1. Introduction
Crops such as vegetables and fruits become diseased between harvesting and consumption, resulting in significant food waste and economic losses. About 45% of harvested fruits, vegetables, roots and tubers are lost. Most of this loss occurs during storage due to the development of pests and pathogens (bacteria, fungi and insects), unfavorable environmental conditions (rain, humidity, frost and heat), water loss, saccharification and sprouting. [
1]
Bacteria of the genus
Bacillus spp. they are recognized as safe microorganisms for application in the food industry. They occupy the same niche as many pathogens and have the ability to produce a wide range of bioactive substances with antibiotic activity. These substances induce various physiological characteristics in the metabolism of the host plant without causing adverse effects on the environment and human health [
2]. Furthermore,
Bacillus spp. (i.e.,
Bacillus subtilis), produce endospores resistant to dynamic physical and chemical treatments, such as heat, desiccation, organic solvents, and ultraviolet radiation, which therefore maintain their ability to trigger defense responses in plants guest, even in unfavorable conditions.[
3]; this makes it capable of easily formulating and storing Bacillus-based biological products and serves as a potent bioactive component against pathogens [
4].
Currently, the protective effect of
Bacillus strains is used in several plant species against a wide variety of biotic (pathogens, pests) [
5] and abiotic (drought, salinity, extreme temperatures, metals, stresses toxic) [
6].
The purpose of the study is to carry out the molecular identification of Bacillus spp. samples. collected in rhizospheric soil from 3 regions of Peru and the relationship that exists between these species through a phylogenetic tree.
2. Materials and Methods
2.1. Sample collection and isolation
The collection of rhizospheric soil samples was carried out in the areas of 1) Canín Annex of the Checras district of the province of Huaura, 2) Kimiri Sector of the Chanchamayo district of the province of Chanchamayo and 3) Catapalla Annex of the district from Lunahuaná in the province of Cañete. Subsequently, the samples were processed for the isolation of
Bacillus spp. strains: 10 g were weighed. of the rhizospheric soil sample and dissolved in physiological saline, then dilutions were carried out in 3 series, subsequently the diluted sample was seeded in the culture medium Glucose Tryptone Meat Extract (TGE) and incubated at 37°C for 24 hours, finally Colonies were selected and purified by streaks [
7].
2.2. DNA extraction, quantification and quality
The isolated strains were seeded in the Luria Broth (LB) culture medium and incubated for 18 hours at 37 °C [
8]. Subsequently, genomic DNA extraction was carried out according to the instructions of the commercial Genomic DNA Extraction Kit – Gram (+) Bacteria/Yeast/Fungi (Cepham Life Sciences). The samples were then quantified using the Eppendorf BioSpectrometer kinetic spectrophotometer [
9] and to verify the quality and integrity of the DNA, a 1% agarose electrophoresis run was performed in a 1X TAE buffer solution [
10].
2.3. PCR amplification with the 16S rRNA gene and DNA sequencing
Amplification was performed by polymerase chain reaction (PCR) [
11] using 2 μl of the DNA sample with the DreamTaq PCR Master Mix kit (2X) and the 16S rRNA 27 F primers (5 ' AGA GTT TGA TCM TGG CTC AG 3') and 1525 R (5' AAG GAG GTG WTC CAR CC 3') [
12]. For a negative control, a mix without sample was used. The mixtures were processed in the Eppendorf Mastercycler minutes, elongation at 72°C for 1 minute and a final extension cycle at 72°C for 15 minutes [
13]. The PCR products were visualized by electrophoresis in a 1.5% agarose gel in a 1X TAE buffer solution and were subsequently sent for Sanger sequencing [
14] to the University of Minnesota - USA.
2.4. Bioinformatic analysis
The sequences obtained were edited with the Chromas v2.66 software (
https://technelysium.com.au/wp/chromas/) [
15], then they were analyzed with the online BLAST platform [
16], subsequently these were aligned using the ClustalW tool and finally the construction of a phylogenetic tree from the 16S rRNA gene was carried out using the software MEGA 11.0.13 [
17] using the following parameters: Analysis (phylogenetic reconstruction), statistical method (Neighbor-Joining), Phylogeny test (Bootstrap method, number of bootstrap replications: 1000), model (Maximun composite likelihood) [
18].
