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. 2019 Dec 24;28:105040. doi: 10.1016/j.dib.2019.105040

Genomic sequence data and single nucleotide polymorphism genotyping of Bacillus anthracis strains isolated from animal anthrax outbreaks in Northern Cape Province, South Africa

Kgaugelo Edward Lekota a,b,∗, Ayesha Hassim a, Henriette van Heerden a
PMCID: PMC6965700  PMID: 31970271

Abstract

This report presents genomic data on sequence reads and draft genomes of Bacillus anthracis isolates from anthrax outbreaks in animals in an endemic region of South Africa as well as genotyping of the strains using canonical single nucleotide polymorphisms (canSNPs). It is derived from an article entitle “Phylogenomic structure of B. anthracis strains in the Northern Cape Province, South Africa revealed novel single nucleotide polymorphisms”. Whole genome sequencing (WGS) of twenty-three B. anthracis strains isolated during 1998 and 2009 anthrax outbreaks in the Northern Cape Province (NCP), as well as a strain from Botswana (6102_6B) and one from Namibia-South Africa transfrontier conservation area (Sendlingsdrift, 6461_SP2) were obtained using both the HiSeq 2500 and MiSeq Illumina platforms. Mismatch amplification mutation assay (melt-MAMA) qPCR were used to identify the canSNP genotypes within the global population of B. anthracis. DNA sequencing data is available at NCBI Sequence Read Archive and GenBank database under accession N0. PRJNA580142 and PRJNA510736 respectively. A phylogenetic tree and CanSNP typing profiles of the isolates are presented within this article.

Keywords: Bacillus anthracis, Whole genome sequencing (WGS), Canonical single nucleotide polymorphism (canSNP)


Specifications Table

Subject Microbial genomics
Specific subject area Comparative microbial genomics of B. anthracis strains for evolution and genetic diversity using single nucleotide polymorphisms (SNPs)
Type of data Sequence files, Table, figure
How data were acquired DNA extraction was performed on pure cultures using DNA Mini kit (Qiagen) purification kit. High-throughput DNA sequencing using Illumina HiSeq 2500 and MiSeq Sequencing system. De novo assemblies was performed using CLC-Genomic workbench version 11.1. Assembled genomes were annotated using NCBI Prokaryotic Genome Annotation Pipeline version 4.7. SNP genotyping Can SNP typing scheme was performed on LightCycler™ 96 (Roche Applied Science). MEGA version 7 was used to generate phylogenetic tree.
Data format Raw and analysed data of whole genome sequences (Fastq and fasta)
Parameters for data collection Samples were collected from animals that died of anthrax. Isolated pure cultures from sheep blood agar were used for DNA extractions, genotyping and sequencing.
Description of data collection Pure culture isolates were identified using classical bacteriological methods including penicillin and bacteriophage sensitivity. DNA samples of these isolates were verified using B. anthracis plasmid and chromosomal gene targets using real- time PCR. Trimmed sequence reads were used for de novo assembly.
Data source location University of Pretoria, Department of Veterinary and Tropical Diseases, Pretoria, South Africa
Data accessibility The sequenced data were deposited to Sequence Read Archive (SRA) and GenBank in National Center for Biotechnology Information (NCBI). Accession numbers are included in this manuscript in a table format.
BioProject numbers:
PRJNA510736 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA510736)
PRJNA580142 (https://www.ncbi.nlm.nih.gov/sra/PRJNA580142)
With the article
Related research article Lekota KE, Bezuidt OKI, Mafofo J, Rees J, Muchayeyi FC, Madoroba E, van Heerden H. Whole genome sequencing and identification of Bacillus endophyticus and B. anthracis isolated from anthrax outbreaks in South Africa. BMC Microbiology (2018) 18:67. doi: 10.1186/s12866-018-1205-9 [1]
Value of the Data
  • •

    The data sheds light of draft genomes and genetic diversity of B. anthracis strains from Northern Cape Province from two anthrax outbreaks during 1998 and 2009 in South Africa.

  • •

    The data serve as a benchmark for other researchers to determine the evolution and genetic diversity of B. anthracis globally.

  • •

    The data could be used to determine the relationship between B. anthracis strains from South Africa and other areas and to expand the canSNP typing scheme using melt-MAMA.

  • •

    The data might enable trace-back in and between anthrax cases/outbreaks, especially within the context of southern Africa.

