Biology subjects

Xiong, G.

Publications and source records attributed to Xiong, G..

14 recordsLinked to original sources

bioRxiv2026

P4HA1 sustains endocrine resistance in luminal breast cancer via regulation of cellular stress

The hormone receptor-positive luminal subtype accounts for approximately 70% of all diagnosed breast cancer cases, with endocrine regimens serving as the first-line therapy. However, 30% to 50% of luminal breast cancer patients acquire therapeutic resistance with five to ten years of treatment. Understanding the mechanisms of endocrine resistance and identifying new therapeutic targets remain urgent priorities. Here, we demonstrate that expression of the alpha subunit of prolyl 4-hydroxylase (P4HA1), a key collagen-modifying enzyme, is significantly upregulated in endocrine therapy-resistant luminal breast cancer cells compared to parental endocrine therapy-sensitive cells. Clinically, elevated P4HA1 expression correlates with shortened relapse-free survival in patients with luminal breast cancer. Genetically knocking down P4HA1 or pharmacologically inhibiting its activity successfully restores the sensitivity of endocrine-resistant luminal breast cancer cells to hormone therapy. Mechanistically, we reveal that combining P4HA1 inactivation with endocrine treatment dramatically enhances endoplasmic reticulum (ER) stress-related gene expression. Consistently, treating resistant cells with an exogenous ER stress inducer similarly enhances sensitivity to hormone therapy. Furthermore, we demonstrate that ER stress induced by P4HA1 inactivation is molecularly mediated by an accumulation of reactive oxygen species (ROS). Together, these findings uncover a novel, non-canonical role for P4HA1 as a critical mediator linking endocrine resistance to cellular stress adaptations, positioning P4HA1 as a promising therapeutic vulnerability in endocrine-resistant breast cancer. P4HA1 serves as a necessary role in maintenance resistant state, making it a viable target for combination therapies to overcome endocrine resistance.

cancer biology↗

bioRxiv2026

Extracts of Bacillus proteolyticus strain OSUB18 exhibit cytostatic activity

Although therapeutic advancements have dramatically improved outcomes for cancer patients in recent decades, advanced cancer remains a significant challenge. There is still an urgent need for new and more effective strategies that minimize toxicity and improve survival outcomes in cancer patients. Natural products from microorganisms are a rich and promising source of bioactive compounds with substantial therapeutic potential in cancer treatment. Recently, B. proteolyticus strain OSUB18, isolated from switchgrass, has been demonstrated to promote plant growth and regulate reactive oxygen species (ROS) production. Here, we investigated the anticancer potential of this plant-associated microbe and demonstrated that its crude extracts exhibited broad-spectrum cytostatic activity across diverse solid tumor cell lines. Importantly, OSUB18 extracts displayed limited cytotoxicity toward normal human mammary epithelial cells and mouse fibroblasts. This potentially selective cytostatic activity was retained within a water soluble, heat-labile, and protease-resistant fraction. The extracts primarily suppressed cell proliferation, accompanied by increased lipid peroxidation, with preliminary evidence suggesting the potential involvement of ferroptosis. These findings suggest that the bioactive component may be a selective cytostatic agent with multifaceted mechanisms of action.

cancer biology↗

bioRxiv2026

Coevolution-driven reconstruction of multi-taxa siderophore interaction networks reveals topological diversity of microbial exploitation

Microbial communities are shaped by secreted metabolites that mediate ecological interactions, yet predicting these interactions from genomic sequences remains difficult, because the specific recognition between co-functional metabolites (CFMs), such as siderophores, and their receptor proteins (Rec) cannot be inferred from gene annotation alone. This difficulty arises from three factors: the prevalence of Rec-mediated exploitation, the lack of high-accuracy functional annotations, and the absence of genomic co-localization between functionally paired CFM-Rec in Gram-positive bacteria. Here we present the Coevolution-based Interaction Model (CIM), an automated framework that maps specific CFM-Rec pairings directly from uncurated genomic datasets. Using a dynamic joint optimization strategy that accounts for exploitation asymmetry and avoids combinatorial explosion, CIM identifies functional pairings solely through evolutionary covariation. We validated this approach by reconstructing macroscale iron scavenging networks across nine bacterial taxa. Experiments confirmed that CIM can bridge genomic distances exceeding 3 Mb in the Gram-positive genus Rhodococcus to identify unlinked cognate receptors, and can accurately predict cross-utilization by exploiter strains despite substantial receptor sequence heterogeneity in Burkholderiaceae and Rhizobiaceae. Finally, topological analysis of the reconstructed networks shows that siderophore exploitation acts as a universal topological glue, fusing fragmented microbial populations into highly connected communities, and that the exploitability of siderophore production reverses depending on network modularity. CIM thus offers a scalable, sequence-to-ecology approach for predicting interactions mediated by secondary metabolites in microbial communities.

