Biology subjects

Li, N.

Publications and source records attributed to Li, N..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Metabolic reshaping drives novel melanin production from tryptophan in a cystic fibrosis Pseudomonas aeruginosa clinical isolate

Pseudomonas aeruginosa is a human opportunistic pathogen, capable of producing a wide range of metabolites, including pyomelanin. This pigment results from alterations in tyrosine catabolism. Melanin synthesis from tryptophan has never been reported in Pseudomonas. In this study, we describe a tryptophan-derived melanin in P. aeruginosa PAH, a strain that was isolated from a fibrocystic patient. PAH produced a brown pigment when grown in LB or L-tryptophan-supplemented media. Structural analysis revealed this pigment was composed by two fractions differing in NaOH solubility: a soluble one consistent of pyomelanin, and an insoluble fraction with a complex structure containing substituted indolic units. A pyomelanin inhibitor enhanced total melanin synthesis, mainly the insoluble fraction, and a tryptophan 2,3-dioxygenase inhibitor decreased pigment formation. Metabolomic profiling identified distinct indolic compounds and low levels of anthranilate in PAH cultures. Genomic and transcriptomic analyses revealed the presence of mutations and downregulation of genes related to pyoverdine biosynthesis. Furthermore, iron supplementation in the culture medium reduced melanin production. Overall, tryptophan arises as a key compound for melanin production in PAH, expanding the diversity of melanins synthesized by this genus. Furthermore, iron deprivation emerges as a critical factor triggering melanin biosynthesis, probably as a survival strategy enabling persistence in the fibrocystic lung environment.

microbiology↗

bioRxiv2025

Fast Loading and Transformation of Large-Volume Bioimaging Data Consistently Approaching the I/O Peak Speed

High-resolution large-volume biological imaging techniques are now widely used in biological research, but inefficiencies in data processing and visualization persist due to bottlenecks in loading/saving pipelines and limitations of conventional pyramid formats. To address these issues, we have decoupled data loading process into reading from disk and in-memory decompression, while data saving has been separated into in-memory compression and writing to disk. This approach allows us to dedicate more CPU cores to decompression and compression tasks, optimizing resource allocation and maximizing disk I/O throughput. As a result, both loading and saving processes operate near the disks peak data transfer capacity. Further, we integrated a video stream-inspired format into the pyramid structure, allowing direct access to regions of interest (ROIs) without loading extraneous data into RAM, reducing memory overhead. Compared to the latest methods, our approach improves pyramid data transformation efficiency by at least 6x and dramatically accelerates downstream tasks like visualization and deep learning inference. TeaserNovel bioimaging data processing pipeline achieves near-peak I/O throughput via decoupled architecture and video-formatting.

bioinformatics↗

bioRxiv2025

React-to-Me: A Conversational Interface for Interactive Exploration of the Reactome Pathway Knowledgebase.

The Reactome Pathway Knowledgebase (www.reactome.org) provides expert-curated information on human biological pathways, molecular interactions, and disease mechanisms. However, its complex data model and keyword-based search interface present accessibility barriers for non-expert users. In contrast, general-purpose conversational AI systems offer intuitive natural language interfaces but lack the domain-specificity, transparent sourcing, and factual reliability required for scientific applications. To address this gap, we developed React-to-Me (https://reactome.org/chat), a domain-specific conversational assistant that enables users to query Reactome using natural language while maintaining scientific rigor and source traceability. React-to-Me integrates hybrid retrieval-augmented generation (RAG) with constrained language model generation to ensure that all responses are grounded in curated Reactome content and directly linked to corresponding knowledgebase entries. When internal coverage is insufficient, the system defers to trusted external biomedical sources rather than generating speculative or unverified content. Computational benchmarking confirmed that combining semantic vector search with keyword-based matching substantially improved contextual grounding and factual precision relative to dense-only retrieval baselines. In blinded expert evaluations, grounded responses were more likely to receive higher quality ratings than ungrounded counterparts, with significant gains in factual accuracy, biological specificity, and mechanistic depth. User surveys further indicated strong satisfaction with ease of use, citation reliability, and factual accuracy. These findings demonstrate that domain-specific grounding can markedly improve the reliability and usability of conversational AI for biological knowledge exploration. React-to-Me provides a transparent and scientifically robust interface for accessing and exploring Reactome content and is freely available at https://reactome.org/chat. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/693752v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@1ef0d73org.highwire.dtl.DTLVardef@15c2d4dorg.highwire.dtl.DTLVardef@a2338corg.highwire.dtl.DTLVardef@e639fd_HPS_FORMAT_FIGEXP M_FIG C_FIG

scientific communication and education↗

bioRxiv2025

Design to Data for mutants of β-glucosidase B from Paenibacillus polymyxa: N160L, N160S, N160C, N160M, N160G

