Biology subjects

Sheng, Y.

Publications and source records attributed to Sheng, Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Capturing R-loops at base-pair resolution unveils clustered R-loops regulate gene expression in a number-dependent manner

R-loops are prevalent triplex nucleic strands found across various organisms, involved in numerous biological processes. However, the physiological and pathological functions of R-loops remain largely unknown due to a lack of effective and high-resolution detection methods. Here, using nuclease P1, T5 exonuclease, and lambda exonuclease mediated digestion of ssRNA, ssDNA, and dsDNA while preserving RNA:DNA hybrid, we report a method named R-loop identification assisted by nuclease and high-throughput sequencing (RIAN-seq) for genome-wide mapping of R-loops at base-pair resolution. RIAN-seq represents ultra-accuracy in position and size of R-loops and identifies an order of magnitude more R-loops than current methods. Notably, we find the majority of R-loops ranging from 60 bp to 130 bp and reveal previously unresolvable patterns of R-loops aggerated in clusters across the genome. Clustered R-loops at gene promoters recruit zinc finger transcription factors (VEZF1 and SP5) to promote transcription. The number of R-loops within a cluster positively correlates with the diversity of bound transcription factors. Furthermore, clustered R-loops are less susceptible to transcription perturbation as the number of R-loops within clusters increases. Overall, we demonstrate the ability to identify R-loops at unprecedented resolution and facilitate investigating the mechanisms of clustered R-loops in gene regulation in diverse biological processes.

molecular biology↗

bioRxiv2025

A scalable approach to investigating sequence-to-expression prediction from personal genomes

Sequence-to-function (S2F) models hold the promise of evaluating arbitrary DNA sequences, providing a powerful framework for linking genotype to phenotype. Yet, despite strong performance across genomic loci, these models often struggle to capture inter-individual variation in gene expression. To address this, we propose personal genome training--training models to make genotype-specific predictions at a single locus. We introduce SAGE-net, a scalable framework and software package for training and evaluating S2F models using personal genomes. Using SAGE-net, we systematically explore model architectures and training regimes, showing that personal genome training improves gene expression prediction accuracy for held-out individuals. However, performance gains arise primarily from identifying predictive variants, rather than learning a cis-regulatory grammar that generalizes across loci. This lack of generalization persists across a wide range of hyperparameters. In contrast, when applied to DNA methylation (DNAm), personal genome training enables improved generalization to unseen individuals in unseen genomic regions. This suggests that S2F models may more readily capture the sequence-level determinants of inter-individual variation in epigenomic traits. These findings highlight the need for further exploration to unlock the full potential of S2F models in decoding the regulatory grammar of personal genomes. Scalable software and infrastructure development will be critical to this progress.

genomics↗

bioRxiv2025

Bacterial pathogen deploys iminosugar galactosyrin to manipulate plant glycobiology

The extracellular space (apoplast) of plants is an important molecular battleground during infection by many pathogens. We previously found that a plant-secreted {beta}-galactosidase BGAL1 acts in immunity by facilitating the release of immunogenic peptides from bacterial flagellin and that Pseudomonas syringae suppresses this enzyme by producing a small molecule inhibitor called galactosyrin. Here, we elucidated the structure and biosynthesis of galactosyrin and uncovered its multifunctional roles during infection. Structural elucidation by cryo-EM and chemical synthesis revealed that galactosyrin is an iminosugar featuring a unique geminal diol attached to the pyrrolidine moiety that mimics galactose binding to the {beta}-galactosidase active site. Galactosyrin biosynthesis branches off from purine biosynthesis and involves three enzymes of which the first is a reductase that is unique in iminosugar biosynthesis. Besides inhibiting BGAL1 to avoid detection, galactosyrin also changes the glycoproteome and metabolome of the apoplast. The manipulation of host glycobiology may be common to plant-associated bacteria that carry putative iminosugar biosynthesis clusters.

plant biology↗

bioRxiv2025

Food pairing independently associated with cardiometabolic traits beyond dietary patterns across western and eastern populations

