Biology subjects

Li, Z.

Publications and source records attributed to Li, Z..

At least 469 records · Page 26Linked to original sources

bioRxiv2025

ERK and PKA signaling drive the evolutionary expansion of the cortex

The human cerebral cortex, essential for intelligence, cognition, and language, evolved its uniqueness through mechanisms that drive neuronal expansion. Here, we demonstrate that ERK and PKA signaling cooperatively preserve the neurogenic capacity of cortical radial glia (RGs) by inhibiting gliogenic YAP/TAZ and SHH signaling. YAP/TAZ signaling drives cortical RGs toward ependymal fate, while SHH signaling facilitates the generation of cortical tripotential intermediate progenitor cells that produce cortical astrocytes, oligodendrocytes, and olfactory bulb interneurons. During evolution, cortical outer radial glia (oRGs) acquire dominant ERK/PKA signaling through a self-reinforcing feedback mechanism that suppresses both YAP and SHH pathways, thereby significantly enhancing oRG self-renewal capacity and extending the neurogenic period. These findings reveal that cortical neurogenesis, gliogenesis, and evolutionary expansion are coordinately regulated by an integrated ERK, PKA, YAP/TAZ, and SHH signaling, identifying a unifying principle of mammalian cortical development and evolution.

developmental biology↗

bioRxiv2025

TUCL-Seq for miRNA single molecule sequencing

MicroRNAs (miRNAs) are pivotal regulatory molecules in gene expression, and their precise quantification is essential for elucidating their roles in diverse biological processes. This research paper introduces a pioneering workflow for the single molecule sequencing (SMS) of miRNA, integrating advanced miRNA sample preparation with SMS sequencing. Central to our approach is TUCL-Seq, which is an automated, on-chip miRNA library preparation method designed to streamline the sequencing process. This innovative approach incorporates the addition of sequencing adaptor to RNA samples in solution, and converts it to cDNA on a sequencing flow cell for sequencing. Coupled with single molecule sequencing instrument and base-call software, our workflow significantly reduces sample-to-result time, and decreases the need for manual interventions compared to traditional SMS and next-generation sequencing methods. We demonstrate the efficacy of TUCL-Seq by accurately quantifying synthetic miRNA samples with a 24-hour workflow, showcasing its potential for high-throughput miRNA profiling. Our findings highlight the promise of this integrated workflow for advancing miRNA research and applications in diagnostics and therapeutics.

biochemistry↗

bioRxiv2025

Pathogenic potential prediction of Vibrio parahaemolyticus by using pangenome data with high performance machine learning algorithms

The presence of Vibrio parahaemolyticus (Vp) at various stages of seafood production has adversely affected public health and threatened the sustainability of the industry. To address the critical public health threats posed by this prevalent seafood-borne pathogen, this research applied advanced machine learning (ML) and deep learning (DL) algorithms to predict the pathogenic potential of Vp using pangenome data. Utilizing comprehensive pangenomic assemblies and sophisticated ML/DL models, this study achieved robust and precise pathogenic potential prediction of Vp based on source attribution, which provides a novel reliable diagnostic tool facilitating conventional serotyping and virulence gene combination approaches. Based on results, non-core regions in Vp pangenome exhibited useful signals ML models can utilize in pathogenic potential determination process. Tree-based ensemble learning methods (Random Forest and Gradient Boosting Trees) have shown the distinguished performance with AUC score 0.97 based on selected pangenome matrix. Furthermore, Convolutional Neural Network successfully predicted the pathogenic potential of isolates with slightly better performance with AUC score 0.98 based on full pangenome. Critical biological insights revealing critical pathogenic potential-associated genes were retrieved from established ML/DL models: the gene feature weight analysis from Random Forest revealed the importance of accessory genes during Vp evolution (similarly highlighted by Gram-cam analysis of Convolutional Neural Network), which provided potential guidance for future research direction.