Protein design is advancing toward quantitative modeling of enzyme function and stability. However, progress remains limited by the scarcity of standardized experimental datasets for training and benchmarking computational models. The Design to Data (D2D) program addresses this need by generating harmonized measurements of catalytic and stability parameters across an extensive {beta}-glucosidase B (BglB) variant library. Here, we expand the D2D dataset with kinetic and thermal characterization of five single-point BglB variants and the wild-type (WT), including soluble expression, Michaelis-Menten constants (kcat, KM, and kcat/KM), and melting temperature (TM,). Foldit Standalone was used to model the structural effects of the mutations. In this study, a weak but consistent association between Foldit total system energy (TSE) and TM was observed, suggesting local energetic effects that may influence stability. Together with the broader D2D corpus, these data enhance the functional mapping of BglB and provide model-ready benchmarks for developing and evaluating data-driven predictors of enzyme activity and stability.

bioengineering↗

bioRxiv2025

Motor Cortical Output Integrates Distorted Proprioceptive Feedback

Proprioceptive feedback from muscles is essential for continuous monitoring and precise control of limb movement, yet how such peripheral feedback is integrated into ongoing descending motor cortical dynamics remains largely unclear. Here we used precisely timed optogenetic stimulation of forelimb muscles to manipulate proprioceptive signals during a mouse reach-to-consume task. Mice were able to successfully reach and consume despite muscle stimulation-evoked forelimb deviations. Across the cortex, the caudal forelimb area (CFA) was preferentially activated by muscle-specific proprioceptive inputs and contributed to stabilizing perturbed forelimb movement. CFA extratelencephalic (ET) neurons encoded movement kinematics as well as proprioceptive feedback. At neuron population level, proprioceptive perturbations rapidly deflected CFA ET neural trajectories away from the task-relevant manifold yet exerted only limited effects on evolving task dynamics. These results reveal that descending cortical circuit implements activity subspace separation to encode and integrate distorted proprioceptive feedback while preserving task-relevant output.

neuroscience↗

bioRxiv2025

A Precisely Controlled Long-Acting Immunosuppression Platform Enables Prolonged Survival of Vascularized Composite Allografts

Vascularized composite allotransplantation (VCA) restores complex tissue defects but demands lifelong systemic immunosuppression. Oral tacrolimus (TAC) is limited by a narrow therapeutic window, pharmacokinetic variability, adherence challenges, and toxicity. Local delivery could mitigate these issues, yet clinical translation has been hindered by burst release, short duration, and the inability to co-deliver agents. We developed PRECISE (Programmable, REtrievable, Controlled ImmunoSuppression Encapsulator), an injectable, in-situ-forming PLGA depot that achieves long-acting, tightly controlled TAC release via structure-guided co-formulation with drug-binding agents (DBAs). GRAS small molecules (e.g., EGCG, maltotriose) identified by in silico docking and in vitro screening suppressed burst and modulated solvent efflux. Notably, rapamycin (RAPA) served dually as an mTOR inhibitor and a TAC-binding excipient, enabling synchronized dual-agent delivery. PRECISE eliminated burst in vitro and produced coordinated TAC+RAPA release with clinically compatible injectability. In rats, monthly intragraft dosing maintained systemic TAC/RAPA within the therapeutic window ([~]5-10 ng/mL) for >300 days, prolonged hindlimb allograft survival, expanded Tregs, and induced donor-specific hyporesponsiveness. Surgical retrieval of the depot triggered rapid TAC decline, demonstrating reversibility. In a stringent, fully MHC-mismatched porcine VCA model, PRECISE maintained on-target drug levels and extended graft survival beyond 90 days with minimal rejection and preserved vascular integrity. PRECISE is, to our knowledge, the first retrievable, injectable platform to deliver long-acting, dual-agent immunosuppression with controlled kinetics, rapid attainment of therapeutic steady state, and sustained graft protection. Its modular, structure-guided design enables clinical translation across VCA and solid-organ transplantation, delivering precise, durable, and safer immunosuppression.

