Biology subjects

Yu, B.

Publications and source records attributed to Yu, B..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

Transcriptomic study of testicular hypoxia adaptation in Tibetan sheep

The Tibetan sheep is a typical hypoxia-tolerant mammal, which lives on the plateau, an altitude of between 2,500 and 5,000 meters above sea level, the study of its hypoxic adaptation mechanism provides reference for exploring the hypoxic adaptation mechanism of other animals. To grope for the genetic mechanism of adaptation to hypoxic environment at the transcriptional level in Tibetan sheep testicular tissue, and to identify candidate genes and key pathways related to sheep adaptation. Histological observation of testicular tissues from two sheep breeds was carried out using hematoxylin-eosin (HE) conventional staining. A total of 277 differentially expressed genes (DEGs) were authenticated at high altitude Tibetan sheep (ZYH) and low altitude Tibetan sheep (ZYM) by RNA sequencing technology (RNA-Seq), which included 165 up-regulated genes and 112 down-regulated genes. Functional analyses revealed several terms and pathways, such as were closely related with testis adaptation to plateau. Several genes (including GGT5, AGTR2, EDN1, LPAR3, CYP2C19, IGFBP3, APOC3 and PKC1) were remarkably enriched in several pathways and terms, which may impact the Plateau adaptability of sheep by adjusting its reproductive activity and sexual maturation, and protecting Sertoli cells, various spermatocytes and spermatogenesis processes. The results make a reasonable case for a better understanding of the molecular mechanisms of adaptation to altitude in sheep.

genomics↗

bioRxiv2024

Mapping and Engineering Antibody-Antigen Interaction Landscapes for Systematic Affinity Enhancement

Antibodies, crucial in adaptive immunity, recognize antigens through specific interactions facilitated by Complementarity Determining Regions (CDRs), diversified via Variable-Diversity-Joining (VDJ) recombination. Traditional antibody development, limited by the scope of animal models and phage display libraries, captures a fraction of the potential antibody-antigen interactions. This underscores a gap in understanding antibody specificity and the relationship between antibody sequence and binding affinity. Here we introduce an approach using the Single-Protein Interaction Detection (SPID) platform, repurposed to systematically map local landscapes of antibody-antigen interactions with unprecedented depth and speed, aiming to rival the precision of methods like Surface Plasmon Resonance (SPR) and Bio-Layer Interferometry (BLI) while significantly boosting throughput. By editing CDR sequences and measuring effects on dissociation constants, we elucidated pathways for optimizing antibody affinity, enhancing predictive models for interactions. Our findings demonstrate the capability of the SPID platform to characterize thousands of variants weekly, offering a deeper insight into antibody-antigen interactions and advancing antibody development with finely-tuned affinities.

bioengineering↗

bioRxiv2024

A metabolic atlas of mouse aging

Humans are living longer, but this is accompanied by an increased incidence of age-related chronic diseases. Many of these diseases are influenced by age-associated metabolic dysregulation, but how metabolism changes in multiple organs during aging in males and females is not known. Answering this could reveal new mechanisms of aging and age-targeted therapeutics. In this study, we describe how metabolism changes in 12 organs in male and female mice at 5 different ages. Organs show distinct patterns of metabolic aging that are affected by sex differently. Hydroxyproline shows the most consistent change across the dataset, decreasing with age in 11 out of 12 organs investigated. We also developed a metabolic aging clock that predicts biological age and identified alpha-ketoglutarate, previously shown to extend lifespan in mice, as a key predictor of age. Our results reveal fundamental insights into the aging process and identify new therapeutic targets to maintain organ health.

molecular biology↗

bioRxiv2024

Dynamical constraints on neural population activity

The manner in which neural activity unfolds over time is thought to be central to sensory, motor, and cognitive functions in the brain. Network models have long posited that the brains computations involve time courses of activity that are shaped by the underlying network. A prediction from this view is that the activity time courses should be difficult to violate. We leveraged a brain-computer interface (BCI) to challenge monkeys to violate the naturally-occurring time courses of neural population activity that we observed in motor cortex. This included challenging animals to traverse the natural time course of neural activity in a time-reversed manner. Animals were unable to violate the natural time courses of neural activity when directly challenged to do so. These results provide empirical support for the view that activity time courses observed in the brain indeed reflect the underlying network-level computational mechanisms that they are believed to implement.

neuroscience↗

bioRxiv2023

DNA-terminus-dependent transcription by T7 RNA polymerase and its C-helix mutants

