Biology subjects

Zhan, X.

Publications and source records attributed to Zhan, X..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Ectoine production by newly isolated halophilic methanotroph Methylotuvimicrobium percolatum using surplus methane from anaerobic digestion

Anaerobic digestion (AD) processes that convert waste such as livestock wastewater into biomethane for energy recovery are expanding globally. However, biogas exceeding storage capacity is typically flared, resulting in the release of carbon dioxide, a greenhouse gas. To address this issue, we focused on halophilic methane-oxidizing bacteria (methanotrophs) capable of converting methane into ectoine, a high-value compatible solute widely used in more than 400 cosmetic active ingredients and valued at approximately US$1,000/kg. Nevertheless, research on halophilic methanotrophs and ectoine biosynthesis remains limited. Here, we report the successful isolation of the Type I methanotroph Methylotuvimicrobium percolatum from activated sludge in a brackish water environment. Complete genome sequencing revealed genes for methane oxidation, osmoadaptation, and notably the ectABCask cluster responsible for ectoine biosynthesis. Activity tests under varying NaCl concentrations confirmed ectoine production, with a maximum yield of 20.1 mg ectoine/g-DCW achieved at 25% methane, 30 {degrees}C, and 3 wt% salinity. Biomass growth remained robust up to 6% salinity but declined sharply at higher NaCl concentrations, indicating that optimal conditions for growth and ectoine synthesis do not entirely coincide. These findings advance the fundamental understanding of halophilic methanotroph physiology and highlight their potential as sustainable platforms for converting surplus methane from AD processes into commercially valuable ectoine.

microbiology↗

bioRxiv2025

The gut microbiota directs vitamin A flux to regulate intestinal T cell development

The intestinal microbiota shapes adaptive immunity, but the mechanisms remain incompletely defined. Here, we show that the microbiota initiates the movement of retinoids--dietary vitamin A derivatives including retinol and retinoic acid--through a sequential pathway from epithelial cells to myeloid cells and ultimately to T cells in the mesenteric lymph nodes (mLNs). This cellular axis is traversed over three days. Microbe-associated molecular patterns (MAMPs) initiate retinoid flux by inducing expression of serum amyloid A (SAA) proteins. These epithelial retinol-binding proteins are necessary and sufficient for epithelial-to-myeloid cell retinoid transfer and for myeloid cell migration to the mLNs. In the mLNs, microbial antigen drives retinoid transfer from myeloid cells to developing T cells, culminating in T cell retinoid uptake and transcriptional programming. This pathway is activated during postnatal development, when gut adaptive immunity is first established. These findings reveal that the microbiota programs intestinal adaptive immunity by regulating immune cell access to a nutrient-derived developmental signal. HighlightsO_LIThe gut microbiota enables vitamin A flux to developing intestinal CD4 T cells. C_LIO_LIMicrobiota-induced SAA initiates vitamin A flux along a gut myeloid-T cell axis. C_LIO_LIMicrobial molecular patterns and antigen drive distinct steps of vitamin A flux. C_LIO_LIMicrobiota-driven vitamin A flux programs intestinal T cell homing and maturation. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=192 HEIGHT=200 SRC="FIGDIR/small/674524v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@13b3906org.highwire.dtl.DTLVardef@11ceee3org.highwire.dtl.DTLVardef@87913forg.highwire.dtl.DTLVardef@50c9a0_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

Microbiota-derived short-chain fatty acids mediate Candida albicans gastrointestinal colonization resistance

The gut microbiota plays a critical role in constraining Candida albicans (Ca) colonization of the gastrointestinal (GI) tract, a key precursor to disseminated fungal infection in immunocompromised hosts. Depletion of commensal microbiota increases Ca burden and promotes dissemination, yet the mechanisms of microbiota-mediated Ca colonization resistance remain poorly defined. Here, we show that gut microbiota-derived short-chain fatty acids (SCFAs) directly inhibit Ca growth by impairing hexose uptake, disrupting central carbon metabolism, and inducing intracellular acidification. In vivo, SCFAs enhance Ca colonization resistance only in the presence of an intact gut microbiome, which is required to drive SCFA-induced taxonomic shifts that further augment resistance. Commensal microbiota lacking SCFA production exhibit diminished capacity to restrict Ca colonization, while prebiotic therapy that increases luminal SCFA levels enhances Ca clearance. These findings define a critical microbiota-metabolite mechanism underlying Ca colonization resistance and suggest strategies to modulate GI fungal burden and prevent invasive disease.