bioengineering↗

bioRxiv2025

An extensive forward genetic screen identifies the HWS-AGO1 axis as pivotal for target mimicry-mediated miRNA degradation in Arabidopsis

Target RNAs have emerged as key regulators of miRNA stability, thereby influencing development and physiological processes in both plants and animals. The F-box protein HAWAIIAN SKIRT (HWS) has been characterized as a crucial factor in targeted miRNA degradation in plants (pTMD), a process triggered by a specific type of target RNA called target mimicry. However, the precise mechanism by which HWS functions is still poorly understood. We previously established a genetic reporter system based on Short Tandem Target Mimicry of miR160 (STTM160) triggered miR160 degradation, resulting in pleiotropic developmental defects that are easy to monitor. Here, through an extensive forward genetic screen, we identified fourteen additional hws alleles that near-completely restored STTM160-induced developmental defects, highlighting a central role for HWS in pTMD. Intriguingly, we discovered two adjacent amino acid substitutions (R421K and G422D) in the PAZ domain of AGO1 that significantly suppressed the STTM160 phenotype. Similar to HWS dysfunction, the AGO1 R421K substitution caused a significant retention of target mimicry RNAs in AGO1 immunoprecipitates, suggesting that the R421 residue of AGO1 may cooperate with HWS for the clearance of AGO1-miRNA-target mimicry complexes. Although the R/G mutations only impacted a small set of endogenous miRNA levels, they were sufficient to rescue the developmental defects caused by HWS overexpression (HWS-OE), suggesting that the developmental abnormalities caused by HWS-OE largely depend on the AGO1-miRNA pathway. Taken together, our findings provide a solid genetic evidence for the coordination of HWS and AGO1 in pTMD.

plant biology↗

bioRxiv2025

MEDUSA: Maintaining Entire DNA Duplexes for Utmost Sequencing Accuracy

Highly accurate DNA sequencing is essential for many applications. Duplex sequencing-based methods achieve unparalleled accuracy by requiring reads from both strands of the original DNA duplex to match. Yet, methods to prepare dsDNA for sequencing may resynthesize portions of each DNA duplex and cause base damage errors on one strand to become indistinguishable from true mutations on both strands. Here, we report MEDUSA (Maintaining Entire DNA Duplexes for Utmost Sequencing Accuracy) which minimizes dsDNA resynthesis to maximize duplex sequencing accuracy and yield. MEDUSA carefully repairs and blunts fragmented dsDNA, then employs apyrase to digest residual dNTPs, followed by restricted dA-tailing to prevent resynthesis. MEDUSA affords full genome coverage in a simplified protocol that is broadly compatible with dsDNA fragmentation and library preparation kits. We benchmarked MEDUSA on sheared genomic DNA and cell-free DNA and found a residual SNV frequency within a median 1.23-fold (range 0.92-1.88; p < 0.001) of what was expected if resynthesis was mostly blocked, but with full genome coverage and duplex yields within a median 1.02-fold (range 0.33 - 1.46; p = 0.258) of traditional methods that do not limit resynthesis. In all, MEDUSA could enable high breadth or depth of duplex sequencing while limiting false discovery. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/687202v1_ufig1.gif" ALT="Figure 1"> View larger version (12K): org.highwire.dtl.DTLVardef@1ddbc77org.highwire.dtl.DTLVardef@802ca9org.highwire.dtl.DTLVardef@f443ecorg.highwire.dtl.DTLVardef@974bdb_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2025

Structural and functional insights into QueC-family protein in QatABCD anti-phage system

QatABCD is a widespread prokaryotic anti-phage defense system comprising four protein components, out of which QatC, a QueC-family protein is the signature component. QueC family proteins are nucleoside biosynthesis enzymes involved in the biosynthesis of queuosine, a 7-deazaguanine derivative. Recently, QueC-family proteins were shown to catalyze a deazaguanylation protein-nucleobase conjugation reaction in type IV CBASS antiphage defense. However, the mechanism of QatABCD, even the function of QatC in this system, remains unknown. Here, we demonstrate that QatBCD forms a complex in which QatD is highly flexible. Crystal structures of the QatBC complex in apo and ATP-bound form support a shared role for QueC-family proteins in targeting protein substrates for N-terminal modification as in type IV CBASS. We show that the QatB N-terminal loop, its binding with QatC and QatC catalytic site are essential for QatABCD defense in vivo, suggesting a modification might occur analogous to CBASS. These findings provide structural and functional insights into QueC-family protein in QatABCD system, suggesting the conserved mechanisms and critical roles of QueC-family in prokaryotic immunity.

