Biology subjects

Lin, J.

Publications and source records attributed to Lin, J..

At least 181 records · Page 10Linked to original sources

bioRxiv2024

UniPTM: Multiple PTM site prediction on full-length protein sequence

AbstractPost-translational modifications (PTMs) enrich the functional diversity of proteins by attaching chemical groups to the side chains of amino acids. In recent years, a myr-iad of AI models have been proposed to predict many specific types of PTMs. However, those models typically adopt the sliding window approach to extract short and equal-length protein fragments from full-length proteins for model training. Unfortunately, such a subtle step results in the loss of long-range information from distal amino acids, which may impact the PTM formation process. In this study, we introduce UniPTM, a window-free model designed to train and test on natural and full-length protein sequences, enabling the prediction of multiple types of PTMs in a holistic manner. Moreover, we established PTMseq, the first comprehensive dataset of full-length pro-tein sequences with annotated PTMs, to train and validate our model. UniPTM has undergone extensive validations and significantly outperforms existing models, eluci-dating the influence of protein sequence completeness on PTM. Consequently, UniPTM offers interpretable and biologically meaningful predictions, enhancing our understand-ing of protein functionally and regulation. The source code and PTMseq dataset for UniPTM are available at https://www.github.com/TransPTM/UniPTM.

bioinformatics↗

bioRxiv2024

A familial, telomere-to-telomere reference for human de novo mutation and recombination from a four-generation pedigree

Using five complementary short- and long-read sequencing technologies, we phased and assembled >95% of each diploid human genome in a four-generation, 28-member family (CEPH 1463) allowing us to systematically assess de novo mutations (DNMs) and recombination. From this family, we estimate an average of 192 DNMs per generation, including 75.5 de novo single-nucleotide variants (SNVs), 7.4 non-tandem repeat indels, 79.6 de novo indels or structural variants (SVs) originating from tandem repeats, 7.7 centromeric de novo SVs and SNVs, and 12.4 de novo Y chromosome events per generation. STRs and VNTRs are the most mutable with 32 loci exhibiting recurrent mutation through the generations. We accurately assemble 288 centromeres and six Y chromosomes across the generations, documenting de novo SVs, and demonstrate that the DNM rate varies by an order of magnitude depending on repeat content, length, and sequence identity. We show a strong paternal bias (75-81%) for all forms of germline DNM, yet we estimate that 17% of de novo SNVs are postzygotic in origin with no paternal bias. We place all this variation in the context of a high-resolution recombination map ([~]3.5 kbp breakpoint resolution). We observe a strong maternal recombination bias (1.36 maternal:paternal ratio) with a consistent reduction in the number of crossovers with increasing paternal (r=0.85) and maternal (r=0.65) age. However, we observe no correlation between meiotic crossover locations and de novo SVs, arguing against non-allelic homologous recombination as a predominant mechanism. The use of multiple orthogonal technologies, near-telomere-to-telomere phased genome assemblies, and a multi-generation family to assess transmission has created the most comprehensive, publicly available "truth set" of all classes of genomic variants. The resource can be used to test and benchmark new algorithms and technologies to understand the most fundamental processes underlying human genetic variation.

genomics↗

bioRxiv2024

EPInformer: A Scalable Deep Learning Framework for Gene Expression Prediction by Integrating Promoter-enhancer Sequences with Multimodal Epigenomic Data

Transcriptional regulation, critical for cellular differentiation and adaptation to environmental changes, involves coordinated interactions among DNA sequences, regulatory proteins, and chromatin architecture. Despite extensive data from consortia like ENCODE, understanding the dynamics of cis-regulatory elements (CREs) in gene expression remains challenging. Deep learning is a powerful tool for learning gene expression and epigenomic signals from DNA sequences, exhibiting superior performance compared to conventional machine learning approaches. However, even the most advanced deep learning-based methods may fall short in capturing the regulatory effects of distal elements such as enhancers, limiting their predictive accuracy. In addition, these methods may require significant resources to train or to adapt to newly generated data. To address these challenges, we present EPInformer, a scalable deep-learning framework for predicting gene expression by integrating promoter-enhancer interactions with their sequences, epigenomic signals, and chromatin contacts. Our model outperforms existing gene expression prediction models in rigorous cross-chromosome validation, accurately recapitulates enhancer-gene interactions validated by CRISPR perturbation experiments, and identifies crucial transcription factor motifs within regulatory sequences. EPInformer is available as open-source software at https://github.com/pinellolab/EPInformer.

