Biology subjects

Chang, C.

Publications and source records attributed to Chang, C..

16 recordsLinked to original sources

bioRxiv2018

Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight novel adipocyte biology

To characterize latent components of genetic associations, we applied truncated singular value decomposition (DeGAs) to matrices of summary statistics derived from genome-wide association analyses across 2,138 phenotypes measured in 337,199 White British individuals in the UK Biobank study. We systematically identified key components of genetic associations and the contributions of variants, genes, and phenotypes to each component. As an illustration of the utility of the approach to inform downstream experiments, we report putative loss of function variants, rs114285050 (GPR151) and rs150090666 (PDE3B), that substantially contribute to obesity-related traits, and experimentally demonstrate the role of these genes in adipocyte biology. Our approach to dissect components of genetic associations across human phenotypes will accelerate biomedical hypothesis generation by providing insights on previously unexplored latent structures.

genetics↗

bioRxiv2018

Molecular Screening of Familial Hypercholesterolemia in the Icelandic Population

Familial hypercholesterolemia (FH) is a monogenic disease characterized by a lifelong exposure to high LDL-C levels that can lead to early onset coronary heart disease (CHD). The main causes of FH identified to date include loss-of-function mutations in LDLR or APOB, or gain-of-function mutations in PCSK9. Early diagnosis and genetic testing of FH suspects is critical for improved prognosis of affected individuals as lipid lowering treatments are effective in preventing CHD related morbidity and mortality. In the present manuscript, we developed a comprehensive next generation sequencing (NGS) panel which we applied on two different resources of FH in the Icelandic population: 62 subjects from 23 FH families with known or unknown culprit mutations, and a population-based sampling of 315 subjects selected for total cholesterol levels above the 95th percentile cut-point. The application of the NGS panel revealed significant diagnostic yields in identifying pathogenic LDLR mutations in both family and population-based genetic testing.

genetics↗

bioRxiv2018

Integrated modeling of peptide digestion and detection for the prediction of proteotypic peptides in targeted proteomics

MotivationThe selection of proteotypic peptides, i.e., detectable unique representatives of proteins of interest, is a key step in targeted shotgun proteomics. To date, much effort has been made to predict proteotypic peptides in the absence of mass spectrometry data. However, the performance of existing tools is still unsatisfactory. One crucial reason is their neglect of the close relationship between protein proteolytic digestion and peptide detection.\n\nResultsWe present an algorithm (named AP3) that firstly considers peptide digestion probability as a feature for proteotypic peptide prediction and demonstrated peptide digestion probability is the most important feature for accurate prediction of proteotypic peptides. AP3 showed higher accuracy than existing tools and accurately predicted the proteotypic peptides for a targeted proteomics assay, showing its great potential for assisting the design of targeted proteomics experiments.\n\nAvailability and ImplementationFreely available at http://fugroup.amss.ac.cn/software/AP3/AP3.html.\n\nContactyfu@amss.ac.cn or zhuyunping@gmail.com\n\nSupplementary InformationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2018

Carbon monoxide, a retrograde messenger generated in post-synaptic mushroom body neurons evokes local dopamine release

Dopaminergic neurons innervate extensive areas of the brain and release dopamine (DA) onto a wide range of target neurons. However, DA release is also precisely regulated, and in Drosophila, DA is released specifically onto mushroom body (MB) neurons, which have been coincidentally activated by cholinergic and glutamatergic inputs. The mechanism for this precise release has been unclear. Here we found that coincidentally activated MB neurons generate carbon monoxide (CO) which functions as a retrograde signal evoking local DA release from presynaptic terminals. CO production depends on activity of heme oxygenase in post-synaptic MB neurons, and CO-evoked DA release requires Ca2+ efflux through ryanodine receptors in DA terminals. CO is only produced in MB areas receiving coincident activation, and removal of CO using scavengers blocks DA release. We propose that DA neurons utilize two distinct modes of transmission to produce global and local DA signaling.\n\nSIGNIFICANCE STATEMENTDopamine (DA) is needed for various higher brain functions including memory formation. However, DA neurons form extensive synaptic connections, while memory formation requires highly specific and localized DA release. Here we identify a mechanism through which DA release from presynaptic terminals is controlled by postsynaptic activity. Postsynaptic neurons activated by cholinergic and glutamatergic inputs generate carbon monoxide, which acts as a retrograde messenger inducing presynaptic DA release. Released DA is required for memory-associated plasticity. Our work identifies a novel mechanism that restricts DA release to the specific postsynaptic sites that require DA during memory formation.

neuroscience↗

bioRxiv2018

Different Effects of Three Types of Water on Developmental Behaviors, Lipid Metabolism and Antioxidant Capacity of Juvenile Zebrafish