1. Data description

We present the genomic data and analysis of whole genome sequences of B. anthracis strains isolated from animals anthrax outbreaks in Northern Cape Province. Sequence reads (in fastq format) and assembled genomes (in fasta format) were deposited at NCBI SRA and GenBank database under project accession No. PRJNA580142 and PRJNA510736 respectively. The information on the sample collection with accession numbers, SNP genotyping and genome assemblies is represented in Table 1, Table 2, Table 3 respectively. Isolates were also grouped using canonical SNPs (Table 4) typing scheme [2] used for phylogenetic branches (Fig. 1).

Table 1.

Whole genome sequences of Bacillus anthracis strains collection with their accession numbers submitted to GenBank and Sequence Reads Achieve (SRA).

Strain name Host Collection date Location Accession number Sequence coverage
2949_1D Ovine 10-May-2009 South Africa: Northern Cape Province RXZW00000000 145
2991_1B Ovine 10-May-2009 South Africa: Northern Cape Province RXZV00000000 199
3008_1B Bovine 10-May-2009 South Africa: Northern Cape Province RXZU00000000 155
3122_2B Oryx gazella 10-May-2009 South Africa: Northern Cape Province RXZT00000000 168
3132_1B Tragelaphus strepsiceros 10-May-2009 South Africa: Northern Cape Province RXZS00000000 201
3275_2D Soil 10-May-2009 South Africa: Northern Cape Province RXZR00000000 267
3517_1C Tragelaphus strepsiceros 10-May-2009 South Africa: Northern Cape Province RXZQ00000000 166
3517_2C Tragelaphus strepsiceros 10-May-2009 South Africa: Northern Cape Province RXZP00000000 137
3631_4C Tragelaphus strepsiceros 10-May-2009 South Africa: Northern Cape Province RXZO00000000 187
3631_3D Tragelaphus strepsiceros 10-May-2009 South Africa: Northern Cape Province RXZN00000000 189
3631_8D Tragelaphus strepsiceros 10-May-2009 South Africa: Northern Cape Province RXZM00000000 300
2110 Ovis aries 1998 South Africa: Northern Cape Province RXZL00000000 38
JB10 Equus burchellii quagga 2009 South Africa: Northern Cape Province RXZK00000000 60
JB25 Tragelaphus strepsiceros 2009 South Africa: Northern Cape Province SDEF00000000 80
3618_2D Tragelaphus strepsiceros 10-May-2009 South Africa: Northern Cape Province RXZJ00000000 178
6461_SP2 Capra aegagrus 2009 South Africa: Northern Cape Province SRP227303; SAMN13151840; SRR10357978 20
6102_6B Loxodonta 2009 Botswana SRP227303; SAMN13151841; SRR10357979 21
3631_7C Soil 2009 South Africa: Northern Cape Province SRP227303; SAMN13151842; SRR10357981 24
5838 Alcelaphus buselaphus 1998 South Africa: Northern Cape Province SRP227303; SAMN13151843; SRR10357980 17
2991_2B Ovine 2009 South Africa: Northern Cape Province SRP227303; SAMN13151844; SRR10357985 19
3080_3B Bovine 2009 South Africa: Northern Cape Province SRP227303; SAMN13151845; SRR10357983 17
3079_1C Oryx gazella 2009 South Africa: Northern Cape Province SRP227303; SAMN13151846; SRR10357984 25
3080_5A Bovine 2009 South Africa: Northern Cape Province SRP227303; SAMN13151847; SRR10357982 26
3080_1B Bovine 2009 South Africa: Northern Cape Province SRP227303; SAMN13151848; SRR10357977 12
3090_1B Unknown 2009 South Africa: Northern Cape Province SRP228283; SAMN10614343; SRR10390628 26

Table 2.

Canonical SNPs used for genotyping of B. anthracis strains. SNP are in relation to B. anthracis Ames ancestor chromosome (NC_007530.2).

B. anthracis Strains SNP-branch
A.Br.006 A.Br.007 A.Br.008 A.Br.005 A.Br.004 A.Br.003 A.Br.002 A.Br.001 A.Br.009 A.Br.011 A.Br.014 A.Br.013

