The cover of iMeta's inaugural issue. The galaxy represents the complexity and value of bioinformatics and metagenomics. DNA, which represents genetic components that guide biological diversity, is at the center of the galaxy. The spiral arms are the microbiome welcoming scientists from all over the world to make novel discoveries. Let us usher in the metaverse era of the microbiome.

High prevalence of gut Prevotella enterotype in nomadic population. Higher microbial diversity is observed in nomadic people with gut Prevotella enterotype. Stable Prevotella enterotype in nomadic people during seasonal shift. Gut Prevotella enterotype might contribute to human adaptation to high-plateau environment.

de Bruijn graph-based sequence assembly approaches have been an essential part of the broad application of sequencing methods, especially in microbiome research. It can be used to efficiently represent sequencing data in a format that is highly scalable and can be extended and modified to address different research questions. de Bruijn graph-based analysis methods have been developed for comparative genomics, the identification of genetic variants, and for large-scale searching of unassembled sequencing data. The de Bruijn graph data structure will continue to be a central component of sequence assembly and analysis approaches in the future.

Plant-associated microbiota affects diverse aspects of plant fitness and development, whereas how plants positively reshape a beneficial microbiota to enhance fitness is less studied. We reviewed the current understanding of the genetic mechanisms underlying plant-mediated reshaping of the microbiota in response to stresses. Due to the complexity of the microbiota, it is challenging to confirm a causal link between microbiota changes and host phenotypes. We also reviewed the approaches to study the effect of microbiota changes on plant phenotypes.

Metagenome benefits for homologous sequence supplement for protein 3D structure. Metagenome utilization efficiency shows a divergent distribution of proteins. Marginal effect model also quantifies this divergent distribution of proteins. For mining homologous sequences, targeted approach outperforms untargeted approach. Current metagenome data is not enough for modeling 3D structure for all proteins.

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.

We presented the first computational tool, termed DeepKla, to identify Kla sites in rice. Supervized embedding layer, convolutional neural network, bidirectional gated recurrent units, and attention mechanism layer were applied to train the model. A robust, generalized, and convenient web-server of DeepKla was established at http://lin-group.cn/server/DeepKla.

Parallel‐Meta Suite (PMS) is an easy‐to‐use software package for fast and comprehensive microbiome data analysis on multiple platforms. PMS covers a wide array of functions for data preprocessing, statistics, visualization by state‐of‐the‐art algorithms. The entire procedure of PMS is optimized by a parallel computing scheme that enables the rapid processing of thousands of microbiomes

Soil fungal richness mediates the bacterial community assembly. Stochastic assembly processes decreased with increasing fungal richness. Increase in aridity reduced bacterial α‐diversity. Our results further suggest that the predicted increase in aridity conditions due to climate change will reduce bacterial α-diversity, particularly in desert soils and subsurface layer, and induce more negative species associations. Together, our study represents a significant advance in linking soil fungi to the mechanisms underlying bacterial biogeographic patterns and community assembly in arid ecosystems under climate aridity and land-use change scenarios.

A deep learning framework was developed to predict community compositions from species assemblages. The framework does not require knowing any microbial dynamics. Validation in various data shows accurate predictions.

We propose that dietary intervention can be a solution to mass Cd poisoning. Dietary licorice effectively reduced mouse blood Cd by >50% within a month. Licorice intake induced Cd accumulation and Mt1 expression in mice liver. Licorice intake modulated mice gut microbiota and metabolism. Overall dietary licorice substantially improved mice fitness under Cd stress.

MetOrigin provides the quick identification of microbiota-related metabolites and their metabolic functions in metabolomics studies. MetOrigin integrates statistical and biological correlations using Sankey network visualization to identify specific microbes associated with metabolites of interest. MetOrigin is a web server of microbiome and metabolome data integration analysis, and it is freely available at http://metorigin.met-bioinformatics.cn/.