Biology subjects

Xu, C.

Publications and source records attributed to Xu, C..

At least 145 records · Page 8Linked to original sources

bioRxiv2024

Squidiff: Predicting cellular development and responses to perturbations using a diffusion model

Single-cell sequencing has revolutionized our understanding of cellular heterogeneity and responses to environmental stimuli. However, mapping transcriptomic changes across diverse cell types in response to various stimuli and elucidating underlying disease mechanisms remains challenging. Studies involving physical stimuli, such as radiotherapy, or chemical stimuli, like drug testing, demand labor-intensive experimentation, hindering mechanistic insight and drug discovery. Here we present Squidiff, a diffusion model-based generative framework that predicts transcriptomic changes across diverse cell types in response to environmental changes. We demonstrate Squidiffs robustness across cell differentiation, gene perturbation, and drug response prediction. Through continuous denoising and semantic feature integration, Squidiff learns transient cell states and predicts high-resolution transcriptomic landscapes over time and conditions. Furthermore, we applied Squidiff to model blood vessel organoid development and cellular responses to neutron irradiation and growth factors. Our results demonstrate that Squidiff enables in silico screening of molecular landscapes, facilitating rapid hypothesis generation and providing valuable insights for precision medicine.

bioinformatics↗

bioRxiv2024

Generating Biomedical Knowledge Graphs from Knowledge Bases, Registries, and Multiomic Data

As large clinical and multiomics datasets and knowledge resources accumulate, they need to be transformed into computable and actionable information to support automated reasoning. These datasets range from laboratory experiment results to electronic health records (EHRs). Barriers to accessibility and sharing of such datasets include diversity of content, size and privacy. Effective transformation of data into information requires harmonization of stakeholder goals, implementation, enforcement of standards regarding quality and completeness, and availability of resources for maintenance and updates. Systems such as the Biomedical Data Translator leverage knowledge graphs (KGs), structured and machine learning readable knowledge representation, to encode knowledge extracted through inference. We focus here on the transformation of data from multiomics datasets and EHRs into compact knowledge, represented in a KG data structure. We demonstrate this data transformation in the context of the Translator ecosystem, including clinical trials, drug approvals, cancer, wellness, and EHR data. These transformations preserve individual privacy. We provide access to the five resulting KGs through the Translator framework. We show examples of biomedical research questions supported by our KGs, and discuss issues arising from extracting biomedical knowledge from multiomics data.

bioinformatics↗

bioRxiv2024

PAIRWISE: Deep Learning-based Prediction of Effective Personalized Drug Combinations in Cancer

Combination therapies offer promise for improving cancer treatment efficacy and preventing recurrence. However, identifying optimal drug combinations tailored to specific cancer subtypes and individual patients is extremely challenging due to the vast number of possible combinations and tumor heterogeneity. To address this gap, we take a machine learning approach combining deep learning with transfer learning to incorporate prior scientific knowledge and predict drug synergy based on tumor-specific transcriptome profiles. This approach, called PAIRWISE, explicitly modeled synergistic effects of drug combinations in cancer cell lines or individual tumor samples based on drug chemical structures, drug targets, and transcriptomes of inferred samples. PAIRWISE outperformed competing models with an area under the receiver operating characteristic curve (AUROC) of 0.85 on held-out cancer cell lines. When applied to an independent dataset of combinations with Bruton Tyrosine Kinase inhibitors (BTKi) in Diffuse Large B Cell Lymphoma (DLBCL) cell lines, PAIRWISE accurately predicted synergistic drug combinations with an AUROC of 0.72. To further confirm the robustness of PAIRWISE predictions, we performed an in silico, patient profile-directed screen for other compounds that would synergize with BTKi in DLBCL patients, and confirmed the synergy of the predictions using a panel of eight non-Hodgkin lymphoma cell lines. These findings demonstrate the ability of PAIRWISE to nominate effective personalized drug combinations, accelerating the development of precision oncology.

bioinformatics↗

bioRxiv2024

Physics-Informed Ellipsoidal Coordinate Encoding Implicit Neural Representation for high-resolution volumetric wide-field microscopy

