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Zheng, H.

Publications and source records attributed to Zheng, H..

At least 91 records · Page 5Linked to original sources

Extensive binding of uncharacterized human transcription factors to genomic dark matter

The functional impact of a large portion of the human genome known as "dark matter DNA", which is composed mainly of repeat sequences, remains enigmatic. The genome also encodes hundreds of putative and poorly characterized transcription factors (TFs). Here, we determined genomic binding locations of 166 poorly characterized human TFs in living cells. Nearly half of them associate strongly with known regulatory regions such as promoters and enhancers, frequently co-localizing with each other at conserved motif matches. The other half often associate with genomic dark matter, however, at largely non-overlapping (i.e., unique) sites, via intrinsic sequence recognition. Fifty-four of the latter half, which we term "Dark TFs", mainly bind within regions of closed chromatin, with each recognizing a unique set of repeat sequences. The Dark TFs include many KZNFs, which are known to bind and silence TEs, and other TFs with apparent repressive functions. By contrast, some may be pioneers: we find that induction of TPRX1, a known regulator of zygotic preimplantation, leads to chromatin opening at many of its binding sites in the dark matter genome. Altogether, our results shed light on a large fraction of poorly characterized human TFs and simultaneously illuminate the diversity of function within the dark matter genome.

genomics↗

Cross-Species Analysis Reveals No Universal Programmed Aging Mechanism: Insights from Single-Cell Transcriptomics in Zebrafish, Fruit Fly, and Nematode

The question of whether aging follows a universal programmed process has been a topic of debate for a long time. Previous arguments, either supporting or refuting programmed aging, were mainly based on different evolutionary biology theories. In this study, we analysed single-cell RNA sequencing data from zebrafish, fruit fly, and nematode at various stages of development to explore gene co-expression modules across these species. We successfully identified a co-expression module related to ribosomal protein genes that is shared across the early development stages in multiple tissues of all three species. However, we did not find any cross-species shared gene co-expression modules related to aging. Further analysis of gene regulatory networks (GRNs) demonstrated that although certain aging-related genes are conserved, their regulatory mechanisms vary significantly between species. These findings suggest that aging is not governed by a conserved universal program but rather by species-specific adaptations to damage and environmental conditions.

evolutionary biology↗

Reconstructing the sequence specificities of RNA-binding proteins across eukaryotes

RNA-binding proteins (RBPs) are key regulators of gene expression. Here, we introduce EuPRI (Eukaryotic Protein-RNA Interactions) - a freely available resource of RNA motifs for 34,736 RBPs from 690 eukaryotes. EuPRI includes in vitro binding data for 504 RBPs, including newly collected RNAcompete data for 174 RBPs, along with thousands of reconstructed motifs. We reconstruct these motifs with a new computational platform -- Joint Protein-Ligand Embedding (JPLE) -- which can detect distant homology relationships and map specificity-determining peptides. EuPRI quadruples the number of known RBP motifs, expanding the motif repertoire across all major eukaryotic clades, and assigning motifs to the majority of human RBPs. EuPRI drastically improves knowledge of RBP motifs in flowering plants. For example, it increases the number of Arabidopsis thaliana RBP motifs 7-fold, from 14 to 105. EuPRI also has broad utility for inferring post-transcriptional function and evolutionary relationships. We demonstrate this by predicting a role for 12 Arabidopsis thaliana RBPs in RNA stability and identifying rapid and recent evolution of post-transcriptional regulatory networks in worms and plants. In contrast, the vertebrate RNA motif set has remained relatively stable after its drastic expansion between the metazoan and vertebrate ancestors. EuPRI represents a powerful resource for the study of gene regulation across eukaryotes.

genomics↗

Du-IN-v2: Unleashing the Power of Vector Quantization for Decoding Cognitive States from Intracranial Neural Signals

