Biology subjects

Ke, S.

Publications and source records attributed to Ke, S..

15 recordsLinked to original sources

bioRxiv2026

Low-Density Lipoprotein Cholesterol and Cerebral Pericyte Dysfunction in Acute Ischemic Stroke: Clinical and Experimental Evidence

Background: Low-density lipoprotein cholesterol (LDL-C) is an established risk factor for atherosclerotic cerebrovascular disease, but its effects on the cerebral microcirculation are poorly defined. We investigated whether LDL-C is associated with pericyte dysfunction in acute ischemic stroke (AIS) and explored underlying mechanisms. Methods: Serum soluble platelet-derived growth factor receptor-{beta} (sPDGFR{beta}) was measured in two independent AIS cohorts (n=97 and n=86). Cerebral pericyte transcriptional responses to LDL-C were analyzed by single-cell RNA sequencing in Apoe-knockout mice fed control or high-fat diet (n=4 [male/female: 2/2]/group), and cultured human brain pericytes were exposed to purified human LDL cholesterol with or without N-acetyl-L-cysteine. Results: Higher serum sPDGFR{beta} was associated with greater neurological deficit and circulating neurofilament light chain. LDL-C positively correlated with sPDGFR{beta} in both clinical cohorts. High-fat diet induced coordinated suppression of type-I interferon pathways, and a positive shift in reactive oxygen species-related transcriptional programs in mouse pericytes; exploratory sex-by-diet analyses suggested larger transcriptional responses in females. In cultured human pericytes, LDL-C induced oxidative-stress, lipid-handling, and ferroptosis-associated transcriptional programs while suppressing type-I interferon signaling. Cross-species enrichment analysis showed that LDL-C-induced and -repressed signatures in cultured pericytes aligned with the sex-by-diet interaction in Apoe-knockout mice. LDL-C also reduced cell-surface PDGFR{beta} and increased sPDGFR{beta} release in cultured pericytes, which were significantly attenuated by N-acetyl-L-cysteine, whereas LDH activity increased numerically but not significantly. Conclusions: Clinical and experimental findings support an LDL-pericyte axis linking atherogenic lipid stress to cerebral microvascular dysfunction, with possible sex-dependent modulation of oxidative stress and type-I interferon signaling as potential mechanisms.

neuroscience↗

bioRxiv2026

Heterogeneous Graph Contrastive Learning for Drug-Gene-Disease Motif Prediction

Drug repurposing and target discovery offer critical strategies for advancing therapeutic development by uncovering the potential biological pathways and novel associations among drugs, genes, and diseases. However, experimental discovery remains expensive and time-consuming, which limits the scalability of large-scale studies. In addition, existing computational approaches often struggle to effectively integrate heterogeneous biomedical data, capture the complex higher-order topological signatures of biological interactomes, and generalize to unseen entities. Here, we present HANAMI (Heterogeneous grAph coNtrastive leArning for drug-gene-disease Motif predIction), a multi-view deep graph learning framework designed to model complex interactions among drugs, genes, and diseases. HANAMI integrates diverse heterogeneous biomedical knowledge, including chemical structures, genomic sequences, and clinical phenotypes, and leverages relation-aware topology encoding, structure-aware aggregation, and contrastive learning to enable accurate motif prediction with biological context from the network. Systematic evaluation on benchmark datasets shows that HANAMI achieves up to 6% improvements over existing state-of-the-art methods in predicting drug-gene-disease motifs. The framework further demonstrates strong inductive generalization, maintaining an [~]18% performance advantage in zero-shot settings involving previously unseen entities. Beyond predictive performance, HANAMI effectively prioritizes drug-disease relationships investigated in Phase II or III trials while identifying candidate genes that suggest plausible mechanistic links. Together, HANAMI provides a computational framework for interpreting complex biomedical interactions, offering a scalable foundation to accelerate drug repurposing and therapeutic innovation.

bioinformatics↗

bioRxiv2026

AI-guided discovery of antimicrobial peptides for urinary tract infections leveraging a new catalogue of the human urinary microbiome

