Biology subjects

Peng, S.

Publications and source records attributed to Peng, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Identification and genomic characterization of a novel bisegmented coronavirus in the lesser panda

Coronaviruses (CoVs) are enveloped positive-sense single-stranded RNA viruses and are renowned for their capacity to infect a diverse range of animals, including humans. In this study, we report the identification and characterization of a novel bisegmented coronavirus, designated LpCoV, from a dead lesser panda, which exhibited severe clinical manifestations and lesions in multiple organs. The LpCoV represents the first documented coronavirus with a unique bisegmented genome while maintaining the typical coronavirus morphology. One genomic segment encodes the ORF1ab polyprotein, while the other segment encodes the spike and nucleocapsid proteins, notably lacking the envelope (E) and membrane (M) genes. The pairwise patristic distances of the five concatenated domains in the replicase region (3CLpro, NiRAN, RdRP, ZBD, and HEL1) between LpCoV and -{delta} coronaviruses range from 1.19 to 1.70. Based on the classification criteria established by the International Committee on Taxonomy of Viruses (ICTV), LpCoV is proposed to constitute a new genus within the Coronaviridae family. An epidemiological investigation identified five LpCoV-like viruses in lesser pandas from two different provinces (Sichuan and Jiangsu) indicating the long-term circulation and expansion of bisegmented coronaviruses in wildlife. These findings highlight the imperative for comprehensive viral surveillance in wildlife, which is essential for understanding and mitigating the risk of animal diseases and zoonotic spillover.

microbiology↗

bioRxiv2024

Identification of a new ORF3a-E fusion subgenomic RNA of SARS-CoV-2 and its biological features in the infection process

Subgenomic RNAs (sgRNAs) are discontinuous transcription products of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that are involved in viral gene expression and replication, but their exact functions are still being studied. Here, we report the identification of a new type of sgRNA, the fusion ORF3a-E-sgRNA, involved in the infection process of SARS-CoV-2. This sgRNA codes both ORF3a and E and can be detected throughout the viral life cycle in SARS-CoV-2-infected cells with high copy numbers. ORF3a-E-sgRNA guides more ORF3a translation and promotes the expression of cellular ribosomal protein S3 (RPS3) and the binding of eukaryotic translation initiation factor 4E (eIF4E). Single-cell sequencing of a SARS-CoV-2-infected human bronchial epithelial cell line (16HBE) revealed that maintenance of this stable translational environment by ORF3a-E-sgRNA is important for the SARS-CoV-2 assembly and release capabilities and is also beneficial for viral evasion of host innate immunity. More importantly, the transcription level of ORF3a-E-sgRNA contributes to differences in infection processes between the Wuhan strain and XBB strain of SARS-CoV-2.

microbiology↗

bioRxiv2024

Evolution of the Spatial transcriptomic landscape during the progression of high-grade pancreatic intraductal papillary mucinous neoplasms to invasive cancer

Intraductal papillary mucinous neoplasms (IPMN) is one of the known precancerous lesions. Patients prognosis is aggravated as IPMN transforms into invasive Pancreatic Ductal Adenocarcinoma (PDAC). The molecular mechanisms underlying this progression lack effective experimental models and urgently need to be elaborated. We performed spatial transcriptomics (ST) on fresh tissue samples from the same patient including normal pancreas, high-grade IPMN, and invasive PDAC, and described the step-by-step development of transcriptional landscape including clone evolution and adjacent TME feature variation. Our findings identified the master transcript factors and critical signaling pathways promoting IPMN progression to invasive PDAC. Additionally, both IPMN and PDAC harbored the ELF3, MYC, and KLF4 amplification. The Spatial CNV profile demonstrated significant heterogeneity among PDAC in their spatial distribution compared to IPMN, with seven distinct subclones showing diverse functions, such as hypoxia, oxidative phosphorylation, and epithelial-mesenchymal Transition. We observed a marked shift in the immune landscape, with the depletion of CD4+ T-cells and dendritic cells and an increase in immune-suppressive M2 macrophages in invasive PDAC, indicating a transition to an immune-evasive microenvironment. Additionally, cancer-associated fibroblasts (CAFs), particularly myofibroblastic CAFs, were enriched adjacent to invasive PDAC, suggesting their active role in tumor progression. By leveraging spatial transcriptomic analysis, our study provides comprehensive insights into the intricate molecular landscape that underlies the progression of IPMNs to invasive PDAC. These findings not only enhance our understanding of this complex process but also offer valuable knowledge for early diagnosis and intervention. HighlightsO_LISpatial CNV analysis reveals clonal evolution and distinct subclones in PDAC. C_LIO_LIKey drivers like ELF3, MYC, and KLF4 are amplified in both IPMN and invasive PDAC. C_LIO_LIImmune landscape shifts from pro-inflammatory in IPMN to immune-evasive in PDAC. C_LIO_LIEnrichment of myofibroblastic CAFs suggests their role in tumor progression C_LI

