Biology subjects

Tian, L.

Publications and source records attributed to Tian, L..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

A versatile cohesion manipulation system reveals CENP-A dysfunction accelerates female reproductive age-related egg aneuploidy.

Female reproductive aging is accompanied by a dramatic rise in the incidence of egg aneuploidy. Premature loss of chromosome cohesion proteins and untimely separation of chromosomes is thought to underly high rates egg aneuploidy during maternal aging. However, because chromosome cohesion loss occurs gradually over female reproductive lifespan and cytoskeletal defects alone can predispose eggs to chromosomal abnormalities, the root causes of exponential rise in egg aneuploidy at advanced reproductive ages remain a mystery. Here, we applied high-resolution live imaging to visualize for the first time cohesion protein dynamics underpinning meiotic chromosome segregation. To discover proteins whose dysfunction accelerates aneuploidies associated with female reproductive aging, we innovated the first experimental system in which chemically induced cohesion reduction rapidly triggers aging-like chromosomal abnormalities in young eggs. By integrating this direct cohesion manipulation system with quantitative high-resolution microscopy and targeted protein degradation tools, we identified the centromeric protein CENP-A as a new factor whose aging-like depletion causes a dramatic rise in premature separation of sister chromatids. Our work illuminates cohesion loss-independent origins of age-related egg aneuploidy and provides new avenues to discover therapeutic targets for extending the female reproductive lifespan.

cell biology↗

bioRxiv2025

Graph-based Contrastive Learning Enables Unified Integration and Niche Transfer Across Single-Cell and Spatial Multi-Omics

The rapid growth of single-cell and spatial omics has outpaced computational methods capable of unifying these data into a cohesive framework for tissue atlas construction and cross-sample analysis. A critical bottleneck lies in the inability of existing tools to co-embed cells from diverse technologies--spanning transcriptomics, epigenomics, and proteomics--into a shared reference space while preserving spatial architecture and molecular specificity. Here, we present Garfield (Graph-based Contrastive Learning Enables Fast Single-Cell Embedding), a geometric deep-learning framework that addresses these challenges through spatially or molecularly aware cell embedding. Leveraging a graph contrastive learning framework, Garfield learns a shared embedding space for data generated by diverse technologies, enabling seamless construction and querying of spatial reference atlases. Our results show that Garfield consistently outperforms state-of-the-art benchmark models in identifying spatial niches across multiple datasets. We further demonstrate Garfields versatility by applying it to multi-modal spatial data, including gene expression and chromatin accessibility, where it successfully identifies distinct niches in the mouse brain. Notably, Garfield reveals tumor microenvironment heterogeneity in non-small cell lung cancer and breast cancer, uncovered conserved, barrier-like immune niches at tumor margins orchestrating CD80-mediated T cell-B cell-dendritic cell interactions and IFN-/B cell activation pathways, forming spatially coordinated immune surveillance hubs. These findings underscore Garfields potential to advance spatial omics research by offering a robust, scalable solution for integrating and interpreting complex spatial data across diverse tissue types and modalities.

bioinformatics↗

bioRxiv2025

Top-down control of the descending pain modulatory system drives placebo analgesia

In placebo analgesia, prior experience and expectations lead to pain suppression by the administration of an inert substance, but causal evidence for its neural basis is lacking. To identify the underlying neural circuits, we reverse-translated a conditioned placebo protocol from humans to mice. Surprisingly, the placebo effect suppresses both nociception and unconditioned emotional-motivational pain-related behavior. Descending pain modulatory neurons in the periaqueductal gray (PAG) are critical for both morphine and placebo antinociception. The placebo effect depends on input to the PAG from the medial prefrontal and anterior cingulate cortices, but not anterior insular cortex. Conditioning enhances noxious stimulus-evoked endogenous opioid release in the PAG to produce analgesia. Our results suggest that cortical control of the descending pain modulatory system (DPMS) is gated by rapid endogenous opioid signaling in the PAG during placebo trials. This study bridges clinical and preclinical research, establishing a central role for the DPMS in placebo analgesia.

