Biology subjects

Feng, J.

Publications and source records attributed to Feng, J..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

ERAD Activity Distinguishes the Functional Heterogeneity of Hematopoietic Stem Cells

Hematopoietic stem cells (HSCs) rely on precisely controlled proteostasis to sustain lifelong self-renewal, yet whether intrinsic proteostatic characteristics can prospectively define functional diversity within the HSC pool remains unknown. In this study, we developed a dual-fluorescence reporter system to visualize endoplasmic reticulum-associated degradation (ERAD) activity in vivo and discovered that ERAD activity can prospectively predicts the long-term reconstitution potential of HSCs. Remarkably, ERAD states were maintained through self-renewal, revealing an inheritable "proteostatic memory" within the HSC pool. Transcriptomic and functional analyses identified SOCS2 as a key regulator of this process: SOCS2 inhibits JAK2 signaling to sustain ERAD activity, whereas hyperactive JAK2 interacts with the ERAD E3 ligase Hrd1 and suppresses VCP-mediated misfolded substrate. These findings define a SOCS2-JAK2-ERAD axis that connects cytokine signaling to intrinsic proteostasis remodeling, establishing ERAD activity as a predictive and heritable marker of HSC function and providing a conceptual framework for understanding hematopoietic stem cell heterogeneity.

cell biology↗

bioRxiv2025

Overexpression of TPM4 promotes cancer progression through EMT in anaplastic thyroid cancer

Anaplastic thyroid cancer (ATC) is an undifferentiated tumour originating from thyroid follicular epithelium and represents the most malignant subtype of thyroid cancer. However, the mechanisms underlying ATC development are not fully understood. This study aimed to investigate the mechanisms driving ATC invasion and metastasis to provide novel insights into its aggressive behavior. Through an integrated bioinformatics analysis of the GEO database, we identified Tropomyosin 4 (TPM4) as a differentially expressed gene in ATC. Bioinformatic correlation and pathway enrichment analyses suggested that TPM4 expression is potentially linked to tumor cell invasion and lymph node metastasis. We showed that TPM4 was highly expressed in both ATC tissues and cell lines, and its expression levels were positively correlated with enhanced cell migration and invasion. Mechanistic studies indicated that TPM4 likely enhances tumour cell migration and invasion by facilitating cytoskeletal remodeling and promoting the epithelial-mesenchymal transition (EMT). Our findings suggest that TPM4 represents a promising diagnostic and therapeutic biomarker for ATC.

cancer biology↗

bioRxiv2025

How minor sequence changes enable mechanistic diversity in MFS transporters? An atomic-level rationale for symport emergence in NarU

AbstractClosely related membrane transporters can diverge sharply in their modes of trans-port despite minimal sequence differences, underscoring how minor structural features can alter transport function. This divergence is exemplified in nitrate and nitrite trans-port across bacterial membranes, which supports anaerobic respiration and involves the major facilitator superfamily (MFS) transporters NarK and NarU. NarK operates as a nitrate/nitrite antiporter, whereas NarUs mechanism remains unresolved, with evidence suggesting potential symport activity. Using extensive adaptive molecular dynamics simulations and Markov State Modeling, we mapped NarUs conformational free-energy landscape and assessed how its behavior contrasts with mechanistic prin-ciples established for NarK. NarU follows a similar gating pathway but displays pro-nounced asymmetry favoring the outward-facing state and stabilizes an apo-occluded intermediate inaccessible to antiporters. This state arises from rotation of an argi-nine gating pair and a hinge glycine substitution that enhances gate flexibility. These sequence-dependent adaptations alter gating energetics and reprogram the scaffold to permit coupled co-transport. Our results show that a presence of a few strategic residue substitutions in the binding pocket and translocation pathway could alter the transport mechanism of transporters with high sequence and structural similarity.

biophysics↗

bioRxiv2025

The electrophilic metabolite of kynurenine, kynurenine-CKA, targets C151 in Keap1 to derepress Nrf2.

