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Bai, Y.

Publications and source records attributed to Bai, Y..

At least 109 records · Page 6Linked to original sources

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↗

BioInformatics Agent (BIA): Unleashing the Power of Large Language Models to Reshape Bioinformatics Workflow

Bioinformatics plays a crucial role in understanding biological phenomena, yet the exponential growth of biological data and rapid technological advancements have heightened the barriers to in-depth exploration of this domain. Thereby, we propose Bio-Informatics Agent (BIA), an intelligent agent leveraging Large Language Models (LLMs) technology, to facilitate autonomous bioinformatic analysis through natural language. The primary functionalities of BIA encompass extraction and processing of raw data and metadata, querying both locally deployed and public databases for information. It further undertakes the formulation of workflow designs, generates executable code, and delivers comprehensive reports. Focused on the single-cell RNA sequencing (scRNA-seq) data, this paper demonstrates BIAs remarkable proficiency in information processing and analysis, as well as executing sophisticated tasks and interactions. Additionally, we analyzed failed executions from the agent and demonstrate prospective enhancement strategies including selfrefinement and domain adaptation. The future outlook includes expanding BIAs practical implementations across multi-omics data, to alleviating the workload burden for the bioinformatics community and empowering more profound investigations into the mysteries of life sciences. BIA is available at: https://github.com/biagent-dev/biagent.

bioinformatics↗

Cross-domain information fusion for enhanced cell population delineation in single-cell spatial-omics data

Cell population delineation and identification is an essential step in single-cell and spatial-omics studies. Spatial-omics technologies can simultaneously measure information from three complementary domains related to this task: expression levels of a panel of molecular biomarkers at single-cell resolution, relative positions of cells, and images of tissue sections, but existing computational methods for performing this task on single-cell spatial-omics datasets often relinquish information from one or more domains. The additional reliance on the availability of "atlas" training or reference datasets limits cell type discovery to well-defined but limited cell population labels, thus posing major challenges for using these methods in practice. Successful integration of all three domains presents an opportunity for uncovering cell populations that are functionally stratified by their spatial contexts at cellular and tissue levels: the key motivation for employing spatial-omics technologies in the first place. In this work, we introduce Cell Spatio- and Neighborhood-informed Annotation and Patterning (CellSNAP), a self-supervised computational method that learns a representation vector for each cell in tissue samples measured by spatial-omics technologies at the single-cell or finer resolution. The learned representation vector fuses information about the corresponding cell across all three aforementioned domains. By applying CellSNAP to datasets spanning both spatial proteomic and spatial transcriptomic modalities, and across different tissue types and disease settings, we show that CellSNAP markedly enhances de novo discovery of biologically relevant cell populations at fine granularity, beyond current approaches, by fully integrating cells molecular profiles with cellular neighborhood and tissue image information.

bioinformatics↗

Human polymerase theta helicase positions DNA microhomologies for double-strand break repair

DNA double-strand breaks occur in all human cells on a daily basis and must be repaired with high fidelity to minimize genomic instability1. Deficiencies in high-fidelity DNA repair by homologous recombination lead to dependence on DNA polymerase theta, which identifies DNA microhomologies in 3 single-stranded DNA overhangs and anneals them to initiate error-prone double-strand break repair. The resulting genomic instability is associated with numerous cancers, thereby making this polymerase an attractive therapeutic target2,3. However, despite the biomedical importance of polymerase theta, the molecular details of how it initiates DNA break repair remain unclear4,5. Here we present cryo-electron microscopy structures of the polymerase theta helicase domain bound to microhomology-containing DNA, revealing DNA-induced rearrangements of the helicase that enable DNA repair. Our structures show that DNA-bound helicase dimers facilitate a microhomology search that positions 3 single-stranded DNA ends in proximity to align complementary base pairs and anneal DNA microhomology. We define the molecular determinants that enable the polymerase theta helicase domain to identify and pair DNA microhomologies to initiate mutagenic DNA repair, providing mechanistic insights into therapeutic targeting of these interactions.

