Biology subjects

Zhao, B.

Publications and source records attributed to Zhao, B..

At least 109 records · Page 6Linked to original sources

bioRxiv2023

Dopamine and neuromodulation shorten the latency from motor intention to execution in Parkinson's disease

The ability to initiate volitional action is fundamental to human behaviour. Loss of dopaminergic neurons in Parkinsons disease is associated with impaired action initiation, also termed akinesia. Both dopamine and subthalamic deep brain stimulation (DBS) can alleviate akinesia, but the underlying mechanisms are unknown. An important question is whether dopamine and DBS facilitate de novo build-up of neural dynamics for motor execution or accelerate existing cortical movement initiation signals through shared modulatory circuit effects. Answering these questions can provide the foundation for new closed-loop neurotherapies with adaptive DBS, but the objectification of neural processing delays prior to performance of volitional action remains a significant challenge. To overcome this challenge, we studied readiness potentials and trained brain signal decoders on invasive neurophysiology signals in 25 DBS patients (12 female) with Parkinsons disease during performance of self-initiated movements. Combined sensorimotor cortex electrocorticography (ECoG) and subthalamic local field potential (LFP) recordings were performed OFF therapy (N=22), ON dopaminergic medication (N=18) and ON subthalamic deep brain stimulation (N=8). This allowed us to compare their therapeutic effects on neural latencies between the earliest cortical representation of movement intention as decoded by linear discriminant analysis classifiers and onset of muscle activation recorded with electromyography (EMG). In the hypodopaminergic OFF state, we observed long latencies between motor intention and motor execution for readiness potentials and machine learning classifications. Both, dopamine and DBS significantly shortened these latencies, hinting towards a shared therapeutic mechanism for alleviation of akinesia. To investigate this further, we analysed directional cortico-subthalamic oscillatory communication with multivariate granger causality. Strikingly, we found that both therapies independently shifted cortico-subthalamic oscillatory information flow from antikinetic beta (13-35 Hz) to prokinetic theta (4-10 Hz) rhythms, which was correlated with latencies in motor execution. Our study reveals a shared brain network modulation pattern of dopamine and DBS that may underlie the acceleration of neural dynamics for augmentation of movement initiation in Parkinsons disease. Instead of producing or increasing preparatory brain signals, both therapies modulate oscillatory communication. These insights provide a link between the pathophysiology of akinesia and its therapeutic alleviation with oscillatory network changes in other non-motor and motor domains, e.g. related to hyperkinesia or effort and reward perception. In the future, our study may inspire the development of clinical brain computer interfaces based on brain signal decoders to provide temporally precise support for action initiation in patients with brain disorders.

neuroscience↗

bioRxiv2023

The mtDNA-derived lncMtDloop promotes mitochondrial homeostasis maintenance and implications in AD

Maintaining mitochondrial homeostasis stands as a critical factor for cell survival and the health of organisms, as evidenced by the links between mitochondrial dysfunction and a spectrum of diseases, including Alzheimers disease (AD). Here we report that lncMtDloop, a lncRNA originating from the mtDNA D-loop, upholds mitochondrial homeostasis. LncMtDloop demonstrates an affinity for mitochondrial transcription factor A (TFAM), thereby facilitating TFAMs recruitment to mtDNA promoters and enhancing gene transcription. We further observed decreased lncMtDloop expression in the brains of human AD patients and 3xTg mice. Through the introduction of allotropic lncMtDloop with the 3UTR of MRPS12, a significant improvement in mitochondrial homeostasis and a concurrent amelioration of AD-like pathology were found, which exerts a positive influence on synaptic plasticity and behavioral deficits observed in AD mice. Our study provides mechanistic insights into lncMtDloop as a regulator of mitochondrial homeostasis, shedding light on a perspective regarding its contribution to Alzheimers pathogenesis.