The remarkable success of mRNA-based vaccines has underscored their potential as a novel biotechnology platform for vaccine development and therapeutic protein delivery. However, the single-subunit RNA polymerase from bacteriophage T7 widely used for in vitro transcription is well known to generate double-stranded RNA (dsRNA) byproducts that strongly stimulate the mammalian innate immune response. The dsRNA was reported to be originated from self-templated RNA extension or promoter-independent transcription. Here, we identified that the primary source of the full-length dsRNA during in vitro transcription is the DNA-terminus-initiated transcription by T7 RNA polymerase. Guanosines or cytosines at the end of DNA templates enhance the DNA-terminus-initiated transcription. Moreover, we found that aromatic residues located at position 47 in the C-helix interfere with the binding of T7 RNA polymerase to DNA termini, leading to a significant reduction in the production of full-length dsRNA. As a result, the mRNA synthesized using the T7 RNA polymerase G47W mutant exhibits higher expression efficiency and lower immunogenicity compared to the mRNA produced using the wild-type T7 RNA polymerase.

molecular biology↗

bioRxiv2023

Structure of scavenger receptor SCARF1 and its interaction with lipoproteins

SCARF1 (Scavenger receptor class F member 1, SREC-1 or SR-F1) is a type I transmembrane protein that recognizes multiple endogenous and exogenous ligands such as modified low-density lipoproteins (LDL) and is important for maintaining homeostasis and immunity. But the structural information and the mechanisms of ligand recognition of SCARF1 are largely unavailable. Here we solve the crystal structures of the N-terminal fragments of human SCARF1, which show that SCARF1 forms homodimers and its epidermal growth factor (EGF)-like domains adopt a long-curved conformation. Then we examine the interactions of SCARF1 with lipoproteins and are able to identify a region on SCARF1 for recognizing modified LDLs. The mutagenesis data show that the positively charged residues in the region are crucial for the interaction of SCARF1 with modified LDLs, which is confirmed by making chimeric molecules of SCARF1 and SCARF2. In addition, teichoic acids, a cell wall polymer expressed on the surface of gram-positive bacteria, are able to inhibit the interactions of modified LDLs with SCARF1, suggesting the ligand binding sites of SCARF1 might be shared for some of its scavenging targets. Overall, these results provide mechanistic insights into SCARF1 and its interactions with the ligands, which are important for understanding its physiological roles in homeostasis and the related diseases.

biophysics↗

bioRxiv2023

Therapeutic Targeting of TIM-4-L With Engineered T Cells for Acute Myeloid Leukemia

Disruption of the lipid asymmetric bilayer is a common feature observed in cancer cells. We utilized the natural immune receptor TIM-4 to interrogate for loss of plasma membrane phospholipid polarity in primary acute myelogenous leukemia (AML) samples. We performed FACs analysis in 33 patients and correlated TIM-4-L expression frequency and intensity with molecular disease characteristics. In normal tissues, TIM-4-L is confined to the internal leaflet of the plasma membrane. By contrast, 86% of untreated AML blasts in our analysis displayed upregulation of cell surface TIM-4-L. These observations were agnostic to AML genetic classification, as samples with mutations in TP53, ASXL1, and RUNX1, also displayed TIM-4-L upregulation similar to that seen in favorable and intermediate subtypes. This TIM-4-L dysregulation was also stably present in both Kasumi-1 and MV-4-11 AML cell lines. To evaluate the potential of upregulated TIM-4-L to serve as a target for adoptive T cell therapy (ACT), we constructed TIM-4-L-directed engineered T cells, which demonstrated potent anti-leukemic effects, effectively eliminating AML cell lines both in vitro and in vivo. This approach led to the eradication of AML cells across a range of endogenous TIM-4-L expression levels. These results highlight TIM-4-L as a highly prevalent and novel target for T cell-based therapy in AML. Further investigations into the role of TIM-4-L in AML pathogenesis and its potential as an anti-leukemic target for clinical development are warranted.

cancer biology↗

bioRxiv2023

Automated customization of large-scale spiking network models to neuronal population activity