biochemistry↗

bioRxiv2025

Zwitterionic hydrogel designs for conducting polymers enable bioelectronics with suppressed foreign body response

For long-term, continuous operation of implantable biosensors and electrophysiological devices, the foreign body response (FBR) is a major obstacle that needs to be overcome. As the FBR progresses, any implanted device will become damaged and isolated from its physiological environment, due to encapsulation by fibrotic tissue and inflammatory immune cells. To achieve more compatible and low-impedance biointerfaces, conducting polymers, such as PEDOT:PSS, have been extensively explored as ideal materials. However, FBR on such conducting polymers remains an unmet challenge. We report a zwitteronic-hydrogel-based double-network design for PEDOT:PSS that can significantly suppress the FBR by 64%, in addition to improving conductivity by more than one order of magnitude. Surprisingly, the FBR level of this design is even lower than that of the parent zwitteronic hydrogel by 53%. Our further immunological investigations at the histological, cellular, and transcriptomic levels give deeper insights into the unique effects that come from the chemical heterogeneity. Furthermore, chronic electrocardiographic recording in mice demonstrate the benefit of this material design to long-term, implanted electrophysiology, which provides indications for the future development of immunocompatible electronic polymers.

bioengineering↗

bioRxiv2025

Integrative k-mer and Transcriptomic Analysis Reveals Putative Sex-Determining Genes in Spinacia turkestanica

Deciphering the regulation of sex-determining gene/s in dioecious crops is crucial for molecular breeding. However, the identification of sex-determining gene/s in Spinacia is challenging due to incomplete genome assemblies, high genomic similarity between males and females, and the limitations of transcriptome-only analyses, which may miss unannotated or novel genes in poorly assembled or absent genomic regions. To overcome these limitations, we employed a reference-genome-free k-mer approach to identify candidate sex-determining genes in Spinacia turkestanica, the closest evolutionary relative of cultivated spinach (S. oleracea). Male-specific reads were de novo assembled into contigs, revealing 21.5 Mb of the sex-determining region (SDR). Using the MAKER pipeline, which integrates transcriptomic and proteomic evidence, we predicted 226 protein-coding genes within the SDR, including nine previously unannotated. Transcriptomic profiling combined with weighted gene co-expression network analysis identified eight SDR DEGs, including two newly annotated genes, co-expressing during early male flower development. qPCR validation confirmed three SDR genes as candidate sex-determining factors, including TU_SDR00087 (bZIP domain), TU_SDR000168 (RNA-binding splicing factor domain), and TU_SDR000174 (MYB domain). Together, these findings provide a foundation for functional characterization of sex determination in Spinacia. HighlightA k-mer based analysis uncovered male-specific regions and candidate sex-determining genes in Spinacia turkestanica, advancing understanding of sex regulation and spinach breeding.

genetics↗

bioRxiv2025

DeviceAgent: An autonomous multimodal AI agent for flexible bioelectronics

The development of flexible bioelectronics remains a complex, multidisciplinary process that demands specialized expertise and labor-intensive efforts, limiting scalability, adaptability and accessibility. Here, we introduce DeviceAgent, an autonomous multimodal AI agent that integrates large language models (LLMs), vision-language models (VLMs), and domain-specific computational tools into a unified framework for bioelectronics research. Leveraging the emergent reasoning abilities of LLMs and VLMs, DeviceAgent enables zero and few-shot generalization, contextual learning, and flexible task execution across modalities. A multimodal context memory system orchestrates these capabilities, providing end-to-end support across the experimental pipeline-from high-level design objectives to fabrication protocol generation, visual defect inspection, and electrophysiological signal analysis, while maintaining human oversight at critical decision points. We demonstrate its capabilities through the development of stretchable mesh electronics for interfacing with human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), a representative application involving complex device architectures, heterogeneous material nanofabrication, and electrophysiology analysis. DeviceAgent autonomously (1) generates customized bioelectronic layouts; (2) creates comprehensive fabrication protocols tailored to specific materials and processes; (3) identifies microscopic defects using visual reasoning; and (4) analyzes cardiac electrophysiological recordings in an interpretable manner. By embedding LLMs and VLMs within a structured, tool-augmented architecture, DeviceAgent establishes a scalable and accessible paradigm for AI-scientist collaboration in nanofabrication and bioelectronics research.

