Biology subjects

Xu, T.

Publications and source records attributed to Xu, T..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

DeepSeMS: a large language model reveals hidden biosynthetic potential of the global ocean microbiome

Microbial biosynthetic diversity holds immense potential for discovering natural products with therapeutic applications, yet a substantial quantity of natural products derived from uncultivated microorganisms remains uncharacterized. The intricate nature of biosynthetic enzymes poses a major challenge in accurately predicting the chemical structures of secondary metabolites solely based on genome sequences using current rule-based methods. Here, we present DeepSeMS, a large language model designed to predict the chemical structures of secondary metabolites from various microbial biosynthetic gene clusters. Built on the Transformer architecture, DeepSeMS innovatively identifies sequence features using functional domains of biosynthetic enzymes, and incorporates feature-aligned chemical structure enumeration for training data augmentation. External evaluation results show that DeepSeMS predicts more accurate chemical structures of secondary metabolites with a Tanimoto coefficient up to 0.6 compared with the ground truth, significantly outperforming antiSMASH and PRISM with coefficients of only 0.14 and 0.45 respectively. Moreover, DeepSeMS successfully predicted secondary metabolites for 96.60% of cryptic biosynthetic gene clusters, surpassing existing methods with success rates less than 50%. Leveraging DeepSeMS, we characterized over 65,000 novel secondary metabolites from the global ocean microbiome with previously undocumented structural types, ecological distribution, and biomedical applications especially antibiotics. A login-free and user-friendly web server for DeepSeMS (https://biochemai.cstspace.cn/deepsems/) has been launched, featuring an integrated global ocean microbial secondary metabolites repository to expedite the discovery of novel natural products. Collectively, this study underscores the great capacity of a large language model-driven method in revealing hidden biosynthetic potential of the global ocean microbiome.

synthetic biology↗

bioRxiv2025

Characterisation of CD4 Th subsets as well as dietary, exercise and lifestyle factors in an established Rheumatoid Arthritis cohort; pilot study.

BackgroundSex disparities in the incidence and severity of Rheumatoid Arthritis (RA) are well-documented, with females experiencing more aggressive disease and different responses to treatment. While underlying mechanisms remain elusive, immune factors and lifestyle components, such as diet and physical activity, could play a role in shaping disease outcomes. Since Th cells are key drivers of RA, this study characterised CD4 Th subset frequencies, including Th1, Th2, Th17 and Th1/17 cells, in a cohort of males and females with established RA. Considering the role of diet and lifestyle in RA development, we also evaluated participant diet and lifestyle patterns. MethodsAn observational cross-sectional cohort study profiling 39 individuals (19 RA and 20 age and sex matched controls) with no major co-morbidities was conducted. Percentages of Th1, Th2, Th17 and Th1/17 cells from peripheral blood were determined by flow cytometry as well as serum levels of RF and cytokines IL17, IFN-{gamma}, TNF-, GM-CSF, TGF-{beta}, IL-6, and CRP by ELISA. Dietary intake was assessed by Food Frequency Questionnaire (FFQ), the Dietary inflammatory Index (DII) calculated from nutrient intake. Physical activity levels were evaluated by Global Physical Activity Questionnaire (GPAQ). ResultsSex-specific differences of Th17, Th1 an Th2 cells were observed in RA groups. Males had lower levels of Th1 cells and higher levels of Th17 cells than control subjects, while females had lower levels of Th2 cells than controls. Female RA subjects had higher ratio of Th1:Th2 cells than controls, while male RA subjects had higher Th17:Th1 ratio than controls. Interestingly, circulating CD4 Th subset levels were predictive of RA in this cohort. No changes in cytokine levels were observed. The male RA group consumed 30% less carbohydrate (RA = 156g +/-57g, Control = 253g +/-59g; p=0.003), 37% less sugar (RA = 74.1g +/-29g, Control = 118g +/-33g; p=0.004) and 30% less dietary fibre (R = 33g +/-8g, Control = 48g +/-13 g; p=0.008) than the male control group. The female RA group had the lowest consumption of alcohol in comparison to female control group (RA = 0.31g, Control = 8.97g; p=0.047). Male subjects had a 4x higher DII than females (p=0.012). ConclusionsOur findings highlight potential sex-specific differences in CD4+ Th cell subsets in individuals with established RA, indicating that sex may influence immune cell composition in this disease. Furthermore, dietary components showed sex-specific consumption patterns, underscoring the potential role of tailored lifestyle interventions in modulating immune responses in RA. Evaluating immunological sex differences and dietary and lifestyle factors may be important for enhancing management strategies in RA.

