Biology subjects

Su, Y.

Publications and source records attributed to Su, Y..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

D-LMBmapX: Generalized Deep-Learning Pipeline for Automated Whole-brain Neural Circuitry Profiling Across Any Developmental Stages

Understanding whole-brain circuitry development is essential for uncovering the origins of disorders linked to abnormal neural wiring, yet progress has been limited by the lack of tools for accurate, comprehensive analysis. Brain development is highly dynamic and region-specific, with pronounced inter-individual variability during early stages, and no existing method achieves whole-brain profiling at arbitrary stages. The rapidly changing morphology of developing axons further complicates segmentation. Here, we present D-LMBmapX, a deep learning pipeline for automated whole-brain circuitry profiling across postnatal development. D-LMBmapX constructs sample-inferred atlases from flanking anchor stages, enabling accurate registration at any time point. By developing a foundation model for generalised axon and soma segmentation, it supports quantitative mesoscale developmental connectomics, demonstrated through spatial-temporal profiling of catecholaminergic projections. D-LMBmapX also enables robust cross-modality and cross-dimensional registration, including precise alignment of single 2D slices to 3D references, and offers generalizable strategies for 5D analysis of diverse biomedical spatial datasets.

neuroscience↗

bioRxiv2025

Comparative molecular landscapes of immature neurons in the mammalian dentate gyrus across species reveal special features in humans

Immature dentate granule cells (imGCs) arising from adult hippocampal neurogenesis contribute to plasticity, learning and memory, but their evolutionary changes across species and specialized features in humans remain poorly understood. Here we performed machine learning-augmented analysis of published single-cell RNA-sequencing datasets and identified macaque imGCs with transcriptome-wide immature neuronal characteristics. Our cross-species comparisons among humans, monkeys, pigs, and mice showed few shared (such as DPYSL5), but mostly species-specific gene expression in imGCs that converged onto common biological processes regulating neuronal development. We further identified human-specific transcriptomic features of imGCs and demonstrated functional roles of human imGC-enriched expression of a family of proton-transporting vacuolar-type ATPase subtypes in development of imGCs derived from human pluripotent stem cells. Our study reveals divergent gene expression patterns but convergent biological processes in the molecular characteristics of imGCs across species, highlighting the importance of conducting independent molecular and functional analyses for adult neurogenesis in different species.

neuroscience↗

bioRxiv2025

Effects of One-week Intake of Different Edible Oils on the Urinary Proteome of Rats

ObjectiveTo explore the effects of different edible oils on the rat body by analyzing the changes in the urinary proteome and post-translational modifications of rats after one-week intake of olive oil, butter, lard, hydrogenated vegetable oil, and rapeseed oil. MethodsSix parallel experiments were set up using male Wistar rats. Group A served as the control group, while groups B - F were administered different edible oils. The daily intakes were calculated respectively according to the "2015 - 2020 Dietary Guidelines for Americans" and the "Dietary Guidelines for Chinese Residents". Urine samples were collected after one week and identified by label - free quantitative proteomics technology of high - performance liquid chromatography - tandem mass spectrometry (LC - MS/MS). Differentially expressed proteins and differential post - translational modifications in the urinary proteome were screened for functional analysis. ResultsAfter the intake of different types of edible oils, rats produced a large number of proteins and biological pathways related to metabolism, but there were few common differentially expressed proteins among different groups. In addition, the olive oil group and the butter group were enriched with many biological pathways related to the nervous system, and the rapeseed oil group produced more differentially expressed proteins and biological pathways related to immunity. ConclusionThe urinary proteome of rats showed significant changes after one-week intake of edible oils, and the effects of various edible oils on the rat urinary proteome were different from each other. This effect is comprehensive and multi-dimensional at the level of the rat body. The changes in post-translational modifications of the proteome were relatively small.

biochemistry↗

bioRxiv2025

APMAT analysis reveals the association between CD8 T cell receptors, cognate antigen, and T cell phenotype and persistence