molecular biology↗

Identifying the gene responsible for NPQ reversal in Phaeodactylum tricornutum

Algae such as diatoms and haptophytes have distinct photosynthetic pigments from plants, including a novel set of carotenoids. This includes a primary xanthophyll cycle comprised of diadinoxanthin and its de-epoxidation product diatoxanthin that enables the switch between light harvesting and non-photochemical quenching (NPQ)-mediated dissipation of light energy. The enzyme responsible for the reversal of this cycle was previously unknown. Here, we identified zeaxanthin epoxidase 3 (ZEP3) from Phaeodactylum tricornutum as the candidate diatoxanthin epoxidase. Knocking out the ZEP3 gene caused a loss of rapidly reversible NPQ following saturating light exposure. This correlated with the maintenance of high concentrations of diatoxanthin during recovery in low light. Xanthophyll cycling and NPQ relaxation were restored via complementation of the wild type ZEP3 gene. The zep3 knockout strains showed reduced photosynthetic rates at higher light fluxes and reduced specific growth rate in variable light regimes, likely due to the mutant strains becoming locked in a light energy dissipation state. We were able to toggle the level of NPQ capacity in a time and dose dependent manner by placing the ZEP3 gene under the control of an inducible promoter. Identification of this gene provides deeper understanding of the diversification of photosynthetic control in algae compared to plants and suggests a potential target to improve the productivity of industrial-scale cultures.

plant biology↗

Epstein-Barr Virus Orchestrates Spatial Reorganization and Immunomodulation within the Classic Hodgkin Lymphoma Tumor Microenvironment

Classic Hodgkin Lymphoma (cHL) is a tumor composed of rare malignant Hodgkin and Reed-Sternberg (HRS) cells nested within a T-cell rich inflammatory immune infiltrate. cHL is associated with Epstein-Barr Virus (EBV) in 25% of cases. The specific contributions of EBV to the pathogenesis of cHL remain largely unknown, in part due to technical barriers in dissecting the tumor microenvironment (TME) in high detail. Herein, we applied multiplexed ion beam imaging (MIBI) spatial pro-teomics on 6 EBV-positive and 14 EBV-negative cHL samples. We identify key TME features that distinguish between EBV-positive and EBV-negative cHL, including the relative predominance of memory CD8 T cells and increased T-cell dysfunction as a function of spatial proximity to HRS cells. Building upon a larger multi-institutional cohort of 22 EBV-positive and 24 EBV-negative cHL samples, we orthogonally validated our findings through a spatial multi-omics approach, coupling whole transcriptome capture with antibody-defined cell types for tu-mor and T-cell populations within the cHL TME. We delineate contrasting transcriptomic immunological signatures between EBV-positive and EBV-negative cases that differently impact HRS cell proliferation, tumor-immune interactions, and mecha-nisms of T-cell dysregulation and dysfunction. Our multi-modal framework enabled a comprehensive dissection of EBV-linked reorganization and immune evasion within the cHL TME, and highlighted the need to elucidate the cellular and molecular fac-tors of virus-associated tumors, with potential for targeted therapeutic strategies.

cancer biology↗

A Spatial Multi-Modal Dissection of Host-Microbiome Interactions within the Colitis Tissue Microenvironment

The intricate and dynamic interactions between the host immune system and its microbiome constituents undergo dynamic shifts in response to perturbations to the intestinal tissue environment. Our ability to study these events on the systems level is significantly limited by in situ approaches capable of generating simultaneous insights from both host and microbial communities. Here, we introduce Microbiome Cartography (MicroCart), a framework for simultaneous in situ probing of host features and its microbiome across multiple spatial modalities. We demonstrate MicroCart by comprehensively investigating the alterations in both gut host and microbiome components in a murine model of colitis by coupling MicroCart with spatial proteomics, transcriptomics, and glycomics platforms. Our findings reveal a global but systematic transformation in tissue immune responses, encompassing tissue-level remodeling in response to host immune and epithelial cell state perturbations, and bacterial population shifts, localized inflammatory responses, and metabolic process alterations during colitis. MicroCart enables a deep investigation of the intricate interplay between the host tissue and its microbiome with spatial multiomics.

immunology↗

LHP1 and INO80 cooperate with ethylene signaling for warm ambient temperature response by activating specific bivalent genes

Ethylene signaling has been indicated as a potential positive regulator of plant warm ambient temperature response but its underlying molecular mechanisms are largely unknown. Here, we show that LHP1 and INO80 cooperate with ethylene signaling for warm ambient temperature response by activating specific bivalent genes. We found that the presence of warm ambient temperature activates ethylene signaling through EIN2 and EIN3, leading to an interaction between LHP1 and accumulated EIN2-C to co-regulate a subset of LHP1-bound genes marked by H3K27me3 and H3K4me3 bivalency. Furthermore, we demonstrate that INO80 is recruited to bivalent genes by interacting with EIN2-C and EIN3, promoting H3K4me3 enrichment and facilitating transcriptional activation in response to warm ambient temperature. Together, our findings illustrate a novel mechanism wherein ethylene signaling orchestrates LHP1 and INO80 to regulate warm ambient temperature response through activating specific bivalent genes in Arabidopsis.

