Biology subjects

Zou, F.

Publications and source records attributed to Zou, F..

48 records · Page 3Linked to original sources

bioRxiv2020

Binding of guide piRNA triggers methylation of the unstructured N-terminal region of Aub leading to assembly of the piRNA amplification complex

Piwi proteins use guide piRNAs to repress selfish genomic elements, protecting the genomic integrity of gametes and ensuring the fertility of animal species. Efficient transposon repression depends on amplification of piRNA guides in the ping-pong cycle, which in Drosophila entails tight cooperation between two Piwi proteins, Aub and Ago3. Here we show that post-translational modification, symmetric dimethylarginine (sDMA), of Aub is essential for piRNA biogenesis, transposon silencing and fertility. Methylation is triggered by loading of a piRNA guide into Aub, which exposes its unstructured N-terminal region to the PRMT5 methylosome complex. Thus, sDMA modification is a signal that Aub is loaded with piRNA guide. Amplification of piRNA in the ping-pong cycle requires assembly of a tertiary complex scaffolded by Krimper, which simultaneously binds the N-terminal regions of Aub and Ago3. To promote generation of new piRNA, Krimp uses its two Tudor domains to bind Aub and Ago3 in opposite modification and piRNA-loading states. Our results reveal that post-translational modifications in unstructured regions of Piwi proteins and their binding by Tudor domains that are capable of discriminating between modification states is essential for piRNA biogenesis and silencing. HighlightsO_LIsDMA modification of Aub is essential for ping-pong cycle, transposon silencing and fertility. C_LIO_LIpiRNA loading triggers Aub sDMA modification by exposing its unstructured N terminal region to the methylosome complex. C_LIO_LIA single molecule of Krimp simultaneously binds piRNA-bound Aub and empty Ago3 to assemble ping-pong complex. C_LIO_LIThe distinct structure of two Tudor domains of Krimp ensures binding of Ago3 and Aub in opposite modification and piRNA-loading states. C_LI

biochemistry↗

bioRxiv2020

A Deep Learning Semiparametric Regression for Adjusting Complex Confounding Structures

Deep Treatment Learning (deepTL), a robust yet efficient deep learning-based semiparametric regression approach, is proposed to adjust the complex confounding structures in comparative effectiveness analysis of observational data, e.g. electronic health record (EHR) data, in which complex confounding structures are often embedded. Specifically, we develop a deep learning neural network with a score-based ensembling scheme for flexible function approximation. An improved semiparametric procedure is further developed to enhance the performance of the proposed method under finite sample settings. Comprehensive numerical studies have demonstrated the superior performance of the proposed methods as compared with existing methods, with a remarkably reduced bias and mean squared error in parameter estimates. The proposed research is motivated by a post-surgery pain study, which is also used to illustrate the practical application of deepTL. Finally, an R package, "deepTL", is developed to implement the proposed method.

neuroscience↗

bioRxiv2020

Permutation-based Identification of Important Biomarkers for Complex Diseases via Black-box Models

Study of human disease remains challenging due to convoluted disease etiologies and complex molecular mechanisms at genetic, genomic, and proteomic levels. Many machine learning-based methods, including deep learning and random forest, have been developed and widely used to alleviate some analytic challenges in complex human disease studies. While enjoying the modeling flexibility and robustness, these model frameworks suffer from non-transparency and difficulty in interpreting the role of each individual feature due to their intrinsic black-box natures. However, identifying important biomarkers associated with complex human diseases is a critical pursuit towards assisting researchers to establish novel hypotheses regarding prevention, diagnosis and treatment of complex human diseases. Herein, we propose a Permutation-based Feature Importance Test (PermFIT) for estimating and testing the feature importance, and for assisting interpretation of individual feature in various black-box frameworks, including deep neural networks, random forests, and support vector machines. PermFIT (available at https://github.com/SkadiEye/deepTL) is implemented in a computationally efficient manner, without model refitting for each permuted data. We conduct extensive numerical studies under various scenarios, and show that PermFIT not only yields valid statistical inference, but also helps to improve the prediction accuracy of black-box models with top selected features. With the application to the Cancer Genome Atlas (TCGA) kidney tumor data and the HITChip atlas BMI data, PermFIT clearly demonstrates its practical usage in identifying important biomarkers and boosting performance of black-box predictive models.

bioinformatics↗

bioRxiv2020

Diffusion property and functional connectivity of superior longitudinal fasciculus underpin human metacognition