genomics↗

bioRxiv2024

Complete sequencing of ape genomes

We present haplotype-resolved reference genomes and comparative analyses of six ape species, namely: chimpanzee, bonobo, gorilla, Bornean orangutan, Sumatran orangutan, and siamang. We achieve chromosome-level contiguity with unparalleled sequence accuracy (<1 error in 500,000 base pairs), completely sequencing 215 gapless chromosomes telomere-to-telomere. We resolve challenging regions, such as the major histocompatibility complex and immunoglobulin loci, providing more in-depth evolutionary insights. Comparative analyses, including human, allow us to investigate the evolution and diversity of regions previously uncharacterized or incompletely studied without bias from mapping to the human reference. This includes newly minted gene families within lineage-specific segmental duplications, centromeric DNA, acrocentric chromosomes, and subterminal heterochromatin. This resource should serve as a definitive baseline for all future evolutionary studies of humans and our closest living ape relatives.

genomics↗

bioRxiv2024

Scalable assessment of genome editing off-targets associated with genetic variants

Genome editing with RNA-guided DNA binding factors carries risk of off-target editing at homologous sequences. Genetic variants may introduce sequence changes that increase homology to a genome editing target, thereby increasing risk of off-target editing. Conventional methods to verify candidate off-targets rely on access to cells with genomic DNA carrying these sequences. However, for candidate off-targets associated with genetic variants, appropriate cells for experimental verification may not be available. Here we develop a method, Assessment By Stand-in Off-target LentiViral Ensemble with sequencing (ABSOLVE-seq), to integrate a set of candidate off-target sequences along with unique molecular identifiers (UMIs) in genomes of primary cells followed by clinically relevant gene editor delivery. Gene editing of dozens of candidate off-target sequences may be evaluated in a single experiment with high sensitivity, precision, and power. We provide an open-source pipeline to analyze sequencing data. This approach enables experimental assessment of the influence of human genetic diversity on specificity evaluation during gene editing therapy development.

genomics↗

bioRxiv2024

Many erroneous noncoding transcripts in cancer cells can highly specifically regulate cancer-related genes and pathways

Transcription and splicing errors in cancer cells generate erroneous transcripts. Since erroneous transcripts are degraded by the nonsense-mediated mRNA decay (NMD) pathway, whether they are junk or could be functional has been overlooked and understudied. We addressed this question by first performing a pan-cancer analysis and identified substantial erroneous noncoding transcripts (ENT) in cancers. Given that RNA/DNA binding domains (DBD) were predicted in ENTs, we deleted predicted DBDs in multiple ENTs in multiple cell lines, with RNA-sequencing and cell experiments before and after DBD deletion. DBD deletion caused significantly changed expression of ENTs target genes (whose promoter regions contain ENTs DNA binding sites, DBS) and changed cell migration and proliferation ability, indicating that many ENTs can transcriptionally regulate genes. Tightly coupled data analysis and experiments reveal that ENTs functions are highly cancer- and cellular-context specific, making ENTs a new class of safe and specific targets for noncoding RNA-based cancer therapeutics.

genomics↗

bioRxiv2024

Synergically enhanced anti-tumor immunity of in vivo CAR by circRNA vaccine boosting