Wide-field fluorescence microscopy through axial scanning provides a simple way for volumetric imaging of cellular and intracellular activities, but the optical transfer function (OTF) of wide-field microscopy suffers from axial frequency deficiencies, leading to strong interference from out-of-focus fluorescence signals and reduced imaging quality. Richardson-Lucy (RL) deconvolution and its variants are commonly employed to reduce inter-plane signal interference of wide-field microscopy. However, these methods are still affected by the "missing cone" issue inherent in the OTF, compromising both the axial resolution and optical sectioning capability. Existing deep learning methods could realize high-fidelity 3D image stack restoration, but relying on high-quality paired datasets or specific assumptions about sample distributions. Here, we propose a novel method named physics-informed ellipsoidal coordinate encoding implicit neural representation (PIECE-INR), to tackle the challenges of background signal interference and resolution loss in axial scanning image stacks using the wide-field microscopy. In PIECE-INR, we integrate the wide-field fluorescence imaging model with the self-supervised INR network for high-fidelity reconstruction of 3D fluorescence data without the need of additional ground truth data for training. We further design a novel ellipsoidal coordinate encoding based on the systems OTF constraints and incorporate implicit priors derived from the physical model as the loss function into the reconstruction process. Our approach enables block-wise reconstruction of large-scale images by using localized physical information. We demonstrate state-of-the-art performance of our PIECE-INR method in volumetric imaging of live HeLa cells, large-volume C. elegans whole-embryo, and mitochondrial dynamics.

cell biology↗

bioRxiv2024

Improving diffusion-based protein backbone generation with global-geometry-aware latent encoding

Recent breakthroughs in diffusion-based generative models have prompted de novo protein design, notably in generating diverse and realistic structures. Nevertheless, while existing models either excel at unconditional generation or employ residue-wise conditioning for topological control, explorations on a holistic, top-down approach to control the overall topological arrangements is still limited. In response, we introduce TopoDiff, a diffusion-based framework augmented by a structure encoder and a latent sampler. Our model can unsupervisedly learn a compact latent representation of protein global geometry, while simultaneously integrating a diffusion module to leverage this information for controlled structure generation. In benchmark against existing models, TopoDiff demonstrates comparable performance on established metrics and exhibits an improved coverage over the fold modes of natural proteins. Moreover, our method enables versatile control at the global-geometry level for structural generation, under the assistance of which we derived a number of novel folds of mainly-beta proteins with comprehensive experimental validation.

bioengineering↗

bioRxiv2024

Homeodomain protein codes specify neuronal diversity in the first ganglion of the Drosophila visual system

The brain deploys diverse neuronal subtypes to split complex inputs into parallel channels--each tuned to distinct features--enabling rich neural processing. Yet how progenitors generate distinct but functionally related subtypes remains unknown. In the Drosophila lamina (five lamina neuron subtypes receiving photoreceptor input), we uncover the regulatory logic: a pan-class homeodomain transcription factor (HDTF), induced by Hedgehog in progenitors and maintained in all lamina neurons, drives diversification within the lamina neuron class by orchestrating a four-step program across the progenitor-to-newborn neuron transition. Specifically, it establishes progenitor identity, promotes cell-cycle exit, induces subtype-specific HDTFs, and acts as their obligate cofactor to specify distinct subtypes. Loss of subtype-specific HDTFs in newborn--but not older--neurons drives subtype-to-subtype fate conversions at molecular, morphological, and functional levels, including a contrast-to-luminance encoding switch. In the mouse retina, we find that each of the 63 amacrine, 15 bipolar, and 45 retinal ganglion cell subtypes expresses pan-class and subtype-specific HDTFs, indicating evolutionary conservation of this regulatory logic. Given the brain-wide expression of HDTFs across species, these findings convert a longstanding mystery into a testable, generalizable principle for within-class subtype diversification and lay the groundwork for subtype-precise reprogramming and cell replacement strategies.

developmental biology↗

bioRxiv2024

Unveiling allopolyploidization-driven genome duplications through progressive analysis of deep genome skimming data