cancer biology↗

bioRxiv2024

Interpretable improving prediction performance of general protein language model by domain-adaptive pretraining on DNA-binding protein

DNA-protein interactions exert the fundamental structure of many pivotal biological processes, such as DNA replication, transcription, and gene regulation. However, accurate and efficient computational methods for identifying these interactions are still lacking. In this study, we propose a novel method ESM-DBP through refining the DNA-binding protein (DBP) sequence repertory and domain-adaptive pretraining based the protein language model (PLM). Our method considers the lack of exploration of general PLM for DBP domain-specific knowledge, so we screened out 170,264 DBPs from the UniProtKB database to construct the model that more suitable for learning crucial characteristics of DBP. The evaluation of ESM-DBP is systematically performed in four different DBP-related downstream prediction tasks, i.e., DNA-binding protein, DNA-binding residue, transcription factor, and DNA-binding Cys2His2 zinc-finger predictions. Experimental results show that ESM-DBP provides a better feature representation of DBP compared to the original PLM, resulting in improved prediction performance and outperforming other state-of-the-art prediction methods. In addition, ESM-DBP incorporates the integrated gradient algorithm for interpretable analysis, which usually ignored in the previous methods. It reveals that ESM-DBP possesses high sensitivity to the key decisive DNA-binding domains. Moreover, we find that ESM-DBP can still perform well even for those DBPs with only a few similar homologous sequences, and this generalization performs better than the original PLM. The data and standalone program of ESM-DBP are freely accessible at https://github.com/pengsl-lab/ESM-DBP.

bioinformatics↗

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↗

bioRxiv2024

GABAAR-PPT1 palmitoylation homeostasis controls synaptic transmission and circuitry oscillation in CLN1 disease

CLN1 disease, also called infantile neuronal ceroid lipofuscinosis, is a fatal neurodegenerative disease caused by mutations in the CLN1 gene encoding palmitoyl protein thioesterase 1 (PPT1). To identify depalmitoylation substrate of PPT1 is crucial to understand CLN1 disease. In this study, we found that PPT1 depalmitoylates GABAAR 1 subunit at Cystein-260, while binding to Cystein-165 and -179. Mutations of PPT1 or its GABAAR 1 subunit binding site result in enhanced inhibitory synaptic transmission, strengthened and oscillation but disrupted phase coupling in CA1 region and impaired learning and memory in 1- to 2-months-old PPT1-deficient and Gabra1em1 mice. Our study highlights the critical role of PPT1 in maintaining GABAAR palmitoylation homeostasis and reveals a previously unknown molecular pathway in PPT1 induced diseases.

neuroscience↗

bioRxiv2024

Human brain aging heterogeneity observed from multi-region omics data reveals a subtype closely related to Alzheimer's disease

INTRODUCTION: The interconnection between brain aging and Alzheimers disease (AD) remain to be elucidated. METHODS: We investigated multi-omics (transcriptomics and proteomics) data from multiple brain regions (i.e., the hippocampus (HIPP), prefrontal cortex (PFC), and cerebellum (CRBL)) in cognitively normal individuals. RESULTS: We found that brain samples could be divided into ADL (AD-like) and NL (normal) subtypes which were correlated across brain regions. The differentially expressed genes in the ADL samples highly overlapped with AD gene signatures and the changes were consistent across brain regions (PFC and HIPP) in the multi-omics data. Intriguingly, the ADL subtype in PFC showed more differentially expressed genes than other brain regions, which could be explained by the baseline gene expression differences in the PFC NL samples. DISCUSSION: We conclude that brain aging heterogeneity widely exists, and our findings corroborate with the hypothesis that AD-related changes occur decades before the clinical manifestation of cognitive impairment in a sub-population.

neuroscience↗

bioRxiv2024

The Role of Rhizosphere Microorganisms and CNPS Genes in Shaping Nutritional Traits of Capsicum