Cardiometabolic health is closely linked to diet. Both specific food choices and dietary indices are commonly used to guide cardiometabolic protection strategies. However, the balance between foods may also significantly impact cardiometabolic health. Here, we explore the balance and imbalance in long-term dietary food intake to quantify food pairing patterns (FPs), providing insights beyond conventional dietary indices and single-food intake frequencies. Using data from our GGMP (n = 6,994) and the NHANES (n = 7,350) cohorts, we observed that long-term food pairing patterns are independent of single food intake frequency and dietary indices. We identified 1,759 and 306 cardiometabolic-related long-term food pairing patterns from two cohorts (FDR < 0.05), respectively. Notably, around 80% of these pairing foods not individually associated with cardiometabolic traits, and food pairing pattern associations with cardiometabolic traits at hyper food group level were consistent across Eastern and Western populations. Besides, mediation analysis revealed that 72.7% of long-term food pairing patterns affected cardiometabolic traits through 31 microbial genera, with Clostridiumsensustricto1 playing a predominant role. Moreover, multi-step mediation analysis found that microbes mediated the impact of long-term food pairing patterns on cardiometabolic traits primarily through their metabolic pathways, such as pyruvate fermentation to propanoate and ergothioneine biosynthesis pathways. Our data suggest that balance between dietary foods is broadly associated with cardiometabolic traits by modulating gut microbial functionalities, in contrast to the lower occurrence when considering individual foods in isolation. These results offer a novel perspective for designing personalized dietary strategies beyond present dietary indices to enhance cardiometabolic health.

microbiology↗

bioRxiv2024

The genetic diversity and populational specificity of the human gut virome at single nucleotide resolution

Large-scale characterization of gut viral genomes provides strain-resolved insights into host-microbe interactions. However, existing viral genomes are mainly derived from Western populations, limiting our understanding of global gut viral diversity and functional variations necessary for personalized medicine and addressing regional health disparities. Here, we introduce the Chinese Gut Viral Reference (CGVR) set, consisting of 120,568 viral genomes from 3,234 deeply sequenced fecal samples collected nationwide, covering 72,751 viral species-level clusters (VSCs), nearly 90% of which are absent from current databases. Analysis of single nucleotide variations (SNVs) in 233 globally prevalent VSCs revealed that 18.9% showed significant genetic stratification between Chinese and non-Chinese populations, potentially linked to bacterial infection susceptibility. The predicted bacterial hosts of population-stratified viruses exhibit distinct genetic components associated with health-related functions, including multidrug resistance. Additionally, viral strain diversity at the SNV level correlated with human phenotypic traits, such as age and gastrointestinal issues like constipation. Our analysis also indicates that the human gut bacteriome is specifically shaped by the virome, which mediates associations with human phenotypic traits. This foundational resource underscores the unique genetic makeup of the gut virome across populations and emphasizes the importance of recognizing gut viral genetic heterogeneity for deeper insights into regional health implications.

microbiology↗

bioRxiv2024

Comprehensive analysis of macrophages infected with avirulent and virulent Mycobacterium tuberculosis uncovers distinct immune mechanisms and anti-TB effect of treated exosomes

Tuberculosis (TB) is now the worlds second deadliest infectious killer after COVID-19. Human-macrophages and their secreted exosomes play important roles in combating invading Mtb. However, the panoramic analysis of the underlying immune mechanism for the infected macrophages, package or secretion mechanism, and anti-TB effect of Mtb treated exosomes remain poorly understood. Here we conducted comprehensive analyses of the macrophages infected with avirulent and virulent Mtb (H37Ra & H37Rv) and their secreted exosomes, collected cells and corresponding exosomes for omics and phenotypic analysis. The results showed that avirulent Mtb stimulated robust immune-responses and apoptosis in macrophages to eliminate the invading Mtb; virulent Mtb induced severe necrosis and immune-escape for survival. The HMGB1 signaling pathway and TNFRSF1B plays important roles in the immune escape of virulent Mtb. Interestingly, our results suggest that macrophages kill Mtb in an IFN-{gamma} independent but simulative way, highlighting the central role of IFN signaling pathway in anti-TB immune response. Moreover, we observed selective transport of host and Mtb RNAs from macrophages to exosomes. Notably, "H37Ra-treated exosomes" displayed a higher anti-TB effect than "H37Rv-treated exosomes" due to some enriched pro-inflammation and immune-escape related Mtb proteins in these two exosomes, respectively. Conclusively, our findings shed new light on the immune mechanism of macrophages in response to Mtb infection, offering a new TB-treatment strategy and some promising vaccine candidates.

