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Biology subjects

Huang, N.

Publications and source records attributed to Huang, N..

At least 19 recordsLinked to original sources

Representational geometry of punishment learning across basolateral amygdala neurons

Punishment learning allows animals to suppress actions that cause harm while maintaining actions that earn reward. Although the basolateral amygdala is necessary for punishment learning, how its population activity changes across learning, and how this activity reflects an action's consequences, remain unknown. We used longitudinal calcium imaging to track 1,147 basolateral amygdala neurons in male mice across instrumental training, punishment, choice test, and punishment extinction. Punishment learning transformed basolateral amygdala neuron activity associated with the punished action. This activity diverged from that associated with the unpunished action and became aligned with activity evoked by the punisher itself. This alignment was action and contingency specific. It preserved the direction of individual neurons' responses to the punisher: neurons activated by the punisher become more activated by the punished action alone, whereas neurons inhibited by the punisher become more inhibited by the punished action alone. We then asked whether reward and punishment were encoded separately or on a common value dimension across basolateral amygdala neurons. Punishment added a strong shock component to action-related activity without reducing its reward component, while reward and shock themselves occupied largely orthogonal population directions. Thus, during punishment learning, basolateral amygdala population activity can encode opposing consequences of the same action instead of simply changing what that action is worth.

neuroscience↗

Glioblastoma Hijacks Astrocyte Ribosomes to Feul Malignancy through Translatome Reprogramming

Cancer cells demand elevated protein synthesis, yet whether they directly requisition ribosomes from microenvironmental host cells remains unknown. Here, utilizing in vivo and in vitro ribosome tracing, we show that glioblastoma (GBM) cells hijack ribosomes from surrounding astrocytes via tunneling nanotube-like structures. This transfer supports GBM malignancy in both murine and patient derived models. Single cell RNA sequencing along with whole cell and cell source traceable ribosome profiling reveal that transferred ribosomes are translationally active and selectively reprogram the tumor translatome, prioritizing cell-cycle genes and driving interferon-response-mediated immune evasion. Through a genome wide CRISPR screen, we identify INTS12 as a critical mediator of ribosome transfer. Genetic inactivation or AAV-mediated knockdown of INTS12 impairs ribosome uptake, curbs translation and proliferation, remodels the immunosuppressive landscape, and extends survival in orthotopic models. Our study uncovers a parasitic translation-support mechanism in GBM, establishing INTS12 as a therapeutic vulnerability to disrupt ribosome transfer.

cancer biology↗

Spatialsnake: a flexible workflow for spatial transcriptomics analysis across platforms

Background: Spatial transcriptomics technologies measure gene expression at different spatial resolutions and generate diverse data outputs. Existing workflows support a range of platforms and analyses, but combining methods and extending analyses to selected populations or tissue regions can require additional scripts and repeated data preparation. Findings: We developed Spatialsnake, a flexible workflow built on SpatialData and Snakemake for analysing processed outputs from Visium, Visium HD, Stereo-seq, Xenium and MERFISH. A common command-line interface supports single- and multi-sample analysis, with adjustable parameters and saved intermediate results. Users can select populations, tissue regions or distance-based neighborhoods, repeat clustering and annotation, and map refined labels back to the full dataset. Additional modules support cell-type composition estimation, spatial-domain identification, cell-cell communication inference, regulon analysis and sample-level comparisons. We demonstrate these functions using mouse-brain Visium and colorectal cancer Visium HD datasets. Joint analysis of three colorectal cancer sections retained 1,527,987 bins and enabled further analysis of 223,632 epithelial bins, linking epithelial subpopulation annotations to their locations within the complete tissue. Conclusions: Spatialsnake provides a unified workflow for spatial transcriptomics analysis across sequencing- and imaging-based platforms. Its flexible analysis modules support both whole-tissue analysis and further investigation of selected cell populations and tissue regions.

bioinformatics↗

A Saturated Aminotriester Lipid Enhances Amonafide Activity in Human Colorectal Cancer Cells