The rhizosphere microbiota plays crucial roles in biogeochemical cycling and primary production. However, there is a lack of research exploring the complex relationships between microbiota and their functional traits in pepper rhizospheres, as well as their impact on nutrient cycling processes. Here, we investigated the effects of pepper species on the rhizomicrobiota and functional genes (C/N/P/S) on nutrient absorptions and accumulations in pepper organs. The results revealed that Pepper YZ/BE had higher N content in all compartments, which could be attributed to the presence of enriched N-metabolic microbes (Gaiellales/Leifsonia) and higher expression of N availability-promoting genes (ureC/amoA2/nxrA/napA) in rhizospheres. Additionally, we utilized co-occurrence network analysis and partial least squares path modeling (PLS-PM) to understand the interactions among the variables. The bacterial network exhibited more associations than the fungal network, and the abundance of certain modules positively correlated with the expression of CNPS genes, which thus significantly influenced pepper nutrient content. The PLS-PM analysis demonstrated that taxa abundance in network modules, functional genes, and rhizospheric soil properties collectively explained 92% of the variance in pepper nutrient content. Overall, this study provides valuable experimental and theoretical insights into the effects of rhizosphere microorganisms and CNPS genes on the nutritional traits of Capsicum. HighlightThe rizho-bacterial community harbored more robust relationships than the fungal ones, which formed the functional clusters highly linking to the below- and aboveground nutrient properties of pepper species.

microbiology↗

bioRxiv2024

Inferring strain-level mutational drivers of phage-bacteria interaction phenotypes

The enormous diversity of bacteriophages and their bacterial hosts presents a significant challenge to predict which phages infect a focal set of bacteria. Infection is largely determined by complementary - and largely uncharacterized - genetics of adsorption, injection, cell take-over and lysis. Here we present a machine learning approach to predict phage-bacteria interactions trained on genome sequences of and phenotypic interactions amongst 51 Escherichia coli strains and 45 phage{lambda} strains that coevolved in laboratory conditions for 37 days. Leveraging multiple inference strategies and without a priori knowledge of driver mutations, this framework predicts both who infects whom and the quantitative levels of infections across a suite of 2,295 potential interactions. We found that the most effective approach inferred interaction phenotypes from independent contributions from phage and bacteria mutations, accurately predicting 86% of interactions while reducing the relative error in the estimated strength of the infection phenotype by 40%. Feature selection revealed key phage{lambda} and E. coli mutations that have a significant influence on the outcome of phage-bacteria interactions, corroborating sites previously known to affect phage{lambda} infections, as well as identifying mutations in genes of unknown function not previously shown to influence bacterial resistance. The methods success in recapitulating strain-level infection outcomes arising during coevolutionary dynamics may also help inform generalized approaches for imputing genetic drivers of interaction phenotypes in complex communities of phage and bacteria.

bioinformatics↗

bioRxiv2024

A Comprehensive Allele Specific Expression Resource for the Equine Transcriptome

BackgroundAllele-specific expression (ASE) analysis provides a nuanced view of cis-regulatory mechanisms affecting gene expression. ResultsIn this work, we introduce and highlight the significance of an equine ASE analysis, containing integrated long- and short-read RNA sequencing data, along with insight from histone modification data, from four healthy Thoroughbreds (2 mares and 2 stallions) across 9 tissues. ConclusionsThis valuable publicly accessible resource is poised to facilitate investigations into regulatory variation in equine tissues and foster a deeper understanding of the impact of allelic imbalance in equine health and disease at the molecular level.

genetics↗

bioRxiv2023

eCV: Enhanced coefficient of variation and IDR extensions for reproducibility 1 assessment of high-throughput experiments with multiple replicates.

