Biology subjects

Huang, Y.-C.

Publications and source records attributed to Huang, Y.-C..

9 recordsLinked to original sources

bioRxiv2018

Bright and photostable chemigenetic indicators for extended in vivo voltage imaging

Imaging changes in membrane potential using genetically encoded fluorescent voltage indicators (GEVIs) has great potential for monitoring neuronal activity with high spatial and temporal resolution. Brightness and photostability of fluorescent proteins and rhodopsins have limited the utility of existing GEVIs. We engineered a novel GEVI, Voltron, that utilizes bright and photostable synthetic dyes instead of protein-based fluorophores, extending the combined duration of imaging and number of neurons imaged simultaneously by more than tenfold relative to existing GEVIs. We used Voltron for in vivo voltage imaging in mice, zebrafish, and fruit flies. In mouse cortex, Voltron allowed single-trial recording of spikes and subthreshold voltage signals from dozens of neurons simultaneously, over 15 minutes of continuous imaging. In larval zebrafish, Voltron enabled the precise correlation of spike timing with behavior.

neuroscience↗

bioRxiv2018

A single-cell level and connectome-derived computational model of the Drosophila brain

Computer simulations play an important role in testing hypotheses, integrating knowledge, and providing predictions of neural circuit functions. While considerable effort has been dedicated into simulating primate or rodent brains, the fruit fly (Drosophila melanogaster) is becoming a promising model animal in computational neuroscience for its small brain size, complex cognitive behavior, and abundancy of data available from genes to circuits. Moreover, several Drosophila connectome projects have generated a large number of neuronal images that account for a significant portion of the brain, making a systematic investigation of the whole brain circuit possible. Supported by FlyCircuit (http://www.flycircuit.tw), one of the largest Drosophila neuron image databases, we began a long-term project with the goal to construct a whole-brain spiking network model of the Drosophila brain. In this paper, we report the outcome of the first phase of the project. We developed the Flysim platform, which 1) identifies the polarity of each neuron arbor, 2) predicts connections between neurons, 3) translates morphology data from the database into physiology parameters for computational modeling, 4) reconstructs a brain-wide network model, which consists of 20,089 neurons and 1,044,020 synapses, and 5) performs computer simulations of the resting state. We compared the reconstructed brain network with a randomized brain network by shuffling the connections of each neuron. We found that the reconstructed brain can be easily stabilized by implementing synaptic short-term depression, while the randomized one exhibited seizure-like firing activity under the same treatment. Furthermore, the reconstructed Drosophila brain was structurally and dynamically more diverse than the randomized one and exhibited both Poisson-like and patterned firing activities. Despite being at its early stage of development, this single-cell level brain model allows us to study some of the fundamental properties of neural networks including network balance, critical behavior, long-term stability, and plasticity.

bioinformatics↗

bioRxiv2018

Germline silencing of UASt depends on the piRNA pathway

One of the most extensively used techniques in Drosophila is the Gal4/UAS binary system, which allows tissue-specific misexpression or knockdown of specific genes of interest. The original UAS vector, UASt, can only be activated for transgene expression in somatic tissues and not in the germline cells. Rorth (1998) generated UASp, a modified UAS vector that is responsive to Gal4 in both somatic and germline tissues, by replacing both the hsp70 promoter and the SV40 3UTR with the P transposase promoter and the K10 3UTR respectively. At present, the mechanisms by which UASt is silenced in germline cells are not fully understood. Here, we report that the piRNA pathway is involved in suppressing UASt expression in ovarian germline cells. Individually knocking down or mutating components of the piRNA biogenesis pathway (e.g., Piwi, AGO3, Aub, Spn-E, and Vasa) resulted in the expression of the UASt-reporter (GFP or RFP) in the germline. An RNA-seq analysis of small RNAs revealed that the hsp70 promoter of UASt is targeted by piRNAs, and in the aub mutant ovary, the amount of piRNAs targeting the hsp70 promoter is reduced by around 40 folds. In contrast, the SV40 3UTR of the UASt, which happens to be targeted by the Nonsense-mediated RNA decay (NMD) pathway, is not responsible for germline UASt suppression, as UASt-reporters with NMD-insensitive 3UTRs fail to show germline expression. Taken together, our studies reveal a crucial role of the piRNA pathway, potentially via the suppression of the hsp70 promoter, in germline UASt silencing in Drosophila ovaries.

genetics↗

bioRxiv2018

Genome-wide identification of CDC34 that stabilizes EGFR and promotes lung carcinogenesis