Chimeric Antigen Receptor (CAR) T cell therapy has shown promise in treating hematologic malignancies. However, it is limited to individualized cell therapy and faces challenges, including high costs, extended preparation time, and limited efficacy against solid tumors. Here, we generated circular RNAs (circRNAs) encoding Chimeric Antigen Receptor (CAR) transmembrane proteins, referred to as circRNACAR, which mediated remarkable tumor killing in both T cells and macrophages. In addition, macrophages exhibited efficient phagocytosis of tumor cells and pro-inflammatory polarization induced by circRNACAR in vitro. We demonstrated that circRNACAR, delivered with immunocyte-tropic lipid nanoparticles (LNPs), significantly inhibited tumor growth, improved survival rates and induced a pro-inflammatory tumor microenvironment in mice. Importantly, the combination of circRNAAnti-HER2-CAR and circRNA-based cancer vaccines encoding the corresponding transmembrane HER2 antigen, termed circRNAHER2, exhibited synergistically enhanced anti-tumor activity. This proof-of-concept study demonstrated that the combination of circRNA-based in vivo CAR and vaccines, termed in vivo CAR-VAC, holds the potential to become an upgraded off-the-shelf immunotherapy.

immunology↗

bioRxiv2024

Discovery of the missing cytochrome P450 monooxygenase cyclases that conclude glyceollin biosynthesis in soybean

Glyceollins are isoflavonoid-derived metabolites produced by soybean that hold great promise in improving human and animal health due to their antimicrobial, and other medicinal properties. They play important roles in agriculture by defending soybean against one of its most destructive pathogens, Phytophthora sojae. Longstanding research efforts have focused on improving accessibility to glyceollins, yet chemical synthesis remains uneconomical. The fact that some of the key genes involved in the final step of glyceollin biosynthesis have not been identified, engineering the accumulation of these important compounds in microbes is not yet possible. Although the activity of a P450 cyclase was inferred to catalyze the final committed step in glyceollin biosynthesis forty years ago, the enzyme in question has never been conclusively identified. This study reports, for the first time, the identification of three cytochrome P450 monooxygenase cyclases that catalyze the final steps of glyceollin biosynthesis. Utilizing P. sojae-soybean transcriptome data, along with genome mining tools and co-expression network analysis, we have identified 16 candidate glyceollin synthases (GmGS). Heterologous expression of these candidate genes in yeast, coupled with in vitro enzyme assays, enabled us to discover three enzymes capable of producing two glyceollin isomers. GmGS11A and GmGS11B catalyzed the conversion of glyceollidin to glyceollin I, whereas GmGS13A converted glyceocarpin to glyceollin III. The functionality of these candidates was further confirmed in planta through gene silencing and overexpression in soybean hairy roots. This groundbreaking study not only contributes to the understanding of glyceollin biosynthesis, but also demonstrates a new synthetic biology strategy that could potentially be scaled up to produce valuable molecules for crop and disease management.

biochemistry↗

bioRxiv2024

Visualizing the translation landscape in human cells at high resolution

Obtaining comprehensive structural descriptions of macromolecules within their natural cellular context holds immense potential for understanding fundamental biology and improving health. Here, we present the landscape of protein synthesis inside human cells in unprecedented detail obtained using an approach which combines automated cryo-focused ion beam (FIB) milling and in situ single-particle cryo-electron microscopy (cryo-EM). With this in situ cryo-EM approach we resolved a 2.19 [A] consensus structure of the human 80S ribosome and unveiled its 21 distinct functional states, nearly all higher than 3 [A] resolution. In contrast to in vitro studies, we identified protein factors, including SERBP1, EDF1 and NAC/3, not enriched on purified ribosomes. Most strikingly, we observed that SERBP1 binds to the ribosome in almost all translating and non-translating states to bridge the 60S and 40S ribosomal subunits. These newly observed binding sites suggest that SERBP1 may serve an important regulatory role in translation. We also uncovered a detailed interface between adjacent translating ribosomes which can form the helical polysome structure. Finally, we resolved high-resolution structures from cells treated with homoharringtonine and cycloheximide, and identified numerous polyamines bound to the ribosome, including a spermidine that interacts with cycloheximide bound at the E site of the ribosome, underscoring the importance of high-resolution in situ studies in the complex native environment. Collectively, our work represents a significant advancement in detailed structural studies within cellular contexts.