Urinary tract infections (UTIs) are common infections that pose a critical burden on healthcare and society. Despite growing recognition that the human urinary tract harbors its own microbiome, its composition, functional potential, and alterations in UTI remain limited. Here, we leveraged the publicly available whole-metagenome shotgun sequencing data from 450 urinary microbiome samples collected in four independent cohorts together with genome assembly and metagenomic binning to construct an extensive human urinary microbiome catalog consisting of [~]1.3 million non-redundant microbial genes and 705 non-redundant metagenome-assembled genomes (nrMAGs). We found that microbiomes from patients with UTI carry significantly more genes linked to antibiotic resistance and virulence vs controls. There was an enrichment of multiple Escherichia strains in patients with UTI from two independent case-control cohorts. UTIs are becoming multidrug-resistant, and we used machine learning models to identify potential antimicrobial peptides (AMPs) in 705 nrMAGs. Furthermore, we experimentally demonstrated that two of these AMPs exhibited strong inhibitory activity against uropathogenic Escherichia coli strains. Our study provides a valuable resource for studying the human urinary microbiome and suggests urinary microbiome-derived AMPs represent a source of new therapeutics for UTIs.

microbiology↗

bioRxiv2026

Oral Gut Microbial Axis in Inflammatory Bowel Disease and Primary Sclerosing Cholangitis

The oral cavity is increasingly recognized as a reservoir of microbes that can translocate to and influence the gut microbiome. This oral-gut microbial axis may contribute to the pathogenesis of chronic gastrointestinal and hepatobiliary disorders, including inflammatory bowel disease (IBD) and its comorbidity, primary sclerosing cholangitis (PSC). To investigate the oral-gut microbial axis in IBD and PSC, we enrolled 191 participants spanning Crohns disease (CD), ulcerative colitis (UC), CD with PSC (CD-PSC), UC with PSC (UC-PSC), and healthy controls. We generated and analyzed the whole-metagenome shotgun sequencing data from saliva, tongue swabs, and fecal samples. Across oral and gut niches, we identified multiple microbial species differentially enriched in participants with UC compared with healthy controls, including Fusobacterium nucleatum and Gemella sanguinis in saliva, Catonella massiliensis and Tannerella serpentiformis on the tongue, and G. sanguinis and Sellimonas intestinalis in feces. Paired oral-gut analyses revealed 15 potential oral-origin species enriched in fecal samples; notably, G. sanguinis and Veillonella rogosae were consistently enriched in participants with UC. These findings were further supported by an external validation dataset comprising 1,716 gut metagenomes from five independent IBD cohorts, highlighting the reproducibility of oral microbial signatures. In exploratory analyses, smoking history was associated with shifts in the oral microbiome toward a UC-like state in healthy controls, suggesting a possible environmental modifier of the oral-gut microbial axis. Collectively, our study identifies distinct oral microbial signatures and their potential translocation to the gut in IBD and PSC, underscoring the role of the oral- gut microbial axis in disease progression.

microbiology↗

bioRxiv2024

Rational Design of Live Biotherapeutic Products for the Prevention of Clostridioides difficile Infection

Clostridioides difficile infection (CDI) is one of the leading causes of healthcare- and antibiotic-associated diarrhea. While fecal microbiota transplantation (FMT) has emerged as a promising therapy for recurrent CDI, its exact mechanisms of action and long-term safety are not fully understood. Defined consortia of clonal bacterial isolates, known as live biotherapeutic products (LBPs), have been proposed as an alternative therapeutic option. However, the rational design of LBPs remains challenging. Here, we employ a computational pipeline and three independent metagenomic datasets to systematically identify microbial strains that have the potential to inhibit CDI. We first constructed the CDI-related microbial genome catalog, comprising 3,741 non-redundant metagenome-assembled genomes (nrMAGs) at the strain level. We then identified multiple potential protective nrMAGs that can be candidates for the design of microbial consortia targeting CDI, including strains from Dorea formicigenerans, Oscillibacter welbionis, and Faecalibacterium prausnitzii. Importantly, some of these potential protective nrMAGs were found to play an important role in the success of FMT, and the majority of the top protective nrMAGs can be validated by various previously reported findings. Our results demonstrate a computational framework for the rational selection of microbial strains targeting CDI, paving the way for the computational design of microbial consortia against other enteric infections.

microbiology↗

bioRxiv2024

SREBP-dependent regulation of lipid homeostasis is required for progression and growth of pancreatic ductal adenocarcinoma

