Biology subjects

Tan, Q.

Publications and source records attributed to Tan, Q..

35 records · Page 2Linked to original sources

bioRxiv2023

Extended Nucleic Acid (exNA): A Novel, Biologically Compatible Backbone that Significantly Enhances Oligonucleotide Efficacy in vivo

Metabolic stabilization of therapeutic oligonucleotides requires both sugar and backbone modifications, where phosphorothioate (PS) is the only backbone chemistry used in the clinic. Here, we describe the discovery, synthesis, and characterization of a novel biologically compatible backbone, extended nucleic acid (exNA). Upon exNA precursor scale up, exNA incorporation is fully compatible with common nucleic acid synthetic protocols. The novel backbone is orthogonal to PS and shows profound stabilization against 3- and 5-exonucleases. Using small interfering RNAs (siRNAs) as an example, we show exNA is tolerated at most nucleotide positions and profoundly improves in vivo efficacy. A combined exNA-PS backbone enhances siRNA resistance to serum 3-exonuclease by [~]32-fold over PS backbone and >1000-fold over the natural phosphodiester backbone, thereby enhancing tissue exposure ([~]6-fold), tissues accumulation (4- to 20-fold), and potency both systemically and in brain. The improved potency and durability imparted by exNA opens more tissues and indications to oligonucleotide-driven therapeutic interventions.

biochemistry↗

bioRxiv2022

Selection and validation of internal control genes for quantitative real-time RT-qPCR normalization of Phlebopus portentosus gene expression under different conditions

Phlebopus portentosus (Berk. and Broome) Boedijin is an attractive edible mushroom and considered as the unique bolete to have achieved artificial cultivation in vitro. Gene expression analysis has become widely used in researches of edible fungi and is important to uncover the functions of genes involved in complex biological processes. Selecting appropriate reference genes is crucial to ensuring reliable results of gene expression analysis by RT-qPCR. In our study, a total of 12 candidate control genes were selected from 25 traditional housekeeping genes based on the expression stability in 9 transcriptomes of 3 developmental stages. These genes were further evaluated using geNorm, NormFinder and RefFinder under different conditions and developmental stages. The results revealed that MSF1-domain-containing protein (MSF1), synaptobrevin (SYB), mitogen-activated protein kinase genes (MAPK), TATA binding protein 1 (TBP1) and SPRY domain protein (SPRY) were the most stable reference genes in all sample treatments, while elongation factor 1-alpha (EF1), Actin and ubiquitin-conjugating enzyme (UBCE) were the most unstably expressed. The gene SYB was selected based on the transcriptome results and was identified as a novel reference gene in P. portentosus. This is the first detailed study for identification reference genes in this fungus and may provide new insights into selecting genes and quantifying gene expression.

microbiology↗

bioRxiv2022

Development of highly potent non-covalent inhibitors of SARS-CoV-2 3CLpro

The SARS-CoV-2 virus is the causal agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19). There is an urgent need for potent, specific antiviral compounds against SARS-CoV-2. The 3C-like protease (3CLpro) is an essential enzyme for the replication of SARS-CoV-2 and other coronaviruses, and thus is a target for coronavirus drug discovery. Nearly all inhibitors of coronavirus 3CLpro reported so far are covalent inhibitors. Here, we report the development of specific, non-covalent inhibitors of 3CLpro. The most potent one, WU-04, effectively blocks SARS-CoV-2 replications in human cells with EC50 values in the 10-nM range. WU-04 also inhibits the 3CLpro of SARS-CoV and MERS-CoV with high potency, indicating that it is a pan-inhibitor of coronavirus 3CLpro. WU-04 showed anti-SARS-CoV-2 activity similar to that of PF-07321332 (Nirmatrelvir) in K18-hACE2 mice when the same dose was administered orally. Thus, WU-04 is a promising drug candidate for coronavirus treatment. One-Sentence SummaryA oral non-covalent inhibitor of 3C-like protease effectively inhibits SARS-CoV-2 replication.

