Biology subjects

Lyu, Y.

Publications and source records attributed to Lyu, Y..

50 records · Page 3Linked to original sources

bioRxiv2021

Interaction between spike protein of SARS-CoV-2 and human virus receptor ACE2 using two-color fluorescence cross-correlation spectroscopy

Infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), is initiated by the interaction between a receptor protein, angiotensin-converting enzyme type 2 (ACE2) on the cell surface, and the viral spike (S) protein. This interaction is similar to the mechanism in SARS-CoV, a close relative of SARS-CoV-2, which was identified in 2003. Drugs and antibodies that inhibit the interaction between ACE2 and S proteins could be key therapeutic methods for preventing viral infection and replication in COVID-19. Here, we demonstrate the interaction between human ACE2 and a fragment of the S protein (S1 subunit) derived from SARS-CoV-2 and SARS-CoV using two-color fluorescence cross-correlation spectroscopy (FCCS), which can detect the interaction of fluorescently labeled proteins. The S1 subunit of SARS-CoV-2 interacted in solution with soluble ACE2, which lacks a transmembrane region, more strongly than that of SARS-CoV. Furthermore, one-to-one stoichiometry of the two proteins during the interaction was indicated. Thus, we propose that this FCCS-based interaction detection system can be used to analyze the interaction strengths of various mutants of the S1 subunit that have evolved during the worldwide pandemic, and also offers the opportunity to screen and evaluate the performance of drugs and antibodies that inhibit the interaction.

biophysics↗

bioRxiv2021

Serotonin signaling modulates aging-associated metabolic network integrity in response to nutrient choice

Aging arises from complex interactions among multiple biochemical and metabolic products. Systems-level analyses of biological networks may provide insights into the causes and consequences of aging that evade single-gene or single-pathway studies. We have shown that dietary choice per se is sufficient to modulate aging and metabolic health in the vinegar fly, Drosophila melanogaster. In other words, how each meal is presented, or the way in which it is eaten, is influential, independent of the amount or type of nutrients that are consumed. For example, when major macronutrients were presented separately, male flies exhibited a rapid and significant increase in mortality rate and a reduced overall lifespan relative to those fed a single medium containing both sugar and yeast. These effects are mediated by specific components of serotonin signaling, as a mutation in serotonin receptor 2A (5-HT2A) eliminated the effects of dietary choice. Here we show that dietary choice influenced several measures of metabolic network integrity, including connectivity, average shortest distance, community structure, and robustness, with the effects of the latter two restricted to tissues in the head. These changes in network structure were associated with organism resilience and increased susceptibility to genetic perturbation, as measured by starvation survival. Our data suggest that the behavioral or perceptual consequences of exposure to individual macronutrients, involving serotonin signaling through 5-HT2A, qualitatively change the state of metabolic networks throughout the organism from one that is highly connected and robust to one that is fragmented, fragile, and vulnerable to perturbations.

genetics↗

bioRxiv2020

Serotonin 2A receptor signaling coordinates central metabolic processes to modulate aging in response to nutrient choice

It has been recognized for nearly a century that diet modulates aging. Despite early experiments suggesting that reduced caloric intake augmented lifespan, accumulating evidence indicates that other characteristics of the diet may be equally or more influential in modulating aging. We demonstrate that behavior, metabolism, and lifespan in Drosophila are affected by whether flies are provided a choice of different nutrients or a single, complete medium, largely independent of the amount of nutrients that are consumed. Meal choice elicits a rapid metabolic reprogramming that indicates a potentiation of TCA cycle and amino acid metabolism, which requires serotonin 2A receptor. Knockdown of glutamate dehydrogenase, a key TCA pathway component, abrogates the effect of dietary choice on lifespan. Our results reveal a mechanism of aging that applies in natural conditions, including our own, in which organisms continuously perceive and evaluate nutrient availability to promote fitness and well-being.

