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Sheng, T.

Publications and source records attributed to Sheng, T..

9 recordsLinked to original sources

Hippocampal-cortical coupling dynamics drive system consolidation of remote memory

System consolidation transforms temporary hippocampal representation of memory into long-term storage in cortex. The underlying neural substrate, however, remains enigmatic. Here, we tracked the spatiotemporal evolution of hippocampus (HPC)-cortex local field potentials and single-neuron spikes in behaving animals during fear memory formation. During learning, HPC fast gamma exhibited a progressive phase shift relative to PFC theta oscillations, with gamma power aligning to progressively later phases of the PFC theta cycle. Strikingly, a related phase-shifted coupling pattern re-emerged during subsequent consolidation in association with hippocampal sharp-wave ripples and transient PFC spindle events during NREM sleep. Across this process, interregional interactions evolved from HPC-driven cortical gamma coherence at recent stages to PFC-mediated cortical low-frequency coherence at remote stages. Using closed-loop optogenetic perturbations, we demonstrated a stepwise causal chain of coupling events underlying remote memory formation. Our study revealed HPC-PFC coupling phase shift as a feasible substrate mediating recent-to-remote transformation of memory.

neuroscience↗

Single-Cell Pharmacogenomic Landscapes of Epigenetic Therapy in Gastric Cancer

Gene expression signatures ("molecular phenotypes") are extensively utilized in cancer research. To study how gastric cancer (GC) molecular phenotypes are shaped by cell-intrinsic genetic alterations interacting with cell-extrinsic therapeutic pressures, we performed direct capture Perturb-seq (dcPerturb-seq) to interrogate >200 GC-related genes across 4 distinct epigenetic drug classes in multiple gastric lines. We captured 17.7 million pharmocogenomic expression interactions in 625,866 cells representing baseline and post-therapeutic molecular phenotypes. This single-cell pharmacogenomic compendium confirmed previously known gene-driven molecular phenotypes, elucidated poorly characterized genes, and uncovered novel gene dosage-molecular phenotype relationships. Molecular phenotypes in post-therapeutic surviving cells revealed diverse gene perturbation-associated pathways causing convergent drug resistance (EMT plasticity, cell cycle alterations, metabolic reprogramming), highlighting combinatorial strategies for restoring sensitivity. Mapping of in vitro molecular phenotypes to primary human GCs imparted prognostic information and insights into spatial heterogeneity. Comparative analysis of gene perturbations across therapies and lines revealed both conserved and context-specific molecular alterations. Our results illustrate how Perturb-seq approaches can systematically map diverse cancer-associated molecular phenotypes across multiple gene/drug/cell line interactions, yielding translational insights.

cancer biology↗

Unsilenced inhibitory cortical ensemble gates remote memory retrieval

Acquired information can be consolidated to remote memory for storage but persists in a dormant state until its retrieval. However, it remains unknown how dormant memory is reactivated. Using a combination of simultaneous two-photon calcium imaging and holographic optogenetics in the anterior cingulate cortex (ACC) in vivo, we discover a subset of GABAergic neurons that are specifically associated with dormant memory retrieval. These interneurons display persistent activity and inter-neuronal synchronization at the remote memory stage. In the absence of natural contextual cues, directly activating these interneurons reliably recalls cortical ensembles relevant to remote memory retrieval with context specificity. Conversely, targeted volumetric inactivation of these interneurons suppresses context-induced memory retrieval. Our results reveal an unexpected role of unsilenced inhibitory cortical ensembles in causally gating the retrievability of dormant remote memory.

neuroscience↗

Spatially Resolved Tumor Ecosystems and Cell States in Gastric Adenocarcinoma Progression and Evolution

Gastric cancer (GC) is a major cause of global cancer mortality with high heterogeneity levels. To explore geospatial interactions in tumor ecosystems, we integrated 1,563 spatial transcriptomic regions-of-interest (ROIs) with 152,423 single-cell expression profiles across 130 GC samples from 70 patients. We observed pervasive expression-based intratumor heterogeneity, recapitulating tumor progression through spatially localized and functionally ordered subgroups with specific immune microenvironments and immune checkpoint profiles. Evolutionary phylogenetic analysis revealed two different evolutionary trajectories (branched evolution and diaspora evolution) associated with distinct molecular subtypes, clinical prognoses, stromal neighborhoods including VWF+ ACKR1+ endothelial cells, and genetic drivers such as SOX9. Spatial analysis of tumor-stromal interfaces across multiple GCs highlighted new ecosystem states not attributable to mere tumor/stroma admixture, landmarked by increased GREM1 expression. Our results provide insights into how the cellular ecosystems of individual GCs are sculpted by tumor intrinsic and extrinsic selective pressures, culminating in individualized patient-specific cancer cartographies.

cancer biology↗

Spatially resolved niche and tumor microenvironmental alterations in gastric cancer peritoneal metastases

Peritoneal metastases (PM) in gastric cancer (GC) portend a poor prognosis, yet our understanding of tumor microenvironmental (TME) characteristics associated with GCPM remain limited. Here, we analyzed intrinsic genomic alterations and transcriptomic programs predictive of GCPM in a prospective cohort of 248 patients, identifying CDH1, PIGR, and ELF3 mutations as predictors. By inspecting the spatial dynamics of the TME, we find that tumor compartment infiltration of pro-tumorigenic cell types such as inflammatory cancer-associated fibroblasts (CAFs) predict peritoneal recurrence. Next, in a cross-sectional study of 205 samples from 55 patients, distinct pathways and immune compositions in GCPM relative to liver metastases highlight the TMEs significance in transcoelomic metastases. Notably, several putative therapeutic targets exhibited distinct expression patterns between PTs and PMs. We also observed increased immune infiltration in GCPMs treated with systemic immunotherapy and intraperitoneal chemotherapy. Our findings highlight transcriptomic variations and niche reprogramming in the GCPM peritoneal environment, revealing roles of myeloid dendritic cells, effector memory CD8+ T cells, and CAFs in metastatic progression. Statement of significanceComprehensive molecular profiling of gastric cancer primary and peritoneal tumors unveils crucial insights into the distinct molecular and immune landscape of peritoneal metastases. Identifying predictive markers and therapeutic targets emphasizes the significance of tumor microenvironment alterations in guiding future therapies for gastric cancer peritoneal metastasis.

