title: MIPE: A metagenome-based community structure explorer and SSU primer evaluation tool.
abstract: An understanding of microbial community structure is an important issue in the field of molecular ecology. The traditional molecular method involves amplification of small subunit ribosomal RNA (SSU rRNA) genes by polymerase chain reaction (PCR). However, PCR-based amplicon approaches are affected by primer bias and chimeras. With the development of high-throughput sequencing technology, unbiased SSU rRNA gene sequences can be mined from shotgun sequencing-based metagenomic or metatranscriptomic datasets to obtain a reflection of the microbial community structure in specific types of environment and to evaluate SSU primers. However, the use of short reads obtained through next-generation sequencing for primer evaluation has not been well resolved. The software MIPE (MIcrobiota metagenome Primer Explorer) was developed to adapt numerous short reads from metagenomes and metatranscriptomes. Using metagenomic or metatranscriptomic datasets as input, MIPE extracts and aligns rRNA to reveal detailed information on microbial composition and evaluate SSU rRNA primers. A mock dataset, a real Metagenomics Rapid Annotation using Subsystem Technology (MG-RAST) test dataset, two PrimerProspector test datasets and a real metatranscriptomic dataset were used to validate MIPE. The software calls Mothur (v1.33.3) and the SILVA database (v119) for the alignment and classification of rRNA genes from a metagenome or metatranscriptome. MIPE can effectively extract shotgun rRNA reads from a metagenome or metatranscriptome and is capable of classifying these sequences and exhibiting sensitivity to different SSU rRNA PCR primers. Therefore, MIPE can be used to guide primer design for specific environmental samples.
authors.affiliation: Department of Microbiology and Microbial Engineering, School of Life Sciences, Fudan University, Shanghai, People's Republic of China.
authors.forename: Bin
authors.initials: B
authors.lastname: Zou
authors.affiliation: Department of Microbiology and Microbial Engineering, School of Life Sciences, Fudan University, Shanghai, People's Republic of China.
authors.forename: JieFu
authors.initials: J
authors.lastname: Li
authors.affiliation: Department of Microbiology and Microbial Engineering, School of Life Sciences, Fudan University, Shanghai, People's Republic of China.
authors.forename: Quan
authors.initials: Q
authors.lastname: Zhou
authors.affiliation: Department of Microbiology and Microbial Engineering, School of Life Sciences, Fudan University, Shanghai, People's Republic of China.
authors.forename: Zhe-Xue
authors.identifier: http://orcid.org/0000-0002-7561-8572
authors.initials: ZX
authors.lastname: Quan
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D017931:DNA Primers; D054892:Metagenome / Q000235:genetics*; D056186:Metagenomics / Q000379:methods*; D064307:Microbiota / Q000235:genetics*; D016133:Polymerase Chain Reaction / Q000379:methods; D012335:RNA, Ribosomal / Q000235:genetics*; D015203:Reproducibility of Results; D012984:Software
chemical_list: D017931:DNA Primers; D012335:RNA, Ribosomal