Biology subjects

Cui, Y.

Publications and source records attributed to Cui, Y..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Brain endothelial PRMT5-ANGPTL4 axis regulates cerebellar inhibitory synaptogenesis and motor coordination

Brain vasculature is essential for central nervous system function, but its specific roles in synaptic development and motor function regulation are poorly understood. In this study, we identify a cerebrovascular signaling axis wherein endothelial PRMT5 critically regulates inhibitory synaptogenesis and motor coordination. Cerebrovascular-specific deletion of Prmt5 gene leads to excessive inhibitory synaptic input onto Purkinje cells and progressive motor deficits in mice. Mechanistically, PRMT5 deficiency epigenetically upregulates the expression of the secreted factor ANGPTL4 through reduced symmetric dimethylation of H3R8 and H4R3, along with increased H3K9 acetylation at the Angptl4 promoter, thereby driving excessive inhibitory synaptogenesis onto Purkinje cells. Importantly, Angptl4 deletion in brain endothelium normalizes inhibitory synaptic input onto Purkinje cells and restores motor coordination in PRMT5-deficient mice. Together, these findings define the endothelial PRMT5-ANGPTL4 axis as a key regulator of cerebellar inhibitory circuitry and motor function, highlighting cerebrovascular mechanisms as potential therapeutic targets for motor coordination disorders. Teaser Cerebrovascular PRMT5 prevents excessive inhibitory synaptogenesis via epigenetic repression of Angptl4.

neuroscience↗

bioRxiv2025

Evolutionary landscape of oral microbiome over 100,000 years

The human oral microbiome represents an intimate and enduring partnership between host and microbial communities, yet its evolutionary trajectory across deep time remains largely uncovered. Here we reconstruct the global history of the oral microbiome over 102,400 years using a global collection of 1854 oral samples spanning 61 countries. We reveal that major cultural transitions of the Neolithic Revolution, industrialization, and recent medical advances have driven a directional, globally coordinated co-evolution of oral microbial ecology, function, and population structure. Network analysis identifies two universal microbial modules of dental calculus modules: the commensal-enriched DCM1 module and the pathogen-enriched DCM2, both exhibiting progressive ecological polarization. DCM2 surged around 4,000 years ago with agricultural intensification but subsequently declined in modern European populations while persisting at high levels in African and some American groups, a geographic divide mirroring socioeconomic inequities. Species-level analyses demonstrate widespread directional changes, with obligate anaerobes declining as aerotolerant taxa expand, reflecting a carbohydrate-associated functional remodeling toward starch metabolism. Phylogenomic reconstruction reveals contrasting evolutionary trajectories. Pauljensenia mediterranea experienced near-extinction following a severe bottleneck, while Actinomyces israelii underwent a selective sweep with rapid population expansion 1,000 years ago. Critically, the oral resistome has accelerated in the antibiotic era, resulting in [~]33-50-fold surge of highly mobile, clinically relevant antimicrobial resistance genes in the last century, with Streptococcus acting as a central hub of dissemination. Collectively, these results position the oral microbiome as an active participant that has co-evolved with human subsistence, urbanization and medical practice, with direct implications for global oral health, antimicrobial resistance and interventions aimed at restoring resilient microbial states.

microbiology↗

bioRxiv2025

Lung Adenocarcinoma Just Desserts: An Expanding Pie of Activating Oncogenes or a Layer Cake of Integrated Alterations

The molecular landscape of lung adenocarcinoma (LUAD) is often summarized as a "pie chart" of driver oncogenes, suggesting identification and targeting of oncogenic drivers is the best clinical approach. However, this model oversimplifies LUAD biology. Patients with identical RAS or RAF mutations exhibit heterogeneous signaling influenced by co-mutations, transcriptional programs, and lineage context. We propose a hierarchical framework integrating oncogenes within cellular context by examining canonical EGFR mutations. We defined an EGFR mutation signature (mSig) by identifying differentially expressed genes in EGFR-mutant LUADs. Semi-supervised clustering and machine learning models were used to test performance and reproducibility across independent datasets. We analyzed molecular subtypes, lineage markers, co-occurring mutations, and candidate drug targets in EGFR-mSig positive (+) versus negative (-) tumors. The EGFR mSig showed robust classification performance across datasets (AUROC = 0.83-0.95; mean NPV = 96.3%). Validated unsupervised gene expression subtypes and lung lineage markers were closely aligned with EGFR mSig status. mSig(+) tumors were identified, even in tumors without EGFR mutations. A subset of canonical RAS mutations mirrored the EGFR mutation pattern. EGFR-mutant/mSig(-) tumors were enriched for non-Bronchioid subtypes and had co-mutations in TP53 or RAS. Coordinated mutations were identified including RAS, KEAP1, STK11, TP53, and CDKN2A, supportive of prior reports. In sum, novel EGFR mSig that captures the transcriptional footprint of EGFR activation, revealed a subset of EGFR wildtype LUADs with "mutant-like" features. Lineage-informed classification highlights subtype-dependent oncogene activity and supports new therapeutic strategies. A context-specific association between RAS mutation and expression of the dual-specificity phosphatase gene DUSP4 may have therapeutic potential.