Elucidating the relationships between a class I peptide antigen, a CD8 T cell receptor (TCR) specific to that antigen, and the T cell phenotype that emerges following antigen stimulation, remains a mostly unsolved problem, largely due to the lack of large data sets that can be mined to resolve such relationships. Here, we describe Antigen-TCR Pairing and Multiomic Analysis of T-cells (APMAT), an integrated experimental-computational framework designed for the high-throughput capture and analysis of CD8 T cells, with paired antigen, TCR sequence, and single-cell transcriptome. Starting with 951 putative antigens representing a comprehensive survey of the SARS-CoV-2 viral proteome, we utilize APMAT for the capture and single cell analysis of CD8 T cells from 62 HLA A*02:01 COVID-19 participants. We leverage this unique, comprehensive dataset to integrate with peptide antigen properties, TCR CDR3 sequences, and T cell phenotypes to show that distinct physicochemical features of the antigen-TCR pairs strongly associate with both T cell phenotype and T cell persistence. This analysis suggests that CD8+ T cell phenotype following antigen stimulation is at least partially deterministic, rather than the result of stochastic biological properties.

immunology↗

bioRxiv2024

Bovine Formative Embryonic Stem Cell Plasticity in Embryonic and Extraembryonic Differentiation

Bovine embryonic stem cells (bESCs) can greatly enhance understanding of bovine embryonic development and applications for disease-resistance, biomedical and zoonotic pre-clinical models. However, formative bESCs with distinct morphology and complete differentiation capacity are still unreported. We document here the generation of bESCs which are pluripotent both in vitro and in vivo, and efficiently converted into neural progenitor cells (NPCs) and primordial germ cell-like cells (PGCLCs) by direct differentiation. These cells exhibited distinct metabolic features from human and mouse ESCs and early embryos. Formative bESCs contributed to a wide range of cell types within embryonic and extraembryonic tissues after aggregating with mouse and bovine embryos. The establishment of bovine formative ESCs with dual developmental plasticity represents a milestone for agricultural biotechnology and decoding the underlying mechanism of bona fide bovine pluripotency. Summary statementGenerating bovine ESCs would greatly enhance understanding of bovine embryonic development and bioengineering of cattle for disease-resistance, biomedical and zoonotic pre-clinical models.

developmental biology↗

bioRxiv2024

Insulin resistance, cognition, and functional brain network topology in older adults with obesity

ObjectiveCross-sectional data from a sample of older adults with obesity was used to determine how peripheral and neuronal insulin resistance (IR) relate to executive function and functional brain network topology. MethodsOlder adults (n=71) with obesity but without type 2 diabetes were included. Peripheral IR was quantified by HOMA2-IR. Neuronal IR was quantified according to a proposed neuron-derived exosome-based method (NDE-IR). An executive function composite score, summed scores to the Auditory Verbal Learning Test (AVLT) trials 1-5, and functional brain networks generated from resting-state functional magnetic resonance imaging were outcomes in analyses. We used general linear models and a novel regression framework for brain network analysis to identify relationships between IR measures and brain-related outcomes. ResultsHOMA2-IR, but not NDE-IR, was negatively associated with executive function. Neither IR measure was associated with AVLT score. Peripheral IR was also related to hippocampal network topology in participants who had undergone functional neuroimaging. Neither peripheral nor neuronal IR were significantly related to network topology of the central executive network. ConclusionsCognitive and functional imaging effects were observed from HOMA2-IR, but not NDE-IR. The hippocampus may be particularly vulnerable to effects of peripheral IR.

neuroscience↗

bioRxiv2024

Changes in urinary proteins of unaffected individuals with a family history of frontotemporal dementia