systems biology↗

bioRxiv2026

A Diploid Panax Genome Reveals Ginsenoside Diversity Driven by UGT Diversification and Network Rewiring, Rather Than Gene Family Expansion

The medicinal herb Panax notoginseng produces a structurally diverse array of triterpene saponins (ginsenosides), yet the genetic basis of this chemical complexity remains unclear. Here we present a high-quality chromosome-level genome of diploid P. notoginseng and integrate comparative genomics with multi-tissue, multi-year metabolomics and transcriptomics. Surprisingly, unlike tetraploid Panax species, P. notoginseng shows no general expansion of core saponin biosynthetic gene families. Instead, lineage-specific diversification of UDP-glycosyltransferase (UGT) families, a recent burst of LTR retrotransposons, and enrichment of species-specific genes in metabolic modification pathways point to an alternative evolutionary route. Saponin accumulation follows strict spatiotemporal compartmentalisation, and co-expression network analysis reveals that the biosynthetic machinery is not static but continuously rewired during development-from a basic synthesis module in the first year to a modular pattern supporting both broad accumulation and branch-specific modification by the third year. Seventeen differentially expressed UGTs show clear tissue preferences and saponin-branch correlations. As a representative example, PnUGT33 is tightly linked to the PPD-type saponin branch; structural modelling, molecular docking and 100 ns molecular dynamics simulations demonstrate its differential recognition of diverse triterpene skeletons. Collectively, our findings establish that ginsenoside diversity in diploid P. notoginseng arises primarily from UGT lineage diversification, developmentally rewired regulatory networks and UGT mediated branch selective post-modification, rather than from expansion of core pathway genes. This work provides a new paradigm for understanding how plants achieve metabolic complexity without whole genome duplication or massive gene amplification.

genomics↗

bioRxiv2025

Co-Evolutionary Characterization of PBP2 as the Predominant Siderophore Recognizer in Diverse Gram-Positive Bacteria

Iron is a scarce yet essential nutrient for bacteria. Microbes often acquire iron by secreting siderophores, a diverse group of small molecules that form high-affinity complexes with iron for microbial uptake. Understanding microbial iron interaction networks requires detailed characterization of siderophore recognition specificity. In Gram-positive bacteria, substrate-binding proteins (SBPs) bind iron-siderophore complexes and deliver them to ABC transporters for import. However, the SBPs responsible for selective recognition remain poorly characterized, hindering large-scale data mining and network reconstruction. Here, we addressed this knowledge gap by systematically analyzing siderophore uptake systems, first in five representative genera and then across a comprehensive dataset of 16,232 Gram-positive genomes. Through a pipeline integrating genome mining, coevolutionary analysis, and structural modeling, we established PBP2 (Peripla_BP_2) subtype SBPs as the primary siderophore recognizer family. We revealed that, unlike the physically clustered systems in Gram-negative bacteria, synthetase and recognizer genes in Gram-positive bacteria are sometimes genomically decoupled yet display coordinated transcriptional regulation by iron-responsive transcription factors. Our findings underscore key differences between Gram-positive and Gram-negative iron acquisition systems, providing foundational knowledge for large-scale inference of siderophore-mediated microbial interactions. Impact StatementBacteria secrete siderophores to scavenge iron and import the siderophore-iron complex via specific receptors, a process that shapes microbial community dynamics. However, predicting these interactions has been challenging, because the specific siderophore receptors in Gram-positive bacteria remained largely uncharacterized. In this study, we opened this "black box" by analyzing a comprehensive dataset of 16,232 genomes spanning the majority of Gram-positive bacteria. Through coevolutionary analysis, we identified PBP2 proteins as the primary "locks" that recognize siderophore "keys." We further demonstrate that these receptors exhibit greater evolutionary flexibility than their Gram-negative counterparts, frequently decoupled genomically from siderophore biosynthesis genes yet linked by transcriptional regulation. This discovery fills a critical knowledge gap, providing the missing link needed to map the global landscape of siderophore uptake potential and enable "sequence-to-ecology" prediction of iron-interaction networks in Gram-positive bacteria.

