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Biology subjects

Song, G.

Publications and source records attributed to Song, G..

At least 55 records · Page 3Linked to original sources
bioRxiv2023

Gene expression plasticity followed by genetic change during colonization a high-elevation environment

Phenotypic plasticity facilitates organismal invasion of novel environments, and the resultant phenotypic change may later be modified by genetic change, so called "plasticity first". Herein we quantify gene expression plasticity and regulatory adaptation in a wild bird (Eurasian Tree Sparrow) from its original lowland (ancestral stage), experimentally implemented hypoxia acclimation (plastic stage) and colonized highland (colonized stage). Using a group of co-expressed genes from the cardiac and flight muscle, respectively, we demonstrate that gene expression plasticity to hypoxia tolerance is more often reversed than reinforced at the colonized stage. By correlating gene expression change with muscle phenotypes, we show that colonized tree sparrows reduce maladaptive plasticity that largely associates with decrease hypoxia tolerance. Conversely, adaptive plasticity that is congruent with increase hypoxia tolerance is often reinforced in the colonized tree sparrows. Genes displaying large levels of reinforcement or reversion plasticity (i.e., 200% of original level) show greater genetic divergence between ancestral and colonized populations. Overall, our work demonstrates that gene expression plasticity at the initial stage of high-elevation colonization can be reversed or reinforced through selection-driven adaptive modification.

evolutionary biology↗
bioRxiv2022

Reimagining Gene-Environment Interaction Analysis for Human Complex Traits

In this study, we introduce PIGEON--a novel statistical framework for quantifying and estimating polygenic gene-environment interaction (GxE) using a variance component analytical approach. Based on PIGEON, we outline the main objectives in GxE studies, demonstrate the flaws in existing GxE approaches, and introduce an innovative estimation procedure which only requires summary statistics as input. We demonstrate the statistical superiority of PIGEON through extensive theoretical and empirical analyses and showcase its performance in multiple analytic settings, including a quasi-experimental GxE study of health outcomes, gene-by-sex interaction for 530 traits, and gene-by-treatment interaction in a randomized clinical trial. Our results show that PIGEON provides an innovative solution to many long-standing challenges in GxE inference and may fundamentally reshape analytical strategies in future GxE studies.

genetics↗
bioRxiv2022

Running ahead of evolution - AI based simulation for predicting future high-risk SARS-CoV-2 variants

The never-ending emergence of SARS-CoV-2 variations of concern (VOCs) has challenged the whole world for pandemic control. In order to develop effective drugs and vaccines, one needs to efficiently simulate SARS-CoV-2 spike receptor binding domain (RBD) mutations and identify high-risk variants. We pretrain a large protein language model with approximately 408 million protein sequences and construct a high-throughput screening for the prediction of binding affinity and antibody escape. As the first work on SARS-CoV-2 RBD mutation simulation, we successfully identify mutations in the RBD regions of 5 VOCs and can screen millions of potential variants in seconds. Our workflow scales to 4096 NPUs with 96.5% scalability and 493.9x speedup in mixed precision computing, while achieving a peak performance of 366.8 PFLOPS (reaching 34.9% theoretical peak) on Pengcheng Cloudbrain-II. Our method paves the way for simulating coronavirus evolution in order to prepare for a future pandemic that will inevitably take place. Our models are released at https://github.com/ZhiweiNiepku/SARS-CoV-2_mutation_simulation to facilitate future related work. JustificationWe develop a novel multi-constraint variation prediction framework to simulate SARS-CoV-2 RBD mutations, reaching a peak performance of 366.8 PFLOPS with 96.5% scalability and achieving 493.9x speedup. Our method facilitates the prediction and prioritization of future high-risk variants for the early deployment of drugs and vaccines. Performance attributes O_TBL View this table: org.highwire.dtl.DTLVardef@1b1873aorg.highwire.dtl.DTLVardef@25314eorg.highwire.dtl.DTLVardef@1c80130org.highwire.dtl.DTLVardef@1c61b21org.highwire.dtl.DTLVardef@11f21c5_HPS_FORMAT_FIGEXP M_TBL C_TBL Overview of the problemCoronavirus Disease 2019 (COVID-19) has spread rapidly to more than 200 countries or regions since December 2019. Due to its high infectivity, there have been over 645 million confirmed cases, including approximately 6.6 million deaths, reported by the World Health Organization (WHO) as of December 20221. In addition to being a serious threat to human health, COVID-19 has had a catastrophic impact on the global economy.