genomics↗

bioRxiv2025

SpatialESD: spatial ensemble domain detection in spatial transcriptomics

Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial EnSemble Domain detection method that integrates results from different spatial domain detection methods to improve spatial domain detection. SpatialESD captures both direct co-occurrence patterns and multiscale indirect relationships between clusters, improving the robustness and accuracy of spatial domain detection. We evaluated SpatialESD on simulated datasets and multiple 10x Visium spatial transcriptomics datasets, including human brain, breast cancer, and ovarian cancer samples. The results show that SpatialESD consistently outperforms individual methods and the existing EnSDD ensemble method in terms of clustering accuracy and stability. Based on the identified domains, we further detected region-specific differentially expressed genes and performed trajectory and cell-cell interaction analyses. These results reveal spatial patterns of gene expression and cellular communication, offering insights into tissue organization and disease mechanisms. Overall, SpatialESD provides a reliable and effective solution for spatial domain detection in ST data and facilitates downstream biological discovery. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/675735v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1344724org.highwire.dtl.DTLVardef@12ab936org.highwire.dtl.DTLVardef@1e59d57org.highwire.dtl.DTLVardef@1bcd55f_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

SPACE: spatially resolved multiomic analysis for high-throughput CRISPR screening in 3D models

Current spatial CRISPR screening technologies are limited by targeted readouts and high costs, restricting the scope of biological discovery. Here we present SPAtial Cell Exploration (SPACE), a spatial CRISPR screening platform that integrates whole-transcriptome profiling ([~]18,000 genes), multiplexed protein detection ([~]68 markers), and CRISPR perturbation mapping at subcellular resolution. SPACE significantly reduces whole-transcriptome profiling costs compared to sequencing methods while preserving spatial context. We demonstrate SPACE by screening 43 CRISPR knockouts (KOs) across [~]100,000 cells in hundreds of cancer-associated fibroblast (CAF)-tumor spheroids, obtaining whole-transcriptome and multiplexed protein readout from the same exact cells. SPACE revealed previously unknown regulatory mechanisms on tumor extracellular matrix (ECM) remodeling, and identified spatially-resolved ligand-receptor interactions and perturbation-specific spatial gene signatures that are not detectable with dissociation-based methods. This scalable, cost-effective platform provides a transformative framework for high-throughput spatial perturbation studies in complex tissue models.

cell biology↗

bioRxiv2025

wspA mutation mediated Pseudomonas aeruginosa rugose small colony variant and its hyper-biofilm