genetics↗

bioRxiv2020

Proximity Biotin Labeling Reveals KSHV Interferon Regulatory Factor Networks

Studies on "HIT&RUN" effects by viral protein are difficult when using traditional affinity precipitation-based techniques under dynamic conditions, because only proteins interacting at a specific instance in time can be precipitated by affinity purification. Recent advances in proximity labeling (PL) have enabled study of both static and dynamic protein-protein interactions. Here we applied PL method with recombinant Kaposis sarcoma-associated herpesvirus (KSHV). KSHV, a gamma-herpesvirus, uniquely encodes four interferon regulatory factors (IRFs 1-4) in the genome, and we identified KSHV vIRF-1 and vIRF-4 interacting proteins during reactivation. Fusion of mini-TurboID with vIRF-1 or vIRF-4 did not interfere with KSHV gene expression, DNA replication, or de novo infections. PL identified 213 and 70 proteins for vIRF-1 and vIRF-4 respectively, which possibly interact during KSHV reactivation, and 47 of those were shared between the two vIRFs; the list also includes three viral proteins, ORF17, thymidine kinase, and vIRF-4. Functional annotation of respective interacting proteins showed highly overlapping biological functions such as mRNA processing and transcriptional regulation by TP53. Involvement of commonly interacting 44 cellular proteins in innate immune regulation were examined by siRNAs, and we identified that splicing factor 3B (SF3B) family proteins were clearly involved in interferons transcription and suppressed KSHV reactivation. We propose that recombinant TurboID-KSHV is a powerful tool to probe key cellular proteins that play a role in KSHV replication, and selective splicing factors may have a function beyond connecting two exon sequences to regulate innate immune responses. ImportanceViral protein interaction with a host protein shows at least two sides: (i) taking host protein functions for its own benefit and (ii) disruption of existing host protein complex formation to inhibit undesirable host responses. Due to use of affinity-precipitation approaches, the majority of our studies focused on how the virus takes advantage of the newly-formed protein interactions for its own replication. Proximity labeling (PL) however, can also highlight the transient and negative effects - those interactions which lead to dissociation from the existing protein complex. Here we highlight the power of PL in combination with recombinant KSHV to study viral host interactions.

microbiology↗

bioRxiv2020

Iterative transfer learning with neural network for clustering and cell type classification in single-cell RNA-seq analysis

An important step in single-cell RNA-seq (scRNA-seq) analysis is to cluster cells into different populations or types. Here we describe ItClust, an Iterative Transfer learning algorithm with neural network for scRNA-seq Clustering. ItClust learns cell type knowledge from well-annotated source data, but also leverages information in the target data to make it less dependent on the source data quality. Through extensive evaluations using datasets from different species and tissues generated with diverse scRNA-seq protocols, we show that ItClust significantly improves clustering and cell type classification accuracy compared to popular unsupervised clustering and supervised cell type classification algorithms.

genomics↗

bioRxiv2019

A statistical framework for measuring reproducibility and replicability of high-throughput experiments from multiple sources

SO_SCPLOWUMMARYC_SCPLOWReplication is essential to reliable and consistent scientific discovery in high-throughput experiments. Quantifying the replicability of scientific discoveries and identifying sources of irreproducibility have become important tasks for quality control and data integration. In this work we introduce a novel statistical model to measure the reproducibility and replicability of findings from replicate experiments in multi-source studies. Using a nested copula mixture model that characterizes the interdependence between replication experiments both across and within sources, our method quantifies reproducibility and replicability of each candidate simultaneously in a coherent framework. Through simulation studies, an ENCODE ChIP-seq dataset and a SEQC RNA-seq dataset, we demonstrate the effectiveness of our method in diagnosing the source of discordance and improving the reliability of scientific discoveries.

bioinformatics↗

bioRxiv2019

RNAseq studies reveal distinct transcriptional response to vitamin A deficiency in small intestine versus colon, discovering novel VA-regulated genes

