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. 2022 Oct 30;13(11):1984.
doi: 10.3390/genes13111984.

Genome Mining Reveals High Biosynthetic Potential of Biocontrol Agent Bacillus velezensis B.BV10

Affiliations

Genome Mining Reveals High Biosynthetic Potential of Biocontrol Agent Bacillus velezensis B.BV10

Rosiana Bertê et al. Genes (Basel). .

Abstract

The present study demonstrates the biocontrol potential of a plant growth-promoting bacterial strain using three different approaches: (i) an in vitro evaluation of antagonistic activity against important phytopathogenic fungi; (ii) an evaluation under greenhouse conditions with strawberry plants to assess the control of gray mold; and (iii) an in silico whole genome sequence mining to assign genetic features such as gene clusters or isolated genes to the strain activity. The in vitro assay showed that the B.BV10 strain presented antagonistic activity, inhibiting the mycelial growth in all the phytopathogenic fungi evaluated. The application of the Bacillus velezensis strain B.BV10 under greenhouse conditions reduced the presence of Botrytis cinerea and increased the mean fruit biomass. The genome of B.BV10 was estimated at 3,917,533 bp, with a GC content of 46.6% and 4088 coding DNA sequences, and was identified as B. velezensis. Biosynthetic gene clusters related to the synthesis of the molecules with antifungal activity were found in its genome. Genes related to the regulation/formation of biofilms, motility, and the important properties for the rhizospheric colonization were also found in the genome. The current study offers a comprehensive understanding of the genomic architecture and control activity of phytopathogenic fungi by the B. velezensis strain B.BV10 that may substantiate the industrialization of this strain in the future.

Keywords: B. velezensis; biocontrol; biosynthetic pathways; plant growth-promoting bacteria.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Micrograph of B.BV10 (100× magnification) under an optical microscope after Gram (a) and Wirtz–Conklin (b) staining; B.BV10 in LBA after 16 h of incubation (c); micrograph of B.BV10 (1000× magnification) in SEM (d).
Figure 2
Figure 2
Antagonistic activity of B.BV10 against phytopathogenic fungi. MGI averages (%) were plotted into column charts (A), and below are the respective images of the in vitro assays (B). Means in each bar followed by the same letter did not differ significantly from each other by the Tukey test (p < 0.05).
Figure 3
Figure 3
Mean HFM of the treatments (T1: water; T2: chemical control; T3: biological control; T4: B.BV10 1 g/L; T5: B.BV10 2 g/L; and T6: B.BV10 4 g/L) at each time of evaluation. Means in each day followed by the same letter did not differ significantly from each other by the Scott–Knott test (p < 0.05).
Figure 4
Figure 4
Mean IFM of the treatments (T1: water; T2: chemical control; T3: biological control; T4: B.BV10 1 g/L; T5: B.BV10 2 g/L; and T6: B.BV10 4 g/L) at each time of evaluation. Means in each day followed by the same letter did not differ significantly from each other by the Scott–Knott test (p < 0.05).
Figure 5
Figure 5
Mean TFM of the treatments (T1: water; T2: chemical control; T3: biological control; T4: B.BV10 1 g/L; T5: B.BV10 2 g/L; and T6: B.BV10 4 g/L) at each time of evaluation. Means in each day followed by the same letter did not differ significantly from each other by the Scott–Knott test (p < 0.05).
Figure 6
Figure 6
AUPDC of IFM data for each treatment (T1: water; T2: chemical control; T3: biological control; T4: B.BV10 1 g/L; T5: B.BV10 2 g/L; and T6: B.BV10 4 g/L). Means ± SE followed by the same letter did not differ significantly from each other by the Scott–Knott test (p < 0.05).
Figure 7
Figure 7
Phylogenomic tree representing the similarity between B. velezensis B.BV10 and strains from the B. subtilis group. The matrix was generated by Gegenees and exported to SplitsTree4 for making the tree using the UPGMA method.
Figure 8
Figure 8
Circular representation of the genome of B. velezensis B.BV10 generated in the BRIG program. Inside-out matches, GC content, GC skew, FZB42, NKG1, QST713, DSM7, IT45, MT45, NCIB 3610, 168, FRI35, and position of BGCs in the genome indicated by antiSMASH.

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