bioengineering↗

bioRxiv2025

Agro-STARR-seq enables in planta genome-wide enhancer discovery and AI-empowerd enhancer design

Comprehensive enhancer screening is essential for dissecting gene regulatory networks. However, methods for such screening remain limited in plants. We present Agro-STARR-seq, an in planta enhancer screening platform using Agrobacterium-mediated delivery of STARR-seq libraries into Nicotiana benthamiana leaves. In the Arabidopsis genome, we identified 14,715 sequences with enhancer activity, of which 91.59% were located outside of open chromatin regions. This largest in planta enhancer dataset to date enabled AI-assisted design of highly active synthetic enhancers. For the large N. benthamiana genome, we pre-processed the genomic DNA with an Assay for Transposase Accessible Chromatin (ATAC) procedure before the Agro-STARR-seq protocol,and found that only one-third of open chromatin exhibited enhancer activity, 76.00% of which showed no canonical H3K27ac histone marks. Footprinting analysis further enables systematic linkage of transcription factor (TF) binding to enhancer function. Overall, Agro-STARR-seq provides a novel platform for dissecting and engineering plant enhancers.

genomics↗

bioRxiv2025

Structural and Functional Characterization of Encapsulin-Targeted Double Ferritin Fold Ferroxidases

Ferritins are a widespread family of proteins involved in iron homeostasis. While classic ferritins consist of four -helices and form 24-meric nanocages, related ferritin-like proteins display other types of assemblies and sometimes lack any iron storage capacity. Here, by analyzing the available genomic data, we identify a family of double ferritin-like proteins (DFLPs) composed of two four-helical domains, which arose by duplication of a ferritin fold protein. We characterize representative DFLPs from Thermocrinis minervae and Caldanaerovirga acetigignens, TmDFLP and CaDFLP, and show that they form homodimers and bind heme. We determine the X-ray structure of TmDFLP and demonstrate its ferroxidase activity. Furthermore, we show that some DFLPs, including TmDFLP and CaDFLP, are highly likely to be targeted into encapsulin shells. Our work expands the range of known iron metabolism systems and highlights the power of genome mining for discovery of new proteins. Graphical Abstract for Table of Contents O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=64 SRC="FIGDIR/small/676036v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@72e6b0org.highwire.dtl.DTLVardef@18752fforg.highwire.dtl.DTLVardef@15a02e7org.highwire.dtl.DTLVardef@74cd02_HPS_FORMAT_FIGEXP M_FIG C_FIG A family of double ferritin-like proteins (DFLPs) composed of two four-helical domains is described and investigated. DFLPs are shown to form homodimers, bind heme, possess diiron sites and display ferroxidase activity. Some DFLPs are shown to be targeted to encapsulin shells as core or secondary cargo, thus representing a new type of iron metabolism systems.

biochemistry↗

bioRxiv2025

An AI Agent for cell-type specific brain computer interfaces

Decoding how specific neuronal subtypes contribute to brain function requires linking extracellular electrophysiological features to underlying molecular identities, yet reliable in vivo electrophysiological signal classification remains a major challenge for neuroscience and clinical brain-computer interfaces (BCI). Here, we show that pretrained, general-purpose vision-language models (VLMs) can be repurposed as few-shot learners to classify neuronal cell types directly from electrophysiological features, without task-specific fine-tuning. Validated against optogenetically tagged datasets, this approach enables robust and generalizable subtype inference with minimal supervision. Building on this capability, we developed the BCI AI Agent (BCI-Agent), an autonomous AI framework that integrates vision-based cell-type inference, stable neuron tracking, and automated molecular atlas validation with real-time literature synthesis. BCI-Agent addresses three critical challenges for in vivo electrophysiology: (1) accurate, training-free cell-type classification; (2) automated cross-validation of predictions using molecular atlas references and peer-reviewed literature; and (3) embedding molecular identities within stable, low-dimensional neural manifolds for dynamic decoding. In rodent motor-learning tasks, BCI-Agent revealed stable, cell-type-specific neural trajectories across time that uncover previously inaccessible dimensions of neural computation. Additionally, when applied to human Neuropixels recordings-where direct ground-truth labeling is inherently unavailable-BCI-Agent inferred neuronal subtypes and validated them through integration with human single-cell atlases and literature. By enabling scalable, cell-type-specific inference of in vivo electrophysiology, BCI-Agent provides a new approach for dissecting the contributions of distinct neuronal populations to brain function and dysfunction.

