Biology subjects

Guan, J.

Publications and source records attributed to Guan, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Impact of Peptide Initial Configuration and Membrane Composition on Melittin's Pore-Forming Ability under Unbiased All-Atom Molecular Dynamics Simulations

The rising challenge of antimicrobial resistance has accelerated the search for alternative therapeutics. Antimicrobial peptides (AMPs), a class of naturally occurring defense molecules found across diverse species, are promising candidates. Despite their potent membrane-disrupting activity, the atomic details of the pore formation process remain insufficiently understood. In this study, we employed all-atom molecular dynamics (MD) simulations to investigate the pore formation process of melittin under different initial configurations. Simulations were conducted using three different membrane systems: a pure POPC bilayer, a mammalian membrane model (DOPC:Cholesterol, 9:1), and a bacterial membrane model (DOPE:DOPG, 3:1). For each system, we examined four different starting configurations, in which six melittin peptides were arranged in a star-like pattern. Our results demonstrated that the pore formation process strongly depends on the initial peptide configuration. In one specific initial arrangement (termed as Conf.I), pore formation consistently occurred within 100 nanoseconds, regardless of membrane composition. Furthermore, the simulations revealed that pore formation was more challenging in the mammalian membrane model and even more so in the bacterial membrane model, in comparison with the pure POPC bilayer. These findings are in line with previously reported minimum inhibitory concentration (MIC) and the 50% hemolysis concentration (HC50) of melittin in the literature. Additionally, we identified lysine-7 (K7) as the key residue in determining whether a stable pore can form. In configurations where the K7 side chain formed electrostatic interactions with the phosphate group of a lipid, melittin were anchored to the membrane surface, thereby preventing pore formation. In contrast, simulations of melittin mutants K7A and K7Q showed no such anchoring effect, and thus pore formation was possible in multiple initial configurations. Notably, the K7Q mutation showed a preference for pore formation in bacterial membranes over mammalian membranes, suggesting that reducing toxicity while maintaining antimicrobial efficacy is possible.

biochemistry↗

bioRxiv2025

An Updated Polygenic Index Repository: Expanded Phenotypes, New Cohorts, and Improved Causal Inference

Polygenic indexes (PGIs) -- DNA-based predictors of individual phenotypes -- have become essential tools across biomedical and social sciences. We introduce Version 2 of the Polygenic Index Repository, which expands phenotype coverage from 47 to 61, increases the number of participating datasets from 11 to 20, and adopts a more consistent and improved methodology for PGI construction. For 16 phenotypes, we leverage summary statistics from an updated GWAS meta-analysis with greater statistical power compared to the original release, thereby improving the PGIs predictive power. To improve power for family-based analyses, we provide imputed parental PGIs in all datasets with first-degree relatives and offer a framework for interpreting results from analyses that control for parental PGIs. We illustrate the utility of parental PGIs using two applications: (1) comparing PGI associations with and without parental PGI controls for all phenotypes in two Repository datasets with family data, and (2) for BMI and diastolic blood pressure, exploring the contribution of causal versus non-causal components of PGI associations to the imperfect portability of PGIs across subgroups within a genetic ancestry. Collectively, the updates enhance predictive performance, broaden the Repositorys scope, and introduce novel resources that reduce confounding bias and improve interpretability.

genomics↗

bioRxiv2025

Two telomere-to-telomere, gap-free genome assemblies and comparisons revealed the conserved key genes associated with sugar accumulation in Rubus genus