Pseudomonas aeruginosa is a major multidrug-resistant pathogen whose biofilm formation complicates treatment. P. aeruginosa rugose small colony variants (RSCVs), characterized by enhanced biofilm production and resistance, pose significant clinical challenges. However, the formation mechanisms remain unclear in clinical strains. Paired clinical P. aeruginosa isolates AR8023-1 (wild-type) and AR8023-2 (RSCV) were collected from urine samples of a neurosurgery inpatient chronologically. The genome comparison was performed using Breseq, and plasmid complementation was performed to construct complemented strain (AR8023-2RifR::wspAAR8023-1). Then, all the aforementioned strains were examined RSCV phenotype, biofilm formation, and motility, and gene expression differences induced by the wspA mutation were analyzed via transcriptome sequencing, followed by quantification of c-di-GMP. In addition, we assessed antimicrobial susceptibility of the strains under both planktonic and biofilm conditions. The results showed that both AR8023-1 and AR8023-2 were identified as ST3420. AR8023-1 exhibited typical smooth morphology, while AR8023-2 displayed a RSCV phenotype. A single SNP difference was identified between the two strains, characterized by a deletion of glutamine at position 289 (CAG triplet deletion) in the wspA gene of strain AR8023-2. The complement isolates restored wild-type morphology, motility, and biofilm formation. Transcriptomics revealed a significant upregulation of c-di-GMP metabolic genes in RSCVs (P < 0.001), indicating that the WspA{Delta}289Q mutation activates diguanylate cyclase (DGC) activity, thereby elevating c-di-GMP synthesis. Intracellular c-di-GMP levels were significantly higher in RSCVs than those in WT and complement isolates, respectively (P < 0.001). Consequently, biofilm susceptibility testing demonstrated the {beta}-lactams MBIC of RSCVs was [≥]8-512-fold higher than those of WT and complement isolates. This study identifies a clinical WspA{Delta}289Q mutation that elevates c-di-GMP, driving RSCV formation and biofilm-mediated resistance. IMPORTANCEP. aeruginosa is a leading multidrug-resistant pathogen whose biofilm formation capability greatly complicates treatment outcomes. This study identifies a novel clinical mutation in the wspA gene (WspA{Delta}289Q) that drives the emergence of rugose small colony variants (RSCVs), a phenotype linked to heightened biofilm production and antimicrobial resistance. We demonstrate that this mutation upregulates cyclic di-GMP synthesis, leading to increased biofilm formation and markedly reduced susceptibility to {beta}-lactam antibiotics under biofilm conditions. These results provide important insights into the genetic basis of RSCV development in clinical settings and highlight the role of c-di-GMP signaling in biofilm-associated resistance. Our findings underscore the need to target c-di-GMP pathways as a potential strategy for combating persistent P. aeruginosa infections.

microbiology↗

bioRxiv2025

TESSA: A unified model to detect trajectory-preserved and spatially-variable genes in spatial transcriptomics

Identifying spatially variable genes (SVGs) has been an essential task in spatial transcriptomics. In addition to SVGs detection, there are genes exhibiting expression patterns that are associated with cellular developmental stages or lineage fates across a tissue section. Identifying such genes could provide novel insights into tumor metastasis. Here, we introduce a unified statistical model, termed TrajEctory-preServed and SpAtially-variable gene detection (TESSA), to detect both types of genes. Moreover, we propose a novel strategy to address the inherent double-dipping issue commonly encountered when assessing temporal gene effects in transcriptomics analysis. We demonstrate the testing performance through extensive simulation studies and real applications to several publicly available datasets. Downstream analyses further highlight the potential of our method in identifying genes associated with tumor progression and enhancing spatial domain detection.

bioinformatics↗

bioRxiv2025

Fusion-driven oncogenic programs shape the immune landscape in translocation renal cell carcinoma

Renal cell carcinomas comprise multiple molecularly distinct cancers but most are treated empirically with therapies designed for clear cell RCC (ccRCC), the most common subtype, due to incomplete understanding of subtype-specific biology. We analyzed single-cell transcriptomes and chromatin accessibility profiles from translocation renal cell carcinoma (tRCC), an aggressive RCC defined by oncogenic TFE3 gene fusions. Unexpectedly, despite arising from a proximal tubule cell of origin similar to ccRCC, tRCCs display markedly distinct oncogenic programs and an immunosuppressive tumor microenvironment. tRCCs exhibit six conserved tumor meta-programs, including epithelial-mesenchymal transition and proximal tubule identity programs whose balance is regulated by TFE3 fusion activity. The fusion-driven EMT program drives a suppressive TME marked by progenitor-exhausted CD8+ T cells, anti-inflammatory SPP1+ macrophages, and matrix-associated fibroblasts (mCAFs). Our findings highlight unique TFE3 fusion-driven biology in tRCC, explaining its reduced immunotherapy responsiveness relative to ccRCC, and suggesting strategies for targeting fusion-driven oncogenic programs and TME reprogramming.

genomics↗

bioRxiv2025

gnSPADE: a reference-free deconvolution method incorporating gene network structures in spatial transcriptomics

Spatial transcriptomics (ST) technologies have offered unprecedented insights into the spatial organization of gene expression, allowing for the study of tissue architecture, domain boundaries, and cell-cell interactions. However, most ST data generated so far are at multicellular resolution, where each spot captures transcripts from a mixture of diverse cells of different cell types. While reference-based deconvolution approaches offer robust solutions, they rely heavily on the availability and quality of external single-cell reference data, which may be incomplete, unavailable, or poorly matched to the spatial data. Moreover, even when such references are available, they often represent only broad cell types, potentially obscuring finer subpopulation structures and masking intra-type heterogeneity. To overcome these limitations, we introduce gnSPADE, a reference-free spatial deconvolution method that incorporates gene network structures via a Markov random field within a latent Dirichlet allocation (LDA) modeling framework. gnSPADE jointly infers cell type-specific transcriptional profiles and spatial compositions without external references. Applied to synthetic and real ST datasets, gnSPADE achieves improved accuracy, spatial resolution, and biological interpretability compared to other methods, highlighting the power of reference-free deconvolution in resolving complex tissues.

