or (ii) based on the presence of cry, cyt, and vip genes, which encode Bt toxins. Multiple bioinformatics tools have been developed for the detection of crystal protein-encoding genes based on whole-genome sequencing (WGS) data. However, the performance of these tools is yet to be evaluated using phenotypic data. Thus, the goal of this study was to assess the performance of four bioinformatics tools for the detection of crystal protein-encoding genes. The accuracy of sequence-based identification of Bt was determined in reference to phenotypic microscope-based screening for production of crystal proteins. A total of 58 diverse B. cereus s.l. strains isolated from clinical, food, environmental, and commercial biopesticide products were underwent WGS. Isolates were examined for crystal protein production using phase contrast microscopy. Crystal protein-encoding genes were detected using BtToxin_Digger, BTyper3, IDOPS, and Cry_processor. Out of 58 isolates, the phenotypic production of crystal proteins was confirmed for 18 isolates. Specificity and sensitivity of Bt identification based on sequences were 0.85 and 0.94 for BtToxin_Digger, 0.97 and 0.89 for BTyper3, 0.95 and 0.94 for IDOPS, and 0.88 and 1.00 for Cry_processor, respectively. Cry_processor predicted crystal protein production with highest specificity, and BtToxin_Digger and IDOPS predicted crystal protein production with the highest sensitivity. Three out of four tested bioinformatic tools performed well overall, with IDOPS achieving both high sensitivity and specificity (>0.90). IMPORTANCEBacillus cereus s.s. biovar Thuringiensis (Bt) is used as an organic biopesticide. It is differentiated from the foodborne pathogen Bacillus cereus s.s. by the production of insecticidal crystal proteins. Thus, reliable genomic identification of biovar Thuringiensis is necessary to ensure food safety and facilitate risk assessment. This study assessed the accuracy of WGS-based identification of Bt compared to phenotypic microscopy-based screening for crystal protein production. Multiple bioinformatics tools were compared to assess their performance in predicting crystal protein production. Among them, IDOPS performed best overall at WGS- based Bt identification.

bioinformatics↗

A community-curated, global atlas of Bacillus cereus sensu lato genomes for epidemiological surveillance

The ability to cause foodborne illness, anthrax, and other infections has been attributed to numerous lineages within Bacillus cereus sensu lato (s.l.). However, existing pathogen surveillance databases facilitate dangerous pathogen misidentifications when applied to B. cereus s.l., potentially hindering outbreak or bioterrorism attack response efforts. To address this, we developed BTyperDB (www.btyper.app), an atlas of B. cereus s.l. genomes with standardized, community-curated metadata. BTyperDB aggregates all publicly available B. cereus s.l. genomes (including >2,600 previously unassembled genomes) with novel genomes donated by laboratories around the world, nearly doubling the number of publicly available B. cereus s.l. genomes. To showcase its utility for pathogen surveillance, we use BTyperDB to identify emerging anthrax toxin- and capsule-harboring lineages. Overall, our study provides insight into the epidemiology of an under-studied group of emerging pathogens and highlights the benefits of inclusive, community-driven metadata FAIRification efforts.

microbiology↗

ElegansBot: Development of equation of motion deciphering locomotion including omega turns of Caenorhabditis elegans

Locomotion is a fundamental behavior of Caenorhabditis elegans (C. elegans). Previous works on kinetic simulations of animals helped researchers understand the physical mechanisms of locomotion and the muscle-controlling principles of neuronal circuits as an actuator part. It has yet to be understood how C. elegans utilizes the frictional forces caused by the tension of its muscles to perform sequenced locomotive behaviors. Here, we present a two-dimensional rigid body chain model for the locomotion of C. elegans by developing Newtonian equations of motion for each body segment of C. elegans. Having accounted for friction-coefficients of the surrounding environment, elastic constants of C. elegans, and its kymogram from experiments, our kinetic model (ElegansBot) reproduced various locomotion of C. elegans such as, but not limited to, forward-backward-(omega turn)-forward locomotion constituting escaping behavior and delta-turn navigation. Additionally, ElegansBot precisely quantified the forces acting on each body segment of C. elegans to allow investigation of the force distribution. This model will facilitate our understanding of the detailed mechanism of various locomotive behaviors at any given friction-coefficients of the surrounding environment. Furthermore, as the model ensures the performance of realistic behavior, it can be used to research actuator-controller interaction between muscles and neuronal circuits.