cancer biology↗

Spatiotemporal Genomic Profiling of Intestinal Metaplasia Reveals Clonal Dynamics of Gastric Cancer Progression

Intestinal metaplasia (IM) is a pre-malignant condition of the gastric mucosa associated with increased gastric cancer (GC) risk. We analyzed 1256 gastric samples (1152 IMs) from 692 subjects through a prospective 10-year study. We identified 26 IM driver genes in diverse pathways including chromatin regulation (ARID1A) and intestinal homeostasis (SOX9), largely occurring as small clonal events. Analysis of clonal dynamics between and within subjects, and also longitudinally across time, revealed that IM clones are likely transient but increase in size upon progression to dysplasia, with eventual transmission of somatic events to paired GCs. Single-cell and spatial profiling highlighted changes in tissue ecology and lineage heterogeneity in IM, including an intestinal stem-cell dominant cellular compartment linked to early malignancy. Expanded transcriptome profiling revealed expression-based molecular subtypes of IM, including a body-resident "pseudoantralized" subtype associated with incomplete histology, antral/intestinal cell types, ARID1A mutations, inflammation, and microbial communities normally associated with the healthy oral tract. We demonstrate that combined clinical- genomic models outperform clinical-only models in predicting IMs likely to progress. Our results raise opportunities for GC precision prevention and interception by highlighting strategies for accurately identifying IM patients at high GC risk and a role for microbial dysbiosis in IM progression.

cancer biology↗

Integrative Epigenomic and High-Throughput Functional Enhancer Profiling Reveals Determinants of Enhancer Heterogeneity in Gastric Cancer

BackgroundEnhancers are distal cis-regulatory elements required for cell-specific gene expression and cell fate determination. In cancer, enhancer variation has been proposed as a major cause of inter-patient heterogeneity - however, most predicted enhancer regions remain to be functionally tested. ResultsAnalyzing 128 epigenomic histone modification profiles of primary GC samples, normal gastric tissues, and GC cell lines, we report a comprehensive catalog of 75,730 recurrent predicted enhancers, the majority of which are tumor-associated in vivo (>50,000) and associated with lower somatic mutation rates inferred by whole-genome sequencing. Applying Capture-based Self-Transcribing Active Regulatory Region sequencing (CapSTARR-seq) to the enhancer catalog, we observed significant correlations between CapSTARR-seq functional activity and H3K27ac/H3K4me1 levels. Super-enhancer regions exhibited increased CapSTARR-seq signals compared to regular enhancers even when decoupled from native chromatin contexture. We show that combining histone modification and CapSTARR-seq functional enhancer data improves the prediction of enhancer-promoter interactions and pinpointing of germline single nucleotide polymorphisms (SNPs), somatic copy number alterations (SCNAs), and trans-acting TFs involved in GC expression. Specifically, we identified cancer-relevant genes (e.g. ING1, ARL4C) whose expression between patients is influenced by enhancer differences in genomic copy number and germline SNPs, and HNF4 as a master trans-acting factor associated with GC enhancer heterogeneity. ConclusionsOur study indicates that combining histone modification and functional assay data may provide a more accurate metric to assess enhancer activity than either platform individually, and provides insights into the relative contribution of genetic (cis) and regulatory (trans) mechanisms to GC enhancer functional heterogeneity.

cancer biology↗

Deconstruction of the retrosplenial granular cortex for social behavior in the mouse model of fragile X syndrome

Deficits in fragile X mental retardation 1 protein lead to fragile X syndrome (FXS) with mental retardation and social activity disorder. Until now, the neuronal circuits that mediate the social impairments of FXS were mostly unclear. Accidently, we found fewer c-fos expression in RSG of KO than WT mice after social behavior test. Inactivation of RSG neurons decreased social novelty but not the sociability of naive mice. Interestingly, although the RSG neurons of KO mice had higher background activity, fewer social contact-related Ca2+ neurons were observed during social interaction test via one-photon Ca2+ imaging in freely-behaving mice. Strikingly, enhancing the activity of RSG neurons rescued the abnormal social novelty in KO mice. Further studies proved that the innervations from the subiculum and ACC to RSG contributes to the social behavior. Take together, we found that abnormal activity in the retrosplenial granular cortex (RSG) led to social novelty deficits in Fmr1-knockout (KO) mice. Moreover, selective manipulation of RSG neurons may be an effective strategy to treat the social deficits in FXS. One Sentence SummaryDeletion of FMRP leads to lower social-related neuronal activity in the RSG; this causes social novelty deficits in Fmr1-KO mice.

neuroscience↗

A probabilistic model-based bi-clustering method for single-cell transcriptomic data analysis

We present here novel computational techniques for tackling four problems related to analyses of single-cell RNA-Seq data: (1) a mixture model for coping with multiple cell types in a cell population; (2) a truncated model for handling the unquantifiable errors caused by large numbers of zeros or low-expression values; (3) a bi-clustering technique for detection of sub-populations of cells sharing common expression patterns among subsets of genes; and (4) detection of small cell sub-populations with distinct expression patterns. Through case studies, we demonstrated that these techniques can derive high-resolution information from single-cell data that are not feasible using existing techniques.

bioinformatics↗