The delivery of small-molecule therapeutics across cellular membranes remains a fundamental challenge in drug development, particularly for compounds whose physicochemical properties limit intracellular bioavailability. Inspired by the low toxicity, biodegradability, and synthetic accessibility of triethanolamine-derived lipids, we investigated a series of C18 aminotriester lipids as excipients for the codelivery of anticancer therapeutics. Four structurally related triester lipids bearing saturated, cis-monounsaturated, trans-monounsaturated, and di-unsaturated C18 tails were synthesized through straightforward esterification reactions with triethanolamine. These lipids were evaluated for their ability to enhance the antiproliferative activity of several anticancer agents, including paclitaxel, doxorubicin, amonafide, homoharringtonine, camptothecin, and SN-38. Across multiple drug classes, the aminotriester lipids exhibited minimal intrinsic cytotoxicity and generally produced limited enhancement of drug potency. However, the fully saturated tris-stearate aminotriester lipid selectively enhanced the antiproliferative activity of amonafide in HCT-116 colorectal cancer cells, particularly at lower concentrations. In contrast, unsaturated lipid analogues displayed negligible enhancement effects, and the activity of the tris-stearate lipid was substantially attenuated in A549 lung adenocarcinoma cells, weakly observed in HT-29 colorectal cancer cells, and absent in CT26 murine colorectal cancer cells. Lactate dehydrogenase release assays indicated that these effects were not associated with membrane lysis or nonspecific cytotoxicity. Further, fluorescence microscopy time course experiments suggest improved membrane trafficking of amonafide when codelivered stoichiometrically with fully saturated C18 aminotriester lipids. Collectively, these findings demonstrate that saturated triethanolamine-based aminotriester lipids may function as selective and biocompatible codelivery excipients for certain small-molecule therapeutics. The observed dependence on both lipid saturation state and cellular context suggests that membrane organization and lipid packing may play important roles in mediating these effects. These results establish a foundation for further mechanistic investigations into aminotriester lipid-assisted small-molecule delivery systems.

cancer biology↗

Development and validation of highly selective monoclonal antibodies for the detection of huntingtin neoepitopes

Huntington's disease is caused by a CAG repeat tract expansion in the huntingtin gene, resulting in production of pathogenic N-terminal huntingtin protein fragments associated with disease pathology. Despite their central role, detection of these fragments has relied on a limited antibody repertoire with reproducibility concerns. Here, we describe the generation and characterization of recombinant rabbit monoclonal antibodies targeting two reciprocal neoepitopes flanking the huntingtin exon 1/exon 2 junction corresponding to amino acids P90 and K91. The P90 antibodies (clones 1B12, 11G2) demonstrate fragment-length-selective recognition of the C-terminal HTTexon1 P90 neoepitope with no detectable binding to full length huntingtin. A side-by-side comparison of the widely used monoclonal antibody MW8 from two different sources revealed measurable lot-to-lot drift in its fragment selectivity, whereas the recombinant P90 antibodies, expressed from a defined, sequenced clone, maintained consistent specificity, addressing this source-dependent variability. Whereas P90-positive fragments can arise through alternative splicing of the HTT1a transcript, generation of the reciprocal K91 N-terminal HTTexon2 neoepitope would require site-specific proteolytic cleavage, a mechanism that has not yet been directly tested for lack of a suitable reagent. The K91 antibody (clone 7G10) binds the N-terminal K91 neoepitope with high affinity and specificity over full length huntingtin and provides, for the first time, a tool capable of directly interrogating whether such cleavage occurs. Neoepitope specificity of these antibodies was orthogonally confirmed by protease digestion (Lys-N and Arg-C) coupled with intact mass spectrometry. As an additional outcome of the immunization and selection strategy, we discovered human-mouse cross-reactive antibodies (clones 27F5, 31C10) targeting the proline-rich domain of huntingtin that will facilitate mouse-human translational studies. All antibodies are recombinant, ensuring long-term reproducibility, and are being made available, along with their sequences, to the research community.

neuroscience↗

Medulloblastoma Forms Symbiotic Metabolic Partnerships with Macrophages to Establish Leptomeningeal Metastases

