https://orcid.org/0000-0002-4999-1672
Figures
Abstract
Plant growth-promoting bacteria (PGPB) are a heterogeneous group of bacteria that can exert beneficial effects on plant growth directly or indirectly by different mechanisms. PGPB-based inoculant formulation has been used to replace chemical fertilizers and pesticides. In our previous studies, two endophytic endospore-forming bacteria identified as Bacillus altitudinis were isolated from roots of Ilex paraguariensis St. Hil. seedlings and selected for their plant growth-promoting (PGP) properties shown in vitro and in vivo. The purposes of this work were to assemble the genomes of B. altitudinis 19RS3 and T5S-T4, using different assemblers available for Windows and Linux and to select the best assembly for each strain. Both genomes were also automatically annotated to detect PGP genes and compare sequences with other genomes reported. Library construction and draft genome sequencing were performed by Macrogen services. Raw reads were filtered using the Trimmomatic tool. Genomes were assembled using SPAdes, ABySS, Velvet, and SOAPdenovo2 assemblers for Linux, and Geneious and CLC Genomics Workbench assemblers for Windows. Assembly evaluation was done by the QUAST tool. The parameters evaluated were the number of contigs ≥ 500 bp and ≥ 1000 bp, the length of the longest contig, and the N50 value. For genome annotation PROKKA, RAST, and KAAS tools were used. The best assembly for both genomes was obtained using Velvet. The B. altitudinis 19RS3 genome was assembled into 15 contigs with an N50 value of 1,943,801 bp. The B. altitudinis T5S-T4 genome was assembled into 24 contigs with an N50 of 344,151 bp. Both genomes comprise several genes related to PGP mechanisms, such as those for nitrogen fixation, iron metabolism, phosphate metabolism, and auxin biosynthesis. The results obtained offer the basis for a better understanding of B. altitudinis 19RS3 and T5S-T4 and make them promissory for bioinoculant development.
Citation: Cortese IJ, Castrillo ML, Onetto AL, Bich GÁ, Zapata PD, Laczeski ME (2021) De novo genome assembly of Bacillus altitudinis 19RS3 and Bacillus altitudinis T5S-T4, two plant growth-promoting bacteria isolated from Ilex paraguariensis St. Hil. (yerba mate). PLoS ONE 16(3): e0248274. https://doi.org/10.1371/journal.pone.0248274
Editor: Ying Ma, Universidade de Coimbra, PORTUGAL
Received: September 14, 2020; Accepted: February 23, 2021; Published: March 11, 2021
Copyright: © 2021 Cortese et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: This study was supported by Proyecto del Instituto Nacional de la Yerba Mate (INYM, Argentina) "Biofertilizantes: validación a campo y estudios de trazabilidad de la utilización de Bacillus sp. como fertilizante para yerba mate” Res. n° 274/17 (INYM - PRASY) granted to ML.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Biological products that enhance plant growth are an alternative for improving crop management and degraded soils. The application of native microorganisms reduces the degradation of the agroecosystem and the loss of nutrients, optimizing the yield of crops. Plant growth-promoting bacteria (PGPB) are a heterogeneous group in the rhizosphere, at root surfaces or in association with plant tissues as endophytes. These bacteria exert beneficial effects on plant growth directly, or indirectly. The mechanisms by which PGPB can influence plant growth may differ from one species to another as well as from strain to strain [1]. PGPB-based inoculant formulation and application have been used in integrated management systems to reduce or replace the use of chemical fertilizers and pesticides [2].
Bacteria genera such as Alcaligenes, Acinetobacter, Arthrobacter, Azoarcus, Azospirillum, Azotobacter, Bacillus, Paenibacillus, Burkholderia, Clostridium, Enterobacter, Gluconacetobacter, Klebsiella, Kosakonia, Pseudomonas, Serratia, and Stenotrophomonas include specific strains that have been reported as PGPB for different plant species [3–9]. Their mechanisms are multiple, diverse, and their effects include the transformation of nutrients into forms available to plants, for example, the capacity to fix atmospheric nitrogen [10], the solubilization of inorganic phosphorus, or the mineralization of organic phosphorus [11, 12]. Some PGPB can also promote plant growth indirectly by controlling the associated pathogens by producing antibiotics and other secondary metabolites [4], or by activating the mechanisms of Induced Systemic Resistance (ISR) [13].
Keeping in mind this context, the genus Bacillus presents a great diversity of species that are distributed widely in the environment. It is one of the most studied and promising genera for achieving sustainable and environmentally safe agricultural practices [14].
They have been shown to enhance plant growth through a combination of mechanisms [15, 16], by activating ISR in the plant against both root and foliar pathogens, by increasing abiotic stress tolerance [17], and by showing biocontrol properties [18]. Elicitation of ISR by Bacillus and its metabolites has been demonstrated on a variety of crops to defend against pathogen attack in both the greenhouse and the field [19, 20]. It can also produce numerous antifungal compounds [21], such as lipopeptides [22], bacillomycin [23], fengycin [24], surfactin [25], bacillibactin [26], and bacteriocin [27].
The PGPB activity of some bacilli strains was studied in the last years. B. subtilis is commercially used as a biofertilizer [28]. It can maintain stable contact with higher plants and promote their growth. B. licheniformis shows beneficial effects when inoculated on tomato and pepper [4]. B. megaterium improves different root parameters in mint [29], while B. mucilaginosus, when inoculated in nutrient-limited soil, can increase mineral availability [30, 31]. B. pumilus is used as a bioinoculant to increase the crop yield of a wheat variety in Mongolia [32]. Genome analysis revealed that B. velezensis can be considered a potential biofertilizer and biopesticide [33]. Likewise, Bacillus spp. consortia present the capability to increase the yield, growth, and nutrition of raspberry [34] and banana plants [35].