animal behavior and cognition↗

Single cell profiling reveals strain-specific differences in myeloid inflammatory potential in the rat liver

Liver transplantation is currently the only treatment for end-stage liver disease and acute liver failure. Liver transplant rejection is among the most lethal complications of transplantation, and therapeutic development is limited by our lack of a comprehensive understanding of the cellular landscape of the liver. The laboratory rat (Rattus norvegicus), ideal in size as a model for surgical procedures, is a strong platform to study liver biology in the context of liver transplantation. Liver allograft rejection is known to be strain-specific in the rat model, although the transplantation is accepted without rejection in some strains, it leads to acute rejection in others. To shed light on the cellular landscape of the rat liver and build a foundation for strain comparison, we present a comprehensive single-cell transcriptomics map of the healthy rat liver of Lewis and Dark Agouti strains. Using a novel computational pipeline we developed to guide the detailed annotation of our rat liver atlas, we discovered that hepatic myeloid cells have strong Lewis and Dark Agouti strain-specific differences focused on inflammatory signaling pathways. We experimentally validated these strain-specific differences in myeloid inflammatory potential in vitro using intracellular cytokine staining. Our work provides the first examination of the multi-strain healthy rat liver by single cell transcriptomics and uncovers key insights into strain-specific differences in this valuable model animal. SummaryThe laboratory rat (Rattus norvegicus) is a standard model animal for orthotopic liver transplantation. Transplanting a liver from a Dark agouti (DA) to a Lewis (LEW) strain rat leads to transplant rejection and the reverse procedure leads to tolerance. Understanding this strain difference may help explain the cellular drivers of liver allograft rejection post-transplant. This study uses single-cell transcriptomics to better understand the complex cellular composition of the rat liver and unravels cellular and molecular sources of inter-strain hepatic variation. We generated single-cell transcriptomic maps of the livers of healthy DA and LEW rat strains and developed a novel, factor analysis-based bioinformatics pipeline to study data covariates, such as strain and batch. Using this approach, we discovered variations within hepatocyte and myeloid populations that explain how the states of these cells differ between strains in the healthy rat, which may explain why these strains respond differently to liver transplants.

genomics↗

Conditional forest models built using metagenomic data could accurately predict Salmonella contamination in Northeastern streams

The use of water contaminated with Salmonella for produce production contributes to foodborne disease burden. To reduce human health risks, there is a need for novel, targeted approaches for assessing the pathogen status of agricultural water. We investigated the utility of water microbiome data for predicting Salmonella contamination of streams used to source water for produce production. Grab samples were collected from 60 New York streams in 2018 and tested for Salmonella. Separately, DNA was extracted from the samples and used for Illumina shotgun metagenomic sequencing. Reads were trimmed and used to assign taxonomy with Kraken2. Conditional forest (CF), regularized random forest (RRF), and support vector machine (SVM) models were implemented to predict Salmonella contamination. Model performance was determined using 10-fold cross-validation repeated 10 times to quantify area under the curve (AUC) and Kappa score. Taxa identified as the most informative for accurately predicting Salmonella contamination based on conditional variable importance were compared to taxa identified by ALDEx2 as being differentially abundant between Salmonella-positive and - negative samples. CF models outperformed the other two algorithms based on AUC (0.82 - CF, 0.76 - RRF, 0.67 - SVM) and Kappa score (0.41- CF, 0.38 - RRF, 0.19 - SVM). CF and differential abundance tests both identified Aeromonas (VI = 0.32) and Tabrizicola (VI = 0.12) as the two most informative taxa for predicting Salmonella contamination. The taxa identified in this study warrant further investigation as indicators of Salmonella contamination in Northeastern freshwater streams. IMPORTANCEUnderstanding the associations between surface water microbiome composition and the presence of foodborne pathogens, such as Salmonella, can facilitate the identification of novel indicators of Salmonella contamination. This study assessed the utility of microbiome data and three machine learning algorithms for predicting Salmonella contamination of Northeastern streams. The research reported here both expanded the knowledge on the microbiome composition of surface waters and identified putative novel indicators (i.e., Aeromonas and Tabrizicola) for Salmonella in Northeastern streams. These putative indicators warrant further research to assess whether they are consistent indicators of Salmonella for regions, waterways, and years not represented in the dataset used in this study.