microbiology↗

bioRxiv2025

Aging-dependent dysregulation of EXOSC2 is maintained in cancer as a dependency

Reprogramming of aged donor tissue cells into induced pluripotent stem cells (A-iPSC) preserved the epigenetic memory of aged-donor tissue, defined as genomic instability and poor tissue differentiation in our previous study. The unbalanced expression of RNA exosome subunits affects the RNA degradation complex function and is associated with geriatric diseases including premature aging and cancer progression. We hypothesized that the age-dependent progressive subtle dysregulation of EXOSC2 (exosome component 2) causes the aging traits (abnormal cell cycle and poor tissue differentiation). We used embryonic stem cells as a tool to study EXOSC2 function as the aging trait epigenetic memory determined in A-iPSC because these aging traits could not be studied in senesced aged cells or immortalized cancer cells. We found that the regulatory subunit of PP2A phosphatase, PPP2R5E, is a key target of EXOSC2 and this regulation is preserved in stem cells and cancer.

cell biology↗

bioRxiv2025

Connecting the Dots: A Computational Framework linking Molecular Regulation, Synaptic Plasticity, and Brain Disorders

Neuroplasticity supports learning, development, and adaptive behavior, but also underlies maladaptive circuit remodeling in neuropsychiatric disorders. Although genetic disruptions of synaptic signaling are widely implicated in these conditions, the causal chain from molecular perturbation to systems-level dysfunction remains unclear. Here we introduce a multiscale computational framework--a parameter-free Boolean regulatory model of glutamatergic signaling--that captures the dynamic control of synaptic plasticity. The model generates emergent attractor states corresponding to long-term potentiation and depression and reveals how these states arise from underlying Hebbian principles. In silico gene-knockout simulations show that specific molecular perturbations destabilize these attractors, impairing synaptic plasticity and producing circuit-level alterations characteristic of diverse brain disorders. Remarkably, the model recapitulates the opposing developmental trajectories of autism spectrum disorder and schizophrenia, offering a mechanistic account of their divergent cortical phenotypes. This computationally tractable and generalizable framework quantitatively links genetic variation to synaptic instability and clinical severity, aligning with experimental and clinical observations. By moving beyond correlative associations, it establishes a causal scaffold for tracing how molecular disruptions propagate through synaptic regulatory networks to impair brain function, informing integrative diagnostics and mechanism-based therapeutic strategies.

neuroscience↗

bioRxiv2025

Mechanistic basis for protection against fatty liver disease by CIDEB loss-of-function mutations

Background & AimsSomatic and germline CIDEB mutations are associated with protection from chronic liver diseases. The mechanistic basis and whether CIDEB suppression would be an effective therapy against fatty liver disease remain unclear. Methods21 CIDEB somatic mutations were introduced into cells to assess functionality. In vivo screening was used to trace Cideb mutant clones in mice fed normal chow, western (WD), and choline-deficient, L-amino acid-defined, high-fat (CDA-HFD) diets. Constitutive and conditional Cideb knockout mice were generated to study Cideb in liver disease. Isotope tracing was used to evaluate fatty acid oxidation and de novo lipogenesis. Transcriptomics, lipidomics, and metabolic analyses were utilized to explore molecular mechanisms. Double knockout models (Cideb/Atgl and Cideb/Ppara) tested mechanisms underlying Cideb loss. ResultsMost CIDEB mutations showed that they impair function, and lineage-tracing showed that loss-of-function clones were positively selected with some, but not all fatty liver inducing diets. Cideb KO mice were protected from WD, CDA-HFD, and alcohol diets, but had the greatest impact on CDA-HFD induced liver disease. Hepatocyte-specific Cideb deletion could ameliorate disease after MASLD establishment, modeling the impact of therapeutic siRNAs. Cideb loss protected livers via increased {beta}-oxidation, specifically through ATGL and PPARa activation. ConclusionsCideb deletion is more protective in some types of fatty liver disease. {beta}-oxidation is an important component of the Cideb protective mechanism. CIDEB inhibition represents a promising approach, and somatic mutations in CIDEB might predict the patient populations that might benefit the most.