For the first time, we assembled two highly continuous, completely gap-free reference genomes of the Rubus subgenus: Rubus hirsutus Thunb. Penglei (XMM) and Rubus eustephanos Focke ex Diels Dahongpao (DHP), which are widely distributed in southern China with similar phenotypic traits (Figures 1A, 1B, and Figure S1), yet ripe fruits display distinct sugar accumulation levels (Table S1), making them ideal candidates for investigating the mechanisms underlying sugar accumulation in the Rubus genus. The XMM (213.53 Mb, 28,204 genes) and DHP (218.26 Mb, 28,569 genes) genomes exhibit close evolutionary relationships, diverging approximately 3.21 Mya. Comparative genomics identified extensive synteny, interspecific structural variations (translocations, inversions, segmental duplications), and presence/absence variation (PAV). Using Hi-C interaction heatmaps and Sanger sequencing, we validated interspecific structural inversions. Additionally, we identified a sugar transporter gene (MFS1), which is present in XMM but absent in DHP. Combined analysis of the gene family expansion/contraction and transcriptome identified two conserved key genes (RhSTP13 and RhSTP7) associated with sugar accumulation in Rubus genus and displayed distinct roles through transient expression assay. To facilitate functional genomics study, we also established a comprehensive Rubus database, RubusDB, a freely accessible repository consolidating all genomic, transcriptomic and phenotypic data of Rubus genus. These findings provide a foundational framework for elucidating the genetic basis of sugar accumulation, genome diversification, and trait improvement in Rubus species. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=170 SRC="FIGDIR/small/646780v2_fig1.gif" ALT="Figure 1"> View larger version (72K): org.highwire.dtl.DTLVardef@1baca20org.highwire.dtl.DTLVardef@2c01eaorg.highwire.dtl.DTLVardef@131dc00org.highwire.dtl.DTLVardef@62a04f_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFIGURE 1.C_FLOATNO Phenotypic characterization, de novo genome assemblies, variation, and evolution of Rubus hirsutus Thunb. Penglei (XMM) and Rubus eustephanos Focke ex Diels Dahongpao (DHP). (A) Illustration of XMM whole plants, stem, flower bud and flower, respectively. (B) Illustration of DHP whole plants, stem, flower bud and flower, respectively. (C) The chromosome karyotype analysis of XMM. Bar = 10 {micro}m. (D) Circular diagram of XMM and DHP reference genomes. (a) Chromosomes are represented by centromeres (dark red) and telomeres (blue); (b) CEN18 density; (c) CEN17 density; (d) Gene density; (e) TE density; (f) PAV density; (g) SNP density; (h) Collinear lines at the center of diagram highlight homoeologous chromosomes relationships and non-homoeologous regions. (E) Genomic alignments between XMM and DHP. Inversions, duplications and translocations are marked with orange, blue and green ribbons, respectively. (F) Identification of large inversions in chromosome 7 between XMM and DHP. The three heatmaps show the chromatin interaction matrix, including mapping Hi-C data of DHP against DHP genome (left), mapping Hi-C data of DHP against XMM genome (middle) and mapping Hi-C data of XMM against XMM genome (right). The lower panel illustrates gene alignments between XMM and DHP. (G) Synteny, structural rearrangements, monomer, and identity distribution in the 16-20 Mbp region of chromosome 6 between XMM and DHP. (H) Local genome synteny of chromosome 5, with a structural variation that is present only in XMM. The PAV region includes a gene related to sugar transporter (MFS1, XMM05G025540). (I) Gene-level matchings of MFS genes in the PAVs region between XMM and DHP. (J) Phylogenetic relationships and divergence times between raspberries and other Rosaceae species. The black numbers close to the divergence nodes indicate the divergence times and the red bars represent the 95% confidence intervals. The red and black numbers indicate expanded and contracted ortholog groups at the corresponding node. Scale bar corresponds to 10 Mya. C_FIG

genomics↗

bioRxiv2025

Munc13-4 mediates tumor immune evasion by regulating the sorting and secretion of PD-L1 via exosomes

