PCycDB: a comprehensive and accurate database for fast analysis of phosphorus cycling genes

• DOI: 10.1186/s40168-022-01292-1
• Publication Date: 2022-07-04T00:02:31Z
• Authors: Jiaxiong Zeng; Qichao Tu; Xiaoli Yu; Lu Qian; Cheng Wang; Longfei Shu; Fei Liu; Shengwei Liu; Zhijian Huang; Jianguo He; Qingyun Yan; Zhili He
• Keywords: 0301 basic medicine; Bacteria; Databases, Factual; Metagenome sequencing data; Microbiota; QR100-130; Comprehensiveness; Methodology; Phosphorus; Phosphorus cycling gene/microorganism; Database; Microbial ecology; 03 medical and health sciences; 13. Climate action; Metagenome; Accuracy

Abstract Background Phosphorus (P) is one of the most essential macronutrients on the planet, and microorganisms (including bacteria and archaea) play a key role in P cycling in all living things and ecosystems. However, our comprehensive understanding of key P cycling genes (PCGs) and microorganisms (PCMs) as well as their ecological functions remains elusive even with the rapid advancement of metagenome sequencing technologies. One of major challenges is a lack of a comprehensive and accurately annotated P cycling functional gene database.

Results In this study, we constructed a well-curated P cycling database (PCycDB) covering 139 gene families and 10 P metabolic processes, including several previously ignored PCGs such as pafA encoding phosphate-insensitive phosphatase, ptxABCD (phosphite-related genes), and novel aepXVWPS genes for 2-aminoethylphosphonate transporters. We achieved an annotation accuracy, positive predictive value (PPV), sensitivity, specificity, and negative predictive value (NPV) of 99.8%, 96.1%, 99.9%, 99.8%, and 99.9%, respectively, for simulated gene datasets. Compared to other orthology databases, PCycDB is more accurate, more comprehensive, and faster to profile the PCGs. We used PCycDB to analyze P cycling microbial communities from representative natural and engineered environments and showed that PCycDB could apply to different environments.

Conclusions We demonstrate that PCycDB is a powerful tool for advancing our understanding of microbially driven P cycling in the environment with high coverage, high accuracy, and rapid analysis of metagenome sequencing data. The PCycDB is available at https://github.com/ZengJiaxiong/Phosphorus-cycling-database.