physiology↗

bioRxiv2025

Noninvasive ultrasound targeted modulation of calcium influx in splenic immunocytes potentiates antineoplastic immunity attenuating hepatocellular carcinoma proliferation

The spleen, as the largest immune organ, plays a pivotal role in modulating immune responses, particularly in the context of carcinogenesis and tumor progression. Non-pharmacological manipulation, particularly splenic ultrasound stimulation (SUS), has demonstrated significant immunomodulatory efficacy in alleviating chronic inflammatory diseases, suggesting its potential to revitalize splenic immunocompetence suppressing tumor proliferation, yet remains underexplored. This study applied low-frequency pulsed focused ultrasound (FUS) noninvasively stimulating the spleen (FUS sti. spleen) to investigate the efficacy in enhancing antitumor immunity and suppressing hepatocellular carcinoma (HCC). The results showed that FUS sti. spleen significantly suppressed tumor proliferation, achieving a suppression rate of >70% for H22-HCC and >83% for Hepa1-6-HCC, along with significantly prolonged survival. Comprehensive flow cytometry, single-cell RNA sequencing (scRNA-seq) and cytokine analyses demonstrated that SUS profoundly reshaped the splenic and intratumoral immune landscape, specifically activating cytotoxic CD8+ T cells and NK cells while suppressing immunosuppressive cell populations. Mechanistically, FUS facilitated calcium influx in splenic immunocytes, activating multiple signaling pathways, such as TNF, NF{kappa}B, MAPK, HIF-1, and ErbB, thereby counteracting tumor-driven immunosuppressive polarization while potentiating robust immune activation that impedes malignant progression and neoplastic proliferation. Leveraging above insights, we developed spleen-targeted nanodroplets encapsulating bioavailable calcium ions (STNDs@Ca{superscript 2}), which, upon FUS stimulation, undergo cavitation-mediated controlled release of Ca{superscript 2}, further amplifying immunocyte activation and tumor suppression, achieving a remarkable H22-HCC suppression rate of over 90%. This study highlights the therapeutic potential of ultrasound-mediated splenic immunomodulation, both as a standalone intervention and in synergy with STNDs@Ca{superscript 2}, as a novel and noninvasive strategy for cancer immunotherapy.

biophysics↗

bioRxiv2025

Population structure and domestication history of the Javan banteng (Bos javanicus javanicus)

The domestication of the banteng in Southeast Asia is one of the Worlds least known livestock domestications, yet a vital component of the agricultural system in Indonesia and surrounding countries. Here we generated the first reference genome of the banteng and used it to analyze a set of 78 resequenced wild and domesticated bantengs, including 19 newly generated whole-genome sequenced samples of which three are historical samples. We found low heterozygosity and significant differentiation, the latter primarily driven by recent genetic drift and inbreeding in two populations, and clearly attributable to anthropogenically driven founder events or ex-situ breeding. Population structure when excluding these two populations was limited, and we found that the evolutionary divergence between wild and domestic banteng is moderate (FST = 0.14), relatively young (10,356 years), and with post-divergence gene flow. We found only weak signals of a domestication bottleneck between [~]6100-2900 years ago, and genetic diversity is on average higher in domestic than in wild banteng. Despite the soft domestication history, we found 56 candidate genes under selection during domestication, with the leptin receptor gene (LEPR) of particular interest due to the robust selection signal across methods, and its known association to metabolism, obesity and energy homeostasis. Finally, genetic load estimation revealed that Bali cattle in Australia have high realized load, while Bali cattle from Bali have high masked load. These findings provide the first genomic insights into an understudied bovine that is Critically Endangered in its wild form, and agriculturally important in its domesticated form.

evolutionary biology↗

bioRxiv2025

Learning interpretable representation for context-specific transcription regulatory networks using a foundation model

