Biology subjects

Cui, T.

Publications and source records attributed to Cui, T..

At least 19 recordsLinked to original sources

bioRxiv2026

Establishment of Rabbit Formative-like Pluripotent Cells by Bidirectional Modulation of WNT Signaling Pathway

The generation of embryonic stem cells (ESCs) with full developmental capacity and robust chimera-forming potential remains a major bottleneck for most non-rodent mammalian species including rabbits, an important animal both for biomedicine and agriculture. Formative pluripotency is a unique intermediate state bridging the naive and primed pluripotent states, which is defined by distinct molecular signatures, intrinsic competence for primordial germ cell (PGC) specification, and unique developmental adaptability to early embryonic microenvironments. Here, we established a novel culture medium termed KFiC, which could bidirectionally and coordinately modulate the WNT/{beta}-catenin signaling pathway via combined treatment of WNT activator CHIR99021 and inhibitor IWR-1. The KFiC culture system enables efficient derivation and stable long-term self-renewal of rbESCs with consistent formative-like pluripotent characteristics. KFiC-cultured rbESCs (KFiC-rbESCs) form compact, undifferentiated colonies, maintain intact genomic stability, and recapitulate the transcriptional landscape of pre-implantation epiblast cells, accompanied by sustained high expression of the core formative pluripotency marker OTX2. Functionally, KFiC-rbESCs possess efficient PGC differentiation competence and extensively contribute to embryonic development after microinjection into rabbit morulae, displaying their superior developmental plasticity. Notably, the KFiC system can stabilize an intermediate formative-like pluripotent state in mouse, human, and porcine pluripotent stem cells, and KFiC-adapted mouse ESCs retain potent chimera-forming ability. Collectively, this study establishes a reliable culture platform for generating and maintaining formative-like rbESCs. This cross-species compatible system provides a promising foundation for further optimizing naive-level pluripotency in rbESCs and facilitates the generation of genetically engineered rabbit disease models.

developmental biology↗

bioRxiv2026

Effects of different shading levels on growth, physiology and leaf surface micromorphology of Sorbus sibirica "Dong Hong" seedlings

BackgroundSorbus sibirica Dong Hong is a promising ornamental cultivar, but its optimal light conditions remain unclear. AimsThis study evaluated the effects of shading on seedling growth, physiology, root morphology, and leaf surface micromorphology. MethodsOne-year-old seedlings were grown under full sunlight (CK) and 30%, 50%, or 70% shade for 100 days. Growth, biomass, root traits, chlorophyll, invertase, soluble protein, stomatal characteristics, and epicuticular wax morphology were determined. ResultsShading significantly affected all measured traits. The 30% shade treatment produced the greatest seedling height, which increased by 118.18% compared with CK, and the highest chlorophyll content, which increased by 120.21%. Soluble protein content was slightly increased, whereas invertase activity decreased under moderate shading. Although total biomass decreased by 18.63%, root development remained relatively stable under 30% shade, with slight increases in total root length and average root diameter. Stomatal density was highest under this treatment, and the epicuticular wax structure remained relatively regular. In contrast, 70% shade markedly inhibited biomass accumulation and root development. ConclusionsModerate shading, particularly 30%, provided the most favorable light environment for Sorbus sibirica Dong Hong seedlings and is recommended for summer nursery cultivation in Northeast China.

plant biology↗

bioRxiv2026

GALILEO: Embodied AI scientist for autonomous therapeutic discovery in dynamic membrane systems

Generalizable Agentic Laboratory Intelligence for Learning, Experimentation, and Optimization (GALILEO) closes the prediction-to-intervention gap in therapeutic peptide discovery. Unlike prior AI-scientist systems, GALILEO couples an Observation-Thought-Action-Summary (OTAS) reasoning loop with robotic peptide synthesis and multimodal phenotyping. Candidate peptides are retrieved from a clinically informed peptide prior (CPP) and locally edited through auditable operations. GALILEO autonomously prioritized LRRC8C and SLC25A1 branches and used wet-lab feedback to update target beliefs, sequence policies, assay choices, and mechanism hypotheses. Peptides generated under this framework blocked LRRC8C currents, perturbed osmolyte/redox homeostasis, and promoted tumor-dependent T-cell activation, while SLC25A1 peptides disrupted citrate-export metabolism, reduced extracellular acidosis, and enhanced CD8+ T-cell function. These results establish retrieval-and-editing-based physical learning as a route for auditable, experimentally grounded interventions and transferable membrane-blocker rules.