While invasive brain-computer interfaces have shown promise for high-performance speech decoding under medical use, the potential of intracranial stereoElectroEn-cephaloGraphy (sEEG), which causes less damage to patients, remains underex-plored. With the rapid progress in representation learning, leveraging abundant pure recordings to further enhance speech decoding becomes increasingly attractive. However, some popular methods pre-train temporal models based on brain-level tokens, overlooking the brains desynchronization nature; others pre-train spatial-temporal models based on channel-level tokens, yet fail to evaluate them on more challenging tasks, e.g., speech decoding, which demands intricate processing in specific brain regions. To tackle these issues, we introduce a general pre-training framework for speech decoding - Du-IN-v2, which can extract contextual embeddings based on region-level tokens through discrete codex-guided mask modeling. To further push its limits, we propose Decoupling Product Quantization (DPQ), where different codexes are designed to extract different parts of brain dynamics. Our model achieves SOTA performance on both the 61-word classification task and the 49-syllable sequence classification task, surpassing all baselines. Model comparison and ablation studies reveal that our design choices, including (i) temporal modeling based on region-level tokens by utilizing 1D depthwise convolution to fuse channels in vSMC and STG regions and (ii) self-supervision by discrete decoupling codex-guided mask modeling, significantly contribute to these performances. Collectively, our approach, inspired by neuroscience findings, capitalizing on region-level representations from specific brain regions, is suitable for invasive brain modeling. It marks a promising neuro-inspired AI approach in BCI.

bioengineering↗

A CXCR4 partial agonist improves immunotherapy by targeting polymorphonuclear myeloid-derived suppressor cells and cancer-driven granulopoiesis

Polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) are pathologically activated neutrophils that potently impair immunotherapy responses. The chemokine receptor CXCR4, a central regulator of hematopoiesis, represents an attractive PMN-MDSC target1. Here, we fused a secreted CXCR4 partial agonist TFF2 to mouse serum albumin (MSA) and demonstrated that TFF2-MSA peptide synergized with anti-PD-1 to induce tumor regression or eradication, inhibited distant metastases, and prolonged survival in multiple gastric cancer (GC) models. Using histidine decarboxylase (Hdc)-GFP transgenic mice to track PMN-MDSC in vivo, we found TFF2-MSA selectively reduced the immunosuppressive Hdc-GFP+ CXCR4hi tumor PMN-MDSCs while preserving proinflammatory neutrophils, thereby boosting CD8+ T cell-mediated anti-tumor response together with anti-PD-1. Furthermore, TFF2-MSA systemically reduced PMN-MDSCs and bone marrow granulopoiesis. In contrast, CXCR4 antagonism plus anti-PD-1 failed to provide a similar therapeutic benefit. In GC patients, expanded PMN-MDSCs containing a prominent CXCR4+LOX-1+ subset are inversely correlated with the TFF2 level and CD8+ T cells in circulation. Collectively, our studies introduce a strategy of using CXCR4 partial agonism to restore anti-PD-1 sensitivity in GC by targeting PMN-MDSCs and granulopoiesis.

cancer biology↗

Mapping AAV capsid sequences to functions through function-guided in silico evolution

Artificial intelligence (AI) offers significant potential to accelerate the functional engineering of adeno-associated virus (AAV) capsids in a time- and cost-efficient manner. However, existing approaches lack the ability to systematically map capsid sequences to multifunctional properties. To address this challenge, we developed ALICE, a knowledge-driven platform for in silico AAV capsid engineering that directly maps sequence to multiple functions. Our method incorporating a heuristic algorithm with contrastive learning principles, termed function-guided evolution (FE), to iteratively optimize high-performing capsid sequences generated by a naive language model toward desired functions. We elucidate FEs evolutionary mechanism, demonstrating its ability to navigate a function-guided landscape and generate capsids with tailored properties. After validating ALICEs ability to design murine-specific AAV capsids targeting Ly6a/Ly6c1 with limited training data, we developed ALICE-X by integrating a curriculum learning strategy. This upgrade facilitated exploration of sequence space beyond existing wet-lab datasets, enabling successful targeting of the human transferrin receptor 1 (hTfR1). The resulting engineered AAV variant, AAV.ALICE-H3, demonstrated improved viability, specific receptor targeting, and [~] 251-fold enhanced CNS tropism in human TFRC knock-in (hTFRC KI) mice compared to wildtype controls. This interpretable, knowledge-driven framework advances in silico AAV capsid design, offering broad applicability for translational gene therapy.

