Biology subjects

Wong, A.

Publications and source records attributed to Wong, A..

7 recordsLinked to original sources

bioRxiv2018

Altered protein quality control contributes to noise-induced hearing loss

Exposure to damaging levels of noise is the most common cause of hearing loss and impairs high frequency hearing in more than 15 % of adult Americans. Using mice exposed to increasing levels of noise in combination with quantitative proteomics, we tested how noise insults remodel the cochlear proteome both acutely and after a two-week recovery period. We used ABR & DPOAE recordings to define the intensity of noise exposure necessary to produce temporary or permanent threshold shifts (TTS, PTS) in young adult mice and found noise at 94 and 105 dB SPL levels for 30 minutes elicits TTS and PTS, respectively. We quantified thousands of proteins and found that noise insults cause a rapid increase rather than a decrease in the levels of many proteins involved with protein homeostasis, myelin, cytoskeletal structures, and cell junctions such as the synapse. The vast majority of proteins with increased levels immediately after noise exposure showed normal levels after two weeks of recovery. However, several proteins involved in oxidative stress and neuroprotection had significantly increased levels only after the recovery period suggesting they play in important role in regeneration. Interestingly, a small panel of mitochondrial proteins were significantly altered only in PTS conditions suggesting potential discrete protein mechanisms. Our discovery-based proteomic analysis extends the recent description of noise-induced cochlear synaptopathy and shows that noise insults drive a robust proteostasis response. These data provide a new understanding of noise sensitive proteins and may inform the development of effective preventiative strategies or therapies for NIHL.

neuroscience↗

bioRxiv2018

High-performance GFP-based calcium indicators for imaging activity in neuronal populations and microcompartments

Calcium imaging with genetically encoded calcium indicators (GECIs) is routinely used to measure neural activity in intact nervous systems. GECIs are frequently used in one of two different modes: to track activity in large populations of neuronal cell bodies, or to follow dynamics in subcellular compartments such as axons, dendrites and individual synaptic compartments. Despite major advances, calcium imaging is still limited by the biophysical properties of existing GECIs, including affinity, signal-to-noise ratio, rise and decay kinetics, and dynamic range. Using structure-guided mutagenesis and neuron-based screening, we optimized the green fluorescent protein-based GECI GCaMP6 for different modes of in vivo imaging. The jGCaMP7 sensors provide improved detection of individual spikes (jGCaMP7s,f), imaging in neurites and neuropil (jGCaMP7b), and tracking large populations of neurons using 2-photon (jGCaMP7s,f) or wide-field (jGCaMP7c) imaging.

neuroscience↗

bioRxiv2018

Adaptive Sampling for Spatial Capture-Recapture: An efficient sampling scheme for rare or patchily distributed species

Rare species present challenges to data collection, particularly when the species is spatially clustered over large areas, such that the encounter frequency of the organism is low. Sampling where the organism is absent consumes resources, and offers relatively low-quality information which are often difficult to model using standard statistical methods. In adaptive sampling, a probabilistic sampling method is employed first, and additional effort is allocated in the vicinity of sites where some measured index variable - assumed to be proportional to local population size - exceeds an a priori threshold. We applied this principle to the spatial capture-recapture (SCR) analytical framework in a Bayesian hierarchical model incorporating capture-recapture (CR) and index information from unsampled sites to estimate density. We assessed the adaptively sampled SCR model (AS-SCR) by simulating CR data and compared performance with a standard SCR baseline (F-SCR), adaptive SCR discarding index information (AS-SCR-), and standard SCR applied at a simple random sample of sites. Under AS-SCR, we observed minimal bias and comparable variance with respect to parameter estimates provided by the standard F-SCR model and sampling implementation, but with substantially reduced effort and significant cost saving potential. This represents the first application of adaptive sampling to SCR.

ecology↗

bioRxiv2017

Imaging-Genomics Study Of Head-Neck Squamous Cell Carcinoma: Associations Between Radiomic Phenotypes And Genomic Mechanisms Via Integration Of TCGA And TCIA