Whole-genome duplication (WGD) events are widespread across the Web of Life (WoL). Given the prevalence of WGDs in the polyploid Prunus (Rosaceae), this economically- and agriculturally-important angiosperm lineage provides an excellent model for exploring this mode of reticulation. We used the polyploid Prunus to demonstrate a progressive strategy for analyzing Deep Genome Skimming (DGS) data in the presence of WGDs. Phylogenomic discordance analyses indicated that allopolyploidization, rather than Incomplete Lineage Sorting (ILS), played a dominant role in the origin and dynamics of polyploid Prunus. This study underscores how a progressive strategy to identify WGD events at different depths in a phylogenetic tree reveals the nuances of evolutionary mechanisms driving allopolyploidization. We inferred that the continued uplift of the Himalayas from the Middle to Late Miocene drove the rapid diversification of the Eastern Asia endemic Maddenia clade, by facilitating frequent hybridization and allopolyploidization, specifically introgression between the Himalayas-Hengduan and the Central-Eastern China clades.

systems biology↗

bioRxiv2024

Transposable elements are prevalent vectors of transgenerational epigenetic inheritance in nature

Loss of DNA methylation over transposable elements (TEs) can affect neighboring genes and be epigenetically inherited in plants, yet the determinants and significance of this additional system of inheritance are unknown. Here, we demonstrate at thousands of TE loci across the Arabidopsis thaliana genome, that experimentally-induced hypomethylation can be transmitted transgenerationally and reveal the role of small RNAs derived from related copies in counteracting this transmission. Using data from >700 strains collected worldwide, we uncover natural hypomethylation at hundreds of the same TE loci, often situated near stress-responsive genes. Like their experimental counterparts, most natural epivariants we tested can be inherited without DNA sequence changes and are therefore bona fide epialleles, although genetic factors modulate their recurrence or persistence. Crucially, we demonstrate that TE-mediated epiallelic variation associated with differential gene expression is generally causal and may be target of selection in specific environments, thus establishing its importance in nature.

genomics↗

bioRxiv2024

Unveil the Molecular Interplay between Aminoglycosides and Pseudouridine in IRES Translation

Eukaryotic ribosomes are enriched with pseudouridine, particularly at the functional centers targeted by antibiotics. Here we investigated the roles of pseudouridine in aminoglycoside-mediated translation inhibition by comparing the structural and functional properties of the wild-type ribosomes and those lacking pseudouridine (cbf5-D95A). We showed that the cbf5-D95A ribosomes have decreased thermostability and high sensitivity to aminoglycosides. When presented with an internal ribosome entry site (IRES) RNA, elongation factor eEF2, GTP, sordarin, hygromycin B preferentially binds to the cbf5-D95A ribosomes during initiation by blocking eEF2 binding and stalls the ribosomes in a non-rotated conformation, further hindering translocation. Hygromycin B binds to the inter-subunit bridge B2a that is known to be sensitive to pseudouridine, revealing a functional link between pseudouridine and aminoglycoside inhibition. Our results suggest that pseudouridine enhances both thermostability and conformational fitness of the ribosomes, thereby influencing their susceptibility to aminoglycosides. HighlightsO_LILoss of pseudouridine increases cell sensitivity to aminoglycosides C_LIO_LIPseudouridine enhances ribosome thermostability C_LIO_LIHygromycin B competes with eEF2 for the non-rotated ribosome C_LIO_LIHygromycin B deforms the codon-anticodon duplex C_LI

biochemistry↗

bioRxiv2024

Intra-hypothalamic circuit orchestrates β-endorphin release following coital ejaculation in male mice