Molecular Biology↗

bioRxiv2026

The Structural Code of Breast Cancer Proteoform: Alternative Splicing-driven Protein Isoform Variation and Functional Diversification

Alternative splicing generates extensive transcript diversity, but the extent to which this diversity contributes to the translated proteome and reshapes protein function remains unclear. Here, we develop 3DisoGalaxy, an atlas integrating transcript reconstruction, ribosome profiling, structural modelling and regulatory annotation in breast cancer. We find that 58,292 of 90,929 transcripts are linked to translation-supported ORFs, 71.9% of which arise from non-canonical transcript structures. These products are broadly accommodated within established protein fold space, indicating that alternative isoforms frequently preserve recognizable protein architectures despite substantial sequence variation. Functional divergence is instead concentrated in domains, intrinsically disordered regions, localization determinants and regulatory motifs. Motif remodelling is biased towards gains and is more extensive in cancer-driver genes than in other genes, linking isoform-associated regulatory variation to cancer-relevant proteins. As an example of domain remodelling, we identify an AKT1-{Delta}PH isoform that lacks the N-terminal PH domain while retaining the kinase core, with immunoblotting revealing a lower-molecular-weight AKT1 species consistent with this isoform. Together, our results show that alternative transcript diversity extensively enters translation-supported proteoform space and establish a systematic link between transcript variation and protein functional diversification.

cancer biology↗

bioRxiv2026

An Isoform-Centric, Structure-Aware Framework for Protein Function Prediction and Evaluation, Instantiated in 3DisoDeepPF

Understanding and accurately predicting function across protein isoforms has been a long-standing challenge with profound implications for both biological and translational research. However, most functional annotations and benchmarks remain tied to genes or reference protein sequences, leaving limited support for distinguishing protein isoforms from the same gene whose sequence, structure and domain composition may lead to different functions. To address this gap, we developed an isoform-centric framework for protein function and domain annotation that integrates a dense graph of sequence and structure similarity with protein features. We implemented this framework as 3DisoDeepPF, a graph-based multimodal model, and applied it to a breast cancer isoform atlas. Across canonical benchmarks and evaluations at isoform resolution, 3DisoDeepPF showed strong performance in predicting GO terms and Pfam domains and remained robust in tests with homology control. It further captured changes in Pfam domain composition among isoforms from the same gene, including reference-relative domain gain and loss. An evidence tracing module links predicted labels to supporting proteins in the graph, as illustrated by the calcium and integrin binding protein 1 (CIB1). Together, this study provides a framework informed by protein structure for function and domain annotation at isoform resolution, converting human protein isoform diversity into traceable functional evidence for cancer atlas interpretation.

cancer biology↗

bioRxiv2026

EvoRMD: Integrating Biological Context and Evolutionary RNA Language Models for Interpretable Prediction of RNA Modifications

RNA modifications are essential regulators of post-transcriptional gene expression, influencing RNA stability, localization, translation, and degradation. Determining the specific modification at a given nucleotide is therefore critical for understanding its regulatory role. Most computational approaches treat each modification type as an independent binary task. This strategy provides a macro-level statistical perspective, but it does not reflect that, under a defined biochemical or cellular condition, only one modification type can occur at a specific site. Current mapping assays also report a single observed modification per site, leaving all other types unlabeled rather than truly negative. These properties motivate a framework that can reason over competing modification types. We introduce EvoRMD, a unified model for biologically contextualized and interpretable prediction of RNA modification types. EvoRMD integrates contextual sequence embeddings from a large-scale RNA language model with structured biological metadata--including species, organ, cell type, and subcellular localization. A lightweight attention mechanism highlights informative sequence positions. A shared multi-class classifier then generates a context-conditioned plausibility distribution over eleven modification types (Am, Cm, Um, Gm, D, pseudouridine, m1A, m5C, m5U, m6A, m7G), consistent with the single-positive, multiple-unlabeled nature of existing datasets. Although trained in a multi-class setting, EvoRMD also produces calibrated multi-label predictions through sigmoid-transformed logits, enabling direct comparison with existing single-modification and multi-label methods. EvoRMD achieves strong predictive performance and offers interpretable insights through attention profiles and motif analyses. Together, these components establish a biologically grounded framework for identifying and prioritizing RNA modification types from sequence and context.