bioinformatics↗

bioRxiv2024

Cancer Histone Mutations Impact Binding and DNA Repair Processes, Leading to Increased Mutagenesis

Histones are key epigenetic factors for regulating the accessibility and compaction of eukaryotic genomes, affecting the replication, repair, and expression of DNA. Recent studies have demonstrated that histone missense mutations can perturb normal histone function, promoting the development of phenotypically distinguishable cancers. However, most histone mutations observed in cancer patients remain enigmatic in their potential to promote cancer development. To assess the oncogenic potential of histone missense mutations, we have gathered whole-exome sequencing data for the tumors of over 12,000 patients. Overall, histone mutations occurred in about 16% of cancer patients, although specific cancer types showed substantially higher rates. Using a combination of genomic, structural, and biophysical analyses, we found several predominant modes of action, where cancer missense mutations in histones affected acidic patches and protein binding interfaces in a cancer-specific manner and targeted interaction sites with specific DNA repair proteins. Consistent with this finding, we observed a high tumour mutational burden in patients with histone mutations affecting interactions of DNA repair proteins. We also identified potential cancer driver mutations in several histone genes, including histone H4-a highly conserved histone without previously documented driver mutations.

bioinformatics↗

bioRxiv2024

Recommendations for Bioinformatics in Clinical Practice

Next Generation Sequencing (NGS) is increasingly used in clinical diagnostics, largely driven by the success and robustness of Whole Genome Sequencing (WGS). Whereas updated guidelines exist for how to interpret and report on variants that are identified from NGS using bioinformatics pipelines, there is a need for standardised bioinformatics practices for diagnostics to ensure clinical consensus, accuracy, reproducibility and comparability of the results. This article presents consensus recommendations developed by 13 clinical bioinformatics units taking part in the Nordic Alliance for Clinical Genomics (NACG), by expert bioinformaticians working in clinical production. The recommendations are based on clinical practice and focus on analysis types, test and validation, standardisation and accreditation, as well as core competencies and technical management required for clinical bioinformatics operations. Key recommendations include adopting the hg38 genome build as the reference and a standard set of recommended analyses, including the use of multiple tools for structural variant (SV) calling and in-house data sets for filtering recurrent calls. Clinical bioinformatics production should operate under the ISO 15189 standard, utilising off-grid clinical-grade high-performance computing systems, standardised file formats, and strict code version control. Containerized software containers or environment management systems are needed to ensure reproducibility. Pipelines should be rigorously documented and tested for accuracy and reproducibility, minimally covering unit, integration, and end-to-end testing. Standard truth sets such as GIAB and SEQC2 for germline and somatic variant calling, respectively, should be supplemented by recall testing of previously validated clinical cases. Data integrity must be verified using file hashing, and sample identity should be checked via sample fingerprinting and genetically inferred identification markers such as sex and relatedness. Finally, clinical bioinformatics teams should encompass diverse skills, including software development, data management, quality assurance, and domain expertise in human genetics. These recommendations provide a consensus framework for standardising bioinformatics practices across clinical WGS applications and can serve as a practical guide to facilities that are new to large-scale sequencing-based diagnostics, or as a reference for those who already run high-volume clinical production using NGS.

bioinformatics↗

bioRxiv2024

DyNDG: Identifying Leukemia-Related Genes based on the Time-Series Dynamical Network by Integrating Differential Genes