Gene expression is shaped by transcription regulatory networks (TRNs), where transcription regulators interact within regulatory elements in a context-specific manner. Despite significant efforts, understanding the intricate interactions of transcription regulators across different genomic regions and cell types remains a major challenge, largely due to data sparsity. Here, we introduce ChromBERT, a foundation model pre-trained on large-scale human ChIP-seq datasets. ChromBERT effectively captures the interaction syntax of approximately one thousand transcription regulators across diverse genomic contexts, generating interpretable representations of context-specific TRNs and their constituent regulators. Fine-tuned for various transcription regulation tasks, ChromBERT demonstrates superior performance in imputing previously unseen cistromes and modeling regulatory effects and dynamics in specific cell types. Notably, ChromBERT adapts its TRN representations for cell-type-specific tasks, providing deep insights into the roles of transcription regulators underlying observed regulatory effects or dynamics without requiring cell-type-specific genomic data for each regulator. By overcoming the limitations of sparse transcription regulator data, ChromBERT significantly enhances our ability to model, interpret, and predict transcriptional regulation across diverse biological contexts.

bioinformatics↗

bioRxiv2025

Object categorization based on abstract concepts by monkeys, humans, and vision models

Humans categorize objects at multiple levels of abstraction--animate versus inanimate, big versus small, and many other attributes. Despite its apparent challenge, the advent of deep neural networks (DNNs) has demonstrated that complex visual processing alone can support such classification without language or human-specific knowledge. This raises a natural question: to what extent can non-human primates, without language, perform such categorization? Although basic object-recognition behavior in monkeys such as similarity judgment has been extensively studied, their ability to classify objects across diverse rules remains poorly characterized. Here, we developed a task paradigm that enabled us to train monkeys on a large battery of binary classification tasks using natural object images, spanning more than 10 rules, such as animate versus inanimate, natural versus man-made objects, and mammalian versus non-mammalian animals. Monkeys acquired each rule in a few days, generalized the learned rules to new images, and exhibited error patterns consistent with human judgments. At the same time, their classification performance correlated more strongly with that of visual DNNs trained without language input, whereas human performance was better explained by language-informed DNNs. These results provide an important benchmark for the capacity of biological neural networks to perform image classification without language and human-specific knowledge.

neuroscience↗

bioRxiv2025

Compact lens-based dual-channel adaptive optics scanning laser ophthalmoscopy for in-vivo three-dimensional retinal imaging in mice

Adaptive optics (AO) enables cellular-resolution retinal imaging, yet mirror-based AOSLO systems are constrained by off-axis aberrations that restrict high-quality imaging to narrow fields of view, limiting in vivo studies of dynamic, large-scale retinal processes. Clinical translation of regenerative cell therapy to neurologic disease is hampered by attrition of donor neurons following transplantation. We hypothesized that early innate neuroinflammatory responses to retinal ganglion cell (RGC) transplantation underlie early death of donor cells and that next-generation imaging technologies would provide evidence for microglial attack of grafted neurons. We present a compact refractive lens-based AOSLO system that achieves two-color fluorescence imaging across up to a 16{degrees} field of view in mouse retina. Dual-wavelength excitation (488 nm and 552 nm) enables visualization of two fluorescence labels, while AO correction improves axial resolution and depth fidelity, allowing robust separation of structures through anatomical layers in retina. Using this platform, we performed 3D time-lapse imaging of microglia and longitudinal imaging in an optic nerve crush model, revealing layer-dependent differences in microglial motility, early activation signatures, and large-scale redistribution longitudinally. The system enabled widefield visualization of injury-associated vascular changes and spatial coupling between microglia and vasculature. Finally, depth-resolved two-color imaging captured immune responses to intravitreally transplanted RGCs, including host-cell recruitment, rapid neurite retraction following local immune-cell contact, and microglial phagocytosis of donor RGCs. Together, these results demonstrate that refractive AOSLO enables in vivo observations of microvascular organization, neuroimmune dynamics, injury responses, and transplanted-cell behavior with spatiotemporal resolution. Our data also suggests that modulation of microglial reactivity may improve outcomes of RGC transplantation. Significance StatementWide-field, depth-resolved imaging is essential for understanding how different cell types interact across a large retinal area, yet existing AOSLO systems retain limited imaging fields due to a conventional optical design using reflective spherical mirrors. Our refractive large-FOV AOSLO overcomes this limitation, enabling simultaneous two-color, diffraction-limited 3D imaging across an up to 16{degrees} field in vivo. This platform reveals previously inaccessible biological phenomena--including layer-specific microglial dynamics after optic nerve injury, microvascular remodeling, and rapid microglial rejection of transplanted RGCs--providing critical insight into neuroimmune behavior and retinal repair mechanisms at single-cell and subcellular resolution.