molecular biology↗

bioRxiv2023

Biosynthesis of H-GDGTs linked to ocean oxygen deficiency

Archaeal membrane lipids GDGTs (glycerol dialkyl glycerol tetraethers) are biomarkers used for tracking Earths historical environmental changes. Among these GDGTs, the H-shaped GDGTs (H-GDGTs, or GMGTs) represent a less-explored and often overlooked subset, with its biosynthetic pathway and geological significance remaining elusive. Here, we identified the gene responsible for biosynthesizing H-GDGTs, which encodes to a radical S-adenosyl-L-methionine (SAM) enzyme, named as H-GDGTs bridge synthase (Hbs). Heterologous expression of the gene hbs in a methanogen, as well as in vitro activity assay using the purified Hbs enzyme were performed. Additionally, we found that the genes encoding Hbs are exclusively present in obligate anaerobic archaea genomes and the metagenomes obtained from oxygen-deficient environments, but not in oxic settings. The H-GDGTs lipids were also consistently enriched in the modern oxygen-deficient environments, and remarkably accumulated in ancient sediments during oceanic anoxic event-2 (OAE-2, [~]94 million years ago) period. Our findings indicate H-GDGTs holds significant promise as a novel biomarker for studying historical ocean oxygen deficiency supported by a well-established biological basis.

microbiology↗

bioRxiv2023

Large-scale imputation models for multi-ancestry proteome-wide association analysis

Proteome-wide association studies (PWAS) decode the intricate proteomic landscape of biological mechanisms for complex diseases. Traditional PWAS model training relies heavily on individual-level reference proteomes, restricting its capacity to harness the emerging summary-level protein quantitative trait loci (pQTL) data in the public domain. Here we introduced BLISS, a novel framework to train protein imputation models using only pQTL summary statistics. By leveraging extensive pQTL data from the UK Biobank, deCODE, and ARIC studies, we applied BLISS to develop large-scale European PWAS models covering 5,779 unique proteins. We further extended BLISS to integrate with small-scale non-European individual-level datasets, enabling the development of models tailored to Asian and African ancestries. We validated the performance of BLISS models through a systematic multi-ancestry analysis of over 2,500 phenotypes across five major genetic data resources. The newly identified protein-phenotype associations offer valuable insights into their cross-ancestry transferability, the contributions of different proteomic platforms, and the complementary perspectives provided by distinct genomic mapping approaches relevant to drug discovery. The developed models and data resources are freely available at https://www.gcbhub.org/.

genetics↗

bioRxiv2023

Asynchronous Detection of Erroneous Behaviors in Human-Robot Interaction with EEG: A Comparative Analysis of Machine Learning Models.

We present a comparative analysis of two distinct machine-learning models designed to detect asynchronous errors during Human-Robot Interaction (HRI). The models under scrutiny are a customized ResNet model and an ensemble model, both trained and validated using EEG data. The ResNet model is a unique adaptation of the Residual Network, comprising a one-dimensional convolutional layer followed by batch normalization and ReLU activation. It also features a custom Residual Block structure and an adaptive average pooling layer, concluding with a fully connected linear layer for binary classification. The ensemble model, on the other hand, incorporates various machine learning models such as MLP, logistic regression, SVM, random forest, and XGBoost, unified in a pipeline with feature extraction and transformation steps. A critical component of our research is the innovative probability map, which maintains a granularity of 0.1 seconds. This map forecasts the likelihood of forthcoming one-second intervals being classified as either Error or Non-error. Our comparative analysis reveals significant variations in the performance of the two models, both of which exhibit promising results in detecting erroneous behaviors during HRI. We provide detailed validation results, including the accuracy, F1 score, and confusion matrix for each model. This study offers valuable insights into the potential of machine learning in enhancing HRI efficiency and accuracy, indicating promising directions for future research.

neuroscience↗

bioRxiv2023

Proteonano: a novel deep proteomics platform with 1000-plex profiling capacity and picogram sensitivity and its application in diabetic kidney disease