Vitamin A (VA) deficiency remains prevalent in resource limited countries, affecting over 250 million preschool aged children. Vitamin A deficiency is associated with reduced intestinal barrier function and increased risk of mortality due to mucosal infection. Using Citrobacter rodentium (C. rodentium) infection in mice as a model for diarrheal diseases in humans, previous reports showed reduced pathogen clearance and survival in vitamin A deficient (VAD) mice compared to their vitamin A sufficient (VAS) counterparts. ObjectivesTo characterize and compare the impact of preexisting VA deficiency on gene expression patterns in the small intestine (SI) and the colon, and to discover novel target genes in VA-related biological pathways. MethodsVAD mice were generated by feeding VAD diet to pregnant C57/BL6 dams and their post-weaning offspring. RNAseq were performed using the total mRNAs extracted from SI and colon. Differentially Expressed Gene (DEG), Gene Ontology (GO) enrichment, and Weighted Gene Co-expression Network Analysis (WGCNA) were performed to characterize expression and co-expression patterns. ResultsDEGs compared between VAS and VAD groups detected 49 SI and 94 colon genes. By GO information, SI DEGs were significantly enriched in categories relevant to retinoid metabolic process, molecule binding, and immune function. Immunity related pathways, including "humoral immune response" and "complement activation" were positively associated with VA in SI. Three co-expression modules showed significant correlation with VA status in SI; these modules contained four known retinoic acid targets. In addition, other SI genes of interest (e.g. Mbl2, Cxcl14, and Nr0b2) in these modules were suggested as new candidate genes regulated by VA. Furthermore, our analysis showed that markers of two cell types in SI, mast cells and Tuft cells, were significantly altered by VA status. In colon, "cell division" was the only enriched category and was negatively associated with VA. Thus, comparison of co-expression modules between SI and colon indicated distinct networks under the regulation of dietary VA and suggest that preexisting VAD could have a significant impact on the host response to a variety of disease conditions.

physiology↗

bioRxiv2019

High throughput small molecule screening reveals NRF2-dependent and -independent pathways of cellular stress resistance

Biological aging is the dominant risk factor for most chronic diseases. Development of anti-aging interventions offers the promise of preventing many such illnesses simultaneously. Cellular stress resistance is an evolutionarily conserved feature of longevity. Here, we identify compounds that induced resistance to the superoxide generator paraquat (PQ), the heavy metal cadmium (Cd), and the DNA alkylator methyl methanesulfonate (MMS). Some rescue compounds conferred resistance to a single stressor, while others provoked multiplex resistance. Induction of stress resistance in fibroblasts was predictive of longevity extension in a published large-scale longevity screen in C. elegans. Transcriptomic analysis implicated Nrf2 signaling in stress resistance provided by two protective compounds, cardamonin and AEG 3482. Molecules that conferred stress resistance also induced cellular inflammatory pathways, and other core pathways such as AMPK signaling. Small molecules identified in this work may represent attractive candidates to evaluate for their potential pro-health and pro-longevity effects in mammals.

cell biology↗

bioRxiv2019

Integrative single-cell and bulk RNA-seq analysis in human retina identified cell type-specific composition and gene expression changes for age-related macular degeneration

Age-related macular degeneration (AMD) preferentially affects distinct cell types and topographic regions in retina. To characterize the impact of AMD on gene expression changes across retinal cell types and regions, we generated both single-cell RNA-seq (scRNA-seq) and bulk RNA-seq data from macular and peripheral retina in postmortem human donors with and without AMD. The scRNA-seq data revealed 11 major cell types with many previously reported AMD risk genes showing substantial cell type and region specificity. Cell type proportional changes with advancing AMD stage were significant for Muller glia, rods, astrocytes, microglia and endothelium.

genomics↗

bioRxiv2019

Deep learning enables accurate clustering and batch effect removal in single-cell RNA-seq analysis

Single-cell RNA sequencing (scRNA-seq) can characterize cell types and states through unsupervised clustering, but the ever increasing number of cells imposes computational challenges. We present an unsupervised deep embedding algorithm for single-cell clustering (DESC) that iteratively learns cluster-specific gene expression signatures and cluster assignment. DESC significantly improves clustering accuracy across various datasets and is capable of removing complex batch effects while maintaining true biological variations.

genomics↗

bioRxiv2019

Perception of naturally dead conspecifics impairs health and longevity through serotonin signaling in Drosophila

Sensory perception modulates health and aging across taxa. Understanding the nature of relevant cues and the mechanisms underlying their action may lead to novel interventions that improve the length and quality of life. In humans, psychological trauma is often associated with the recognition of dead individuals, with chronic exposure leading to persistent mental health issues including depression and post-traumatic stress disorder. The mechanisms that link mental and physical health, and the degree to which these are shared across species, remain largely unknown. Here we show that the vinegar fly, Drosophila melanogaster, has the capability to perceive dead conspecifics in its environment and that this perceptive experience induces both short- and long-term effects on health and longevity. Death perception is mediated by visual and olfactory cues, and remarkably, its effects on aging are eliminated by targeted attenuation of serotonin signaling. Our results suggest a complex perceptive ability in Drosophila that reveals deeply conserved mechanistic links between psychological state and aging, the roots of which might be unearthed using invertebrate model systems.