Survey-based evidence suggests that men experience a distinct post-ejaculation affective state1,2, marked by intense pleasure sometimes compared to the euphoric rush from intravenous injection of opioid drugs such as heroin3. However, the intrinsic neural circuit mechanisms underlying the ejaculation-triggered affective state remain unclear. Here, we discovered that Calbindin1-expressing (Calb1+) neurons in the preoptic area (POA) of the hypothalamus, an evolutionarily conserved regulatory region for male mating behavior4, are specifically activated during ejaculation in male mice. Inhibiting POA Calb1+ neurons prolongs mating and delays ejaculation. Importantly, POA Calb1+ neurons transmit the ejaculation signal and activate proopiomelanocortin-expressing (Pomc+) neurons in the arcuate nucleus of the hypothalamus, which show robust and sustained activity lasting for tens of seconds, specifically upon ejaculation. This activity is accompanied by elevated levels of {beta}-endorphins5, opioid peptides secreted by Pomc+ neurons, post-ejaculation in male mice. Optogenetic activation of Pomc+ neurons increases {beta}-endorphins levels and conditioned placed preference, similar to ejaculation. Conversely, intracerebroventricular (i.c.v.) infusion of drugs blocking Pomc neuropeptides signaling eliminates ejaculation-conditioned place preference. Collectively, these results elucidate an intra-hypothalamic circuit from POA Calb1+ neurons to arcuate Pomc+ neurons that coordinate {beta}-endorphin release with ejaculation, shedding light on the neurobiological basis of the post-ejaculation affective state.

neuroscience↗

bioRxiv2024

Dimensionality reduction simplifies synaptic partner matching in an olfactory circuit

The distribution of postsynaptic partners in three-dimensional (3D) space presents complex choices for a navigating axon. Here, we discovered a dimensionality reduction principle in establishing the 3D glomerular map in the fly antennal lobe. Olfactory receptor neuron (ORN) axons first contact partner projection neuron (PN) dendrites at the 2D spherical surface of the antennal lobe during development, regardless of whether the adult glomeruli are at the surface or interior of the antennal lobe. Along the antennal lobe surface, axons of each ORN type take a specific 1D arc-shaped trajectory that precisely intersects with their partner PN dendrites. Altering axon trajectories compromises synaptic partner matching. Thus, a 3D search problem is reduced to 1D, which simplifies synaptic partner matching and may generalize to the wiring process of more complex brains.

developmental biology↗

bioRxiv2024

Selective regulation of IFN-γ and IL-4 co-producing unconventional T cells by purinergic signalling

Unconventional T cells, including mucosal-associated invariant T (MAIT), natural killer T (NKT), and gamma-delta T ({gamma}{delta}T) cells, comprise distinct T-bet+, IFN-{gamma}+ and ROR{gamma}t+, IL-17+ subsets which play differential roles in health and disease. NKT1 cells are susceptible to ARTC2-mediated P2X7 receptor (P2RX7) activation, but the effects on other unconventional T-cell types are unknown. Here, we show that MAIT, {gamma}{delta}T, and NKT cells express P2RX7 and are sensitive to P2RX7-mediated cell death. Mouse peripheral T-bet+ MAIT1, {gamma}{delta}T1, and NKT1 cells, especially in liver, co-express ARTC2 and P2RX7, which can be further upregulated by retinoic acid. Blocking ARTC2 or inhibiting P2RX7 protected MAIT1, {gamma}{delta}T1, and NKT1 cells from cell death, enhanced their survival in vivo, and increased the number of IFN-{gamma}-secreting cells without affecting IL-17 production. Importantly, this revealed the existence of IFN-{gamma} and IL-4 co-producing unconventional T-cell populations normally lost upon isolation due to ARTC2/P2RX7-induced death. Administering extracellular NAD in vivo activated this pathway, depleting P2RX7-sensitive unconventional T cells. Our study reveals ARTC2/P2RX7 as a common regulatory axis modulating the unconventional T-cell compartment, affecting the viability of IFN-{gamma}- and IL-4-producing T cells, offering important insights to facilitate future studies into how these cells can be regulated in health and disease.

immunology↗

bioRxiv2024

Unraveling the Web of Life: Incomplete lineage sorting and hybridization as primary mechanisms over polyploidization in the evolutionary dynamics of pear species

