Baláž Andrej, Kajsik Michal, Budiš Jaroslav, Szemes Tomáš, Turňa Ján
Geneton Ltd., Ilkovicova 8, 841 04 Bratislava, Slovakia.
Department of Applied Informatics, Faculty of Mathematics, Physics and Informatics, Comenius University, Mlynska dolina F1, 842 48 Bratislava, Slovakia.
Microorganisms. 2023 May 26;11(6):1398. doi: 10.3390/microorganisms11061398.
Antibiotic resistance is becoming a common problem in medicine, food, and industry, with multidrug-resistant bacterial strains occurring in all regions. One of the possible future solutions is the use of bacteriophages. Phages are the most abundant form of life in the biosphere, so we can highly likely purify a specific phage against each target bacterium. The identification and consistent characterization of individual phages was a common form of phage work and included determining bacteriophages' host-specificity. With the advent of new modern sequencing methods, there was a problem with the detailed characterization of phages in the environment identified by metagenome analysis. The solution to this problem may be to use a bioinformatic approach in the form of prediction software capable of determining a bacterial host based on the phage whole-genome sequence. The result of our research is the machine learning algorithm-based tool called PHERI. PHERI predicts the suitable bacterial host genus for the purification of individual viruses from different samples. In addition, it can identify and highlight protein sequences that are important for host selection.
抗生素耐药性正在成为医学、食品和工业领域的一个常见问题,所有地区都出现了多重耐药细菌菌株。未来可能的解决方案之一是使用噬菌体。噬菌体是生物圈中最丰富的生命形式,因此我们很有可能针对每种目标细菌纯化出特定的噬菌体。单个噬菌体的鉴定和一致表征是噬菌体研究的常见形式,包括确定噬菌体的宿主特异性。随着新的现代测序方法的出现,通过宏基因组分析鉴定出的环境中的噬菌体详细表征出现了问题。解决这个问题的方法可能是以预测软件的形式使用生物信息学方法,该软件能够根据噬菌体全基因组序列确定细菌宿主。我们研究的结果是基于机器学习算法的工具PHERI。PHERI预测从不同样本中纯化单个病毒的合适细菌宿主属。此外,它可以识别并突出显示对宿主选择很重要的蛋白质序列。