Metabolic reprogramming is a necessary component of oncogenesis and cancer progression that solid tumors undergo when their growth outstrips local nutrient supply. The supply of lipids such as cholesterol and fatty acids is required for continued tumor cell proliferation, and oncogenic mutations stimulate de novo lipogenesis to support tumor growth. Sterol regulatory element-binding protein (SREBP) transcription factors control cellular lipid homeostasis by activating genes required for lipid synthesis and uptake. SREBPs have been implicated in the progression of multiple cancers, including brain, breast, colon, liver, and prostate. However, the role the SREBP pathway and its central regulator SREBP cleavage activating protein (SCAP) in pancreatic ductal adenocarcinoma (PDAC) has not been studied in detail. Here, we demonstrated that pancreas-specific knockout of Scap has no effect on mouse pancreas development or function, allowing for examination of the role for Scap in the murine KPC model of PDAC. Notably, heterozygous loss of Scap prolonged survival in KPC mice, and homozygous loss of Scap impaired PDAC tumor progression. Using subcutaneous and orthotopic xenograft models, we showed that SCAP is required for human PDAC tumor growth. Mechanistically, chemical or genetic inhibition of the SREBP pathway prevented PDAC cell growth under low serum conditions due to a lack of lipid supply. Highlighting the clinical importance of this pathway, the SREBP pathway is broadly required for cancer cell growth, SREBP target genes are upregulated in human PDAC tumors, and increased expression of SREBP targets genes is associated with poor survival in PDAC patients. Collectively, these results demonstrate that SCAP and the SREBP pathway activity are essential for PDAC cell and tumor growth in vitro and in vivo, identifying SCAP as a potential therapeutic target for PDAC. SIGNIFICANCEOur findings demonstrate that SREBP pathway activation is a critical part of the metabolic reprogramming that occurs in PDAC development and progression. Therefore, targeting the SREBP pathway has significant therapeutic potential.

cancer biology↗

bioRxiv2023

Optogenetic strategies for optimizing the performance of biosensors of membrane phospholipids in live cells

High-performance biosensors play a crucial role in elucidating the intricate spatiotemporal regulatory roles and dynamics of membrane lipids. However, enhancing their sensitivity and substrate-detecting capabilities remains a significant challenge. Here, we presented optogenetic-based strategies to optimize phospholipid biosensors. These strategies involved pre-sequestering unbound probes in the cell nucleus to minimize background signals in the cytoplasm. These stored probes could be released from the nucleus in response to blue light according to experimental requirements. Furthermore, we employed optically-controlled phase separation to generate punctate probes that amplified signals and facilitated the visualization of phospholipids in cells. These improved phospholipid biosensors hold great potential for enhancing our understanding of the spatiotemporal dynamics and regulatory roles of membrane lipids in live cells and this methodological insights might be valuable for developing other high-performance biosensors.

cell biology↗

bioRxiv2022

Pre-mRNA splicing inhibits m6A deposition, allowing longer mRNA half-life and flexible protein coding

Both pre-mRNA splicing and N6-methyladenosine (m6A) mRNA modification occur during transcription, enabling the potential crosstalk regulation between these two fundamental processes. The regional m6A location bias of avoiding splice site region, calls for an open hypothesis whether pre-mRNA splicing could affect m6A deposition. By deep learning modeling, we find that pre-mRNA splicing represses a proportion (4% to 32%) of m6A deposition at nearby exons. Experimental validation confirms such an inhibition as the m6A signal increases in mRNA once the host gene does not undergo pre-mRNA splicing to produce the same mRNA. Pre-mRNA splicing inhibited m6A sites tend to have higher m6A enhancers and lower m6A silencers locally than the m6A sites that are not inhibited. Moreover, this m6A deposition inhibition by pre-mRNA splicing shows high heterogeneity at different exons of mRNAs at genome-widely, with only a small proportion (12% to 15%) of exons showing strong inhibition, enabling stable mRNAs and flexible protein coding for important biological functions.