To systematically identify ubiquitin pathway genes that are critical to lung carcinogenesis, we used a genome-wide silencing method in this study to knockdown 696 genes in non-small cell lung cancer (NSCLC) cells. We identified 31 candidates that were required for cell proliferation in two NSCLC lines, among which the E2 ubiquitin conjugase CDC34 represented the most significant one. CDC34 was elevated in tumor tissues in 67 of 102 (65.7%) NSCLCs, and smokers had higher CDC34 than nonsmokers. The expression of CDC34 was inversely associated with overall survival of the patients. Forced expression of CDC34 promoted, whereas knockdown of CDC34 inhibited lung cancer in vitro and in vivo. CDC34 bound EGFR and competed with E3 ligase c-Cbl to inhibit the polyubiquitination and subsequent degradation of EGFR. In EGFR-L858R and EGFR-T790M/Del(exon 19)-driven lung cancer in mice, knockdown of CDC34 by lentivirus mediated transfection of short hairpin RNA significantly inhibited tumor formation. These results demonstrate that an E2 enzyme is capable of competing with E3 ligase to inhibit ubiquitination and subsequent degradation of oncoprotein substrate, and CDC34 represents an attractive therapeutic target for NSCLCs with or without drug-resistant EGFR mutations.

cancer biology↗

bioRxiv2017

Excitatory Motor Neurons Function As Central Pattern Generators In An Anatomically Compressed Motor Circuit For Reverse Locomotion

Central pattern generators are cell- or network-driven oscillators that underlie motor rhythmicity. The existence and identity of C. elegans CPGs are unknown. Through cell ablation, electrophysiology, and calcium imaging, we identified oscillators for C. elegans reverse locomotion. We show that the cholinergic and excitatory class A motor neurons exhibit intrinsic and oscillatory activity, and such an activity can drive reverse locomotion without premotor interneurons. Regulation of their oscillatory activity, either through effecting the P/Q/N high voltage-activated calcium channel, an endogenous constituent of their intrinsic oscillation, or, via the dual regulation by descending premotor interneurons, determines the propensity, velocity, and sustention of reverse locomotion. Thus, the reversal motor neuron themselves serve as distributed local oscillators; regulation of their intrinsic activity controls the reversal motor state. These findings exemplify anatomic and functional compression: motor executors integrate the role of rhythm generation in a locomotor network that is constrained by small cell numbers.\n\nHighlightsO_LIThe class A motor neurons (A-MNs) intrinsically oscillate.\nC_LIO_LIHigh voltage-activated calcium channel is a constituent of A-MN oscillation.\nC_LIO_LIRegulation of A-MN oscillation by interneurons determines the reversal state.\nC_LIO_LIA-MNs integrate the role of multiple neuron types in large locomotor networks.\nC_LI

neuroscience↗

bioRxiv2017

Biologics-associated Risks for Incident Skin and Soft Tissue Infections in Psoriasis Patients: Results from Propensity Score-Stratified Survival Analysis

BackgroundHow biologics affect psoriasis patients risks for SSTIs in a pragmatic clinical setting remains unclear.\n\nMethodsIn a cohort of adult psoriasis outpatients (aged 20 years or older) who visited the Dermatology Clinic in 2010-2015, we compared incident SSTI risks between patients using biologics (users) versus nonbiologics (nonusers). We also estimated SSTI risks in biologics-associated time-periods relative to nonbiologics only in users. We applied random effects Cox proportional hazard models with propensity score-stratification to account for differential baseline hazards.\n\nResultsOver a median follow-up of 2.8 years (interquartile range: 1.5, 4.3), 172 of 922 patients ever received biologics (18.7%); 233 SSTI incidents occurred during 2518.3 person-years, with an overall incidence of 9.3/100 person-years (95% confidence interval [CI]: 8.1, 10.6). In univariate analysis, users showed an 89% lower risk for SSTIs than nonusers (hazard ratio [HR]: 0.11, 95%CI: 0.05, 0.26); the association persisted in a multivariable model (adjusted HR: 0.26, 95%CI: 0.12, 0.58). Among biologics users, biologics-exposed time-periods were associated with a nonsignificant 21% increased risk (adjusted HR: 1.21, 95%CI: 0.41, 3.59).\n\nConclusionsDespite of adjusting for the underlying risk profiles, risk comparisons between biologics users and nonusers remained confounded by treatment selection. By comparing time-periods being exposed versus unexposed to biologics among users, the current analysis did not find evidence for an increased SSTI risk that was associated with biologics use in psoriasis patients.

epidemiology↗

bioRxiv2017

Mupirocin-associated temporal changes in the nasal microbiota and host’s antimicrobial responses: A pilot study in healthy staphylococcal carriers

