Biology subjects

Liu, Y.

Publications and source records attributed to Liu, Y..

At least 973 records · Page 54Linked to original sources

bioRxiv2024

Magnetically induced magnetosome chain (MAGiC):A biogenic magnetic-particle-imaging tracer with high performance and navigability

Magnetic particle imaging (MPI) enables real-time, sensitive and quantitative visualization of magnetic tracers spatial distribution, augmenting the capability of in vivo imaging technologies. Previous tracer studies in MPI have primarily focused on superparamagnetic nanoparticles; however, their non-ideal sigmoidal magnetization response limits the spatial resolution. Here we demonstrate the utilization of magnetically induced magnetosome chain (MAGiC) as a novel superferromagnetic MPI tracer, exhibiting a 25-fold improvement in resolution and a 91-fold enhancement in signal intensity compared to the commercial tracer VivoTrax+. The spatial resolution of MPI was pushed to an unprecedented 80 m under a 4 T/m gradient field. Additionally, MAGiC can be precisely controlled using magnetic fields, enabling it to function as a MPI trackable microrobot. We provided a theoretical model elucidating MAGiCs unique properties, and validated its imaging and actuation performance through phantom studies and in vivo experiments. As a high-performance MPI tracer and magnetic microrobot with exceptional capabilities, MAGiC holds tremendous potential for diverse applications including cell tracking, targeted drug delivery as well as therapeutic interventions.

bioengineering↗

bioRxiv2024

Interaction of osteoprotegerin with fibulin-1 is essential for extracellular matrix deposition in fibrotic lung tissue

Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal lung disease with an unclear cause and no cure. Osteoprotegerin (OPG), a well-known regulator of bone extracellular matrix (ECM), is increased in pulmonary fibrosis and this is associated with lower lung function and IPF progression. Fibulin-1, a key ECM protein, is increased in lung fibroblasts and lung tissues from patients with IPF and high levels are predictive of a poor prognosis for these patients. We found a positive correlation between levels of OPG and fibulin-1 in serum from patients with IPF, but it is unknown if these proteins interact. This study aimed at investigating interactions between OPG and fibulin-1 in lung fibrosis, hypothesizing that OPG may form a complex with fibulin-1 thereby possibly influencing lung fibrosis. We investigated intracellular interactions between OPG and fibulin-1 in human lung fibroblasts, showing neither OPG nor fibulin-1 expression were dependent on each other. However, OPG protein deposition was significantly decreased in lung tissues of fibulin-1 knockout mice (fibulin-1-/-)compared to controls suggesting extracellular interactions. Subsequently, we detected colocalization of both proteins in both IPF and control lung tissues using immunofluorescence, with both of them also colocalizing with latent TGF{beta} binding protein 1 (LTBP1). Proximity ligation analyses confirmed close proximity of OPG to fibulin-1 and fibulin-1 to LTBP1, particularly in the interstitial regions of both control and IPF lung tissue, but not OPG and LTBP1. In conclusion, we found that OPG, fibulin-1 and LTBP1 seem to form a complex, with fibulin-1 playing a bridging role between OPG and LTBP1, in the extracellular environment. This complex may play a regulatory role in deposition of extracellular matrix in lung tissue.

pathology↗

bioRxiv2024

HCN1 channels in GABAergic amygdalar neurons underpin male-biased aggressive behaviors

Aggression behaviors typically vary between sexes, but the molecular mechanisms driving these disparities in neural coding are unclear. We found that aggression selectively activates GABAergic neurons in the posterior substantia innominata (pSI), an extend amygdala region critical for aggressive behaviors in both sexes of mice, with males exhibiting higher neuronal activity during the attack. Utilizing single-nucleus RNA sequencing, we characterized the diverse molecular landscape of pSI neurons, revealing significant differences in ion channels and hormone regulator genes that may underpin sex-specific aggression. Male GABAergic pSI neurons exhibited remarkable hyperexcitability due to increased Ih currents. Strikingly, modulating HCN1 expression not only adjusted this hyperexcitability but also influenced sexual dimorphism in aggression: silencing HCN1 in the GABAergic pSI neurons reduced male aggression, while its overexpression markedly heightened aggression in females. Furthermore, testosterone was shown to intensify aggression by upregulating HCN1 and remodeling pSI circuits. These findings provide detailed sex-specific molecular mechanisms underlying social behaviors.