Frontotemporal dementia (FTD) is a common type of neurodegenerative dementia and the primary cause of dementia in individuals under 65 years old. Current studies typically consider family members carrying relevant gene mutations as genetic risk populations, while individuals with a family history of FTD but without known mutations are sometimes included as healthy controls in research, with their potential pathophysiological changes not being fully addressed. This study performed urinary proteomics analysis on individuals with a family history of FTD but without known mutations and healthy controls to investigate whether there are differential urinary proteins and biological pathways in FTD family members who remain undiagnosed with FTD or common mutations under existing diagnostic methods. The results showed 428 significantly differentially expressed proteins (P<0.01; FC[≥]2.0 or [≤]0.5) between the two groups, among which multiple proteins have been reported to be involved in FTD or nervous system functions, particularly Progranulin (PGRN), recognized as an effective biomarker for FTD. The 146 enriched biological pathways (P<0.01) of differentially expressed proteins included multiple pathways directly related to neurons and the nervous system, such as glial cells. The differences in urinary proteins between individuals with a family history of FTD without known mutations and healthy controls indicate that urinary proteomics holds unique potential in exploring unknown pathogenic factors of FTD, providing a new perspective for deepening disease understanding and optimizing prevention and treatment strategies.

biochemistry↗

bioRxiv2024

Association between COVID-19 Disease Severity and T Cell Receptor Repertoire

During the COVID-19 pandemic, while most infected individuals experienced mild to moderate symptoms, a significant subset developed severe illness. A clinical test distinguishing between mild and severe cases could inform effective treatment strategies. Toward the latter stages of the pandemic, it became evident that vaccination or prior infection cannot entirely prevent reinfection. However, they are crucial in reducing the risk of severe disease by inducing T-cell memory. T cell receptors (TCRs), which can be obtained from human blood, serve as valuable biomarkers for monitoring T cell responses to SARS-CoV-2 infection. In this study, we investigated the associations between TCR metrics and COVID-19 severity and found significant associations. Furthermore, such associations could depend on the subset of TCRs used (e.g., TCRs from CD8+ T or CD4+ T cells) and when the TCRs were collected.

bioinformatics↗

bioRxiv2024

Dual-timescale motor circuit dynamics underlies fast head exploratory behavior and efficient locomotion

Motor systems must balance flexibility and structure to enable efficient and adaptive movements. Traditional hierarchical descending models struggle to explain the intrinsic dynamism in natural behaviors. Here, we investigate the head exploratory behavior of Caenorhabditis elegans, a minimal system capable of intricate motor patterns. Using variational mode decomposition, we identified two distinct motor dynamics: slow rhythmic bends propagating along the body and fast, phase-specific head casts influencing directional bias. Combinatorial ablations of three types of cholinergic motor neurons, in conjunction with dynamical systems analysis, revealed their distinct and overlapping roles: RMD contributes to head casts, SMD sustains bending states, SMB and SMD enable slow rhythmic bending and head-body coupling. Collectively, these neurons form a central pattern generator (CPG) driving forward locomotion. In addition, RMD subgroups displayed unique calcium dynamics correlated with rapid head movements and slow transitions between behavior states. We propose that dual-proprioceptive feedback underlies these multi-timescale dynamics, with slow feedback coordinating rhythmic bending and fast feedback shaping head casts, thereby optimizing roaming efficiency. These findings highlight how intrinsic dynamics and structured composition emerge from highly interactive low-level circuits.

neuroscience↗

bioRxiv2024

Quantitative Resolving Cell Fate in the Early Embryogenesis of Caenorhabditis elegans

The nematode Caenorhabditis elegans exhibits an invariant cell lineage during its development where the gene-molecular network that regulates the development is crucial for the biological process. While there are many molecular cell atlases describing the phenomena and key molecules involved in cell transformation, the underlying mechanisms from a systems biology perspective have received less attention. Based on an endogenous molecular-cellular theory that relates the molecular mechanisms to biological phenotypes, we constructed a model of core endogenous network to describe the early stages of embryonic development of the nematode. Different cell types and intermediate cell states during development from zygotes to founder cells correspond to the steady states of the network as a nonlinear stochastic dynamical system. Connections between steady states form a topological landscape that encompasses known developmental lineage trajectories. By regulating the expression of agents in the network, we quantitatively simulated the effects of the Wnt and Notch signaling pathway on cell fate transitions and predicted the possible trajectories of transdifferentiation of the AB cell across the lineage. The success of the current study may help advance our understanding of the fundamental principles of developmental biology and cell fate determination, offering an effective tool for quantitative analysis of cellular processes.