bioinformatics↗
bioRxiv2022

High-throughput identification of prefusion-stabilizing mutations in SARS-CoV-2 spike

Designing prefusion-stabilized SARS-CoV-2 spike is critical for the effectiveness of COVID-19 vaccines. All COVID-19 vaccines in the US encode spike with K986P/V987P mutations to stabilize its prefusion conformation. However, contemporary methods on engineering prefusion-stabilized spike immunogens involve tedious experimental work and heavily rely on structural information. Here, we established a systematic and unbiased method of identifying mutations that concomitantly improve expression and stabilize the prefusion conformation of the SARS-CoV-2 spike. Our method integrated a fluorescence-based fusion assay, mammalian cell display technology, and deep mutational scanning. As a proof-of-concept, this method was applied to a region in the S2 domain that includes the first heptad repeat and central helix. Our results revealed that besides K986P and V987P, several mutations simultaneously improved expression and significantly lowered the fusogenicity of the spike. As prefusion stabilization is a common challenge for viral immunogen design, this work will help accelerate vaccine development against different viruses.

biochemistry↗
bioRxiv2022

Evolution of antibody immunity following Omicron BA.1 breakthrough infection

Understanding the evolution of antibody immunity following heterologous SAR-CoV-2 breakthrough infection will inform the development of next-generation vaccines. Here, we tracked SARS-CoV-2 receptor binding domain (RBD)-specific antibody responses up to six months following Omicron BA.1 breakthrough infection in mRNA-vaccinated individuals. Cross-reactive serum neutralizing antibody and memory B cell (MBC) responses declined by two- to four-fold through the study period. Breakthrough infection elicited minimal de novo Omicron-specific B cell responses but drove affinity maturation of pre-existing cross-reactive MBCs toward BA.1. Public clones dominated the neutralizing antibody response at both early and late time points, and their escape mutation profiles predicted newly emergent Omicron sublineages. The results demonstrate that heterologous SARS-CoV-2 variant exposure drives the evolution of B cell memory and suggest that convergent neutralizing antibody responses continue to shape viral evolution.

immunology↗
bioRxiv2022

Protein Fold Classification using Graph Neural Network and Protein Topology Graph

Protein fold classification reveals key structural information about proteins that is essential for understanding their function. While numerous approaches exist in the literature that classifies protein fold from sequence data using machine learning, there is hardly any approach that classifies protein fold from the secondary or tertiary structure data using deep learning. This work proposes a novel protein fold classification technique based on graph neural network and protein topology graphs. Protein topology graphs are constructed according to definitions in the Protein Topology Graph Library from protein secondary structure level data and their contacts. To the best of our knowledge, this is the first approach that applies graph neural network for protein fold classification. We analyze the SCOPe 2.07 data set, a manually and computationally curated database that classifies known protein structures into their taxonomic hierarchy and provides predefined labels for a certain number of entries from the Protein Data Bank. We also analyze the latest version of the CATH data set. Experimental results show that the classification accuracy is at around 82% - 100% under certain settings. Due to the rapid growth of structural data, automating the structure classification process with high accuracy using structural data is much needed in the field. This work introduces a new paradigm of protein fold classification that meets this need. The implementation of the model for protein fold classification and the datasets are available here https://github.com/SuriDipannitaSayeed/ProteinFoldClassification.git Author summaryClassification of protein structures is traditionally done using manual curation, evolutionary relationship, or sequence comparison-based methods. Applying machine learning and deep learning to protein structure classification is a comparatively new trend that holds great promises for automating the structure classification process. Advance deep learning technique like Graph Neural Network is still unexplored in this respect. SCOP and CATH are two traditional databases that provide the hierarchical taxonomic classification of protein structures. This work provides a novel computational approach that classifies protein folds in SCOP and CATH with graph neural network, performing a graph classification task.

bioinformatics↗
bioRxiv2022

Engineering precise adenine base editor with infinitesimal rates of bystander mutations and off-target editing

Adenine base editors (ABEs) catalyze A-to-G transitions showing broad applications, but their bystander mutations and off-target editing effects raise the concerns of safety issues. Through structure-guided engineering, we found ABE8e with an N108Q mutation reduced both adenine and cytosine bystander editing, and introduction of an additional L145T mutation (ABE9), further refined the editing window to 1-2nt with eliminated cytosine editing. Importantly, ABE9 induced very minimal RNA and undetectable Cas9-independent DNA off-target effects, which mainly installed desired single A-to-G conversion in mouse and rat embryos to efficiently generate disease models. Moreover, ABE9 accurately edited A5 position of the protospacer sequence in pathogenic homopolymeric adenosine sites (up to 342.5-fold precision than ABE8e) and was further confirmed through a library of guide RNA-target sequence pairs. Due to the minimized editing window, ABE9 could further broaden the targeting scope for precise correction of pathogenic SNVs when fused to Cas9 variants with expanded PAM compatibility.