The Kelch-like ECH-associated protein 1 / Nuclear factor-erythroid 2 p45-related factor 2 (Keap1/Nrf2) system responds to a wide array of structurally diverse small molecules, of both exogenous and endogenous origin, by inducing a robust cytoprotective program that allows adaptation during oxidative, metabolic and inflammatory stress. Here, we report that exposure to the tryptophan metabolite kynurenine and its electrophilic derivative kynurenine-carboxyketoalkene (Kyn-CKA) leads to an increase in the abundance of transcription factor Nrf2 and induction of Nrf2-target genes, including NAD(P)H:quinone oxidoreductase 1 (NQO1), in murine and human cells. Additionally, both kynurenine and Kyn-CKA activate the aryl hydrocarbon receptor (AhR). Using cellular thermal shift assays, we found that Kyn-CKA increases the thermal stability of Keap1-mCherry fusion protein, but not free mCherry, indicating target engagement of Keap1, the principal repressor of Nrf2. The use of purified recombinant BTB domain of Keap1 and its C151S mutant counterpart revealed that Kyn-CKA reacts with wild-type, but not C151S mutant, Keap1-BTB, and at a much faster rate than with the small molecule thiol N-acetyl cysteine, demonstrating Kyn-CKA is targeted to react with C151 by the surrounding protein environment. In close agreement, Kyn-CKA increased the abundance of Nrf2 and expression of NQO1 in mouse embryonic fibroblast (MEF) cells expressing wild-type Keap1, but its inducer potency was greatly diminished in C151S-Keap1 mutant MEFs. Experiments in WT, AhR-knockout, and Nrf2-knockout primary murine bone marrow-derived macrophages showed that Nrf2 is required for the acute anti-inflammatory activity of Kyn-CKA, whereas AhR is dispensable. Together, these findings demonstrate that Kyn-CKA targets C151 in Keap1 to derepress Nrf2 and reveal that Nrf2, but not AhR, is a main contributor to the anti-inflammatory activity of Kyn-CKA in macrophages.

biochemistry↗

bioRxiv2025

Structure-Based Calculation of Excipient Effects on the Viscosity ofConcentrated Antibody Solutions

Computational prediction of the viscosity of therapeutic monoclonal antibodies (mAbs) at high concentration is highly desirable in the early discovery and development phases where the material needed for experimental determination is typically limited. Here, we present a unique coarse-grained (CG) simulation method that enables residue-level simulation of full-length antibodies with an elastic network, under simulated shearing force, to de novo predict viscosities of solutions of two distinct mAbs (an IgG1 and an IgG4), in the absence and presence of 6 excipients. Our results suggest the method can properly distinguish the viscosity profile of the two model mAbs, and directionally forecast viscosity change in response to added excipients. Furthermore, this CG modeling approach provides detailed protein-protein interaction mapping down to residue level contacts, including contact lifetimes and nature of interactions, illuminating microscopic insights into the underlying molecular interactions. It serves as a valuable tool for viscosity prediction, mechanistic insights, and mitigation strategies.

pharmacology and toxicology↗

bioRxiv2025

Cell recovery and DNA extraction methods skew relative abundance estimations of foodborne pathogens and spoilage organisms on stainless steel surfaces

Studies investigating surface microbiota in food facilities often include estimates of relative abundance. However, obtaining accurate relative abundance values can be challenging. Differences among microbes can lead to different degrees of cell recovery from the surface and different DNA extraction yields that skew downstream relative abundance estimates. Here, we evaluated (1) the impact of cell recovery from surfaces using sponge swabs and (2) DNA extraction protocol on the relative abundance estimates of relative abundance on artificially inoculated surfaces. Our results showed that Escherichia coli (Gram-negative cell), Listeria monocytogenes (Gram-positive cell), Bacillus cereus (bacterial spore), Alicyclobacillus suci (bacterial spore), Exophiala phaeomuriformis (fungal cell), Aspergillus fischeri (fungal spore) differed significantly (p<0.05) in their recovery rates from stainless steel surfaces, ranging from 2.9%{+/-}3.0% recovery to 94.9%{+/-}3.0% recovery. Modification of the DNA extraction protocol by extending the bead-beating step by 10 min generally improved DNA yields, though the impact varied by organism. For example, DNA yields of E. coli increased from 70 to 84 ng/mL while that of L. monocytogenes increased only from 23.2 to 29.2 ng/mL. Amplicon sequencing results indicated that the differences in cell recovery and DNA extraction among microbial species skewed the relative abundance estimates from inoculated surfaces. For example, the estimated relative abundance of L. monocytogenes was 9-17%, which was lower than its actual relative abundance (25%). These results underscore the limitations of surface microbiota characterization in food facilities and highlighted the need to improve current recovery and DNA extraction methods. ImportanceAmplicon sequencing has been used to characterize microbial communities on facility surfaces. However, few studies have evaluated the accuracy of the amplicon sequencing workflow for quantifying spoilage and pathogenic organisms in these microbial communities. Here, we assessed the accuracy for amplicon sequencing to evaluate the relative abundance of spoilage and pathogenic organisms commonly found in food processing environments. The results revealed biases in relative abundances due to limitations in cell recover and DNA extraction methods. These findings revealed the potential biases in surface microbiota characterization in food facilities, and the need to refine current recovery and extraction methods to enhance the accuracy of microbiota characterization.