bioengineering↗

Interpreting Sleep Activity Through Neural Contrastive Learning

Memories are spontaneously replayed during sleep, a process thought to support memory consolidation. However, capturing this replay in humans has been challenging because unlike wakefulness, sleep EEG is dominated by slow, rhythmic background activity. Moreover, each sleep stage (e.g., NREM, REM) has distinct rhythms, hindering generalisation of models trained on wake-state data. To overcome these challenges, we developed the Sleep Interpreter (SI), a neural network model that decodes memory replay from sleep EEG. In a large dataset comprising 135 participants ([~]1,000 h of overnight sleep; [~]400 h of wake), we employed a TMR-like paradigm with 15 semantically congruent cue-image pairs to tag specific memories. SI was trained separately for NREM and REM using contrastive learning to align neural patterns across wake and sleep, filtering out stage-specific background rhythms. We also examined how slow oscillations and spindle coupling influence decoding in NREM sleep. In a 15-way classification, SI achieved up to 40.02% Top-1 accuracy on unseen subjects. To test generalisability, we followed up with two independent nap experiments in separate samples and applied the trained SI model off-the-shelf. The first probed spontaneous reactivation without auditory cues, while the second used semantic-free sounds with new images. In both, SI successfully decoded reactivation during sleep that correlated with post-nap memory performance. By openly sharing our dataset and SI system, we provide a unique resource for advancing research on memory and learning during sleep, and related disorders.

neuroscience↗

Identification of a new ORF3a-E fusion subgenomic RNA of SARS-CoV-2 and its biological features in the infection process

Subgenomic RNAs (sgRNAs) are discontinuous transcription products of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that are involved in viral gene expression and replication, but their exact functions are still being studied. Here, we report the identification of a new type of sgRNA, the fusion ORF3a-E-sgRNA, involved in the infection process of SARS-CoV-2. This sgRNA codes both ORF3a and E and can be detected throughout the viral life cycle in SARS-CoV-2-infected cells with high copy numbers. ORF3a-E-sgRNA guides more ORF3a translation and promotes the expression of cellular ribosomal protein S3 (RPS3) and the binding of eukaryotic translation initiation factor 4E (eIF4E). Single-cell sequencing of a SARS-CoV-2-infected human bronchial epithelial cell line (16HBE) revealed that maintenance of this stable translational environment by ORF3a-E-sgRNA is important for the SARS-CoV-2 assembly and release capabilities and is also beneficial for viral evasion of host innate immunity. More importantly, the transcription level of ORF3a-E-sgRNA contributes to differences in infection processes between the Wuhan strain and XBB strain of SARS-CoV-2.

microbiology↗

Multimodal Protein-Ligand Contrastive Pretraining for Effective and Efficient Drug Discovery

Recent advancements in genomics and proteomics have identified numerous clinically significant protein targets, with notably 85% categorized as undruggable. These targets present widespread challenges due to their complex structures and dynamics, rendering conventional drug design strategies not always effective. In this study, we introduce Uni-Clip, a contrastive learning framework that incorporates multi-modal features of proteins (structure and residue) and ligands (conformation and graph). Optimized with a specifically designed CF-InfoNCE loss, Uni-Clip enhances the modeling of protein-ligand interactions for both undruggable and druggable proteins. Uni-Clip demonstrates superior performance in benchmark evaluations on widely acknowledged datasets, LIT-PCBA and DUD-E, achieving a 147% and 218% improvements in enrichment factors at 1% compared to baselines. Furthermore, Uni-Clip proves to be a practical tool for various drug discovery applications. In virtual screening for the challenging protein target GPX4 with flat surface, it identified non-covalent inhibitors with an IC50 of 4.17 M, in contrast to the predominantly covalent inhibitors currently known. Through target fishing for benzbromarone, Uni-Clip identified the intrinsically disordered protein c-Myc as a potential target, highlighting benzbromarones potential for repurposing in cancer therapy. Explainable analyses effectively identified binding sites consistent with molecular dynamics and experimental results, even for challenging undruggable targets.

bioinformatics↗

High-Intensive Interval Training Decreases Circulating HMGB1 in Insulin Resistant Patients; Plasma Lipidomics Identifies Associated Cardiometabolic Benefits