Leptomeningeal metastases are the primary source of morbidity and mortality for pediatric medulloblastoma patients. Due to limited surgical sampling of metastases in patients, little is understood of the mechanisms of metastasis. Here, we identify biologically distinct quiescent small metastases (designated as micrometastases) and mitotically active larger metastases (macrometastases). Macrometastases are more metabolically active than micrometastases and contain higher levels of lipids, particularly cholesterol. Macrometastases secrete CXCL12, which attracts lipid-laden macrophages into the tumor. Lipid-laden macrophages upregulate the cholesterol transporter ABCG1, promoting the efflux of free cholesterol, which is then taken up by tumor cells via the HDL receptor SCARB1. CXCL12-driven macrophage recruitment and exogenous cholesterol are sufficient and necessary to drive progression of medulloblastoma leptomeningeal metastases in vivo. High fat diets drive metastatic progression in vivo. Dietary or pharmacological interventions targeting the CXCL12-SCARB1-cholesterol axis represent therapeutic strategies to either prevent or treat medulloblastoma leptomeningeal metastases.

cancer biology↗

Ependymomas are cancers of the pre-neural crest/roof plate lineage

Distinct molecular variants of the brain cancer ependymoma are distributed along the rostral-caudal extent of the central nervous system (CNS). Historically proposed to arise from ventricular ependyma, recent studies have suggested conflicting cellular origins, including the neural radial glia and the roof plate lineages. Using single-cell transcriptomics, immunohistochemistry, and lineage tracing, we demonstrate that ependymomas across all CNS compartments transcriptionally mirror MSX1+ve pre-neural crest/roof plate (Pre-NC/RP) lineage derivatives. Ependymoma subgroups recapitulate the spatial and molecular diversity of regional Pre-NC/RP populations, while retaining conserved MSX1 expression. Expression of the oncogenic fusion ZFTA-RELA within the murine Pre-NC/RP lineage generated tumors that faithfully resembled human ependymoma. These findings identify a common embryonic cellular origin for ependymomas and reconcile previously conflicting models of tumorigenesis.

developmental biology↗

Directed Human Structural Connectome Reveals Hierarchical Organization and Shapes Large-Scale Brain Dynamics

The human structural connectome, most commonly derived from diffusion-weighted imaging (DWI) and tractography, provides a macroscopic description of whole-brain wiring and serves as the structural foundation of network neuroscience, large-scale brain simulations, and personalized digital brain twins. However, tractography-derived connectomes are fundamentally limited by their inability to distinguish afferent from efferent connections, yielding networks that are undirected and therefore blind to the hierarchical organization imposed by the directionality of anatomical connections. In this study, we introduce a directed human structural connectome (DHSC) by transferring tracer-derived projection patterns from macaque to human using cross-species connectivity blueprints. Topological analysis of the DHSC manifests biological plausibility, a small-world network organization, and a directionality-based hierarchy, which offer the hierarchical organization of human brain networks. In the context of brain dynamics, the introduction of directionality reshapes the propagation and persistence of sensory inputs. DHSC also best captures the empirical spatiotemporal dynamics of stimulus-evoked brain activity. The findings demonstrate that anatomical directionality is a critical determinant of large-scale brain organization and dynamics. This provides evidence that directed connectome may offer potential advantages in large-scale simulations of the human brain. The resulting DHSC, along with all related analyses and data are openly available.

neuroscience↗

Relative Index of Chimeric Expression (RICE) Analysis: A Quantitative Approach for Chimeric RNAs Using FusionBlaster