microbiology↗

bioRxiv2025

Gene library deep sequencing for protein super-family profiling

Unravelling protein function at scale remains challenging. Gain-of-function (GOF) screens harnessing large open reading frame (ORF) libraries enable systematic functional annotations of cell behavior drivers and drug targets. Currently, few sequencing methods are established to analyze existing ORF libraries and facilitate future library generation. Here, we developed a barcode-free deep sequencing method termed pooled plasmid library sequencing (PPLseq). PPLseq achieved high efficiency and single nucleotide accuracy, including the detection of previously undocumented variants, on a prototypical super-family ORF library (>300 human G-protein-coupled receptors (GPCRs)). We next combined PPLseq with high-throughput gene engineering to generate a new library of 246 GPCR-fluorescent protein (FP) fusions. We quantified expression of all members of this library and identified robustly expressed yet understudied receptors. Collectively, we demonstrate accessible, scalable, and sensitive ORF library sequencing towards a deeper understanding of proteome function.

synthetic biology↗

bioRxiv2025

Chronic kidney disease exacerbates hyperlipidemia and atherosclerosis via miR-148a-3p targeting SIK1/AMPKα1 in liver

BackgroundCardiovascular complications are the leading cause of death in patients with chronic kidney disease (CKD). As a major risk factor for atherosclerotic cardiovascular disease (ASCVD), hyperlipidemia is a common sequela of CKD, which is linked to increased lipid synthesis, impaired lipoprotein clearance, and maladapted reverse cholesterol transport. Because exosomes can transport miRNAs to modulate intercellular and tissue communication, we hypothesized that exosomal miRNAs can act as endocrine-like molecules to modulate the CKD-associated hyperlipidemia and ASCVD. MethodsSmall RNA-seq and qPCR were used to determine the differential plasma level of exosomal miR-148a-3p in ASCVD patients with and without CKD. RNA-seq and in silico analysis were used to establish the regulation of lipid metabolism via miR-148a-3p/salt-inducible kinase 1 (SIK1)/AMP-activated protein kinase alpha 1 subunit (AMPK1) in the liver. Inhibition of miR-148a-3p or overexpression of SIK1/AMPK1 in ApoE-/- mice with 5/6 nephrectomy was used to elucidate the role of the miR-148a-3p/SIK1/AMPK1 axis in CKD-related hyperlipidemia and atherosclerosis. ResultsThe plasma level of exosomal miR-148a-3p was significantly elevated in patients with ASCVD and CKD (ASCVD/CKD) and ApoE-/- mice with 5/6 nephrectomy. Via circulating exosomes, kidney-generated miR-148a-3p was delivered to the liver, where it targeted SIK1/AMPK1 transcripts, thereby upregulating SREBP2/PCSK9 and reciprocally downregulating LDLR. Levels of SIK1 and AMPK1 were decreased in hepatocytes transfected with miR-148a-3p or treated with plasma exosomes from ASCVD/CKD patients, with attendant SREBP2 activation and attenuated LDL-C binding. The decreased LDL-C binding was rectified by SIK1/AMPK1 or LNA-miR-148a-3p overexpression. LNA-miR-148a-3p or AAV8-SIK1/AMPK administration in 5/6 nephrectomy/ApoE-/- mice significantly ameliorated hyperlipidemia and atherosclerosis. ConclusionIn ASCVD/CKD patients and nephrectomy/ApoE-/- mice, kidney-originating miR-148a-3p targeted hepatic SIK1/AMPK1 mRNA. This exosome-mediated endocrine effect upregulated SREBP2/PCSK9 and reciprocally reduced LDLR level, which elevated plasma LDL-C level and exacerbated ASCVD. These findings underscore a kidney-liver-artery axis involved in cardiovascular-kidney-metabolic syndrome.