microbiology↗

bioRxiv2024

Tri-omic mapping revealed concerted dynamics of 3D epigenome and transcriptome in brain cells

Exploring the genomic basis of transcriptional programs has been a longstanding research focus. Here, we report a high-throughput single-cell tri-omic method to capture chromatin accessibility, interaction, and RNA simultaneously (ChAIR). After validating in cultured cells, we applied ChAIR to brain cells across mouse lifespan and delineated the concerted dynamics of 3D-epigenomic architecture and transcription during maturation and aging. Particularly, ultra-long chromatin megacontacts and promoter-associated 3D-epigenomic states are effective in defining cell identity and revealing spatially-resolved anatomic specificity. Importantly, we found that neurons in different brain regions and non-neuronal cells may undergo divergent genomic mechanisms during differentiation and aging. Our results demonstrated ChAIRs robustness of connecting chromatin folding architecture with cellular property and its potential applications to address complex questions in single-cell resolution and spatial specificity.

genomics↗

bioRxiv2024

Genome-wide analysis of flavonoid biosynthetic genes in Musaceae (Ensete, Musella, and Musa species) reveals amplification of flavonoid 3',5'-hydroxylase

Flavonoids in Musaceae are involved in pigmentation and stress responses, including pathogen defense and UV protection, and are a component of the healthy human diet. Identification and analysis of the sequence and copy number of flavonoid biosynthetic genes are valuable for understanding the nature and diversity of flavonoid evolution in Musaceae species. In this study, we identified 71 to 80 flavonoid biosynthetic genes in chromosome-scale genome sequence assemblies of Musaceae, including those of Ensete glaucum, Musella lasiocarpa, Musa beccarii, M. acuminata, M. balbisiana, and M. schizocarpa, checking annotations with BLAST and determining the presence of conserved domains. The number of genes increased through segmental duplication and tandem duplication. Orthologues of both structural and regulatory genes in the flavonoid biosynthetic pathway are highly conserved across Musaceae. The flavonoid 3,5-hydroxylase gene F35Hs was amplified in Musaceae and ginger compared with grasses (rice, Brachypodium, Avena longiglumis, and sorghum). One group of genes from this gene family amplified near the centromere of chromosome 2 in the x = 11 Musaceae species. Flavonoid biosynthetic genes displayed few consistent responses in the yellow and red bracts of Musella lasiocarpa when subjected to low temperatures. The expression levels of MlDFR2/3 increased while MlLAR was reduced by half. These results establish the range of diversity in both sequence and copy number of flavonoid biosynthetic genes during evolution of Musaceae. The combination of allelic variants of genes, changes in their copy numbers, and variation in transcription factors with the modulation of expression under cold treatments and between bract-colours suggests the variation may be exploited in plant breeding programmes, particularly for improvement of stress-resistance in the banana crop.

genetics↗

bioRxiv2023

DeepGSEA: Explainable Deep Gene Set Enrichment Analysis for Single-cell Transcriptomic Data