bioinformatics↗

bioRxiv2025

Phenotypic screening converges on CDK9 inhibition as a therapeutic strategy in translocation renal cell carcinoma

Translocation renal cell carcinoma (tRCC) is an aggressive kidney cancer driven by gene fusions of the TFE3 transcription factor. TFE3 is essential in tRCC but dispensable in normal cells, presenting an attractive but pharmacologically challenging therapeutic target. We show that the basic helix-loop-helix (bHLH) domain of TFE3 is crucial for chromatin binding and transcriptional function. Via a phenotypic screen of 25,000 compounds, we identified molecules that either displace or retain chromatin-bound TFE3. BRD6866, a compound trapping TFE3 on chromatin, emerged as a pan-CDK inhibitor. Mechanistically, its inhibition of CDK9 - a key regulator of transcriptional elongation - was linked to impaired TFE3 fusion activity. These effects were recapitulated by the CDK9-selective inhibitor enitociclib, which downregulated TFE3 targets and suppressed tRCC cell growth. Our findings nominate CDK9 inhibition as a therapeutic strategy in tRCC and demonstrate the utility of mechanism-informed phenotypic screening for challenging targets.

cancer biology↗

bioRxiv2025

Efficient biosynthesis of 3-hydroxypropionic acid in recombinant Escherichia coli by metabolic engineering

3-Hydroxypropionic acid (3-HP) is a platform compound that can produce many chemical commodities. This study focuses on establishing and optimizing the production of 3-HP in E. coli. We constructed a series of engineered E. coli strains which can produce 3-HP via the malonyl-CoA pathway. To increase the metabolic flux of acetyl-CoA, a precursor for the synthesis of 3-HP, CRISPR/Cas9-based DNA editing technique was used to knock out the genes encoding pyruvate oxidase (poxB), lactate dehydrogenase (ldhA) and phosphate transacetylase (pta), thereby reducing the formation of by-products. Concurrently, the acetyl coenzyme a carboxylase gene (accDABC) is overexpressed on the chromosome with the objective of augmenting intracellular acetyl-CoA levels and, consequently, 3-HP production. Next, we introduced a plasmid containing a codon-optimized malonyl-CoA reductase gene (mcr) into the engineered strain. Finally, we constructed a transcription factor-based metabolite biosensor utilizing the PpHpdR/PhpdH system, followed by the screening of mutant strains for enhanced 3-HP production through adaptive laboratory evolution. Combining the above metabolic engineering efforts with optimisation of media and fermentation conditions, the 3-HP titer of the engineered strain WY7 increased from an initial titer 0.34 g/L to 48.8 g/L. This study encourages further research in metabolic pathway optimizationto produce 3-HP. HighlightsO_LISynthesis 3-HP in the malonyl-CoA pathway. C_LIO_LIEdit the Escherichia coli genome using the CRISPR/Cas9 system. C_LIO_LIElevated production of 3-HP by knocking out bypass genes ldhA/pta/poxB. C_LIO_LIA biosensor was designed to respond to 3-HP concentration. C_LIO_LIAdaptive laboratory evolutionary strategies increase 3-HP production. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/672340v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1f8b65borg.highwire.dtl.DTLVardef@18c23d6org.highwire.dtl.DTLVardef@184edc3org.highwire.dtl.DTLVardef@15bcc2_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2025

Activation-Free Upgrading of Carboxylic Acids to Aldehydes and Alcohols

Advances in organic and gas waste valorization have enabled high-yield production of carboxylic acids, positioning them as promising feedstocks for the bioeconomy. However, carboxylic acids must be activated before downstream use, typically requiring ATP, CoA, or reduced ferredoxin to overcome unfavorable thermodynamics. These activators are costly to generate and divert carboxylic acids into CO2-releasing pathways, reducing carbon efficiency. Here, we demonstrate that aldehyde dehydrogenases (ALDHs) can directly reduce carboxylic acids to aldehydes without prior activation, a process previously thought to be biologically inaccessible. Screening 133 ALDHs revealed that this activity is remarkably widespread within the protein family, enabling production of aliphatic aldehydes and alcohols, diols, and aromatic alcohols, at titers >1 g/L, in some cases, after optimization of thermodynamic driving forces. Additionally, we applied this system to upgrade waste-derived carboxylic acid effluent streams from wastewater sludge, food waste, and waste gas (CO2). This activation-free process, termed "reverse aldehyde oxidation" (rAOX), establishes a broadly applicable, energy-efficient platform for carboxylic acid valorization at 100% carbon yield. Analogous to the reverse tricarboxylic acid cycle (rTCA) and reverse {beta}-oxidation (rBOX), rAOX exemplifies that metabolic reactions classically defined as unidirectional may have unexpected plasticity to operate in reverse and open new avenues in biomanufacturing.