Leukemia is a malignant disease of progressive accumulation characterized by high morbidity and mortality rates, and investigating its disease genes is crucial for understanding its etiology and pathogenesis. Network propagation methods have emerged and been widely employed in disease gene prediction, but most of them focus on static biological networks, which hinders their applicability and effectiveness in the study of progressive diseases. Moreover, there is currently a lack of special algorithms for the identification of leukemia disease genes. Here, we proposed DyNDG, a novel Dynamic Network-based model, which integrates Differentially Expressed Genes to identify leukemia-related genes. Initially, we constructed a time-series dynamic network to model the development trajectory of leukemia. Then, we built a background-temporal multilayer network by integrating both the dynamic network and the static background network, which was initialized with differentially expressed genes at each stage. To quantify the associations between genes and leukemia, we extended a random walk process to the background-temporal multilayer network. The experimental results demonstrate that DyNDG achieves superior accuracy compared to several state-of-the-art methods. Moreover, after excluding housekeeping genes, DyNDG yields a set of promising candidate genes associated with leukemia progression or potential biomarkers, indicating the value of dynamic network information in identifying leukemia-related genes. The implementation of DyNDG is available at https://github.com/CSUBioGroup/DyNDG.

bioinformatics↗

bioRxiv2024

SMAC: identifying DNA N6-methyladenine (6mA) at the single-molecule level using SMRT CCS data

DNA modifications, such as N6-methyladenine (6mA), play important roles in various processes in eukaryotes. Single molecule, real-time (SMRT) sequencing enables the direct detection of DNA modifications without requiring special sample preparation. However, most SMRT-based studies of 6mA rely on ensemble-level consensus by combining multiple reads covering the same genomic position, which misses the single-molecule heterogeneity. While recent methods have aimed at single-molecule level detection of 6mA, limitations in sequencing platforms, resolution, accuracy, and usability restrict their application in comprehensive epigenetic studies. Here, we present SMAC (Single Molecule 6mA analysis of CCS reads), a novel framework for accurately detecting 6mA at the single-molecule level using SMRT CCS data from the Sequel II system. It is an automated method that streamlines the entire workflow by packaging both existing software and built-in script, with support for user-defined parameters to allow easy adaptation for various studies. This algorithm utilizes the statistical distribution characteristics of enzyme kinetic indicators to identify 6mA of each DNA molecule, rather than relying on a fixed cutoff, which significantly improves accuracy at the single-nucleotide and single-molecule level. SMAC is a powerful new tool that enables de novo detection of 6mA and empowers investigation of its functions in modulating physiological processes.

bioinformatics↗

bioRxiv2024

Metabolic Control of Glycosylation Forms for Establishing Glycan-Dependent Protein Interaction Networks

Protein-protein interactions (PPIs) provide essential insights into the complex molecular mechanisms and signaling pathways within cells that regulate development and disease-related phenotypes. However, for membrane proteins, the impact of various forms of glycosylation has often been overlooked in PPI studies. In this study, we introduce a novel approach, glycan-dependent affinity purification followed by mass spectrometry (GAP-MS), to assess variations in PPIs for any glycoprotein of interest under different glycosylation conditions. As a proof of principle, we selected four glycoproteins--BSG, CD44, EGFR, and SLC3A2--as baits to compare their co-purified partners across five metabolically controlled glycan conditions. The findings demonstrate the capability of GAP-MS to identify PPIs influenced by altered glycosylation states, establishing a foundation for systematically exploring the Glycan-Dependent Protein Interactome (GDPI) for other glycoproteins of interest.

biochemistry↗

bioRxiv2024

Genomic diversity and underlying metabolic variations of the human gut microbiome between populations at single nucleotide resolution

BackgroundA comprehensive and representative reference database is crucial for accurate taxonomic and functional profiling of the human gut microbiome in population-level studies. However, with 70% of current microbial reference data derived from Europeans and the Americans, East Asia, especially China, remain underrepresented. MethodsWe constructed the human Gut Microbiome Reference (GMR), comprising 478,588 high-quality microbial genomes from Chinese (247,134) and non-Chinese (231,454) populations. Species-level clustering and protein annotations were performed to characterize microbial diversity and function. We further integrated novel genomes into taxonomic profiling database and validated the improvements using independent cohort data. ResultsThe GMR dataset spans 6,664 species, including 26.4% newly classified species, and encodes over 20 million unique proteins, with 47% lacking known functional annotations. Notably, we observed that 35.35% and 32.46% of species unique to Chinese and non-Chinese populations, respectively. For 2,145 species shared between populations, 74% of 304 species with balanced prevalence between populations exhibited population-specific phylogenetic stratification, involving health relevant functionalities such as antibiotic resistance. Integration of novel genomes into taxonomic improved population-level species profiling by up to 23% and uncovered replicable associations between novel species and host physiological traits. ConclusionsOur study largely expands the compositional and functional landscape of the human gut microbiome, providing a crucial resource for studying the role of gut microbiome for regional health disparities.

