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【目的】探究酶法高效提取头孢菌素C菌渣中蛋白质的工艺条件，拓展抗生素菌渣资源化利用途径。【方法】以蛋白质提取率为指标，在溶菌酶、蜗牛酶、酸性蛋白酶、中性蛋白酶、碱性蛋白酶和木瓜蛋白酶6种酶最适条件下，对头孢菌素C菌渣蛋白质进行提取，确定最适提取酶；考察酶添加质量分数、温度、时间、pH值和V（酶液/mL）∶m（头孢菌素C菌渣/g）（以下简称液固比）对头孢菌素C菌渣中蛋白质提取的影响，通过响应面试验优化确定最佳提取工艺条件。【结果】溶菌酶酶法提取头孢菌素C菌渣中蛋白质的效果最好，且主要受时间、pH值、液固比影响，影响顺序由高到低依次为液固比、时间、pH值。利用溶菌酶提取头孢菌素C菌渣蛋白质的最佳工艺条件为液固比7.0∶1.0，时间99 min,pH值7.2，酶添加质量分数1.0%，温度35℃，在此条件下头孢菌素C菌渣中蛋白质提取率最高，为69.06%。【结论】溶菌酶酶法能够快速、有效地提取菌渣中的蛋白质，促进头孢菌素C菌渣综合利用。
Abstract：【Objective】To study the process conditions for the efficient extraction of proteins from cephalosporin C residues by enzyme method, expanding the resource utilization of antibiotic residues.【Method】Under the optimum conditions of six enzymes, lysozyme, snail enzyme, acidic protease, neutral protease, alkaline protease and papain, the protein of cephalosporin C residues was extracted, and the optimum enzyme was determined used on the protein extraction rate; The effects of enzyme addition mass fraction, temperature, time, pH value and V/mL∶m(cephalosporin C residues/g)(liquid-solid ratio) on the extraction of the protein in cephalosporin C residues were investigated, and the optimum conditions of extraction were determined by optimization of the response surface test.【Result】Lysozyme was the optimum enzyme for protein extraction from cephalosporin C fermentation residues. The protein extraction efficiency was mainly affected by three factors in the order of liquidsolid ratio, time and pH value. The optimal process conditions for protein extraction were as follows: liquid-solid ratio of 7. 0∶1. 0, extraction time of 99 min, pH value 7. 2, enzyme amount of 1. 0%, temperature of 35 ℃, and the highest protein extraction rate of 69. 06% was achieved under this condition. 【Conclusion】Lysozyme is suitable for enzymatic hydrolysis and comprehensive utilization of cephalosporin C fermentation residues, which can quickly and effectively extract the proteins from bacterial fermentation residues.
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基本信息:
DOI：10.16445/j.cnki.1000-2340.20240412.001
中图分类号:TQ465
引用信息:
[1]赵会如,刘柯妤,张立美,等.酶法提取头孢菌素C菌渣中蛋白质工艺优化[J].河南农业大学学报,2025,59(02):266-275.DOI:10.16445/j.cnki.1000-2340.20240412.001.
基金信息:
河南省重点研发专项（221111112300）; 河南省科技攻关项目（222102110120）; 河南农业大学高层次人才专项支持基金项目（30501469）