synthetic biology↗

bioRxiv2025

Temporal foundation model unveils ancient HepatitisB virus evolution

Since ancient hepatitis B virus (HBV) sequencing data are scarce and incomplete, the evolutionary dynamics of HBV have long remained enigmatic. This data gap hinders a comprehensive understanding of HBV genetic variations, evolutionary trajectories, and host interactions in different historical periods, preventing insight into its long-standing co-evolutionary relationship with humans. In this study, we developed a sequence-based generative foundational model, ViraChron (Viral Chronology Foundation Model), that integrates multi-scale temporal information to compensate for the lack of ancient HBV data. We confirmed the robustness of our model through sequence identity, phylogenetic, and recombination analyses. ViraChron enabled the identification of fixed mutations specific to HBV genotype A, demonstrating that HBV acquires survival advantages through mutations that are ultimately fixed by natural selection. Our model outperforms the original baseline in terms of sequence completion, achieving significantly higher accuracy. The model significantly reduced data acquisition time from 80 hours to 5.4 minutes per HBV genome, providing reliable, high-quality data for 7 new HBV genomes from specific archeological sites. ViraChron overcomes previous limitations, obtaining high-quality genomic data from samples over ten thousand years old, thereby facilitating a systematic understanding of viral evolution and its biological characteristics.

paleontology↗

bioRxiv2025

Data Representation Bias and Conditional Distribution Shift Drive Predictive Performance Disparities in Multi-Population Machine Learning

Machine learning frequently encounters challenges when applied to population-stratified datasets, where data representation bias and data distribution shifts substantially impact model performance and generalizability across different population groups. These challenges are well illustrated in the context of polygenic prediction for diverse ancestry groups, and the underlying mechanisms are broadly applicable to machine learning with population-stratified data across domains. Using synthetic genotype-phenotype datasets representing five continental populations, we evaluate three approaches for utilizing population-stratified data, mixture learning, independent learning, and transfer learning, to systematically investigate how data representation bias and distribution shifts influence multi-population machine learning. Our results show that conditional distribution shifts, in combination with data representation bias, significantly influence machine learning performance across diverse populations and the effectiveness of transfer learning as a disparity mitigation strategy, while the effect of marginal distribution shifts is limited. The joint effects of data representation bias and distribution shifts demonstrate distinct patterns under different multi-population machine learning approaches, providing critical insights for the development of effective and equitable machine learning models for population-stratified data.

bioinformatics↗

bioRxiv2025

DiffusionST: A deep generative diffusion model-based framework for enhancing spatial transcriptomics data quality and identifying spatial domains

Recent advancements in spatial transcriptomics technology have generated substantial volumes of spatial transcriptome data. However, the quality of this data is often compromised due to the limitations of current sequencing technologies. To address this issue, DiffusionST proposes a method for imputing spatial transcriptomics data and clustering the imputed data. The method employs a graph convolutional network (GCN) model combined with a newly designed loss function, denoising data using the zero-inflated negative binomial (ZINB) distribution, and data enhancement through a diffusion model to improve clustering accuracy. DiffusionST demonstrates superior clustering accuracy compared to six of the most popular spatial transcriptomics clustering algorithms. DiffusionST also excels in data imputation when compared to five single-cell RNA sequencing (scRNA-seq) imputation algorithms. Additionally, DiffusionSTs robustness against noise is quantitatively validated by manually introducing random dropout noise into the dataset, where our model significantly enhances the quality of spatial transcriptomic data. Moreover, DiffusionST is well-suited for high-resolution spatial transcriptomics data and has been demonstrated, through survival analysis and cell-cell communication studies, to dissect spatial domains within breast cancer tissues. These findings provide strong evidence of DiffusionSTs efficacy in handling spatial transcriptomic data especially with strong noise, making it a valuable tool in this field.