neuroscience↗

bioRxiv2025

Spatial Profiling Reveals Equivalence-Derived Molecular Signatures of Brain Mimicry and Adaptation in Breast Cancer Brain Metastases

Brain metastases (BrMets), common for advanced-stage breast cancer patients, are associated with poor median survival and accompanied by severe neurologic decline. Halting the progression of breast cancer brain metastases (BCBMs) may require modulation of the tumor microenvironment (TME), yet little is known about the impact of the primary breast TME on brain tropism, or how, once there, metastatic breast cancer cells coexist with brain-resident cells (e.g., neurons and glia). Traditionally, studies in this space have focused on differential expression analysis, overlooking potential insights gained from investigating genes with equivalent expression between groups. This is particularly crucial in distant metastasis, where tumor cells may co-opt the transcriptional programs of the host organ (e.g., brain) to facilitate successful seeding and outgrowth. Prior to our work, no computational framework existed to determine biologically-relevant equivalent gene expression. To resolve molecular mechanisms of BCBM enabled by metastatic cancer cells and/or resident brain cells, we leveraged Nanostring GeoMx to perform spatially-resolved transcriptomic profiling on 235 patient-derived tissue cores from BCBM (including adjacent normal brain), primary invasive breast cancers, and normal (non-cancer) brain; analyzing 18,677 RNAs in 450 areas of interest (AOIs). We introduce the "Equivalent Expression Index" a highly specific and accurate algorithm that identifies statistically significant "Equivalently-Expressed Genes". This method facilitated the identification of molecular remodeling and mimicry genes within tissue-specific TMEs. By integrating differential expression analysis with the Equivalent Expression Index, we discovered multiple novel gene signatures associated with BCBM and primary tumor brain-metastatic potential. We demonstrate that the Equivalent Expression Index is a powerful tool to uncover shared gene expression programs representing the adaptation of metastatic cells and brain-resident cells to the BCBM microenvironment.

cancer biology↗

bioRxiv2025

Absolute measurement of fast and slow neuronal signals with fluorescence lifetime photometry at high temporal resolution

The concentrations of extracellular and intracellular signaling molecules, such as dopamine and cAMP, change over both fast and slow timescales and impact downstream pathways in a cell-type specific manner. Fluorescence sensors currently used to monitor such signals in vivo are typically optimized to detect fast, relative changes in concentration of the target molecule. They are less well suited to detect slowly-changing signals and rarely provide absolute measurements of either fast and slow signaling components. Here, we developed a system for fluorescence lifetime photometry at high temporal resolution (FLIPR) that utilizes frequency-domain analog processing to measure the absolute fluorescence lifetime of genetically-encoded sensors at high speed but with long-term stability and picosecond precision in freely moving mice. We applied FLIPR to investigate dopamine signaling in two functionally distinct regions in the striatum, the nucleus accumbens core (NAC) and the tail of striatum (TOS). We observed higher tonic dopamine levels at baseline in the TOS compared to the NAC and detected differential and dynamic responses in phasic and tonic dopamine to appetitive and aversive stimuli. Thus, FLIPR enables simple monitoring of fast and slow time-scale neuronal signaling in absolute units, revealing previously unappreciated spatial and temporal variation even in well-studied signaling systems.