bioengineering↗
bioRxiv2022

Probing the biophysical constraints of SARS-CoV-2 spike N-terminal domain using deep mutational scanning

Increasing the expression level of the SARS-CoV-2 spike (S) protein has been critical for COVID-19 vaccine development. While previous efforts largely focused on engineering the receptor-binding domain (RBD) and the S2 subunit, the N-terminal domain (NTD) has been long overlooked due to the limited understanding of its biophysical constraints. In this study, the effects of thousands of NTD single mutations on S protein expression were quantified by deep mutational scanning. Our results revealed that in terms of S protein expression, the mutational tolerability of NTD residues was inversely correlated with their proximity to the RBD and S2. We also identified NTD mutations at the interdomain interface that increased S protein expression without altering its antigenicity. Overall, this study not only advances the understanding of the biophysical constraints of the NTD, but also provides invaluable insights into S-based immunogen design.

biochemistry↗
bioRxiv2022

Quantifying portable genetic effects and improving cross-ancestry genetic prediction with GWAS summary statistics

Polygenic risk scores (PRS) calculated from genome-wide association studies (GWAS) of Europeans are known to have substantially reduced predictive accuracy in non-European populations, limiting its clinical utility and raising concerns about health disparities across ancestral populations. Here, we introduce a novel statistical framework named X-Wing to improve predictive performance in ancestrally diverse populations. X-Wing quantifies local genetic correlations for complex traits between populations, employs a novel annotation-dependent estimation procedure to amplify correlated genetic effects between populations, and combines multiple population-specific PRS into a unified score with GWAS summary statistics alone as input. Through extensive benchmarking, we demonstrate that X-Wing pinpoints portable genetic effects and substantially improves PRS performance in non-European populations, showing 18.7%-122.1% gain in predictive R2 compared to state-of-the-art methods based on GWAS summary statistics. Overall, X-Wing addresses critical limitations in existing approaches and may have broad applications in cross-population polygenic prediction.

genetics↗
bioRxiv2022

Elucidating host cell response pathways and repurposing therapeutics for SARS-CoV-2 and other coronaviruses using gene expression profiles of chemical and genetic perturbations

COVID-19 is an ongoing pandemic that has been causing devastation across the globe for over 2 years. Although there are multiple vaccines that can prevent severe symptoms, effective COVID-19 therapeutics are still of importance. Using our proprietary in silico SMarTR engine, we screened more than 22,000 unique compounds represented by over half a million gene expression profiles to uncover compounds that can be repurposed for SARS-CoV-2 and other coronaviruses in a timely and cost-efficient manner. We then tested 13 compounds in vitro and found three with potency against SARS-CoV-2 with reasonable cytotoxicity. Bortezomib and homoharringtonine are some of the most promising hits with IC50 of 1.39 M and 0.16 M, respectively for SARS-CoV-2. Tanespimycin and homoharringtonine were effective against the common cold coronaviruses. In-depth analysis highlighted proteasome, ribosome, and heat shock pathways as key targets in modulating host responses during viral infection. Further studies of these pathways and compounds have provided novel and impactful insights into SARS-CoV-2 biology and host responses that could be further leveraged for COVID-19 therapeutics development.

genomics↗
bioRxiv2022

A broad and potent neutralization epitope in SARS-related coronaviruses

Many neutralizing antibodies (nAbs) elicited to ancestral SARS-CoV-2 through natural infection and vaccination generally have reduced effectiveness to SARS-CoV-2 variants. Here we show therapeutic antibody ADG20 is able to neutralize all SARS-CoV-2 variants of concern (VOCs) including Omicron (B.1.1.529) as well as other SARS-related coronaviruses. We delineate the structural basis of this relatively escape-resistant epitope that extends from one end of the receptor binding site (RBS) into the highly conserved CR3022 site. ADG20 can then benefit from high potency through direct competition with ACE2 in the more variable RBS and interaction with the more highly conserved CR3022 site. Importantly, antibodies that are able to target this site generally neutralize all VOCs, albeit with reduced potency against Omicron. Thus, this highly conserved and vulnerable site can be exploited for design of universal vaccines and therapeutic antibodies.