Metacognition as the capacity of monitoring ones own cognition operates across domains. Here, we addressed whether metacognition in different cognitive domains rely on common or distinct neural substrates with combined diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) techniques. After acquiring DTI and resting-state fMRI data, we asked participants to perform a temporal-order memory task and a perceptual discrimination task, followed by trial-specific confidence judgments. DTI analysis revealed that the structural integrity (indexed by fractional anisotropy) in the anterior portion of right superior longitudinal fasciculus (SLF) was associated with both perceptual and mnemonic metacognitive abilities. Using perturbed mnemonic metacognitive scores produced by inhibiting the precuneus using TMS, the mnemonic metacognition scores did not correlate with individuals SLF structural integrity anymore, revealing the relevance of this tract in memory metacognition. In order to further verify the involvement of several cortical regions connected by SLF, we took the TMS-targeted precuneus region as a seed in a functional connectivity analysis and found the functional connectivity between precuneus and two SLF-connected regions (inferior parietal cortex and precentral gyrus) differentially mediated mnemonic but not perceptual metacognition performance. These results illustrate the importance of SLF and a putative white-matter grey-matter circuitry that supports human metacognition.

neuroscience↗

bioRxiv2020

Teicoplanin potently blocks the cell entry of 2019-nCoV

Since the outbreak of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the public health worldwide has been greatly threatened. The development of an effective treatment for this infection is crucial and urgent but is hampered by the incomplete understanding of the viral infection mechanism and the lack of specific antiviral agents. We previously reported that teicoplanin, a glycopeptide antibiotic that has been commonly used in the clinic to treat bacterial infection, significantly restrained the cell entry of Ebola virus, SARS-CoV and MERS-CoV by specifically inhibiting the activity of cathepsin L (CTSL). Here, we found that the cleavage sites of CTSL on the Spike of SARS-CoV-2 were highly conserved among all the variants. The treatment with teicoplanin suppressed the proteolytic activity of CTSL on Spike and prevented the cellular infection of different pseudotyped SARS-CoV-2 viruses. Teicoplanin potently prevented the entry of authentic SARS-CoV-2 into the cellular cytoplasm with an IC50 of 2.038 M for the Wuhan-Hu-1 reference strain and an IC50 of 2.116 M for the SARS-CoV-2 (D614G) variant. The pre-treatment of teicoplanin also prevented SARS-CoV-2 infection in hACE2 mice. In summary, our data reveal that CTSL is required for both SARS-CoV-2 and SARS-CoV infection and demonstrate the therapeutic potential of teicoplanin for universal anti-CoVs intervention. ImportanceDisease prevention and treatment are two important countermeasures to end the coronavirus disease 2019 (COVID-19). However, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, evolves all the time, resulting in the emerging of many epidemic SARS-CoV-2 mutants, which significantly impairs the effectiveness of early strain-based vaccines and antibodies. Developing universal vaccines and broad-spectrum antiviral drugs are essential to confront SARS-CoV-2 mutants including those may emerge in the future. Our study reported here showed that the cleavage sites of cellular cathepsin L (CTSL) are highly conserved among all the SARS-CoV-2 mutants and SARS-CoV. The CTSL inhibitor teicoplanin not only inhibited the cell entry of two live SARS-CoV-2 strains and various pseudotyped viruses but also prevented live virus infection in animal models. Based on our previous finding that teicoplanin also inhibited SARS-CoV and MERS-CoV infection, we believe that teicoplanin possesses the potential to become a universal anti-CoVs drug.

microbiology↗

bioRxiv2020

Chemically Induced Chromosomal Interaction (CICI): A New Tool to Study Chromosome Dynamics and Its Biological Roles

Numerous intra- and inter-chromosomal contacts have been mapped in eukaryotic genomes, but it remains challenging to link these 3D structures to their regulatory functions. To establish the causal relationships between chromosome conformation and genome functions, we need a method that allows us to selectively perturb the conformation at targeted loci. Here, we developed a method in budding yeast, Chemically Induced Chromosomal Interaction (CICI), to engineer long-distance chromosomal interactions selectively and dynamically. We implemented CICI at multiple intra- and inter-chromosomal loci pairs and showed that CICI can form in >50% of cells, even between loci with very low Hi-C contact frequencies. CICI formation is slower at these low Hi-C sites, revealing the dynamic nature of the Hi-C signals. As a functional test, we forced the interaction between mating-type locus (MAT) and HMR and observed significant change in donor preference during mating-type switching, showing that chromosome conformation plays an important role in homology-directed DNA repair. Overall, these results demonstrate that CICI is a powerful tool to study chromosome dynamics and the 3D genome function.

synthetic biology↗

bioRxiv2019

Infection risk and extensive parental care govern the molecular evolution of Toll-like receptors in birds.