Different crops have great economic agro-food importance in the world, and it is of interest to improve their production through the implementation of PGPB as a biofertilizer [36, 37]. Ilex paraguariensis St. Hil., a plant that is also commonly called yerba mate, is one of the most economically important crops in the northeast of Argentina. It is widely marketed in South America, but it is also consumed worldwide. It is emphasized that despite this overall consumption, yerba mate can only grow in certain regions of Argentina, Paraguay, and Brazil due to unique soil characteristics, such as lateritic soils, and warm and moist weather [38, 39].
Currently, there are plantations of good performance in the region, however, there are concerns about the increase of degraded crop sites, as a result of the monoculture system, erosion and compaction of soil, and nutrient loss combined with little or no soil fertilization [40]. This motivates the research and development of a biofertilizer from native bacteria isolated from yerba mate to recover crop performance.
In our previous study, two Gram-positive endophytic endospore-forming bacteria, coded as 19RS3 and T5S-T4, were isolated from roots of I. paraguariensis St. Hil. seedlings. These bacteria were selected for their in vitro PGP properties. Both strains were identified morphologically and molecularly as Bacillus altitudinis. Also, B. altitudinis 19RS3 and B. altitudinis T5S-T4 showed in vivo growth promotion in yerba mate seedlings in greenhouse conditions with promising results [41].
The study of the genome of microorganisms used for biofertilizer production is important to bioinoculant technology because it helps to identify genes that contribute to the beneficial activity and increasing knowledge of the molecular mechanisms related to plant growth potential. In the last decade, the development of new bioinformatics tools and next-generation sequencing technologies has allowed researchers to gain deeper insights into the molecular and genetic mechanisms of plant growth-promoting (PGP) activities such as the study of Pho regulon involved in the inorganic phosphate (Pi) solubilization, the detection of nif gene cluster associated to nitrogen fixation, the study of metabolic pathways related to the siderophore production, and the discovery of antibiotics and volatile compounds production mechanisms implicated in biocontrol properties. These advances were accompanied by an exponential increase in the number of assembler algorithms available to obtain complete prokaryotic genomes [42]. Principio del formulario Final del formulario Currently, there are two widely used classes of algorithms: overlap–layout–consensus (OLC) and de-Bruijn-graph (DBG) [43]. The DBG algorithm is based on the k-mers approach [44]. This value divides the short sequences into smaller fragments of size k, and these k-mers overlap with k-1, which represents the next k-mer. Since Illumina sequencing technology entered the global market, several short-read assembly software based on DBG have been developed, such as Velvet [45], ABySS [46], SPAdes [47], and SOAPdenovo2 [48]. Despite this, the selection of assembly tools, the determination of the parameters to be executed, as well as the evaluation of the assemblies, are still a challenge [49].
In this context, to advance knowledge of PGP mechanisms, the genomes of B. altitudinis 19RS3 and B. altitudinis T5S-T4 were sequenced. The purposes of this work were to assemble both genomes, to compare the results obtained using different de novo assemblers available for Windows and Linux operating systems, and to select the best assembly for each B. altitudinis strain. Finally, both genomes were automatically annotated to detect genes involved in PGP capabilities and compare these sequences with other Bacillus sp. genomes reported.
Materials and methods
Bacteria
B. altitudinis 19RS3 and B. altitudinis T5S-T4 were isolated from roots of I. paraguariensis St. Hil. seedlings [41]. Both strains were identified by analysis of 16S rRNA gene sequencing (accession number MH883312 and MH883235, respectively) and characterized as Gram-positive endospore-forming rod-shaped bacteria. B. altitudinis 19RS3 and B. altitudinis T5S-T4 were deposited into the bacterial collection of the Instituto de Biotecnología Misiones “Dra. María Ebe Reca”, under accession numbers LBM250 and LBM251, respectively. Bacteria were preserved in 50% glycerol stocks at -80°C until the performance of this study.
DNA extraction
The strains were cultivated in nutrient broth (Britania Lab. SA) for 24 h at 30°C. The DNA extraction procedures were done using Sambrook´s work protocol modified [50, 51]. The DNA was resuspended by 20 μL of sterile distilled DNAse-free water (BioPack ®). The extracted DNA was qualitatively evaluated by agarose gel (1% w/v) electrophoresis stained with a solution of GelRed® (Sigma-Aldrich, Germany). The DNA quantification was performed by UV spectrophotometry.
Library preparation and genome sequencing
Genomic TruSeq Nano DNA library (350) construction and draft genome paired-end sequencing were performed by Macrogen Co. (Seoul, Korea) services using Illumina HiSeq technology.
Genome assembly and evaluation
The quality of the FASTQ files was verified with FastQC [52] and reads were trimmed to ensure high quality (Phred score > 30) using Trimmomatic version 0.39 [53].
The genomes were assembled using different de novo assemblers available for Linux and Windows operating systems (Table 1).
The k-mer values were selected according to the manual user instructions of each assembler. In general terms, the values were odd to avoid palindromes and were strictly inferior to read length.
The assemblies obtained in Linux were evaluated using QUAST (Quality Assessment Tool for Genome Assemblies) [56–58]. The assemblies generated in Windows showed their own statistics tables.
The parameters evaluated were the number of contigs ≥ 500 bp, the number of contigs ≥ 1000 bp, the length of the longest contig, and the value of N50.
Genome annotation
Gene prediction and annotation were performed using The Rapid Prokaryotic Genome Annotation (Prokka) [59]. Putative genes involved in plant growth-promoting mechanisms were determined using the Rapid Annotations using Subsystems Technology (RAST) [60] annotation server and KEGG Automatic Annotation Server (KAAS) [61].