microbiology↗

Internally-controlled and dynamic optical measures of functional tumor biology

Imaging defined aspects of functional tumor biology with bioluminescent reporter transgenes is a popular approach amongst the research community in drug development, as it is sensitive, relatively high-throughput and low cost. However, the lack of internal controls subject functional bioluminescence to a number of unpredictable variables that reduce this powerful tool to semi-quantitative interpretation of large-scale effects. Here we report the generation of sensitive and quantitative live reporters for two key measures of functional cancer biology and pharmacologic stress: the cell cycle and oxidative stress. We developed a two-colored readout, where two independent enzymes convert a common imaging substrate into spectrally distinguishable light. The signal intensity of one color is dependent upon biological state, whereas the other color is constitutively expressed. The ratio of emitted colored light corrects the functional signal for independent procedural variables, substantially improving the robustness and interpretation of relatively low-fold changes in functional signal intensity after drug treatment. The application of these readouts in vitro is highly advantageous, as peak cell response to therapy can now be readily visualized for single or combination treatments and not simply assessed at an arbitrary and destructive timepoint. Spectral imaging in vivo can be challenging, but we also present evidence to show that the reporters can work in this context as well. Collectively, the development and validation of these internally controlled reporters allow researchers to robustly and dynamically visualize tumor cell biology in response to treatment. Given the prevalence of bioluminescence imaging, this presents significant and much needed opportunities for preclinical therapeutic development.

cancer biology↗

Brain Anatomical Covariation Patterns Linked to Binge Drinking and Age at First Full Drink Prior to 21 Years

Binge drinking and age at first full drink of alcohol prior to 21 years (AFD<21) have been linked to neuroanatomical differences in cortical and subcortical grey matter (GM) volume, cortical thickness, and surface area. Despite the potential to reveal novel network-level relationships, structural covariation patterns among these morphological measures have yet to be examined relative to binge drinking and AFD<21. Here, we used the Joint and Individual Variance Explained (JIVE) method to characterize structural covariation patterns common across and specific to morphological measures in 293 participants (149 individuals with binge drinking and 144 healthy controls) from the Human Connectome Project (HCP). An independent dataset (Nathan Kline Institute Rockland Sample; NKI-RS) was used to examine reproducibility/ generalizability. We identified a highly reproducible joint component dominated by structural covariation between GM volume in the brainstem and thalamus proper, and GM volume and surface area in prefrontal cortical regions. Using linear mixed regression models, we found that this joint component was related to AFD<21 in both the HCP and NKI-RS datasets, whereas the individual thickness component associated with binge drinking and AFD<21 in the HCP dataset was not statistically significant in the NKI-RS sample. Taken together, our results show that a highly reproducible structural pattern involving covariation in brain regions relevant to thalamic-PFC-brainstem neural circuitry is linked to age at first full drink.

neuroscience↗

Developmental differentiation in a cytoplasm-dwelling obligate intracellular bacterium