Background: Exercise is a fundamental primary standard of care for cardiometabolic health. Body Weight (BW) High-Intensity Interval Training (HIIT) is an effective strategy for reducing cardiometabolic markers in individuals with insulin resistance and Type-2 diabetes (T2D). High-mobility group box 1 (HMGB1), a ubiquitous nuclear factor, plays an ample role beyond an alarmin in T2D development and progression. Our group has described this novel role previously, showing the beneficial effect of whole body HMGB1 silencing in decreasing hyperglycemia in diabetic mice. In the present study we tested the hypothesis that BW-HIIT as an effective exercise training modality will decrease cardiometabolic risk with a concomitant decrease in circulating HMGB1 more prominently in insulin resistant individuals compared to non-insulin resistant individuals contrasting to what we can evidence in a preclinical murine model of insulin resistance; Methods: Human and mouse pre- and post-exercise serum/plasma samples were analyzed for Lipidomics as well as Metabolic and Cytokine Multiplex assays. Standard of care, as well as cardiometabolic parameters, was also performed in human subjects; Results: insulin resistant individuals had the most positive effect, primarily with a decrease in the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR). as an index of insulin resistance as well as decreased HMGB1 post-exercise. Lipidomic analysis illustrated the highly beneficial effect of exercise training using a modified HIIT program, showing an enhanced panel of circulating lipids post-exercise exclusively in insulin resistant individuals. Plasma multiplex revealed significant translational heterogeneity in our studies with distinct metabolic hormone responses to exercise conditioning with a decrease in inflammatory markers in insulin resistant individuals; Conclusions: The current study demonstrated that 6-week BW-HIIT training improves cardiometabolic, anti-inflammatory markers, metabolic hormones, and insulin sensitivity in humans, strongly associated with decreased circulating HMGB1. Overall, these experiments reinforce the potential of HMGB1 as a marker of changes in insulin resistance and the positive effect of exercise training on insulin resistance possibly preventing the development of T2D and associated complications.

molecular biology↗

Three-dimension transcriptomics maps of whole mouse embryo during organogenesis

Understanding mammalian development heavily relies on classical animal models like the house mouse (Mus musculus). Advanced spatial transcriptomics has enabled biologists to break new ground in studies of molecular dynamics and cellular patterning during embryonic development with spatiotemporal resolution. To construct a comprehensive developmental trajectory, current three-dimensional (3D) spatial transcriptomic profiling leverages mouse embryos from gastrulation (E5.5) to organogenesis (E13.5) in continuity. However, a crucial phase for early organogenesis between E9.5 and E11.5 was deficient. To unveil the mystery of this stage, we present the 3D transcriptomics of mouse embryos at E9.5 and E11.5, with a widely applicable reconstruction workflow that bypasses sophisticated bioinformatic calculations. As our 3D atlas is generated at single-cell resolution, we demonstrate how organogenetic processes can be interpreted at different levels of granularity, from local cellular interactions to whole embryonic regionalization. We release the open-access database MOSTA3D (Mouse Organogenesis Spatiotemporal Transcriptomic Atlas in Three-dimensional) and hope a broader community will contribute to extending this framework from conception to senility in the near future.

developmental biology↗

Improving the value utilization of tuna peptide powder for the cosmetics field through ozone oxidation

To improve the utilization efficiency of small molecule peptides in marine proteins and promote their application in cosmetics, this study adopts ozone oxidation to conduct deodorization research on tuna small molecule peptides. To devise a method for the ozone oxidation and deodorization of tuna peptide powder suitable for the cosmetics field, orthogonal tests were carried out. The time, ozone concentration, and temperature were adjusted to determine the optimal conditions for ozonation and deodorization of tuna peptide powder. The results showed that at 50{degrees}C and an ozone concentration of 99.10 x 103 mg/m3, wet ozone oxidation for 40 min can also significantly reduce the fishy smell. Under these conditions, the color of tuna peptide powder treated with wet ozone was lighter. In addition, the main volatile compounds were detected by gas chromatography-mass spectrometry (GC-MS). The content of the main fishy volatile substance, hexanal, decreased by 66.4%, and two octyl aldehydes were observed. The results also showed that the protein activity of tuna peptide powder after ozonation remained unchanged. Thus, this study presents an approach to the ozone oxidation of tuna peptide powder that is suitable for cosmetics.

bioengineering↗

Paraptosome: A Novel Pathological Feature in Paraptotic Cell Death

Paraptosis is a novel form of programmed cell death characterized by distinct morphological features such as swelling of the endoplasmic reticulum and mitochondria, and cytoplasmic vacuolation. Unlike apoptosis, paraptosis does not involve the activation of caspases or DNA fragmentation. These unique features make paraptosis an intriguing target for cancer therapy, particularly against apoptosis-resistant cells. Here, we report a novel morphological feature of paraptosis: the formation of high-density spherical structure, which we tentatively term "paraptosome." We found that these putative paraptosomes originate from the Golgi apparatus, appearing as high-density formations under light microscopy and colocalizing with the trans-Golgi marker {beta}4GALT1-RFP. Time-lapse confocal microscopy and immunostaining demonstrated that putative paraptosomes form due to Golgi stress or disintegration, leading to severe disruption of Golgi function. Furthermore, we show that paraptosis inducers such as glabridin, morusin, and honokiol can cause significant alterations in the endoplasmic reticulum, mitochondria, autophagosomes, and lysosomes in U251MG glioblastoma cells; however, the formation of putative paraptosomes is not induced by isolated stress inducers. Collectively, these findings suggest that the putative paraptosome may be a novel characteristic structure of paraptosis. The discovery of paraptosomes provides a unique marker for defining paraptotic cell death and offers new insights into the characteristic pathological phenomena associated with multiple organelle dysfunction. This finding broadens the scope of cell biology research by introducing a new structural paradigm linked to paraptosis and may have implications for developing targeted therapies against apoptosis-resistant cancers.