neuroscience↗

bioRxiv2025

Transfer learning applied in predicting small molecule bioactivity

Despite over a half-century of effort by computational chemists, developing accurate empirical QSAR (Quantitative Structure-Activity Relationships) models for predicting bioactivity directly from chemical structure has remained elusive. The difficulties have been especially pronounced for virtual screening, finding new active compounds substantially different from the known chemical matter used to train the models. Recent breakthroughs have been achieved by employing transfer of learning across huge numbers of bioactivity assays, greatly increasing the amount and diversity of chemical and biological information that informs each model. An early example was Profile-QSAR (pQSAR), a 2-level stacked model, where level-2 PLS (Partial Least Squares) models characterize compounds by their profile of bioactivity predictions from individual level-1 random forest regression QSAR models built on up to 10,000+ other assays. This study introduces metaNN, a meta-learner that trains deep neural networks (DNN) for each individual assay initialised from a well-generalized consensus DNN optimized across all assays. Comparison of the results suggested that while Profile-QSAR and metaNN perform similarly overall, metaNN works slightly better for smaller assays which were well-predicted by the consensus DNN; whereas pQSAR struggled more with smaller assays, due to the large number of level-1 models but was less sensitive to similarity to an overall consensus. An ensemble average of both methods combined the strengths of each, working better than either alone. The similar performance of the 2 largely orthogonal algorithms raises questions about whether we are approaching a limit of prediction accuracy in transfer learning, for this application scenario.

bioinformatics↗

bioRxiv2025

Vesicular glutamate release is necessary for neural tube formation

The brain and spinal cord originate from a neural tube that is preceded by a flat structure known as the neural plate during early embryogenesis. In humans, failure of the neural plate to convert into a tube by the fourth week of pregnancy leads to neural tube defects (NTDs), birth defects with serious neurological consequences. The signaling mechanisms governing the process of neural tube morphogenesis are unclear. Here we show that in Xenopus laevis embryos, neural plate cells release glutamate during neural plate folding in a Ca2+ and vesicular glutamate transporter-1 (VGluT1)-dependent manner. Vesicular release of glutamate elicits Ca2+ transients in neural plate cells that correlate with activation of Erk1/2. Knocking down or out VGluT1 leads to NTDs through increased expression of Sox2, neural stem cell transcription factor, and neural plate cell proliferation. Exposure during early pregnancy to neuroactive drugs that disrupt these signaling mechanisms might increase the risk of NTDs in offspring.

neuroscience↗

bioRxiv2025

Convergent state-control of endogenous opioid analgesia

Pain is a dynamic and nonlinear experience shaped by injury and contextual factors, including expectations of future pain or relief1. While {micro} opioid receptors are central to the analgesic effects of opioid drugs, the endogenous opioid neurocircuitry underlying pain and placebo analgesia remains poorly understood. The ventrolateral column of the posterior periaqueductal gray is a critical hub for nociception and endogenous analgesia mediated by opioid signaling2. However, significant gaps remain in understanding the cell-type identities, the sub-second neural dynamics involved in pain modulation, the role of endogenous peptide neuromodulators, and the contextual factors influencing these processes. Using spatial mapping with single-nuclei RNA sequencing of pain-active neurons projecting to distinct long-range brain targets, alongside cell type-specific and activity-dependent genetic tools for in vivo optical recordings and modulation of neural activity and opioid peptide release, we identified a functional dichotomy in the ventrolateral periaqueductal gray. Neurons expressing {micro} opioid receptors encode active nociceptive states, whereas enkephalin-releasing neurons drive pain relief during recovery from injury, in response to learned fear predictions, and during placebo analgesia. Finally, by leveraging the functional effects of placebo analgesia, we used direct optogenetic activation of vlPAG enkephalin neurons to drive opioid peptide release, resulting in a robust reduction in pain. These findings show that diverse need states converge on a shared midbrain circuit that releases endogenous opioids with high spatiotemporal precision to suppress nociceptive activity and promote analgesia.