neuroscience↗

bioRxiv2024

Metagenomic mining reveals novel viral histones in dsDNA viruses

The compaction of genomic DNA into nucleosomes with the help of histones had long been considered as a fundamental feature exclusive to eukaryotic cells. However, it was recently shown that archaea and bacteria also encode histones. A complex picture has emerged with more recent discoveries of eukaryotic-like histones within one phylum of double-stranded DNA (dsDNA) viruses. Nevertheless, the extent to which other dsDNA viruses encode histones remains largely unexplored. Here we conducted a metagenomic survey of viral histones that were further clustered based on sequence and predicted structural similarities. We identified over 1,500 viral histones and histone-fold proteins, including previously undescribed proteins found in the viral class Caudoviricetes. Structural predictions and in vitro assays demonstrated that histone triplets (where three histone folds are fused) and singlets co-occurring in the same viral genome are capable of forming nucleosome-like particles. Beyond nucleosomal histone functions, our analysis revealed six types of structurally and functionally diverse viral histone-fold proteins, some of which do not have known structural or functional homologs. Altogether, our findings reveal a previously unrecognized diversity of viral histones in dsDNA viruses, expanding the known repertoire, structural diversity, and functional versatility of viral histones beyond nucleocytoplasmic large DNA viruses. HighlightsO_LIHistone triplets and singlets co-occurring in the same dsDNA viral genomes assemble into nucleosome-like particles C_LIO_LISix novel types of structurally and functionally distinct viral histone-fold proteins are identified C_LIO_LIThe presence of viral histones is significantly positively associated with proteins containing SNF2 chromatin remodeling domain found in viral genomes C_LI

microbiology↗

bioRxiv2024

Automated Cell Type Annotation with Reference Cluster Mapping

Single-cell RNA sequencing has transformed the field of cellular biology by providing unprecedented insights into cellular heterogeneity. However, characterizing scRNA-seq datasets remains a significant challenge. We introduce RefCM, a novel computational method that combines optimal transport and integer programming to enhance the annotation of scRNA clusters using established reference datasets. Our method produces highly accurate cross-technology, cross-tissue, and cross-species mappings while remaining tractable at atlas scale, outperforming existing methods across all these tasks. By providing precise annotations, RefCM can enable the discovery of new cell types, states, and relationships in single-cell transcriptomic data.

bioinformatics↗

bioRxiv2024

Systems biology-enabled targeting of NF-κB and BCL2 overcomes microenvironment-mediated BH3-mimetic resistance in DLBCL.

In Diffuse Large B-cell Lymphoma (DLBCL), elevated anti-apoptotic BCL2-family proteins (e.g., MCL1, BCL2, BCLXL) and NF-{kappa}B subunits (RelA, RelB, cRel) confer poor prognosis. Heterogeneous expression, regulatory complexity, and redundancy offsetting the inhibition of individual proteins, complicate the assignment of targeted therapy. We combined flow cytometry fingerprinting, immunofluorescence imaging, and computational modeling to identify therapeutic vulnerabilities in DLBCL. The combined workflow predicted selective responses to BCL2 inhibition (venetoclax) and non-canonical NF-{kappa}B inhibition (Amgen16). Within the U2932 cell line we identified distinct resistance mechanisms to BCL2 inhibition in cellular sub-populations recapitulating intratumoral heterogeneity. Co-cultures with CD40L-expressing stromal cells, mimicking the tumor microenvironment (TME), induced resistance to BCL2 and BCLXL targeting BH3-mimetics via cell-type specific upregulation of BCLXL or MCL1. Computational models, validated experimentally, showed that basal NF-{kappa}B activation determined whether CD40 activation drove BH3-mimetic resistance through upregulation of RelB and BCLXL, or cRel and MCL1. High basal NF-{kappa}B activity could be overcome by inhibiting BTK to resensitize cells to BH3-mimetics in CD40L co-culture. Importantly, non-canonical NF-{kappa}B inhibition overcame heterogeneous compensatory BCL2 upregulation, restoring sensitivity to both BCL2- and BCLXL-targeting BH3-mimetics. Combined molecular fingerprinting and computational modelling provides a strategy for the precision use of BH3-mimetics and NF-{kappa}B inhibitors in DLBCL.