cell biology↗

Endocytic dynamin deficiency impairs the host colonization of phytopathogenic fungi

During host-pathogen interactions, fungal pathogens exploit the endolysosomal trafficking network to fine-tune their responses to host and environmental stimuli, thereby facilitating disease progression. However, the molecular mechanisms underlying the fungal-specific functions of the endolysosomal network require further investigation. Here, we systematically characterized the endolysosomal network in Fusarium graminearum using the dynamin-like GTPase FgVps1 as an entry point. Functional analysis revealed that FgVps1 is essential for the release of retromer- and sorting nexin-associated vesicles from endosomes, thereby facilitating the trafficking of v-SNARE protein FgSnc1 and promoting fungal development and pathogenicity. Building on this, we further discovered that the retromer core subunit FgVps35 interacts with sorting nexin FgSnx4 and identified the corresponding interaction interface, which involves residues FgVps35N383 and FgSnx4E373. In addition, the ESCRT-II component FgVps36 bridges ESCRT-I and -III and interacts with both FgVps35 and FgSnx4, thereby preventing their mislocalization to the vacuole and maintaining endolysosomal trafficking. Notably, we demonstrated that inhibition of FgVps1 function, either by blocking its GTPase activity or by disrupting actin polymerization, effectively impaired endosomal trafficking and attenuates fungal pathogenicity. Altogether, our results uncover key mechanisms underlying the function of fungal endolysosomal network and providing a promising broad-spectrum strategy for controlling phytopathogenic fungi.

microbiology↗

Self-Assembled Chambered Cardiac Organoids for Modeling Cardiac Chamber Formation and Cardiotoxicity Assessment

The human heart, crucial for health and longevity, is a primary focus of medical research. Despite advancements in cardiac organoid technology, replicating early cardiac chamber formation stages remains challenging. Here, we develop chambered cardiac organoids (CCOs) by orchestrating cardiac signaling pathways, including the synergistic modulation of FGF and Wnt signaling via the HAND1 transcription factor. These CCOs exhibit stable chambers with self-organized outer myocardial and inner endocardial layers, and express developmental markers such as NKX2.5, TNNT2, and NAPPA, demonstrating physiological functionality including spontaneous contractions and calcium transients. Immunofluorescence and single-cell RNA sequencing confirmed the presence and stability of cardiomyocytes within CCOs. Further validation showed CCOs involvement in critical processes like endothelial-mesenchymal transition (EndoMT) and valvulogenesis. Ultrastructural and electrophysiological analysis revealed organized myofibrils and atrial-like action potentials. Importantly, CCOs proved effective in assessing cardiotoxicity through observable morphological changes, demonstrating specific cellular responses to established cardiotoxic compounds, thereby highlighting their potential for drug testing and safety evaluations. Our findings offer insights into cardiac chamber formation mechanisms and establish a robust platform for drug testing, disease modeling, and personalized medicine, representing a significant advancement in functional cardiac organoid development for both basic research and translational applications.

cell biology↗

Targeting SEZ6L2 in Colon Cancer: Efficacy of Bexarotene and Implications for Survival