pathology↗

bioRxiv2025

Template switching by coronavirus polymerase requires helicase activity and is stimulated by remdesivir and molnupiravir

Polymerase template switching is an essential mechanism in coronaviruses (CoVs) that enables both sub-genomic (sg) RNA synthesis and increases genomic diversity via RNA recombination. Despite its importance, the molecular mechanism of CoV polymerase template switching remains unclear. Using magnetic tweezers, we show that the CoV non-structural protein (nsp) 13-helicase drives polymerase template switching, followed by copy-back RNA synthesis. This activity requires nsp13-helicase ATPase activity and a duplex RNA downstream of the CoV polymerase. This novel function of nsp13-helicase is targeted by the nucleotide analogs remdesivir and molnupiravir, whose incorporation in the nascent strand increases CoV polymerase template switching probability, leading to defective RNA production. We propose a novel mechanism of action where incorporation of these analogs dramatically reduces full length genome copy number by stimulating polymerase template switching. Our study further demonstrates nsp13-helicases central role in CoV replication and how this enzyme function can be indirectly targeted by analogs.

microbiology↗

bioRxiv2025

The turbulent brain: Modelling vortex interactions for understanding human cognition

The human brain needs distributed, time-critical computation to efficiently solve complex problems. Turbulence provides such highly efficient spacetime information processing and transmission across wide-spread brain networks, yet we have been missing a mechanistic understanding of the interactions of turbulent vortices underlying human cognition. Here, we build the first whole-brain model of turbulent vortices as defined by the levels of local synchronisation in brain signals quantifying turbulent interactions in vortex space. Specifically, using large-scale human neuroimaging data, we found that the interactions of turbulent vortices is an excellent framework for understanding cognition and brain computation. It is not only useful for distinguishing the detailed spacetime dynamics of rest and cognition - but can even distinguish between subtle sub-components of cognitive tasks, where manipulation of vortices can be shown to change cognition. Overall, this whole-brain framework creates a natural vortex space for the brain computation underlying cognition, as well as potentially providing novel ways of controlling turbulent interactions in disease.

neuroscience↗

bioRxiv2025

ADAMTS3 as a promising novel biomarker for the diagnosis of hepatocellular carcinoma

Early diagnosis of hepatocellular carcinoma (HCC) still represents a significant challenge. The rising of obesity and non-viral liver disease associated HCC further limits the effectiveness of conventional screening approaches such as ultrasonography and alpha-fetoprotein (AFP) testing. In this context, the identification of potential effective biomarkers for rapid and precise diagnosis of HCC still represents an extremely important task. Here, we identify ADAMTS3 as a novel mechanistic serum biomarker for HCC that addresses this shifting etiological landscape. Transcriptome analysis of four independent cohorts-including HCC patients, individuals with obesity-or non-viral liver disease, and healthy controls- reveals four secreted proteins associated with HCC progression. Among them, ADAMTS3 demonstrates strong diagnostic performance by ROC (receiver operating characteristic) and LASSO (least absolute shrinkage and selection operator) analysis. High ADAMTS3 expression correlates with aggressive molecular signature, characterized by enhanced proliferative signaling, suppressed immune effector responses, and a reprogrammed immune microenvironment marked by reduced NK cell infiltration and increased accumulation of immunosuppressive tumor-associated macrophages, driven by extracellular matrix stiffening. Knockdown of ADAMTS3 in cell lines significantly reduced proliferation, and clonogenic potential. Reintroduction of ADAMTS3 partially rescued both phenotypes, further confirming its role in promoting HCC cell growth. Optical tweezer-based measurements further reveal reduced cell stiffness upon ADAMTS3 deficiency, highlighting its role in extracellular matrix (ECM) remodeling. Finally, to provide a simple strategy for HCC diagnosis based on this novel biomarker, we demonstrated a DNA origami-based SERS biosensor capable of detecting ADAMTS3 at 10-11 M. Together, these findings identify ADAMTS3 as a mechanistic biomarker and demonstrate a translational sensing strategy for non-invasive HCC early screening.