immunology↗

bioRxiv2025

Shaping of developmental gradients through selection on multiple loci in Antirrhinum

Development depends on precise shaping of molecular gradients, but how natural selection acts to establish precision is unknown. Here we analyse genes that control differences in the gradient of yellow flower colour between two varieties of snapdragon (Antirrhinum). We show that these differences depend, in part, on cis regulatory variation in the pigment biosynthetic gene, FLAVIA (FLA). FLA interacts multiplicatively with three other loci, one of which is a trans-acting regulator of FLA, to further shape the yellow gradient. All the loci exhibit clines at a hybrid zone, with widths that correlate with phenotypic effect, showing how selection can hone gradient shape with remarkable precision by acting on cis and trans variation at multiple loci.

evolutionary biology↗

bioRxiv2025

ggalign: Bridging the Grammar of Graphics and Biological Multilayered Complexity

Composable visualization is essential in biomedical research, particularly when working with complex, multi-dimensional biological data. However, many existing tools focus on specific fields and lack the comprehensive features needed to capture the intricacies and interrelations of datasets. To address this, we introduce ggalign, an R package built on the grammar of graphics framework, providing an easy-to-use platform for creating composable visualizations of interconnected data. It offers a variety of layout options, including StackLayout, QuadLayout, and CircleLayout, tailored to different data types, and supports flexible multi-dimensional relationships, such as one-to-many, many-to-one, many-to-many, and crosswise connections. Additionally, ggalign enhances the clarity of visualizations through its annotation features. Overall, ggalign offers a powerful and flexible solution for visualizing complex data in biomedical research. O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/636847v1_ufig1.gif" ALT="Figure 1"> View larger version (92K): org.highwire.dtl.DTLVardef@d4bb97org.highwire.dtl.DTLVardef@67c236org.highwire.dtl.DTLVardef@1ff9cc6org.highwire.dtl.DTLVardef@8dc6a9_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Developmental Variations in Recurrent Spatiotemporal Brain Propagations from Childhood to Adulthood

The brain undergoes profound structural and functional transformations from childhood to adolescence. Convergent evidence suggests that neurodevelopment proceeds in a hierarchical manner, characterized by heterogeneous maturation patterns across brain regions and networks. However, the maturation of the intrinsic spatiotemporal propagations of brain activity remains largely unexplored. This study aims to bridge this gap by delineating spatiotemporal propagations from childhood to early adulthood. By leveraging a recently developed approach that captures time-lag dynamic propagations, we characterized intrinsic dynamic propagations along three axes: sensory-association (S-A), task-positive to default networks (TP-D), and somatomotor-visual (SM-V) networks, which progress towards adult-like brain dynamics from childhood to early adulthood. Importantly, we demonstrated that as participants mature, there is a prolonged occurrence of the S-A and TP-D propagation states, indicating that they spend more time in these states. Conversely, the prevalence of SM-V propagation states declines during development. Notably, top-down propagations along the S-A axis exhibited an age-dependent increase in occurrence, serving as a superior predictor of cognitive scores compared to bottom-up S-A propagation. These findings were replicated across two independent cohorts (N = 677 in total), emphasizing the robustness and generalizability of these findings. Our results provide new insights into the emergence of adult-like functional dynamics during youth and their role in supporting cognition.

neuroscience↗

bioRxiv2025

Inhibition of cathepsin B blocks amyloidogenesis in the mouse models of neurological lysosomal diseases mucopolysaccharidosis type IIIC and sialidosis