The development of blood-based multi-biomarker panels for screening diabetic patients, and as an easy-to-access tool for identifying individuals at greatest risk of developing diabetic kidney disease (DKD) and its progression, is essential. However, conventional blood biomarker-based methodologies (e.g. clinical tests and ELISA) are unable to predict DKD progression with high sensitivity and specificity. To overcome these challenges, we developed a deep, untargeted plasma proteome profiling technology (Proteonano platform) to identify potential multiple protein biomarkers involved in DKD progression. The Proteonano technology is an affinity selective mass spectrometric platform that comprises nanoparticle-based affinity binders (nanobinders) for low abundant protein enrichment, automated workflow for parallel sample preparation, and machine learning empowered bioinformatic software for data analysis. Using the Proteonano platform, we performed untargeted proteomics on 75 subjects (DKD progressors, n = 30; DKD non-progressors, n = 45) and identified an average of 953 {+/-} 80 (AVG {+/-} SD) protein groups, with a wide dynamic range of 8 orders of magnitude (with the lowest concentration down to 3.00 pg/mL). Among these, 38 proteins were differentially expressed between DKD progressors relative to non-progressors, and the predictive power for these proteins were assessed. Further, we performed random forest and LASSO analyses for additional variable selection. Variables selected by these approaches were assessed by Akaike information criterion method followed by ROC analysis, which identified a combination of multiple proteins (including VWF, PTGDS, B2M, BT3A2, and LCAT) that showed excellent predictive power over current methods, with an area under the curve value up to 0.97. Some of these plasma proteins are not previously recognized in the context of DKD progression, suggesting they are novel biomarkers. Our studies pave the way to develop multi-biomarker panels for DKD progression management. This study suggests that the Proteonano technology platform reported here can be employed as an established workflow enabling untargeted deep proteomic analysis to identify highly discriminative biomarkers for precise medicine.

bioinformatics↗

bioRxiv2023

Large-scale annotated dataset for cochlear hair cell detection and classification

Our sense of hearing is mediated by cochlear hair cells, localized within the sensory epithelium called the organ of Corti. There are two types of hair cells in the cochlea, which are organized in one row of inner hair cells and three rows of outer hair cells. Each cochlea contains a few thousands of hair cells, and their survival is essential for our perception of sound because they are terminally differentiated and do not regenerate after insult. It is often desirable in hearing research to quantify the number of hair cells within cochlear samples, in both pathological conditions, and in response to treatment. However, the sheer number of cells along the cochlea makes manual quantification impractical. Machine learning can be used to overcome this challenge by automating the quantification process but requires a vast and diverse dataset for effective training. In this study, we present a large collection of annotated cochlear hair-cell datasets, labeled with commonly used hair-cell markers and imaged using various fluorescence microscopy techniques. The collection includes samples from mouse, human, pig and guinea pig cochlear tissue, from normal conditions and following in-vivo and in-vitro ototoxic drug application. The dataset includes over 90,000 hair cells, all of which have been manually identified and annotated as one of two cell types: inner hair cells and outer hair cells. This dataset is the result of a collaborative effort from multiple laboratories and has been carefully curated to represent a variety of imaging techniques. With suggested usage parameters and a well-described annotation procedure, this collection can facilitate the development of generalizable cochlear hair cell detection models or serve as a starting point for fine-tuning models for other analysis tasks. By providing this dataset, we aim to supply other groups within the hearing research community with the opportunity to develop their own tools with which to analyze cochlear imaging data more fully, accurately, and with greater ease.

neuroscience↗

bioRxiv2023

Self-assembly vascularized human cardiac organoids model cardiac diseases in petri dishes and in mice

In this study, we generated self-assembly cardiac organoids (COs) from human pluripotent stem cells by dual-phase modulation of Wnt/{beta}-catenin pathway, utilizing CHIR99021 and IWR-1-endo. The resulting COs exhibited a diverse array of cardiac-specific cell lineages, cardiac cavity-like structures and demonstrated the capacity of spontaneous beating and vascularization in vitro. We further employed these complex and functional COs to replicate conditions akin to human myocardial infarction and SARS-CoV-2 induced fibrosis. These models accurately captured the pathological characteristics of these diseases, in both in vitro and in vivo settings. In addition, we transplanted the COs into NOD SCID mice and observed that they survived and exhibited ongoing expansion in vivo. Impressively, over a span of 75-day transplantation, these COs not only established blood vessel-like structures but also integrated with the host mices vascular system. It is noteworthy that these COs developed to a size of approximately 8 mm in diameter, slightly surpassing the dimensions of the mouse heart. This innovative research highlighted the potential of our COs as a promising avenue for cardiovascular research and therapeutic exploration.

