Literature DB >> 21105982

Diversity, abundance and characterization of ruminal cysteine phytases suggest their important role in phytate degradation.

Huoqing Huang1, Rui Zhang, Dawei Fu, Jianjie Luo, Zhongyuan Li, Huiying Luo, Pengjun Shi, Peilong Yang, Qiyu Diao, Bin Yao.   

Abstract

A novel class of cysteine phytase showing ability to degrade phytate has recently been isolated from rumen bacteria. To expand our knowledge of this enzyme class, a total of 101 distinct cysteine phytase gene fragments were identified from the ruminal genomic DNA of Bore goats and Holstein cows, and most of them shared low identities (< 50%) with known sequences. By phylogenetic analysis, these sequences were separated into three clusters that showed substantial diversity. The two most abundant cysteine phytase genes of goat rumens were cloned and their protein products were characterized. Four findings were revealed based on our results. (i) Compared with soil and water environment, where β-propeller phytase is the most important phytate-degrading enzyme, cysteine phytase is the major phytate-degrading enzyme in the anaerobic ruminal environment. (ii) Cysteine phytase fragments in the rumen contents of goat and cow have the same diversity profile, although most of the sequences and their abundance differ in the two species. (iii) Each species has their respective high-abundance genes, which may play major roles for phytate degradation. (iv) Compared with previously reported cysteine phytases that have pH optimum at 4.5, the pH optima of the two most abundant secreted goat cysteine phytases are 6.5 and 6.0, which are within the pH range found in the rumens. This study provides valuable information about the diversity, abundance and enzymatic properties of the ruminal cysteine phytases and emphasizes the important role(s) of these cysteine phytases probably in the terrestrial cycle of phosphorus.
© 2010 Society for Applied Microbiology and Blackwell Publishing Ltd.

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Year:  2010        PMID: 21105982     DOI: 10.1111/j.1462-2920.2010.02379.x

Source DB:  PubMed          Journal:  Environ Microbiol        ISSN: 1462-2912            Impact factor:   5.491


  7 in total

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Journal:  Curr Microbiol       Date:  2011-08-19       Impact factor: 2.188

2.  Screening and Characterization of Phytases from Bacteria Isolated from Chilean Hydrothermal Environments.

Authors:  Milko A Jorquera; Stefanie Gabler; Nitza G Inostroza; Jacquelinne J Acuña; Marco A Campos; Daniel Menezes-Blackburn; Ralf Greiner
Journal:  Microb Ecol       Date:  2017-08-31       Impact factor: 4.552

3.  Comparative quantitative analysis of gene expression profiles of glycoside hydrolase family 10 xylanases in the sheep rumen during a feeding cycle.

Authors:  Zhongyuan Li; Heng Zhao; Peilong Yang; Junqi Zhao; Huoqing Huang; Xianli Xue; Xinshang Zhang; Qiyu Diao; Bin Yao
Journal:  Appl Environ Microbiol       Date:  2012-12-07       Impact factor: 4.792

4.  Abundance and genetic diversity of microbial polygalacturonase and pectate lyase in the sheep rumen ecosystem.

Authors:  Peng Yuan; Kun Meng; Yaru Wang; Huiying Luo; Huoqing Huang; Pengjun Shi; Yingguo Bai; Peilong Yang; Bin Yao
Journal:  PLoS One       Date:  2012-07-17       Impact factor: 3.240

5.  Structural and biochemical analysis of a unique phosphatase from Bdellovibrio bacteriovorus reveals its structural and functional relationship with the protein tyrosine phosphatase class of phytase.

Authors:  Robert J Gruninger; John Thibault; Michael J Capeness; Robert Till; Steven C Mosimann; R Elizabeth Sockett; Brent L Selinger; Andrew L Lovering
Journal:  PLoS One       Date:  2014-04-09       Impact factor: 3.240

6.  Relationship between the True Digestibility of Dietary Calcium and Gastrointestinal Microorganisms in Goats.

Authors:  Yuehui Liu; Ali Mujtaba Shah; Lizhi Wang; Lei Jin; Zhisheng Wang; Bai Xue; Quanhui Peng
Journal:  Animals (Basel)       Date:  2020-05-18       Impact factor: 2.752

7.  Structure- and context-based analysis of the GxGYxYP family reveals a new putative class of glycoside hydrolase.

Authors:  Daniel J Rigden; Ruth Y Eberhardt; Harry J Gilbert; Qingping Xu; Yuanyuan Chang; Adam Godzik
Journal:  BMC Bioinformatics       Date:  2014-06-17       Impact factor: 3.169

  7 in total

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