bioinformatics↗

bioRxiv2026

Enhancing non-local interaction modeling for ab initio biomolecular calculations and simulations with ViSNet-PIMA

AI-based molecular dynamics simulation brings ab initio calculations to biomolecules in an efficient way, in which the machine learning force field (MLFF) locates at the central position by accurately predicting the molecular energies and forces. Most existing MLFFs assume localized interatomic interactions, limiting their ability to accurately model non-local interactions, which are crucial in biomolecular dynamics. In this study, we introduce ViSNet-PIMA, which efficiently learns non-local interactions by physics-informed multipole aggregator (PIMA) and accurately encodes molecular geometric information. ViSNet-PIMA outperforms all state-of-the-art MLFFs for energy and force predictions of different kinds of biomolecules and various conformations on MD22 and AIMD-Chig datasets, while adapting the PIMA blocks into other MLFFs further achieves 55.1% performance gains, demonstrating the superiority of ViSNet-PIMA and the universality of the model design. Furthermore, we propose AI2BMD-PIMA to incorporate ViSNet-PIMA into AI2BMD simulation program by introducing "Transfer Learning-Pretraining-Finetuning" scheme and replacing molecular mechanics-based non-local calculations among protein fragments with ViSNet-PIMA, which reduces AI2BMDs energy and force calculation errors by more than 50% for different protein conformations and protein folding and unfolding processes. ViSNet-PIMA advances ab initio calculation for the entire biomolecules, amplifying the application values of AI-based molecular dynamics simulations and property calculations in biochemical research.

bioinformatics↗

bioRxiv2025

Derivation, Characterizations, and Applications of Rabbit Haploid Embryonic Stem Cells

Haploid embryonic stem cells (haESCs), which contain a single set of chromosomes, provide powerful systems for investigating gene function and creating gene-edited animal models. haESCs have been derived from several mammalian species including human, mouse and rats, yet not from rabbits. Here, we report the derivation of parthenogenetic haESCs of rabbit (rbPhESCs) using an optimized culture medium. These cells maintain a stable haploid karyotype during long-term culture and own pluripotency features comparable to diploid embryonic stem cells derived from rabbit fertilized embryos. By integrating gene trapping cassette into ROSA26 locus, rbPhESCs offer an ideal platform for high-throughput functional genomic screening, as shown in haESCs from other mammals. Consistent with their parthenogenetic origin, rbPhESCs durably preserve maternal-specific imprinting patterns even after extended culture in serum-containing conditions, providing a valuable platform for generating disease models deficient in maternally expressed imprinted genes. Therefore, our findings expand the repertoire of mammalian haESCs and establish rbPhESCs as a valuable platform for genetic studies and biotechnological applications in rabbits.

cell biology↗

bioRxiv2025

DAESC+: High-performance, integrated software for single-cell allele-specific expression data

Single-cell allele-specific expression (ASE) provides valuable insights into gene regulatory mechanisms. However, its utility is limited by the lack of dedicated computational tools. We present DAESC+, an end-to-end software package for the processing and analysis of single-cell ASE. The preprocessing module, DAESC-P, is a user-friendly bioinformatics pipeline to obtain ASE counts from multiplexed scRNA-seq data. The analysis module, DAESC-GPU, is a scalable tool for differential ASE analysis powered by graphics processing units (GPUs). We demonstrated that DAESC-P is more accurate than the existing SALSA pipeline. DAESC-GPU is dozens of times faster than our previous method (DAESC) and scalable to over a million cells. Applying DAESC+ to a subset of the OneK1K cohort, we identified 15 genes exhibiting differential regulatory patterns between naive and central memory CD4+ T cells, and 2 genes between naive and memory B cells.

