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Discovery of new antibiotics using genome data mining
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Cheng SHI, Ying SUN, Bin XIAO, Heng ZHENG*
Acta Pharmaceutica Sinica | 2018, 53(6) : 845 - 851
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Acta Pharmaceutica Sinica | 2018, 53(6): 845-851
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Discovery of new antibiotics using genome data mining
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Cheng SHI, Ying SUN, Bin XIAO, Heng ZHENG*
Affiliations
  • School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China
Published: 2018-06-12 doi: 10.16438/j.0513-4870.2018-0221
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With the worldwide spread of multi-drug resistant (MDR) bacteria, bacterial resistance has become a major issue affecting human health. Although traditional methods for obtaining antibiotics by screening bacterial strains have found the most available antibiotics for us, this method has resulted in fewer and fewer antibiotics in the past few decades and is increasingly difficult to find the new structure of the compound entity. At present, there are few drugs that can fight super-resistant bacteria in the clinic or even research. therefore, the development and application of new technologies to address the issue of bacterial resistance is imminent. Since the first bacterial genome was sequenced more than 20 years ago, a large number of bacterial genomic sequence information can provide clues for the discovery of new antibiotics. In this review, we briefly outline the available data sources and highlight the use of genomic mining and metagenomics in discovery of new antibiotics.

antibiotic  /  multidrug resistance  /  antibiotic resistance gene  /  database  /  genome mining  /  metagenomic mining
Cheng SHI, Ying SUN, Bin XIAO, Heng ZHENG. Discovery of new antibiotics using genome data mining[J]. Acta Pharmaceutica Sinica, 2018 , 53 (6) : 845 -851 . DOI: 10.16438/j.0513-4870.2018-0221
Year 2018 volume 53 Issue 6
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doi: 10.16438/j.0513-4870.2018-0221
  • Receive Date:2018-03-15
  • Online Date:2026-01-15
  • Published:2018-06-12
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  • Received:2018-03-15
  • Revised:2018-04-26
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    School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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