The arms race between pathogens and the immune system of their hosts is a critical evolutionary force that affects the ecology and life history of organisms. An increased infection risk selects for adaptations in immune genes that encode receptors involved in pathogen recognition and the initiation of innate immune responses, including Toll-like receptor (TLR) genes. Although recent studies assessed the evolution of major histocompatibility complex (MHC) genes, the ecological and evolutionary processes that drive the evolution of immune genes across major phylogenetic lineages remain unstudied. Moreover, trade-offs between immune responses and other energy-demanding vital functions may limit the resource allocation into costly immune functions, and therefore affect the evolution of immune genes. Here we assess the evolutionary patterns of six TLR genes across 121 bird species, covering 95% of extant orders that represent diverse ecologies and life histories. Selection analyses revealed that all six TLR genes show strong signs of purifying selection, while few sites underwent episodic positive selection. Comparative phylogenetic analyses showed that the intensity of positive selection of TLR genes is associated with long-distance migration, extensive parental care (i.e., altricality and prolonged parent-offspring association), and a large body size (a proxy of increased longevity). Together, these results suggest that the evolution of immune genes is characterized by episodic positive selection, and is shaped by an increased inflection risk and extensive parental care that buffers the costs of immune functions.

evolutionary biology↗

bioRxiv2019

Antipsychotic behavioral phenotypes in the mouse Collaborative Cross recombinant inbred inter-crosses (RIX)

Schizophrenia is an idiopathic disorder that affects approximately 1% of the human population, and presents with persistent delusions, hallucinations, and disorganized behaviors. Antipsychotics are the standard pharmacological treatment for schizophrenia, but are frequently discontinued by patients due to inefficacy and/or side effects. Chronic treatment with the typical antipsychotic haloperidol causes tardive dyskinesia (TD), which manifests as involuntary and often irreversible orofacial movements in around 30% of patients. Mice treated with haloperidol develop many of the features of TD, including jaw tremors, tongue protrusions, and vacuous chewing movements (VCMs). In this study, we used genetically diverse Collaborative Cross (CC) recombinant inbred inter-cross (RIX) mice to elucidate the genetic basis of antipsychotic-induced adverse drug reactions (ADRs). We performed a battery of behavioral tests in 840 mice from 73 RIX lines (derived from 62 CC strains) treated with haloperidol or placebo in order to monitor the development of ADRs. We used linear mixed models to test for strain and treatment effects. We observed highly significant strain effects for almost all behavioral measurements investigated (p<0.001). Further, we observed strong strain-by-treatment interactions for most phenotypes, particularly for changes in distance traveled, vertical activity, and extrapyramidal symptoms (EPS). Estimates of overall heritability ranged from 0.21 (change in body weight) to 0.4 (VCMs and change in distance traveled) while the portion attributable to the interactions of treatment and strain ranged from 0.01 (for change in body weight) to 0.15 (for change in EPS). Interestingly, close to 30% of RIX mice exhibited VCMs, a sensitivity to haloperidol exposure, approximately similar to the rate of TD in humans chronically exposed to haloperidol. Understanding the genetic basis for the susceptibility to antipsychotic ADRs may be possible in mouse, and extrapolation to humans could lead to safer therapeutic approaches for schizophrenia.

systems biology↗

bioRxiv2019

SCDC: Bulk Gene Expression Deconvolution by Multiple Single-Cell RNA Sequencing References

Recent advances in single-cell RNA sequencing (scRNA-seq) enable characterization of transcriptomic profiles with single-cell resolution and circumvent averaging artifacts associated with traditional bulk RNA sequencing (RNA-seq) data. Here, we propose SCDC, a deconvolution method for bulk RNA-seq that leverages cell-type specific gene expression profiles from multiple scRNA-seq reference datasets. SCDC adopts an ENSEMBLE method to integrate deconvolution results from different scRNA-seq datasets that are produced in different laboratories and at different times, implicitly addressing the problem of batch-effect confounding. SCDC is benchmarked against existing methods using both in silico generated pseudo-bulk samples and experimentally mixed cell lines, whose known cell-type compositions serve as ground truths. We show that SCDC outperforms existing methods with improved accuracy of cell-type decomposition under both settings. To illustrate how the ENSEMBLE framework performs in complex tissues under different scenarios, we further apply our method to a human pancreatic islet dataset and a mouse mammary gland dataset. SCDC returns results that are more consistent with experimental designs and that reproduce more significant associations between cell-type proportions and measured phenotypes.

bioinformatics↗

bioRxiv2018

Is Polygenic Risk Scores Prediction Good?