microbiology↗
bioRxiv2022

Integration of multi-omics data reveals interplay between brassinosteroid and TORC signaling in Arabidopsis

Brassinosteroids (BR) and Target of Rapamycin Complex (TORC) are two major actors coordinating plant growth and stress responses. BRs function through a signaling pathway to extensively regulate gene expression and TORC is known to regulate translation and autophagy. Recent studies revealed that these two pathways crosstalk, but a system-wide view of their interplay is still missing. Thus, we quantified the level of 23,975 transcripts, 11,183 proteins, and 27,887 phosphorylation sites in wild-type Arabidopsis and in mutants with altered levels of either BRASSINOSTEROID INSENSITIVE 2 (BIN2) or REGULATORY ASSOCIATED PROTEIN OF TOR 1B (RAPTOR1B), two key players in BR and TORC signaling, respectively. We found that perturbation of BIN2 or RAPTOR1B levels affects a common set of gene-products involved in growth and stress responses. Furthermore, we used the multi-omic data to reconstruct an integrated signaling network. We screened 41 candidate genes identified from the reconstructed network and found that loss of function mutants of many of these proteins led to an altered BR response and/or modulated autophagy activity. Altogether, these results establish a predictive network that defines different layers of molecular interactions between BR-or TORC-regulated growth and autophagy.

plant biology↗
bioRxiv2022

Broadly neutralizing anti-S2 antibodies protect against all three human betacoronaviruses that cause severe disease

Pan-betacoronavirus neutralizing antibodies may hold the key to developing broadly protective vaccines against coronaviruses that cause severe disease, for anticipating novel pandemic-causing viruses, and to respond more effectively to SARS-CoV-2 variants. The emergence of the Omicron variant of SARS-CoV-2 has illustrated the limitations of solely targeting the receptor binding domain (RBD) of the envelope Spike (S)-protein. Here, we isolated a large panel of broadly neutralizing antibodies (bnAbs) from SARS-CoV-2 recovered-vaccinated donors that target a conserved S2 region in the fusion machinery on betacoronavirus spikes. Select bnAbs show broad in vivo protection against all three pathogenic betacoronaviruses, SARS-CoV-1, SARS-CoV-2 and MERS-CoV, that have spilled over into humans in the past 20 years to cause severe disease. The bnAbs provide new opportunities for antibody-based interventions and key insights for developing pan-betacoronavirus vaccines.

immunology↗
bioRxiv2021

Molecular insights into antibody-mediated protection against the prototypic simian immunodeficiency virus

SIVmac239 infection of macaques is a favored model of human HIV infection. However, the SIVmac239 envelope (Env) trimer structure, glycan occupancy, and the targets and ability of neutralizing antibodies (nAbs) to protect against SIVmac239 remain unknown. Here, we report the isolation of SIVmac239 nAbs that recognize a glycan hole and the V1/V4 loop. A high-resolution structure of a SIVmac239 Env trimer-nAb complex shows many similarities to HIV and SIVcpz Envs, but with distinct V4 features and an extended V1 loop. Moreover, SIVmac239 Env has a higher glycan shield density than HIV Env that may contribute to poor or delayed nAb responses in SIVmac239-infected macaques. Passive transfer of a nAb protects macaques from repeated low dose intraveneous SIVmac239 challenge at serum titers comparable to those described for protection of humans against HIV infection. Our results provide structural insights for vaccine design and shed light on antibody-mediated protection in the SIV model.

immunology↗
bioRxiv2021

A recurring YYDRxG pattern in broadly neutralizing antibodies to a conserved site on SARS-CoV-2, variants of concern, and related viruses

Studying the antibody response to SARS-CoV-2 informs on how the human immune system can respond to antigenic variants as well as other SARS-related viruses. Here, we structurally and functionally characterized a potent human antibody ADI-62113 that also neutralizes SARS-CoV- 2 variants of concern and cross-reacts with many other sarbecoviruses. A YYDRxG motif encoded by IGHD3-22 in CDR H3 facilitates targeting to a highly conserved epitope on the SARS-CoV-2 receptor binding domain. A computational search for a YYDRxG pattern in publicly available sequences identified many antibodies with broad neutralization activity against SARS-CoV-2 variants and SARS-CoV. Thus, the YYDRxG motif represents a common convergent solution for the human humoral immune system to counteract sarbecoviruses. These findings also suggest an epitope targeting strategy to identify potent and broadly neutralizing antibodies that can aid in the design of pan-sarbecovirus vaccines and antibody therapeutics. Short SummaryDecryption of a recurrent sequence feature in anti-SARS-CoV-2 antibodies identifies how potent pan-sarbecovirus antibodies target a conserved epitope on the receptor binding domain.

