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Pato:利用代谢特征预测益生菌

Pato: prediction of probiotic bacteria using metabolic features.

作者信息

Dias Rafaella Sinnott, Martinez Daniela Peres, Leite Fábio Pereira Leivas, Avila Luciana Farias da Costa de, Kremer Frederico Schmitt

机构信息

Laboratório de Bioinformática OmixLab, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brazil.

Laboratório de Parasitologia, Faculdade de Medicina, Universidade Federal do Rio Grande, Rio Grande, Rio Grande do Sul, Brazil.

出版信息

Braz J Microbiol. 2025 Jun;56(2):1169-1178. doi: 10.1007/s42770-025-01678-x. Epub 2025 Apr 23.

Abstract

Probiotics have gained recognition for their health-promoting benefits, particularly in the gastrointestinal and immunological systems. Among promising probiotic candidates, Lactobacillus strains, belonging to the lactic acid bacteria (LAB) group, play a significant role in human microbiota. To aid in the in silico identification of Lactobacillus strains with probiotic potential, this study presents a novel classification approach based on functional and metabolism-related elements, which offers improved accuracy and explainability compared to traditional k-mer-based methods. By considering the functional characteristics of genomic sequences, this approach contributes to a clearer understanding of the traits associated with probiotic activity, facilitating the selection of strains with optimal health-promoting attributes. The webserver is available at http://200.132.101.156:5001/ .

摘要

益生菌因其促进健康的益处而获得认可,尤其是在胃肠道和免疫系统方面。在有前景的益生菌候选菌株中,属于乳酸菌(LAB)组的乳酸杆菌菌株在人类微生物群中发挥着重要作用。为了有助于在计算机上识别具有益生菌潜力的乳酸杆菌菌株,本研究提出了一种基于功能和代谢相关元素的新型分类方法,与传统的基于k-mer的方法相比,该方法具有更高的准确性和可解释性。通过考虑基因组序列的功能特征,这种方法有助于更清楚地了解与益生菌活性相关的特性,便于选择具有最佳促进健康属性的菌株。该网络服务器可在http://200.132.101.156:5001/获取。

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本文引用的文献

1
A survey of k-mer methods and applications in bioinformatics.生物信息学中k-mer方法及其应用综述。
Comput Struct Biotechnol J. 2024 May 21;23:2289-2303. doi: 10.1016/j.csbj.2024.05.025. eCollection 2024 Dec.
6
Vaginal microbiome: considerations for reproductive health.阴道微生物组:生殖健康的考虑因素。
Future Microbiol. 2022 Dec;17:1501-1513. doi: 10.2217/fmb-2022-0112. Epub 2022 Oct 31.
10
Representation learning applications in biological sequence analysis.生物序列分析中的表示学习应用。
Comput Struct Biotechnol J. 2021 May 23;19:3198-3208. doi: 10.1016/j.csbj.2021.05.039. eCollection 2021.

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