developmental biology↗

bioRxiv2024

Single-cell RNA-seq Reveals Early Transcriptional Programs of the Maternal to Zygote Transition in Mice and Rats

The maternal to zygote transition in mammals has been an area of intensive research over the past few decades, with an ever-changing landscape of understanding that has accompanied the rapid development of cell-profiling technology. Utilizing a full-length single cell RNA-seq protocol, we profiled mature oocytes and zygotes of mice and rats to uncover elusive transcriptomic dynamics during the maternal to zygote transition. We note the existence of early gene expression of crucial zygotic development pathways in the mouse zygote while revealing a similar chain of events occurring in the rat zygote. We further observe an increase in nascent and intergenic transcription in both species. Moreover, we find subtle but pervasive signals of differential transcript usage in genes related to epigenetic regulation occurring in both species. In terms of post-transcriptional modifications, we find distinct profiles of alternative polyadenylation between zygotes and oocytes in both species, particularly, in genes related to cell cycle processes within the zygotes of mice. Finally, although a more dynamic transcriptomic landscape exists in the mouse zygote, the rat zygote also displays similar transcriptomic features, suggesting that minor zygotic activation in rat may occur earlier than originally thought.

developmental biology↗

bioRxiv2024

GABAergic neuron dysregulation in a human neurodevelopmental model for major psychiatric disorders

"GABA dysfunction" is a major hypothesis for the biological basis of schizophrenia with indirect supporting evidence from human post-mortem brain and genetic studies. Patient-derived induced pluripotent stem cells (iPSCs) have emerged as a valuable platform for modeling psychiatric disorders, and previous modeling has revealed glutamatergic synapse deficits. Whether GABAergic synapse properties are affected in patient-derived human neurons and how this impacts neuronal network activity remain poorly understood. Here we optimized a protocol to differentiate iPSCs into highly enriched ganglionic eminence-like neural progenitors and GABAergic neurons. Using a collection of iPSCs derived from patients of psychiatric disorders carrying a Disrupted-in-Schizophrenia 1 (DISC1) mutation and their unaffected family member, together with respective isogenic lines, we identified mutation-dependent deficits in GABAergic synapse formation and function, a phenotype similar to that of mutant glutamatergic neurons. However, mutant glutamatergic and GABAergic neurons contribute differentially to neuronal network excitability and synchrony deficits. Finally, we showed that GABAergic synaptic transmission is also defective in neurons derived from several idiopathic schizophrenia patient iPSCs. Transcriptome analysis further showed some shared gene expression dysregulation, which is more prominent in DISC1 mutant neurons. Together, our study supports a functional GABAergic synaptic deficit in major psychiatric disorders.

neuroscience↗

bioRxiv2024

Overcoming immune evasion from post-translational modification of a mutant KRAS epitope to achieve TCR-engineered T cell-mediated antitumor activity

