Details

Autor(en) / Beteiligte

• Rosa Martins, Paulo Henrique
• Rabinovitch, Leon
• de Orem, Juliana Capela
• Silva, Waldeyr Mendes C.
• de Araujo Mesquita, Felipe
• de Magalhães, Maria Ines Andre
• de Andrade Cavalcante, Danilo
• Vivoni, Adriana Marcos
• de Oliveira, Edmar Justo
• de Lima, Vera Cristina Pessoa
• Brito, Josiane Teixeira
• De-Souza, Marlene Teixeira

Titel

Biochemical, physiological, and molecular characterisation of a large collection of aerobic endospore-forming bacteria isolated from Brazilian soils

Ist Teil von

• Neotropical biology and conservation, 2023-02, Vol.18 (1), p.53-72

Ort / Verlag

Sophia: Pensoft Publishers

Erscheinungsjahr

2023

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• The aerobic endospore-forming bacteria (AEFB) comprise species of Bacillus and related genera and have long been regarded as prominent constituents of the soil bacterial community. The wide diversity of AEFB renders appropriate categorisation and generalisations a challenging task. We previously isolated 312 AEFB strains from Brazilian soils that we designated SDF ( Solo do Distrito Federal ) strains. To better understand the SDF diversity and explore their biotechnological potential, we addressed the biochemical and physiological profiles of these 312 environmental strains by performing 30 tests in this work. Of these, the 16S rRNA gene sequences segregated 238 SDF strains into four genera in the family Bacillaceae and two in the Paenibacillaceae. Bacillus spp. were the most prevalent, followed by species of Paenibacillus . We summarised the phenotypic test relationships among selected SDF strains using a Pearson correlation-based clustering represented in heatmaps. In practice, biochemical and physiological profiles are often less discriminatory than molecular data and may be unstable because of the loss of traits. Although these test reactions are not universally positive or negative within species, they may define biotypes and be efficient strain markers, enhancing the accuracy of unknown sample identification. It can also help select the most representative phenotypes of samples. Along with the other phenotypic and genotypic data, the present results are of great importance for the robust classification of the SDF strains within the scope of the polyphasic approach.