Chimeric RNA molecules, which contain nucleotide sequences originating from multiple genes, are generated by chromosomal rearrangements, transcriptional read-throughs, or trans-splicing between separate parental transcripts. Chimeric RNAs have been functionally validated in both pathological and normal healthy physiological contexts indicating the biological significance of chimeric RNA expression. There is, however, currently no standard for computationally quantifying chimeric RNA expression and only limited benchmarking data available for the few chimeric RNA detection software that attempt to measure the abundance of the predicted chimeras. Here, we develop the relative index of chimeric expression, RICE, that is calculated based on the relative expression of chimeric transcripts compared to the respective parental WT transcripts. We evaluate three different methods for generating this measurement from simulated RNA sequencing data with known transcript abundances. Our BLAST-based approach outperforms STAR and Kallisto based approaches when considering both accuracy and consistency between simulated data of different read lengths and sequencing depths. We further demonstrate that RICE values can be validated using qPCR and are sensitive to dynamic conditions using siRNA targeting chimeric RNA expression. Finally, we apply our RICE analysis pipeline to clinical prostate cancer data. We quantify over 1200 chimeric RNAs in primary prostate cancer, metastatic prostate cancer, and non-cancer tissue samples from GTEx. Our differential RICE analysis revealed a clustering of prostate cancer tissue samples from three different sequencing cohorts distinct from their associated tissue type noncancer GTEx clusters. Our pipeline is publicly available on github and can be run on a personal laptop with computational resources and processing time dependent on the number of quantified chimeras.

bioinformatics↗

Spacing effect improves generalization in biological and artificial systems

Generalization is a fundamental criterion for evaluating learning effectiveness, a domain where biological intelligence excels yet artificial intelligence continues to face challenges. In biological learning and memory, the well-documented spacing effect shows that appropriately spaced intervals between learning trials can significantly improve behavioral performance. While multiple theories have been proposed to explain its underlying mechanisms, one compelling hypothesis is that spaced training promotes integration of input and innate variations, thereby enhancing generalization to novel but related scenarios. Here we examine this hypothesis by introducing a bio-inspired spacing effect into artificial neural networks, integrating input and innate variations across spaced intervals at the neuronal, synaptic, and network levels. These spaced ensemble strategies yield significant performance gains across various benchmark datasets and network architectures. Biological experiments on Drosophila further validate the complementary effect of appropriate variations and spaced intervals in improving generalization, which together reveal a convergent computational principle shared by biological learning and machine learning.

neuroscience↗

Unimeth: A unified transformer framework for accurate DNA methylation detection from nanopore reads

Nanopore sequencing enables direct detection of DNA modifications from native DNA. However, accurate methylation calling across species, sequence contexts, modification types and chemistries remains challenging. We present Unimeth, a transformer-based framework that jointly processes raw signals and basecalled sequences in read patches and predicts all target methylation sites within each patch. Unimeth uses a three-phase training strategy that combines signal pre-training, methylation fine-tuning and site-level calibration using methylation frequency information. We evaluated Unimeth for 5mC and 6mA detection using public and in-house datasets spanning 14 species, three nanopore chemistries and wild-type, mutant and enzyme-treated samples. Unimeth improved plant 5mC detection in non-CpG contexts, reduced false-positive calls in low-methylation samples and maintained high 5mCpG performance in mammalian datasets. For 6mA, Unimeth reduced background calls while preserving signals for Fiber-seq nucleosome and gene-level analyses. Unimeth provides a unified framework for nanopore-based methylation detection across methylation types and biological contexts.

bioinformatics↗

The brain architecture of punishment learning

Learning which actions cause harm is essential for survival, yet how the brain transforms this knowledge into adaptive control of behavior remains unclear. We combined whole-brain analysis, multisite chemogenetic silencing, spatial transcriptomics, and longitudinal calcium imaging to map how punishment learning reorganizes brain networks across scales. Learning reshaped mesoscale community organization into a network anchored by the amygdala, subthalamic-hypothalamic zone, and ventral midbrain tegmentum. These regions contributed distinct components of adaptive avoidance and engaged diverse transcriptional programs across multiple neuronal subclasses. Within this network, the amygdala acted as a hub, partitioning action and outcome information and remapping neural geometry to segregate punished from safe actions. Together, these results identify a multiscale neural architecture through which aversive experience can be transformed into flexible behavioral control.

neuroscience↗

Pharmacological Induction of Irreversible Senescence in Drug-Tolerant Persister Cells Prevents Tumor Relapse