molecular biology↗

bioRxiv2024

Physical constraints and biological regulations underlie universal osmoresponses

Microorganisms constantly transition between environments with dramatically different external osmolarities. However, theories of microbial osmoresponse integrating physical constraints and biological regulations are lacking. Here, we propose such a theory, utilizing the separation of timescales for passive responses and active regulations. We demonstrate that regulations of osmolyte production and cell-wall synthesis assist cells in coping with intracellular crowding effects and adapting to a broad range of external osmolarity. Furthermore, we predict a threshold value above which cells cannot grow, ubiquitous across bacteria and yeast. Intriguingly, the theory predicts a dramatic speedup of cell growth after an abrupt decrease in external osmolarity due to cell-wall synthesis regulation. Our theory rationalizes the unusually fast growth observed in fission yeast after an oscillatory osmotic perturbation, and the predicted growth rate peaks match quantitatively with experimental measurements. Our study reveals the physical basis of osmoresponse, yielding farreaching implications for microbial physiology.

biophysics↗

bioRxiv2024

Unraveling Lineage Roadmaps and Cell Fate Determinants to Postnatal Neural Stem Cells and Ependymal cells in the Developing Ventricular Zone

The ventricular zone (VZ) is made up of adult neural stem cells (NSCs) and multi-ciliated ependymal cells (EPCs). Both NSCs and EPCs are derived from radial glial cells (RGCs). To date, the transcriptomic dynamics and the molecular mechanisms guiding the cell fate commitment during the differentiation remain poorly understood. In this study, we analysed the developing VZ at the single-cell resolution and identified three distinct cellular states of RGCs: bipotent glial progenitor cells (bGPCs), neonatal NSC-neuroblasts (nNSC-NBs) and neonatal EPCs (nEPCs). The differentiation from bGPCs to nNSC-NBs and nEPCs forms a continuous bifurcating trajectory. Further molecular analysis along the NSC branch unveiled a novel intermediate state of cells expressing oligodendrocyte precursor cell (OPC) and neuroblast (NB) marker genes. Several transcription factors (TFs) were proved to be essential for the EPC-lineage differentiation, with TFEB emerging as a key regulator dictating the bGPC fate. The activation of TFEB promoted differentiation towards NSC-NBs while restrained the trajectory towards EPCs. Our findings offer detailed insights into further understanding VZ development and lay the groundwork for investigating potential therapeutic strategies against VZ-related disorders, such as hydrocephalus and neurodegenerative diseases (NDDs).

genomics↗

bioRxiv2024

Occurrence, risk assessment of antibiotics and antimicrobial resistance in Escherichia coli in typical rivers of Sichuan

Worldwide interest has been generated by the presence and distribution of antibiotics and antibiotic resistance genes (ARGs) in rivers. However, there was a dearth of research on the contamination of Sichuan provinces typical rivers with antibiotics. In this study, the residual level of antibiotics in 42 national/provincial sites of 9 rivers was analyzed by UPLC-MS/MS, the ecological risk level was evaluated using risk assessment method, and the drug resistance of E. coli in water was evaluated by Kirby-Bauer method. Redundancy analysis demonstrated how residual antibiotics affect the structure of the microbial community in the Minjiang River basin (RDA). Nine rivers all contained antibiotics. Among them, the MinJiang, TuoJiang, and JiaLingJiang rivers were severely contaminated with antibiotic concentrations ranging from 0.29 to 2233.71 ng/L. The Sichuan Basins antibiotic pollution level was significantly higher when compared to other Sichuan zones, which was consistent with the regions high population density. Additionally, it was discovered that 9.77% of the E. coli isolated from 9 rivers had antibiotic resistance, and more than 5.8% of them had multidrug resistance. Moreover, Norfloxacin, amoxicillin, ampicillin, and tetracycline were the main risk factors for high ecological risk in 26 of the 42 monitoring sites. Additionally, there is a strong correlation between the microbial community change and residual antibiotic. These results offered some reference information regarding the distribution of antibiotics and ARGs in typical rivers in the Chinese province of Sichuan, and this study showed that more attention needs to be paid to antibiotic pollution in Sichuans typical rivers.

microbiology↗

bioRxiv2024

Biochemical characterization of extended-spectrum β-lactamases from Akkermansia genus