genomics↗

bioRxiv2022

Association Rule Mining of the Human Gut Microbiome

The human gut carries a vast and diverse microbial community that is essential for human health. Understanding the structure of this complex community requires quantitative approaches. Traditional co-occurrence and correlation analyses typically focus on pair-wise relationships and ignore higher-order relationships. Association rule mining (ARM) is a well-developed technique in data mining and has been applied to human microbiome data to identify higher-order relationships. Yet, existing attempts suffer from small sample sizes and low taxonomic resolution. Here we leverage the curatedMetagenomic Database (CMD) to resolve those issues. We first infer association rules from gut microbiome samples of a large cohort of healthy individuals (n=2,815) in CMD. Then we compare those rules with that inferred from samples of individuals with different diseases: Inflammatory Bowel Disease (IBD, n=768), Colorectal cancer (CRC, n=368), Impaired Glucose Tolerance (IGT, n=199), and Type 2 Diabetes (T2D, n=164). Finally, we demonstrate that using ARM as a feature selection tool can improve the performance of microbiome-based disease classification. Together, this study provides a comprehensive study of higher-order microbial relationships in the human gut microbiome and highlights the importance of incorporating association rules in microbiome-based disease classification.

microbiology↗

bioRxiv2022

Gut feelings: Associations of emotions and emotion regulation with the gut microbiome in women

Accumulating evidence suggests that positive and negative emotions, as well as emotion regulation processes, influence the onset and the progression of multiple human diseases. However, the underlying mechanisms connecting these emotion-related factors with physical health are not fully understood. Recent work linking the gut microbiome with both mental and physical health suggests it may be a potential pathway. Yet, its association with emotions and emotion regulation are understudied. In this study, we examined whether positive and negative emotions, as well as two emotion regulation strategies (i.e., cognitive reappraisal and suppression), were associated with the diversity, overall structure, and specific species/pathways of the gut microbiome in 206 healthy women. We found that the alpha diversity was negatively associated with suppression. Moreover, using multivariate analysis, we found that positive emotions were inversely associated with the relative abundance of Firmicutes bacterium CAG 94 and Ruminococcaceae bacterium D16, while negative emotions were directly related to relative abundance of these same species. Moreover, we found associations of emotions and emotion regulation with microbial metabolic pathways. For example, negative emotions were inversely related to biosynthesis of pantothenate, coenzyme A, and adenosine. Taken together, our findings offer human evidence supporting linkages of emotions and related regulatory processes with the gut microbiome. These findings highlight the critical importance of incorporating the human gut microbiome in our understanding of emotion-related factors and their associations with physical health.

microbiology↗

bioRxiv2022

Dissecting the Role of the Human Microbiome in COVID-19 via Metagenome-assembled Genomes

Coronavirus disease 2019 (COVID-19), primarily a respiratory disease caused by infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is often accompanied by gastrointestinal symptoms. However, little is known about the relation between the human microbiome and COVID-19, largely due to the fact that previous studies fail to provide high taxonomic resolution to identify microbes that likely interact with SARS-CoV-2 infection. Here we used whole-metagenome shotgun sequencing data together with assembly and binning strategies to reconstruct metagenome-assembled genomes (MAGs) from a total of 514 nasopharyngeal and fecal samples of patients with COVID-19 and controls. We reconstructed a total of 11,584 medium-and high-quality microbial MAGs and obtained 5,403 non-redundant MAGs (nrMAGs) with strain-level resolution. We found that, thanks to the high taxonomic resolution of nrMAGs, the gut microbiome signatures can accurately distinguish COVID-19 cases from healthy controls and predict the progression of COVID-19. Moreover, we identified a set of nrMAGs with a putative causal role in the clinical manifestations of COVID-19 and revealed their functional pathways that potentially interact with SARS-CoV-2 infection. The presented results highlight the importance of incorporating the human gut microbiome in our understanding of SARS-CoV-2 infection and disease progression. The genomic content of nrMAGs presented here has the potential to inform microbiome-based therapeutic developments for COVID-19 progression and post-COVID conditions.

microbiology↗

bioRxiv2022

A Computational Method to Dissect Colonization Resistance of the Gut Microbiota against Pathogens

The indigenous gut microbes have co-evolved with their hosts for millions of years. Those gut microbes play a crucial role in host health and disease. In particular, they protect the host against incursion by exogenous and often harmful microorganisms, a mechanism known as colonization resistance (CR). Yet, identifying the exact microbes responsible for the gut microbiota-mediated CR against a particular pathogen remains a fundamental challenge in microbiome research. Here, we develop a computational method --- Generalized Microbe-Phenotype Triangulation (GMPT) to systematically identify causal microbes that directly influence the microbiota-mediated CR against a pathogen. We systematically validate GMPT using a classical population dynamics model in community ecology, and then apply it to microbiome data from two mouse studies on C. difficile infection. The developed method will not only significantly advance our understanding of CR mechanisms but also pave the way for the rational design of microbiome-based therapies for preventing and treating enteric infections.