Ancestral Template SNP C A A A T T C T A G T A
Derived Template SNP A G C G C C T C G A C G
Ames ancestor A.Br.001 (Ames) A A A G C C T C A G T A
Sterne A.Br.002 (Sterne) A A A G C C T T A G T A
3080_5A A.Br.002 (Sterne) A A A G C C T T A G T A
3080_1B A.Br.002 (Sterne) A A A G C C T T A G T A
6102_6B A.Br.005/006 (Ancient A) A A A A T T C T A G T A
6461_SP2 A.Br.005/006 (Ancient A) A A A A T T C T A G T A
2110 A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
5838 A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
3631_1C A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
3080_3B A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
3079_1C A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
3090_1B A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
JB10/NC14 A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
JB25/NC_29 A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
2991_2B A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
3618_2D A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
3517_1C A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
3631_4C A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
3631_7C A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
3275_2D A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
3122_2B A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
3008_1B A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
2949_1D A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
2991_1B A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
3517_2C A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
3132_1B A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
3631_3D A.Br.003/004 (A,Br.101) A A A G C C C T A G C A
3631_8D A.Br.003/004 (A.Br.101) A A A G C C C T A G C A
Aust94 A.Br.003/004 (Aust94) A A A G C C C T A G C G
Vollum A.Br.007 (Vollum) A G A G T T C T A G T A

Table 3.

Genomic features of the de novo assemblies B. anthracis strains (n = 15) using CLC Genomic workbench.

Strain name Sequence coverage Number of contigs N50 Minimum contig size (bp) Maximum contig size (bp) GC content Genome Size Total coding sequences (CDSs) Total number of RNAs
2949_1D 145 441 28 406 423 125 072 35.1 5 147 319 5 764 65
2991_1B 199 378 38 630 316 185 192 35.1 5 395 612 5 736 54
3008_1B 155 442 34 402 406 226 189 35.1 5 418 987 5 763 63
3122_2B 168 431 34 419 361 175 230 35.1 5 401 847 5 740 54
3132_1B 201 170 74 712 146 335 422 35.1 5 350 330 5 611 97
3275_2D 267 751 14 738 509 89 998 35.1 5 352 180 5 463 59
3517_1C 166 121 203 477 354 343375 35.1 5 416 293 5 692 68
3517_2C 137 1194 9 613 352 55 932 35.1 5 265 628 5 869 37
3631_4C 187 385 35 768 418 177 852 35.1 5 402 081 5 718 68
3631_3D 189 513 22 221 415 108 007 35.1 4 654 382 5 766 52
3631_8D 300 882 14 279 401 98 835 35.1 5 252 949 5 717 68
2110 38 856 7 046 517 77 020 35.0 3 843 425 5 906 74
JB10 60 1856 6 493 153 50 654 35.1 5 180 538 5 861 34
JB25 80 136 91 967 519 646 630 35.1 5 422 668 5 695 88
3618_2D 178 72 154 041 2803 489 427 35.1 5 417 873 5 674 62

Table 4.

Melt-MAMA primers targeting canonical SNPs of the existing Birdsell et al. (2012) primers used in this study for the phylogenetic branches.

Assay name aReference genome position Derived MAMA 5′-3′ Ancestral MAMA
5′-3′
Common reverse 5′-3′ Annealing Temperature (°C)
Existing primers by Birdsell et al., 2012
A.Br.001 182 106 cggggcggggcggggcgggcAGAAGGAGCAAGTAATGTTATAGGTTTAaGT GGAGCAAGTAATGTTATAGGTTTAcGC ACCTAAAATCGATAAAGCGACTGC 55
A.Br.002 947 760 cggggcggggcggggcgggcAGAAGGAGCAAGTAATGTTATAGGTTTAaGT GGAGCAAGTAATGTTATAGGTTTAcGC ACCTAAAATCGATAAAGCGACTGC 55
A.Br.003 1 493 280 cggggcggggcggggcgggcAATTTAGATTTTCGTGTCGAATTAtGC AATTTAGATTTTCGTGTCGAATTAgGT TGTATAAAAACCTCCTTTTTCTACCTCAA 55
A.Br.004 3 600 786 cggggcggggcggggcgggcCGCCGTCATACTTTGGAAaGC CGCCGTCATACTTTGGAAcGT GAATTGGTGGAGCTATGGAAGGATTA 60
A.Br.005 3 842 864 cggggcggggcggggcgggcGAAAGATATATAAAAATGTTTTTTTATTTCGTtTG
GAAAGATATATAAAAATGTTTTTTTATTTCGTcTA GCTGCGTTTAGTTATGCAAATC
55
A.Br.006 162 509 cggggcggggcggggcgggcAATATGTTGTTGATCATTCCATCGCtTA
TATGTTGTTGATCATTCCATCGCgTC
TAGCGTTTTTAAGTTCATCATACCCATGC
55
A.Br.007 266439 cggggcggggcggggcgggcACAAGGTGGTAGTATTCGAGCTGAtTG
AATTACAAGGTGGTAGTATTCGAGCTGAcTA
CGAGACGATAAACTGAATAATACCATCCT
62.5
A.Br.008 3947375
cggggcggggcggggcgggcGTTACAAATATACGTTTAACAAGCcGC AAAAGTTACAAATATACGTTTAACAAGCtGA
CTACGCTATACGTTTTAGATGGAGATAATTC
55
A.Br.009 2589947
cggggcggggcggggcgggcCCACTGTTTTTGAACGGCTcTG GCCACTGTTTTTGAACGGCTaTA
TTTTAGGTATATTAACTGCGGATGATGC
60
A.Br.011 1455402
cggggcggggcggggcgggcCATAAAAGAAATCGGTACAATAGAAtAG CATAAAAGAAATCGGTACAATAGAAcAA
TCGGATATGATACCGATACCTTCTTATC
55
A.Br.014 5078168 ggggcggggcggggcggggcggggcAATGGTAAATTGTAATGTTGAGCTtC AATGGTAAATTGTAATGTTGAGCTgT TTTTTACTAAAAAATTACTTTTTTTGAAAA 57
A.Br.013 2465446 ggggcggggcggggcggggcggggcTTGTAAAAATTCTATGTGAATCACATtG TTGTAAAAATTCTATGTGAATCACATcA TTATCCACCTTCTTATAATTATTTATTACTAT 57