Tumor-derived extracellular vesicles primarily carry PD-L1 via exosomes, which interact with PD-1 receptors on T cells, impacting immune responses in the tumor microenvironment and beyond, leading to a more extensive immunosuppressive landscape. However, the mechanisms governing exosomal PD-L1 sorting and secretion remain elusive. In this study, we identified Munc13-4 as a crucial regulator of exosomal PD-L1 sorting and secretion. Deletion of Munc13-4 in breast tumors enhances T cell-mediated anti-tumor immunity, suppresses tumor growth, and improves the efficacy of immune checkpoint inhibitors. Our results illustrate how Munc13-4 collaborates with HRS, Rab27, and SNAREs to facilitate PD-L1 sorting and secretion via exosomes. The cryo-EM structure of the Munc13-4-Rab27a complex provide new insights into its role in exosome secretion. Importantly, we discovered that Munc13-4 has a novel role in sorting PD-L1 onto exosomes, which relies on the formation of a ternary complex with PD-L1 and HRS. In addition, IFN{gamma} stimulation modifies Munc13-4 and HRS, establishing a dynamic regulatory mechanism that enables tumor cells to adapt to immune pressure by modulating PD-L1 sorting. Using a specially designed peptide to disrupt the Munc13-4-PD-L1 interaction and impede PD-L1 sorting significantly enhances anti-tumor immunity and slows tumor growth in vivo. These results highlight the potential of targeting the Munc13-4-PD-L1 axis to suppress tumor immune evasion.

cell biology↗

bioRxiv2025

SynBioGPT: A Retrieval-Augmented Large Language Model Platform for AI-Guided Microbial Strain Development

Synthetic biology seeks to engineer microbial cell factories for sustainable bioproduction, yet the optimization of these systems is impeded by the complexity of metabolic engineering and the protracted timelines of iterative design-build-test-learn (DBTL) cycles. Traditional computational approaches, such as constraint-based modeling, provide valuable insights but demand extensive manual curation. Large language models (LLMs) hold promises for automating knowledge extraction and strain design, yet conventional models like GPT-4 suffer from outdated corpora and hallucination errors in domain-specific tasks. SynBioGPT v1.0, a Retrieval-Augmented Generation (RAG)-enhanced LLM, enhanced knowledge retrieval using vector search but often retrieved semantically similar yet contextually irrelevant documents. Here, we introduce SynBioGPT v2.0 (https://synbiogpt.biodesign.ac.cn), which mitigates these limitations by decomposing queries into sub-questions and employing keyword-based searches. Tested on a 100-question synthetic biology benchmark, SynBioGPT v2.0 achieved 98% accuracy with the Claude-3.7-sonnet backend, a 10% improvement over v1.0s 88% with Llama3-8B-Instruct. This advance highlight the efficacy of query decomposition and precise retrieval in enhancing LLM utility for synthetic biology.

synthetic biology↗

bioRxiv2025

HP-Bodies - Ancestral Condensates that Regulate RNA Turnover and Protein Translation in Bacteria

Uncovering what drives select biomolecules to form phase-separated condensates in vivo and identifying their physiological significance are topics of fundamental importance. Here we show that nitrogen-starved Escherichia coli produce long-chain polyphosphates, which scaffold the RNA chaperone Hfq into phase-separating high molecular weight complexes together with components of the RNA translation and processing machinery. The presence of polyphosphate within these condensates, which we termed HP-bodies, controls Hfq function by selectively stabilizing polyadenylated RNAs involved in transcription and protein translation, and promoting interactions with translation- and RNA-metabolism-associated proteins involved in de novo protein synthesis. Lack of polyphosphate prevents HP-body formation, which increases cell death and significantly hinders recovery from N-starvation. In functional analogy, we demonstrate that polyP contributes specifically to the formation of Processing (P)-bodies in human cell lines, revealing that a single, highly conserved and ancestral polyanion serves as the universal scaffold for functional phase-separated condensate formation across the tree of life.

microbiology↗

bioRxiv2024

Decipher Fundamental Atomic Interactions to Unify Generative Molecular Docking and Design