plant biology↗

Degradation of indole-3-acetic acid by plant-associated microbes

Plant-associated microbiota affect pant growth and development by regulating plant hormones homeostasis. Indole-3-acetic acid (IAA), a well-known plant hormone, can be produced by various plant-associated bacteria. However, the prevalence of microbes with the capacity to degrade IAA in the rhizosphere has not been systematically studied. In this study, we analyzed the IAA degradation capabilities of bacterial isolates from the roots of Arabidopsis and rice. Using genomics analysis and in vitro assays, we found that 21 out of 189 taxonomically diverse bacterial isolates possess the ability to degrade IAA. Through comparative genomics and transcriptomic assays, we identified iac-like or iad-like operon in the genomes of these IAA degraders. Additionally, the regulator of the operon was found to be highly conserved among these strains through protein structure similarity analysis. Some of the IAA degraders could utilize IAA as their sole carbon and energy source. In planta, most of the IAA degrading strains mitigated Arabidopsis seedling root growth inhibition (RGI) triggered by exogenous IAA. Importantly, we observed increased colonization preference of IAA degraders from soil to root according to the frequency of the biomarker genes in metagenome-assembled genomes (MAGs) collected from different habitats, suggesting that there is a close association between IAA degraders and IAA-producers. In summary, our findings further the understanding of the functional diversity and roles of plant-associated microbes.

microbiology↗

OligoFormer: an accurate and robust prediction method for siRNA design

MotivationRNA interference(RNAi) has become a widely used experimental approach for post-transcriptional regulation and is increasingly showing its potential as future targeted drugs. However, the prediction of highly efficient siRNAs(small interfering RNA) is still hindered by dataset biases, the inadequacy of prediction methods, and the presence of off-target effects. To overcome these limitations, we propose an accurate and robust prediction method, OligoFormer, for siRNA design. ResultsOligoFormer comprises three different modules including thermodynamic calculation, RNA-FM module, and Oligo encoder. Oligo encoder is the core module based on the transformer encoder. Taking siRNA and mRNA sequences as input, OligoFormer can obtain thermodynamic parameters, RNA-FM embedding, and Oligo embedding through these three modules, respectively. We carefully benchmarked OligoFormer against 5 comparable methods on siRNA efficacy datasets. OligoFormer outperforms all the other methods, with an average improvement of 9% in AUC and 10.7% in F1 score in our inter-dataset validation. We also provide a comprehensive pipeline with prediction of siRNA efficacy and off-target effects using PITA score and TargetScan score. The ablation study shows RNA-FM module and thermodynamic parameters improved the performance and accelerated convergence of OligoFormer. The saliency map by gradient backpropagation shows certain base preferences in initial and terminal region of siRNAs.

bioinformatics↗

Large-scale multi-omics analyses identified root-microbiome associations underlying plant nitrogen nutrition

The microbiome determines the performance and fitness of the host plant. Nevertheless, the causal interaction between host genetic variation, gene regulation and the impact of the microbiome on the host phenotype remain unknown. Here we generated 1,341 paired root transcriptome, rhizosphere microbiome and root ionome samples and performed a multi-omics analyses of the host-microbe association at the root-soil interface using 175 rapeseeds (Brassica napus L.) resequenced ecotypes at two field environments. We observed the highest statistically explained variance for root nitrogen uptake among natural ionomic variation by overall transcriptome-wide gene expression and microbial abundance variation. Moreover, we identified significant genome-wide associations for 203 highly heritable amplicon sequence variants (ASVs) at multiple genetic loci regulated by eQTL hotspots associated with nitrogen metabolism components. These associations involved a central bacterial genus (Sphingopyxis), which plays a dominant role on gene regulatory effect on its variation regulated by eQTL hotspots. In addition, we performed high-throughput bacterial cultivation from rapeseed roots and subjected Sphingopyxis to whole genome sequencing. Finally, targeted metabolite profiling and confocal imaging assays demonstrated a host-microbiome regulatory effect on Sphingopyxis established by lateral root development and plant nitrogen nutrition. In summary, our integrative approach reveals the genetic basis of host-microbiome trait associations in the transcriptional, nutritional and environmental domains and suggests that the microbiome might have causal effects on root development with implications towards the breeding of nutrient-efficient crops.

plant biology↗

A single-cell 3D spatiotemporal multi-omics atlas from Drosophila embryogenesis to metamorphosis