cancer biology↗

bioRxiv2025

RhoV Promotes Proliferation, Migration, and MAPK Activation in Pancreatic Ductal Adenocarcinoma

Background and AimsPancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy characterized by diagnosis at advanced stages, limited therapeutic options, and frequent resistance to therapies. Although oncogenic KRAS mutations are central drivers of PDAC, alternative pathways indisputably contribute to its tumorigenesis and progression. RhoV, a member of the Rho family of small GTPases, has been implicated in tumor development in other cancer types, such as breast cancer and lung adenocarcinoma; however, its role in PDAC remains unclear. MethodsIn this study, we investigated the expression and functional impact of RhoV on PDAC. Analysis of publicly available datasets and immunohistochemical profiling of 114 PDAC patient specimens were used to evaluate the expression of RhoV in PDAC and its prognostic impact. Overexpression and CRISPR-Cas9-mediated knockout of RhoV were established in three pancreatic cancer cell lines. Functional analyses, such as cell proliferation, migration, invasion, colony formation, spheroid growth, and mouse xenograft, were used to evaluate the role of RhoV in PDAC cells. ResultsRhoV overexpression was associated with reduced overall and recurrence-free survival in public datasets and our own patient cohort. Functional assays demonstrated that RhoV overexpression promoted PDAC cell proliferation, colony formation, and spheroid growth, whereas knockout of RhoV suppressed these changes. Moreover, RhoV enhanced PDAC cell migration and invasion in vitro, accompanied by downregulation of E-cadherin and upregulation of N-cadherin and vimentin, indicating induction of epithelial-mesenchymal transition. Mechanistically, RhoV overexpression activated key MAPK pathway components, including phosphorylation of ERK, JNK, and p38. In vivo, xenograft models confirmed that RhoV drives tumor growth and increases tumor burden. ConclusionThese results establish RhoV as a novel oncogenic factor in PDAC progression and highlight its potential as a biomarker and therapeutic target, warranting further investigation into combinatorial targeting strategies to overcome KRAS inhibitor resistance.

cancer biology↗

bioRxiv2025

Integrative Multi-omics Deciphers the Assembly Rules of the Human Skin Microbiome and Highlights Lipid-Mediated Niche Partitioning

Understanding the ecological assembly mechanisms of microbial communities is critical for deciphering host-microbiota interactions, however, such processes remain poorly characterized in cutaneous ecosystems. By profiling a non-industrialized rural cohort, this study deciphers the assembly rules governing the human skin microbiome and reveals an evolutionarily conserved core microbiota structured by niche selection. Microbial -diversity peaks when C. acnes and M. osloensis reach equilibrium, supporting the Intermediate Disturbance Hypothesis. Host lipids, rather than aqueous compounds, emerged as the primary drivers of microbial niche partitioning. We further demonstrate that C. acnes and Malassezia restricta function as core metabolic engineers, expressing diverse lipases that hydrolyze triglycerides (TGs) into free fatty acids (FFAs), thereby maintaining skin surface lipid homeostasis ([~]85% TG + FFA). Notably, virtually all skin surface FFAs are microbially derived and function as "public goods", enabling cross-feeding that supports auxotrophic members and fosters mutualistic interactions. Importantly, in vitro coculture experiments confirm that C. acnes establish a survival niche for M. restricta. Our findings support a paradigm shift from a taxonomic to a functional understanding of the skin ecosystem, underscoring microbial lipid metabolism as a central orchestrator of ecological stability and a promising target for therapeutic intervention. O_FIG O_LINKSMALLFIG WIDTH=182 HEIGHT=200 SRC="FIGDIR/small/674196v1_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@1274fa5org.highwire.dtl.DTLVardef@1ddfa07org.highwire.dtl.DTLVardef@49f917org.highwire.dtl.DTLVardef@807a14_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGRAPHIC ABSTRACTC_FLOATNO C_FIG

