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Analysis of the Minimum Inhibitory Concentration of Antibiotics against the Lactococcus Genus

Author(s): Jinshang Liu and Cong Nie*
Department of Bioengineering, Qilu University of Technology, Jinan, Shandong 250353, China

Correspondence Address:
Cong Nie, Department of Bioengineering, Qilu University of Technology, Jinan, Shandong 250353, China, E-mail:

Lactic acid bacteria are widely found in nature, have extensive biodiversity and are widely applied to food, feed and medicine. Currently, most probiotics in the market are lactic acid bacteria. In recent years, antibiotic technology has been actively developed, and the development and application of lactic acid bacteria greatly promoted the development of resources. All genome information based on lactic acid bacteria can systematically fully understand the metabolic properties of the strains, potential probiotic functions and application directions and can further study the genetics, evolution, and classification of lactic acid bacteria. The safety evaluation plan for lactic acid bacteria requires determining whether the genes are resistant, virulent, or virulence-related genes and whether or not the related genes can propagate horizontally. Study of 18 strains of Streptococcus from different regions and milk sources, including myriad bacteria, Streptococcus, Enterococcus and Streptococcus pyogenes. 26S ribosomal ribonucleic acid analysis of gene sequences was performed; amino glycosides, tetracyclines, fluoroquinolones, glycosides and macro lactones using the minimum inhibitory concentration method, the authors examined the resistance and sensitivity of 15 kinds of general antibiotics of phenyl propylene glycols and amphotericin to different lactic acid strains. As a result, three kinds of Staphylococcus aureus showed different resistance to five kinds of antibiotics. The results of this experiment provide guidance to the use of human antibiotics and lactic acid bacteria and make them more rational and secure. Antibiotic sequencing techniques are used to compare the gene sequence and the structural differences of antibiotics in different genomes. Based on whole genome information, the reconstruction of the genome scale metabolic network model can simulate and predict the behavior of bacterial cells in a particular environment of antibiotics, and to systematically control the metabolic engineering strategy of the strain.

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