Neuronal accumulation of amyloid aggregates is a hallmark of brain pathology in neurological lysosomal storage diseases (LSDs) including mucopolysaccharidoses (MPS), however, the molecular mechanism underlaying this pathology has not been understood. We demonstrate that elevated lysosomal cathepsin B (CTSB) levels and CTSB leakage to the cytoplasm triggers amyloidogenesis in two neurological LSDs. CTSB levels were elevated 3-5-fold in the cortices of mouse models of MPS IIIC (Hgsnat-Geo and HgsnatP304L) and sialidosis (Neu1{Delta}Ex3), as well as in cortical samples of MPS I, IIIA, IIIC and IIID patients. CTSB was found in the cytoplasm of pyramidal layer IV-V cortical neurons containing Thioflavin-S-positive, {beta}-amyloid-positive aggregates consistent with pro-senile phenotype. In contrast, CTSB-deficient MPS IIIC (HgsnatP304L/Ctsb-/-) mice as well as HgsnatP304L and Neu1{Delta}Ex3 mice chronically treated with irreversible brain-penetrable CTSB inhibitor, E64, showed a drastic reduction of neuronal Thioflavin-S-positive/APP-positive deposits. Neurons of HgsnatP304L/Ctsb-/- mice and E64-treated HgsnatP304L mice also showed reduced levels of P62/LC3-positive puncta, GM2 ganglioside and misfolded subunit C of mitochondrial ATP synthase (SCMAS) consistent with restored autophagy. E64 treatment also rescued hyperactivity and reduced anxiety in HgsnatP304L mice implying that CTSB may become a novel pharmacological target for MPS III and similar LSDs.

genetics↗

bioRxiv2025

A self-supervised deep learning pipeline for segmentation in two-photon fluorescence microscopy

Two-photon fluorescence microscopy (TPFM) allows in situ investigation of the structure and function of the brain at a cellular level, but the conventional image analyses of TPFM data are labour-intensive. Automated deep learning (DL)-based image processing pipelines used to analyze TPFM data require large labeled training datasets. Here, we developed a self supervised learning (SSL) pipeline to test whether unlabeled data can be used to boost the accuracy and generalizability of DL models for image segmentation in TPFM. We specifically developed four pretext tasks, including shuffling, rotation, axis rotation, and reconstruction, to train models without supervision using the UNet architecture. We validated our pipeline on two tasks (neuronal soma and vasculature segmentation), using large 3D microscopy datasets. We introduced a novel density-based metric, which provided more sensitive evaluation to downstream analysis tasks. We further determined the amount of labeled data required to reach performance on par with fully supervised learning (FSL) models. SSL-based models that were fine-tuned with only 50% of data were on par or superior (e.g., Dice increase of 3% for neuron segmentation and Dice score of 0.88 {+/-} 0.09 for vessel segmentation) to FSL models. We demonstrated that segmentation maps generated by SSL models pretrained on the reconstruction and rotation tasks can be better translated to downstream tasks than can other SSL tasks. Finally, we benchmarked all models on a publicly available out-of-distribution dataset, demonstrating that SSL models outperform FSL when trained with clean data, and are more robust than FSL models when trained with noisy data.

neuroscience↗

bioRxiv2025

Extracellular stiffness regulates site-specific lung development

Extracellular matrix (ECM) stiffness plays a crucial role in regulating cell fate and maturation, but its influence on lung development is limited known. Here we utilized stiffness-tunable gelatin methacryloyl (GelMA) hydrogels to investigate how ECM stiffness influences site-specific lung development in a stem cell-derived lung organoid model. We found increased stiffness promoted NKX2-1+ lung progenitor cells (LPCs) generation. In airway organoids (hAWOs), stiff hydrogels directed proximal airway differentiation enriched with goblet, ciliated, and basal cells; whereas the decreased stiffness favored emergence of secretory cells in the proximal-distal transition zone and distal airway. In alveolar organoids (hALOs), increased stiffness enhanced AT2 and AT1 cells transition. Moreover, infection assays with Omicron BA.1.1 and Delta variants recapitulated the proximal-to-distal tropism of SARS-CoV-2 in the lung. Transcriptomic sequencing revealed ECM stiffness regulates lung development via Hippo, TGF-{beta}, HIF and Wnt pathways. These findings advance mechanism understanding of ECM stiffness on lung development and provide a novel mechanical regulation for generating site-specific lung organoids.