Understanding molecular interactions is essential to structural biology and drug discovery. Despite the progress of AI models in revealing and exploiting the interaction mechanisms for various applications, they are predominantly tailored to specific tasks without fully exploiting the underlying transferability across molecular data and tasks. Here, we present PocketXMol, an atom-level generative foundation model to decipher fundamental atomic interactions for general protein-pocket-interacting molecular tasks. It adopts a novel unified generative framework with an innovative task prompt mechanism and an exclusive atom-level representation, making it applicable to diverse tasks covering structure prediction and design of small molecules and peptides, without requiring fine-tuning. PocketXMol was compared to 55 baseline models across 13 typical tasks, achieving state-of-the-art performance in 11 tasks and remaining competitive in the others. We successfully utilized PocketXMol to design novel small molecules that inhibit caspase-9 with efficacy comparable to that of commercial pan-caspase inhibitors. Furthermore, we employed PocketXMol to design PD-L1-binding peptides, demonstrating a success rate substantially higher than random library screening. Three representative peptides underwent further experiments, which validated the cellular specificity and confirmed their potential for molecular probing and therapeutics. PocketXMol presents a powerful and versatile tool with promising prospects for future applications and will have a profound impact on AI-aided drug discovery.

bioinformatics↗

bioRxiv2024

P(all-atom) Is Unlocking New Path For Protein Design

We introduce Pallatom, an innovative protein generation model capable of producing protein structures with all-atom coordinates. Pallatom directly learns and models the joint distribution P(structure, seq) by focusing on P(all-atom), effectively addressing the interdependence between sequence and structure in protein generation. To achieve this, we propose a novel network architecture specifically designed for all-atom protein generation. Our model employs a dual-track framework that tokenizes proteins into residue-level and atomic-level representations, integrating them through a multi-layer decoding process with "traversing" representations and recycling mechanism. We also introduce the atom14 representation method, which unifies the description of unknown side-chain coordinates, ensuring high fidelity between the generated all-atom conformation and its physical structure. Experimental results demonstrate that Pallatom excels in key metrics of protein design, including designability, diversity, and novelty, showing significant improvements across the board. Our model not only enhances the accuracy of protein generation but also exhibits excellent sampling efficiency, paving the way for future applications in larger and more complex systems.

bioinformatics↗

bioRxiv2024

MOSTPLAS: A Self-correction Multi-label Learning Model for Plasmid Host Range Prediction

Plasmids play an essential role in horizontal gene transfer among diverse microorganisms, aiding their host bacteria in acquiring beneficial traits like antibiotic and metal resistance. Identifying the host bacteria where a plasmid can transfer, replicate or persist provides insights into how plasmids promote bacterial evolution. Plasmid host range prediction tools can be categorized as alignment-based and learning-based. Alignment-based tools have high precision but fail to align many newly sequenced plasmids with characterized ones in reference databases. In contrast, learning-based tools help predict the host range of these newly discovered plasmids. Although previous researches have demonstrated the existence of broad-host-range (BHR) plasmids, there is no database providing their detailed and complete host labels. Without adequate well-annotated training samples, learning-based tools fail to extract discriminative feature representations and obtain limited performance. To address this problem, we propose a self-correction multi-label learning model called MOSTPLAS. We design a pseudo label learning algorithm and a self-correction asymmetric loss to facilitate the training of multi-label learning model with samples containing some unknown missing positive labels. Experimental results on multi-host plasmids generated from the NCBI RefSeq database, metagenomic data, and real-world plasmid sequences with experimentally determined host range demonstrate the superiority of MOSTPLAS.

bioinformatics↗

bioRxiv2024

Gut Microbiome Perturbation Affected Conjugative Transfer of Antimicrobial Resistance Genes