Genome comparison
The genomes of B. altitudinis 19RS3, B. altitudinis T5S-T4, B. altitudinis W3 (accession number: NZ_CP011150.1) an NCBI reference sequence, B. altitudinis GQYP101 (accession number: NZ_CP040514.1) an NCBI reference sequence reported as PGPB, and B. velezensis FZB42 (accession number: CP000560.2) [23] a commercial PGPB strain used as an active principle of Biomex® and Rhizovital®42, were compared to locate genes involved in PGP mechanisms using Geneious 11.0.1 software.
Results
The genome sequencing of B. altitudinis 19RS3 showed 9,938,250 paired-end reads of 101 bp with a GC content of 41.014% and an average coverage of 249. While B. altitudinis T5S-T4 showed 12,397,272 paired-end reads of 101 bp with a GC content of 40.390% and an average coverage of 292.
After the quality filtering by Trimmomatic, B. altitudinis 19RS3 and B. altitudinis T5S-T4 resulted in 9,329,838 and 10,923,782 paired-end reads, respectively.
Genome assembly’s quality statistics generated by different assemblers for B. altitudinis 19RS3 and B. altitudinis T5S-T4 are summarized in Tables 2 and 3, respectively. The complete quality statistics obtained by all the assemblers using different k-mer values are available as S1–S12 Tables.
In the assembly of B. altitudinis 19RS3 genome, ABySS and Velvet generated the contigs with the highest N50 value. These two assemblies produced N50 values that are more than five times higher than the worst assemblies. Velvet also generated the fewest number of contigs and performed considerably better than the other assemblers. Geneious generated the worst assembly with the fewest N50 value and the highest number of contigs.
For the assembly of B. altitudinis T5S-T4 genome, ABySS had the highest N50 value, followed by Velvet. This last assembler also generated the fewest number of contigs. The CLC Genomics Workbench assembly, despite its large N50 contig size, had more contigs than any other assembler.
The best assembly for both genomes was obtained using the Velvet software. The B. altitudinis 19RS3 genome was assembled into 15 contigs (≥ 500 bp) with an N50 value of 1,943,801 bp and the longest contig length of 1,943,801 bp. The B. altitudinis T5S-T4 genome was assembled into 24 contigs (≥ 500 bp) with an N50 of 344,151 bp and the longest contig length of 805,135 bp. The B. altitudinis 19RS3 and B. altitudinis T5S-T4 assembled contigs were deposited in Genbank under accession numbers JACAAH01 and JACAAI01 respectively.
Genomic features of B. altitudinis 19RS3 (Fig 1) and B. altitudinis T5S-T4 (Fig 2) presented similar size, noncoding sequences, ribosomal RNA sequences, and transfer RNA (Table 4).
Circularized DNA plotter diagram of the chromosome of B. altitudinis, orientated from the origin; the outer black circle designates the genome base positions around the chromosome. The outer blue circles depict predicted 3861 CDSs on both the forward and reverse strands. The predominantly brown circle represents the main chromosomal core structure with likely horizontally acquired DNA elements, including areas representing non-coding RNA (ncRNA) and areas representing tRNA. The inner circle is a GC skew plot [GC/(G+C)].
Circularized DNA plotter diagram of the chromosome of B. altitudinis, orientated from the origin; the outer black circle designates the genome base positions around the chromosome. The outer blue circles depict predicted 3801 CDSs on both the forward and reverse strands. The predominantly brown circle represents the main chromosomal core structure with likely horizontally acquired DNA elements, including areas representing non-coding RNA (ncRNA) and areas representing tRNA. The inner circle is a GC skew plot [GC/(G+C)].
In the chromosome sequence of B. altitudinis 19RS3 a total of 3861 CDSs and 80 RNAs genes were predicted (Table 4). Among these CDSs 2762 (68.43%) genes were classified into 469 functional subsystems. Similarly, in the chromosome sequence of B. altitudinis T5S-T4 a total of 3801 CDSs and 67 RNAs genes were predicted (Table 4). Among these CDSs 2750 (69.54%) genes were classified into 472 functional subsystems. There is a high similarity among the number of genes in each category between B. altitudinis 19RS3 and B. altitudinis T5S-T4; but the former has more genes in several metabolism-related functions in cellular processes such as cell wall formation and capsule formation, regulation and cellular signaling, and genes related to phages, prophages, transposable elements, plasmids (Table 5). Most of the genes were associated with the metabolism of carbohydrates and amino acids derivates.
The presence of related genes to PGPR mechanisms or the metabolic pathway prediction of RAST was found from the gene annotation. The production of enzymes involved in the metabolism of indole acetic acid (IAA) via the tryptophan pathway coded by the gene cluster trp(ABD) was predicted, suggesting that B. altitudinis 19RS3 and B. altitudinis T5S-T4 have the potential to biosynthesize auxin. The gene cluster that encodes to produce bacilibactin, dhb(ACEBF), was also found in both genomes showing the potential for the production of siderophore.
The pst(SCAB) genes, coding for Pi-specific transporter, were found in the genome of B. altitudinis 19RS3 and B. altitudinis T5S-T4 suggesting the capacity of both strains for inorganic phosphate solubilization. Finally, the genes nif(U) and nif(S), were present in both strains which are involved in nitrogenase enzymatic activity responsible for the biological fixation of nitrogen. However, the presence of the complete gene cluster which is essential for the nitrogenase activity was not found.
Volatile compounds as 2,3-butanediol and acetoin might be produced by B. altitudinis 19RS3 and B. altitudinis T5S-T4 given that it has the potential to produce the enzymes α−acetolactate synthetase, α−acetolactate decarboxylase, and acetoin utilization protein. Coding regions for surfactin production were also found and the complete gene cluster srf(ABCD) was annotated in each genome. Genes responsible for flagellar motility, chemotaxis, and biofilm synthesis, which allow B. altitudinis 19RS3 and T5S-T4 to move toward root-exudates facilitating adhesion to plant surfaces, were encountered. Also, some genes related to stress response, such as implicated in osmotic stress, oxidative stress, cold and heat shock, and detoxification, in addition to genes related to sporulation were present in both genomes, indicating a possible protection mechanism to extreme environmental conditions.