bioengineering↗

bioRxiv2025

AT1R and Integrin β3 Synergize to Drive Aortic Dissection via Non-Canonical Wnt/β-Catenin Signaling

Aortic dissection (AD), a life-threatening cardiovascular emergency, continues to impose high mortality due to insufficient therapeutic options, as monotherapy targeting angiotensin II type 1 receptor (AT1R) demonstrates limited clinical efficacy. Utilizing single-cell RNA sequencing, we identified integrin {beta}3 as a critical driver of AD progression, with expression levels positively correlated with disease severity. Histopathological validation in human AD specimens and a murine angiotensin II (AngII)-infusion model confirmed marked upregulation of integrin {beta}3 activation. Pharmacological blockade of integrin {beta}3 with Cyclo(-RGDfK) significantly attenuated aortic pathogenesis in vivo, reducing dissection incidence and aortic degeneration. Mechanistically, AngII-mediated AT1R activation induced formation of a receptor complex with integrin {beta}3, triggering its conformational activation. Transcriptomic profiling revealed that activated integrin {beta}3 potentiates vascular endothelial dysfunction by binding glycogen synthase kinase 3{beta} (GSK3{beta}), which stabilizes {beta}-catenin via a non-canonical Wnt signaling axis. This pathway drives endothelial barrier disruption, hallmarks of aortic wall destabilization in AD. Our findings unveil a previously unrecognized synergy between AT1R and integrin {beta}3, implicating aberrant Wnt/{beta}-catenin signaling as a nexus of endothelial injury in AD pathogenesis. These results advocate for a paradigm-shifting dual-therapeutic strategy concurrently targeting AT1R and integrin {beta}3 to restore vascular homeostasis, offering a mechanistically grounded approach to mitigate this lethal disease. This work bridges critical gaps in understanding AD pathophysiology and provides a transformative framework for precision therapeutics.

pharmacology and toxicology↗

bioRxiv2025

Predicting Three-Dimensional Atomic-Level Structures of Biomolecular Complexes

OpenComplex1 is an open-source platform for comprehending and developing biomolecular models. Based on the architectures of AlphaFold2 and AlphaFold-Multimer, the current version of OpenComplex realizes end-to-end predictions of the biomolecular three-dimensional (3D) structures including protein, RNA, and protein-RNA complexes. OpenComplex makes it able to infer and train models of biomolecular complexes in a unified framework and supports encoders that use both MSAs and protein language models (pLM). Through extensive training on both structure and sequence databases such as the Protein Data Bank (PDB) and RNA families (Rfam) database, OpenComplex is able to generate models with equivalent or better accuracy for a wide range of biomolecules including monomers or multimers of protein and RNA as well as protein-RNA complexes. In summary, OpenComplex is a powerful tool for predicting accurate biomolecular structures in diverse application scenarios.

molecular biology↗

bioRxiv2025

Profilin promotes lamellipodium protrusion by tuning the antagonistic activities of CP and VASP