The global spread of antimicrobial resistance genes (ARGs) poses a significant threat to public health. While antibiotics effectively treat bacterial infections, they can also induce gut dysbiosis, the severity of which varies depending on the specific antibiotic treatment used. However, it remains unclear how gut dysbiosis affects the mobility and dynamics of ARGs. To address this, mice were pre-treated with streptomycin, ampicillin, or sulfamethazine, and then orally inoculated with Salmonella enterica serovar Typhimurium and S. Heidelberg carrying a multi-drug resistance IncA/C plasmid. The streptomycin pre- treatment caused severe microbiome perturbation, promoting high-density colonization of S. Heidelberg and S. Typhimurium, and enabling IncA/C transfer from S. Heidelberg to S. Typhimurium and a commensal Escherichia coli. The ampicillin pre-treatment induced moderate microbiome perturbation, supporting only S. Heidelberg colonization and IncA/C transfer to commensal E. coli. The sulfamethazine pre-treatment led to mild microbiome perturbation, favoring neither Salmonella spp. colonization nor conjugative plasmid transfer. The degree of gut dysbiosis also influenced the enrichment or depletion of ARGs associated with mobile plasmids or core commensal bacteria, respectively. These findings underscore the significance of pre-existing gut dysbiosis induced by various antibiotic treatments on ARG dissemination and may inform prudent antibiotic use practices.

microbiology↗

bioRxiv2024

PlasGO: enhancing GO-based function prediction for plasmid-encoded proteins based on genetic structure

Plasmid, as a mobile genetic element, plays a pivotal role in facilitating the transfer of traits, such as antimicrobial resistance, among the bacterial community. Annotating plasmid-encoded proteins with the widely used Gene Ontology (GO) vocabulary is a fundamental step in various tasks, including plasmid mobility classification. However, GO prediction for plasmid-encoded proteins faces two major challenges: the high diversity of functions and the limited availability of high-quality GO annotations. Thus, we introduce PlasGO, a tool that leverages a hierarchical architecture to predict GO terms for plasmid proteins. PlasGO utilizes a powerful protein language model to learn the local context within protein sentences and a BERT model to capture the global context within plasmid sentences. Additionally, PlasGO allows users to control the precision by incorporating a self-attention confidence weighting mechanism. We rigorously evaluated PlasGO and benchmarked it against six state-of-the-art tools in a series of experiments. The experimental results collectively demonstrate that PlasGO has achieved commendable performance. PlasGO significantly expanded the annotations of the plasmid-encoded protein database by assigning high-confidence GO terms to over 95% of previously unannotated proteins, showcasing impressive precision of 0.8229, 0.7941, and 0.8870 for the three GO categories, respectively, as measured on the novel protein test set.

bioinformatics↗

bioRxiv2024

Gradual labeling with fluorogenic probes for MINFLUX nanoscopy of densely packed structures

Single-molecule localization in densely packed structures represents a formidable challenge in nanoscopy. Here we develop a gradual labeling method with fluorogenic probes for MINFLUX nanoscopy (GLF-MINFLUX), with which individual proteins in packed structures can be sequential illuminated and quantitatively localized at the nanoscale solely by adjusting probe concentration. With a 1.7-fold localization precision improvement and 2.2-fold faster acquisition, GLF-MINFLUX enables dual-channel nanoscale imaging of densely neuronal microtubules and microfilaments, and three-dimensional quantitative mapping of individual TOM20 proteins in mitochondrial clusters.