microbiology↗

bioRxiv2025

A new dual-affinity peptide nucleic acid for targeting miRNA-21 precursor rescues tumor repressor PTEN expression

MicroRNAs (miRNAs) have multiple functions in cells and are related to many diseases including cancer by regulating posttranscriptional gene expression. The microRNA precursors (pre-miRs), which can be cleaved by Dicer endonuclease to produce mature miRNAs, often have a cleavage site consisting of both double-stranded (ds) and single-stranded (ss) RNA structures. Peptide nucleic acid (PNA) is a kind of analogue of DNA which can hybridize to DNA or RNA through Watson-Crick and Hoogsteen pairing. We previously reported a novel dual-affinity PNA (daPNA) platform that can simultaneously form a duplex and a triplex with a target RNAs ssRNA-dsRNA junction region. The PNA-RNA complex structure is stabilized by forming antisense PNA (asPNA)-ssRNA duplex immediately adjacent to a chemically modified dsRNA-binding PNA (dbPNA)-dsRNA triplex. In this study, we further explored the application of the daPNA platform to target the precursor of miR-21, which is considered an oncogene. We have designed a set of PNAs including asPNAs, dbPNAs, and daPNAs. The nondenaturing polyacrylamide gel electrophoresis (PAGE) and biolayer interferometry (BLI) data reveal that daPNA-21-10 can strongly bind to pre-miR-21 with high specificity. The data show that pre-miR-21 is easily targeted by traditional antimir, asPNA or dbPNA and optimization of the dsRNA-ssRNA junction position is needed for identifying a tightly binding daPNA. Furthermore, daPNA-21-10 not only inhibits the Dicer activity on pre-miR-21 in cell-free assays, but also down-regulates the expression of miR-21, rescuing PTEN protein expression in cells. Taken together, the biofunction and programmability of daPNA make it a promising platform for probing and regulating miRNA biogenesis and many other RNA-involved biological processes. HighlightsO_LISimultaneous recognition of dsRNA and ssRNA regions C_LIO_LIRNA targeting by dividing and conquering through a dsRNA-ssRNA junction construction C_LIO_LISubstrate-specific inhibition of Dicer acting on pre-miR-21 C_LIO_LIDerepressing PTEN expression by inhibiting miR-21 maturation C_LI O_FIG O_LINKSMALLFIG WIDTH=170 HEIGHT=200 SRC="FIGDIR/small/668835v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@c8af64org.highwire.dtl.DTLVardef@172d2bdorg.highwire.dtl.DTLVardef@1698ea1org.highwire.dtl.DTLVardef@112fa16_HPS_FORMAT_FIGEXP M_FIG C_FIG eToc BlurbLian et al. show that the miR-21 precursor structure containing the Dicer cleavage site can be targeted by a new type of dual-affinity peptide nucleic acids (daPNAs) through the creation of a dsRNA-ssRNA junction, energetically optimized for the simultaneous duplex and triplex formation. Pre-miR-21 structure, which is hardly accessible to traditional antisense strategies and triplex formation alone, can be targeted by a daPNA with high sequence/structure specificity and strong binding affinity. daPNA platform has a great potential in probing many other RNA structures and broad therapeutic applications.

molecular biology↗

bioRxiv2025

Towards the Development of Isoenergetic Peptide Nucleic Acid Based Probes Targeting Double-Stranded RNAs Through Enhancing Sequence-Specific Stacking Interactions