cell biology↗

bioRxiv2024

Dissociable neurofunctional and molecular characterizations of reward and punishment sensitivity

While the hyper-and hypo-reward or punishment sensitivities (RS, PS) have received considerable attention as prominent transdiagnostic features of psychopathology, the lack of an overarching neurobiological characterization currently limits their early identifications and neuromodulations. Here we combined microarray data from the Allen Human Brain Atlas with a multimodal fMRI approach to uncover the neurobiological signatures of RS and PS in a discovery-replication design (N=655 participants). Both RS and PS were mapped separately in the brain, with the intrinsic functional connectome in the fronto-striatal network encoding reward responsiveness, while the fronto-insular system was particularly engaged in punishment sensitivity. This dissociable functional connectome patterns related to RS and PS were also specific in differentiating decisions driven by social or monetary reward and punishment motivations. Further imaging transcriptomic analyses revealed that functional connectome variations for RS and PS were associated with topography of specific gene sets enriched in ontological pathways, including synaptic transmission, dopaminergic metabolism, immune response and stress adaptation. On the neurotransmitter level, the serotonin neuromodulator was identified as a pivotal hub regulating the intrinsic functional connectome patterns of RS and PS, with this process critically dependent on its interactions with dopaminergic, opioid and GABAergic systems. Overall, these findings indicate dissociable neural connectome mapping of RS and PS and highlight their linkage with transcriptomic profiles, which may offer valuable insights into the treatment evaluation for symptomatology relevant to reward/punishment processing deficits.

neuroscience↗

bioRxiv2024

Development of a novel peripherally acting alpha2A-adrenergic receptor antagonist for anti-diabetic

Yohimbine, a potent alpha2A-adrenergic receptor (2AAR) antagonist, was found therapeutic potential for type 2 diabetes through improving insulin release. However, the adverse side effects mediated by its actions in the brain hampered its use. Here, based on molecular docking analysis and structural modification, we have developed a novel peripherally acting yohimbine derivative (CDS479-2). CryoEM data found that yohimbine and CDS479-2 have similar interactions with the structure of 2AAR. Importantly, CDS479-2 shows similar 2AAR antagonist activity as yohimbine, but with very limited access to the brain, and thus avoiding the unwanted central effects such as hypertension and anxiety. Acute administration of CDS479-2 by injection or gavage lowered blood glucose levels and improved glucose tolerance in the high-fat diet-induced obesity (DIO) mice, an animal model for human type 2 diabetes. Remarkably, DIO mice received 2 weeks of daily administration of CDS479-2, but not yohimbine, exhibited sustained normoglycaemia, and increased density of the insulin-producing beta cells, in which important proliferation genes were found upregulated. Moreover, the overall protein expression levels of their pancreas were more similar to that of the healthy chow-fed mice. Thus, CDS479-2 may indicate a new direction for type 2 diabetes treatment. Importantly, the strategy we employed in this study will inspire the optimization for drugs that with both peripheral and central targets. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=166 HEIGHT=200 SRC="FIGDIR/small/628818v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@1d3d7corg.highwire.dtl.DTLVardef@1afbad3org.highwire.dtl.DTLVardef@12a1aborg.highwire.dtl.DTLVardef@1341a02_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2024

BioMedGraphica: An All-in-One Platform for Biomedical Prior Knowledge and Omic Signaling Graph Generation

