The assembled ATCC MP-9 genomes along with E. coli strains EC4115 (O157:H7; Eppinger et al., 2011 (link)) and K-12 substrain MG1655 (Blattner et al., 1997 (link)) were imported into SeqSphere+ (v.8.3; Ridom GmbH, Münster, Germany) for gene-by-gene alignment, allele calling, and comparison (Jünemann et al., 2013 (link)). MLST typing was performed using targeted and whole genome schemas developed for E. coli (Foley et al., 2009 (link); Zhou et al., 2020 (link)). We determined the Sequence Type (ST) by applying the 7-gene ST Achtman schema (Zhou et al., 2020 (link)). Allele sequences for the 7 genes (adk, fumC, gyrB, icd, mdh, purA, and recA) were accessed on the EnteroBase website5 and imported into Ridom SeqSphere+. A core genome (cg) MLST schema was developed using the closed chromosome of K-12 substrain MG1655 (GenBank accession U00096; Riley et al., 2006 (link)) as seed as previously described (Díaz et al., 2021 (link)). Core and accessory MLST targets were identified according to the inclusion/exclusion criteria of the SeqSphere+ Target Definer. The allele information from the targeted seven-gene schema and the defined core genome gene of the panel strains were used to establish phylogenetic hypotheses using the minimum-spanning method (Kruskal, 1956 (link); Francisco et al., 2009 (link)) with default settings in Ridom SeqSphere+ (v.8.3).
Seqsphere
Manufactured by Ridom
Sourced in Germany
SeqSphere+ is a laboratory software tool designed for sequence-based typing of microbial isolates. It provides a comprehensive workflow for analyzing next-generation sequencing data and performing multilocus sequence typing (MLST) analysis.
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Lab products found in correlation
Miseq platform, by Illumina (7 mentions)
Qiaamp dna mini kit, by Qiagen (2 mentions)
Nextera xt dna library preparation kit, by Illumina (2 mentions)
Seqsphere version 7, by Ridom (2 mentions)
Miseq sequencer, by Illumina (2 mentions)
Magattract hmw dna kit, by Qiagen (2 mentions)
Miseq instrument, by Illumina (2 mentions)
Hiseq 2500, by Illumina (2 mentions)
Nextera kit, by Illumina (2 mentions)
Dneasy blood and tissue kit, by Qiagen (2 mentions)
Miseq reagent kit v2, by Illumina (2 mentions)
Kapa hyper prep kit, by Roche (2 mentions)
Clc genomics workbench 11, by Qiagen (2 mentions)
Nextera xt dna sample preparation kit, by Illumina (2 mentions)
Identibac microarray, by Abbott (1 mentions)
Staphtype, by Ridom (1 mentions)
Ion torrent platform, by Thermo Fisher Scientific (1 mentions)
Nextseq 500 platform, by Illumina (1 mentions)
Version 7, by BioNumerics (1 mentions)
Lysostaphin, by Merck Group (1 mentions)
109 protocols using seqsphere
1
Comparative Genomic Analysis of E. coli Strains
2
Genomic Analysis of Salmonella Enterica
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Assembled genomes were imported into Ridom SeqSphere+ software, version 6.0.2 (Jünemann et al., 2013 (link)) and core genome multilocus sequence typing (cgMLST) profiles were assigned using the default Salmonella enterica task template with 3,002 core gene targets created based on EnteroBase S. enterica cgMLST v2 scheme,1 as previously described (Di Marcantonio et al., 2020 (link)). Default settings were applied for allele calling and cgMLST complex detection [complex cut-off ≤ 7 loci (Dangel et al., 2019 (link))]. Only genomes containing ≥98% good target sequences were used in further in silico analyses. Minimum-spanning tree (MST) was generated by pairwise comparison of cgMLST alleles ignoring missing values. Multilocus sequence typing (MLST) analysis of the set of 103 strains sequenced in this study was performed in Ridom SeqSphere + using the Achtman Salmonella seven locus MLST scheme, available at http://enterobase.warwick.ac.uk/species/index/senterica . A novel MLST profile (ST-8528) was generated for strain 2020-CB-4517-1-2 by submitting the sequencing reads directly to EnteroBase.