biophysics↗

bioRxiv2024

Defining the constituents and functions of a lipid-based jumbo phage compartment

Viruses are vulnerable to cellular defenses at the start of the infection when a single copy genome has not yet initiated de novo viral protein synthesis. A family of jumbo phages related to phage {Phi}KZ, which infects Pseudomonas aeruginosa, uses a protein-based phage nucleus to protect the DNA during middle and late stages of infection, but how it is protected prior to phage nucleus assembly is unclear. To reveal the environment surrounding injected phage DNA, we determine which proteins interact with phage proteins injected with the phage genome. Here, we surprisingly identify host proteins related to membrane and lipid biology co-purifying with the injected phage protein. Staining of infected cells with lipophilic dyes revealed a clustering of host lipids co-localized with phage DNA and protein in an early phage infection (EPI) vesicle. Early gene expression is induced by the co-injected virion RNAP (vRNAP), with specific early proteins then associating with the EPI vesicle and ribosomes, likely to facilitate localized translation. As the infection progresses, the phage genome separates from the EPI vesicle and vRNAP, moving into the nascent proteinaceous phage nucleus. Enzymes involved in DNA replication and CRISPR/restriction immune nucleases notably do not localize to the EPI vesicle, supporting that DNA is not exposed at this early time point. We therefore propose that the EPI vesicle is rapidly constructed together with injected phage proteins, phage DNA, host lipids, and host membrane proteins to enable genome protection, early transcription, localized translation, and to ensure the faithful transfer of the single copy phage genome to the proteinaceous nucleus.

microbiology↗

bioRxiv2024

ViraLM: Empowering Virus Discovery through the Genome Foundation Model

MotivationViruses, with their ubiquitous presence and high diversity, play pivotal roles in ecological systems and have significant implications for public health. Accurately identifying these viruses in various ecosystems is essential for comprehending their variety and assessing their ecological influence. Metagenomic sequencing has become a major strategy to survey the viruses in various ecosystems. However, accurate and comprehensive virus detection in metagenomic data remains difficult. Limited reference sequences prevent alignment-based methods from identifying novel viruses. Machine learningbased tools are more promising in novel virus detection but often miss short viral contigs, which are abundant in typical metagenomic data. The inconsistency in virus search results produced by available tools further highlights the urgent need for a more robust tool for virus identification. ResultsIn this work, we develop a Viral Language Model, named ViraLM, to identify novel viral contigs in metagenomic data. By employing the latest genome foundation model as the backbone and training on a rigorously constructed dataset, the model is able to distinguish viruses from other organisms based on the learned genomic characteristics. We thoroughly tested ViraLM on multiple datasets and the experimental results show that ViraLM outperforms available tools in different scenarios. In particular, ViraLM improves the F1-score on short contigs by 22%. AvailabilityThe source code of ViraLM is available via: https://github.com/ChengPENG-wolf/ViraLM. Contactyannisun@cityu.edu.hk

bioinformatics↗

bioRxiv2023

E3 ligase ASB3 downregulates antiviral innate immunity by targeting MAVS for ubiquitin-proteasomal degradation

E3 ubiquitin ligases are very important to regulate antiviral immunity during viral infection. Here, we discovered that Ankyrin repeat and SOCS box-containing protein 3 (ASB3), an E3 ligase, are upregulated in the presence of RNA viruses, particularly Influenza A virus (IAV). Notably, overexpression of ASB3 inhibits type I IFN (IFN-I) responses induced by Sendai virus (SeV) and H9N2, and ablation of ASB3 restores SeV and H9N2 infection-mediated transcription of IFN-{beta} and its downstream interferon-stimulated genes (ISGs). Interestingly, animals lacking ASB3 showed a decreased susceptibility to H9N2 and PR8 infections. Mechanistically, ASB3 interacts with MAVS and directly mediates K48-linked polyubiquitination and degradation of MAVS at K297, thereby inhibiting the phosphorylation levels of TBK1 and IRF3, downregulating downstream antiviral signaling. These findings establish ASB3 as a critical negative regulator in controlling the activation of antiviral signaling and describe a novel function of ASB3 that has not been previously reported. IMPORTANCEIAV is a significant zoonotic pathogen that causes infections of the respiratory system. Hosts have evolved multiple strategies to defend against IAV infection. However, not all host proteins play an active defense role. In this study, we found that the E3 ligase ASB3 regulates antiviral immunity by manipulating MAVS stability. Briefly, overexpression of ASB3 degrades MAVS, thereby promoting viral replication. In contrast, ASB3 deletion restores MAVS expression, upregulating IFN-I responses. Additional research revealed that ASB3 mediates the K48-linked polyubiquitination of MAVS at K297, resulting in ASB3 being degraded via the ubiquitin-proteasome pathway. These findings reveal, for the first time, a novel mechanism by which ASB3 negatively regulates antiviral immunity and provides a potential target for anti-IAV drug development.