Peptide nucleic acid (PNA), a synthetic nucleic acid analog, exhibits substantial potential in biotechnology and therapeutic applications due to its high binding affinity and nuclease/protease resistance. Chemically modified PNAs capable of forming stable triplex structures with double-stranded RNAs (dsRNAs) under near-physiological conditions further expand their utility by enabling sequence-specific precise targeting and probing of functional RNA structural motifs. However, the presence of inverted Watson-Crick pairs (C-G and U-A) may significantly weaken the triplex formation of the dsRNA-binding PNAs (dbPNAs). Our previous work demonstrated that dbPNA P3 (composed of L, T, and Q monomers for the recognition of G-C, A-U, and C-G base pairs, respectively) can stimulate ribosomal frameshifting by binding to rHP2, a model RNA hairpin structure in an mRNA, albeit with suboptimal efficiency, due to its significantly weakened Q*C-G triple formation. We hypothesize that incorporating s2U adjacent to Q may offer unique stacking and hydrogen bonding interactions facilitating the development of isoenergetic dbPNA-based probes binding toward dsRNAs with varied sequences. In this study, we investigate how incorporating s2U adjacent to Q residues in P3 influences its binding to rHP2. Bio-layer interferometry (BLI) and non-denaturing polyacrylamide gel electrophoresis (PAGE) analyses demonstrate that substituting T with s2U at the N-terminal position adjacent to Q (P3-2QT) enhances binding affinity by [~]10-fold compared to unmodified P3, whereas C-terminal substitution (P3-TQ2) yields only a 2-fold improvement. Consistent with these findings, a cell-free dual-luciferase reporter assay reveals that P3-2QT significantly increases ribosomal frameshifting efficiency compared to P3 and P3-TQ2. Molecular dynamics simulations further indicate that P3-2QT maintains enhanced PNA-PNA stacking stability, particularly between s2U3 and Q4, suggesting a structural basis for its superior activity. Intriguingly, analogous s2U substitution in the P5 oligomer with the Q replaced by L does not confer a comparable enhancement in binding to the target RNA (rHP1) and frameshifting stimulation, highlighting the context-dependent nature of this modification. To assess the broader applicability of the s2U-Q motif, we examined its effect in dbPNAs targeting the RNA panhandle structure of influenza virus A and precursor microRNA-21, respectively. Both PAGE and BLI data confirm that s2U incorporation improves binding affinity, reinforcing the generality of this strategy. These findings underscore the potential of sequence-dependent uracil thiolation in optimizing triplex-forming dsRNA-binding PNAs, warranting further exploration of modified nucleobase designs to enhance their binding and functional properties. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/662161v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@15d86aborg.highwire.dtl.DTLVardef@1347369org.highwire.dtl.DTLVardef@852040org.highwire.dtl.DTLVardef@84b0a_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIThiolation of uracil upstream of Q base in PNA markedly enhances triplex binding affinity and enables isoenergetic and orthogonal targeting/activation. C_LIO_LIN-terminal s2U modification adjacent to Q residues increases PNA-dsRNA binding by [~]10-fold and significantly boosts ribosomal frameshifting efficiency. C_LIO_LIBiophysical assays and molecular dynamics simulations reveal that thiolation improves PNA stacking stability and slows dissociation, thereby enhancing functional activity toward structured RNA targets. C_LIO_LIThe general applicability of s2U modification is demonstrated with influenza A virus RNA panhandle structure and precursor micoRNA-21 targets, underscoring its broad potential for optimizing PNA-based therapeutics and biotechnological tools. C_LI

biochemistry↗

bioRxiv2025

Identifying Optimal Machine Learning Approaches for Microbiome-Metabolomics Integration with Stable Feature Selection

Microbiome research is often limited by methodological inconsistencies that reduce reproducibility and functional insight. Traditional taxonomy-based profiling is limited by sparse data, variable resolution, and reliance on gDNA sequencing which provides only indirect links to microbial function. Multi-omics integration offers a framework for linking community composition to functional outputs, but progress has been hindered by the lack of standardized frameworks and inconsistent use of machine learning. In particular, feature selection stability, which is central to biomarker discovery and experimental validation, remains underexplored. Here, we systematically benchmarked three widely used algorithms (Elastic Net, Random Forest, XGBoost) across seven multi-omics integration strategies and single-omics models. Additionally, we evaluated the impact of transforming metabolomics and taxonomic abundance data. Using human gut microbiome datasets that integrate metagenomic taxonomic profiles with metabolomics, we evaluated models for 9 binary and 8 continuous outcomes across 20 train/test splits per dataset. We further assessed the effect of feature reduction on both predictive accuracy and feature selection stability. Nonlinear learners were most consistently competitive: continuous outcomes favored metabolomics-dominant models, whereas binary outcomes favored stacked multi-omics models. Random Forest and XGBoost also yielded greater feature selection stability, particularly for full dimensional metabolomics data. Together, these findings demonstrate how integration strategy, algorithm choice, and data preprocessing jointly shape predictive performance and feature selection reproducibility in multi-omics microbiome modeling.