cancer biology↗

bioRxiv2024

Deep-learning-enabled generative prevalent mutation prediction through host-to-herd in silico virus evolution

Predicting the mutation prevalence trends of emerging viruses in the real world is an efficient means to update vaccines or drugs in advance. It is crucial to develop a computational method for the prediction of real-world prevalent SARS-CoV-2 mutations considering the impact of multiple selective pressures within and between hosts. Here, a deep-learning generative framework for real-world prevalent SARS-CoV-2 mutation prediction, named ViralForesight, is developed on top of protein language models and in silico virus evolution. Through the paradigm of host-to-herd in silico virus evolution, ViralForesight reproduced previous real-world prevalent SARS-CoV-2 mutations for multiple lineages with superior performance. More importantly, ViralForesight correctly predicted the future prevalent mutations that dominate the COVID-19 pandemic in the real world more than half a year in advance with in vitro experimental validation. Overall, ViralForesight demonstrates a proactive approach to the prevention of emerging viral infections, accelerating the process of discovering future prevalent mutations with the power of generative deep learning.

evolutionary biology↗

bioRxiv2024

PlantRing: A high-throughput wearable sensor system for decoding plant growth, water relations and innovating irrigation

The combination of flexible electronics and plant science has generated various plant-wearable sensors, yet challenges persist in their applications in real-world agriculture, particularly in high-throughput settings. Overcoming the trade-off between sensing sensitivity and range, adapting them to a wide range of crop types, and bridging the gap between sensor measurements and biological understandings remain the primary obstacles. Here we introduce PlantRing, an innovative, nano-flexible sensing system designed to address the aforementioned challenges. PlantRing employs bio-sourced carbonized silk georgette as the strain sensing material, offering exceptional resolution (tensile deformation: < 100 m), stretchability (tensile strain up to 100 %), and remarkable durability (season long), exceeding existing plant strain sensors. PlantRing effectively monitors plant growth and water status, by measuring organ circumference dynamics, performing reliably under harsh conditions and being adaptable to a wide range of plants. Applying PlantRing to study fruit cracking in tomato and watermelon reveals novel hydraulic mechanism, characterized by genotype-specific excess sap flow within the plant to fruiting branches. Its high-throughput application enabled large-scale quantification of stomatal sensitivity to soil drought, a traditionally difficult-to-phenotype trait, facilitating drought tolerant germplasm selection. Combing PlantRing with soybean mutant led to the discovery of a potential novel function of the GmLNK2 circadian clock gene in stomatal regulation. More practically, integrating PlantRing into feedback irrigation achieves simultaneous water conservation and quality improvement, signifying a paradigm shift from experience- or environment-based to plant-based feedback control. Collectively, PlantRing represents a groundbreaking tool ready to revolutionize botanical studies, agriculture, and forestry.

plant biology↗

bioRxiv2024

Successful establishment of an exogenous gene expression system in Chlamydomnas chloroplast based on viral replication elements

Currently, transformation in unicellular green alga (Chlamydomonas reinhardtii) chloroplast is hindered by a low yield of target products, possibly due to the heterogeneity of the chloroplast genome. In this study, an expression platform was established in C. reinhardtii by leveraging replicative elements from beet curly top geminivirus, which led to a high level of heterologous gene expression, as previously reported in Nicotiana tabacum. Platform performance was verified by the successful expression of a linearized mvenus cassette, achieving a higher expression level than that obtained using the homologous-recombination-based approach. This study provides a new strategy in microalgae synthetic biology and opens new avenue for accumulating valuable bioproducts at high concentrations.