BackgroundBexarotene, also recognized as Targretin, is categorized as a retinoid, a type of cancer drug. Nevertheless, the precise mechanisms of Bexarotene in relation to colon cancer remain unclear. In colon cancer, SEZ6L2 was suggested as one of the biomarkers and targets. This study presents a comprehensive exploration of the role of SEZ6L2 in colon cancer. MethodsWe utilized both TCGA data and a cohort of Chinese patients. In a meticulous analysis of 478 colon cancer cases, SEZ6L2 expression levels were examined in relation to clinical characteristics, staging parameters, and treatment outcomes. Additionally, we investigated the pharmacological impact of Bexarotene on SEZ6L2, demonstrating a significant downregulation of SEZ6L2 at both mRNA and protein levels in colon cancer patients following Bexarotene treatment. ResultsSEZ6L2 consistently overexpresses in colon cancer, serving as a potential universal biomarker with prognostic significance, validated in a diverse Chinese cohort. In vitro, SEZ6L2 promotes cell viability without affecting migration. Bexarotene treatment inhibits SEZ6L2 expression, correlating with reduced viability both in vitro and in vivo. SEZ6L2 overexpression accelerates declining survival rates in an in vivo context. Bexarotenes efficacy is context-dependent, effective in parental cells but not with SEZ6L2 overexpression. Computational predictions suggest a direct SEZ6L2-Bexarotene interaction, warranting further experimental exploration. ConclusionThe study provides valuable insights into SEZ6L2 as a prognostic biomarker in colon cancer, revealing its intricate relationship with clinical parameters, treatment outcomes, and Bexarotene effects. Context-dependent therapeutic responses emphasize the nuanced understanding required for SEZ6L2s role in colon cancer, paving the way for targeted therapeutic strategies.

biochemistry↗

Mealtime alters daily rhythm in nuclear O-GlcNAcome to regulate hepatic gene expression

The liver circadian clock and hepatic transcriptome are highly responsive to metabolic signals generated from feeding-fasting rhythm. Previous studies have identified a number of nutrient-sensitive signaling pathways that could interpret metabolic input to regulate rhythmic hepatic biology. Here, we investigated the role of O-GlcNAcylation, a nutrient-sensitive post-translational modification (PTM) in mediating metabolic regulation of rhythmic biology in the liver. We observe daily oscillation of global nuclear protein O-GlcNAcylation in the liver of mice subjected to night-restricted feeding (NRF) using label-free global O-GlcNAc proteomics. Additional site-specific O-GlcNAc analysis by tandem mass tag mass spectrometry further supports temporal differences in O-GlcNAcylation by revealing day-night differences. Proteins involved in gene expression are enriched among rhythmically O-GlcNAcylated proteins, suggesting rhythmic O-GlcNAcylation may directly regulate the daily rhythmicity of the hepatic transcriptome. We show that rhythmic O-GlcNAcylation can also indirectly modulate the hepatic transcriptome by interacting with phosphorylation. Several proteins harboring O-GlcNAcylation-phosphorylation interplay motif exhibit rhythmic O-GlcNAcylation and phosphorylation. Specifically, we show that O-GlcNAcylation occurs at a phospho-degron of a key circadian transcriptional activator, circadian locomotor output cycles kaput (CLOCK), thus regulating its stability and transcriptional output. Finally, we report that day-restricted feeding (DRF) in the nocturnal mouse significantly alters O-GlcNAcylation rhythm. Whereas global O-GlcNAcylation analysis indicates dampening of global O-GlcNAcylation rhythm in mice fed under DRF, site-specific analysis reveals differential responses of O-GlcNAc sites when timing of food intake is altered. Notably, a substantial number of O-GlcNAcylation sites exhibit inverted day-night profiles when mice are subjected to DRF. This suggests the dysregulation of daily nuclear protein O-GlcNAcylation rhythm may contribute to the disruption in liver transcriptomic rhythm previously observed in DRF condition. In summary, our results provide new mechanistic insights into metabolic regulation of daily hepatic transcriptomic rhythm via interplay between O-GlcNAcylation and phosphorylation and shed light on the deleterious effects of improper mealtimes.

physiology↗

Functional imaging of whole mouse embryonic development in utero

Despite significant advances in structural and genetic studies, investigations of early embryonic functions, such as brain activity, have long been constrained by technical challenges. Functional ultrasound (fUS) has emerged as a breakthrough modality, enabling real-time monitoring of brain activity with exceptional spatial and temporal resolution and offering unprecedented opportunities for studying functional embryonic development. In this study, we used fUS to monitor whole-embryo activity in mice from embryonic days E8.5 to E18.5, revealing patterns of neural activity throughout embryogenesis. This approach provides new opportunities to explore brain development dynamically as it unfolds. Moreover, we observed embryo responses to external stimuli, including sound, in both mice and cynomolgus macaques, offering insights into early sensory processing and neural maturation. In summary, our study establishes fUS as a powerful tool for studying embryonic brain functional development, with significant implications for scientific research, especially in non- human primate models, and clinical applications.

developmental biology↗