cell biology↗

bioRxiv2023

Resolution enhancement with deblurring by pixel reassignment (DPR)

Improving the spatial resolution of a fluorescence microscope has been an ongoing challenge in the imaging community. To address this challenge, a variety of approaches have been taken, ranging from instrumentation development to image post-processing. An example of the latter is deconvolution, where images are numerically deblurred based on a knowledge of the microscope point spread function. However, deconvolution can easily lead to noise-amplification artifacts. Deblurring by post-processing can also lead to negativities or fail to conserve local linearity between sample and image. We describe here a simple image deblurring algorithm based on pixel reassignment that inherently avoids such artifacts and can be applied to general microscope modalities and fluorophore types. Our algorithm helps distinguish nearby fluorophores even when these are separated by distances smaller than the conventional resolution limit, helping facilitate, for example, the application of single-molecule localization microscopy in dense samples. We demonstrate the versatility and performance of our algorithm under a variety of imaging conditions.

cell biology↗

bioRxiv2023

Mark2 phosphorylation of KIF13A at 14-3-3 binding site is required for maintaining TfR vesicle transport dendritically in neuron

Neurons regulate the microtubule-based transport of certain vesicles selectively into axons or dendrites to ensure proper polarization of function. The mechanism of this polarized vesicle transport is still not fully elucidated, though it is known to involve kinesins, which drive anterograde transport on microtubules. Here we explore how the kinesin-3 family member KIF13A is regulated such that vesicles containing transferrin receptor (TfR) travel only to dendrites. In experiments involving live-cell imaging, knockout of KIF13A, BioID assay, we found that the kinase MARK2 phosphorylates KIF13A at a 14-3-3 binding motif, strengthening interaction of KIF13A with 14-3-3 such that it dissociates from TfR-containing vesicles, which therefore cannot enter axons. Overexpression of KIF13A or knockout of MARK2 leads to axonal transport of TfR-containing vesicles. These results suggest a novel kinesin-based mechanism for polarized transport of vesicles to dendrites. SignificanceOur findings suggest that at least one type of vesicles, those containing transferrin receptor, travel exclusively to dendrites and are excluded from axons because the kinase MARK2 phosphorylates the kinesin KIF13A to promote its separation from vesicles at the proximal axon, preventing vesicle transport into axons, such that they travel only to dendrites. Future studies should explore how this mechanism of polarized vesicle transport supports neuronal function.

neuroscience↗

bioRxiv2023

The ChickenGTEx pilot analysis: a reference of regulatory variants across 28 chicken tissues

Chicken is a valuable model for understanding fundamental biology, vertebrate evolution and diseases, as well as a major source of nutrient-dense and lean-protein-enriched food globally. Although it is the first non-mammalian amniote genome to be sequenced, the chicken genome still lacks a systematic characterization of functional impacts of genetic variants. Here, through integrating 7,015 RNA-Seq and 2,869 whole-genome sequence data, the Chicken Genotype- Tissue Expression (ChickenGTEx) project presents the pilot reference of regulatory variants in 28 chicken tissue transcriptomes, including millions of regulatory effects on primary expression (including protein-coding genes, lncRNA and exon) and post-transcriptional modifications (alternative splicing and 3 untranslated region alternative polyadenylation). We explored the tissue-sharing and context-specificity of these regulatory variants, their underlying molecular mechanisms of action, and their utility in interpreting adaptation and genome-wide associations of 108 chicken complex traits. Finally, we illustrated shared and lineage-specific features of gene regulation between chickens and mammals, and demonstrated how the ChickenGTEx resource can further assist with translating genetic findings across species. One-Sentence SummaryThe ChickenGTEx provides a multi-tissue reference of regulatory variants for chicken genetics and genomics, functional genomics, precision breeding, veterinary medicine, vertebrate evolution and even human biomedicine.

genetics↗

bioRxiv2023

Synthetic Frizzled agonist and LRP antagonist for high-efficiency Wnt/β-catenin signaling manipulation in organoid cultures and in vivo