microbiology↗

bioRxiv2022

Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions

Non-coding RNA structure and function are essential to understanding various biological processes, such as cell signaling, gene expression, and post-transcriptional regulations. These are all among the core problems in the RNA field. With the rapid growth of sequencing technology, we have accumulated a massive amount of unannotated RNA sequences. On the other hand, expensive experimental observatory results in only limited numbers of annotated data and 3D structures. Hence, it is still challenging to design computational methods for predicting their structures and functions. The lack of annotated data and systematic study causes inferior performance. To resolve the issue, we propose a novel RNA foundation model (RNA-FM) to take advantage of all the 23 million non-coding RNA sequences through self-supervised learning. Within this approach, we discover that the pre-trained RNA-FM could infer sequential and evolutionary information of non-coding RNAs without using any labels. Furthermore, we demonstrate RNA-FMs effectiveness by applying it to the downstream secondary/3D structure prediction, SARS-CoV-2 genome structure and evolution prediction, protein-RNA binding preference modeling, and gene expression regulation modeling. The comprehensive experiments show that the proposed method improves the RNA structural and functional modelling results significantly and consistently. Despite only being trained with unlabelled data, RNA-FM can serve as the foundational model for the field.

bioinformatics↗

bioRxiv2022

Two shifts in evolutionary lability underlie independent gains and losses of root-nodule symbiosis in a single clade of plants

Root nodule symbiosis (RNS) allows plants to access atmospheric nitrogen converted into usable forms through a mutualistic relationship with soil bacteria. RNS is a complex trait requiring coordination from both the plant host and the bacterial symbiont, and pinpointing the evolutionary origins of root nodules is critical for understanding the genetic basis of RNS. This endeavor is complicated by data limitations and the intermittent presence of RNS in a single clade of ca. 30,000 species of flowering plants, i.e., the nitrogen-fixing clade (NFC). We developed the most extensive de novo phylogeny for all major lineages of the NFC and an enhanced root nodule trait database to reconstruct the evolution of RNS. Through identification of the evolutionary pathway to RNS gain, we show that shifts among heterogeneous evolutionary rates can explain how a complex trait such as RNS can arise many times across a large phylogeny. Our analysis identifies a two-step process in which an ancestral precursor state gave rise to a more labile state from which RNS was quickly gained at specific points in the NFC. Our rigorous reconstruction of ancestral states illustrates how a two-step pathway could have led to multiple independent gains and losses of RNS, contrary to recent hypotheses invoking just a single gain and numerous losses. RNS may be an example of multi-level convergent evolution, thus requiring a broader phylogenetic and genetic scope for genome-phenome mapping to elucidate mechanisms enabling fully functional RNS.

evolutionary biology↗

bioRxiv2022

DeepAcr: Predicting Anti-CRISPR with Deep Learning

As an important group of proteins discovered in phages, anti-CRISPR inhibits the activity of the immune system of bacteria (i.e., CRISPR-Cas), showing great potential for gene editing and phage therapy. However, the prediction and discovery of anti-CRISPR are challenging for its high variability and fast evolution. Existing biological studies often depend on known CRISPR and anti-CRISPR pairs, which may not be practical considering the huge number of pairs in reality. Computational methods usually struggle with prediction performance. To tackle these issues, we propose a novel deep neural network for anti-CRISPR analysis (AcrNET), which achieves impressive performance. On both the cross-fold and cross-dataset validation, our method outperforms the previous state-of-the-art methods significantly. Impressively, AcrNET improves the prediction performance by at least 15% regarding the F1 score for the cross-dataset test. Moreover, AcrNET is the first computational method to predict the detailed anti-CRISPR classes, which may help illustrate the anti-CRISPR mechanism. Taking advantage of a Transformer protein language model pre-trained on 250 million protein sequences, AcrNET overcomes the data scarcity problem. Extensive experiments and analysis suggest that Transformer model feature, evolutionary feature, and local structure feature complement each other, which indicates the critical properties of anti-CRISPR proteins. Combined with AlphaFold prediction, further motif analysis and docking experiments demonstrate that AcrNET captures the evolutionarily conserved pattern and the interaction between anti-CRISPR and the target implicitly. With the impressive prediction capability, AcrNET can serve as a valuable tool for anti-CRISPR study and new anti-CRISPR discovery, with a free webserver at https://proj.cse.cuhk.edu.hk/aihlab/AcrNET/.