neuroscience↗

bioRxiv2025

Hypoxia-Induced Active Dynamics Promotes Early Tumorigenesis

Understanding early tumor formation provides insights for cancer prevention. However, in vivo studies focus on later stages, leaving initial tumorigenesis poorly understood. Hypoxia is a key microenvironmental factor in cancer, yet its impact on single-cell tumor initiation and dynamics remains unclear. To address this, we developed an integrated live-imaging platform for hypoxic conditions, enabling first direct observation of 3D tumor spheroid development from a single cell. We show hypoxia accelerates tumorigenesis. Beyond growth, directional movement promotes spheroid fusion. This is driven by optimized actin polymerization and cell-cell adhesion. Hypoxia induces specialized, fusion-competent cells with outstretched F-actin and tiny nuclei that bridge spheroids. Concurrently, hypoxia triggers genetic instability, evidenced by tiny nuclei and aneuploidy. The interplay between dynamic and genetic instability optimizes spheroid mechanical properties, creating a positive feedback loop fuels proliferation. Our findings offer insight into hypoxias role in early tumorigenesis and highlight potential of targeting dynamic-genetic balance for prevention. Statement of SignificanceHypoxia accelerates early tumorigenesis by promoting directional 3D tumor spheroid fusion via optimized actin dynamics and mechanical balance, while inducing micronuclei formation and aneuploidy-linked genetic instability, forming a positive feedback loop that boosts proliferation and malignant progression.

cancer biology↗

bioRxiv2024

A Systematic Comparison of Single-Cell Perturbation Response Prediction Models

Predicting single-cell transcriptional responses to perturbations is central to dissecting gene regulation and accelerating therapeutic design, yet the field lacks a rigorous, task-spanning assessment of model behavior. We present a large-scale benchmark of 13 representative methods and baselines across 25 datasets spanning diverse perturbation modalities and species, including two primary immune-cell drug-response resources. We evaluated three core tasks--generalization to unseen single-gene perturbations, prediction of combinatorial interactions, and transfer across cell types--using 24 metrics covering expression-level accuracy, relative changes, differential expression recovery, and distributional similarity. Across tasks, performance depended strongly on perturbation effect size and evaluation perspective: expression-level agreement was highest for small-effect perturbations resembling controls, whereas delta- and DE-based metrics improved with larger effects, providing clearer signals. Models shared a conservative bias, with fine-tuned foundation models compressing variance and underestimating synergistic effects in combinations. PerturbNet showed superior recovery of DE signatures in Tasks 1 and 2, while no method consistently generalized across cell types in Task 3, where biological consistency dominated outcomes. This benchmark establishes current methodological limits, clarifies that different metrics probe distinct biological signals rather than redundant summaries of the same prediction problem, and provides a foundation for developing virtual-cell models that more faithfully capture heterogeneous perturbation responses. Teaser: A large-scale benchmark reveals strengths and limits of models predicting single-cell perturbation responses.

bioinformatics↗

bioRxiv2024

Multiomic foundation model predicts epigenetic regulation by zero-shot

Deciphering cell type-specific perturbation effects on genes and cellular states demands considerable experimental resources. To overcome this challenge, we propose Perturbation Transformer (PertFormer), a foundation model to uncover functional and regulatory mechanisms through interpretable in silico perturbation process. PertFormer comprises 3 billion parameters pretrained on both bulk and single-cell datasets covering 9 types of multiomics (55 billion bp bulk multiomics and the largest-to-date 1.5 billion paired multiomic samples from 1 million single cells), capturing regulation of 300 kb around every genic region. PertFormer enables zero-shot prediction of functional perturbations and cell fate dynamics, outperforming existing methods by 20.9%-480.2%. PertFormer identifies novel tumor treatment targets, validated experimentally. The generalization capabilities of PertFormer have the potential to accelerate the discovery of biological and clinical targets.

genomics↗

bioRxiv2024

Rapid riparian ecosystem recovery in low-latitudinal North China following the end-Permian mass extinction

The greatest mass extinction at the end of the Permian, ca. 252 million years ago, led to a tropical dead zone on land and sea. The speed of recovery of life has been debated, whether fast or slow, and terrestrial ecosystems are much less understood than marine. Here, we show fast reestablishment of riparian ecosystems in low-latitude North China as little as [~]2 million years after the end-Permian mass extinction. The initial ichnoassemblages in shallow lacustrine and fluvial facies of late Smithian age are monospecific, devoid of infaunalization, with apparent size reduction. In the following Spathian, relatively complex, multi-level, structured riverain ecosystems had been rebuilt including medium-sized carnivores, plant stems, root traces, increased ichnological complexity, and significantly increased infaunalization. Specifically, burrowing behavior had re-emerged as a key life strategy not only to minimize stressful climatic conditions, but possibly to escape predation.