Cell migration on rigid surfaces employs flat protrusions termed lamellipodia, which constitute the prime model system for branched actin filament networks that generate pushing forces for membrane movement. Branched actin filaments are nucleated by the Arp2/3 complex and play vital roles in various cell biological processes, such as organelle trafficking, phagocytosis and autophagy. Here we utilize genome editing to explore the functional connections between the actin monomer-binding protein profilin (Pfn), the filament nucleating Arp2/3 complex, its co-factor heterodimeric capping protein (CP) and the Ena/VASP family of actin filament polymerases in lamellipodial actin assembly. Individual and combinations of knockouts show that Pfn counters Ena/VASP but promotes Arp2/3 complex activity, while Ena/VASP and CP mutually antagonize each other. Notably, while Pfn is important for Arp2/3 complex activity irrespective of Ena/VASP, sensitivity of CP to Pfn removal is lost in the absence of Ena/VASP. Our findings establish Pfn as master regulator of Arp2/3 complex-dependent actin network formation, which differentially regulates VASP and its antagonizer CP. Finally, mathematical modeling of our data suggest that Ena/VASP and CP compete for binding at the lamellipodial edge, likely contributing to their functional antagonism at this subcellular site. This work provides critical insights into the molecular logic of branched actin network assembly in membrane protrusion and cellular force generation.

cell biology↗

bioRxiv2025

Temporal dynamics of proteome and phosphorproteome during neuronal differentiation in the reference KOLF2.1J iPSC line

Induced pluripotent stem cell (iPSC)-derived neurons have emerged as a powerful model to investigate both neuronal development and neurodegenerative diseases. Although transcriptomics and imaging have been applied to characterize neuronal development signatures, comprehensive datasets of protein and post-translational modifications (PTMs) are not readily available. Here, we applied quantitative proteomics and phosphoproteomics to profile the differentiation of the KOLF2.1J iPSC line, the first reference line of the iPSC Neurodegenerative Disease Initiative (iNDI) project. We developed an automated workflow enabling high-coverage enrichment of proteins and phosphoproteins. Our results revealed molecular signatures across proteomic and phosphoproteomic landscapes during differentiation of iPSC-derived neurons. Proteomic data highlighted distinct changes in mitochondrial pathways throughout the course of differentiation, while phosphoproteomics revealed specific regulatory dynamics in GTPase signaling pathways and microtubule proteins. Additionally, phosphosite dynamics exhibited discordant trends compared to protein expression, particularly in processes related to axon functions and RNA transport. Furthermore, we mapped the kinase dynamic changes that are critical for neuronal development and maturation. We developed an interactive Web app (https://niacard.shinyapps.io/Phosphoproteome/) to visualize temporal landscape dynamics of protein and phosphosite expression. By establishing baselines of proteomic and phosphoproteomic profiles for neuronal differentiation, this dataset offers a valuable resource for future research into neuronal development and neurodegenerative diseases using this reference iPSC line. HighlightsO_LITemporal dynamics of proteome and phosphoproteome profiles in KOLF2.1J iPSC derived neurons. C_LIO_LIPhosphoproteomics highlights GTPase signaling and microtubule regulation in neuronal differentiation. C_LIO_LIKinome mapping reveals a shift in kinase activity patterns from early to late differentiation. C_LIO_LIShinyapp for visualizing the trajectory of protein and phosphosite expression during neuronal differentiation. C_LI

neuroscience↗

bioRxiv2025

Energy predicts global mountain endemic plant richness better than environmental heterogeneity