Despite substantial advances in targeted therapies, most patients with advanced cancers ultimately relapse. This relapse is frequently seeded by drug-tolerant persister cells (DTPs), which persist as minimal residual disease (MRD) by adopting a reversible quiescent state and later reacquire proliferative capacity under ongoing treatment. To address this, we sought to convert quiescent DTPs into an irreversible, non-proliferative state by pharmacologically inducing senescence. Through large-scale chemical screening and combination optimization, we identified SAHA plus tilorone dihydrochloride (SIC) as a regimen that robustly induces senescence in melanoma DTPs and abolishes their proliferative potential in vitro. Mechanistically, SAHA relieves HDAC1-mediated repression of HMGA2, a key senescence driver, while tilorone synergistically inhibits autophagy to promote a fully senescent state. In a melanoma xenograft mouse model receiving MAPK-targeted therapy, SIC treatment significantly suppressed MRD progression. Importantly, SIC also induced robust senescence across diverse DTP models irrespective of tumor origin, mutational background, or prior treatment. Collectively, these findings provide proof-of-concept that converting DTPs from reversible quiescence to permanent senescence represents an effective strategy to prevent relapse under targeted therapy and position SIC as a broadly applicable pharmacological approach for durable control of residual disease in advanced cancers.

cancer biology↗

Translation-specific disruption of Col1a1 expression in multiple models of Spinal Muscular Atrophy can be rescued by Risdiplam.

Spinal muscular atrophy (SMA) is a monogenic neurodegenerative disorder caused by decreased levels of Survival of Motor Neuron (SMN) protein. If left untreated, SMA patients have a poor prognosis, marked by the degeneration of motor neurons, progressive muscle weakness and atrophy. The approval of SMN-restoring therapies that improve symptoms and lifespan in patients with SMA has created emerging, non-neuronal phenotypes and an urgent need for deepening our understanding of disease pathogenesis. Leveraging the knowledge that SMN loss drives alterations in translation, we used multiple tissues from a mouse model of SMA to uncover early translational alterations in key mRNAs and proteins, which act as contributors to pathogenesis and hallmarks of the disease. Among hundreds of differentially translated mRNAs, Col1a1 emerged as a translation-specific manifestation of early defects in the mouse model. These findings were confirmed in fibroblasts derived from patients with varying levels of disease severity. Notably, treatment with SMN-restoring therapies rescued COL1A1 protein levels, particularly in fibroblasts from patients with the most severe forms of the disease. Overall, our study identifies COL1A1 as an indicator of disease severity in SMA, which captures early molecular alterations and respond to SMN-modifying therapies.

molecular biology↗

SNP calling, haplotype phasing and allele-specific analysis with long RNA-seq reads

Long-read RNA sequencing (lrRNA-seq) is a powerful technology to link transcript structures to genetic variants but such analysis is not often performed due to the lack of end-user tools. Here, we introduce longcallR for joint SNP calling, haplotype phasing, and allele-specific analysis, which achieves high accuracy on benchmark datasets. Applied to 202 human samples, longcallR identified 88 significant allele-specific splicing events per sample on average. 46% of them involved unannotated junctions.

bioinformatics↗

Disturbed engram network caused by NPTXs downregulation underlies aging-related memory deficits

Engram cells storing specific memories are allocated to separate neuronal ensembles, which preferentially recruit either excitatory or inhibitory inputs to drive precise memory expression. However, how these formed neuronal ensembles maintain their stability, and whether the disturbed stability contributes to aging-related memory deficits remain elusive. Here, we show that neuronal pentraxin1 (NPTX1) facilitates Kv7.2-mediated inhibition of Fos+ensemble hyperexcitability, thereby restricting its response to excitatory inputs from medial entorhinal cortex (MEC) and promoting memory expression in the fear context. Meanwhile, NPTX2 facilitates the perisomatic inhibition of the Npas4+ ensemble by parvalbumin+ (PV+) interneurons, thus preventing fear memory overgeneralization. Pharmacological activation of Kv7.2 or chemogenetic activation of PV+ interneurons repaired memory deficits caused by engram specific NPTXs depletion. Contextual fear memory precision and NPTXs expression in dentate gyrus (DG) engram cells are decreased in aged mice. Overexpression of NPTX1 in Fos+ensemble or AMPAR binding domain of NPTX2 in Npas4+ ensemble rescued memory imprecision. These findings elucidate that the coordination of NPTXs prevents engram ensembles from becoming hyperactive and provide a causal link between engram network destabilization and aging-associated memory deficits.

