FoodMicroDB: A microbiome database for composition and time‐series research in food

Abstract Microorganisms are crucial for food fermentation, preservation, and safety, directly impacting human health. The number of studies on the food microbiome has surged recently, along with a substantial increase in data. However, there is a notable lack of databases specialized for this field. To address this gap, we developed Food Microbiome Database (FoodMicroDB), a platform aimed at enhancing the reusability and accessibility of food microbiome data through comprehensive data management and data visualization tools. FoodMicroDB aggregates 6358 amplicon data from 108 meta‐taxonomic projects covering 62 foods, and harbors 4710 taxa of bacteria, archaea, and fungi. The collected data were consistently analyzed and curated, then visualized using versatile utilities, including unique tools for visualizing microbial composition and time‐series microbiome data. It also includes advanced modules for microbial abundance analysis, cross‐host abundance comparison, and cross‐food analysis. FoodMicroDB will be a valuable resource platform for the food microbiome research field. The database is freely accessible at: https://www.bic.ac.cn/FoodMicro/

Unveiling microbial communities with EasyAmplicon: A user‐centric guide to perform amplicon sequencing data analysis

Abstract The advent of next‐generation sequencing has revolutionized microbiome research, enabling in‐depth exploration of microbial communities through amplicon sequencing. The widespread adoption of sequencing across diverse fields, coupled with decreasing costs, underscores the critical need for validated, fully automated, reproducible, and adaptable analysis pipelines. However, analyzing these high‐throughput datasets often necessitates extensive bioinformatics expertize, hindering accessibility for many researchers. To address this challenge, in 2023 we developed EasyAmplicon, a comprehensive, user‐friendly pipeline that integrates popular tools such as USEARCH and VSEARCH, offering a streamlined workflow from raw data to results. Remarkably, EasyAmplicon has garnered significant recognition within a year, as evidenced by 127 citations to date. To further facilitate the researchers and enhance usability, we present a detailed protocol with a video recording that guides users through each step of the pipeline, including data preprocessing (quality filtering, chimera removal), amplicon sequence variant analysis, diversity analysis, and data visualization. The protocol is designed for ease of use, with each step documented, allowing researchers to execute the workflow without requiring complex scripting skills. The EasyAmplicon pipeline is freely available on GitHub (https://github.com/YongxinLiu/EasyAmplicon)