کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
3416324 1593696 2016 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Molecular identification of potential denitrifying bacteria and use of D-optimal mixture experimental design for the optimization of denitrification process
موضوعات مرتبط
علوم زیستی و بیوفناوری ایمنی شناسی و میکروب شناسی میکروب شناسی
پیش نمایش صفحه اول مقاله
Molecular identification of potential denitrifying bacteria and use of D-optimal mixture experimental design for the optimization of denitrification process
چکیده انگلیسی


• Three probiotic strains were identified as Agrococcus sp. LN828197, C. sakazakii LN828198 and P. pentosaceus LN828199.
• These strains harbored denitrifing genes.
• The most predictable reduction of nitrate was 100% with 14.98% of COD consumption and 5.57 mg/l nitrite accumulation.
• The D-optimal mixture experimental design is the an tools for optimizing the proportion combination in each assay.

Three bacterial strains (TE1, TD3 and FB2) were isolated from date palm (degla), pistachio and barley. The presence of nitrate reductase (narG) and nitrite reductase (nirS and nirK) genes in the selected strains was detected by PCR technique. Molecular identification based on 16S rDNA sequencing method was applied to identify positive strains. In addition, the D-optimal mixture experimental design was used to optimize the optimal formulation of probiotic bacteria for denitrification process.Strains harboring denitrification genes were identified as: TE1, Agrococcus sp LN828197; TD3, Cronobacter sakazakii LN828198 and FB2, Pedicoccus pentosaceus LN828199. PCR results revealed that all strains carried the nirS gene. However only C. sakazakii LN828198 and Agrococcus sp LN828197 harbored the nirK and the narG genes respectively. Moreover, the studied bacteria were able to form biofilm on abiotic surfaces with different degree.Process optimization showed that the most significant reduction of nitrate was 100% with 14.98% of COD consumption and 5.57 mg/l nitrite accumulation. Meanwhile, the response values were optimized and showed that the most optimal combination was 78.79% of C. sakazakii LN828198 (curve value), 21.21% of P. pentosaceus LN828199 (curve value) and absence (0%) of Agrococcus sp LN828197 (curve value).

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Microbial Pathogenesis - Volume 93, April 2016, Pages 158–165
نویسندگان
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