3. Results
3.1. Sample collection and isolation
A total of 14 strains of Bacillus spp. were isolated and analyzed: 7 in the Canín annex of the Checras district of the province of Huaura, 5 in the Kimiri sector of the Chanchamayo district of the province of Chanchamayo and 2 in the Catapalla annex of the Lunahuaná district of the province of Cañete.
3.2. DNA quantification and quality
For the DNA quantification of the samples, an average result of 30.35 ng/μl was obtained, with a minimum of 21.4 ng/μl for samples UNDC_06, UNDC_09 and a maximum of 39.5 ng/μl for sample UNDC_05. While in the quality of the extracted genomic DNA, defined bands with a large molecular weight exceeding 10,000 bp were evident, which indicate an acceptable quality for PCR amplification and corroborates the quantification previously carried out. (
Figure 1)
3.3. PCR amplification with the 16S rRNA gene and DNA sequencing
The PCR amplification products of the 14 samples were analyzed by 1.5% agarose electrophoresis and visualized amplicons with an expected weight of 1500 bp. (
Figure 2). As a result of the sequencing, 14 electropherograms were obtained which were subsequently analyzed.
3.4. Bioinformatic analysis
According to the molecular identification analysis with the BLAST platform, the species of Bacillus subtilis, Bacillus licheniformis, Bacillus paralicheniformis and Bacillus cereus were identified, with a minimum of 92.05% and maximum of 100% similarity (
Table 1).
The construction of the phylogenetic tree reveals the evolutionary relationship and homology between the 14 strains worked on. (
Figure 3)
4. Discussion
In the collection stage, the strawberry rhizosphere soil was used as a sample to obtain the Bacillus spp strains, similar to a work reported in the rhizosphere of cacti [
19]. On the contrary, studies have been carried out where they obtain samples of mites [
20], plants [
21], fish [
22], birds, bovines [
23], fungi [
24] among others. In this work, rhizospheric soil is used due to the high diversity of microbiota and the environmental conditions that favor the development of the genus
Bacillus spp due to its close relationship with the roots of vegetable crops [
25]. In the PCR amplification stage, the universal primers of the 16S rRNA gene were used [
26], however other authors used different primers such as Bc-Rep-1, Bc-Rep-2 [
27] and M-B1 [
28].
The sanger sequencing used in this work was efficient for molecular identification, however, the results can be improved using third generation sequencing such as Oxford Nanopore Technologies technology [
29], its greatest advantage is the reading length and the speed of the process [
30]. This will allow us to expand the database, having more sampling points and repetitions of them. The molecular characterization of species was
Bacillus subtilis [
31],
Bacillus licheniformis [
32],
Bacillus paralicheniformis [
33],
Bacillus cereus [
34], unlike other authors who found other types of species such as
Bacillus amyloliquefaciens,
Bacillus vallismortis,
Bacillus halotolerans [
35],
Bacillus thuringiensis [
36].
Finally, the phylogenetic tree was built using the Neighbor Joining method, aligned with the Clustal can be improved by increasing the number of primers for the 16S rRNA gene and the number of replications using a specialized server for bioinformatic analysis.
5. Conclusions
The molecular characterization of the genus Bacillus spp. Through the analysis of the 16S rRNA gene, it allowed the identification of 8 strains of Bacillus subtilis, 4 strains of Bacillus licheniformis, 1 strain of Bacillus paralicheniformis, 1 strain of Bacillus cereus; with a minimum of 92.05% and maximum of 100% similarity in the regions of Huaura, Chanchamayo and Cañete.
Author Contributions
Conceptualization, J.V.; methodology, A.Q., M.C. and D.M..; software, J.V.; validation, J.V and A.Q.; writing—original draft preparation, J.V.; writing—review and editing, J.V.; supervision, J.V. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by first research seedbed contest with contract N°004-2021-UNDC-PSI
Acknowledgments
We duly appreciate the stipend granted by the vice presidency of research of the National University of Cañete, Cañete, Peru.
Conflicts of Interest
The authors declare no conflict of interest.
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