bioinformatics↗

bioRxiv2022

Lung injury epigenetically primes mesenchyme for amplified activation upon re-injury

The lungs have a remarkable capacity to repair. However, repetitive injury can lead to progressive fibrosis and end-stage organ failure. Whether tissue-resident mesenchymal cell populations retain epigenetic memory of prior injuries that contribute to this pathological process is unknown. Here we used a genetic lineage labeling approach to mark the lung mesenchyme prior to injury, then performed multi-modal analyses on isolated lung mesenchyme during the initiation, progression and resolution of the fibrotic response. Our results demonstrate the remarkable epigenetic and transcriptional plasticity of the lung mesenchyme during fibrogenic activation and de-activation. Despite this plasticity, we also find that the lung mesenchyme retains specific epigenetic traits (memory) of prior activation, resulting in amplified induction of a fibrogenic program upon re-injury. We identify Runx1 as a critical driver of both fibrogenic activation and epigenetic memory. Comparison of fresh isolated and cultured lung mesenchyme demonstrates that Runx1 is spontaneously activated in standard culture conditions, previously masking these roles of Runx1. Genetic and pharmacological targeting of Runx1 dampens fibrogenic mesenchymal cell activation in cell and tissue models, confirming its functional importance. Finally, publicly available scRNAseq data reveal selective expression of Runx1 in the fibrogenic cell subpopulations that emerge in mouse and human fibrotic lung tissue. Collectively, our findings implicate Runx1 in both the initiation and memory of fibrogenic mesenchymal cell activation that together prime amplified mesenchymal cell responses upon repeated injury.

cell biology↗

bioRxiv2021

fastMSA: Accelerating Multiple Sequence Alignment with Dense Retrieval on Protein Language

Evolutionarily related sequences provide information for the protein structure and function. Multiple sequence alignment, which includes homolog searching from large databases and sequence alignment, is efficient to dig out the information and assist protein structure and function prediction, whose efficiency has been proved by AlphaFold. Despite the existing tools for multiple sequence alignment, searching homologs from the entire UniProt is still time-consuming. Considering the success of AlphaFold, foreseeably, large-scale multiple sequence alignments against massive databases will be a trend in the field. It is very desirable to accelerate this step. Here, we propose a novel method, fastMSA, to improve the speed significantly. Our idea is orthogonal to all the previous accelerating methods. Taking advantage of the protein language model based on BERT, we propose a novel dual encoder architecture that can embed the protein sequences into a low-dimension space and filter the unrelated sequences efficiently before running BLAST. Extensive experimental results suggest that we can recall most of the homologs with a 34-fold speed-up. Moreover, our method is compatible with the downstream tasks, such as structure prediction using AlphaFold. Using multiple sequence alignments generated from our method, we have little performance compromise on the protein structure prediction with much less running time. fastMSA will effectively assist protein sequence, structure, and function analysis based on homologs and multiple sequence alignment.

bioinformatics↗

bioRxiv2021

USPNet: unbiased organism-agnostic signal peptidepredictor with deep protein language model

Signal peptide is a short peptide located in the N-terminus of proteins. It plays an important role in targeting and transferring transmembrane proteins and secreted proteins to correct positions. Compared with traditional experimental methods to identify and discover signal peptides, the computational methods are faster and more efficient, which are more practical for the analysis of thousands or even millions of protein sequences in reality, especially for the metagenomic data. Therefore, computational tools are recently proposed to classify signal peptides and predict cleavage site positions, but most of them disregard the extreme data imbalance problem in these tasks. In addition, almost all these methods rely on additional group information of proteins to boost their performances, which, however, may not always be available. To deal with these issues, in this paper, we present Unbiased Organism-agnostic Signal Peptide Network (USPNet), a signal peptide prediction and cleavage site prediction model based on deep protein language model. We propose to use label distribution-aware margin (LDAM) loss and evolutionary scale modeling (ESM) embedding to handle data imbalance and object-dependence problems. Extensive experimental results demonstrate that the proposed method significantly outperforms all the previous methods on the classification performance. Additional study on the simulated metagenomic data further indicates that our model is a more universal and robust tool without dependency on additional group information of proteins, with the Matthews correlation coefficient improved by up to 17.5%. The proposed method will be potentially useful to discover new signal peptides from the abundant metagenomic data.