GC-clamp (cggggcggggcggggcgggc).

a

Bacillus anthracis Ames ancestor reference genome (NC_007530.2).

Fig. 1.

Fig. 1

Maximum likelihood phylogeny of the major canonical single nucleotide polymorphism (canSNP) groups for the 26 B. anthracis strains as well as B. anthracis Ames ancestor, Vollum and Sterne control sequences. Most of the B. anthracis strains (n = 21) grouped in the canSNP A.Br 003/004 (Aust94) clade (red), while two strains, 3080_1B and 3080_5A, isolated from bovine grouped in A.Br.001/002 (Sterne) group (green) and isolates from Botswana (6102_6B) and Sendlingsdrift (6461_SP2) grouped in the A.Br.005/006 (Ancient a) group (purple).

2. Experimental design, materials, and methods

2.1. Diagnostic real-time PCR for chromosomal and plasmids markers of B. anthracis

The identification of B. anthracis isolates was performed as described by WHO [3]. The 20 μl PCR reaction consisted of 10 μl of FastStart Essential master mix (Roche Applied Science), 0.5 μM of each primer, 0.2 μM of probe for each chromosomal and plasmid target pairs with fluorescein on the one and LCRed640 on the other (Tib MolBiol GmbH, Germany) and 2.5 μl of template DNA. The PCR conditions on a LightCycler™ Nano (Roche Applied Science) were used as described in WHO [3]. The PCR conditions on a LightCycler™ Nano (Roche Applied Science) consisted of an initial cycle at 95 °C for 10 minutes, slope at 20 °C/second, followed by 40 cycles of 95 °C for 10 seconds; 57 °C for 20 seconds; 72 °C for 30 seconds, slope 20 °C/second with one single signal acquisition at the end of annealing cycle. Denaturation at 95 °C for 3 seconds with a slope 20 °C/second; 40 °C for 30 seconds, slope 20 °C/second; 80 °C for 3 seconds at a slope of 0.1 °C/second with continuous acquisition of the signal. Cooling to 40 °C for 30 seconds, slope 20 °C/second.

2.2. Genotyping of B. anthracis strains using Melt-MAMA assays

Melt-MAMA assays of the canSNP markers were used to amplify the DNA of the NCP B. anthracis strains. The panel included 12 canSNPs that were used for the grouping of the B. anthracis strains (n = 26) using existing Melt-MAMA primers (Table 4) derived and ancestral controls were created as described by Birdsell et al. [2]. The reaction included 2.5 μl DNA diluted in 1× FastStart DNA Green Master (Roche Applied Science) with an ancestral forward and a derived forward SNP target primer (GC-clamp: no-GC-clamp) and a common reverse primer (Inqaba Biotec™) (Table 2) with a starting concentration of 0.2 μM depending on the ratio indicated which allowed for separation of melt peaks by at least 5 °C. Thermocycling parameters on the LightCycler™ 96 (Roche Applied Science) were 95 °C for 10 minutes, followed by 35 cycles at 95 °C for 15 seconds and 55 °C-60 °C (oligonucleotide dependent for 1 minute) for 35 cycles. End-point PCR amplicons were subjected to melt analysis using a dissociation protocol comprising of 95 °C for 15 seconds, followed by incremental temperature ramping (0.1 °C) from 60 °C to 95 °C. SYBR Green fluorescence intensity was measured at 530 nm at each ramp interval and plotted against temperature and observed as the separate melt peaks for each SNP. Controls included in every run were DNA from B. anthracis Ames, Vollum and Sterne 34F2 strains. Phylogenetic relationships between 26 B. anthracis strains were determined in the MEGA version 7 [4] using the maximum likelihood method based on the Tamura three-parameter model. The tree was generated with a bootstrap replication value of 500.