synthetic biology↗

bioRxiv2024

Synthetic ratio computation for programming population composition and multicellular morphology

Recent advancements in genetic engineering have provided diverse tools for artificially synthesizing population diversity in both prokaryotic and eukaryotic systems. However, achieving precise control over the ratios of multiple cell types within a population derived from a single founder remains a significant challenge. In this study, we introduce a suite of recombinase-mediated genetic devices designed to achieve accurate population ratio control, enabling the distribution of distinct functionalities across multiple cell types. We systematically evaluated key parameters influencing recombination efficiency and developed data-driven models to reliably predict binary differentiation outcomes. Using these devices, we implemented parallel and series circuit topologies to create user-defined, complex cell fate branching programs. These branching devices facilitated the autonomous differentiation of precision fermentation consortia from a single founder strain, optimizing cell-type ratios for applications such as pigmentation and cellulose degradation. Beyond biomanufacturing, we engineered multicellular aggregates with genetically encoded morphologies by coordinating self-organization through cell adhesion molecules (CAMs). Our work provides a comprehensive characterization of recombinase-based cell fate branching mechanisms and introduces a novel approach for the bottom-up, high-resolution construction of synthetic consortia and multicellular assemblies.

synthetic biology↗

bioRxiv2024

Task-induced internal bodily rather than brain states regulate human self-perception

A fundamental ability for us is to identify and distinguish with others, known as the self, whose neural substrate is hard to identify by external self-related stimuli because of possible interference from internal self-related states of both body and brain. Using the same stimuli, we ruled out this dilemma by manipulating human subjects performing own- and celebrity-face discrimination tasks to induce self-related and non-self-related states, respectively. Results showed that stimulus-driven sensory sensory differences among own-, celebrity-, and stranger-faces were independent of task-induced internal states, whereas their perceptual differences were strongly modulated by these states. Intriguingly, we further found that subjects bodily (indexed by heartbeat-evoked potentials) rather than brain (indexed by pre-stimulus -powers) states not only predicated their self-perception but also moderated the relationship between external stimuli and self-perception. Our results reveal for the first time an adaptive self-perception, shaped by not only external stimuli but also internal states, especially the interoception.

neuroscience↗

bioRxiv2024

Variable phylosymbiosis and cophylogeny patterns in wild fish gut microbiota in a large subtropical river

The persistence and specificity of fish host-microbial interaction during evolution is an important part of exploring the host-microbial symbiosis mechanism. However, it remains unclear how the environmental and host factors shape fish host-microbe symbiotic relationship in subtropical rivers with complex natural environments. Freshwater fish are important consumers in rivers and lakes and considered keystone species in maintaining the stability of food webs there. In this study, patterns and mechanisms shaping gut microbiota community in 42 fish species from the Pearl River, in the subtropical zone of China were investigated. The results showed that fish host specificity is key driver of gut microbiota evolution and diversification. Different taxonomic levels of host showed different degrees of contribution in gut microbiota variation. Geographical location and habitat type were the next most important factors in shaping gut microbiota across the 42 fishes, followed by diet and gut trait. Our results emphasized the contribution of stochastic processes (drift and homogenizing dispersal) in the gut microbial community assembly of freshwater fishes in the middle and lower reach of the Pearl River. Phylosymbiosis is evident at both global and local levels, which are jointly shaped by complex factors including ecological or host physiological filtration and evolutionary process. The core microbiota showed co-evolutionary relationships of varying degrees with different taxonomic groups. We speculate that host genetic isolation or habitat variation facilitate the heterogeneous selection (deterministic process), which occurs and results in different host-core bacterium specificity.

evolutionary biology↗

bioRxiv2024

Machine learning application to predict binding affinity between peptide containing non-canonical amino acids and HLA0201

