通过大规模基因组学和机器学习,揭示与健康相关的乳酸菌群中的加密抗菌
Rubing Du1,2, Fei Han2, Zhen Li2
1Lab of Brewing Microbiology and Applied Enzymology, The Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu, 214000, People's Republic of China.
Microbiome
|June 21, 2025
概括
乳酸菌种细菌是新型抗微生物 (AMP) 的丰富来源,具有广泛的活性. 这项研究确定了数千种潜在的AMP,包括一个有前途的候选人delbruin_1,用于打击抗生素耐药性.
科学领域:
- 微生物学 微生物学
- 基因组学就是基因组学.
- 生物化学 生物化学
背景情况:
- 抗微生物 (AMP) 显示出对抗抗生素耐药细菌的承诺.
- 乳酸菌家族是已知的有益微生物来源,但其AMP潜力尚未被探索.
- 了解AMP在乳酸菌群中的分布对于发现新的抗菌剂至关重要.
研究的目的:
- 调查乳酸菌家族中AMP的流行率和多样性.
- 识别来自乳酸菌家族的新型AMP,具有潜在的临床应用.
- 开发用于AMP发现的机器学习引导框架.
主要方法:
- 对10,327个乳杆菌家族基因组进行全基因组分析,以确定AMP生物合成潜力.
- 将已识别的AMP聚合到基因群家族 (GCF) 中,并根据现有数据库对新奇性进行评估.
- 机器学习对抗微生物活性 (MIC) 的预测以及候选AMP的实验合成和测试.
主要成果:
- 在69.90%的乳酸菌种中发现了AMP生物合成潜力,在2092个GCF中确定了9601个AMP.
- 确定的GCF中很大一部分 (72.47%) 是新的,与已知的AMP没有相似之处.
- 机器学习预测了664种GCF的强烈抗菌活性,实验验证证证了16种合成AMP中的10种活性,包括广谱delbruin_1.1.
结论:
- 乳酸菌种代表着一个巨大的,未开发的新型AMP储备,对于解决抗生素耐药性危机至关重要.
- 建立了一种机器学习引导的发现框架,提供了一种可扩展的方法来识别乳杆菌和其他生物体中的AMP.
- 从Lactobacillus delbrueckii中发现的AMPdelbruin_1显示出作为临床可行的抗菌剂的巨大潜力.
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