Wnt/{beta}-catenin signaling and its dysregulation play critical roles in the fate determination of stem cells and the pathology of various diseases. However, the application of translated Wnt ligand in regenerative medicine is hampered by its hydrophobicity and cross-reactivity with Frizzled (FZD) receptors. Here, we generate an engineered water-soluble, FZD subtype-specific agonist, RRP-pbFn, for high-efficiency Wnt/{beta}-catenin signaling activation. In the absence of direct binding to LRP5/6, RRP-pbFn stimulates Wnt/{beta}-catenin signaling more potently than surrogate Wnt. RRP-pbFn supports the growth of a variety of mouse and human organoids, and induces the expansion of liver and intestine progenitors in vivo. Meanwhile, we develop a synthetic LRP antagonist, RRP-Dkk1c, which exhibits heightened effectiveness in attenuating Wnt/{beta}-catenin signaling activity compared to Dkk1, thereby abolishing the formation of CT26-derived colon cancer xenograft in vivo. Together, these two paired Wnt/{beta}-catenin signaling manipulators hold great promise for biomedical research and potential therapeutics.

synthetic biology↗

bioRxiv2023

Levy statistics define anxiety and depression in mice subjected to chronic stress

IntroductionAnxiety and depression are recognized as adaptive responses to external stressors in organisms. Current methods for evaluating anxiety and depression in rodents are both burdensome and stressful. The objective of this investigation is to explore a simplified methodology for identifying stress-induced and stress-free states, as well as anxiety and depression levels, by analyzing the movement patterns of rodents. MethodsTo address this issue, we utilized Levy statistics to examine the movement patterns of stressed rodents and compared them to non-stressed controls. We employed the two-dimensional Kolmogorov-Smirnov test to identify significant differences in the {gamma} and parameters derived from Levy flight (LF) between anxiety, depression, and control mice. Additionally, we employed the support vector machine algorithm to optimize the classification of each group. ResultsOur analysis revealed that stressed mice displayed heavy-tailed distributions of movement velocity in open fields, resembling the movement patterns observed in animal predators searching for scarce food sources in nature. In contrast, non-stressed mice exhibited a normal distribution of speed. Notably, the effectiveness of this methodology in the field of drug discovery was confirmed by the response of stressed mice to fluoxetine, a well-established selective serotonin reuptake inhibitor (SSRI). ConclusionThis study unveils a previously unidentified statistical walking pattern in mice experiencing anxiety and depression. These findings offer a novel and accessible approach for distinguishing between anxiety, depression, and healthy mice. This method provides a one-step gentle approach (free walk in an open field) instead of the traditional multi-step stressful tests.

animal behavior and cognition↗

bioRxiv2023

Evolution of Shewanella oneidensis MR-1 in competition with Citrobacter freundii

Interspecific competition is one of the most important metabolic interactions within microbial communities, and exoelectrogenic bacteria that can conduct extracellular electron transfer act essential roles in nature and engineering systems for pollutants removal. In the present study we investigated the long-term impact of substrate competition from non-exoelectrogenic Citrobacter freundii An1 on exoelectrogenic Shewanella oneidensis MR-1. Without additional electron acceptor or with electron acceptor of oxygen, C. freundii An1 typically suppressed the growth of S. oneidensis MR-1. In contrast, S. oneidensis MR-1 grown better with electron acceptor of ferrihydrite by taking advantage of extracellular electron transfer. However, the presence of ferrihydrite did not enhance the ferrihydrite reduction of S. oneidensis MR-1 after the 160 d-acclimation. The whole genome resequencing showed a complex evolution of S. oneidensis MR-1 when the strain faced the competition from C. freundii An1 for substrate.

microbiology↗

bioRxiv2023

Analyzing bivariate cross-trait genetic architecture in GWAS summary statistics with the BIGA cloud computing platform

As large-scale biobanks provide increasing access to deep phenotyping and genomic data, genome-wide association studies (GWAS) are rapidly uncovering the genetic architecture behind various complex traits and diseases. GWAS publications typically make their summary-level data (GWAS summary statistics) publicly available, enabling further exploration of genetic overlaps between phenotypes gathered from different studies and cohorts. However, systematically analyzing high-dimensional GWAS summary statistics for thousands of phenotypes can be both logistically challenging and computationally demanding. In this paper, we introduce BIGA (https://bigagwas.org/), a website that aims to offer unified data analysis pipelines and processed data resources for cross-trait genetic architecture analyses using GWAS summary statistics. We have developed a framework to implement statistical genetics tools on a cloud computing platform, combined with extensive curated GWAS data resources. Through BIGA, users can upload data, submit jobs, and share results, providing the research community with a convenient tool for consolidating GWAS data and generating new insights.