Class 1 major histocompatibility complexes (MHC-I), encoded by the highly polymorphic HLA-A, HLA-B, and HLA-C genes in humans, are expressed on all nucleated cells. Both self and foreign proteins are processed to peptides of 8 to 10 amino acids, loaded into MCH-1 within the endoplasmic reticulum and then presented on the cell surface. Foreign peptides presented in this fashion activate CD8+ T cells and their immunogenicity correlates with their affinity for the MHC-1 binding groove. Thus, predicting antigen binding affinity for MHC-I is a valuable tool for identifying potentially immunogenic antigens. While quite a few predictors for MHC-I binding exist, there are no currently available tools that can predict antigen/MHC-I binding affinity for antigens with explicitly labeled post-translational modifications or unusual/non-canonical amino acids (NCAAs). However, such modifications are increasingly recognized as critical mediators of peptide immunogenicity. In this work, we propose a machine learning application that quantifies the binding affinity of epitopes containing NCAAs to MHC-I and compares its performance with other commonly used regressors. Our model demonstrates robust performance, with 5-fold cross-validation yielding an R2 value of 0.477 and a root-mean-square error (RMSE) of 0.735, indicating strong predictive capability for peptides with NCAAs. This work provides a valuable tool for the computational design and optimization of peptides incorporating NCAAs, potentially accelerating the development of novel peptide-based therapeutics with enhanced properties and efficacy.

bioinformatics↗

bioRxiv2024

Strikingly different neurotransmitter release strategies in dopaminergic subclasses

Neuronal function is intimately tied to axodendritic polarity. Neurotransmitter release, for example, is usually the role of the axon. There are widespread exceptions to this rule, however, including many mammalian neuronal types that can release neurotransmitter from their dendrites. In the mouse olfactory bulb, closely related subclasses of dopaminergic interneuron differ markedly in their polarity, with one subtype lacking an axon entirely. These axon-bearing and anaxonic dopaminergic subclasses have distinct developmental profiles and sensory responses, but how their fundamental polarity differences translate to functional outputs remains entirely unknown. Here, we provide anatomical evidence for distinct neurotransmitter release strategies among these closely related dopaminergic subtypes: anaxonic cells release from their dendrites, while axon-bearing neurons release exclusively from their intermittently myelinated axon. These structural differences are linked to a clear functional distinction: anaxonic, but not axon-bearing dopaminergic neurons are capable of self-inhibition. Our findings suggest that variations in polarity can produce striking distinctions in neuronal outputs, and that even closely related neuronal subclasses may play entirely separate roles in sensory information processing.

neuroscience↗

bioRxiv2024

Development of Non-Spatial Grid-Like Neural Codes Predicts Inference and Intelligence

Piagets theory posits that children develop structured knowledge schemas for inferring and assimilating new information, yet the underlying neural mechanisms remain unclear. In 203 participants aged 8-25 years, we investigated how maturation of a two-dimensional (2D) knowledge map underpins inferential reasoning and knowledge assimilation. Grid-cell-like codes in the entorhinal cortex (EC) strengthened with age, reflecting schema representations in non-spatial conceptual spaces, and were directly linked to improved inferential reasoning. These grid-like codes also supported the medial prefrontal cortex (mPFC) in encoding distance relationships between objects on the 2D map. As participants assimilated new information, they integrated it into existing grid patterns in the EC. Moreover, the maturation of these neural codes predicted real-world intelligence measures, particularly in reasoning abilities. Our findings demonstrate that the development of non-spatial grid-like neural codes offers a mechanistic account of cognitive development, bridging psychological theory with a fundamental cellular representation of cognitive map.

neuroscience↗

bioRxiv2024

Ultra-small Particle Size Nanobubbles Water Drinking Exerts Antifatigue Effects in Chronic Exercise Fatigue Rats via Improving Antioxidative Activities