bioinformatics↗

bioRxiv2021

Structures of the human cholecystokinin receptors in complex with agonists and antagonists

Cholecystokinin receptors, CCKAR and CCKBR, are important neuro-intestinal peptide hormone receptors and play a vital role in food intake and appetite regulation. Here we report three crystal structures of the human CCKAR in complex with different ligands, including one peptide agonist and two small-molecule antagonists, as well as two cryo-electron microscopy structures of CCKBR-gastrin in complex with Gi2 and Gq, respectively. These structures reveal the recognition pattern of different ligand types and the molecular basis of peptide selectivity in the cholecystokinin receptor family. By comparing receptor structures in different conformational states, a stepwise activation process of cholecystokinin receptors is proposed. Combined with pharmacological data, our results provide atomic details for differential ligand recognition and receptor activation mechanisms. These insights will facilitate the discovery of potential therapeutics targeting cholecystokinin receptors.

biophysics↗

bioRxiv2020

ZNF416 is a pivotal transcriptional regulator of fibroblast mechano-activation

Matrix stiffness is a central regulator of fibroblast function. However, the transcriptional mechanisms linking matrix stiffness to changes in fibroblast phenotype are incompletely understood. Here, we evaluated the effect of matrix stiffness on genome-wide chromatin accessibility in freshly-isolated lung fibroblasts using assay for transposase-accessible chromatin followed by sequencing (ATAC-seq). We found higher matrix stiffness profoundly increased global chromatin accessibility relative to lower matrix stiffness, and these alterations were in close genomic proximity to known pro-fibrotic gene programs. Motif analysis of these regulated genomic loci identified ZNF416 as a putative mediator of fibroblast stiffness responses. Similarly, motif analysis of the promoters of differentially expressed genes observed in freshly sorted fibroblasts from an experimental bleomycin lung fibrosis model also identified ZNF416 as a putative mediator of in vivo fibroblast activation. Genome occupancy analysis using chromatin-immunoprecipitation followed by sequencing (ChIP-seq) confirmed that ZNF416 occupies a broad range of genes implicated in fibroblast activation and tissue-fibrosis, with relatively little overlap in genomic occupancy with other mechanoresponsive and pro-fibrotic transcriptional regulators. Using loss and gain of function studies we demonstrated that ZNF416 plays a critical role in fibroblast proliferation, extracellular matrix synthesis and contractile function. Together these observations identify ZNF416 as novel mechano-activated transcriptional regulator of fibroblast biology.

cell biology↗

bioRxiv2020

Integrated technology platform for accelerated discovery of antiviral antibody therapeutics

The emergence and reemergence of highly virulent viral pathogens with pandemic potential has created an urgent need for accelerated discovery of antiviral therapeutics. Antiviral human monoclonal (mAbs) are promising drug candidates to prevent or treat severe viral diseases, but the long timelines needed for discovery limits their rapid deployment and use. Here, we report the development of an integrated sequence of technologies incorporating advances in single-cell mRNA sequence analysis, bioinformatics, synthetic biology, and high-throughput functional analysis that allowed us to discover highly potent antiviral human mAbs and validate their activity in vivo at an unprecedented scale, speed, and efficiency. In a 78-day study, modeling deployment of a rapid response platform to an outbreak, we isolated >100 individual Zika virus (ZIKV) specific human mAbs, assessed their function, identified 29 broadly-neutralizing mAbs, and verified therapeutic potency of lead candidates with antibody-encoding mRNA formulation and/or IgG protein delivery in mice and nonhuman primates. Our work provides a roadmap for the rapid antibody discovery programs against viral pathogens of global concern.