immunology↗

bioRxiv2023

AhR ligands from LGG metabolites promote piglet intestinal ILC3 activation and IL-22 secretion to inhibit PEDV infection

In maintaining organismal homeostasis, gut immunity plays a crucial role. The coordination between the microbiota and the immune system through bidirectional interactions regulates the impact of microorganisms on the host. Our research focused on understanding the relationship between substantial changes in jejunal intestinal flora and metabolites and intestinal immunity during porcine epidemic diarrhea virus (PEDV) infection in piglets. We discovered that Lactobacillus rhamnosus GG (LGG) could effectively prevent PEDV infection in piglets. Further investigation revealed that LGG metabolites interact with type 3 innate lymphoid cells (ILC3) in the jejunum of piglets through the aryl hydrocarbon receptor (AhR). This interaction promotes the activation of ILC3 cells and the production of interleukin-22 (IL-22). Subsequently, IL-22 facilitates the proliferation of IPEC-J2 cells and activates the STAT3 signaling pathway, thereby preventing PEDV infection. Moreover, the AhR receptor exerts its influence on various cell types within organoids, including intestinal stem cells (ISCs), Paneth cells, and enterocytes, fostering their growth and development, suggesting a broad impact of AhR on intestinal health. In conclusion, our study demonstrates the ability of LGG to modulate intestinal immunity and effectively prevent PEDV infection in piglets. These findings highlight the potential application of LGG as a preventive measure against viral infections in livestock.

immunology↗

bioRxiv2023

Attila and Aetius on the roof: The succession phenomenon in the roof greening area of a primary school in Beijing during the lockdown period of the COVID-19

"Succession" refers to the process of certain species replacing others over time. It is of great significance for understanding the characteristics and evolution of ecosystems. This article compares the changes in school rooftop green areas before and after the COVID-19 epidemic (2019, 2023), and studies the situation of wild grass invading roofs during the three years of the epidemic, as well as the response of original rooftop plants to the invasion. The results showed that: [circled1] invasive weeds were concentrated in 2 families and 4 species, forming a population advantage in most of the invaded planting boxes; [circled2] The succession has had a significant impact on the roof greening area; [circled3] Among the two cultivated plants (Phedimus aizoon (PA) and Sedum sarmentosum (SS)), SS was greatly affected, with the community almost disappearing, while PA was almost unaffected.

ecology↗

bioRxiv2023

An axonemal intron splicing program sustains Plasmodium male development

Differentiation of male gametocyte into flagellated fertile male gamete relies on the axoneme assembly, a major component of male development for mosquito transmission of malaria parasite. RNA-binding protein (RBP)-mediated post-transcription regulation plays important roles in eukaryotic sexual development, including the Plasmodium female development. However, the role of RBP in defining the Plasmodium male transcriptome and its function in the male gametogenesis remain elusive. Here, we screened the gender expression of the genome-wide RBPs and identified an undescribed male-specific RBP gene Rbpm1 in the Plasmodium. RBPm1 is localized in the nucleus of male gametocytes. RBPm1-deficient parasites fail to assemble the axoneme for male gametogenesis and thus mosquito transmission. RBPm1 interacts with spliceosome E complex and regulates splicing initiation of certain introns in a group of 26 axonemal genes. RBPm1 deficiency results in intron retention and protein loss of these axonemal genes. Intron deletion restores axonemal proteins expression and partially rectifies axonemal defects in RBPm1-null gametocytes. Further splicing assays in both reporter and endogenous genes exhibit stringent recognition of the axonemal introns by RBPm1. Therefore, the splicing activator RBPm1 and its target introns constitute an axonemal intron splicing program in the post-transcription regulation essential for Plasmodium male development.

microbiology↗