The development of a multicellular organism is a highly intricate process tightly regulated by numerous genes and pathways in both spatial and temporal manners. Here, we present Flysta3D, a comprehensive multi-omics atlas of the model organism Drosophila, spanning its developmental lifespan from embryo to pupa. Our datasets encompass 3D single-cell spatial transcriptomic, single-cell transcriptomic, and single-cell chromatin accessibility information. By integrating these multi-dimensional data, we constructed cell state trajectories that uncover the detailed profiles of tissue development. With a focus on the central nervous system (CNS) and midgut, we dissected the spatiotemporal dynamics of gene regulatory networks, cell type diversity, and morphological changes from a multi-omics perspective. This extensive atlas provides an unprecedentedly rich resource and serves as a systematic platform for studying Drosophila development with integrated single-cell data at an ultra-high spatiotemporal resolution.

developmental biology↗

Individualized functional connectivity markers associated with motor and mood symptoms of Parkinson's disease

Parkinsons disease (PD) is a complex neurological disorder characterized by many motor and non-motor symptoms. While most studies focus on the motor symptoms of the disease, it is important to identify markers that underlie different facets of the disease. In this case-control study, we sought to discover reliable, individualized functional connectivity markers associated with both motor and mood symptoms of PD. Using functional MRI, we extensively sampled 166 patients with PD (64 women, 102 men; mean age=61.8 years, SD=7.81) and 51 healthy control participants (32 women, 19 men; mean age=55.68 years, SD=7.62). We found that a model consisting of 44 functional connections predicted both motor (UPDRS-III: Pearson r=0.21, FDR-adjusted p=0.006) and mood symptoms (HAMD: Pearson r=0.23, FDR-adjusted p=0.006; HAMA: Pearson r=0.21, FDR-adjusted p=0.006). Two sets of connections contributed differentially to these predictions. Between-network connections, mainly connecting the sensorimotor and visual large-scale functional networks, substantially contributed to the prediction of motor measures, while within-network connections in the insula and sensorimotor network contributed more so to mood prediction. The middle to posterior insula region played a particularly important role in predicting depression and anxiety scores. We successfully replicated and generalized our findings in two independent PD datasets. Taken together, our findings indicate that sensorimotor and visual network markers are indicative of PD brain pathology, and that distinct subsets of markers are associated with motor and mood symptoms of PD.

neuroscience↗

Screening for metastasis-related genes in mouse melanoma cells through sequential tail vein injection

Tumor metastasis, responsible for approximately 90% of cancer-associated mortality, remains poorly understood. Here in this study we employed a melanoma lung metastasis model to screen for metastasis-related genes. By sequential tail vein injection of mouse melanoma B16F10 cells and the subsequently derived cells from lung metastasis into BALB/c mice, we successfully obtained highly metastatic B16F15 cells after five rounds of in vivo screening. RNA-sequencing analysis of B16F15 and B16F10 cells revealed a number of differentially expressed genes, some of these genes have previously been associated with tumor metastasis while others are novel discoveries. The identification of these metastasis-related genes not only improve our understanding of the metastasis mechanisms, but also provide potential diagnostic biomarkers and therapeutic targets for metastatic melanoma.

cell biology↗

A spatial cell atlas of neuroblastoma reveals developmental, epigenetic and spatial axis of tumor heterogeneity

Neuroblastoma is a pediatric cancer arising from the developing sympathoadrenal lineage with complex inter- and intra-tumoral heterogeneity. To chart this complexity, we generated a comprehensive cell atlas of 55 neuroblastoma patient tumors, collected from two pediatric cancer institutions, spanning a range of clinical, genetic, and histologic features. Our atlas combines single-cell/nucleus RNA-seq (sc/scRNA-seq), bulk RNA-seq, whole exome sequencing, DNA methylation profiling, spatial transcriptomics, and two spatial proteomic methods. Sc/snRNA-seq revealed three malignant cell states with features of sympathoadrenal lineage development. All of the neuroblastomas had malignant cells that resembled sympathoblasts and the more differentiated adrenergic cells. A subset of tumors had malignant cells in a mesenchymal cell state with molecular features of Schwann cell precursors. DNA methylation profiles defined four groupings of patients, which differ in the degree of malignant cell heterogeneity and clinical outcomes. Using spatial proteomics, we found that neuroblastomas are spatially compartmentalized, with malignant tumor cells sequestered away from immune cells. Finally, we identify spatially restricted signaling patterns in immune cells from spatial transcriptomics. To facilitate the visualization and analysis of our atlas as a resource for further research in neuroblastoma, single cell, and spatial-omics, all data are shared through the Human Tumor Atlas Network Data Commons at www.humantumoratlas.org.

