Screening of Cellulase-producing Bacteria,Whole-gene Analysis,and Optimization of the Enzyme Production Process for the Functional Bacterium NF-101
Northern China is a major agricultural region,primarily producing cereal crops,which are associated with large amounts of residual straw.To efficiently utilize this natural agricultural resource and identify efficient cellulose-degrading bacteria,100 samples were collected from 20 sites in three northeastern provinces.After preliminary screening,2 052 strains capable of decomposing cellulose were isolated,which were provisionally identified as 1 207 strains of bacteria,598 strains of mold,and 195 strains of actinomycetes.These strains were stored in an ultra-low temperature freezer at-80 ℃ for subsequent establishment of a functional cellulase-degrading strain library.After re-screening,16 functional bacteria with high cellulase production ability were obtained,which were identified based on 16S rDNA analysis and physiological and biochemical identification as Serratia marcescens,Bacillus licheniformis,and halotolerant Bacillus,among which B.licheniformis NF-101 was found to be characterized by the most efficient enzyme production.Following single-factor and response surface optimization,the optimal enzyme-producing medium for cultivating NF-101 was identified as a medium comprising sodium carboxymethylcellulose 0.75 wt.％,peptone 0.6 wt.％,potassium dihydrogen phosphate 0.2 wt.％,and magnesium sulfate 0.05 wt.％.The optimal process conditions were a 4％inoculation amount,initial pH of 7.0,temperature of 37 ℃,and incubation time of 72 h.Optimized filter enzyme activity reached 181.22 U/mL,which represented an approximate 3.63-fold increase compared with that prior to optimization.Whole-gene analysis of NF-101 proved that it was a dominant strain for efficient cellulase-mediated degradation.It also provided information on a dominant strain and an experimental basis for cellulase degradation experiments.
strain selectioncellulaseoptimization of enzyme-producing conditionswhole-gene analysis
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