MotivationReproducibility assessment is essential in extracting reliable scientific insights from highthroughput experiments. Inconsistency between technical replicates poses a challenge, particularly clear in next generation sequencing technologies based on immunoprecipitations, where the assessment of reproducibility in peak identification is a critical analytical step. While the Irreproducibility Discovery Rate (IDR) method has been instrumental in assessing reproducibility, its standard implementation is constrained to handling only two replicates. In the current era of steadily growing sample sizes, eased by multiplexing and reduced sequencing costs, highly performing methods that handle any number of replicates are desirable. ResultsWe introduce three novel methods for reproducibility assessment in high-throughput data that handle an arbitrary number of replicates. The first, general IDR (gIDR), extends the standard IDR by adapting its Expectation-Maximization (EM) algorithm to handle distributions of any dimensions dictated by the number of replicates. The second, meta-IDR (mIDR), employs a meta-analysis approach, calculating local IDR scores for all pairs of replicates and combining them using standard probability rules. The third method introduces an "enhanced" Coefficient of Variation (eCV), ranking features based on intensity and variability, using a parametric bootstrap approach to obtain an index analogous to local IDR. Comparative analysis with traditional IDR in simulated and experimental data reveals the heightened performance of the proposed multivariate alternatives under varying scenarios, thereby addressing the critical challenge of reproducibility assessment in contemporary high-throughput experiments. Availability and implementationThe described methods are implemented as an R package: https://github.com/eclipsebio/eCV Contactinfo@eclipsebio.com

bioinformatics↗

bioRxiv2023

Trojan horse virus delivering CRISPR-AsCas12f1 controls plant bacterial wilt caused by Ralstonia solanacearum

Plant bacterial wilt caused by the Ralstonia solanacearum species complex results in huge food and economic losses. Accordingly, the development of an effective control method for this disease is urgently required. Traditional lytic phage biocontrol methods have inherent limitations. However, filamentous phages, which do not lyse host bacteria and exert minimal burden, offer a potential solution. A filamentous phage RSCq that infects R. solanacearum was isolated in this study through genome mining. We constructed engineered filamentous phages based on RSCq by employing our proposed approach with a wide applicability to non-model phages, enabling the infection of R. solanacearum in medium and soil and delivering exogenous genes into bacterial cells. Similar to the Greek soldiers hidden within the Trojan horse, CRISPR-AsCas12f1 gene editing system that targets the key virulence regulator gene hrpB was implanted into the engineered phage, generating the engineered phage RSCqCRISPR-Cas. Our findings demonstrated that RSCqCRISPR-Cas could disarm the key "weapon", hrpB, of R. solanacearum, in medium and in plants. Remarkably, pretreatment with RSCqCRISPR-Cas significantly controlled tobacco bacterial wilt, highlighting the potential of engineered filamentous phages as promising biocontrol agents against plant bacterial wilt and other bacterial diseases.

microbiology↗

bioRxiv2023

Metagenomic analysis of individual mosquitos reveals the ecology of insect viruses

Mosquito transmitted viruses are responsible for an increasing burden of human disease. Despite this, little is known about the diversity and ecology of viruses within individual mosquito hosts. Using a meta-transcriptomic approach, we analysed the virome of 2,438 individual mosquitos (79 species), spanning [~]4000 km along latitudes and longitudes in China. From these data we identified 393 core viral species associated with mosquitos, including seven (putative) arbovirus species. We identified potential species and geographic hotspots of viral richness and arbovirus occurrence, and demonstrated that host phylogeny had a strong impact on the composition of individual mosquito viromes. Our data revealed a large number of viruses shared among mosquito species or genera, expanding our knowledge of host specificity of insect-associated viruses. We also detected multiple virus species that were widespread throughout the country, possibly facilitated by long-distance mosquito migrations. Together, our results greatly expand the known mosquito virome, linked the viral diversity at the scale of individual insects to that at a country-wide scale, and offered unique insights into the ecology of viruses of insect vectors.

ecology↗

bioRxiv2023

Phenologically-informed species distribution models (SDMs) forecast less species loss and turnover versus standard SDMs

Species distribution models (SDMs) have been central for documenting the relationship between species geographic ranges and environmental conditions for more than two decades. However, the vast majority of SDMs rarely consider functional traits, such as phenology, which strongly affect species demography and fitness. Using >120,000 herbarium specimens representing 360 plant species across the eastern United States, we developed a novel "phenology-informed" SDM that integrates dynamic phenological responses to changing climates. Compared to standard SDMs based only on abiotic variables, our phenology-informed SDMs forecast significantly lower species habitat loss and less species turnover within communities under climate change. These results suggest that phenotypic plasticity or local adaptation in phenology may help many species adjust their ecological niches and persist in their habitats during periods of rapid environmental change. By modeling historical data that link phenology, climate, and species distributions, our findings reveal how species reproductive phenology mediates their geographic distributions along environmental gradients and affects regional biodiversity patterns in the face of future climate change. More importantly, our newly developed model also circumvents the need for mechanistic models that explicitly link traits to occurrences for each species, thus better facilitating the deployment of trait-based SDMs across unprecedented spatial and taxonomic scales.