The genomes comparison revealed specific gene clusters involved in PGP capabilities (Table 6). All the genomes presented genes associated with the production of volatile compounds such as 2,3-butanediol and acetoin. Only B. altitudinis 19RS3, B. altitudinis T5S-T4 and B. velezensis FZB42 showed the presence of genes associated with surfactin production. This commercial strain also presented genes for phytase and iturin production. Interestingly, other genes coding for bacilibactin, IAA production, Pi-specific transporter, and PHO regulon were discovered only in our studied strains.
Discussion
In the present study the genome of two PGP strains isolated from I. paraguariensis St. Hil., B. altitudinis 19RS3 and B. altitudinis T5S-T4, were sequenced and assembled. We compared the assembled genome quality statistics generated by different de novo assemblers available for Windows and Linux operating systems. Although no assembler was the best in all the various metrics simultaneously, the Velvet assembler generated the fewest contig number and the higher N50 value. We also annotated both genomes, detected the genes associated with PGP properties, and determinate the presence of these sequences in two B. altitudinis genomes reported in the NCBI.
The prokaryotic genomic structure characteristics were considered to select the sequencing platform, as well as the construction of the library. Some authors [62] indicate it may be useful to try different strategies for de novo assembly of a newly sequenced organism. They propose to evaluate the strategies for the construction of contigs and analyze their effect on the assembly when choosing the best parameters. They also emphasize that knowing the characteristics of the genomic structure of an organism, the sequencing platform, and the construction of the library can be especially useful when choosing assembly tools.
The raw reads obtained for both genomes were processed to eliminate adapters and possible contaminants that can affect the quality of the results, creating a problem when comparing the efficiency of the assemblers. Some authors [28] recommend a trimming step to ensure the high quality of the data. We agree and highlight the importance of filtering and trimming to generate better results because in a previous study we evaluated the effect of the use of raw and filtered reads as input files, in the assembly of the genome of B. altitudinis 19RS3 and obtained a better assembly using the filtered reads [63].
When considering the number of contigs, the longest contig length, and the N50 value in the assemblies of both genomes, the software Velvet and ABySS generated the best results. As in our study, other authors [64] evaluated de novo assemblers using reads of prokaryotic genomes. In their work, Velvet showed a greater number of contigs and a lower value of N50, while ABySS generated a lower number of contigs in the paired data sets and showed a higher N50 value. The authors associated these results variation to factors such as the quality of the data and the k-mer size. About this last item, we decided to use different k-mer values considering their effect in genome assemblies. For SPAdes assembler, we used a k-mer value of 63 greater than the average size of the reads and we sought to gradually increase the values, getting to obtain more precise assemblies with k-mer values of 79 and 97. Large k-mers often result in larger contigs, but excessively large k-mers can cause a fragmented graph with a higher number of contigs. SPAdes, ABySS, and SOAPdenovo2 generated their best assemblies with the highest k-mer value, however, they also produced the most fragmented assemblies. Several authors [65, 66], showed SPAdes stands out as one of the best assemblers for the assembly of Illumina data, due to its quality and high precision. Although in our study, assemblies with a fewer number of contigs were obtained using other software, SPAdes produced very good results for the assembly of both genomes.
As showed in the assemblies obtained in this work, the value that presented the greatest variation was the number of contigs. We agree with some authors [49] that the wide variety of assemblers’ available use different heuristic approaches to meet the challenges of genome assembly and this results in significant differences when comparing the number of contigs they generated. For this reason, we consider necessary a thorough and complete evaluation of the assembled genome quality statistics generated by different assemblers before selecting the best assembly.
In the present study, we predicted genes and enzymes associated with PGP mechanisms in the B. altitudinis 19RS3 and B. altitudinis T5S-T4 genomes. We detected genes related to the conversion pathway of tryptophan to indole, which is consistent with the determined indole production observed in the in vitro assays [41]. The presence of the bacillibatin gene cluster showed the potential of siderophore production, while the detection of Pi transporters and the Pho regulon indicated a possibility for inorganic phosphate solubilization. The presence of nif(U) and nif(S) was also determined in both genomes suggesting the possibility of the strain to fix environmental nitrogen. The properties mentioned above are consistent with the in vitro and in vivo PGP activities determined experimentally in previous studies for both strains [41].
The results obtained for the assembly of B. altitudinis 19RS3 and B. altitudinis T5S-T4 genomes are like the reported for other Bacillus PGP strains such as B. flexus KLBMP 4941 [15–67], B. pumilus GM3FR [68], B. mycoides GM6LP [69], B. vallismortis NBIF-001 [70], B. velezensis 2A-2B [71], and B. velezensis UCMB5140 [14]. Particularly the genome of B. altitudinis FD48 [72] comprises several genes related to plant growth promotion mechanisms, such as those for the biogenesis of organic acids involved in inorganic phosphorus solubilization, iron, and siderophore uptake systems, and nitrogen metabolism. Perhaps of this, genome annotation isn´t available to realize a deeper genome comparison. The PGP genes reported for B. subtilis EA-CB0575 [28] related to IAA, siderophore production, acetoin, 2,3-butanediol, and LPs production, nitrogen fixation, and phosphate solubilization are like those detected in B. altitudinis 19RS3 and B. altitudinis T5S-T4 genomes. The comparison realized with B. altitudinis W3, B. altitudinis GQYP101, and B. velezensis FZB42 genomes indicated that our strains present some unique genes able to promote I. paraguariensis growth. The five genomes present genes associated with the production of volatile compounds as 2,3-butanediol and acetoin, but the other PGP gene clusters were only detected in our studied strains. Also, we determinate the presence of loci for surfactins codification in the genomes of B. altitudinis 19RS3, B. altitudinis T5S-T4, and B. velezensis FZB42. The commercial strain FZB42 also presents genes to the phytase and iturin production. Each Bacillus PGP strain provides a subtle difference in terms of their plant growth-promoting and biocontrol activities. Future design of an effective bioinoculant should be based on combinations of PGP strains supplementing each other.