Understanding brain function is facilitated by constructing computational models that accurately reproduce aspects of brain activity. Networks of spiking neurons capture the underlying biophysics of neuronal circuits, yet the dependence of their activity on model parameters is notoriously complex. As a result, heuristic methods have been used to configure spiking network models, which can lead to an inability to discover activity regimes complex enough to match large-scale neuronal recordings. Here we propose an automatic procedure, Spiking Network Optimization using Population Statistics (SNOPS), to customize spiking network models that reproduce the population-wide covariability of large-scale neuronal recordings. We first confirmed that SNOPS accurately recovers simulated neural activity statistics. Then, we applied SNOPS to recordings in macaque visual and prefrontal cortices and discovered previously unknown limitations of spiking network models. Taken together, SNOPS can guide the development of network models and thereby enable deeper insight into how networks of neurons give rise to brain function.

neuroscience↗

bioRxiv2023

The ubiquitin ligase UBR-1 regulates the synaptic strength between the GABAergic and glutamatergic signaling

Excitation/Inhibition (E/I) balance is carefully maintained by the nervous system. Neurotransmitter GABA has been reported to be co-released with its sole precursor, another neurotransmitter glutamate. The genetic and circuitry mechanisms to establish the balance between GABAergic and Glutamatergic signaling have not fully elucidated. C. elegans DVB is a classically defined excitatory GABAergic motoneuron that drives the expulsion step in defecation motor program. We show that in addition to UNC-47, the vesicular GABA transporter, DVB also expresses EAT-4, a vesicular glutamate transporter. UBR-1, a conserved ubiquitin ligase, regulates the DVB activity by suppressing a bidirectional inhibitory glutamate signaling. Loss of UBR-1 impairs the DVB Ca2+ activity and the expulsion frequency. These impairments are fully compensated by the knock-down of EAT-4 in DVB. Further, glutamate-gated chloride channels GLC-3 and GLC-2/4 receive DVBs glutamate signals to inhibit DVB and enteric muscle, respectively. These results implicate an intrinsic cellular mechanism that promotes the inherent asymmetric neural activity. We propose that the elevated glutamate in ubr-1 being the cause of the E/I shift, potentially contributes to the Johanson Blizzard Syndrome.

neuroscience↗

bioRxiv2023

Human Plasma Proteomic Profile of Clonal Hematopoiesis

Plasma proteomic profiles associated with subclinical somatic mutations in blood cells may offer novel insights into downstream clinical consequences. Here, we explore such patterns in clonal hematopoiesis of indeterminate potential (CHIP), which is linked to several cancer and non-cancer outcomes, including coronary artery disease (CAD). Among 61,833 ancestrally diverse participants (3,881 with CHIP) from NHLBI TOPMed and UK Biobank with blood-based DNA sequencing and proteomic measurements (1,148 proteins by SomaScan in TOPMed and 2,917 proteins by Olink in UK Biobank), we identified 32 and 345 unique proteins from TOPMed and UK Biobank, respectively, associated with the most prevalent driver genes (DNMT3A, TET2, and ASXL1). These associations showed substantial heterogeneity by driver genes, sex, and race, and were enriched for immune response and inflammation pathways. Mendelian randomization in humans, coupled with ELISA in hematopoietic Tet2-/- vs wild-type mice validation, disentangled causal proteomic perturbations from TET2 CHIP. Lastly, we identified plasma proteins shared between CHIP and CAD.

genetics↗

bioRxiv2023

Eugenol mimics exercise to promote skeletal muscle fiber remodeling and myokine IL-15 expression by activating TRPV1 channel

Metabolic disorders are highly prevalent in modern society. Exercise mimetics are defined as pharmacologic compounds that can produce the beneficial effects of fitness. Recently, there has been increased interest in the role of eugenol and transient receptor potential vanilloid 1 (TRPV1) in improving metabolic health. The aim of this study was to investigate whether eugenol acts as an exercise mimetic by activating TRPV1. Here, we showed that eugenol improved endurance capacity, caused the conversion of fast to slow muscle fibers, and promoted white fat browning and lipolysis in mice. Mechanistically, eugenol promoted muscle fiber type transformation by activating TRPV1-mediated CaN signaling pathway. Subsequently, we identified IL-15 as a myokine that is regulated by the CaN/Nuclear factor of activated T cells cytoplasmic 1 (NFATc1) signaling pathway. Moreover, we found that TRPV1-mediated CaN/NFATc1 signaling, activated by eugenol, controlled IL-15 levels in C2C12 myotubes. Our results suggest that eugenol may act as an exercise mimetic to improve metabolic health via activating the TRPV1-mediated CaN signaling pathway.