paleontology↗

bioRxiv2024

Hunger modulates exploration through suppression of dopamine signaling in the tail of striatum

Caloric depletion leads to behavioral changes that help an animal find food and restore its homeostatic balance. Hunger increases exploration and risk-taking behavior, allowing an animal to forage for food despite risks; however, the neural circuitry underlying this change is unknown. Here, we characterize how hunger restructures an animals spontaneous behavior as well as its directed exploration of a novel object. We show that hunger-induced changes in exploration are accompanied by and result from modulation of dopamine signaling in the tail of the striatum (TOS). Dopamine signaling in the TOS is modulated by internal hunger state through the activity of agouti-related peptide (AgRP) neurons, putative "hunger neurons" in the arcuate nucleus of the hypothalamus. These AgRP neurons are poly-synaptically connected to TOS-projecting dopaminergic neurons through the lateral hypothalamus, the central amygdala, and the periaqueductal grey. We thus delineate a hypothalamic-midbrain circuit that coordinates changes in exploration behavior in the hungry state.

neuroscience↗

bioRxiv2024

Distribution of haploid chromosomes into separate nuclei in two pathogenic fungi

The presence of nuclei defines eukaryotes, enabling compartmentalization of macromolecules and cellular regulation. Inside the nucleus, chromosome numbers vary greatly across organisms, both in terms of ploidy status and haploid chromosome number. For cells harboring multiple nuclei as in many fungal mycelia and animal muscle cells, each healthy nucleus is traditionally believed to carry at least one haploid set of chromosomes. Abnormal chromosome numbers in nuclei are often associated with aging, diseases such as cancer, developmental disorders or lethality. Here we report a surprising discovery that chromosomes in haploid cells of the fungal species Sclerotinia sclerotiorum and Botrytis cinerea are segregated into separate nuclei, with each nucleus containing only a fraction of the chromosomes. This is the first report of eukaryotic cells that partition chromosome subsets into distinct nuclei, bringing new questions and opening fresh avenues for chromosome biology.

microbiology↗

bioRxiv2024

Spatiotemporal lineage tracing reveals the dynamic spatial architecture of tumor growth and metastasis

Tumour progression is driven by dynamic interactions between cancer cells and their surrounding microenvironment. Investigating the spatiotemporal evolution of tumours can provide crucial insights into how intrinsic changes within cancer cells and extrinsic alterations in the microenvironment cooperate to drive different stages of tumour progression. Here, we integrate high-resolution spatial transcriptomics and evolving lineage tracing technologies to elucidate how tumour expansion, plasticity, and metastasis co-evolve with microenvironmental remodelling in a Kras;p53-driven mouse model of lung adenocarcinoma. We find that rapid subclonal expansion contributes to a hypoxic, immunosuppressive, and fibrotic microenvironment that is associated with the emergence of pro-metastatic cancer cell states. Furthermore, metastases arise from spatially-confined subclones of primary tumours and remodel the distant metastatic niche into a fibrotic, collagen-rich microenvironment. Together, we present a comprehensive dataset integrating spatial assays and lineage tracing to elucidate how sequential changes in cancer cell state and microenvironmental structures cooperate to promote tumour progression.

cancer biology↗

bioRxiv2024

In vivo two-photon FLIM resolves photosynthetic properties of maize bundle sheath cells

Maize (Zea mays L.) performs highly efficient C4 photosynthesis by dividing photosynthetic metabolism between mesophyll and bundle sheath cells. In vivo physiological measurements are indispensable for C4 photosynthesis research as any isolated cells or sectioned leaf often show interrupted and abnormal photosynthetic activities. Yet, direct in vivo observation regarding bundle sheath cells in the delicate anatomy of the C4 leaf is still challenging. In the current work, we used two-photon fluorescence-lifetime imaging microscopy (two-photon-FLIM) to access the photosynthetic properties of bundle sheath cells on intact maize leaves. The results provide spectroscopic evidence for the diminished total PSII activity in bundle sheath cells at its physiological level and show that the single PSIIs could undergo charge separation as causal. We also report an acetic acid-induced chlorophyll fluorescence quenching on intact maize leaves, which might be a physiological state related to the nonphotochemical quenching mechanism.

