The figure shows side-by-side quality comparison of the data before and after preprocessing using fastp 1.0. As can be seen from this figure, the data quality has been significantly improved after fastp processing. The Q20 ratio and Q30 ratio increased, and the GC base ratio returned to balance.

Type 2 Diabetes Mellitus (T2DM) is a growing global health concern that is associated with severe complications including diabetic tendinopathy. In this study, we found that T2DM patients had a significantly higher prevalence of tendon surgery compared to non-T2DM patients, which were alongside impaired ECM and cell adhesion. Notably, metformin-treated T2DM patients had a lower prevalence of tendon surgery compared to other medications, along with improved tendon fiber structure, downregulation of tendon damage marker MMP3, and upregulation of HES1, a Notch signaling effector gene. Metformin also activates Notch signaling in cultured tenocytes, and tendons from diabetic mice and aged monkey. These findings highlight metformin's potential to protect tendons by activating Notch signaling, offering novel insights into its therapeutic benefits beyond glucose regulation.

Conventional single-cell analytical approaches frequently fail to incorporate critical phenotypic indicators such as malignancy status, consequently restricting their biological interpretability within complex tumor microenvironments. To overcome this fundamental limitation, we developed Single-Cell and Tissue Phenotype prediction (SCTP), an innovative multimodal fusion framework that combines machine learning-enhanced deep learning architecture with phenotypic, cellular, and spatial data to achieve continuous quantification of malignancy at single-spot resolution. Our comprehensive evaluations demonstrate that SCTP consistently surpasses current state-of-the-art methods in malignant region identification across diverse tumor types through multiple-performance metrics. As a specific application, we implemented SCTP for colorectal cancer (SCTP-CRC), successfully achieving three key objectives: precise identification of CRC-associated cells, high-resolution mapping of their spatial architecture, and reliable detection of early-stage biomarkers including MUC2 and MMP2. Overall, SCTP establishes a powerful unified platform that effectively connects microscopic cellular characteristics with macroscopic phenotypic manifestations, significantly advancing tumor microenvironment analysis and supporting clinical translation in precision oncology.

Prophages are ubiquitously present in bacterial genomes, significantly influencing host physiological and ecological functions. We present Prophage SOS-dependency Predictor (PSOSP), a novel bioinformatics tool that predicts prophages induction modes by analyzing the Heterology Index (HI) of LexA protein binding to target DNA, classifying prophages into SOS-dependent prophages (SdPs) and SOS-independent prophages (SiPs). PSOSP was experimentally validated to accurately distinguish SdPs from SiPs in a test set, achieving 100% sensitivity and specificity. Applying PSOSP to 49,333 complete bacterial genomes, we inferred prophage induction modes in 15,493 bacterial genomes and identified 11,806 SiPs. These SiPs are widely distributed across 145 bacterial genera and exhibit distinct genomic features compared to SdPs. Correspondingly, the hosts of these two prophage types are hypothesized to differ in their physiological characteristics. These findings, powered by PSOSP, provide not only novel insights into the diverse induction mechanisms but also a critical methodology for future phage–host interaction studies.

Gemcitabine resistance drives bladder cancer recurrence and progression. Using high-throughput drug screening in bladder cancer cells, we identified Bavachalcone (Bava) as a potent gemcitabine sensitizer. Mechanistically, Bava simultaneously targets transferrin receptor (TFRC) and epidermal growth factor receptor (EGFR). It competes with transferrin (Tf) for TFRC binding, reducing cellular iron influx, and inhibits EGFR-mediated phosphorylation of TFRC at tyrosine 20 (Y20). These actions disrupt mitochondria iron utilization and impairs respiration. The combination of Bava and gemcitabine synergistically inhibits the repair of gemcitabine-induced DNA damage, while suppressing the iron-dependent ATR-CHEK1-E2F1 pathway and downregulating RRM1 expression. Patient-derived xenograft models confirmed the superior antitumor efficacy of the Bava-gemcitabine co-treatment compared to monotherapies. Clinically, elevated TFRC and RRM1 expression correlates with poor prognosis, supporting their utility as biomarkers of bladder cancer. Our study identified Bava as the first small-molecule TFRC inhibitor that overcomes gemcitabine resistance through iron modulation, providing both mechanistic insights and a promising therapeutic strategy for bladder cancer.