bioinformatics↗

bioRxiv2025

Splicing factor SRSF1 is a pH-stat to restore nucleolar integrity and function

Nucleolus is a multiphase biomolecular assembly containing three distinct subcompartments. Evidence is just emerging that nucleolar proteins with characteristic electrochemical properties condense to generate a pH gradient, which serves as a key driving force to organize the nucleolar sub-phases. Given the indispensable functionality of nucleolus in most, if not all, of the cellular activities, it is vital for a cell to sense potential fluctuation in the nucleolar pH and subsequently maintain the pH homeostasis. The mechanisms how a cell achieve this task remains poorly decoded. Here, we show that splicing factor SRSF1 is shuttled from nuclear speckles (NSs) to the nucleolus in times of stress that interrogates the nucleolar pH. SRSF1 nucleolar localization is reliant on an acidic patch and molecular interactions with a nucleolar-resident protein, DDX18. Loss of SRSF1 impedes pH homeostasis in the nucleolus, and subsequently obstructs the restoration of the nucleolar multiphase and function. The arginine residues in the RS (arginine/serine rich) domain of SRSF1, endowed by high isoelectric point (pI), directly alkalize the nucleolar microenvironment. Interestingly, synthetic arginine-rich dipeptides derivative of SRSF1 RS domain safeguard nucleolus from pH and functional disturbance. Our findings uncover unprecedented mechanistic insights into nucleolar pH-sensing and regulation.

cell biology↗

bioRxiv2025

Super-Resolution Diffusivity Mapping Reveals Spatial Correlations Between Lateral Mobility and Structural Heterogeneities on Cellular Membranes

Cellular membranes orchestrate critical processes such as molecular transport and signal transduction, both regulated by the lateral mobility of lipids and proteins. However, resolving nanoscale diffusional heterogeneities and elucidating their underlying mechanisms remains a formidable challenge due to the membranes intricate architecture and compositional diversity. Here, we present point-cloud single-molecule diffusivity mapping (pc-SMdM), a cutting-edge super-resolution technique that offers a point-cloud data format with enhanced spatial resolution for diffusivity mapping. Using pc-SMdM, we visualize nanoscale diffusion slowdown clusters with [~]50 nm in diameter on plasma membranes. These clusters are predominantly governed by cholesterol content, alongside contributions from membrane protein assemblies and topographical features. Leveraging two-color pc-SMdM, we concurrently imaged multiple lipids and membrane probes, revealing distinct "fingerprint" diffusivity maps shaped by their interactions within lipid bilayers. Our findings position pc-SMdM as a transformative tool for spatially resolving molecular interactions and membrane dynamics in live cells, offering new insights into the underlying mechanisms that govern membrane mobility at the nanoscale.

biophysics↗

bioRxiv2025

Attention Guided Mechanism Interpretable Drug-Gene Interaction (MIDI) Modeling for Cancer Drug Response Prediction and Target Effect Explanation

Cancer drug discovery using genetic information is still poorly developed. Precisely locating drug atoms and explaining the targeting effect is crucial in precision medicine since it helps understand the drugs mechanism of action. Much data has been collected regarding drug response against cancer cell lines, and many models predict the drug response based on genomic information. However, to our knowledge, none of the data-driven techniques propose to detect the targeting mechanism of small drug molecules against genetic targets. In this work, we propose MIDI (Mechanism Interpretable Drug-Gene Interaction) model to delve deep into the targeting relation between drug molecules against genetic patterns. We show that purely based on a data-driven approach, the attention mechanism in our model could capture the important binding effect of small molecules towards gene targets. We provide both theoretical derivation and experiment results to show the information flow regarding the attention mechanism. In the meantime, we demonstrate that our model presents much higher prediction performance with the interpretation mechanism than the other state-of-the-art drug response prediction models.