Conclusion
The best assembly for B. altitudinis 19RS3 and B. altitudinis T5S-T4 was obtained using the Velvet software. A great number of genes associated with PGP mechanisms were annotated and analyzed. It was found genes involved in auxin biosynthesis, siderophore production, phosphate metabolism, and nitrogen fixation. Also, other genes associated with acetoin and 2,3-butanediol production, motility, chemotaxis, adhesion, sporulation, and defense functions were encountered. The gene detection realized in the present study supports the PGP properties observed in previous assays.
The results obtained offer the basis for a better understanding of B. altitudinis 19RS3 and T5S-T4 biology and make them promissory for the development of novel strategies in the biotechnological application of these bacteria as bioinoculant. The information presented here will allow in-depth functional and comparative genome analyses to provide a better understanding of beneficial plant-bacteria associations.
Supporting information
S1 Table. Assembled genome quality statistics obtained for Bacillus altitudinis 19RS3 a plant growth-promoting bacterium isolated from Ilex paraguariensis St. Hil. using ABySS assembler.
https://doi.org/10.1371/journal.pone.0248274.s001
(DOCX)
S2 Table. Assembled genome quality statistics obtained for Bacillus altitudinis T5S-T4 a plant growth-promoting bacterium isolated from Ilex paraguariensis St. Hil. using ABySS assembler.
https://doi.org/10.1371/journal.pone.0248274.s002
(DOCX)
S3 Table. Assembled genome quality statistics obtained for Bacillus altitudinis 19RS3 a plant growth-promoting bacterium isolated from Ilex paraguariensis St. Hil. using SPAdes assembler.
https://doi.org/10.1371/journal.pone.0248274.s003
(DOCX)
S4 Table. Assembled genome quality statistics obtained for Bacillus altitudinis T5S-T4 a plant growth-promoting bacterium isolated from Ilex paraguariensis St. Hil. using SPAdes assembler.
https://doi.org/10.1371/journal.pone.0248274.s004
(DOCX)
S5 Table. Assembled genome quality statistics obtained for Bacillus altitudinis 19RS3 a plant growth-promoting bacterium isolated from Ilex paraguariensis St. Hil. using Velvet assembler.
https://doi.org/10.1371/journal.pone.0248274.s005
(DOCX)
S6 Table. Assembled genome quality statistics obtained for Bacillus altitudinis T5S-T4 a plant growth-promoting bacterium isolated from Ilex paraguariensis St. Hil. using Velvet assembler.
https://doi.org/10.1371/journal.pone.0248274.s006
(DOCX)
S7 Table. Assembled genome quality statistics obtained for Bacillus altitudinis 19RS3 a plant growth-promoting bacterium isolated from Ilex paraguariensis St. Hil. using SOAPdenovo2 assembler.
https://doi.org/10.1371/journal.pone.0248274.s007
(DOCX)
S8 Table. Assembled genome quality statistics obtained for Bacillus altitudinis T5S-T4 a plant growth-promoting bacterium isolated from Ilex paraguariensis St. Hil. using SOAPdenovo2 assembler.
https://doi.org/10.1371/journal.pone.0248274.s008
(DOCX)
S9 Table. Assembled genome quality statistics obtained for Bacillus altitudinis 19RS3 a plant growth-promoting bacterium isolated from Ilex paraguariensis St. Hil. using geneious assembler with the Velvet algorithm.
https://doi.org/10.1371/journal.pone.0248274.s009
(DOCX)
S10 Table. Assembled genome quality statistics obtained for Bacillus altitudinis T5S-T4 a plant growth-promoting bacterium isolated from Ilex paraguariensis St. Hil. using geneious assembler with the Velvet algorithm.
https://doi.org/10.1371/journal.pone.0248274.s010
(DOCX)
S11 Table. Assembled genome quality statistics obtained for Bacillus altitudinis 19RS3 a plant growth-promoting bacterium isolated from Ilex paraguariensis St. Hil. using CLC workbench assembler.
https://doi.org/10.1371/journal.pone.0248274.s011
(DOCX)
S12 Table. Assembled genome quality statistics obtained for Bacillus altitudinis T5S-T4 a plant-growth-promoting bacteria isolated from Ilex paraguariensis St. Hil. using CLC workbench assembler.
https://doi.org/10.1371/journal.pone.0248274.s012
(DOCX)
References
- 1. Chakraborty AP, Chakraborty BN, Chakraborty U. Bacillus megaterium from tea rhizosphere promotes growth and induces systemic resistance in tea against Sclerotium rolfsii. Indian Phytopathol. 2015;68(3): 237–247.
- 2. Mendis HC, Thomas VP, Schwientek P, Salamzade R, Chien JT, Waidyarathne P, et al. Strain-specific quantification of root colonization by plant growth promoting rhizobacteria Bacillus firmus I-1582 and Bacillus amyloliquefaciens QST713 in non-sterile soil and field conditions. PLoS One. 2018;13(2): e0193119. pmid:29447287
- 3.
Bergottini VM, Benrey B, Sosada, Otegui MB, Zapata PD, Junier P. Testing plant growth promoting rhizobacteria (PGPR) isolates as inoculants for Ilex paraguariensis (yerba mate). In: 5th Swiss Microbial Ecology Meeting (SME). Murten, Switzerland. 2013. p. 64.