neuroscience↗

bioRxiv2025

PAQman: reference-free ensemble evaluation of long-read eukaryotic genome assemblies

Advances in long-read sequencing have made it easier and more cost effective to generate high-quality genome assemblies. However, assessing assembly quality remains a challenge, as existing tools often focus on a few metrics and/or require a reference assembly for comparison. Furthermore, the number of available metrics and associated tools for genome evaluation have expanded in recent years, making it more difficult for researchers to easily use and develop comprehensive pipelines. To address this, we developed the Post-Assembly Quality manager (PAQman), a tool that lowers the barrier to entry for assembly quality assessment by measuring seven reference-free features of genome quality within a single framework: Contiguity, Gene content, Completeness, Accuracy, Correctness, Coverage, and Telomerality. PAQman integrates multiple commonly used tools alongside custom scripts, requiring users to provide only a query genome assembly and its underlying long-read data, while providing a streamlined and consistent framework for quality assessment across datasets. Impact StatementPAQman is an ensemble-based tool for comprehensive, reference-free evaluation of genome assemblies derived from long-read sequencing data. The simultaneous integration of seven quality features enables users to easily assess assembly quality within a standardized, reproducible framework across diverse organisms, while lowering the barrier to entry for biologists analyzing their data.

bioinformatics↗

bioRxiv2025

Identification of novel human cellular substrates of Staphylococcus aureus serine protease SplB

Staphylococcus aureus colonizes up to one third of the human population yet retains the capacity to cause invasive, life-threatening infections. The growing prevalence of antimicrobial resistance further complicates treatment. A major contributor to the versatility of S. aureus is its broad repertoire of virulence factors, among which secreted proteases facilitate dissemination from colonization sites into deeper tissues. Twelve extracellular proteases are secreted, with the serine protease-like protein (Spl) family (SplA-SplF), encoded within a single operon, accounting for half of them. Despite this prominence, the pathophysiological roles and substrate specificities of the Spl proteases remain poorly understood. Here, we employed a direct protein-protein interaction approach to identify novel SplB substrates in human serum. We demonstrate that SplB cleaves three intermediate filament proteins, namely desmin, vimentin, and nestin, as well as heat shock protein {beta}1 and -enolase, which have not previously been recognized as targets of S. aureus proteases. Moreover, SplB was found to cleave native IgG, a feature otherwise described only for the glutamyl endopeptidase V8. These findings expand the host protein repertoire targeted by SplB and suggest broader roles for Spl proteases in immune evasion and tissue invasion.

immunology↗

bioRxiv2025

Segmented poly(A) tails with microRNA target sites confer tissue-specific regulation for mRNA therapeutics

Targeted delivery and controlled expression of mRNA-LNPs are critical for the development of safe and effective mRNA medicines. However, efficient post-delivery regulation of mRNA-LNP expression remains challenging. In this study, we engineered segmented poly(A) tail variants that function as gene-specific regulatory elements for synthetic mRNAs. Specifically, we inserted microRNA target sites (MTS) for miR-122 or miR-142 at various positions of the poly(A) tail of synthesized luciferase reporter mRNA. These modifications significantly reduced luciferase expression in non-target tissues in vitro and in vivo, demonstrating position-dependent selective expression control. Furthermore, by incorporating triple-MTS sequences for miR-142, miR-126, and miR-148a in all possible combinations at the 5 end of the poly(A) tail, we identified triple-MTS arrangements that simultaneously decrease luciferase activities in three non-target hepatic cell types, while preserving robust expression in hepatocytes. The results highlighted the importance of MTS insertion order for optimal mRNA silencing. These triple-MTS modules significantly expanded the utility of single miRNA-responsive elements, enabling cell-type selective regulation for mRNA therapeutics. By complementing tissue-tropic delivery LNPs, our mRNA cargo regulatory elements have the potential to improve tissue and cell type selectivity as a novel platform for post-delivery regulation of mRNA-LNP.

bioengineering↗