Orientia tsutsugamushi (Ot) is an obligate intracellular bacterium in the family Rickettsiaceae that causes scrub typhus, a severe mite-borne human disease. Its mechanism of cell exit is unusual amongst Rickettsiaceae, as Ot buds off the surface of infected cells enveloped in plasma membrane. Here, we show that Ot bacteria that have budded out of host cells are in a distinct developmental stage compared with intracellular bacteria. We refer to these two stages as intracellular and extracellular bacteria (IB and EB, respectively). These two forms differ in physical properties: IB is elongated, and EB is round. Additionally, IB has higher levels of peptidoglycan and is physically robust compared with EB. The two bacterial forms differentially express proteins involved in bacterial physiology and host-pathogen interactions, specifically those involved in bacterial dormancy and stress response, secreted bacterial effectors, and outer membrane autotransporter proteins ScaA and ScaC. Whilst both populations are infectious, entry of IB Ot is sensitive to inhibitors of both clathrin-mediated endocytosis and macropinocytosis, whereas entry of EB Ot is only sensitive to a macropinocytosis inhibitor. Our identification and detailed characterization of two developmental forms of Ot significantly advances our understanding of the intracellular lifecycle of an important human pathogen. Author SummaryOrientia tsutsugamushi (Ot) is a bacterial pathogen that causes scrub typhus, a mite-transmitted human disease. This illness is traditionally known to be endemic in the Asia-Pacific, but recent reports of Orientia-like organisms from the Middle East, Africa, and Latin America suggest that it may be globally distributed. Scrub typhus is associated with high mortality if not treated promptly with appropriate antibiotics. Ot is a highly specialized bacterium that can only replicate within living cells, either within the mite vector or in mammalian or human hosts. Ot exits infected cells using a unique mechanism that involves budding off the surface of infected cells. We have discovered that this unusual aspect of its lifecycle involves the bacteria themselves differentiating into a distinct growth form. Different growth forms have not been described in other members of the family Rickettsiaceae, and no other family members have been shown to bud out of host cells in a manner similar to Ot. We find that the two forms of Ot, which we refer to as intracellular and extracellular bacteria (IB and EB respectively), differ in physical properties and protein expression and infect cells through different mechanisms. The identification of structurally and functionally distinct forms of Ot elucidates a vital aspect of this pathogens intracellular life cycle. The two forms are likely to have different antibiotic susceptibilities, therefore our findings may advance the development of novel interventions aimed at inhibiting Ot growth in scrub typhus patients.

microbiology↗

Neurocognitive development of inhibitory control and substance use vulnerability

Previous research indicates that risk for substance use is associated with poor inhibitory control. However, it remains unclear whether at risk youth use follow divergent patterns of inhibitory control development. As part of the longitudinal National Consortium on Adolescent Neurodevelopment and Alcohol (NCANDA) study, participants (N = 113, baseline age: 12-21) completed a rewarded antisaccade task during fMRI, with up to three time points. We examined whether substance use risk factors, including dimensional measures of psychopathology (externalizing, internalizing) and family history of substance use disorder, were associated with developmental differences in inhibitory control performance and BOLD activation at both the trial-level and within individual antisaccade epochs (cue, preparation, and response). Among substance use risk factors, only externalizing psychopathology predicted developmental differences in inhibitory control, where high externalizing predicted lower correct response rates and faster latencies were observed in early adolescence, but normalized by late adolescence. Neuroimaging results revealed high externalizing was associated with developmentally-stable hypo-activation in the left middle frontal gyrus (trial-level), but divergent developmental patterns of posterior parietal cortex activation (cue epoch). Developmental differences in inhibitory control associated with externalizing suggest early adolescence may be a unique period of substance use vulnerability via cognitive and phenotypic disinhibition.\n\nHighlightsO_LICharacterized inhibitory control development in adolescents at-risk for substance use.\nC_LIO_LIExternalizing psychopathology is associated with lower antisaccade correct response rate and faster latencies in early adolescence.\nC_LIO_LIExternalizing performance differences normalize by late adolescence.\nC_LIO_LIExternalizing is associated with prefrontal hypo-activation across development.\nC_LIO_LIExternalizing moderates age-related increases in posterior parietal cortex activity.\nC_LI

neuroscience↗