T cell receptor (TCR)-T cell immunotherapy, in which T cells are engineered to express a TCR targeting a tumor epitope, is a form of adoptive cell therapy (ACT) that has exhibited promise against various tumor types. Mutants of oncoprotein KRAS, particularly at glycine-12 (G12), are frequent drivers of tumorigenicity, making them attractive targets for TCR-T cell therapy. However, class I-restricted TCRs specifically targeting G12-mutant KRAS epitopes in the context of tumors expressing HLA-A2, the most common human HLA-A allele, have remained elusive despite evidence an epitope encompassing such mutations can bind HLA-A2 and induce T cell responses. We report post-translational modifications (PTMs) on this epitope may allow tumor cells to evade immunologic pressure from TCR-T cells. A lysine side chain-methylated KRASG12V peptide, rather than the unmodified epitope, may be presented in HLA-A2 by tumor cells and impact TCR recognition. Using a novel computationally guided approach, we developed by mutagenesis TCRs that recognize this methylated peptide, enhancing tumor recognition and destruction. Additionally, we identified TCRs with similar functional activity in normal repertoires from primary T cells by stimulation with modified peptide, clonal expansion, and selection. Mechanistically, a gene knockout screen to identify mechanism(s) by which tumor cells methylate/demethylate this epitope unveiled SPT6 as a demethylating protein that could be targeted to improve effectiveness of these new TCRs. Our findings highlight the role of PTMs in immune evasion and suggest identifying and targeting such modifications should make effective ACTs available for a substantially greater range of tumors than the current therapeutic landscape. One-sentence summaryTumor cell methylation of KRASG12V epitope in HLA-A2 permits immune evasion, and new TCRs were generated to overcome this with engineered cell therapy.

immunology↗

bioRxiv2024

Three-color single-molecule localization microscopy in chromatin

Super-resolution microscopy has revolutionized our ability to visualize structures below the diffraction limit of conventional optical microscopy and is particularly useful for investigating complex biological targets like chromatin. Chromatin exhibits a hierarchical organization with structural compartments and domains at different length scales, from nanometers to micrometers. Single molecule localization microscopy (SMLM) methods, such as STORM, are essential for studying chromatin at the supra-nucleosome level due to their ability to target epigenetic marks that determine chromatin organization. Multi-label imaging of chromatin is necessary to unpack its structural complexity. However, these efforts are challenged by the high-density nuclear environment, which can affect antibody binding affinities, diffusivity and non-specific interactions. Optimizing buffer conditions, fluorophore stability, and antibody specificity is crucial for achieving effective antibody conjugates. Here, we demonstrate a sequential immunolabeling protocol that reliably enables three-label studies within the dense nuclear environment. This protocol couples multiplexed localization datasets with a robust analysis algorithm, which utilizes localizations from one target as seed points for distance, density and multi-label joint affinity measurements to explore complex organization of all three targets. Applying this multiplexed algorithm to analyze distance and joint density reveals that heterochromatin and euchromatin are not-distinct territories, but that localization of transcription and euchromatin couple with the periphery of heterochromatic clusters. This work is a crucial step in molecular imaging of the dense nuclear environment as multi-label capacity enables for investigation of complex multi-component systems like chromatin with enhanced accuracy.

bioengineering↗

bioRxiv2024

Early to Middle Pleistocene transition shapes the evolution of human-specific mutations associated with height and basal metabolic rate

Understanding the genetic basis of modern-human-specific traits is essential for elucidating the formation of anatomically modern humans (AMHs). Here, we studied the genetic underpinnings of height and basal metabolic rate (BMR), which have undergone extensive modifications in AMHs compared to other Homo species and apes. The results revealed a significant genetic correlation between the two traits. The evolution of the variants associated with height and BMR was heavily influenced by environmental factors, marked by two bursts during the Early to Middle Pleistocene transition and one afterward, accounting for 37.4% of the inferred causal variants for height and BMR. We identified an AMH-specific mutation, rs34590044-A, which emerged around 981,916 years ago, coinciding with the first burst of variants associated with increased height and BMR. rs34590044-A upregulates the expression of ACSF3 via increasing its enhancer activity, leading to increased mitochondrial function, body length, and BMR exclusively in mice fed essential amino acids, specifically threonine-enriched diets, which are characteristic of meat-based diets. Therefore, the emergence of rs34590044-A may contribute to the shift from an herbivorous to a carnivorous diet in AMHs. Our results underscore the complex interplay between genetics and environment in shaping the crucial phenotypes and physiological traits of AMHs.