ecology↗

bioRxiv2023

Living cell mTORC1 inhibition reporter mTIR reveals nutrient-sensing targets of histone deacetylase inhibitor

Mammalian or mechanistic target of rapamycin complex 1 (mTORC1) is a clinically effective therapeutic target for diseases such as cancer, diabetes, aging, and neurodegeneration, yet an efficient tool to monitor mTORC1 inhibition in living cells or tissues is still lacking. Here we devised a genetically encoded mTORC1 inhibition reporter termed mTIR that exhibits a highly contrasted fluorescence puncta pattern in response to mTORC1 inhibition. mTIR specifically senses physiological, pharmacological and genetic inhibition of mTORC1 signaling in living cells and tissues. Importantly, mTIR can be applied as an powerful tool for imaging-based visual screening of mTORC1 inhibitors. By this method, we identified histone deacetylase inhibitors (HDACi) that selectively inhibit mTORC1 by inducing nutrient-sensing gene expression. Thus, mTIR is a unique living cell reporter efficiently detecting the inhibition of mTORC1 activity, and the HDACi Panobinostat transcriptionally target mTORC1 signaling via amino acids sensing.

cell biology↗

bioRxiv2023

An Unexpected Role of Neutrophils in Clearing Apoptotic Hepatocytes In Vivo

Billions of apoptotic cells are removed daily in a human adult by professional phagocytes (e.g. macrophages) and neighboring nonprofessional phagocytes (e.g. stromal cells). Despite being a type of professional phagocyte, neutrophils are thought to be excluded from apoptotic sites to avoid tissue inflammation. Here we report a fundamental and unexpected role of neutrophils as the predominant phagocyte responsible for the clearance of apoptotic hepatic cells in the steady state. In contrast to the engulfment of dead cells by macrophages, neutrophils burrowed directly into apoptotic hepatocytes, a process we term perforocytosis, and ingested the effete cells from the inside. The depletion of neutrophils caused defective removal of apoptotic bodies, induced tissue injury in the mouse liver and led to the generation of autoantibodies. Human autoimmune liver disease showed similar defects in the neutrophil-mediated clearance of apoptotic hepatic cells. Hence, neutrophils possess a specialized immunologically silent mechanism for the clearance of apoptotic hepatocytes through perforocytosis, and defects in this key housekeeping function of neutrophils contribute to the genesis of autoimmune liver disease.

physiology↗

bioRxiv2023

Single-cell transcriptomic analyses reveal the cellular and genetic basis of aquatic locomotion in scyphozoan jellyfish

The authors have withdrawn their manuscript because the authors need to re-organize the data and writing. More experimental evidence from whole-mount ISH assay and RNAi assays will be added to support the viewpoints. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

ecology↗

bioRxiv2023

Effect of oncolytic virotherapy on immune microenvironment in immune subtypes identified in gastric cancer and hepatocellular carcinoma

Tumor occurrence and progression are significantly influenced by immunity, and the immune infiltration and immune-related gene expression in solid tumors are closely correlated to the response of patients to immunotherapy. In this study, the level of tumor infiltrating immune cells in gastric cancer and hepatocellular carcinoma samples from the TCGA database were assessed using ssGSEA, and the tumor samples were divided into two subtypes (Imm_H and Imm_L) with different immune cell infiltration level. The differences in immune cell percentage and immune checkpoint gene expression between the two subtypes indicated that the Imm_H group had higher levels of immune infiltration, but also more infiltrated immunosuppressive cells and higher mRNA levels of immune checkpoint genes. Then the immune subtype-specific gene network was built and the main modules representing the genes and functions that differ between the two immune subtypes were identified. To explore the effect of oncolytic virus on tumor immune microenvironment, we constructed the previously developed synthetic adenovirus containing the synthetic sensory switch gene circuit, assessed the antitumor effect in mouse models, and measured the proportion of different cell types by single-cell RNA sequencing. The results showed that synthetic oncolytic virus inhibited tumor development and altered the proportion of infiltrating immune cells, suggesting that synthetic oncolytic virus may have different mechanism on the two immune subtypes. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=168 HEIGHT=200 SRC="FIGDIR/small/524374v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@dffa9dorg.highwire.dtl.DTLVardef@be8e2eorg.highwire.dtl.DTLVardef@68acf6org.highwire.dtl.DTLVardef@33862f_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