With the current accumulation of metagenome data,it is possible to build a database of rigorously selected metagenomic samples (also referred as “metagenomic communities” here)of interests.Any metagenomic samples could then be searched against this database to find the most similar sample(s).However,on one hand,current databases with a large number of metagenomic samples mostly serve as data repositories but not well annotated database,and they only offer little functionality for analysis.On the other hand,the few available methods to measure the similarity of metagenomic data could only compare a few pre-defined set of metagenome.It has long been intriguing scientists to effectively find similar microbial communities from a large repository,to know the meta-information of these samples and to examine how similar these samples are.In this study,we have proposed a novel system,Meta-Mesh (http://www.meta-mesh.org/),which includes a database and its companion analysis system that could systematically and efficiently search similar metagenomic samples.In the database part,we have collected more than 10,000high quality and well annotated metagenomic samples from the public domain and in-house facilities.The analysis part includes a list of tools which could accept metagenomic samples,build taxonomical annotations,and then search for similar samples against its carefully selected,well-organized and annotated database by a fast scoring function.It has a multi-thread submission portal and a well-designed data management client for easy submission of large and complex data sets and integrates a variety of viewers to provide a visualization solution for result analysis.Users can also use Meta-Mesh to compare their samples and get a similar score matrix.In the Meta-Mesh online service work,user access is protected to ensure data privacy.Meta-Mesh would serve as a database and data analysis system to quickly parse and identify similar metagenomic samples from a large pool of well annotated samples.