Gene set enrichment (GSE) analysis allows for an interpretation of gene expression through pre-defined gene set databases and is a critical step in understanding different phenotypes. With the rapid development of single-cell RNA sequencing (scRNA-seq) technology, GSE analysis can be performed on fine-grained gene expression data to gain a nuanced understanding of phenotypes of interest. However, due to the extreme heterogeneity of single-cell gene expression, current statistical GSE analysis methods sometimes fail to identify enriched gene sets. Meanwhile, deep learning has gained traction in specific applications like clustering and trajectory inference in single-cell studies due to its prowess in capturing complex data patterns. However, its use in GSE analysis remains limited, primarily due to interpretability challenges. In this paper, we present DeepGSEA, an explainable deep gene set enrichment analysis approach which leverages the expressiveness of interpretable, prototype-based neural networks to provide an in-depth analysis of GSE. DeepGSEA learns the ability to capture GSE information through our designed classification tasks, and significance tests can be performed on each gene set, enabling the identification of enriched sets. The underlying distribution of a gene set learned by DeepGSEA can be explicitly visualized using the encoded cell and cellular prototype embeddings. We demonstrate the expressiveness of DeepGSEA over commonly used GSE analysis methods by examining their sensitivity and specificity with four simulation studies. In addition, we test our model on three real scRNA-seq datasets and illustrate the interpretability of DeepGSEA by showing how its results can be explained. The source code of DeepGSEA is available at https://github.com/Teddy-XiongGZ/DeepGSEA.

bioinformatics↗

bioRxiv2023

From sequence to ecology: siderophore-receptor coevolution algorithm predicts bacterial interactions in complex communities

Predicting bacterial social interactions from genome sequences is notoriously difficult. Here, we developed bioinformatic tools to predict whether secreted iron-scavenging siderophores stimulate or inhibit the growth of community members. Siderophores are chemically diverse and can be stimulatory or inhibitory depending on whether bacteria possess or lack corresponding uptake receptors. We focused on 1928 representative Pseudomonas genomes and developed a co-evolution algorithm to match all encoded siderophore synthetases to corresponding receptor gene groups with >90% accuracy based on experimental validation. We derived community-level iron interaction networks to show that selection for siderophore-mediated interactions differs across habitats and lifestyles. Specifically, dense networks of siderophore sharing and competition were observed among environmental (soil/water/plant) strains and non-pathogenic species, while only fragmented networks occurred among human-derived strains and pathogenic species. Altogether, our sequence-to-ecology approach empowers the analyses of social interactions among thousands of bacterial strains and uncovers ways for targeted intervention to microbial communities. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=87 SRC="FIGDIR/small/565711v3_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@60d907org.highwire.dtl.DTLVardef@48756eorg.highwire.dtl.DTLVardef@115aac1org.highwire.dtl.DTLVardef@17d76e5_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2022

Global mosquito virome profiling and mosquito spatial diffusion pathways revealed by marker-viruses

Mosquitoes are vectors of numerous emergence and reemergence of mosquito-borne diseases, leading to an overwhelming global challenge. The boom in metagenomic studies promoted the increase of mosquito viruses being described, and studies from different regions of the world showed that mosquitoes harbor abundant and diverse viromes. However, there is still a lack of large-scale systematic comparison of viromes among various ecological factors such as the mosquito species/genera, location, etc, and consistent patterns associated with these factors are not clear. Here, we provide an overview of virome profiling that integrated the perspective of mosquito genus, locations, and climates based on the global scale, and redefined the core-virome. Our results also further implicate some mosquito-associated viruses strongly associated with the ecological factors and highlighted the evidence of mosquitoes cross-regional movements by the candidate marker viruses. The study may be helpful in gaining new insights into strategies to prevent arbovirus epidemics.

microbiology↗

bioRxiv2021

Enabling technology for microbial source tracking based on transfer learning: From ontology-aware general knowledge to context-aware expert systems

Microbial source tracking quantifies the potential origin of microbial communities, facilitates better understanding of how the taxonomic structure and community functions were formed and maintained. However, previous methods involve a tradeoff between speed and accuracy, and have encountered difficulty in source tracking under many context-dependent settings. Here, we present EXPERT for context-aware microbial source tracking, in which we adopted a Transfer Learning approach to profoundly elevate and expand the applicability of source tracking, enabling biologically informed novel microbial knowledge discovery. We demonstrate that EXPERT can predict microbial sources with performance superior to other methods in efficiency and accuracy. More importantly, we demonstrate EXPERTs context-aware ability on several applications, including tracking the progression of infant gut microbiome development and monitoring the changes of gut microbiome for colorectal cancer patients. Broadly, transfer learning enables accurate and context-aware microbial source tracking and has the potential for novel microbial knowledge discovery.