bioinformatics↗

bioRxiv2021

Gut Microbiota predicts Healthy Late-life Aging in Male Mice

Calorie restriction (CR) extends lifespan and retards age-related chronic diseases in most species. There is growing evidence that the gut microbiota has a pivotal role in host health and age-related pathological conditions. Yet, it is still unclear how CR and the gut microbiota are related to healthy aging. Here we report findings from a small longitudinal study of male C57BL/6 mice maintained on either ad libitum or mild (15%) CR diets from 21 months of age and tracked until natural death. We demonstrate that CR results in a significant reduction in frailty index (FI), a well-established indicator of aging. We observed significant alterations in bacterial load, diversity, and compositional patterns of the mouse gut microbiota during the aging process. Interrogating the FI-related microbial features using machine learning techniques, we show that gut microbial signatures from 21-month-old mice can predict the healthy aging of 30-month-old mice with reasonable accuracy. This study deepens our understanding of the links between CR, gut microbiota, and frailty in the aging process of mice.

microbiology↗

bioRxiv2021

Neuropilin-1 Mediates SARS-CoV-2 Infection in Bone Marrow-derived Macrophages

SARS-CoV-2 infection in human can cause medical complications across various tissues and organs. Despite of the advances to understanding the pathogenesis of SARS-CoV-2, its tissue tropism and interactions with host cells have not been fully understood. Existing clinical data have suggested possible SARS-CoV-2 infection in human skeleton system. In the present study, we found that authentic SARS-CoV-2 could efficiently infect human and mouse bone marrow-derived macrophages (BMMs) and alter the expression of macrophage chemotaxis and osteoclast-related genes. Importantly, in a mouse SARS-CoV-2 infection model that was enabled by the intranasal adenoviral (AdV) delivery of human angiotensin converting enzyme 2 (hACE2), SARS-CoV-2 was found to be present in femoral BMMs as determined by in situ immunofluorescence analysis. Using single-cell RNA sequencing (scRNA-Seq), we characterized SARS-CoV-2 infection in BMMs. Importantly, SARS-CoV-2 entry on BMMs appeared to be dependent on the expression of neuropilin-1 (NRP1) rather than the widely recognized receptor ACE2. It was also noted that unlike brain macrophages which displayed aging-dependent NRP1 expression, BMMs from neonatal and aged mice had constant NRP1 expression, making BMMs constantly vulnerable target cells for SARS-CoV-2. Furthermore, it was found that the abolished SARS-CoV-2 entry in BMM-derived osteoclasts was associated with the loss of NRP1 expression during BMM-to-osteoclast differentiation. Collectively, our study has suggested that NRP1 can mediate SARS-CoV-2 infection in BMMs, which precautions the potential impact of SARS-CoV-2 infection on human skeleton system.

microbiology↗

bioRxiv2020

An ancient deletion in the ABO gene affects the composition of the porcine microbiome by altering intestinal N-acetyl-galactosamine concentrations

We have generated a large heterogenous stock population by intercrossing eight divergent pig breeds for multiple generations. We have analyzed the composition of the intestinal microbiota at different ages and anatomical locations in > 1,000 6th- and 7th- generation animals. We show that, under conditions of exacerbated genetic yet controlled environmental variability, microbiota composition and abundance of specific taxa (including Christensenellaceae) are heritable in this monogastric omnivore. We fine-map a QTL with major effect on the abundance of Erysipelotrichaceae to chromosome 1q and show that it is caused by a common 2.3-Kb deletion inactivating the ABO acetyl-galactosaminyl-transferase gene. We show that this deletion is a trans-species polymorphism that is [≥]3.5 million years old and under balancing selection. We demonstrate that it acts by decreasing the concentrations of N-acetyl-galactosamine in the cecum thereby reducing the abundance of Erysipelotrichaceae strains that have the capacity to import and catabolize N-acetyl-galactosamine.

genetics↗