2.3. High-throughput sequencing and bioinformatics analysis

The DNA samples that were extracted from B. anthracis were subjected to library preparation by using the Nextera XT DNA Sample Prep kit (Illumina-compatible, Epicentre Biotechnology). Different sequence reads of B. anthracis genomes were generated on HiSeq 2500 and MiSeq instruments platforms. Clusters were generated on the flow cell using HiSeq Paired-End Cluster Generation kit (Ilumina, USA) for the HiSeq 2500 platform. Sequencing of paired end libraries were performed on the Illumina MiSeq and HiSeq 2500 sequencer using the 200-cycle SBS (sequencing by synthesis) sequencing v3 kit (Illumina, USA) and HiSeq Sequencing Kit (200 cycles) (Illumina, USA) respectively. Quality of the genome sequenced reads were assessed using FastQC software 0:10.1 [5]. Trimommatic version 0.33 [6] was used to remove the sequenced adapter, and ambiguous nucleotide reads. De novo assemblies of the paired end reads were performed using CLC Genomics Workbench version 11.1 (CLC, Denmark). The assembled contigs were ordered by Mauve tool version 2.3.1 [7] using B. anthracis Ames ancestor (GenBank accession numbers NC_007530.2, NC_007322.2 and NC_007323.3) in order to assess the accuracy and efficiency of the contigs. All trimmed sequence reads were also mapped to the reference using Burrows-Wheeler Aligner (BWA) version 0.7.12 [8] to determine B. anthracis replicons i.e. chromosome and the two plasmids. Assembled genomes were annotated using the NCBI Prokaryotic Genome Annotation pipeline. Sequenced reads were deposited to NCBI under Sequence Reads Archive (SRA), and assembled genomes to GenBank.

Acknowledgments

The authors would like to thank the farmers of the Northern Cape for their wholehearted participation in the study of anthrax in the region. We also wish to extend our appreciation to the Northern Cape Provincial government and State Veterinary Services for allowing us to conduct this study and improve our understanding of this zoonotic pathogen. We would like to thank the Institute of Tropical Medicine (ITM), Belgium, National Research Foundation and AgriSETA (Agriculture Sector Education Training Authority) in South Africa for funding.

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.dib.2019.105040.

Conflict of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

The following is the Supplementary data to this article:

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References

  • 1.Lekota K.E., Bezuidt O.K.I., Mafofo J., Rees J., Muchayeyi F.C., Madoroba E., van Heerden H. Whole genome sequencing and identification of Bacillus endophyticus and B. anthracis isolated from anthrax outbreaks in South Africa. BMC Microbiol. 2018;18:67. doi: 10.1186/s12866-018-1205-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Birdsell D.N., Pearson T., Price E.P., Hornstra H.M., Nera R.D., Stone N., Gruendike J., Kaufman E.L., Pettus A.H., Hurbon A.N., Buchhagen J.L., Harms N.J., Chanturia G., Gyuranecz M., Wagner D.M., Keim P.S. Melt analysis of mismatch amplification mutation assays (Melt-MAMA): a functional study of a cost-effective SNP genotyping assay in bacterial models. PLoS One. 2012;7 doi: 10.1371/journal.pone.0032866. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.World Health Organization (WHO) 4th edition. World Health Organization; 2008. Anthrax in Humans and Animals. [Google Scholar]
  • 4.Kumar S., Stecher G., Tamura K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol. Biol. Evol. 2016;33:1870–1874. doi: 10.1093/molbev/msw054. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Andrews S. 2010. FastQC: a Quality Control Tool for High Throughput Sequence Data. [Google Scholar]
  • 6.Bolger A.M., Lohse M., Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–2120. doi: 10.1093/bioinformatics/btu170. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Darling A.C., Mau B., Blattner F.R., Perna N.T. Mauve: multiple alignment of conserved genomic sequence with rearrangements. Genome Res. 2004;14:1394–1403. doi: 10.1101/gr.2289704. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Li H., Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25:1754–1760. doi: 10.1093/bioinformatics/btp324. [DOI] [PMC free article] [PubMed] [Google Scholar]

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