bioinformatics↗

bioRxiv2025

DynaRNA: Dynamic RNA Conformation Ensemble Generation with Diffusion Model

RNA plays a wide variety of roles in biological processes. In addition to serving as the coding messenger RNA (mRNA), the vast majority of RNAs function as non-coding RNAs (ncRNAs), where their dynamic structural ensemble is critical for mediating diverse biological functions. However, traditional experimental techniques and molecular dynamics (MD) simulations face significant challenges in characterizing the conformational dynamics of RNA, due to inherent methodological limitations and high computing power cost. We herein presented DynaRNA, a diffusion-based generative model for RNA conformation ensemble. DynaRNA employs denoising diffusion probabilistic model (DDPM) with equivariant graph neural network (EGNN) to directly model RNA 3D coordinates, enabling rapid exploration of RNA conformational space. DynaRNA enables end-to-end generation of RNA conformation ensemble reproducing experimental geometries without the need for Multiple Sequence Alignments (MSA) information. Our results demonstrate that DynaRNA effectively and accurately generate tetranucleotides ensemble with lower intercalation rate than molecular dynamics simulations. Besides, DynaRNA has the ability to capture rare excited states of HIV TAR(trans-activation response) element, and recapitulate de novo folding of tetraloops. DynaRNA serve as a versatile and efficient platform for modeling RNA structural dynamics, with broad implications potential in RNA structural biology, synthetic biology, and therapeutic development.

bioinformatics↗

bioRxiv2025

AI-Driven Efficient De Novo design of GLP-1RAs with Extended Half-Life and Enhanced Efficacy

Peptide drug has revolutionized modern therapeutics, offering novel treatment avenues for various diseases. However, low efficacy, time consumption, and high cost hinder peptide drug design and discovery. We present an efficientin approach that integrates deep learning-based protein design with efficient functional screening, enabling the rapid design of biotechnologically important peptides with improved the stability and efficacy. We designed 10,000 de novo GLP-1 receptor agonists (GLP-1RAs), of which 60 met the stability, efficacy, and diversity criteria in the vitral functional screening. In vitro validation revealed a 62% success rate, while in vivo experiment demonstrated that two designed GLP-1RAs exhibited significantly extended half-lives, approximately three times longer than Semaglutide. In diabetic and obesity mouse models, the most competitive candidate showed superior therapeutic efficacy over Semaglutide. Our AI driven peptide design pipline integrats protein design, functional screening, and experiment validation, reducing the number of iterations required to find novel peptide candidates. The entire process, from design to screening, can be completed in a single cycle within two weeks.

bioengineering↗

bioRxiv2025

Mutations and structural variants arising during double-strand break repair

Double-strand break (DSB) repair is highly mutagenic compared to normal replication. In budding yeast, repair of an HO endonuclease-induced DSB at MAT can be repaired by using a transcriptionally silent HMR::Kl-URA3 donor. During repair, -1 deletions in homonucleotide runs are strongly favored over +1 insertions, whereas during replication, spontaneous +1 and -1 events are equal. Microhomology-bounded, repair-associated intragenic deletions (IDs) are recovered 12 times more frequently than tandem duplications (TDs). IDs have a mean length of 56 bp, while TDs average 22 bp. These data suggest a picture of the structure of the repair replication fork: IDs and TDs occur within the open structure of a migrating D-loop, where the 3 end of a partly copied new DNA strand can dissociate and anneal with a single-stranded region of microhomology that lies either [~]80 bp ahead or [~]40 bp behind the 3 end. Another major class of repair-associated mutations ([~]10%) are interchromosomal template switches (ICTS), even though the K. lactis URA3 sequence in HMR is only 72% identical (homeologous) with S. cerevisiae ura3-52. ICTS events begin and end at regions of short ([~]7 bp) microhomology; however, ICTS events are constrained to the middle of the copied sequence. Whereas microhomology usage in intragenic deletions is not influenced by adjacent homeology, we show that extensive pairing of adjacent homeology plays a critical role in ICTS. Thus, although by convention, structural variants are characterized by the precise base pairs at their junction, microhomology-mediated template switching actually requires alignment of extensive adjacent homeology. Significance statementDNA synthesis during repair of a double-strand chromosome break by homologous recombination exhibits a high rate of mutation compared to normal replication. Using a genetic system in budding yeast, we isolated thousands of mutations occurring during repair. We conclude that the repair replication fork appears to have the two DNA strands open [~]80 bp ahead of the DNA polymerase, but the strands re-anneal rapidly behind the polymerase. Additionally, we analyzed interchromosomal template switching, in which the partially copied DNA strand dissociates and pairs with a new template at a short stretch of perfectly matching bases (microhomology), and resumes copying. We show that these apparent microhomology-mediated template switching events in fact require the pairing of [~]200 bp of imperfectly matching bases (homeology).

genetics↗

bioRxiv2024

A Multi-Property Optimizing Generative Adversarial Network for de novo Antimicrobial Peptide Design