In contrast to the traditional Tree of Life (ToL) paradigm, the Web of Life (WoL) model provides a more nuanced and precise depiction of organismal phylogeny, particularly considering the prevalent incongruence observed among gene/species trees. The lack of a generalized pipeline for teasing apart potential evolutionary mechanisms--such as Incomplete Lineage Sorting (ILS), hybridization, introgression, polyploidization, and Whole-Genome Duplication--poses significant challenges to the delineation of the WoL. The pear genus Pyrus, characterized by extensive hybridization events, serves as an excellent model for investigating the WoL. This study introduces a novel Step-by-Step Exclusion (SSE) approach to deciphering the complexities inherent in the WoL. Our findings indicate: 1) ILS, rather than polyploidization, is identified as the primary driver behind the origin of Pyrus from the arid regions of the Himalayas-Central Asia; 2) the two subgenera of Pyrus have independent evolutionary trajectories, facilitated by the geographical barriers that arose via the uplift of the Tibetan Plateau and increased aridity in Central Asia; 3) ILS and hybridization have facilitated the diversification of Oriental pears, while hybridization alone has driven the reticulate evolution of Occidental pears; 4) the establishment of the Silk Road during the Han Dynasty acted as a conduit for genetic exchange between Occidental and Oriental pears. The novel SSE approach provides a universally applicable framework for investigating evolutionary mechanisms defining the WoL paradigm.

systems biology↗

bioRxiv2024

Label-free multiphoton imaging reveals volumetric shifts across development in sensory-related brain regions of a miniature transparent vertebrate

Animals integrate information from different sensory modalities as they mature and perform increasingly complex behaviors. This may parallel differential investment in specific brain regions depending on the demands of changing sensory inputs. To investigate developmental changes in the volume of canonical sensory integration brain regions, we used third harmonic generation imaging for morphometric analysis of forebrain and midbrain regions from 5 to 90 days post fertilization (dpf) in Danionella dracula, a transparent, miniature teleost fish whose brain is optically accessible throughout its lifespan. Relative to whole brain volume, increased volume or investment in telencephalon, a higher order sensory integration center, and torus longitudinalis (TL), a midbrain visuomotor integration center, is relatively consistent from 5 to 30 dpf, until it increases at 60 dpf, followed by another increase at 90 dpf, as animals reach adulthood. In contrast, investment in midbrain optic tectum (TeO), a retinal-recipient target, progressively decreases from 30-90 dpf, whereas investment is relatively consistent across all stages for the midbrain torus semicircularis (TS), a secondary auditory and mechanosensory lateral line center, and the olfactory bulb (OB), a direct target of the olfactory epithelium. In sum, increased investment in higher order integration centers (telencephalon, TL) occurs as juveniles reach adulthood and exhibit more complex cognitive tasks, whereas investment in modality-dominant regions occurs in earlier stages (TeO) or is relatively consistent across development (TS, OB). Complete optical access throughout Danionellas lifespan provides a unique opportunity to investigate how changing brain structure over development correlates with changes in connectivity, microcircuitry, or behavior.

neuroscience↗

bioRxiv2024

A multiomic atlas of human early skeletal development

Bone and joint formation in the developing skeleton rely on co-ordinated differentiation of progenitors in the nascent developing limbs and joints. The cell states, epigenetic processes and key regulatory factors underlying their lineage commitment to osteogenic and other mesenchymal populations during ossification and joint formation remain poorly understood and are largely unexplored in human studies. Here, we apply paired single-nuclei transcriptional and epigenetic profiling of 336,000 droplets, in addition to spatial transcriptomics, to construct a comprehensive atlas of human bone, cartilage and joint development in the shoulder, hip, knee and cranium from 5 to 11 post-conception weeks. Spatial mapping of cell clusters to our highly multiplexed in situ sequencing (ISS) data using our newly developed tool ISS-Patcher revealed new cellular mechanisms of zonation during bone and joint formation. Combined modelling of chromatin accessibility and RNA expression allowed the identification of the transcriptional and epigenetic regulatory landscapes that drive differentiation of mesenchymal lineages including osteogenic and chondrogenic lineages, and novel chondrocyte cell states. In particular, we define regionally distinct limb and cranial osteoprogenitor populations and trajectories across the fetal skeleton and characterise differential regulatory networks that govern intramembranous and endochondral ossification. We also introduce SNP2Cell, a tool to link cell-type specific regulatory networks to numerous polygenic traits such as osteoarthritis. We also conduct in silico perturbations of genes that cause monogenic craniosynostosis and implicate potential pathogenic cell states and disease mechanisms involved. This work forms a detailed and dynamic regulatory atlas of human fetal skeletal maturation and advances our fundamental understanding of cell fate determination in human skeletal development.