Akkermansia muciniphila, a member of the Verrucomicrobiota phylum, is recognized as a key gut microbe and has emerged as a potential next-generation probiotic. Assessment of antibiotic resistance in probiotics is a prerequisite for their therapeutic application, while very few is known in Akkermansia species. Firstly, we screened eight representative class A {beta}-lactamases (36.90%-41.30% identity with known {beta}-lactamases) from the Akkermansia species, which could increase the minimum inhibitory concentration (MIC) of Escherichia coli to{beta}-lactams. Secondly, four{beta}-lactamases were purified and identified as extended-spectrum {beta}-lactamase because they exhibited hydrolase activity against 19 {beta}-lactam antibiotics from penicillin, cephalosporins, and monobactam classes. Based on sequence alignment, three-dimensional structure, and binding pocket information, we hypothesized and validated that serine at 51 position was catalytic amino acid. Thirdly, the genomic context analysis revealed the absence of mobile genetic elements or other antibiotic resistance genes surrounding {beta}-lactamase genes, suggesting that the {beta}-lactamases from Akkermansia species may not be transferable. The finding and biochemical characterization of {beta}-lactamase from Akkermansia species provide a foundational basis for the safety evaluation of Akkermansia species as probiotics.

microbiology↗

bioRxiv2024

The Role of ADGRA3 in Adipose Thermogenesis: A Potential Therapeutic Target for Obesity

The induction of adipose thermogenesis plays a critical role in maintaining body temperature and improving metabolic homeostasis to combat obesity. {beta}3-adrenoceptor ({beta}3-AR) is widely recognized as a canonical {beta}-adrenergic G protein-coupled receptor (GPCR) that plays a crucial role in mediating adipose thermogenesis in mice. Nonetheless, the limited expression of {beta}3-AR in human adipocytes restricts its clinical application. The objective of this study was to identify a GPCR that is highly expressed in human adipocytes and to explore its potential involvement in adipose thermogenesis. Our research findings have demonstrated that the adhesion G protein-coupled receptor A3 (ADGRA3), an orphan GPCR, plays a significant role in adipose thermogenesis through its constitutively active effects. ADGRA3 exhibited high expression levels in human adipocytes and mouse brown fat. Furthermore, the knockdown of Adgra3 resulted in an exacerbated obese phenotype and a reduction in the expression of thermogenic markers. Conversely, Adgra3 overexpression activated the adipose thermogenic program and improved metabolic homeostasis without an exogenous ligand supplementation. We found that ADGRA3 facilitates the biogenesis of beige adipocytes through the Gs-PKA-CREB axis. Moreover, hesperetin was identified as a potential agonist of ADGRA3, capable of inducing adipocyte browning and ameliorating insulin resistance. In conclusion, our study demonstrated that the overexpression of constitutively active ADGRA3 or the activation of ADGRA3 by hesperetin can induce adipocyte browning by Gs-PKA-CREB axis. These findings indicate that the utilization of hesperetin and the selectively overexpression of ADGRA3 in adipose tissue could serve as promising therapeutic strategies in the fight against obesity.

cell biology↗

bioRxiv2024

An Updated Structure of Oxybutynin Hydrochloride

Oxybutynin (Ditropan), a widely distributed muscarinic antagonist for treating the overactive bladder, has been awaiting a definitive crystal structure for nearly 50 years due to the sample and technique limitations. Past reports used powder X-ray diffraction (PCRD) to shed light on the possible packing of the molecule however a 3D structure remained elusive. Here we used Microcrystal Electron Diffraction (MicroED) to successfully unveil the 3D structure of oxybutynin hydrochloride. We identify several inconsistencies between the reported PXRD analyses and the experimental structure. Using the improved model, molecular docking was applied to investigate the binding mechanism between M3 muscarinic receptor (M3R) and (R)-oxybutynin, revealing essential contacts/residues and conformational changes within the protein pocket. A possible universal conformation was proposed for M3R antagonists, which is valuable for future drug development and optimization. This study underscores the immense potential of MicroED as a complementary technique for elucidating the unknown pharmaceutical crystal structures, as well as for the protein-drug interactions.

biochemistry↗

bioRxiv2024

Negative regulation of Activation-Induced Cytidine Deaminase gene transcription in developing B cells by a PU.1-interacting intronic region