PurposeRecent data suggest that imaging radiomics features for a tumor could predict important genomic biomarkers. Understanding the relationship between radiomic and genomic features is important for basic cancer research and future patient care. For Head and Neck Squamous Cell Carcinoma (HNSCC), we perform a comprehensive study to discover the imaging-genomics associations and explore the potential of predicting tumor genomic alternations using radiomic features.\n\nMethodsOur retrospective study integrates whole-genome multi-omics data from The Cancer Genome Atlas (TCGA) with matched computed tomography imaging data from The Cancer Imaging Archive (TCIA) for the same set of 126 HNSCC patients. Linear regression analysis and gene set enrichment analysis are used to identify statistically significant associations between radiomic imaging features and genomic features. Random forest classifier is used to predict two key HNSCC molecular biomarkers, the status of human papilloma virus (HPV) and disruptive TP53 mutation, based on radiomic features.\n\nResultsWide-spread and statistically significant associations are discovered between genomic features (including miRNA expressions, protein expressions, somatic mutations, and transcriptional activities, copy number variations, and promoter region DNA methylation changes of pathways) and radiomic features characterizing the size, shape, and texture of tumor. Prediction of HPV and TP53 mutation status using radiomic features achieves an area under the receiver operating characteristics curve (AUC) of 0.71 and 0.641, respectively.\n\nConclusionOur analysis suggests that radiomic features are associated with genomic characteristics in HNSCC and provides justification for continued development of radiomics as biomarkers for relevant genomic alterations in HNSCC.

cancer biology↗

bioRxiv2017

Apolipoprotein-E (ApoE) ϵ4 and cognitive decline over the adult life course

We tested the association between APOE-{varepsilon}4 and processing speed and memory between ages 43 and 69 in a population-based birth cohort. Analyses of processing speed (using a timed letter search task) and episodic memory (a 15-item word learning test) were conducted at ages 43, 53, 60-64 and 69 years using linear and multivariable regression, adjusting for gender and childhood cognition. Linear mixed models, with random intercepts and slopes, were conducted to test the association between APOE and the rate of decline in these cognitive scores from age 43 to 69. Model fit was assessed with the Bayesian Information Criterion. A cross-sectional association between APOE-{varepsilon}4 and memory scores was detected at age 69 for both heterozygotes and homozygotes ({beta}=-0.68 & {beta}=-1.38 respectively, p=.03) with stronger associations in homozygotes; no associations were observed before this age. Homozygous carriers of APOE-{varepsilon}4 had a faster rate of decline in memory between ages 43 and 69, when compared to noncarriers, after adjusting for gender and childhood cognition ({beta}=-0.05, p=.04). There were no cross-sectional or longitudinal associations between APOE-{varepsilon}4 and processing speed. We conclude that APOE-{varepsilon}4 is associated with a subtly faster rate of memory decline from midlife to early old age; this may be due to effects of APOE-{varepsilon}4 becoming manifest around the latter stage of life. Continuing follow-up will determine what proportion of this increase will become clinically significant.

epidemiology↗

bioRxiv2017

Memory retrieval recruits both innate and learned olfactoryprocessing centres in Drosophila

Animals can show either learned or innate behavioral responses to a given stimulus. How these circuits interact to produce an appropriate behavioral response is unknown. In the Drosophila olfactory system, the lateral horn (LH) and the mushroom body (MB) are thought to mediate innate and learned olfactory behavior respectively, although the function of the LH has not been directly tested. Here we identify two LH cell-types (PD2a1/b1) that receive input from an MB output neuron required for recall of aversive olfactory memories. In contrast to the model above we find that PD2a1/b1 are required for aversive memory retrieval. PD2a1/b1 activity is modulated by training, indicating that memory information is passed to the innate olfactory processing centre. We map the connectivity of PD2a1/b1 to other olfactory neurons with connectomic data. This provides a circuit mechanism by which learned and unlearned olfactory information can interact to produce appropriate behavior.

neuroscience↗

bioRxiv2017

Designing Anti-Zika Virus Peptides Derived from Predicted Human-Zika Virus Protein-Protein Interactions

The production of anti-Zika virus (ZIKV) therapeutics has become increasingly important as the propagation of the devastating virus continues largely unchecked. Notably, a causal relationship between ZIKV infection and neurodevelopmental abnormalities has been widely reported, yet a specific mechanism underlying impaired neurological development has not been identified. Here, we report on the design of several synthetic competitive inhibitory peptides against key pathogenic ZIKV proteins through the prediction of protein-protein interactions (PPIs). Often, PPIs between host and viral proteins are crucial for infection and pathogenesis, making them attractive targets for therapeutics. Using two complementary sequence-based PPI prediction tools, we first produced a comprehensive map of predicted human-ZIKV PPIs (involving 209 human protein candidates). We then designed several peptides intended to disrupt the corresponding host-pathogen interactions thereby acting as anti-ZIKV therapeutics. The data generated in this study constitute a foundational resource to aid in the multi-disciplinary effort to combat ZIKV infection, including the design of additional synthetic proteins.

synthetic biology↗