Adolescence is an important period when people need adequate nutrition for healthy growth and development, whether from food or water. Tap water, bottled water (bottled purified water, and bottled natural water) are now the three most popular drinking waters consumed by adolescents in China. However, the constituents of them differ, which may cause different long-term health effects. In order to determine which type of water is the most beneficial regarding developmental behaviors, lipid metabolism and antioxidant capacity of juvenile zebrafish, 21 dpf (days post-fertilization) zebrafish were given these three waters separately with the same feed until 90 dpf. Results showed that zebrafish in purified water had the lowest survival rate, body weight and body length, while zebrafish in natural water and tap water had similar developmental behaviors; the highest HDL-C level and the lowest TG level were found in natural water, tap water second; and zebrafish in natural water showed the best antioxidant capacity. Thus, the best outcomes were found in natural water, which had suitable pH and proper amount of minerals, tap water also showed good performance, while purified water seemed not suitable for juvenile zebrafish.

developmental biology↗

bioRxiv2018

Humanized Mcl-1 mice enable accurate pre-clinical evaluation of MCL-1 inhibitors destined for clinical use

MCL-1 is a pro-survival BCL-2 protein required for the sustained growth of many cancers. Recently a highly specific MCL-1-inhibitor, S63845, showing 6-fold higher affinity to human compared to mouse MCL-1 has been described. To accurately test efficacy and tolerability of this BH3 mimetic drug in pre-clinical cancer models, we developed a humanized Mcl-1 (huMcl-1) mouse in which MCL-1 was replaced with its human homologue. HuMcl-1 mice are phenotypically indistinguishable from wild-type mice but are more sensitive to MCL-1 inhibition. Importantly, non-transformed cells and lymphomas from huMcl-1;E-Myc mice are more sensitive to S63845 in vitro than their control counterparts. When huMcl-1;E-Myc lymphoma cells are transplanted into huMcl-1 mice, treatment with S63845 alone or alongside cyclophosphamide leads to long-term remission in ~60% or almost 100% of mice, respectively. These results demonstrate the potential of our huMCL-1 mouse model to test MCL-1 inhibitors, allowing precise predictions of efficacy and tolerability for clinical translation.

cancer biology↗

bioRxiv2018

PANDA: A comprehensive and flexible tool for proteomics data quantitative analysis

SummaryAs the experiment techniques and strategies in quantitative proteomics are improving rapidly, the corresponding algorithms and tools for protein quantification with high accuracy and precision are continuously required to be proposed. Here, we present a comprehensive and flexible tool named PANDA for proteomics data quantification. PANDA, which supports both label-free and labeled quantifications, is compatible with existing peptide identification tools and pipelines with considerable flexibility. Compared with MaxQuant on two complex da-tasets, PANDA was proved to be more accurate and precise with less computation time. Additionally, PANDA is an easy-to-use desktop ap-plication tool with user-friendly interfaces.\n\nAvailabilityPANDA is freely available for download at https://sourceforge.net/projects/panda-tools/.\n\nContact1987ccpacer@163.com and zhuyunping@gmail.com

bioinformatics↗

bioRxiv2018

LFAQ: towards unbiased label-free absolute protein quantification by predicting peptide quantitative factors

Mass spectrometry (MS) has become a prominent choice for large-scale absolute protein quantification, but its quantification accuracy still has substantial room for improvement. A crucial issue is the bias between the peptide MS intensity and the actual peptide abundance, i.e., the fact that peptides with equal abundance may have different MS intensities. This bias is mainly caused by the diverse physicochemical properties of peptides. Here, we propose a novel algorithm for label-free absolute protein quantification, LFAQ, which can correct the biased MS intensities by using the predicted peptide quantitative factors for all identified peptides. When validated on datasets produced by different MS instruments and data acquisition modes, LFAQ presented accuracy and precision superior to those of existing methods. In particular, it reduced the quantification error by an average of 46% for low-abundance proteins.

bioinformatics↗

bioRxiv2018

Recombinant expression of Proteorhodopsin and biofilm regulators in Escherichia coli for nanoparticle binding and removal in a wastewater treatment model

