Pato: prediction of probiotic bacteria using metabolic features.

Journal: Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology]
Published Date:

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/ .

Authors

  • Rafaella Sinnott Dias
    Laboratório de Bioinformática OmixLab, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brazil.
  • Daniela Peres Martinez
    Laboratório de Bioinformática OmixLab, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brazil.
  • Fábio Pereira Leivas Leite
    Laboratório de Bioinformática OmixLab, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brazil.
  • Luciana Farias da Costa de Avila
    Laboratório de Parasitologia, Faculdade de Medicina, Universidade Federal do Rio Grande, Rio Grande, Rio Grande do Sul, Brazil.
  • Frederico Schmitt Kremer
    Laboratório de Bioinformática OmixLab, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brazil. fred.s.kremer@gmail.com.