cancer biology↗

bioRxiv2025

Quantitative and large-scale investigation of human TCR-HLA Cross-Reactivity

The interaction between Human leukocyte antigens (HLA) and T cell receptor (TCR) is essential for adaptive immune recognition. While it is known that one TCR can map to multiple HLA alleles, the extent of this cross-reactivity remains poorly understood. Here, we introduce THNet, a TCR-based HLA similarity inference method, and performed a comprehensive analysis of HLA-TCR cross-reactivity. This method is built upon clustering over 47 million TCRs to identify over 9 million significant HLA-TCR pairs. We created similarity networks for both class I and class II HLA alleles, illustrating how peptide cross-presentation contributes to HLA-TCR cross-reactivity. This analysis revealed novel disease-susceptibilities missed by single-HLA enrichment analyses, especially in the Black populations. Finally, we demonstrated that THNet prioritized optimal HLA mismatch candidates for organ transplantation, thereby improving patient survival rates. Our investigation of HLA-TCR cross-reactive network might provide useful insights for autoimmune risk prediction and better transplantation outcomes. One Sentence SummaryWe introduced THNet, a large-scale TCR-based HLA similarity mapping network that uncovers previously unrecognized cross-reactivity patterns across HLA alleles and provides valuable insights into their influence on disease susceptibility and graft rejection.

bioinformatics↗

bioRxiv2025

Spatial distribution of the proteome in human body and cancers

A comprehensive spatial distribution of the proteome in human body and cancers is fundamental for understanding human biology and diseases including cancers. Here, we present an anatomically resolved human proteome derived from 1781 benign and malignant samples from 58 major tissue types encompassing 251 specific tissues and 25 carcinomas. Based on a spectral library covering over 75% of the human protein-coding genes with 208 understudied and 82 missing proteins characterized, we quantified over 13,000 proteins in these samples using data-independent acquisition proteomics. This data resource presents the so far most comprehensive quantitative proteomic landscape of human tissues and common carcinomas. It allows systematic evaluation of tissue-specific drug responses, identification of drug candidates that may be repurposed as antineoplastics, and discovery of novel targets for anticancer therapy. This resource, available as an online knowledgebase, refines our knowledge of spatial distribution of the human proteome and tumor-specific protein modulation.

systems biology↗

bioRxiv2025

Single cell resolved spatial immune repertoire unveils spatial heterogeneity of lymphoid aggregates in human immune disorders

Adaptive immunity, mediated by T and B cell responses, is essential for defending against infections and cancers while also being implicated in autoimmune diseases. Tracking T and B cell repertoires in situ at single-cell resolution is essential for understanding adaptive immune responses. To address the lack of tools for in situ single-cell T/BCR (XCR) sequencing, we developed Stereo-XCR-seq, an efficient strategy for retrieving and sequencing TCR and BCR from Stereo-seq cDNA libraries at subcellular resolution. Stereo-XCR-seq provides unbiased full-length XCR reads alongside spatial transcriptomics, enabling the identification of heterogeneous lymphoid aggregates with distinct clonal activities in cancers and inflammatory bowel disease (IBD). We identified plasma cell aggregates that differ from tertiary lymphoid structures (TLSs) in both transcriptomic profiles and clonal activities, with spatial positioning potentially mediating unique immune responses. Collectively, Stereo-XCR-seq enables in situ single-cell profiling of T and B cell clonal activities within tissue microenvironments, providing insights into lymphocyte adaption to environmental stimuli. This technology provides potential for advancing our understanding of tissue immunity and the development of therapeutic strategies for immune disorders.

immunology↗

bioRxiv2024

Inbreeding and demography interact to impact population recovery from bottlenecks

Biodiversity loss driven by climate change and human activities poses a critical global challenge. Population restoration and reintroduction programs are essential for mitigating this threat, yet their outcomes are often unpredictable due to poorly understood success factors. The conservation program of the crested ibis (Nipponia nippon) marks a successful example where the population rose from seven survivors to over 9,000 in the past four decades. To learn whether this successful restoration was due to chance or largely repeatable, we developed an individual-based model that simulates the restoration process by incorporating life-history parameters from empirical data. Our simulation results closely mirror empirical findings, including the time taken to reach the current population size and population-level inbreeding coefficients. We further analyzed the model to compare the effectiveness of two reintroduction strategies and analyzed how inbreeding depression interacts with demography to influence the chance of recovery from bottlenecks. The reintroduction simulations reveal that the firework approach (one-source translocations) outperforms the stepping-stone (serial translocations) approach in restoration effectiveness. Our simulations over broad demographic parameters demonstrate that the net effect of inbreeding varies with species-specific demography, and highlight the importance of considering this interaction when interpreting conservation outcomes and designing future reintroduction programs.