Multi-omic data analysis is essential for scientific discovery in precision medicine. However, translating statistical results of omic data analysis into novel scientific hypothesis remains a significant challenge. Human experts must manually review analysis results and generate new hypothesis based on extensive and inter-connected biomedical prior knowledge, which is subjective and not scalable. While large language models (LLMs) can accelerate the discovery, their reasoning improves when grounded in structured, auditable and comprehensive biomedical prior knowledge. Biomedical knowledge, however, is scattered across heterogeneous databases that use diverse and inconsistent nomenclature systems, making it difficult to integrate resources into a unified format for scalable analysis. This fragmentation limits the ability of AI systems to fully leverage biomedical data for scientific discovery. To address these challenges, we developed BioMedGraphica, an all-in-one platform that harmonizes fragmented biomedical resources by integrating 11 entity types and 30 relation types from 43 databases into a unified knowledge graph containing 2,306,921 entities and 27,232,091 relations. In addition, to the best of our knowledge, this is the first work to propose a novel Textual-Numeric Graph (TNG) data-structure for multi-omics data analysis. In TNG, textual information captures prior biological knowledge (e.g., transcription start sites, functions, mechanisms), while numeric values represent quantitative biomedical features, and the integrated relations can help uncover mechanisms. By bridging prior knowledge with user-specific data, TNG is a novel and ideal data-structure for the development of graph foundation models, with the potential to improve prediction performance and interpretability, while also augmenting LLMs by supplying graph-structured mechanistic context to strengthen reasoning. The details for BioMedGraphica code can be accessed by github link: https://github.com/FuhaiLiAiLab/BioMedGraphica and BioMedGraphica knowledge graph data can be downloaded from huggingface dataset: https://huggingface.co/datasets/FuhaiLiAiLab/BioMedGraphica

bioinformatics↗

bioRxiv2024

Optimizing femtosecond laser fabricating strategy of Nitinol hypotube for vascular interventional surgery

Guidewires and catheters are essential in minimally invasive procedures, particularly in accessing targets within the vascular system for neuron surgery. Femtosecond lasers can precisely cut nickel-titanium micro tubes, known as Nitinol hypotubes, serving as the heads of micro guidewires while protecting their core tips. The quality and geometry of these hypotubes depend on the focus of the laser cutting system. We evaluated the cutting efficiency and quality of Nitinol hypotubes using objective lenses with three numerical apertures (NA). Quantitative analysis indicated that higher NA objectives yield better surface quality, resulting in lower debris. Additionally, cutting with high NA objectives produced significantly lower arithmetic mean surface roughness and enhanced mechanical properties. Using a two-temperature model, we simulated the interaction between femtosecond lasers and Nitinol, showing that higher NA objectives increase electron temperatures, thus improving material removal efficiency. This study also tested the optimized Nitinol hypotube prformance in simulations of invasive neuron surgery.

neuroscience↗

bioRxiv2024

Multi-purpose controllable protein generation via prompted language models

Deep learning is increasingly powerful for designing proteins that meet structural and functional requirements. However, most existing methods follow a conventional pipeline: first defining a backbone structure and then generating sequences consistent with it. This approach, which encodes all design goals indirectly through structures, restricts flexibility and struggles to address multiple, complex design objectives simultaneously. We present PROPEND, a multi-purpose protein sequence design method based on the "pre-train and prompt" framework. We show PROPENDs broad utility and accuracy both in silico and in vitro by directly controlling multiple properties through the prompt of backbones, blueprints, functional tags, and their combinations. For the five sequences tested with in vitro experiments, PROPEND achieved a maximum functional recovery of 105.2%, significantly outperforming the classical design pipelines 50.8%.

synthetic biology↗

bioRxiv2024

Restoration of PKM1 improves functional maturation of human stem-cell derived-β cell by regulating PEP metabolism