cancer biology↗

Unveiling Elevated Spontaneous Mutation Rates in Phyllostachys edulis (Moso Bamboo) through Whole Genome Sequencing (WGS) and Investigating the Impact of Atmospheric and Room Temperature Plasma (ARTP) Induced Mutagenesis

Moso bamboo, recognized for its wide distribution and economic importance, encounters challenges in varietal enhancement due to its protracted sexual reproduction cycle. This study employed whole-genome resequencing to uncover spontaneous mutations in Moso bamboo and investigated mutagenesis using atmospheric and room temperature plasma (ARTP). Through the sequencing results, we identified the population of flowering bamboo as an asexual breeding line. Notably, the flowering Moso bamboo population, exclusively derived from asexual reproduction, exhibited a high spontaneous mutation rate (4.54 x 10-4 to 1.15 x 10-3/bp) during sexual reproduction, considering parental and cross-pollination effects. Genetic disparities between offspring and parents exhibited a bimodal distribution, indicating a substantial cross-pollination rate. ARTP mutagenesis increased structural variations in offspring, while changes in SNPs and INDELs were less pronounced. Sanger sequencing validated a gene subset, providing a foundation for spontaneous mutation rate investigation via whole-genome sequencing. These insights, particularly from mutagenized offspring sequencing, contribute to Moso bamboo breeding strategies. HighlightMoso bamboo breeding revolutionized--high spontaneous mutations in asexually derived flowering population. ARTP mutagenesis boosts structural variations, shaping innovative breeding approaches.

genetics↗

The somato-cognitive action network links diverse neuromodulatory targets for Parkinson's disease

The newly-recognized somato-cognitive action network (SCAN) is posited to be important in movement coordination. Functional disruptions in Parkinsons disease (PD) correspond with complex, non-effector-specific motor symptoms, indicating that SCAN dysfunction may underlie these symptoms. Along the same lines, the SCAN may link multiple neuromodulatory targets used for PD treatment. To investigate the role of the SCAN in PD, we leveraged resting-state precision functional mapping, analyzing data from 673 individuals across 6 independent datasets and 5 types of neuromodulation. Our findings revealed functional abnormalities within the SCAN in PD patients and the selective involvement of the SCAN in diverse neuromodulatory targets. Moreover, our data suggests causal links between SCAN connectivity changes and motor symptom alleviation following both invasive and non-invasive neuromodulation. Collectively, these findings underscore the critical role of the SCAN in the pathophysiology of PD and its brain stimulation treatments, and suggest the SCAN as a promising candidate target for neuromodulation.

neuroscience↗

New insights on the role of SlDMR6-1 in drought avoidance in tomato

The DOWNY MILDEW RESISTANCE 6 (DMR6) protein is a 2-oxoglutarate (2OG) and Fe(II)-dependent oxygenase, involved in salicylic acid (SA) metabolism, and its inactivation in tomato was found to increase SA levels and to confer disease-resistance against several pathogens. SA is also recognized as an abiotic stress-tolerance enhancer, and we tested the resistance to drought stress in Sldmr6-1 tomato mutants generated by the CRISPR/Cas9 technique. Wild-type (WT) tomato cultivar San Marzano and its Sldmr6-1 mutants were subjected to water deprivation for 7 days. At the end of the period, while WT plants exhibited severe wilting, the T2 Sldmr6-1 mutant plants showed turgid leaves and maintained higher Soil Relative Water Content (SRWC). Sldmr6-1 mutants adopted a water saving behaviour reducing transpiration rate (E) by decreasing stomatal conductance (Gs). Assimilation rate (A) decreased in parallel to E under drought stress, resulting in no alteration of the CO2 concentration in the sub-stomatal chamber (Ci) and increasing the Water Use Efficiency (WUE, A/E). Defence mechanisms of the photosynthetic machinery triggered in Sldmr6-1 mutants, that under drought stress showed up-regulation of the genes SlAPX and SlGST (anti-oxidant related) as well as down-regulation of SlCYP707A2 gene, which is involved in ABA catabolism. Our results suggest that the disabling of SlDMR6-1 in tomato plants leads to a drought-avoidance strategy through tight control of stomatal closure controlling water loss. In addition, it was highlighted, for the first time in tomato, that Sldmr6-1 mutants showed reduced susceptibility to Phytophthora infestans, the causal agent of Late Blight.

plant biology↗