genomics↗

bioRxiv2024

Rubisco packaging and stoichiometric composition of a native β-carboxysome

Carboxysomes are anabolic bacterial microcompartments that play an essential role in carbon fixation in cyanobacteria. This self-assembling proteinaceous organelle encapsulates the key CO2-fixing enzymes, Rubisco and carbonic anhydrase, using a polyhedral shell constructed by hundreds of shell protein paralogs. Deciphering the precise arrangement and structural organization of Rubisco enzymes within carboxysomes is crucial for understanding the formation process and overall functionality of carboxysomes. Here, we employed cryo-electron tomography and subtomogram averaging to delineate the three-dimensional packaging of Rubiscos within {beta}-carboxysomes in the freshwater cyanobacterium Synechococcus elongatus PCC7942 that were grown under low light. Our results revealed that Rubiscos are arranged in multiple concentric layers parallel to the shell within the {beta}-carboxysome lumen. We also identified the binding of Rubisco with the scaffolding protein CcmM in {beta}-carboxysomes, which is instrumental for Rubisco encapsulation and {beta}-carboxysome assembly. Using QconCAT-based quantitative mass spectrometry, we further determined the absolute stoichiometric composition of the entire {beta}-carboxysome. This study and recent findings on the {beta}-carboxysome structure provide insights into the assembly principles and structural variation of {beta}-carboxysomes, which will aid in the rational design and repurposing of carboxysome nanostructures for diverse bioengineering applications.

biochemistry↗

bioRxiv2024

The microbiota extends the reproductive lifespan by safeguarding the ovarian reserve

Infertility is a devastating condition affecting one in six people globally. In many cases, the underlying causes are unknown. Emerging evidence suggests that the microbiota influences reproduction, yet the mechanistic link between the microbiota, ovarian function, and length of the fertile lifespan remain unexplored. Here we report that the microbiota controls the length of the reproductive lifespan by maintaining the primordial follicle pool, a process mediated by microbiota-derived short chain fatty acids modulating gene regulatory networks crucial for the survival of the ovarian reserve. Dietary perturbation of the microbiota during a critical developmental window is sufficient to diminish the ovarian reserve, reduce oocyte retrieval, and impair preimplantation embryo viability, mirroring challenges in human fertility treatments. Targeted interventions to restore microbiota improve assisted reproductive outcomes, particularly when implemented early. These findings reveal a novel contribution of host-microbe interactions in mammalian reproduction and demonstrate that the microbiota impacts ovarian function and fertility.

developmental biology↗

bioRxiv2024

Dual-Targeted Microbubbles Promote Apoptosis of M1 Macrophages by Inhibiting Telomerase Activity for Atherosclerosis Therapy

It is known that M1 macrophages are the dominant phenotype in progressive atherosclerosis (AS). Studies have shown that telomerase in macrophages can be activated during the atherosclerosis formation, but how to regulate the telomerase activity of M1 macrophages is the focus of treatment of AS. Herein, we report a dual-targeted microbubbles delivery system encapsulating the telomerase inhibitor BIBR1532 (Ab-MMB1532), designed for precise targeted therapy of AS. The Ab-MMB1532 exhibits excellent biocompatibility and remarkable targeting capability towards M1 macrophages with its targeting advantage notably accentuated under high shear forces. Furthermore, it significantly downregulates telomerase activity. Metabolomics analysis indicates that the decrease in telomerase activity upregulates the expression of aspartic acid, a key protein in the Caspase pathway of apotosis. In vivo, Ab-MMB1532 efficiently targeted and accumulated within AS lesions, leading to significantly delay of the AS progression by inhibiting telomerase activity and promoting apoptosis of M1 macrophages after 4-week treatment. In summary, Ab-MMB1532 provides a new approach for potentially safer and more effective treatment of AS in the future.