The drivers of biodiversity in mountain ecosystems have long been a central focus in ecologists. Increasing evidence suggests that energy is a key determinant of mountain species diversity; however, whether this pattern holds universally across different mountain ecosystems remains unclear, especially as there may be differences between different plant taxa. To address this knowledge gap, we selected mountain endemic plant genera from global biodiversity hotspots to explore the main drivers of diversity of different taxa in the mountains. Our results indicate that energy is the key driver of endemic plant richness in mountain regions worldwide, particularly for endemic tree and shrub taxa, while endemic herb richness is shaped by both energy and environmental heterogeneity. Regional studies have shown that energy availability drives total endemic plant groups in 70% of mountain regions. Specifically, energy is the dominant driver for 86% of endemic tree groups and 67% of endemic shrub groups, whereas endemic herb groups are the least influenced by energy, with only 50% of mountain regions showing energy as the primary driver. Our findings indicate that energy availability is the predominant factor shaping the diversity of endemic plant groups in mountain ecosystems worldwide. Therefore, mountain ecological conservation efforts should focus extensively on energy input aspects. HighlightsO_LIClimate energy is the main driver of the richness of montane endemic plant taxa, especially for tree and shrub, whereas herb richness is determined by a combination of energy and environmental heterogeneity. C_LIO_LIEnvironmental heterogeneity predominantly drives endemic taxa richness in the Cape of Good Hope, whereas both climatic energy and environmental heterogeneity jointly influence endemic taxa richness in the Andes and Japan. In all other mountain ranges, climatic energy is the primary determinant. C_LIO_LIEndemic tree taxa have the highest number of mountains dominated by climatic energy, followed by endemic shrub taxa, and endemic herb taxa are more affected by environmental heterogeneity. C_LI

ecology↗

bioRxiv2025

Cerebellin-2 positive (Cbln2+) Neurons in the Parafascicular Thalamic Nucleus Regulate Self-Grooming Behavior

Self-grooming represents a stereotyped repetitive behavior which is commonly observed in various neuropsychiatric disorders. Deep brain stimulation (DBS) targeting the centromedian / parafascicular complex (CM/PF) has been shown to alleviate obsessive-compulsive disorder/behavior (OCD/OCB) symptoms in human. However, little is known about the neural circuits of the PF that are involved in the regulation of self-grooming behavior in rodents. Here, we report that cerebellin-2 positive (Cbln2+) neurons in PF bidirectionally encode self-grooming. Chemogenetic activation of Cbln2+ PF neurons significantly reduces both physiological and pathological self-grooming, and chemogenetic inhibition of Cbln2+ PF neurons increases physiological self-grooming. Moreover, activating synaptic excitatory inputs to Cbln2+ PF neurons inhibits self-grooming, while synaptic inhibitory inputs enhance it. Cbln2+ PF neurons independently transmit neural signals to the dorsal and ventral striatum. Activation of PF-dorsal striatum and PF-ventral striatum pathways both inhibit self-grooming behavior. Most excitingly, we alleviate excessive grooming in OCD mice by the activation of PF neurons using non-invasive ultrasound stimulation. Together, these data reveal that Cbln2+ PF neurons are integral components of a brain network involved in self-grooming behavior and highly promising targets in the non-invasive therapy of OCD.

neuroscience↗

bioRxiv2025

A split ALFA tag-nanobody system for protein localization and proximity proteomics in mycobacteria

Tuberculosis remains a globally significant infection and new insights into the biology of Mycobacterium tuberculosis are badly needed. Discovery of protein localization and protein complex composition are powerful approaches to determine protein function, but have not been widely applied in mycobacteria, in part due to technical barriers. Here we develop a multi-functional system that utilizes the ALFA tag and functional protein fusions to an anti-ALFA nanobody (NBALFA) to target proteins in fast and slow growing mycobacteria. Insertion of the ALFA epitope tag on the target protein, coupled with conditional expression of the NBALFA fused to a fluorescent protein faithfully recapitulates cytosolic and membrane protein localization by fluorescent microscopy in living cells. Targeted NBALFA can relocalize an ALFA tagged protein to inclusion bodies or the cytoplasmic membrane, demonstrating enforced protein localization. Finally, conditional expression of the NBALFA fused to TurboID for proximity proteomics allowed identification of known partner proteins of the RNA polymerase complex and the PKS13 mycolic acid biosynthesis protein. We conclude that the split ALFA tag-nanobody system is a flexible platform for discovery protein biology in mycobacteria.

microbiology↗