molecular biology↗

bioRxiv2023

Leucine alleviates cytokine storm syndrome by regulating macrophage polarization via the mTORC1/LXRα signaling pathway

Cytokine storms are associated with severe pathological damage and death in some diseases. Excessive activation of M1 macrophages and the subsequent secretion of pro-inflammatory cytokines are a major cause of cytokine storms. Therefore, promoting the polarization of M2 macrophages to restore immune balance is a promising therapeutic strategy for treating cytokine storm syndrome (CSS). This study was aimed at investigating the potential protective effects of leucine on lipopolysaccharide (LPS)-induced CSS in mice and exploring the underlying mechanisms. CSS was induced by LPS administration in mice, which were concurrently administered leucine orally. In vitro, BMDMs were polarized to M1 and M2 phenotypes with LPS and IL-4, respectively, and treated with leucine. Leucine decreased mortality in mice treated with lethal doses of LPS. Specifically, leucine decreased M1 polarization and promoted M2 polarization, thus diminishing pro-inflammatory cytokine levels and ameliorating CSS in mice. Further studies revealed that leucine induced macrophage polarization through the mechanistic target of rapamycin complex 1 (mTORC1)/liver X receptor (LXR) pathway, which synergistically enhanced the expression of the IL-4-induced M2 marker Arg1 and subsequent M2 polarization. In summary, this study revealed that leucine ameliorates CSS in LPS mice by promoting M2 polarization through the mTORC1/LXR/Arg1 signaling pathway. Our findings indicate that a fundamental link between metabolism and immunity contributes to the resolution of inflammation and the repair of damaged tissues.

immunology↗

bioRxiv2023

Prokaryotic Gabija complex senses and executes nucleotide depletion and DNA cleavage for antiviral defense

The Gabija antiviral system consists of the GajA and GajB proteins. We previously revealed that GajA is a DNA nicking endonuclease. In this work, we found that the DNA binding of GajA is strictly inhibited by NTP. Furthermore, the antiviral defense of GajA requires the assistance from GajB, which senses DNA termini produced from the DNA nicking by GajA to hydrolyze (d)A/(d)GTP. The synergy between the DNA cleavage by GajA and the nucleotide hydrolysis by GajB results in an efficient abortive infection defense against virulent bacteriophages. GajA binds to GajB to form stable complexes in vivo and in vitro. However, a functional Gabija complex requires the molecular ratio between GajB and GajA below 1:1. Through (i) sequential sensing and executing the nucleotide depletion and DNA cleavage to cause a cascade suicide effect and (ii) stoichiometry regulation of the DNA/nucleotide processing complex, the Gabija system exhibits a unique mechanism distinct from other known prokaryotic antiviral systems.

microbiology↗

bioRxiv2023

Identification of allele-specific KIV-2 repeats and impact on Lp(a) measurements for cardiovascular disease risk

The abundance of Lp(a) protein holds significant implications for the risk of cardiovascular disease (CVD), which is directly impacted by the copy number (CN) of KIV-2, a 5.5 kbp sub-region. KIV-2 is highly polymorphic in the population and accurate analysis is challenging. In this study, we present the DRAGEN KIV-2 CN caller, which utilizes short reads. Data across 166 WGS show that the caller has high accuracy, compared to optical mapping and can further phase [~]50% of the samples. We compared KIV-2 CN numbers to 24 previously postulated KIV-2 relevant SNVs, revealing that many are ineffective predictors of KIV-2 copy number. Population studies, including USA-based cohorts, showed distinct KIV-2 CN, distributions for European-, African-, and Hispanic-American populations and further underscored the limitations of SNV predictors. We demonstrate that the CN estimates correlate significantly with the available Lp(a) protein levels and that phasing is highly important.

genomics↗

bioRxiv2023

StocSum: stochastic summary statistics for whole genome sequencing studies

Genomic summary statistics, usually defined as single-variant test results from genome-wide association studies, have been widely used to advance the genetics field in a wide range of applications. Applications that involve multiple genetic variants also require their correlations or linkage disequilibrium (LD) information, often obtained from an external reference panel. In practice, it is usually difficult to find suitable external reference panels that represent the LD structure for underrepresented and admixed populations, or rare genetic variants from whole genome sequencing (WGS) studies, limiting the scope of applications for genomic summary statistics. Here we introduce StocSum, a novel reference-panel-free statistical framework for generating, managing, and analyzing stochastic summary statistics using random vectors. We develop various downstream applications using StocSum including single-variant tests, conditional association tests, gene-environment interaction tests, variant set tests, as well as meta-analysis and LD score regression tools. We demonstrate the accuracy and computational efficiency of StocSum using two cohorts from the Trans-Omics for Precision Medicine Program. StocSum will facilitate sharing and utilization of genomic summary statistics from WGS studies, especially for underrepresented and admixed populations.