ecology↗

bioRxiv2024

Birds migrate longitudinally in response to the resultant Asian monsoons of the Qinghai-Tibet Plateau uplift

The uplift of the Qinghai-Tibet Plateau is one of the greatest geological events on Earth, pivotally shaping biogeographic patterns across continents, especially for migratory species that need to overcome topographical barriers to fulfil their annual circle. However, how the uplift influences animal migration strategies remains largely unclear. We compare the current flyways of 50 avian species migrating across the plateau with those reconstructed before the uplift as a counterfactual. We find that the major effect of the plateau uplift is changing avian migratory directions from the latitudinal to the longitudinal. The monsoon system generated by the uplift rather than the high elevation per se shapes those changes. These findings unveil how an important global geological event has influenced biogeographic patterns of migratory birds, yielding testable hypotheses for how observed avian distributions emerge.

ecology↗

bioRxiv2024

AMPGLDA: Predicting LncRNA-Disease Associations Based on Adaptive Meta-Path Generation and Multi-Layer Perceptron

Increased evidence suggests that long non-coding RNA (lncRNA) holds a vital position in intricate human diseases. Nonetheless, the current pool of identified lncRNA linked to diseases remains restricted. Hence, the scientific community emphasizes the need for a reliable and cost-effective computational approach to predict the probable correlations between lncRNA and diseases. It would facilitate the exploration of the underlying mechanisms of lncRNA in ailments and the development of novel disease treatments. In this study, we propose a novel approach for predicting the associations between lncRNAs and diseases, which relies on the adaptive meta-path generation (AMPGLDA). Firstly, we integrate information about lncRNA, diseases, and miRNAs to construct a heterogeneous graph. Then, we utilize principal component analysis to extract global features from nodes. Based on this heterogeneous graph, AMPGLDA adaptively generates multiple meta-path graph structures and uses a graph convolutional neural network to learn the semantic feature representations of lncRNA and disease from the meta-path. Ultimately, AMPGLDA utilizes a deep neural network classifier to accurately predict the association between lncRNA and disease. The AMPGLDA model achieves impressive results, with AUC and AUPR scores of 99.66% and 99.66%, respectively, under the independent test set. Furthermore, three case studies demonstrate its accuracy in discovering new lncRNA-disease associations.

bioinformatics↗

bioRxiv2024

Structural and Biophysical Dynamics of Fungal Plasma Membrane Proteins and Implications for Echinocandin Action in Candida glabrata

Fungal plasma membrane proteins represent key therapeutic targets for antifungal agents, yet their structure and spatial distribution in the native context remain poorly characterized. Herein, we employ an integrative multimodal approach to elucidate the structural and functional organization of plasma membrane protein complexes in Candida glabrata, focusing on prominent and essential membrane proteins, the polysaccharide synthase {beta}-(1,3)-glucan synthase (GS) and the proton pump Pma1. Cryo-electron tomography (cryo-ET) and live cell imaging reveal that GS and Pma1 are heterogeneously distributed into distinct plasma membrane microdomains. Treatment with caspofungin, an echinocandin antifungal that targets GS, alters the plasma membrane and disrupts the native distribution of GS and Pma1. Based on these findings, we propose a model for echinocandin action that considers how drug interactions with the plasma membrane environment lead to inhibition of GS. Our work underscores the importance of interrogating the structural and dynamic characteristics of fungal plasma membrane proteins in situ to understand function and facilitate precisely targeted development of novel antifungal therapies.

cell biology↗

bioRxiv2024

Recognition of RNA secondary structures with a programmable peptide nucleic acid-based platform