microbiology↗

bioRxiv2025

Merits and challenges of plasma proteomics on association replicability

Developments in proteomic platforms have enabled the generation of large-scale high-throughput plasma proteomics data [1-3]. With recent breakthroughs in AI modelling, these data have significantly enhanced our understanding of molecular mechanisms underlying human behaviors and diseases [4-6]. However, the replicability of associations between plasma proteomics and phenotypes remains underexplored. Here, we systematically assessed the replicability of associations with recent plasma proteomics data in the UK biobank. Over 75% of cognitive function and mental health traits demonstrated high overall (proteomics-wide) replicability when brain-related traits were considered as phenotypes. Although mean cortical thickness (CT) as phenotype exhibited clearly reduced replicability, total cortical surface area (CSA) and cortical volume (CV) showed high overall replicability across hemispheres and over twenty brain regions. In comparative multi-omics analyses based on the same cohort of participants, proteomics outperformed genomics across all brain-related traits, and exceeded metabolomics for over half of traits where metabolomics also exhibited high overall replicability. Furthermore, we developed a predictive framework to estimate the replicability for potential future proteomics panels based on the crucial influential factors including dilution level, proportion of samples below the limit of detection (LOD), and sample size. Moreover, we constructed an individual replicability index for proteins and identified eleven proteins with highly replicable associations across cognitive function and mental health traits, which was in line with the recent identifications of pleiotropic proteins in large-scale population studies. Collectively, our results revealed the challenges in the association replicability of plasma proteomics under reduced data quality (from "Explore" to "Expansion" assay panels), and we further explored how to sustain high replicability in potential future panels. Fundamentally, our findings affirm the merits of plasma proteomics: this molecular omics platform enables highly replicable associations for mapping biomedical signatures.

bioinformatics↗

bioRxiv2025

ESMDynamic: A Fast and Accurate Prediction of Protein Dynamic Contact Maps from Single Sequences

Understanding conformational dynamics is essential for elucidating protein function, yet most deep learning models in structural biology predict only static structures. Here, we present ESMDynamic, a deep learning model that predicts residue-residue contact dynamics directly from protein sequence. Built on the ESMFold architecture and trained on conformational variability from experimental structure ensembles and molecular dynamics (MD) simulations, ESMDynamic predicts dynamic contact probabilities, contact frequencies reflecting equilibrium populations, and coarse-grained kinetics of contact formation and dissociation across multiple temperature conditions. On large-scale MD benchmarks (mdCATH and ATLAS), ESMDynamic matches or outperforms state-of-the-art ensemble prediction methods (AlphaFlow, ESMFlow, BioEmu) while requiring orders-of-magnitude less computation. We demonstrate generalization to diverse systems, including membrane transporters, a de novo designed protein, and a homodimer complex. We show that predicted dynamic contacts enable automated selection of collective variables for Markov state model construction. Applied to the human proteome, ESMDynamic generates predictions for over 18,000 proteins, enabling large-scale analysis of conformational variability. Overall, ESMDynamic provides a scalable, sequence-based representation of protein dynamics to inform simulation, analysis, and design workflows.

biophysics↗

bioRxiv2025

Rationally Engineered Coronavirus-mimicking Protein Nanocage Platform for Glioblastoma Targeted Delivery and Immunity Regulation