genetics↗

bioRxiv2023

Inter-user comparison for quantification of superparamagnetic iron oxides with magnetic particle imaging across two institutions highlights a need for standardized approaches

PurposeMagnetic particle imaging (MPI) is being explored in biological contexts that require accurate and reproducible quantification of superparamagnetic iron oxide nanoparticles (SPIONs). While many groups have focused on improving imager and SPION design to improve resolution and sensitivity, few have focused on improving quantification and reproducibility of MPI. The aim of this study was to compare MPI quantification results by two different systems and the accuracy of SPION quantification performed by multiple users at two institutions. ProceduresSix users (3 from each institute) imaged a known amount of Vivotrax+ (10 g Fe), diluted in a small (10 L) or large (500 L) volume. These samples were imaged with or without calibration standards in the field of view, to create a total of 72 images (6 users x triplicate samples x 2 sample volumes x 2 calibration methods). These images were analyzed by the respective user with two region of interest (ROI) selection methods. Image intensities, Vivotrax+ quantification, and ROI selection was compared across users, within and across institutions. ResultsMPI imagers at two different institutes produce significantly different signal intensities, that differ by over 3 times for the same concentration of Vivotrax+. Overall quantification yielded measurements that were within {+/-} 20% from ground truth, however SPION quantification values obtained at each laboratory were significantly different. Results suggest that the use of different imagers had a stronger influence on SPION quantification compared to differences arising from user error. Lastly, calibration conducted from samples in the imaging field of view gave the same quantification results as separately imaged samples. ConclusionsThis study highlights that there are many factors that contribute to the accuracy and reproducibility of MPI quantification, including variation between MPI imagers and users, despite pre-defined experimental set up, image acquisition parameters, and ROI selection analysis.

biophysics↗

bioRxiv2023

Mitigation of chromosome loss in clinical CRISPR-Cas9-engineered T cells

CRISPR-Cas9 genome editing has enabled advanced T cell therapies, but occasional loss of the targeted chromosome remains a safety concern. To investigate whether Cas9-induced chromosome loss is a universal phenomenon and evaluate its clinical significance, we conducted a systematic analysis in primary human T cells. Arrayed and pooled CRISPR screens revealed that chromosome loss was generalizable across the genome and resulted in partial and entire loss of the chromosome, including in pre-clinical chimeric antigen receptor T cells. T cells with chromosome loss persisted for weeks in culture, implying the potential to interfere with clinical use. A modified cell manufacturing process, employed in our first-in-human clinical trial of Cas9-engineered T cells,1 dramatically reduced chromosome loss while largely preserving genome editing efficacy. Expression of p53 correlated with protection from chromosome loss observed in this protocol, suggesting both a mechanism and strategy for T cell engineering that mitigates this genotoxicity in the clinic.

cell biology↗

bioRxiv2023

Unsupervised pattern discovery in spatial gene expression atlas reveals mouse brain regions beyond established ontology

The rapid growth of large-scale spatial gene expression data demands efficient and reliable computational tools to extract major trends of gene expression in their native spatial context. Here, we used stability-driven unsupervised learning (i.e. staNMF) to identify principal patterns (PPs) of 3D gene expression profiles and understand spatial gene distribution and anatomical localization at the whole mouse brain level. Our subsequent spatial correlation analysis systematically compared the PPs to known anatomical regions and ontology from the Allen Mouse Brain Atlas using spatial neighborhoods. We demonstrate that our stable and spatially coherent PPs, whose linear combinations accurately approximate the spatial gene data, are highly correlated with combinations of expert-annotated brain regions. These PPs yield a new brain ontology based purely on spatial gene expression. Our PP identification approach outperforms principal component analysis (PCA) and typical clustering algorithms on the same task. Moreover, we show that the stable PPs reveal marked regional imbalance of brainwide genetic architecture, leading to region-specific marker genes and gene co-expression networks. Our findings highlight the advantages of stability-driven machine learning for plausible biological discovery from dense spatial gene expression data that are infeasible by conventional manual approaches.

neuroscience↗