Chronic exercise fatigue is a prevalent issue that can lead to a decline in physical performance, metabolic dysregulation, and oxidative damage, posing significant health risks. This study aims to investigate the effects of Ultra-small Particle Size Nanobubbles Water (UsNBsW) which was Koishio technology produced water on physiological and biochemical parameters in a rat model of chronic exercise fatigue. We established a chronic fatigue model, and evaluated various physiological and biochemical indicators. Our key findings revealed that Koishio water significantly improved rats swimming performance, reduced blood lactate levels, and enhanced antioxidant capacity, as evidenced by increased hemoglobin content, decreased lactate dehydrogenase and creatine kinase activities (p<0.01). Additionally, liver glycogen levels were notably elevated (p<0.05). Futhermore, the antioxidant markers, including superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities were significantly higher (p<0.01), while malondialdehyde (MDA) and 8-hydroxydeoxyguanosine (8-OH-dG) levels were markedly reduced (p<0.01). Our results provide new clues for the promising role of Koishio water in mitigating chronic exercise fatigue and supply a reliable reference for future research into nutritional interventions and recovery strategies in exercise physiology.

physiology↗

bioRxiv2024

SuperWater: Predicting Water Molecule Positions on Protein Structures by Generative AI

Water molecules play a significant role in maintaining protein structural stability and facilitating molecular interactions. Accurate prediction of water molecule positions around protein structures is essential for understanding their biological roles and has significant implications for protein engineering and drug discovery. Here, we introduce SuperWater, a novel generative AI framework that integrates a score-based diffusion model with equivariant graph neural networks to predict water molecule placements around proteins with high accuracy. SuperWater surpasses existing methods, delivering state-of-the-art performance in both crystal water coverage and prediction precision, achieving water localization within 0.3 {+/-} 0.06 {degrees}A of experimentally validated positions. We demonstrate the capabilities of SuperWater through case studies involving protein hydration, protein-ligand binding, and protein-protein binding sites. This framework can be adapted for various applications, including structural biology, binding site prediction, multi-body docking, and water-mediated drug design.

bioinformatics↗

bioRxiv2024

Enhanced antifungal activity of NK-92 cells against Candida albicans mediated by a mannan-specific chimeric antigen receptor

Chimeric antigen receptors (CARs) offer promising prospects for innovative cell-based therapies against invasive fungal infections such as invasive candidiasis. Here, we have developed four CARs targeting Candida albicans with distinct single-chain variable fragments (scFvs): scFv3-CAR, scFv5-CAR, scFv12-CAR, and scFv{kappa}3-1-CAR. In T cells, scFv5-CAR induced IL-2 expression in response to C. albicans hyphae, while scFv3-CAR and scFv12-CAR did not mediate cell activation against C. albicans. Notably, scFv{kappa}3-1-CAR mediated the strongest cell activation against C. albicans yeast, hyphae, and other clinically relevant Candida species. scFv{kappa}3-1-CAR-NK-92 cells exhibited elevated IFN-{gamma} and CD107a expression, reducing C. albicans viability. NOD scid gamma (NSG) mice treated with scFv{kappa}3-1-CAR-NK-92 cells had reduced C. albicans burden in the kidney 24 hours postinfection. We showed that scFv{kappa}3-1-CAR targets C. albicans mannan but no other glycans in glycan microarray screening analyses. These findings reveal the scFv{kappa}3-1-CAR potential as a therapeutic strategy for treating Candida spp. by modifying peripheral blood mononuclear cells. ImportanceRecent studies on novel immunotherapies, including chimeric antigen receptor (CAR)-T cells, have shown promising results in preclinical models against invasive fungal infections (IFIs). However, the application of CAR technology in natural killer (NK) cells for treating IFIs remains unexplored. NK cells play a key role in early fungal clearance due to their antifungal activity mediated by granzymes, perforins, and the secretion of proinflammatory cytokines. This study is the first to demonstrate the feasibility and efficacy of CAR-modified NK cells targeting Candida spp. We provided proof-of-concept data showing that CAR-expressing NK cells exhibit enhanced activation and antifungal effects against clinically relevant Candida species by targeting mannan in the fungal cell wall. These findings are significant as they open new avenues for developing CAR-NK-based therapies to treat invasive candidiasis - a severe infection with limited treatment options and high mortality rates, particularly in immunocompromised patients.

bioengineering↗