The small size of nanoparticles is both an advantage and a problem. Their high surface-area-to-volume ratio enables novel medical, industrial, and commercial applications. However, their small size also allows them to evade conventional filtration during water treatment, posing health risks to humans, plants, and aquatic life. This project aims to remove nanoparticles during wastewater treatment using genetically modified Escherichia coli in two ways: 1) binding citrate-capped nanoparticles with the membrane protein Proteorhodopsin, and 2) trapping nanoparticles using Escherichia coli biofilm produced by overexpressing two regulators: OmpR234 and CsgD. We demonstrate experimentally that Escherichia coli expressing Proteorhodopsin binds to 60 nm citrate-capped silver nanoparticles. We also successfully upregulate biofilm production and show that Escherichia coli biofilms are able to trap 30 nm gold particles. Finally, both Proteorhodopsin and biofilm approaches are able to bind and remove nanoparticles in simulated wastewater treatment tanks. We envision integrating our trapping system in both rural and urban wastewater treatment plants to efficiently capture all nanoparticles before treated water is released into the environment.\n\nFinancial DisclosureThis work was funded by the Taipei American School. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\nCompeting InterestsThe authors have declared that no competing interests exist.\n\nEthics StatementN/A\n\nData AvailabilityYes - all data are fully available without restriction. Sequences for the plasmids used in this study are available through the Registry of Standard Biological Parts. Links to raw data are included in Supplementary Information.

synthetic biology↗

bioRxiv2018

Comprehensive Genetic Testing for Female and Male Infertility Using Next Generation Sequencing

ObjectiveTo develop a comprehensive genetic test for female and male infertility in support of medical decisions during assisted reproductive technology (ART) protocols.\n\nDesignRetrospective analysis of results from 118 DNA samples with known variants in loci representative of female and male infertility.\n\nInterventions(s)None\n\nMain Outcome Measure(s)Next-Generation Sequencing (NGS) of 87 genes including promoters, 5 and 3 untranslated regions, exons and selected introns. In addition, sex chromosome aneuploidies and Y chromosome microdeletions are analyzed concomitantly using the same panel.\n\nResultsAnalytical accuracy was >99%, with >98% sensitivity for Single Nucleotide Variants (SNVs) and >91% sensitivity for insertions/deletions (indels). Clinical sensitivity was assessed with samples containing variants representative of male and female infertility, and it was 100% for SNVs/indels, CFTR IVS8-5T variants, sex chromosome aneuploidies and Copy Number Variants (CNVs), and >93% for Y chromosome microdeletions. Cost analysis comparing the NGS assay with standard, multiple analysis approach, shows potential savings of $2723 per case. Conclusion: A single, comprehensive, NGS panel can simplify the ordering process for healthcare providers, reduce turnaround time, and lower the overall cost of testing for genetic assessment of infertility in females and males, while maintaining accuracy.

genomics↗

bioRxiv2018

BAX requires VDAC2 to mediate apoptosis and to limit tumor development

Intrinsic apoptosis is critical for normal physiology including the prevention of tumor formation. BAX and BAK are essential for mediating this process and for the cytotoxic action of many anticancer drugs. BAX and BAK are thought to act in a functionally redundant manner and are considered to be regulated similarly. From an unbiased genome-wide CRISPR/Cas9 screen, we identified VDAC2 (voltage-dependent anion channel 2) as essential for BAX, but not BAK, to function. The genetic deletion of VDAC2 abrogated the association of BAX and BAK with mitochondrial complexes that contain VDAC1, VDAC2 and VDAC3. By disrupting its localization to mitochondria, BAX is rendered completely ineffective. Moreover, we defined an interface unique to VDAC2 that is required to drive BAX activity. Consequently, interfering with this interaction or deleting VDAC2 phenocopied the loss of BAX, including impairing the killing of tumor cells by anti-cancer agents such as the BCL-2 inhibitor venetoclax. Furthermore, the ability of BAX to prevent tumor formation was attenuated in the absence of VDAC2. Taken together, our studies show for the first time that BAX-mediated apoptosis, but not BAK-mediated apoptosis, is critically dependent on VDAC2, hence revealing the differential regulation of BAX and BAK.

cell biology↗

bioRxiv2017

Template-based prediction of vigilance fluctuations in resting-state fMRI

Changes in vigilance or alertness during a typical resting state fMRI scan are inevitable and have been found to affect measures of functional brain connectivity. Since it is not often feasible to monitor vigilance with EEG during fMRI scans, it would be of great value to have methods for estimating vigilance levels from fMRI data alone. A recent study, conducted in macaque monkeys, proposed a template-based approach for fMRI-based estimation of vigilance fluctuations. Here, we use simultaneously acquired EEG/fMRI data to investigate whether the same template-based approach can be employed to estimate vigilance fluctuations of awake humans across different resting-state conditions. We first demonstrate that the spatial pattern of correlations between EEG-defined vigilance and fMRI in our data is consistent with the previous literature. Notably, however, we observed a significant difference between the eyes-closed (EC) and eyes-open (EO) conditions finding stronger negative correlations with vigilance in regions forming the default mode network and higher positive correlations in thalamus and insula in the EC condition when compared to the EO condition. Taking these correlation maps as \"templates\" for vigilance estimation, we found that the template-based approach produced fMRI-based vigilance estimates that were significantly correlated with EEG-based vigilance measures, indicating its generalizability from macaques to humans. We also demonstrate that the performance of this method was related to the overall amount of variability in a subjects vigilance state, and that the template-based approach outperformed the use of the global signal as a vigilance estimator. In addition, we show that the template-based approach can be used to estimate the variability across scans in the amplitude of the vigilance fluctuations. We discuss the benefits and tradeoffs of using the template-based approach in future fMRI studies.