bioinformatics↗

bioRxiv2020

Transcriptomic expression patterns of two contrasting lowland rice varieties reveal high iron stress tolerance

Iron (Fe) toxicity is a major challenge for plant cultivation in acidic water-logged soil environments, where lowland rice is a major staple food crop. Only few studies addressed the molecular characterization of excess Fe tolerance in rice, and these highlight different mechanisms for Fe tolerance in the studied varieties. Here, we screened 16 lowland rice varieties for excess Fe stress growth responses to identify contrasting lines, Fe-tolerant Lachit and -susceptible Hacha. Hacha and Lachit differed in their physiological and morphological responses to excess Fe, including leaf growth, leaf rolling, reactive oxygen species generation, Fe and metal contents. These responses were mirrored by differential gene expression patterns, obtained through RNA-sequencing, and corresponding GO term enrichment in tolerant versus susceptible lines. From the comparative transcriptomic profiles between Lachit and Hacha in response to excess Fe stress, individual genes of the category metal homeostasis, mainly root-expressed, may contribute to the tolerance of Lachit. 22 out of these 35 metal homeostasis genes are present in selection sweep genomic regions, in breeding signatures and/or differentiated during rice domestication. These findings will serve to design targeted Fe tolerance breeding of rice crops. Summary statementLowland rice varieties Hacha and Lachit were selected for contrasting abilities to cope with iron excess stress. Morphological and physiological phenotypes were mirrored by molecular transcriptome changes, indicating altered metal homeostasis in the root as an adaptive tolerance mechanism in Lachit.

plant biology↗

bioRxiv2018

Growth- and stress-related defects associated to wall hypoacetylation are strigolactone-dependent

Mutants affected in the Arabidopsis TBL29/ESK1 xylan O-acetyltransferase display a strong reduction in total wall O-acetylation accompanied by a dwarfed plant stature, collapsed xylem morphology, and enhanced freezing tolerance. A newly identified tbl29/esk1 suppressor mutation affects the biosynthesis of strigolactones (SL) due to the reduced expression of the MAX4 gene. Genetic and biochemical evidence suggests that blocking the biosynthesis of SL is sufficient to recover all developmental and stress-related defects associated with the TBL29/ESK1 loss of function without affecting its direct effect - reduced wall O-acetylation. Altered levels of the MAX4 SL biosynthetic gene, reduced branch number, and higher levels of methyl carlactonoate, an active SL, were also found in tbl29/esk1 plants consistent with a constitutive activation of the SL pathway. These results indicate that the reduction of O-acetyl substituents in xylan is not directly responsible for the observed tbl29/esk1 phenotypes. Alternatively, plants may perceive defects in the structure of wall polymers and/or wall architecture activating the SL hormonal pathway as a compensatory mechanism.

plant biology↗

bioRxiv2017

Melanism patches up the defective cuticular morphological traits through promoting the up-regulation of cuticular protein-coding genes in Bombyx mori

Melanin and cuticular proteins are important cuticle components in insect. Cuticle defects caused by mutations in cuticular protein-encoding genes can hinder melanin deposition. However, the effects of melanin variation on cuticular protein-encoding genes and the corresponding morphological traits associated with these genes are remain largely unknown. Using Bombyx mori as a model, we showed that the melanism levels during larval cuticle pigmentation correlated positively with the expression of cuticular protein-encoding genes. This correlation stemmed from the simultaneous induction of these genes by the melanin precursors. More importantly, the effect of the melanism background on the cuticles induced the up-regulation of other functionally redundant cuticular protein-encoding genes to rescue the morphological and adaptive defects caused by the dysfunction of some mutated cuticular proteins, and the restorative ability increased with increasing melanism levels, which gives a novel evidence that melanism enhances insect adaptability. These findings deepen our understanding of the interactions among cuticle components, as well as their importance in the stabilizing of the normal morphology and function of the cuticle.

genetics↗