neuroscience↗

F-53B damages cell viability leading to impaired root development in Arabidopsis

The emerging contaminant chlorinated polyfluoroalkyl ether sulfonate (Cl-PFAES/F-53B) has been detected in many plant species, however, the impact of F-53B on the development in plants and the underpinning mechanisms remain largely unelucidated. In this study, we demonstrate by molecular biology, cytogenetics, and fluorescence microscopy mythologies that F-53B impairs cell viability leading to disrupted root development in Arabidopsis (Arabidopsis thaliana). We show that F-53B suppresses root length and the inhibitory effect is pronunanced at increasing concentrations. F-53B disrupts cell wall and microtubule-mediated cell plate formation and configuration in meristem cells, revealing its toxicity to cell division and cytoskeleton organization. F-53B induces cell death predominantly at the meristematic zone, however, gene exression and genetic studies indicate that F-53B does not trigger DNA double-strand breaks, implying a divergent effect on DNA stability across species. Moreover, we show that F-53B damages nuclei stability and viability, and induces Autophagy-Related 8 protein foci formation implying that it triggers autophagy-mediated cell responses. Taken together, this study provides cellular and molecular insights into the toxicity of F-53B to plant cells, which highlights its damage to agriculture and ecology security that deserve imperative environmental management actions. Environmental ImplicationF-53B has been detected in many plant species, which raises increasing concerns on its toxicity to plants and thus agriculture and ecology safety. However, the toxicity of F-53B to development in plants and the underpinning mechanisms remain largely unelucidated. Here, we demonstrate that F-53B damages nuclei stability and viability leading to cell death and impaired root development in the model plant species Arabidopsis thaliana. Our study provides cytogenetic and molecular insights into the F-53B toxicity to plant cells, which highlights imperative environmental management actions and can be referenced for developing F-53B control and management policies. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/653422v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@159b211org.highwire.dtl.DTLVardef@1b99a95org.highwire.dtl.DTLVardef@53b964org.highwire.dtl.DTLVardef@b089be_HPS_FORMAT_FIGEXP M_FIG C_FIG One-sentence summaryF-53B triggers DNA double-strand break-free cell unviability leading to impaired meristematic cell division and root development in plants. HIGHLIGHTSO_LIF-53B impairs root development in Arabidopsis. C_LIO_LIF-53B prohibits mitotic cell division at root tips. C_LIO_LIF-53B damages cell viability predominantly at the meristematic zone in seedlings. C_LIO_LIF-53B does not induce DNA double-strand breaks in Arabidopsis seedlings. C_LIO_LIF-53B damages nuclei viability and stability in seedlings. C_LI

developmental biology↗

The phosphatases TCPTP, PTPN22, and SHP1 play unique roles in T cell phosphotyrosine maintenance and feedback regulation of the TCR

The protein tyrosine phosphatases (PTPs) TCPTP, PTPN22, and SHP1 are critical regulators of the activating phosphotyrosine (pY) site on the initiating T cell kinase, LckY394. Still, the broader implications of these phosphatases in T cell receptor (TCR) signalling and T cell biology remain unclear. By combining CRISPR/Cas9 gene editing and mass spectrometry, we evaluate the protein- and pY-level effects of TCPTP, PTPN22, and SHP1 in the Jurkat T cell model system. We find that deletion of each phosphatase corresponds to unique changes in the proteome of T cells, with few large-scale changes to TCR signalling proteins. Notably, PTPN22 and SHP1 deletions have opposing effects on pY abundance globally, while TCPTP deletion modestly elevates pY levels. Finally, we show that TCPTP is indirectly involved in Erk1/2 positive feedback to the TCR. Overall, our work provides evidence for alternative functions of three T cell phosphatases long thought to be redundant.

systems biology↗