genetics↗

bioRxiv2023

The Genetic Heterogeneity of Multimodal Human Brain Age

The complex biological mechanisms underlying human brain aging remain incompletely understood, involving multiple body organs and chronic diseases. In this study, we used multimodal magnetic resonance imaging and artificial intelligence to examine the genetic architecture of the brain age gap (BAG) derived from gray matter volume (GM-BAG, N=31,557 European ancestry), white matter microstructure (WM-BAG, N=31,674), and functional connectivity (FC-BAG, N=32,017). We identified sixteen genomic loci that reached genome-wide significance (P-value<5x10-8). A gene-drug-disease network highlighted genes linked to GM-BAG for treating neurodegenerative and neuropsychiatric disorders and WM-BAG genes for cancer therapy. GM-BAG showed the highest heritability enrichment for genetic variants in conserved regions, whereas WM-BAG exhibited the highest heritability enrichment in the 5 untranslated regions; oligodendrocytes and astrocytes, but not neurons, showed significant heritability enrichment in WM and FC-BAG, respectively. Mendelian randomization identified potential causal effects of several exposure variables on brain aging, such as type 2 diabetes on GM-BAG (odds ratio=1.05 [1.01, 1.09], P-value=1.96x10-2) and AD on WM-BAG (odds ratio=1.04 [1.02, 1.05], P-value=7.18x10-5). Overall, our results provide valuable insights into the genetics of human brain aging, with clinical implications for potential lifestyle and therapeutic interventions. All results are publicly available at the MEDICINE knowledge portal: https://labs.loni.usc.edu/medicine.

genetics↗

bioRxiv2023

RBP-J regulates homeostasis and function of circulating Ly6C lo monocytes

Notch-RBP-J signaling plays an essential role in maintenance of myeloid homeostasis. However, its role in monocyte cell fate decisions is not fully understood. Here we showed that conditional deletion of transcription factor RBP-J in myeloid cells resulted in marked accumulation of blood Ly6Clo monocytes that highly expressed chemokine receptor CCR2. Bone marrow transplantation and parabiosis experiments revealed a cell intrinsic requirement of RBP-J for controlling blood Ly6CloCCR2hi monocytes. RBP-J-deficient Ly6Clo monocytes exhibited enhanced capacity competing with wildtype counterparts in blood circulation. In accordance with alterations of circulating monocytes, RBP-J deficiency led to markedly increased population of lung tissues with Ly6Clo monocytes and CD16.2+ interstitial macrophages. Furthermore, RBP-J deficiency-associated phenotypes could be genetically corrected by further deleting Ccr2 in myeloid cells. These results demonstrate that RBP-J functions as a crucial regulator of blood Ly6Clo monocytes and thus derived lung-resident myeloid populations, at least in part through regulation of CCR2.

immunology↗

bioRxiv2023

Engineered allostery in light-regulated LOV-Turbo enables precise spatiotemporal control of proximity labeling in living cells

The incorporation of light-responsive domains into engineered proteins has enabled control of protein localization, interactions, and function with light. We integrated optogenetic control into proximity labeling (PL), a cornerstone technique for high-resolution proteomic mapping of organelles and interactomes in living cells. Through structure-guided screening and directed evolution, we installed the light-sensitive LOV domain into the PL enzyme TurboID to rapidly and reversibly control its labeling activity with low-power blue light. "LOV-Turbo" works in multiple contexts and dramatically reduces background in biotin-rich environments such as neurons. We used LOV-Turbo for pulse-chase labeling to discover proteins that traffick between endoplasmic reticulum, nuclear, and mitochondrial compartments under cellular stress. We also showed that instead of external light, LOV-Turbo can be activated by BRET from luciferase, enabling interaction-dependent PL. Overall, LOV-Turbo increases the spatial and temporal precision of PL, expanding the scope of experimental questions that can be addressed with PL.

molecular biology↗