- 4. Sivasakthi S, Usharani G, Saranraj P. Biocontrol potentiality of plant growth promoting bacteria (PGPR)-Pseudomonas fluorescens and Bacillus subtilis: a review. Afr J Agric Res. 2014;9(16): 1265–1277.
- 5. Kuan KB, Othman R, Abdul Rahim K, Shamsuddin ZH. Plant Growth-Promoting Rhizobacteria Inoculation to Enhance Vegetative Growth, Nitrogen Fixation and Nitrogen Remobilisation of Maize under Greenhouse Conditions. PLoS One. 2016;11(3): e0152478 pmid:27011317
- 6. Singh RP, Jha PN. The Multifarious PGPR Serratia marcescens CDP-13 Augments Induced Systemic Resistance and Enhanced Salinity Tolerance of Wheat (Triticum aestivum L.). PLoS One. 2016;11(6): e0155026. pmid:27322827
- 7. Xiang N, Lawrence KS, Kloepper JW, Donald PA, McInroy JA. Biological control of Heterodera glycines by spore-forming plant growth-promoting rhizobacteria (PGPR) on soybean. PloS One. 2017;12(7): e0181201. pmid:28704498
- 8. Yadav AN, Verma P, Kour D, Rana KL, Kumar V, Singh B, et al. Plant microbiomes and its beneficial multifunctional plant growth promoting attributes. Int J Environ Sci Nat Resour. 2017;3(1): 1–8.
- 9. Alexander A, Singh VK, Mishra A, Jha B. Plant growth promoting rhizobacterium Stenotrophomonas maltophilia BJ01 augment endurance against N2 starvation by modulating physiology and biochemical activities of Arachis hypogea. PLoS One. 2019;14(9): e0222405. pmid:31513643
- 10. Bashan Y, Levanony H. Current status of Azospirillum inoculation technology: Azospirillum as a challenge for agriculture. Can J Microbiol. 1990;36(9): 591–608.
- 11. Miller SH, Browne P, Prigent‐Combaret C, Combes‐Meynet E, Morrissey JP, O’Gara F. Biochemical and genomic comparison of inorganic phosphate solubilization in Pseudomonas species. Environ Microbiol Rep. 2010;2(3): 403–411. pmid:23766113
- 12. Mosimann C, Oberhänsli T, Ziegler D, Nassal D, Kandeler E, Boller T, et al. Tracing of Two Pseudomonas Strains in the Root and Rhizoplane of Maize, as Related to Their Plant Growth-Promoting Effect in Contrasting Soils. Front Microbiol. 2017;7: 2150. pmid:28119675
- 13. Choudhary DK, Johri BN. Interactions of Bacillus spp. and plants–with special reference to induced systemic resistance (ISR). Microbiol res. 2009;164(5): 493–513. pmid:18845426
- 14. Reva ON, Larisa SA, Mwakilili AD, Tibuhwa D, Lyantagaye S, Chan WY, et al. Complete genome sequence and epigenetic profile of Bacillus velezensis UCMB5140 used for plant and crop protection in comparison with other plant-associated Bacillus strains. Appl Microbiol Biotechnol. 2020: 1–14. pmid:32651600
- 15. Wang TT, Ding P, Chen P, Xing K, Bai JL, Wan W, et al. Complete genome sequence of endophyte Bacillus flexus KLBMP 4941 reveals its plant growth promotion mechanism and genetic basis for salt tolerance. J Biotechnol. 2017;260: 38–41. pmid:28888960
- 16. Kashyap BK, Solanki MK, Pandey AK, Prabha S, Kumar P, Kumari B. Bacillus as plant growth promoting rhizobacteria (PGPR): a promising green agriculture technology. Plant Health Under Biotic Stress. Singapore: Springer; 2019. pp. 219–236.
- 17. Kumar A, Patel JS, Meena VS, Srivastava R. Recent advances of PGPR based approaches for stress tolerance in plants for sustainable agriculture. Biocatal Agric Biotechnol. 2019;20: 101271.
- 18. Lu X, Zhou D, Chen X, Zhang J, Huang H, Wei L. Isolation and characterization of Bacillus altitudinis JSCX-1 as a new potential biocontrol agent against Phytophthora sojae in soybean [Glycine max (L.) Merr.]. Plant Soil. 2017;416(1–2): 53–66.
- 19. Garkovenko AV, Vasilyev IY, Ilnitskaya EV, Radchenko VV, Asaturova AM, Kozitsyn AE, et al. Draft Genome Sequence of Bacillus velezensis BZR 336g, a Plant Growth-Promoting Antifungal Biocontrol Agent Isolated from Winter Wheat. Microbiol Resour Announc. 2020;9(30). pmid:32703828
- 20.