BackgroundHow mupirocin affects the human nasal microbiota over time remains uncharacterized.\n\nMethodsWe repeatedly sampled the anterior nares of four healthy staphylococcal carriers before and after mupirocin use. By sequencing bacterial 16S ribosomal cDNA, we characterized sequential changes in the carriage status, the nasal microbiota, and the hosts antimicrobial peptide expression up to 90 days after decolonization.\n\nResultsBefore mupirocin use, the nasal microbiota differed by the initial, culture-based staphylococcal carriage status, with Firmicutes (54.1%) being the most predominant in carriers and Proteobacteria (75.8%) in the only noncarrier. The nasal microbiota became less diverse (Shannon diversity: 1.33, 95% confidence interval [CI]: 1.06-1.54) immediately after decolonisation than that before decolonisation (1.78, 95%CI: 0.58-1.93). Based on results of differential abundance analysis, Firmicutes were significantly enriched (log2 fold changes [≥] 4, Benjamini-Hochberg adjusted P < .01) while Actinobacteria, particularly Corynbebacterium, were relatively depleted in samples from staphylococcal carriers. Results of nonmetric multidimensional scaling (NMDS) and constrained correspondence analysis (CCA) also suggested that the initial staphylococcal carriage status, human neutrophil peptide 1 levels, and sampling times were major contributors to the between-community dissimilarities (P for marginal permutation test: .014) though the significance attenuated when within-group correlation was considered (P for blocked permutation test: .047).\n\nConclusionThese findings suggest that large-scale investigations on antibiotic effects on the human nasal microbiota are warranted.

microbiology↗

bioRxiv2016

The Fruit Fly Brain Observatory: from structure to function

The Fruit Fly Brain Observatory (FFBO) is a collaborative effort between experimentalists, theorists and computational neuroscientists at Columbia University, National Tsing Hua University and Sheffield University with the goal to (i) create an open platform for the emulation and biological validation of fruit fly brain models in health and disease, (ii) standardize tools and methods for graphical rendering, representation and manipulation of brain circuits, (iii) standardize tools for representation of fruit fly brain data and its abstractions and support for natural language queries, (iv) create a focus for the neuroscience community with interests in the fruit fly brain and encourage the sharing of fruit fly brain structural data and executable code worldwide. NeuroNLP and NeuroGFX, two key FFBO applications, aim to address two major challenges, respectively: i) seamlessly integrate structural and genetic data from multiple sources that can be intuitively queried, effectively visualized and extensively manipulated, ii) devise executable brain circuit models anchored in structural data for understanding and developing novel hypotheses about brain function. NeuroNLP enables researchers to use plain English (or other languages) to probe biological data that are integrated into a novel database system, called NeuroArch, that we developed for integrating biological and abstract data models of the fruit fly brain. With powerful 3D graphical visualization, NeuroNLP presents a highly accessible portal for the fruit fly brain data. NeuroGFX provides users highly intuitive tools to execute neural circuit models with Neurokernel, an open-source platform for emulating the fruit fly brain, with full data support from the NeuroArch database and visualization support from an interactive graphical interface. Brain circuits can be configured with high flexibility and investigated on multiple levels, e.g., whole brain, neuropil, and local circuit levels. The FFBO is publicly available and accessible at http://fruitflybrain.org from any modern web browsers, including those running on smartphones.

neuroscience↗

bioRxiv2016

NeuroNLP: a natural language portal for aggregated fruit fly brain data

NeuroNLP, is a key application on the Fruit Fly Brain Observatory platform (FFBO, http://fruitflybrain.org), that provides a modern web-based portal for navigating fruit fly brain circuit data. Increases in the availability and scale of fruit fly connectome data, demand new, scalable and accessible methods to facilitate investigation into the functions of the latest complex circuits being uncovered. NeuroNLP enables in-depth exploration and investigation of the structure of brain circuits, using intuitive natural language queries that are capable of revealing the latent structure and information, obscured due to expansive yet independent data sources. NeuroNLP is built on top of a database system call NeuroArch that codifies knowledge about the fruit fly brain circuits, spanning multiple sources. Users can probe biological circuits in the NeuroArch database with plain English queries, such as \"show glutamatergic local neurons in the left antennal lobe\" and \"show neurons with dendrites in the left mushroom body and axons in the fan-shaped body\". This simple yet powerful interface replaces the usual, cumbersome checkboxes and dropdown menus prevalent in todays neurobiological databases. Equipped with powerful 3D visualization, NeuroNLP standardizes tools and methods for graphical rendering, representation, and manipulation of brain circuits, while integrating with existing databases such as the FlyCircuit. The userfriendly graphical user interface complements the natural language queries with additional controls for exploring the connectivity of neurons and neural circuits. Designed with an open-source, modular structure, it is highly scalable/flexible/extensible to additional databases or to switch between databases and supports the creation of additional parsers for other languages. By supporting access through a web browser from any modern laptop or smartphone, NeuroNLP significantly increases the accessibility of fruit fly brain data and improves the impact of the data in both scientific and educational exploration.

neuroscience↗