developmental biology↗

bioRxiv2024

Genomic evolution reshapes cell type diversification in the amniote brain

Over 320 million years of evolution, amniotes have developed complex brains and cognition through largely unexplored genetic and gene expression mechanisms. We created a comprehensive single-cell atlas of over 1.3 million cells from the telencephalon and cerebellum of turtles, zebra finches, pigeons, mice, and macaques, employing single-cell resolution spatial transcriptomics to validate gene expression patterns across species. Our study revealed significant species-specific variations in cell types, highlighting their conservation and diversification in evolution. We found pronounced differences in telencephalon excitatory neurons (EX) and cerebellar cell types between birds and mammals. Birds predominantly express SLC17A6 in EX, whereas mammals expressed SLC17A7 in neocortex and SLC17A6 elsewhere, possibly due to loss of SLC17A7 function loss in birds. Additionally, we identified a novel bird-specific Purkinje cell subtype (SVIL+), implicating the LSD11/KDM1A pathway in learning and circadian rhythms, and related numerous positively selected genes in birds, suggesting an evolutionary optimization of cerebellar functions for ecological and behavioral adaptation. Our findings elucidate the complex interplay between genetic evolution and environmental adaptation, underscoring the role of genetic diversification in the development of specialized cell types across amniotes.

evolutionary biology↗

bioRxiv2024

Bin2cell reconstructs cells from high resolution Visium HD data

SummaryVisium HD by 10X Genomics is the first commercially available platform capable of capturing full scale transcriptomic data paired with a reference morphology image from archived FFPE blocks at sub-cellular resolution. However, aggregation of capture regions to single cells poses challenges. Bin2cell reconstructs cells from the highest resolution data (2 m bins) by leveraging morphology image segmentation and gene expression information. It is compatible with established Python single cell and spatial transcriptomics software, and operates efficiently in a matter of minutes without requiring a GPU. We demonstrate improvements in downstream analysis when using the reconstructed cells over default 8 m bins on mouse brain and human colorectal cancer data. Availability and ImplementationBin2cell is available at https://github.com/Teichlab/bin2cell, along with documentation and usage examples, and can be installed from pip. Probe design functionality is available at https://github.com/Teichlab/gene2probe Contactny1@sanger.ac.uk, st9@sanger.ac.uk Supplementary informationSupplementary data are available online.

bioinformatics↗

bioRxiv2024

Spatially Resolved Tumor Ecosystems and Cell States in Gastric Adenocarcinoma Progression and Evolution

Gastric cancer (GC) is a major cause of global cancer mortality with high heterogeneity levels. To explore geospatial interactions in tumor ecosystems, we integrated 1,563 spatial transcriptomic regions-of-interest (ROIs) with 152,423 single-cell expression profiles across 130 GC samples from 70 patients. We observed pervasive expression-based intratumor heterogeneity, recapitulating tumor progression through spatially localized and functionally ordered subgroups with specific immune microenvironments and immune checkpoint profiles. Evolutionary phylogenetic analysis revealed two different evolutionary trajectories (branched evolution and diaspora evolution) associated with distinct molecular subtypes, clinical prognoses, stromal neighborhoods including VWF+ ACKR1+ endothelial cells, and genetic drivers such as SOX9. Spatial analysis of tumor-stromal interfaces across multiple GCs highlighted new ecosystem states not attributable to mere tumor/stroma admixture, landmarked by increased GREM1 expression. Our results provide insights into how the cellular ecosystems of individual GCs are sculpted by tumor intrinsic and extrinsic selective pressures, culminating in individualized patient-specific cancer cartographies.

cancer biology↗