RNA secondary structures comprise double-stranded (ds) and single-stranded (ss) regions. Antisense peptide nucleic acids (asPNAs) enable the targeting of ssRNAs and weakly formed dsRNAs. Nucleobase-modified dsRNA-binding PNAs (dbPNAs) allow for targeting of relatively stable dsRNAs. A programmable RNA structure-specific targeting strategy is needed for simultaneous recognition of dsRNAs and ssRNAs. Here, we report on combining dbPNAs and asPNAs (designated as daPNAs) for the targeting of dsRNA-ssRNA junctions. Our binding and modeling data suggest that combining traditional asPNA (with a 4-letter code: T, C, A, and G) and dbPNA (with a 4-letter code: T or s2U, L, Q, and E) scaffolds facilitates RNA structure-specific tight binding (nM to M) under physiologically-relevant conditions. We further applied our daPNAs in substrate specific inhibition of Dicer acting on pre-miR-198 in a cell-free assay and regulating ribosomal frameshifting induced by model hairpins in both cell-free and cell culture assays. daPNAs would be a useful platform for developing chemical probes and therapeutic ligands targeting RNA. HighlightO_LIWe demonstrated that sequence- and structure-specific targeting of RNA can be facilitated by nucleobase-modified dsRNA-binding PNAs (dbPNAs) platform in combination with antisense PNAs (asPNAs). We name the novel PNAs as daPNAs. C_LIO_LIdaPNAs can be used in a programmable way for targeting RNAs by formation of a short triplex next to a short duplex at a dsRNA-ssRNA junction. C_LIO_LIWe applied our daPNAs in substrate specific inhibition of Dicer acting on pre-miR-198 in a cell-free assay and regulating ribosomal frameshifting induced by model hairpins in both cell-free and cell culture assays. C_LIO_LIThe daPNAs platform would serve as useful junction-specific molecular glues for the targeting of many biologically important RNA structures in transcriptomes. C_LI

biochemistry↗

bioRxiv2024

Calcium-dependent regulation of neuronal excitability is rescued in Fragile X Syndrome by a tat-conjugated N-terminal fragment of FMRP

Fragile X Syndrome arises from the loss of Fragile X Messenger Ribonucleoprotein (FMRP) needed for normal neuronal excitability and circuit functions. Recent work revealed that FMRP contributes to mossy fiber LTP by adjusting Kv4 A-type current availability through interactions with a Cav3-Kv4 ion channel complex, yet the mechanism has not yet been defined. In this study using wild-type and Fmr1 knockout (KO) tsA-201 cells and cerebellar sections from Fmr1 KO mice, we show that FMRP associates with all subunits of the Cav3.1-Kv4.3-KChIP3 complex, and is critical to enabling calcium-dependent shifts in Kv4.3 inactivation to modulate A-type current. Specifically, upon depolarization Cav3 calcium influx activates dual specific phosphatase 1/6 (DUSP1/6) to deactivate ERK1/2 (ERK) and lower phosphorylation of Kv4.3, a signalling pathway that does not function in Fmr1 KO cells. In Fmr1 KO mouse tissue slices cerebellar granule cells exhibit a hyperexcitable response to membrane depolarizations. Either incubating Fmr1 KO cells or in vivo administration of a tat-conjugated FMRP N-terminus fragment (FMRP-N-tat) rescued Cav3-Kv4 function and granule cell excitability, with a decrease in the level of DUSP6. Together these data reveal a Cav3-activated DUSP signalling pathway critical to the function of a FMRP-Cav3-Kv4 complex that is misregulated in Fmr1 KO conditions. Moreover, FMRP-N-tat restores function of this complex to rescue calcium-dependent control of neuronal excitability as a potential therapeutic approach to alleviating the symptoms of Fragile X Syndrome. Significance StatementChanges in neuronal excitability and ion channel functions have been a focus in studies of Fragile X Syndrome. Previous work identified ion channels that are regulated by FMRP through either protein translation or direct protein-protein interactions. The current study reveals FMRP as a constitutive member of a Cav3-Kv4 complex that is required for a Cav3-DUSP-ERK signalling pathway to increase A-type current and reduce cerebellar granule cell excitability. In Fmr1 KO cells, Cav3-Kv4 function and calcium-dependent modulation of A-type current is lost, leading to a hyperexcitable state of cerebellar granule cells. Pretreating with FMRP-N-tat restores all Cav3-Kv4 function and granule cell excitability, providing support for FMRP-tat peptide treatment as a potential therapeutic strategy for Fragile X Syndrome.

neuroscience↗