Type 1 diabetes mellitus (T1DM) is an autoimmune disease that can lead to severe diabetic complications. While the changes and correlations between gut microbiota and the pathogenesis of T1DM have been extensively studied, little is known about the benefits of interventions on gut bacterial communities, particularly using probiotics, for this disease. In the present study, we reported that the mice surviving after 5 months of streptozotocin (STZ) injection had reduced blood glucose level and recovered gut microbiota with increased Akkermansia muciniphila proportion. Gavage of heat-killed A. muciniphila increases the diversity of gut microbiota and elevated immune and metabolic signaling pathways in the intestine. Mechanistically, A. muciniphila treatment promoted the secretion of insulin-like growth factor 2 (IGF2) which subsequently activated IGF2 signaling in skeletal muscles and enhanced muscle and global metabolism. Our results suggest that the administration of heat-killed A. muciniphila could be a potential therapeutic strategy for T1DM and its associated hyperglycemia.

The graphical abstract illustrates the advanced capabilities of iNAP 2.0, an integrated network analysis platform designed for comprehensive metabolic interaction studies. iNAP 2.0 enables the calculation of various metabolic indices, including the PhyloMint complementarity and competition index, SMETANA (species metabolic interaction analysis) scores, and metabolic distance, facilitating in-depth analysis of metabolic complementarity and competition. It innovatively employs the random matrix theory (RMT) method to determine thresholds for constructing robust metabolic interaction networks. Additionally, the platform introduces PhyloMint PTM, which identifies potentially transferable metabolites between microbial interactions, integrating them into microbe-metabolite bipartite networks alongside traditional microbial interaction networks. This combined approach provides a holistic view of microbial metabolic exchanges, making iNAP 2.0 a powerful tool for studying microbial ecology and inferring its metabolic keystones.

The multifaceted interactions among the immune system, cancer cells and microbial components have established a novel concept of the immuno-oncology-microbiome (IOM) axis. Microbiome sequencing technologies have played a pivotal role in not only analyzing how gut microbiota affect local and distant tumors, but also providing unprecedented insights into the intratumor host-microbe interactions. Herein, we discuss the emerging trends of transiting from bulk-level to single cell- and spatial-level analyses. Moving forward with advances in biotechnology, microbial therapies, including microbiota-based therapies and bioengineering-inspired microbes, will add diversity to the current oncotherapy paradigm.

The well-known bioinformatic software USEARCH v12 was open sourced. Its meaning encourages the microbiome research community to constantly develop excellent bioinformatic software based on the codes. The open source and popularization of artificial intelligence (AI) will make a better infrastructure for microbiome research.

TCellSI is a novel method to evaluate T cell states via transcriptome data, using specific marker gene sets and a compiled reference spectrum. TCellSI calculates T cell state scores for eight states: quiescence, regulating, proliferation, helper, cytotoxicity, progenitor exhaustion, terminal exhaustion, and senescence, offering valuable insights into the immune environment.

Through integrative analysis of immune multiomics data and single-cell RNA-seq data, this study identifies lymphotoxin β receptor (LTBR) as a potential immune checkpoint of tumor-associated macrophages (TAMs). LTBR+ TAMs are associated with lung adenocarcinoma stages, immunotherapy failure, and poor prognosis. Mechanistically, LTΒR maintains TAM immunosuppressive activity and M2 phenotype by noncanonical nuclear factor kappa B and Wnt/β-catenin signaling pathways. Disruption of LTΒR in TAMs enhances the therapeutic effect of cancer immunotherapy.

Microbes play a significant role in human tumor development and profoundly impact treatment efficacy, particularly in immunotherapy. The respiratory tract extensively interacts with the external environment and possesses a mucosal immune system. This prompts consideration of the relationship between respiratory microbiota and lung cancer. Advancements in culture-independent techniques have revealed unique communities within the lower respiratory tract. Here, we provide an overview of the respiratory microbiota composition, dysbiosis characteristics in lung cancer patients, and microbiota profiles within lung cancer. We delve into how the lung microbiota contributes to lung cancer onset and progression through direct functions, sustained immune activation, and immunosuppressive mechanisms. Furthermore, we emphasize the clinical utility of respiratory microbiota in prognosis and treatment optimization for lung cancer.

Hi-C can obtain three-dimensional chromatin structure information and is widely used for genome assembly. We constructed the GutHi-C technology. As shown in the graphical abstract, it is a highly efficient and quick-to-operate method and can be widely used for human, livestock, and poultry gut microorganisms. It provides a reference for the Hi-C methodology of the microbial metagenome. DPBS, Dulbecco's phosphate-buffered saline; Hi-C, high-through chromatin conformation capture; LB, Luria-Bertani; NGS, next-generation sequencing; PCR, polymerase chain reaction; QC, quality control.

The Tumor Immunotherapy Gene Expression R package (tigeR) toolkit provides four distinct yet closely interconnected modules, including the Biomarker Evaluation module, Tumor Microenvironment Deconvolution module, Prediction Model Construction module, and Response Prediction module, to explore biomarkers and construct predictive models via built-in or custom immunotherapy gene expression data. With a comprehensive suite of functionalities, tigeR not only streamlines the analysis process but also catalyzes discoveries in the realm of tumor immunotherapy.

Overview of personalized dietary therapies. This flow chart exhibits the future prospect for integrating human microbiome and bio-medical research to revolutionize the precise personalized dietary therapies. With the development of artificial intelligence (AI), incorporating database may achieve personalized dietary therapies with high precision.

The OmicShare tools platform is a user-friendly online resource for data analysis and visualization, encompassing 161 bioinformatic tools. Users can easily track the progress of projects in real-time through an overview interface. The platform has a powerful interactive graphics engine that allows for the custom-tailored modification of charts generated from analyses. The visually appealing charts produced by OmicShare improve data interpretability and meet the requirements for publication. It has been acknowledged in over 4000 publications and is available in https://www.omicshare.com/tools/.

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.