physiology↗

bioRxiv2024

Neurovascular Impulse Response Function (IRF) during spontaneous activity differentially reflects intrinsic neuromodulation across cortical regions

Ascending neuromodulatory projections from deep brain nuclei generate internal brain states that differentially engage specific neuronal cell types. Because neurovascular coupling is cell-type specific and neuromodulatory transmitters have vasoactive properties, we hypothesized that the impulse response function (IRF) linking spontaneous neuronal activity with hemodynamics would depend on neuromodulation. To test this hypothesis, we used optical imaging to measure (1) release of neuromodulatory transmitters norepinephrine (NE) or acetylcholine (ACh), (2) Ca2+ activity of local cortical neurons, and (3) changes in hemoglobin concentration and oxygenation across the dorsal surface of cerebral cortex during spontaneous neuronal activity in awake mice. A canonical convolution model with a global, stationary IRF (i.e., the convolution kernel) describing evolution of total hemoglobin (HbT, reflective of dilation dynamics) with respect to Ca2+, resulted in a poor fit to the data. However, the HbT time-course was well predicted, pixel-by-pixel, by a weighted sum of Ca2+ and NE time-courses. Consistent with this result, modeling HbT as a weighted sum of stationary Ca2+ - and NE-specific IRFs (IRFCa2+ and IRFNE) convolved with the respective time-courses dramatically improved the fit compared to the global IRF. IRFCa2+ and IRFNE, estimated from the data, were positive and negative, respectively. In contrast to NE, ACh was largely redundant with Ca2+ and therefore did not improve HbT estimation. Because NE covaried with arousal, we observed instances of the diminished hemodynamic coherence between cortical regions during high arousal despite coherent behavior of the underlying neuronal Ca2+ activity. We conclude that while neurovascular coupling with respect to neuronal Ca2+ is a dynamic and seemingly complex phenomenon, hemodynamic fluctuations can be captured by a simple linear model with stationary IRFs with respect to the underlying dilatory and constrictive forces. In the current study, these forces were captured by the positive IRFCa2+ (dilation) and negative IRFNE (constriction). Without accounting for NE neuromodulation and the associated vasoconstriction, diminished hemodynamic coherence, commonly referred to as "functional (dys)connectivity" in BOLD fMRI studies, can be falsely interpreted as neuronal desynchronizations.

neuroscience↗

bioRxiv2024

SARS-CoV-2 nsp16 is regulated by host E3 ubiquitin ligases, UBR5 and MARCHF7

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), remains a global public health threat with considerable economic consequences. The non-structural protein 16 (nsp16), in complex with nsp10, facilitates the final viral mRNA capping step through its 2'-O-methylase activity, helping the virus to evade host immunity and prevent mRNA degradation. However, nsp16 regulation by host factors remains poorly understood. While various E3 ubiquitin ligases interact with SARS-CoV-2 proteins, their roles in targeting nsp16 for degradation are unclear. In this study, we demonstrate that nsp16 undergoes ubiquitination and proteasomal degradation mediated by the host E3 ligases UBR5 and MARCHF7. UBR5 induces K48-linked ubiquitination, whereas MARCHF7 promotes K27-linked ubiquitination, independently suppressing SARS-CoV-2 replication in cell cultures and in mice. Notably, UBR5 and MARCHF7 also degrade nsp16 variants from different viral strains, exhibiting broad-spectrum antiviral activity. Our findings reveal novel antiviral mechanisms of the ubiquitin-proteasome system (UPS) and highlight their potential therapeutic targets against COVID-19.

microbiology↗