Catarina LEAL, Fontaine F, Aziz, A, Egas C, Clement C, Trotel-Aziz P. Genome sequence analysis of Bacillus subtilis PTA-271 isolated from a Vitis vinifera (cv. Chardonnay) rhizospheric soil: a highlight on some of its biocontrol traits. 2020. Available from: https://assets.researchsquare.com/files/rs-47930/v1_stamped.pdf
- 21. Zhu Z, Peng Q, Man Y, Li Z, Zhou X, Bai L, et al. Analysis of the antifungal properties of Bacillus velezensis B-4 through a bioassay and complete-genome sequencing. Front Genet. 2020;11. pmid:32765583
- 22. Ongena M, Jacques P. Bacillus lipopeptides: versatile weapons for plant disease biocontrol. Trends Microbiol. 2008;16: 115–125. pmid:18289856
- 23. Chen XH, Koumoutsi A, Scholz R, Eisenreich A, Schneider K, Heinemeyer I, et al. Comparative analysis of the complete genome sequence of the plant growth-promoting bacterium Bacillus amyloliquefaciens FZB42. Nat Biotechnol. 2007;25: 1007–1014. pmid:17704766
- 24. Vanittanakom N, Loeffler W, Koch U, Jung G. Fengycin- a novel antifungal lipopeptide antibiotic produced by Bacillus subtilis F-29-3. J Antibio. 1986;39: 888–901. pmid:3093430
- 25. Thimon L, Peypoux F, Magetdana R, Roux B, Michel G. Interactions of bioactive lipopeptides, iturin-a and surfactin from Bacillus subtilis. Biotechnol Appl Bioc. 1992;16: 144–151. pmid:1457050
- 26. Dertz EA, Xu JD, Stintzi A, Raymond KN. Bacillibactin mediated iron transport in Bacillus subtilis. J Am Chem Soc. 2006;128: 22–23. pmid:16390102
- 27. Nazari M, Smith DL. A PGPR-Produced Bacteriocin for Sustainable Agriculture: A Review of Thuricin 17 Characteristics and Applications. Front Plant Sci. 2020;11. pmid:32733506
- 28. Franco-Sierra ND, Posada LF, Santa-María G, Romero-Tabarez M, Villegas-Escobar V, Álvarez JC. Bacillus subtilis EA-CB0575 genome reveals clues for plant growth promotion and potential for sustainable agriculture. Funct Integr Genomics. 2020: 1–15. pmid:32198678
- 29. Kaymak HC, Yarali F, Guvenc I, Donmez MF. The effect of inoculation with plant growth rhizobacteria (PGPR) on root formation of mint (Mentha piperita L.) cuttings. Afr J Biotechnol. 2008;7(24).
- 30. Han HS, Lee KD. Effect of co-inoculation with phosphate and potassium solubilizing bacteria on mineral uptake and growth of pepper and cucumber. Plant soil Environ. 2006;52(3): 130.
- 31. Supanjani HS, Han HS, Jung JS, Lee KD. Rock phosphate-potassium and rock solubilising bacteria as alternative, sustainable fertilizers. Agronomy for Sustainable Development, Springer Verlag. 2006;26(4): 233–240.
- 32. Hafeez FY, Yasmin S, Ariani D, Zafar Y, Malik KA. Plant growth-promoting bacteria as biofertilizer. Agro Sustain Dev. 2006;26: 143–150.
- 33. Wang J, Xing J, Lu J, Sun Y, Zhao J, Miao S, et al. Complete Genome Sequencing of Bacillus velezensis WRN014, and Comparison with Genome Sequences of other Bacillus velezensis Strains. J Microbiol Biotechnol. 2019;29(5): 794–808. pmid:31030454
- 34. Orhan E, Esitken A, Ercisli S, Turan M, Sahin F. Effects of plant growth promoting rhizobacteria (PGPR) on yield, growth and nutrient contents in organically growing raspberry. Sci Hortic. 2006;111(1): 38–43.
- 35. Gamez RM, Ramirez S, Montes M, Cardinale M. Complementary Dynamics of Banana Root Colonization by the Plant Growth-Promoting Rhizobacteria Bacillus amyloliquefaciens Bs006 and Pseudomonas palleroniana Ps006 at Spatial and Temporal Scales. Microb Ecol. 2020: 1–13. pmid:32778917
- 36. Dutta J, Thakur D. Evaluation of multifarious plant growth promoting traits, antagonistic potential and phylogenetic affiliation of rhizobacteria associated with commercial tea plants grown in Darjeeling, India. PLoS One. 2017;12(8): e0182302. pmid:28771547
- 37. Kenneth OC, Nwadibe EC, Kalu AU, Unah UV. Plant growth promoting rhizobacteria (PGPR): A novel agent for sustainable food production. Am J Agric Biol Sci. 2019;14: 35–54.
- 38.
Alonso J, Desmarchelier C. Plantas medicinales autóctonas de la argentina. Bases científicas para su aplicación en atención primaria de la salud. 1st ed. Aires Buenos: Literature of Latin America; 2005. pp. 614–617.
- 39.
Margalot JA. Geografía de Misiones. 6th ed. Buenos Aires: Printed; 1994. pp. 110–111, 164.
- 40.
INYM—INSTITUTO NACIONAL DE LA YERBA MATE. Relevamiento Aerofotogramétrico de Plantaciones. 2019. Available from: http://www.inym.org.ar/el-relevamiento-aerofotogrametrico-deplantaciones-encargado-por-el-inym/.
- 41. Laczeski ME, Onetto AL, Cortese IJ, Mallozzi G, Castrillo ML, Bich GA, et al. Isolation and selection of endophytic spore-forming bacteria with plant growth promoting properties isolated from Ilex paraguariensis St. Hil. (Yerba mate). An Acad Bras Cienc. 2020;92. pmid:32638866
- 42. Reddy TBK, Thomas AD, Stamatis D, Bertsch J, Isbandi M, Jansson J, et al. The Genomes OnLine Database (GOLD) v.5: a metadata management system based on a four level (meta)genome project classification. Nucleic Acids Res. 2015;43: D1099–D1106. pmid:25348402
- 43. Li Z, Chen Y, Mu D, Yuan J, Shi Y, Zhang H, et al. Comparison of the two major classes of assembly algorithms: overlap–layout–consensus and de-bruijn-graph. Brief Funct Genomics. 2012;11(1): 25–37. pmid:22184334
- 44. Medvedev P, Pham S, Chaisson M, Tesler G, Pevzner P. Paired de bruijn graphs: a novel approach for incorporating mate pair information into genome assemblers. J Comput Biol. 2011;18(11): 1625–34. pmid:21999285
- 45. Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008;18: 821–829. pmid:18349386
- 46. Simpson JT, Wong K, Jackman SD, Schein JE, Jones SJ, Birol I. ABySS: a parallel assembler for short read sequence data. Genome res. 2009;19(6): 1117–1123. pmid:19251739
- 47. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19(5): 455–77. pmid:22506599
- 48. Luo R, Liu B, Xie Y, Li Z, Huang W, Yuan J, et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience. 2012;1(1): 2047–217X. pmid:23587118
- 49. Mikheenko A, Prjibelski A, Saveliev V, Antipov D, Gurevich A. Versatile genome assembly evaluation with QUAST-LG. Bioinformatics. 2018;34(13): i142–i150. pmid:29949969
- 50.