Antimicrobial peptides (AMPs) play a crucial role in developing novel antiinfective drugs due to their broad-spectrum antimicrobial activity and lower likelihood of causing bacterial resistance. However, laboratory synthesis of AMPs is tedious and time-consuming. Existing computational methods have limited capability in optimizing multiple desired properties simultaneously. Here, we propose a Multi-Property Optimizing Generative Adversarial Network (MPOGAN), a feedback-loop framework that iteratively learns from data with multiple desired properties. This approach enables de novo design of AMPs with potent antimicrobial activity, reduced cytotoxicity, and diversity. Through extensive computational tests, MPOGAN exhibits superior performance in optimizing multiple desired properties of generated AMPs. Ten of the most promising candidates are chemically synthesized, with nine showing potent antimicrobial activity against three bacterial strains and low cytotoxicity against eukaryotic cells. MPOGAN offers a powerful computational approach for effective multi-property optimization of AMPs, thereby advancing the field of AI-aided drug discovery.

bioinformatics↗

bioRxiv2024

Upregulated expression of ubiquitin ligase TRIM21 promotes PKM2 nuclear translocation and astrocyte activation in experimental autoimmune encephalomyelitis

Reactive astrocytes play critical roles in the occurrence of various neurological diseases such as multiple sclerosis. Activation of astrocytes is often accompanied by a glycolysis-dominant metabolic switch. However, the role and molecular mechanism of metabolic reprogramming in activation of astrocytes have not been clarified. Here, we found that PKM2, a notoriously known rate-limiting enzyme of glycolysis, displayed nuclear translocation in astrocytes of EAE (experimental autoimmune encephalomyelitis) mice, an animal model of multiple sclerosis. Prevention of PKM2 nuclear import by DASA-58 significantly reduced the activation of primary astrocytes, which was observed by decreased proliferation, glycolysis and secretion of inflammatory cytokines. Most importantly, we identified the ubiquitination-mediated regulation of PKM2 nuclear import by ubiquitin ligase TRIM21. TRIM21 interacted with PKM2, promoted its nuclear translocation and stimulated its nuclear activity to phosphorylate STAT3, NF-{kappa}B and interact with c-myc. Further single-cell RNA sequencing and immunofluorescence staining demonstrated that TRIM21 expression was upregulated in astrocytes of EAE. TRIM21 overexpressing in primary astrocytes enhanced PKM2-dependent glycolysis and proliferation, which could be reversed by DASA-58. Moreover, intracerebroventricular injection of a lentiviral vector to knockdown TRIM21 in astrocytes or intraperitoneal injection of TEPP-46, which inhibit the nuclear translocation of PKM2, effectively decreased disease severity, CNS inflammation and demyelination in EAE. Collectively, our study provides novel insights into the pathological function of nuclear glycolytic enzyme PKM2 and ubiquitination-mediated regulatory mechanism that are involved in astrocyte activation. Targeting this axis may be a potential therapeutic strategy for the treatment of astrocyte-involved neurological disease.

neuroscience↗

bioRxiv2024

Biomimetic fractal topography enhances podocyte maturation in vitro

Cells and tissues in their native environment are organized into intricate fractal structures, which are rarely recapitulated in their culture in vitro. The extent to which fractal patterns that resemble complex topography in vivo influence cell maturation, and the cellular responses to such shape stimulation remain inadequately elucidated. Yet, the application of fractal cues (topographical stimulation via self-similar patterns) as an external input may offer a much-needed solution to the challenge of improving the differentiated cell phenotype in vitro. Here, we established fractality in podocytes, branching highly differentiated kidney cells, and glomerulus structure. Biomimetic fractal patterns derived from glomerular histology were used to generate topographical (2.5-D) substrates for cell culture. Podocytes grown on fractal topography were found to express higher levels of functional markers and exhibit enhanced cell polarity. To track morphological complexities of differentiated podocytes, we employed a fluorescent labelling assay where labelled individual cells are tracked within otherwise optically silent confluent cell monolayer to reveal cell-cell interdigitation. RNAseq analysis suggests enhanced ECM deposition and remodeling in podocytes grown on fractal topography compared to flat surface or non-fractal microcurvature, mediated by YAP signaling. The incorporation of fractal topography into standard tissue culture well plates as demonstrated here may serve as a user-friendly bioengineered platform for high-fidelity cell culture.