The human microbiome is now recognized as a central regulator of cancer biology, intricately shaping tumor development, immune dynamics, and therapeutic response. This comprehensive review delineates the multifaceted roles of bacteria, viruses, and fungi in modulating the tumor microenvironment and systemic immunity across diverse cancer types. We synthesize current evidence on how microbial dysbiosis promotes carcinogenesis via chronic inflammation, metabolic reprogramming, genotoxic stress, immune evasion, and epigenetic remodeling. This review emphasizes organ-specific microbiome signatures and highlights their potential as non-invasive biomarkers for early detection, treatment stratification, and prognosis. Furthermore, we explore the impact of intratumoral microbiota on cancer therapies, uncovering how microbial metabolites and host–microbe interactions shape therapeutic efficacy and resistance. Finally, advances in microbiome-targeted strategies, such as probiotics, fecal microbiota transplantation, and engineered microbes offer new avenues for adjunctive cancer therapy. This review provides a roadmap for future investigation and underscores the transformative promise of microbiome modulation in cancer prevention and treatment.

AI-driven and computation-based high-throughput methods were developed to mine novel dipeptidyl peptidase IV (DPP-IV) inhibitory peptides from hemp seed proteins. The identified peptide VAMP demonstrates a glucose-lowering effect through dual mechanisms: inhibition of DPP-IV activity and selective promotion of intestinal Akkermansia muciniphila growth.

This study proposes an innovative therapeutic approach by combining RRM2 gene knockout with a nanocarrier system, significantly enhancing the efficacy of radiofrequency ablation for hepatocellular carcinoma. The study developed a tumor microenvironment-responsive nanosystem that achieves synergistic effects through SPIO-mediated and RRM2 knockout-induced ferroptosis, along with precise targeting of tumor microenvironment regulation.

This study demonstrates that hypoacylated, rough-type lipopolysaccharides (LPS) derived from Akkermansia muciniphila strain HW07 (ALPS) alleviates diet-induced obesity. ALPS acts as a weak TLR4 agonist and significantly reduces weight gain, improves metabolic parameters, and restores gut barrier integrity in obese mice. The antiobesity effects are mediated primarily through activation of the TLR4−IL-23−IL-22 immune axis, leading to increased IL-22 production. ALPS also reshapes the gut microbiota (e.g., increases SFB, C. cocleatum) and elevates beneficial short-chain fatty acids. These findings identify A. muciniphila LPS as a safe and effective therapeutic candidate for metabolic disorders via TLR4-dependent IL-22 induction. The diagram was created using Microsoft PowerPoint and https://BioRender.com.

Polycystic ovary syndrome (PCOS) is a prevalent endocrine and reproductive disorder affecting women of reproductive age. While the gut microbiota has been implicated in PCOS pathophysiology, the role of microbial-derived metabolites as mediators of host–microbe interactions remains poorly defined. Here, we integrated untargeted gut metabolomics with metagenomic profiling in patients with PCOS and identified a marked depletion of 3,4-dihydroxyphenylacetic acid (DHPAA), a flavonoid-derived microbial catabolite. Oral administration of DHPAA ameliorated PCOS-like phenotypes in two mouse models by suppressing bone morphogenetic protein signaling and reducing anti-Müllerian hormone (AMH) levels. We found that DHPAA production depends on gut microbial degradation of dietary flavonoids. We further identified a bacterial species, Streptococcus thermophilus, consistently depleted in PCOS across two human cohorts and a mouse model, restored DHPAA levels and improved reproductive outcomes in mice. Conversely, a β-galactosidase-deficient mutant of S. thermophilus failed to confer these benefits, highlighting β-galactosidase as a critical enzyme in DHPAA biosynthesis. Our findings establish DHPAA as a key microbial metabolite linking diet, microbiota, and reproductive health, and propose its potential as a novel therapeutic candidate for PCOS.