animal behavior and cognition↗

bioRxiv2018

Structural variants, clonal propagation, and genome evolution in grapevine (Vitis vinifera)

Little is known about the type and numbers of structural variants (SVs) in plant genomes, the evolutionary processes that shape SV variation, or their effects on phenotypes. Here we assembled the 605Mb genome of the Chardonnay grape (Vitis vinifera ssp. sativa), which we use to catalog SVs within and between genomes and also across 69 cultivars and wild accessions. SVs underlie widespread hemizygosity of protein coding genes within Chardonnay and genic presence-absence variation between cultivars. Negative selection acts against all SV types, but they also accrue as heterozygous, recessive mutations in clonally propagated grapevines. SV hotspots in the sex determination region and the berry color locus illustrate their impact on phenotype and the role of SVs as drivers of convergent phenotypic evolution.

evolutionary biology↗

bioRxiv2018

Condition-adaptive fused graphical lasso (CFGL): an adaptive procedure for inferring condition-specific gene co-expression network

Co-expression network analysis provides useful information for studying gene regulation in biological processes. Examining condition-specific patterns of co-expression can provide insights into the underlying cellular processes activated in a particular condition. One challenge in this type of analysis is that the sample sizes in each condition are usually small, making the statistical inference of co-expression patterns highly underpowered. A joint network construction that borrows information from related structures across conditions has the potential to improve the power of the analysis.\n\nOne possible approach to constructing the co-expression network is to use the Gaussian graphical model. Though several methods are available for joint estimation of multiple graphical models, they do not fully account for the heterogeneity between samples and between co-expression patterns introduced by condition specificity. Here we develop the condition-adaptive fused graphical lasso (CFGL), a data-driven approach to incorporate condition specificity in the estimation of co-expression networks. We show that this method improves the accuracy with which networks are learned. The application of this method on a rat multi-tissue dataset and The Cancer Genome Atlas (TCGA) breast cancer dataset provides interesting biological insights. In both analyses, we identify numerous modules enriched for Gene Ontology functions and observe that the modules that are upregulated in a particular condition are often involved in condition-specific activities. Interestingly, we observe that the genes strongly associated with survival time in the TCGA dataset are less likely to be network hubs, suggesting that genes associated with cancer progression are likely to govern specific functions, rather than regulating a large number of biological processes. Additionally, we observed that the tumor-specific hub genes tend to have few shared edges with normal tissue, revealing tumor-specific regulatory mechanism.\n\nAuthor summaryGene co-expression networks provide insights into the mechanism of cellular activity and gene regulation. Condition-specific mechanisms may be identified by constructing and comparing co-expression networks of multiple conditions. We propose a novel statistical method to jointly construct co-expression networks for gene expression profiles from multiple conditions. By using a data-driven approach to capture condition-specific co-expression patterns, this method is effective in identifying both co-expression patterns that are specific to a condition and that are common across conditions. The application of this method on real datasets reveals interesting biological insights.

bioinformatics↗

bioRxiv2017

Gene regulatory network rewiring by an adaptively evolving microRNA cluster in Drosophila

New miRNAs are evolutionarily important but their impact on existing biological networks remains unclear. We report the evolution of a microRNA cluster, mir-972C, that arose de novo and the subsequently rewired gene regulatory networks in Drosophila. Molecular evolution analyses revealed that mir-972C originated in the common ancestor of Drosophila where it comprises five old miRNAs. It subsequently recruited five new members in the melanogaster subgroup after conservative evolution for at least 50 million years. Population genetics analyses reveal that young and old mir-972C miRNAs evolved rapidly under positive selection in both seed and non-seed regions. Combining target prediction and cell transfection experiments, we find that sequence changes in individual mir-972C members resulted in extensive gene regulatory network divergence among D. melanogaster, D. simulans, and D. virilis, whereas the target pool of the cluster as a whole remains relatively conserved. Our results suggest that clustering of young and old miRNAs at the same locus broadens target repertoires, resulting in the gain of new targets without losing many old ones. This may facilitate the establishment of new miRNAs within existing regulatory networks.

evolutionary biology↗