Glioblastoma (GBM) is one of the most aggressive and treatment-resistant brain tumors, owing to the dual challenges of the blood-brain barrier (BBB) and a profoundly immunosuppressive tumor microenvironment. However, few existing strategies are capable of simultaneously overcoming these two barriers, underscoring a critical scientific gap and the need for innovative therapeutic platforms that enable both effective BBB traversal and tumor immune reprogramming. Here, we present a coronavirus-mimicking protein nanocage platform (EcomPC) derived from Thermotoga maritima encapsulin, rationally engineered for the targeted and sustained delivery of interferon- (IFN-) to GBM lesions. Through strategic insertion of flexible linkers, cysteine-to-serine mutations, and modular surface functionalization via SpyTag/SpyCatcher chemistry, EcomPC enables intracellular self-assembly of IFN- and glioma-specific targeting. In orthotopic GBM models, EcomPC-IFN demonstrates efficient BBB translocation, selective tumor accumulation, and potent anti-tumor efficacy. Mechanistically, localized IFN- release induces tumor cell apoptosis and reprograms the immune microenvironment--characterized by increased CD8 T cell infiltration, decreased Foxp3 regulatory T cells, and a favorable chemokine shift. These therapeutic effects are not recapitulated by free IFN- or untargeted nanocages, underscoring the essential role of both structural mimicry and ligand-guided delivery. Collectively, this work establishes EcomPC as a programmable, virus-inspired protein delivery platform capable of overcoming key physiological barriers in brain tumor immunotherapy, and lays the foundation for its broader application in CNS-targeted biologic delivery.

bioengineering↗

bioRxiv2025

Serotonin shapes the temporal window for associative fear learning

Fear learning is a critical adaptive mechanism that enables the association of an environmental cue (the conditioned stimulus, CS) with a potential threat (the unconditioned stimulus, US), even when these events are temporally discontiguous. When associations are instead formed between unrelated cues and threats, the maladaptive learning process can give rise to neurological disorders. Therefore, maintaining accurate temporal boundaries for forming such associations is crucial for distinguishing real threats from irrelevant stimuli. Despite its importance, the mechanisms defining this precise time window remain poorly understood. Here, we report that serotonin plays a crucial role in modulating the associable interval in trace fear conditioning. Specifically, we show that serotonergic projections from the dorsal raphe nuclei (DRN) to the CA1 region of the ventral hippocampus (vCA1) dynamically regulate the association of discontiguous CS and US. Mechanistically, we demonstrate that sustained serotonin release in the vCA1 maintains the ensemble activity of 5-HT2C receptor-expressing pyramidal neurons, facilitating the association between temporally separated events. In contrast, when the trace interval exceeds the associable window, transient serotonin release fails to drive vCA1 neuronal ensemble activity, thus preventing maladaptive learning. These findings highlight a key role for serotonin in regulating the temporal precision of fear learning and reveal the DRN-vCA1 serotonergic pathway as a potential therapeutic target for related disorders.

neuroscience↗

bioRxiv2025

High-Affinity, Structure-Validated and Selective Macrocyclic Peptide Tools for Chemical Biology Studies of Huntingtin

Huntingtons disease (HD) is a fatal neurodegenerative disorder caused by a CAG repeat expansion in the Huntingtin (HTT) gene, with no disease-modifying therapies currently available. The precise molecular function of the HTT protein is unclear, and the lack of selective chemical tools has limited functional studies. We have identified and characterized macrocyclic peptide binders targeting HTT. These binders exhibit low-nanomolar affinity in vitro and engage distinct HTT and HTT-HAP40 interfaces, as revealed by hydrogen-deuterium exchange mass spectrometry and cryo-electron microscopy. Chemoproteomics confirmed selective binding in cell extracts from wildtype but not HTT-null cell lines. HAP40 consistently and stoichiometrically co-purified with HTT across cell lines, including with HTT variants containing different CAG repeat lengths, highlighting the broad presence of the HTT-HAP40 complex. Significance StatementHuntingtin (HTT) is a large, essential protein with conserved roles in development, intracellular trafficking, and protein homeostasis, yet its precise molecular functions remain incompletely defined. Here, we report the first high-affinity, selective, and structurally validated macrocyclic peptide ligands for HTT. These chemical tools bind HTT and its complex with HAP40 across polyglutamine repeat lengths, enabling direct interrogation of HTT structure and function in health and disease contexts. By overcoming longstanding barriers to studying HTT at the molecular level, these ligands open new avenues for discovery in neurobiology, cell biology, and offer opportunities for therapeutic development. This study delivers urgently needed tools to both the Huntingtons disease field and the broader scientific community seeking to understand this elusive and biologically fundamental protein.

biochemistry↗