immunology↗
bioRxiv2021

Phosphorylation dynamics in a flg22 induced, heterotrimeric G protein dependent signaling network in Arabidopsis thaliana reveals a candidate PP2A phosphatase involved in AtRGS1 trafficking

flg22 is a 22-amino peptide released from bacterial flagellin, a Microbe-Associated Molecular Pattern (MAMP) that is recognized by the plant cell as a signal indicating that bacteria are present. On its own, flg22 initiates a rapid increase in cytoplasmic calcium, extracellular reactive oxygen species, and activation of a Mitogen Activated Protein Kinase (MAPK) cascade, all of which are activated within 15 minutes after the cell perceives flg22. Here we show a massive change in protein abundance and phosphorylation state of the Arabidopsis root cell proteome within this 15-minute duration in wildtype and a mutant deficient in G-protein coupled signaling. Integration of phosphoproteome with protein-protein interactome data followed by network topology analyses discovered that many of the flg22-induced phosphoproteome changes fall on proteins that comprise the G protein interactome and on the most highly populated hubs of the immunity network. Approximately 95% of the phosphorylation changes in the G-protein interactome depend on a functional heterotrimeric G protein complex, some occur on proteins that interact directly with components of G-coupled signal transduction. One of these is ATB, a substrate-recognition sub-unit of the PP2A Ser/Thr phosphatase and an interactor to Arabidopsis thaliana REGULATOR OF G SIGNALING 1 protein (AtRGS1), a 7-transmembrane spanning modulator of the nucleotide-binding state of the core G protein complex. AtRGS1 is phosphorylated by BAK1, a component of the flg22 receptor, to initiate AtRGS1 endocytosis. A null mutation of ATB confers high basal endocytosis of AtRGS1, suggesting sustained phosphorylated status. Loss of ATB confers traits associated with loss of AtRGS1. Because the basal level of AtRGS1 is lower in the atb null mutant in a proteasome-dependent manner, we propose that phosphorylation-dependent endocytosis of AtRGS1 is part of a mechanism to degrade AtRGS1 which then sustains activation of the G protein complex. Thus, the role of ATB is now established as a central component of phosphorylation-dependent regulation of system dynamics in innate immunity.

systems biology↗
bioRxiv2021

Epicardial HDAC3 promotes myocardial growth through a novel microRNA pathway

RationalEstablishment of the myocardial wall requires proper growth cues from nonmyocardial tissues. During heart development, the epicardium and epicardium-derived cells (EPDCs) instruct myocardial growth by secreting essential factors including fibroblast growth factor 9 (FGF9) and insulin-like growth factor 2 (IGF2). However, it is poorly understood how the epicardial secreted factors are regulated, in particular by chromatin modifications for myocardial formation. ObjectiveTo understand whether and how histone deacetylase 3 (HDAC3) in the developing epicardium regulates myocardial growth. Methods and ResultsWe deleted Hdac3 in the developing murine epicardium and mutant hearts showed ventricular myocardial wall hypoplasia with reduction of EPDCs. The cultured embryonic cardiomyocytes with supernatants from Hdac3 knockout (KO) mouse epicardial cells (MECs) also showed decreased proliferation. Genome-wide transcriptomic analysis revealed that Fgf9 and Igf2 were significantly down-regulated in Hdac3 KO MECs. We further found that Fgf9 and Igf2 expression is dependent on HDAC3 deacetylase activity. The supplementation of FGF9 or IGF2 can rescue the myocardial proliferation defects treated by Hdac3 KO supernatant. Mechanistically, we identified that microRNA (miR)-322 and miR-503 were upregulated in Hdac3 KO MECs and Hdac3 epicardial KO hearts. Overexpression of miR-322 or miR-503 repressed FGF9 and IGF2 expression, while knockdown of miR-322 or miR-503 restored FGF9 and IGF2 expression in Hdac3 KO MECs. ConclusionsOur findings reveal a critical signaling pathway in which epicardial HDAC3 promotes compact myocardial growth by stimulating FGF9 and IGF2 through repressing miR-322/miR-503, providing novel insights in elucidating etiology of congenital heart defects, and conceptual strategies to promote myocardial regeneration.

developmental biology↗