Improved sensitivity, accuracy and prediction provided by a high-performance liquid chromatography screen for the isolation of phytase-harbouring organisms from environmental samples.
Improved sensitivity, accuracy and prediction provided by a high-performance liquid chromatography screen for the isolation of phytase-harbouring organisms from environmental samples.
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DOI:
10.1111/1751-7915.13733
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发表时间:
2021-07
影响因子:
5.7
通讯作者:
Brearley CA
中科院分区:
文献类型:
--
作者:
Rix GD;Todd JD;Neal AL;Brearley CA
HPLC‐based screening of soil identifies Multiple Inositol Polyphosphate Phosphatase as a contributor to aggregate soil phytase activity. HPLC also reveals the position of attack on phytate by different histidine phosphatases and affords opportunity for isolation of phytases for biotechnological use from other environments. HPLC methods are shown to be of predictive value for classification of phytase activity of aggregate microbial communities and pure cultures. Applied in initial screens, they obviate the problems of ‘false‐positive’ detection arising from impurity of substrate and imprecision of methodologies that rely on phytate‐specific media. In doing so, they simplify selection of candidates for biotechnological applications. Combined with 16S sequencing and simple bioinformatics, they reveal diversity of the histidine phosphatase class of phytases most commonly exploited for biotechnological use. They reveal contribution of multiple inositol‐polyphosphate phosphatase (MINPP) activity to aggregate soil phytase activity, and they identity Acinetobacter spp. as harbouring this prevalent soil phytase activity. Previously, among bacteria MINPP was described exclusively as an activity of gut commensals. HPLC methods have also identified, in a facile manner, a known commercially successful histidine (acid) phosphatase enzyme. The methods described afford opportunity for isolation of phytases for biotechnological use from other environments. They reveal the position of attack on phytate by diverse histidine phosphatases, something that other methods lack.
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影响因子:
3.7
作者:
da Silva, Caio Abercio;Callegari, Marco Aurelio;Hermes, Rafael
通讯作者:
Hermes, Rafael
影响因子:
9.5
作者:
Katoh K;Rozewicki J;Yamada KD
通讯作者:
Yamada KD
DOI:
10.1016/j.ijfoodmicro.2009.07.015
发表时间:
2009-09-30
影响因子:
5.4
作者:
Haros, Monika;Carlsson, Nils-Gunnar;Andlid, Thomas
通讯作者:
Andlid, Thomas
影响因子:
3.9
作者:
GREINER, R;KONIETZNY, U;JANY, KD
通讯作者:
JANY, KD
影响因子:
9.8
作者:
Chen, Xiaodong;Jiang, Nan;Chen, Lijun
通讯作者:
Chen, Lijun