immunology↗

bioRxiv2020

A Small-Bodied Troodontid (Dinosauria, Theropoda) from the Upper Cretaceous Wulansuhai Formation of Inner Mongolia, China

A new small-bodied troodontid (LH PV39) recovered from the Upper Cretaceous Wulansuhai Formation, Suhongtu, Inner Mongolia, China, is described. The new specimen preserves six postaxial cervical vertebrae, five completely fused sacral and four posterior caudal vertebrae in addition to two manual unguals. The completely fused neurocentral junctions indicate that a skeletally mature individual of the same species of LH PV39 would be smaller than Philovenator and comparable in body size to a skeletal mature individual of Almas. The extremely dorsoventrally compressed sacral centra and neural canal, and the middle three sacral centra that are shorter and wider than the first and the last one distinguishing LH PV39 from other known troodontids. A series of phylogenetic analyses were conducted using modified published matrices. By coding LH PV39 in different strategies, the troodontid affinity of LH PV39 is confirmed and it was recovered as the sister taxon of either Mei and Sinovenator (LH PV39 scored as a separate OTU) or Linhevenator (incorporating LH PV39 into Philovenator) in the best resolved coelurosaurian interrelationships. The referral of LH PV39 to Philovenator does not seriously alter the phylogenetic position of Philovenator nor the interrelationships of troodontids. This new finding confirms that the small and large sized troodontids are coexisted in the Gobi Desert of the Mongolia Plateau until the end of Cretaceous.

evolutionary biology↗

bioRxiv2019

A decade of epigenetic change in aging twins: genetic and environmental contributions to longitudinal DNA methylation

Summary/AbstractO_ST_ABSBackgroundC_ST_ABSEpigenetic changes may result from the interplay of environmental exposures and genetic influences and contribute to differences in age-related disease, disability and mortality risk. However, the etiologies contributing to stability and change in DNA methylation have rarely been examined longitudinally. MethodsWe considered DNA methylation in whole blood leukocyte DNA across a 10-year span in two samples of same-sex aging twins: (a) Swedish Adoption Twin Study of Aging (SATSA; N = 53 pairs, 53% female; 62.9 and 72.5 years, SD=7.2 years); (b) Longitudinal Study of Aging Danish Twins (LSADT; N = 43 pairs, 72% female, 76.2 and 86.1 years, SD=1.8 years). Joint biometrical analyses were conducted on 358,836 methylation probes in common. Bivariate twin models were fitted, adjusting for age, sex and country. ResultsOverall, results suggest genetic contributions to DNA methylation across 358,836 sites tended to be small and lessen across 10 years (broad heritability M=23.8% and 18.0%) but contributed to stability across time while person-specific factors explained emergent influences across the decade. Aging-specific sites identified from prior EWAS and methylation age clocks were more heritable than background sites. The 5,037 sites that showed the greatest heritable/familial-environmental influences (p<1E-07) were enriched for immune and inflammation pathways while 2,020 low stability sites showed enrichment in stress-related pathways. ConclusionsAcross time, stability in methylation is primarily due to genetic contributions, while novel experiences and exposures contribute to methylation differences. Elevated genetic contributions at age-related methylation sites suggest that adaptions to aging and senescence may be differentially impacted by genetic background.

genetics↗

bioRxiv2019

Age and mortality associated DNA methylation patterns on the X-chromosome in male and female samples

BackgroundMultiple epigenetic association studies on human aging have been performed reporting large numbers of sites differentially methylated across ages on the autosomal chromosomes. The X-chromosome has been studied little, due to analytical difficulties in dealing with sex differences in X-chromosome content and X-inactivation in females. Based on large collections of genome-wide DNA methylation data on two Danish cohorts of identical twins (mean ages, 66 and 79 years) and the Lothian Birth Cohort 1921 (mean age 79 years), we conducted a chromosome-wide association analysis on male and female samples separately with equal sample sizes to discover age-dependent X-linked DNA methylation patterns using chromosome 20 with about same number of CpGs analysed as an autosomal reference, and compare the age-related changes in DNA methylation between the two sexes. In addition, age-related methylation sites were assessed for their associations with mortality.\n\nResultsWe identified more age-related DNA methylation sites (FDR<0.05) in females than in males. Among them, predominantly more sites were hypermethylated in the older as compared with the younger cohorts, a pattern similar to that observed on chromosome 20. Among the age-related sites, 13 CpGs in males and 24 CpGs in females were found significant (FDR<0.05) in all cohorts. Survival analysis showed that there are more age-methylated CpGs that contribute to reduce mortality than those that increase mortality in male but not in female samples.\n\nConclusionThe X-chromosome displays significant age-and sex-dependent methylation patterns which might be differentially associated with mortality in the two sexes.