genetics↗

bioRxiv2024

CellFM: a large-scale foundation model pre-trained on transcriptomics of 100 million human cells

The rapid evolution of single-cell sequencing technologies has facilitated precise transcriptomics profiling at the single-cell level, shedding light on the intricate heterogeneity within cellular populations. Despite these advances, the inherent diversity of cells and data challenges such as noise, batch effects, and sparsity, underscores the pressing need for a unified model to learn and represent cellular states effectively. Single-cell Large Language Models (LLMs) have been crafted to bridge this gap yet exhibit limited performance on human cells. This short-fall may stem from the confounding effects of training data from diverse species, partly because of limited cells for the single species. Here, we have compiled a dataset of approximately 100 million human cells sequenced by multiple technolo-gies from human single-cell datasets with various file types deposited in public databases and websites. Leveraging these extensive data cohorts, we developed CellFM, a robust single-cell foundation model with an impressive 800 million parameters, marking an eight-fold increase over the current largest single-species model. To ensure the training of CellFM on the MindSpore AI framework from Huawei, we have integrated RetNet, a Transformer architecture variant with lin-ear complexity for a balance between efficiency and performance, serving as the backbone of our model. Our comprehensive experiments have shown that CellFM outperforms existing models across diverse applications, such as cell annotation, perturbation prediction, and gene function prediction.

bioinformatics↗

bioRxiv2024

Transcriptomic Analysis of the Spatiotemporal Axis of Oogenesis and Fertilization in C. elegans

The oocyte germline of the C. elegans hermaphrodite presents a unique model to study the formation of oocytes. However, the size of the model animal and difficulties in retrieval of specific stages of the germline have obviated closer systematic studies of this process throughout the years. Here, we present a transcriptomic level analysis into the oogenesis of C. elegans hermaphrodites. We dissected a hermaphrodite gonad into seven sections corresponding to the mitotic distal region, the pachytene, the diplotene, the early diakinesis region and the 3 most proximal oocytes, and deeply sequenced the transcriptome of each of them along with that of the fertilized egg using a single-cell RNA-seq protocol. We identified specific gene expression events as well as gene splicing events in finer detail along the oocyte germline and provided novel insights into underlying mechanisms of the oogenesis process. Furthermore, through careful review of relevant research literature coupled with patterns observed in our analysis, we attempt to delineate transcripts that may serve functions in the interaction between the germline and cells of the somatic gonad. These results expand our knowledge of the transcriptomic space of the C. elegans germline and lay a foundation on which future studies of the germline can be based upon.

developmental biology↗

bioRxiv2024

Biologically informed machine learning modeling of immune cells to reveal physiological and pathological aging process

The immune system undergoes progressive functional remodeling from neonatal stages to old age. Therefore, understanding how aging shapes immune cell function is vital for precise treatment of patients at different life stages. Here, we constructed the first transcriptomic atlas of immune cells encompassing human lifespan, ranging from newborns to supercentenarians, and comprehensively examined gene expression signatures involving cell signaling, metabolism, differentiation, and functions in all cell types to investigate immune aging changes. By comparing immune cell composition among different age groups, HLA highly expressing NK cells and CD83 positive B cells were identified with high percentages exclusively in the teenager (Tg) group, whereas CD4_CTL precursors were exclusively enriched in the supercentenarian (Sc) group. Notably, we found that the biological age (BA) of pediatric COVID-19 patients with multisystem inflammatory syndrome accelerated aging according to their chronological age (CA). Besides, we proved that inflammatory shift-myeloid abundance and signature correlate with the progression of complications in Kawasaki disease (KD). Finally, based on those age-related immune cell compositions, we developed a novel BA prediction model, PHARE (https://xiazlab.org/phare/), which applies to both scRNA-seq and bulk RNA-seq data. Overall, our study revealed changes in immune cell proportions and function associated with aging, both in health and disease, and provided a novel tool for successfully capturing features that accelerate or delay aging.

immunology↗