Activation-induced cytidine deaminase (AID, encoded by Aicda) plays a key role in somatic hypermutation and class switch recombination in germinal center B cells. However, off-target effects of AID are implicated in human leukemia and lymphoma. A mouse model of precursor B cell acute lymphoblastic leukemia driven by deletion of the related transcription factors PU.1 and Spi-B revealed C->T transition mutations compatible with being induced by AID. Therefore, we hypothesized that PU.1 negatively regulates Aicda during B cell development. Aicda mRNA transcript levels were increased in leukemia cells and preleukemic bone marrow pre-B cells lacking PU.1 and/or Spi-B, relative to wild type cells. Using chromatin immunoprecipitation, PU.1 was found to interact with a negative regulatory region (R2-1) within the first intron of Aicda. CRISPR-Cas9-induced mutagenesis of R2-1 in cultured pre-B cells resulted in upregulation of Aicda in response to lipopolysaccharide stimulation. Mutation of the PU.1 interaction site and neighboring sequences resulted in reduced repressive ability of R2-1 in transient transfection analysis followed by luciferase assays. These results show that a PU.1-interacting intronic region negatively regulates Aicda transcription in developing B cells.

immunology↗

bioRxiv2024

Design principles to tailor Hsp104 therapeutics

The hexameric AAA+ disaggregase, Hsp104, collaborates with Hsp70 and Hsp40 via its autoregulatory middle domain (MD) to solubilize aggregated protein conformers. However, how ATP- or ADP-specific MD configurations regulate Hsp104 hexamers remains poorly understood. Here, we define an ATP-specific network of interprotomer contacts between nucleotide-binding domain 1 (NBD1) and MD helix L1, which tunes Hsp70 collaboration. Manipulating this network can: (a) reduce Hsp70 collaboration without enhancing activity; (b) generate Hsp104 hypomorphs that collaborate selectively with class B Hsp40s; (c) produce Hsp70-independent potentiated variants; or (d) create species barriers between Hsp104 and Hsp70. Conversely, ADP-specific intraprotomer contacts between MD helix L2 and NBD1 restrict activity, and their perturbation frequently potentiates Hsp104. Importantly, adjusting the NBD1:MD helix L1 rheostat via rational design enables finely tuned collaboration with Hsp70 to safely potentiate Hsp104, minimize off- target toxicity, and counteract FUS proteinopathy in human cells. Thus, we establish important design principles to tailor Hsp104 therapeutics. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/591398v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1520616org.highwire.dtl.DTLVardef@db3f5org.highwire.dtl.DTLVardef@1a1ae5eorg.highwire.dtl.DTLVardef@1beab7e_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

InstructPLM: Aligning Protein Language Models to Follow Protein Structure Instructions

Large language models are renowned for their efficacy in capturing intricate patterns, including co-evolutionary relationships, and underlying protein languages. However, current methodologies often fall short in illustrating the emergence of genomic insertions, duplications, and insertion/deletions (indels), which account for approximately 14% of human pathogenic mutations. Given that structure dictates function, mutated proteins with similar structures are more likely to persist throughout biological evolution. Motivated by this, we leverage crossmodality alignment and instruct fine-tuning techniques inspired by large language models to align a generative protein language model with protein structure instructions. Specifically, we present a method for generating variable-length and diverse proteins to explore and simulate the complex evolution of life, thereby expanding the repertoire of options for protein engineering. Our proposed protein LM-based approach, InstructPLM, demonstrates significant performance enhancements both in silico and in vitro. On native protein backbones, it achieves a perplexity of 2.68 and a sequence recovery rate of 57.51, surpassing Protein-MPNN by 39.2% and 25.1%, respectively. Furthermore, we validate the efficacy of our model by redesigning PETase and L-MDH. For PETase, all fifteen designed variable-length PETase exhibit depolymerization activity, with eleven surpassing the activity levels of the wild type. Regarding L-MDH, an enzyme lacking an experimentally determined structure, InstructPLM is able to design functional enzymes with an AF2-predicted structure. Code and model weights of InstructPLM are publicly available*.

bioinformatics↗