neuroscience↗

bioRxiv2017

No major flaws in "Identification of individuals by trait prediction using whole-genome sequencing data"

In a recently published PNAS article, we studied the identifiability of genomic samples using machine learning methods [Lippert et al., 2017]. In a response, Erlich [2017] argued that our work contained major flaws. The main technical critique of Erlich [2017] builds on a simulation experiment that shows that our proposed algorithm, which uses only a genomic sample for identification, performed no better than a strategy that uses demographic variables. Below, we show why this comparison is misleading and provide a detailed discussion of the key critical points in our analyses that have been brought up in Erlich [2017] and in the media. Further, not only faces may be derived from DNA, but a wide range of phenotypes and demographic variables. In this light, the main contribution of Lippert et al. [2017] is an algorithm that identifies genomes of individuals by combining multiple DNA-based predictive models for a myriad of traits.

genomics↗

bioRxiv2017

Medical relevance of protein-truncating variants across 337,208 individuals in the UK Biobank study

Protein-truncating variants can have profound effects on gene function and are critical for clinical genome interpretation and generating therapeutic hypotheses, but their relevance to medical phenotypes has not been systematically assessed. We characterized the effect of 18,228 protein-truncating variants across 135 phenotypes from the UK Biobank and found 27 associations between medical phenotypes and protein-truncating variants in genes outside the major histocompatibility complex. We performed phenome-wide analyses and directly measured the effect of homozygous carriers, commonly referred to as \"human knockouts,\" across medical phenotypes for genes implicated to be protective against disease or associated with at least one phenotype in our study and found several genes with strong pleiotropic or non-additive effects. Our results illustrate the importance of protein-truncating variants in a variety of diseases.

genetics↗

bioRxiv2017

Inter-subject phase synchronization and the dynamics of human cognition

Massive whole-brain blood-oxygen-level dependent (BOLD) signal modulation (up to 95% of brain voxels) in response to task stimuli has recently been reported in functional MRI investigations. These findings have two implications. First, they highlight inability of a conventional 'top-down' general linear model approach to capture all forms of task-driven brain activity. Second, as opposed to a static 'active' or 'non-active' localization theory of the neural implementation of cognitive processes, functional neuroimaging should develop and pursue dynamical theories of cognition involving the dynamic interactions of all brain networks, in line with psychological constructionist theories of cognition. In this study, we describe a novel exploratory, bottom-up approach that directly estimates task-driven brain activity regardless of whether it follows an a priori reference function. Leveraging the property that task-driven brain activity is associated with reductions in BOLD signal variability, we combine the tools of instantaneous phase synchronization and independent component analysis to characterize whole-brain task-driven activity in terms of group-wise similarity in temporal signal dynamics of brain networks. We applied this novel framework to task fMRI data from a motor, theory of mind and working memory task provided through the Human Connectome Project. We discovered a large number of brain networks that dynamically synchronized to various features of the task scan, some overlapping with areas identified as 'active' in the top-down GLM approach. Using the results provided through this novel approach, we provide a more comprehensive description of cognitive processes whereby task-related brain activity is not restricted to dichotomous 'active' or 'non-active' inferences, but is characterized by the temporal dynamics of brain networks across time.

neuroscience↗

bioRxiv2016

Tuning the course of evolution on the biophysical fitness landscape of an RNA virus

Predicting viral evolution remains a major challenge with profound implications for public health. Viral evolutionary pathways are determined by the fitness landscape, which maps viral genotype to fitness. However, a quantitative description of the landscape and the evolutionary forces on it remain elusive. Here, we apply a biophysical fitness model based on capsid folding stability and antibody binding affinity to predict the evolutionary pathway of norovirus escaping a neutralizing antibody. The model is validated by experimental evolution in bulk culture and in a drop-based microfluidics device, the \"Evolution Chip\", which propagates millions of independent viral sub-populations. We demonstrate that along the axis of binding affinity, selection for escape variants and drift due to random mutations have the same direction. However, along folding stability, selection and drift are opposing forces whose balance is tuned by viral population size. Our results demonstrate that predictable epistatic tradeoffs shape viral evolution.

evolutionary biology↗