bioengineering↗

bioRxiv2024

Cost-effective DNA storage with DNA movable type

In the face of exponential data growth, DNA-based storage offers a promising solution for preserving big-data. However, most existing DNA storage methods, akin to traditional block printing, require costly chemical synthesis for each individual data file, adopting a sequential, one-time-use synthesis approach. To overcome these limitations, we introduce a novel, cost-effective "DNA-Movable-Type Storage" system, inspired by movable type printing. This system utilizes pre-fabricated DNA movable types-short, double-stranded DNA oligonucleotides encoding specific payload, address, and checksum data. These DNA-MTs are enzymatically ligated/assembled into cohesive sequences, termed "DNA movable type blocks", streamlining the assembly process with the automated BISHENG-1 DNA-MT inkjet printer. Using BISHENG-1, we successfully printed, assembled, stored and accurately retrieved 43.7 KB of data files in diverse formats (text, image, audio, and video) in vitro and in vivo, using only 350 DNA-MTs. Notably, each DNA-MT, synthesized once (2 OD), can be used up to 10,000 times, reducing costs to 122 $/MB-outperforming existing DNA storage methods. This innovation circumvents the need to synthesize entire DNA sequences encoding files from scratch, offering significant cost and efficiency advantages. Furthermore, it has considerable untapped potential to advance a robust DNA storage system, better meeting the extensive data storage demands of the big-data era.

bioinformatics↗

bioRxiv2024

Proteasome inhibition induces DNA methylation alteration by attenuating the synthesis of DNA methyltransferase 1 and 3B in colorectal cancer

Proteasome is an essential organelle in guarding cellular protein homeostasis. Here, we report that inhibition of proteasome leads to alterations in DNA methylation patterns in colorectal cancer (CRC) by surpressing the synthesis of DNA methyltransferases (DNMTs). We found that treating CRC cells with proteasome inhibitors results in attenuated translation of DNMT1 and DNMT3B, mediated by the inactivation of AKT and mammalian target of rapamycin (mTOR), which is dependent on the accumulation of p300, an acetyltransferase that inhibits AKT through acetylation modification. Furthermore, we demonstrated that downregulation of DNMT1 and DNMT3B confers protection against proteasome inhibitor treatment, potentially through reprogramming the transcriptome of CRC cells, highlighting the significant role of DNMTs in response to disruptions in protein homeostasis. Interestingly, the proteasome inhibitor-induced downregulation of DNMT1 and DNMT3B appears to be CRC specific, notwithstanding the underlying mechanism remains unclear. Altogether, our findings reveal an epigenetic effect of proteasome on DNA methylation in CRC through its regulation of DNA methyltransferase synthesis.

cancer biology↗

bioRxiv2024

Asymmetric binding of coactivator SRC1 to FXR-RXR and allosteric communication within the complex

Farnesoid X receptor (FXR) is a promising target for treatment of metabolic associated fatty liver disease (MAFLD). In this study, we employed an integrative approach to investigate the interaction between FXR-RXR-hSHP-1 complex and the entire coactivator SRC1-NRID (nuclear receptor interaction domain). We constructed a multi-domain model of FXR120-RXR98-hSHP-1, highlighting the interface between FXR-DBD and LBD. Using HDX-MS, XL-MS, and biochemical assays, we revealed the allosteric communications in FXR-RXR-hSHP-1 upon agonist and DNA binding. We then demonstrated that SRC1 binds only to the coactivator binding surface of FXR within the FXR-RXR heterodimer, with the NR-box2 and NR-box3 of SRC1 as the key binding motifs. Our findings, which provide the first model of SRC1-NRID in complex with FXR-RXR-hSHP-1, shed light on the molecular mechanism through which the coactivator asymmetrically interacts with nuclear receptors and provide structural basis for further understanding the function of FXR and its implications in diseases.

biophysics↗