Porcine deltacoronavirus (PDCoV) is a significant pathogen of swine with a global distribution, leading to severe gastrointestinal disease and substantial economic losses. Furthermore, PDCoV poses a potential threat to human health, as evidenced by the recent identification of three cases of infection in Haitian children. This study aimed to investigate the effects of PDCoV infection on host intestinal microbiota and bile acid metabolism, as well as the antiviral effects of lithocholic acid (LCA) in vitro and in vivo. Our results revealed that PDCoV infection caused microbiota dysbiosis in piglets, significantly reducing the intestinal abundance of Bacteroides fragilis (B. fragilis), a reduction that correlated with disruptions in bile acid metabolism. Colonization with bile salt hydrolase (BSH)-producing B. fragilis increased the levels of unconjugated bile acids and inhibited PDCoV infection, highlighting the role of microbiota-associated bile acid metabolism in viral pathogenesis. LCA, a prominent unconjugated bile acid, was shown to effectively inhibit PDCoV infection in porcine small intestinal epithelial cells and porcine intestinal enteroids. Notably, LCA inhibited PDCoV replication independently of bile acid receptor signaling and innate immune modulation. Mechanistic studies indicated that LCA prevents PDCoV infection by disrupting the viral entry process, specifically inhibiting the binding between the PDCoV spike protein and its cellular receptor, aminopeptidase N. In vivo experiments further confirmed that LCA significantly inhibited PDCoV infection in piglets. These results collectively highlight the potential of LCA as a therapeutic agent against PDCoV by targeting and disrupting the viral entry process, providing a novel strategy to control zoonotic PDCoV infections.

Extensive herbicide residues in the black soil of northeastern China are considered a significant agricultural pollution threat, yet effective bioremediation of this complex and persistent mixture remains a challenge. We identified 16 bacterial species that associated with these herbicide residues in situ, nine of which were culturable and could degrade multiple herbicides. From these strains, we constructed a four-member synthetic microbial community (SynCom) that degrades multiple herbicides, stabilizes colonization, increases soil bacterial biodiversity, and alters soil enzyme activity. Under laboratory conditions, the SynCom degraded eight herbicides within 48 h with >60% efficiency, and accumulated carbon on the cell surface of the constituent species. In black soil microcosm trials, the SynCom achieved 60%−99% degradation efficiency of the endogenous herbicides over 35 days and was able to consistently maintain biomass above 104 cfu/g soil. Additionally, SynCom application resulted in an accumulation of carbohydrate-active enzymes and microbial necromass-associated carbon, which suggests activation of soil microbial carbon metabolism. In support of this, metagenomic analyses identified a significant increase in the abundance of genes involved in the tricarboxylic acid cycle, pyruvate metabolism, and glycolysis. This SynCom represents a compelling bioremediation solution that simultaneously improves soil microbial carbon metabolism activity in polluted soils.

EasyMetagenome is a user-friendly shotgun metagenomics pipeline designed for comprehensive microbiome analysis, supporting quality control, host removal, read-based, assembly-based, binning, genome and pan-genome analysis. It offers customizable settings, data visualizations, and parameter explanations. The pipeline is freely available at https://github.com/YongxinLiu/EasyMetagenome.

The concept of “gut–X axis”: the intestine and intestinal microbiota are proven to be able to modulate the pathophysiologic progressions of the extraintestinal organs' diseases. The bioactive chemicals and/or intestinal immune cells can translocate into the circulatory system and other organs and influence the immune reactions, metabolic status, cells physiology, and so forth of extraintestinal organs, finally regulating these organs' homeostasis. Meanwhile, other organs may reversely impact the intestine, namely such regulatory axis is bidirectional.

Fastp is a widely adopted tool for FASTQ data preprocessing and quality control. It is ultrafast and versatile and can perform adapter removal, global or quality trimming, read filtering, unique molecular identifier processing, base correction, and many other actions within a single pass of data scanning. Fastp has been reconstructed and upgraded with some new features. Compared to fastp 0.20.0, the new fastp 0.23.2 is even 80% faster.

Representative visualization results of ImageGP. ImageGP supports 16 types of images and four types of online analysis with up to 26 parameters for customization. ImageGP also contains specialized plots like volcano plot, functional enrichment plot for most omics-data analysis, and other 4 specialized functions for microbiome analysis. Since 2017, ImageGP has been running for nearly 5 years and serving 336,951 visits from all over the world. Together, ImageGP (http://www.ehbio.com/ImageGP/) is an effective and efficient tool for experimental researchers to comprehensively visualize and interpret data generated from wet-lab and dry-lab.

The ggtree object is designed to store phylogenetic tree and associated data, and the object itself is a graphic object that can be rendered as an image file. This work will increase the reproducibility and reusability of phylogenetic data, as well as facilitate integrative and comparative studies.

A new release of PhyloSuite, capable of conducting tree-based analyses. Detailed guidelines for each step of phylogenetic and tree-based analyses, following the “What? Why? and How?” structure. This protocol will help beginners learn how to conduct multilocus phylogenetic analyses and help experienced scientists improve their efficiency.