Polygenic risk score (PRS) is the state-of-art prediction method for complex traits using summary level data from discovery genome-wide association studies (GWAS). The PRS, as its name suggests, is designed for polygenic traits by aggregating small genetic effects from a large number of causal SNPs and thus is viewed as a powerful method for predicting complex polygenic traits by the genetics community. However, one concern is that the prediction accuracy of PRS in practice remains low with little clinical utility, even for highly heritable traits. Another practical concern is whether genome-wide SNPs should be used in constructing PRS or not. To address the two concerns, we investigate PRS both empirically and theoretically. We show how the performance of PRS is influenced by the triplet (n, p, m), where n, p, m are the sample size, the number of SNPs studied, and the number of true causal SNPs, respectively. For a given heritability, we find that i) when PRS is constructed with all p SNPs (referred as GWAS-PRS), its prediction accuracy is controlled by the p/n ratio; while ii) when PRS is built with a set of top-ranked SNPs that pass a pre-specified threshold (referred as threshold-PRS), its accuracy varies depending on how sparse the true genetic signals are. Only when m is magnitude smaller than n, or genetic signals are sparse, can threshold-PRS perform well and outperform GWAS-PRS. Our results demystify the low performance of PRS in predicting highly polygenic traits, which will greatly increase researchers aware-ness of the power and limitations of PRS, and clear up some confusion on the clinical application of PRS.

genetics↗

bioRxiv2018

Individual susceptibility to TMS affirms the precuneual role in meta-memory upon recollection

BackgroundA recent virtual-lesion study using inhibitory repetitive transcranial magnetic stimulation (rTMS) confirmed the causal behavioral relevance of the precuneus in the evaluation of ones own memory performance (aka mnemonic metacognition).\n\nObjectiveThis studys goal is to elucidate how these TMS-induced neuromodulatory effects might relate to the neural correlates and be modulated by individual anatomical profiles in relation to meta-memory.\n\nMethodsIn a within-subjects design, we assessed the impact of 20-min rTMS over the precuneus, compared to the vertex, across three magnetic resonance imaging (MRI) neuro-profiles on 18 healthy subjects during a memory versus a perceptual task.\n\nResultsTask-based functional MRI revealed that BOLD signal magnitude in the precuneus is associated with variation in individual meta-memory efficiency, and such correlation diminished significantly following TMS targeted at the precuneus. Moreover, individuals with higher resting-state functional connectivity (rs-fcMRI) between the precuneus and the hippocampus, or smaller grey matter volume in the stimulated precuneal region exhibit considerably higher vulnerability to the TMS effect. These effects were not observed in the perceptual domain.\n\nConclusionWe provide compelling evidence in outlining a possible circuit encompassing the precuneus and its mnemonic midbrain neighbor the hippocampus at the service of realizing our meta-awareness during memory recollection of episodic details.\n\nHighlightsO_LITMS on precuneus reduces meta-memory ability during memory retrieval.\nC_LIO_LITMS disrupts the correlation between BOLD activity and meta-memory ability.\nC_LIO_LITMS effect is modulated by rs-fcMRI between precuneus and hippocampus.\nC_LIO_LIIndividuals with greater precuneal grey matter volume more immune to TMS effect.\nC_LI

neuroscience↗

bioRxiv2018

Causal evidence for mnemonic metacognition in human precuneus

Metacognition is the capacity to introspectively monitor and control ones own cognitive processes. Previous anatomical and functional neuroimaging findings implicated the important role of precuneus in metacognition processing, especially during mnemonic tasks. However, the issue of whether this medial parietal cortex is a domain-specific region that supports mnemonic metacognition remains controversial. Here, we focally disrupted this parietal area with repetitive transcranial magnetic stimulation in healthy participants of both sexes, seeking to ascertain its functional necessity for metacognition for memory versus perceptual decisions. Perturbing the precuneal activity impaired the metacognitive efficiency selectively in the memory judgment of temporal-order, but not in perceptual discrimination. Moreover, the correlation in individuals metacognitive efficiency between the domains disappeared when the precuneus was perturbed. Together with the previous finding that lesion to the anterior prefrontal cortex impairs perceptual but not mnemonic metacognition, we double dissociated the macro-anatomical underpinnings for the two kinds of metacognitive capacity in an interconnected network of brain regions.\n\nSIGNIFICANCE STATEMENTTheories on the neural basis of metacognition have thus far largely centered on the role of prefrontal cortex. Here we refined the theoretical framework through characterizing a unique precuneal involvement in mnemonic metacognition with a noninvasive but inferentially powerful method: transcranial magnetic stimulation. By quantifying meta-cognitive efficiency across two distinct domains (memory vs. perception) that are matched for stimulus characteristics, we reveal an instrumental - and highly selective - role of the precuneus in mnemonic metacognition. These causal evidence corroborate ample clinical reports that parietal lobe lesions often produce inaccurate self-reports of confidence in memory recollection and establish that the precuneus as a nexus for the introspective ability to evaluate the success of memory judgment in humans.

neuroscience↗