bioengineering↗

bioRxiv2023

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

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

immunology↗

bioRxiv2023

Double-strand break repair-associated intragenic deletions and tandem duplications suggest the architecture of the repair replication fork

Double-strand break (DSB) repair is associated with a 1000-fold increase in mutations compared to normal replication of the same sequences. In budding yeast, repair of an HO endonuclease-induced DSB at the MAT locus can be repaired by using a homologous, heterochromatic HMR::Kl-URA3 donor harboring a transcriptionally silenced URA3 gene, resulting in a MAT::URA3 (Ura+) repair product where URA3 is expressed. Repair-associated ura3- mutations can be selected by resistance to 5-fluoroorotic acid (FOA). Using this system, we find that a major class of mutations are -1 deletions, almost always in homonucleotide runs, but there are few +1 insertions. In contrast, +1 and -1 insertions in homonucleotide runs are nearly equal among spontaneous mutations. Approximately 10% of repair-associated mutations are interchromosomal template switches (ICTS), even though the K. lactis URA3 sequence embedded in HMR is only 72% identical with S. cerevisiae ura3-52 sequences on a different chromosome. ICTS events begin and end in regions of short microhomology, averaging 7 bp. Long microhomologies are favored, but some ICTS junctions are as short as 2 bp. Both repair-associated intragenic deletions (IDs) and tandem duplications (TDs) are recovered, with junctions sharing short stretches of, on average, 6 bp of microhomology. Intragenic deletions are more than 5 times more frequent than TDs. IDs have a mean length of 60 bp, but, surprisingly there are almost no deletions shorter than 25 bp. In contrast, TDs average only 12 bp. The usage of microhomologies among intragenic deletions is not strongly influenced by the degree of adjacent homeology. Together, these data provide a picture of the structure of the repair replication fork. We suggest that IDs and TDs occur within the migrating D-loop in which DNA polymerase {delta} copies the template, where the 3 end of a partly copied new DNA strand can dissociate and anneal with a single-stranded region of microhomology that lies either in front or behind the 3 end, within the open structure of a migrating D-loop. Our data suggest that [~]100 bp ahead of the polymerase is "open," but that part of the repair replication apparatus remains bound in the 25 bp ahead of the newly copied DNA, preventing annealing. In contrast, the template region behind the polymerase appears to be rapidly reannealed, limiting template switching to a very short region.

genetics↗

bioRxiv2023

Associative memory neurons of encoding multi-modal signals are recruited by neuroligin-3 mediated new synapse formation

The joint storage and reciprocal retrieval of leant associated signals are presumably encoded by associative memory cells. In the accumulation and enrichment of memory contents in lifespan, a signal often becomes a core signal associatively shared for other signals. One specific group of associative memory neurons that encode this core signal likely interconnects multiple groups of associative memory neurons that encode these other signals for their joint storage and reciprocal retrieval. We have examined this hypothesis in a mouse model of associative learning by pairing the whisker tactile signal sequentially with the olfactory signal, the gustatory signal and the tail-heating signal. Mice experienced this associative learning show the whisker fluctuation induced by olfactory, gustatory and tail-heating signals, or the other way around, i.e., memories to multi-modal associated signals featured by their reciprocal retrievals. Barrel cortical neurons in these mice become able to encode olfactory, gustatory and tail-heating signals alongside the whisker signal. Barrel cortical neurons interconnect piriform, S1-Tr and gustatory cortical neurons. With the barrel cortex as the hub, the indirect activation occurs among piriform, gustatory and S1-Tr cortices for the second-order associative memory. These associative memory neurons recruited to encode multi-modal signals in the barrel cortex for associative memory are downregulated by neuroligin-3 knockdown. Thus, associative memory neurons can be recruited as the core cellular substrate to memorize multiple associated signals for the first-order and the second-order of associative memories by neuroligin-3-mediated synapse formation, which constitutes neuronal substrates of cognitive activities in the field of memoriology. HighlightO_LIThe coactivity of cerebral cortices during associative learning induces their interconnections. C_LIO_LIInterconnections endorse the first order and the second order of associative memory. C_LIO_LIAssociative memory cells in cerebral cortices are recruited by mutual synapse innervations. C_LIO_LINeuroligin-3 mediates the recruitment of associative memory cells for associative memory. C_LI

neuroscience↗