Human stem cell-derived {beta} (SC-{beta}) cells still exhibit limited glucose response required for insulin secretion due to glycolytic bottlenecks, yet how these metabolic abnormalities impact glucose response and functional maturation of SC-{beta} cells remains unclear. In this study, we identified a metabolic checkpoint located at PEP accumulation that impeded the functional maturation, which was rescued by restoration of pyruvate kinase 1 (PKM1). Glucose-tracing metabolomics in human stem cell-derived islets revealed abnormal glycolytic PEP accumulation at resting condition, resulting in impaired calcium response and insulin secretion upon high glucose or glycolytic metabolite stimulation. Mechanistically, elevated PEP significantly raised intracellular basal calcium levels, leading to downregulated expression of genes involved in TCA cycle elucidated by single cell transcriptomics. Furthermore, the activity of pyruvate kinase, which metabolizes PEP, was notably reduced due to low PKM1 expression. By overexpressing PKM1, the impairment of TCA-related genes caused by PEP accumulation was reversed via modulating PEP metabolism, resulting in enhanced calcium responses and insulin secretion upon high glucose stimulation. Together, we discovered a novel role of PKM1-regulated PEP metabolism in mediating the functional maturation of human SC-{beta} cells. This study highlights the importance of metabolic reprogramming in human SC-{beta} cell maturation, advancing cell therapy approaches for diabetes treatment.

cell biology↗

bioRxiv2024

An adaptive autoregressive diffusion approach to design active humanized antibody and nanobody

Humanization is a critical process for designing efficiently specific antibodies and nanobodies prior to clinical trials. Developing widely recognized deep learning techniques or frameworks for humanizing conventional antibodies and nanobodies presents a valuable yet challenging task. Inspired by the effectiveness of diffusion models across various applications, we introduce HuDiff, an adaptive diffusion approach for humanizing antibodies and nanobodies from scratch, referred to as HuDiff-Ab and HuDiff-Nb, respectively. This approach begins the humanization process exclusively with complementarity-determining region (CDR) sequences, eliminating the need for humanized templates. On public benchmark datasets, the results of HuDiff-Abs humanized antibodies are more similar to experimentally humanized antibodies than to those of the Sapiens humanization model. Besides, humanized nanobodies produced by HuDiff-Nb exhibit a higher humanness score and greater nativeness than those generated by the Lammanade pipeline for humanization nanobody. We apply HuDiff to humanize a mouse antibody and an alpaca nanobody, both targeting the SARS-CoV-2 RBD, and validate the binding affinity of humanized sequences through Bio-Layer Interferometry (BLI) experiments. The results show the binding affinity of the best humanized antibody is nearly equal to that of the parental mouse antibody (0.15 nM vs. 0.12 nM). Remarkably, the top-performing humanized nanobody exhibits a significantly enhanced binding affinity compared to the parental alpaca nanobody (2.52 nM vs. 5.47 nM), representing a 54% increase. These findings indicate that our approach HuDiff is highly effective in enhancing the humanness of antibodies and nanobodies while maintaining or potentially improving the binding affinity of the designed humanized sequences. The code and checkpoints of HuDiff are available at https://github.com/TencentAI4S/HuDiff.

bioinformatics↗

bioRxiv2024

Does Unfairness Evoke Anger or Disgust? A Quantitative Neurofunctional Dissection Based on 25 Years of Neuroimaging

Over the last decades, the traditional Homo economicus model has been increasingly challenged by convergent evidence underscoring the impact of emotions on decision-making. A classic example is the perception of unfairness operationalized in the Ultimatum Game where humans readily sacrifice personal gains to punish those who violate fairness norms. While the emotional mechanism underlying costly punishments has been widely acknowledged, the distinct contributions of moral emotions (anger or disgust) remain debated, partly due to methodological limitations of the conventional experiments. Here, we capitalize on a quantitative neurofunctional dissection approach by combining recent developments in neuroimaging meta-analyses, behavioral-level, network-level, and neurochemical-level decoding and data from 3,266 participants from functional neuroimaging studies to determine the common and distinct neural representations between unfairness and the two moral emotions. Experience of unfairness engaged a widespread bilateral network encompassing insular, cingulate, and frontal regions, with dorsal striatal regions mediating the decision to reject unfair offers. Disgust engaged a defensive-avoidance circuit encompassing amygdalar, occipital, and frontal regions, while anger engaged non-overlapping systems including mid-cingulate, thalamic, and frontal regions. Unfairness and anger or disgust respectively commonly engaged the anterior and mid-insula, while the latter additionally showed common recruitment of ventrolateral prefrontal and orbitofrontal cortices. Multimodal network, behavioral, and serotonergic decoding provided a more granular and convincing dissection of these results. Findings indicate a shared neuroaffective basis underlying the impact of emotions on unfairness-induced punishment behavior and suggest a common brain circuit has been evolutionarily shaped to protect individuals from personal harm and enforce societal norms.