Sambrook J, Rusell DW. Molecular Cloning: a Laboratory Manual. Nueva York: Cold Spring Harbor; 2001.
- 51.
Cariaga Martinez AE, Zapata PD. Protocolos de extracción de ADN. In: El laboratorio de biología molecular. Edición ampliada. Buenos Aires: Ed. Universitaria; 2007. pp. 23–39.
- 52. Andrews S. FastQC a quality control tool for high throughput sequence data. Babraham bioinformatics. 2010. Available from: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/.
- 53. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15): 2114–2120. pmid:24695404
- 54. Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, et al. Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics. 2012;28(12): 1647–1649. pmid:22543367
- 55.
Knudsen B, Knudsen T, Flensborg M, Sandmann H, Heltzen M, Andersen A, et al. CLC Main Workbench. Version 5.5. Aarhus: CLC bio; 2007.
- 56. Gurevich A, Vladislav S, Nikolay V, Glenn T. QUAST: quality assessment tool for genome assemblies. Bioinformatics. 2013;29 (8): 1072–1075. pmid:23422339
- 57. Liao YC, Lin SH, Lin HH. Completing bacterial genome assemblies: strategy and performance comparisons. Sci Rep. 2015;5: 8747. pmid:25735824
- 58. Schmid M, Frei D, Patrignani A, Schlapbach R, Frey JE, Remus-Emsermann MN, et al. Pushing the limits of de novo genome assembly for complex prokaryotic genomes harboring very long, near identical repeats. Nucleic acids res. 2018;46(17): 8953–8965. pmid:30137508
- 59. Seemann T. Prokka: Rapid prokaryotic genome annotation. Bioinformatics. 2014;30: 20682069. pmid:24642063
- 60. Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, et al. The RAST server: Rapid Annotations using Subsystems Technology. BMC Genomics. 2008;9: 75. pmid:18261238
- 61. Moriya Y, Itoh M, Okuda S, Yoshizawa AC, Kanehisa M. KAAS: an automatic genome annotation and pathway reconstruction server. Nucleic Acids Res. 2007;35: W182–W185. pmid:17526522
- 62. Kremer FS, McBride AJA, Pinto L DS. Approaches for in silico finishing of microbial genome sequences. Genet Mol Biol. 2017;40(3): 553–576. pmid:28898352
- 63. Cortese IJ, Castrillo ML, Zapata PD, Laczeski ME. Efecto del filtrado de secuencias en el ensamblado del genoma de Bacillus altitudinis aislado de Ilex paraguariensis. Acta Biol Colomb. 2021. Forthcoming.
- 64. Khan AR, Pervez MT, Babar ME, Naveed N, Shoaib M. A comprehensive study of de novo genome assemblers: current challenges and future prospective. Evol Bioinform. 2018;14. pmid:29511353
- 65. Liu B, Liu C, Li D, Li Y, Ting H, Yiu SM, et al. BASE: a practical de novo assembler for large genomes using long NGS reads. BMC Genomics. 2016. pmid:27586129
- 66. Al-Okaily AA. HGA: de novo genome assembly method for bacterial genomes using high coverage short sequencing reads. BMC genomics. 2016;17: 193. pmid:26945881
- 67. Xiong YW, Li XW, Wang TT, Gong Y, Zhang CM, Xing K, et al. Root exudates-driven rhizosphere recruitment of the plant growth-promoting rhizobacterium Bacillus flexus KLBMP 4941 and its growth-promoting effect on the coastal halophyte Limonium sinense under salt stress. Ecotoxicol Environ Saf. 2020;194: 110374. pmid:32120174
- 68. Hollensteiner J, Poehlein A, Daniel R, Liesegang H, Vidal S, Wemheuer F. Draft Genome Sequence of Bacillus pumilus Strain GM3FR, an Endophyte Isolated from Aerial Plant Tissues of Festuca rubra L. Genome Announc. 2017;5(13): e00085–17. pmid:28360161
- 69. Wemheuer F, Hollensteiner J, Poehlein A, Liesegang H, Daniel R, Wemheuer B. Draft genome sequence of the endophyte Bacillus mycoides strain GM6LP isolated from Lolium perenne. Genome Announc. 2018;6(5): e00011–18. pmid:29437086
- 70. Liu X, Min Y, Huang D, Zhou R, Fang W, Liu C, et al. Complete Genome Sequence of Bacillus vallismortis NBIF-001, a Novel Strain from Shangri-La, China, That Has High Activity against Fusarium oxysporum. Genome Announc. 2017;5(48): e01305–17. pmid:29192077
- 71. Martínez-Raudales I, De La Cruz-Rodríguez Y, Alvarado-Gutiérrez A, Vega-Arreguín J, Fraire-Mayorga A, Alvarado-Rodríguez M, et al. Draft genome sequence of Bacillus velezensis 2A-2B strain: a rhizospheric inhabitant of Sporobolus airoides (Torr.) Torr., with antifungal activity against root rot causing phytopathogens. Stand Genomic Sci. 2017;12(1): 73. pmid:29225729
- 72. Kumaravel S, Thankappan S, Raghupathi S, Uthandi S. Draft genome sequence of plant growth-promoting and drought-tolerant Bacillus altitudinis FD48, isolated from rice phylloplane. Genome Announc. 2018;6(9): e00019–18. pmid:29496824