bioinformatics↗

bioRxiv2025

Intratumoral microbiota-derived S1P sensitizes the combination therapy of Capecitabine and Nivolumab

Clinical responses of colorectal cancer (CRC) treatments vary considerably due to the heterogeneity of tumor micro-environment (TME), where intratumoral microbiota may reshape the unique inflammation imprints. However, its complex mechanistic underpinnings remain incompletely elucidated. Herein we sought to delineate the critical role of intratumoral microbiota in potentiating combination therapeutics against CRC. By comparing germ-free (GF) and specific pathogen-free (SPF) mouse models of 33 potential CRC treatments, we screened out the combination regimen of Capecitabine-Nivolumab significantly augmented by intratumoral microbiota in tumor regression and survival prolongation. The enrichment of Bacteroides fragilis induced by Capecitabine-Nivolumab was concomitant with elevated microbial sphingosine-1-phosphate (S1P), which further upregulated tumoral PD-L1 expression by enhancing histone deacetylation at the CD274 locus. Activation of microbial sphingosine kinase 2 (SphK2) ultimately led to an expansion of effector memory CD8+ T cells and reduction of exhausted T cell subsets within TME. To conclude, these findings advance our understanding of the intricate interplay among intratumoral microbiota, sphingolipid metabolites and immunochemotherapeutics. It highlights microbial sphingolipids as potential predictive biomarkers for strategies of targeting intratumoral microbiota in CRC management.

microbiology↗

bioRxiv2025

Engineering the key central metabolic enzyme to utilize a non-canonical redox cofactor

Redesigning central metabolism enzymes to utilize non-canonical cofactors that are orthogonal to NAD+ and NADP+ may allow partitioning of reducing power into a distinct redox cofactor pool that is preserved for user-desired biosynthetic tasks, without being dissipated by the complex natural metabolism in the cells. Here, we engineer Escherichia coli glyceraldehyde-3-phosphate dehydrogenase (GapA), the key enzyme in glycolysis, to utilize nicotinamide mononucleotide (NMN+) while greatly reducing its original activity with its native cofactor, NAD+. Through rational design, we identify the variant A180S with a [~]3-fold increase in NMN+ specific activity compared to that of the wildtype (WT). Next, we design a double mutant, G10R-A180S (RS), where G10R mutation hampers the catalytic efficiency for NAD+ but also decreased the activity toward NMN+. Importantly, based on the hypothesis that the role of NAD+ in coordinating oligomer interface must be recapitulated in NMN+-utilizing enzymes, we develop a triple mutant G10R-A180S-G187Q (RSQ). Rosetta modeling predicts that the new mutation G187Q bridges separate subunits across the cofactor binding pocket, which possibly affords stronger association of the GapA tetramer, the active form of this enzyme. This final GapA variant features a [~]2.8 x 104 switch of cofactor specificity from GapAs natural cofactor NAD+ to the non-canonical cofactor NMN+. Overall, this work demonstrates the engineering of a highly conserved, central metabolic enzyme for the utilization of a non-canonical redox cofactor NMN+. The design principle discovered here may be broadly applicable to many enzymes that bind cofactors using an intersubunit pocket.

molecular biology↗

bioRxiv2025

Selective RNA sequestration in biomolecular condensates directs cell fate transitions

Recent studies have emphasized the significance of biomolecular condensates in modulating gene expression through RNA processing and translational control. However, the functional roles of RNA condensates in cell fate specification remains poorly understood. Here, we profiled the coding and non-coding transcriptome within intact biomolecular condensates, specifically P-bodies, in diverse developmental contexts, spanning multiple vertebrate species. Our analyses revealed the conserved, cell type-specific sequestration of untranslated RNAs encoding key cell fate regulators. Notably, P-body contents did not directly reflect active gene expression profiles for a given cell type, but rather were enriched for translationally repressed transcripts characteristic of the preceding developmental stage. Mechanistically, microRNAs (miRNAs) direct the selective sequestration of RNAs into P-bodies in a context-dependent manner, and perturbing AGO2 or alternative polyadenylation profoundly reshapes P-body RNA content. Building on these mechanistic insights, we demonstrate that modulating P-body assembly or miRNA activity dramatically enhances both activation of a totipotency transcriptional program in naive pluripotent stem cells as well as the programming of primed human embryonic cells towards the germ cell lineage. Collectively, our findings establish a direct link between biomolecular condensates and cell fate decisions across vertebrate species and provide a novel framework for harnessing condensate biology to expand clinically relevant cell populations.

cell biology↗