neuroscience↗

bioRxiv2024

State and trait serotonin variations interact to shape the intrinsic connectivity and gradient architecture of the brain: a combined TPH2 genetics and tryptophan depletion study

BackgroundSerotonin (5-HT) critically regulates cognitive and emotional functions, and both stable and transient variations in 5-HT signaling have been associated with emotional dysregulations. However, findings regarding the neurofunctional effects of transient 5-HT variations have been highly inconsistent. Therefore, we examined whether individual variations in a central 5-HT-regulating genetic polymorphism (tryptophan hydroxylase 2, TPH2) represent a vulnerability or resilience factor for the effects of acute tryptophan depletion (ATD) on functional brain architecture. MethodThe current study utilized a pharmacogenetic within-subject randomized placebo-controlled resting-state fMRI design with n=53 healthy male participants in combination with spontaneous intrinsic neural activity, functional connectivity, and connectome gradient analyses to compare the neurofunctional effects of ATD-induced transient reduction in central 5-HT signaling between TPH2 genotypes (a priori genotyping for rs4570625, GG n = 25 vs. TT n = 23). ResultsATD induced significant increases in spontaneous neural activity in hippocampal CA1 irrespective of genotype and enhanced communication of this region with the bilateral amygdala and the vmPFC specifically in GG carriers. ATD sharpened the intrinsic connectome gradient architecture in several large-scale networks, including the salience, frontoparietal, and default mode network. ConclusionsOur results identify a potential genetic marker for an increased vulnerability to the neural effects of transient variations in 5-HT signaling on the functional architecture of an anxiety- and stress-related brain circuit. Connectome gradient results underscore the regulatory role of 5-HT on the intricate organization of large-scale networks involved in emotional reactivity and regulation.

neuroscience↗

bioRxiv2024

Bergeyella cardium variant induces unique cytoplasmic vacuolization cell death

Bacterial pathogens have evolved multiple mechanisms to modulate host cell death, evade host immunity, and establish persistent infection. Here, we show that an emerging pathogen Bergeyella cardium variant (BCV) survives serum killing, inducing unique cytoplasmic vacuolization cell death in the majority of cells and apoptosis in a small number of bystanders. The cytoplasmic vacuolization cell death triggered by BCV is characterized by fused lysosome-associated termination and is inhibited by the sodium channel inhibitor amiloride. Endosomal solute carrier family 9 member A9 (SLC9A9) was identified as a critical regulator in the process of BCV-triggered cytoplasmic vacuolization cell death. Moreover, outer membrane vesicles (OMVs) or transfection of barrel-like membrane proteins lipocalin, {beta}-barrel, and PorV dramatically induced cytoplasmic vacuolization. BCV hijacked SLC9A9 by maintaining its high expression, increasing cytoplasmic vacuolization, and enhancing pathogenicity. These findings contribute to the development of novel approaches to modulate cytoplasmic vacuolization cell death and treat infectious diseases. HighlightsO_LIBCV triggers unique cytoplasmic vacuolization cell death. C_LIO_LISLC9A9 is essential for BCV-induced cytoplasmic vacuolization cell death. C_LIO_LIOMVs and the transfection of barrel-like proteins derived from BCV induce cytoplasmic vacuolization cell death. C_LIO_LIBCV increases pathogenicity via cytoplasmic vacuolization cell death. C_LI

cell biology↗