genetics↗

bioRxiv2019

Risk variant in miR-544a binding site in CCDC170 is associated with osteoporosis

MicroRNAs (miRNAs) play essential roles in regulating bone formation and homeostasis. Genomic variations within miRNA target sites may therefore be important sources of genetic differences in osteoporosis risk. To investigate this possibility, we searched for miRNA recognition sites within genes using the TargetScan, miRNASNP and miRbase databases. In this study, we showed that miR-544a differentially regulated the allele variants of rs6932603 in the CCDC170 3 ' untranslated (3'-UTR). We also showed that miR-544a suppressed osteogenesis and promoted osteoclastogenesis by regulating the expressions of Runx2, Osterix, Alp, Col1a1, Osteopontin (OPN) ,Osteocalcin (OCN) and Osteoprotegerin (OPG). Our results suggest that allele-specific regulation of CCDC170 by miR-544a explains the observed disease risk, and provides a potential therapeutic target for osteoporosis therapy.

genetics↗

bioRxiv2018

Rapid CD4 cell loss is caused by specific CRF01_AE cluster with V3 signatures favoring CXCR4 usage

HIV-1 evolved into various genetic subtypes and circulating recombinant forms (CRFs) in the global epidemic, with the same subtype or CRF usually having similar phenotype. Being one of the worlds major CRFs, CRF01_AE infection was reported to associate with higher prevalence of CXCR4 (X4) viruses and faster CD4 decline. However, the underlying mechanisms remain unclear. We identified eight phylogenetic clusters of CRF01_AE in China and hypothesized that they may have different phenotypes. In the national HIV molecular epidemiology survey, we discovered that people infected by CRF01_AE cluster 4 had significantly lower CD4 count (391 vs. 470, p < 0.0001) and higher prevalence of predicted X4-using viruses (17.1% vs. 4.4%, p < 0.0001) compared to those infected by cluster 5. In a MSM cohort, X4-using viruses were only isolated from sero-convertors infected by cluster 4, which associated with rapid CD4 loss within the first year of infection (141 vs. 440, p = 0.01). Using co-receptor binding model, we identified unique V3 signatures in cluster 4 that favor CXCR4 usage. We demonstrate for the first time that HIV-1 phenotype and pathogenicity can be determined at the phylogenetic cluster level in a single subtype. Since its initial spread to human from chimpanzee in 1930s, HIV-1 remains undergoing rapid evolution in larger and more diverse population. The divergent phenotype evolution of two major CRF01_AE clusters highlights the importance in monitoring the genetic evolution and phenotypic shift of HIV-1 to provide early warning for the appearance of more pathogenic strains such as CRF01_AE cluster 4.\n\nSignificance StatementPast studies on HIV-1 evolution were mainly at the genetic level. This study provides well-matched genotype and phenotype data and demonstrates disparate pathogenicity of two major CRF01_AE clusters. While both CRF01_AE cluster 4 and cluster 5 are mainly spread through the MSM route, cluster 4 but not cluster 5 causes fast CD4 loss, which is associated with the higher prevalence CXCR4 viruses in cluster 4. The higher CXCR4 use tendency in cluster 4 is derived from its unique V3 loop favoring CXCR4 binding. This study for the first time demonstrates disparate HIV-1 phenotype between different phylogenetic clusters. It is important to monitor HIV-1 evolution at both the genotype and phenotype level to identify and control more pathogenic HIV-1 strains.

microbiology↗