3
Salmonella Telelkebir Genomes cgMLST Analysis
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The cgMLST analysis was carried out using the Ridom SeqSphere+ software v6.0.2 (Ridom). An ad hoc core genome MLST (cgMLST) scheme was created for the gene-by-gene analysis with SeqSphere+ (Ridom® GmbH, Münster, Germany). Hence, the S. Typhimurium LT2 (NC_003197.1) genome comprising 4,451 genes was used as annotated reference. The cgMLST target definer tool was applied to 121 Salmonella Telelkebir genomes with the default settings of the software to define the core genome loci (Simon et al., 2018 (link)). A cgMLST tree was built using the neighbor-joining method. The cgMLST distance matrix showing pairwise comparison of allelic differences between 121 isolates is given in Supplementary Table 3 .
4
Genomic Analysis of B. pseudomallei Isolates
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Illumina short reads of the environmental B. pseudomallei isolates from this study were submitted to the Sequence Read Archive under the NCBI accession ERR9146399 (IND_S3) an ERR9138530 (IND_S14). Whole genome sequencing data of B. pseudomallei strains were analyzed in SeqSphere (Ridom GmbH, Germany) using our previously published B. pseudomallei core genome MLST (cgMLST) scheme (Lichtenegger et al., 2021 (link)). A UPGMA tree and a minimum spanning tree were constructed based on the allelic profiles of the isolates. Columns with missing values for at least one sample were removed before analysis, resulting in 3635 targets/distance columns. Figures were created and annotated with Ridom SeqSphere.
5
Genomic Analysis of MRSA Isolates
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The reads were de novo assembled using Velvet (General public licence version 2.0) integrated in Ridom SeqSphere+32 (link) using default settings: reads were trimmed until the average base quality of 30 was reached in a window of 20 bases. The samples were aligned to the COL reference sequence analysed by cgMLST using the software Ridom SeqSphere+ scheme based on 1861 genes33 (link),34 (link). More than 50-fold average coverage with an average read length of > 200 bp, and percentage good targets for cgMLST ≥ 97% was considered acceptable sequence quality for further data analysis. A phylogenetic tree was constructed in SeqSphere+ using their neighbour-joining tree algorithm (Fig. 1 ) and distance matrix calculation35 (link) was performed; missing values were pairwise ignored. Additional information was extracted regarding the ST, CC, spa and CT. The CT is an additional identifier that clusters together samples with very similar cgMLST profiles and every combination of genomic allele profiles is given a unique identifier. The threshold used to define the CT in the cgMLST analysis was up to 24 allele differences (https://www.cgmlst.org/ncs/schema/141106/ )10 (link).
6
Genome-based Brucella melitensis Genotyping
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Genome assemblies of Italian B. melitensis B. melitensis Brucella https://pubmlst.org/brucella/ [42 (link)] and accessed through Ridom SeqSphere+.
7
Comparative Genomics of Salmonella Typhimurium
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Whole genome sequences (WGS) of S. Typhimurium isolates from the feces of two patients with diarrhea and two slaughtered poultry from Ouagadougou, capital city of Burkina Faso, were analyzed by multilocus sequence typing (MLST). De novo assembly was performed using Velvet assembler included in the Ridom SeqSphere+ software. The sequencing reads were trimmed before assembly using default settings of Ridom SeqSphere+ (trim at both ends of the reads until the average base quality was > 30 in a window of 20 bases). An automatic k-mer mode was used to define the best k-mer value to be used in the assembly. The UPGMA dendrogram was constructed using the allele call results of the core genome MLST (cgMLST) targets. For comparative genomics, the obtained sequences of strains from human and poultry feces were compared to each other and to complete or draft genome sequences of 20 S. Typhimurium strains downloaded from Genbank (http://www.ncbi.nlm.nih.gov/genbank ).
8
Molecular Characterization of Bacterial Isolates
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All (n = 51) sequenced isolates were analyzed with Ridom SeqSphere + software v7.7.5 (Ridom GmbH, Germany) [30 ]. Quality analysis of the sequences was performed with FastQC v0.1.1.7 [31 ] and adapters were removed with Trimmomatic v0.36 [32 ]. Raw reads were assembled with SKESA v2.3.0 using default settings [33 ], and quality trimming was performed with an average quality of ≥ 30 and a window of 20 bases. Remapping and polishing were performed with the BWA-MEM mapping algorithm. Sequencing statistics are presented in Additional file 1 . Acquired AMR genes were identified from assembled genomes with NCBI AMRFinderPlus 3.2.3 [34 ], using 100% alignment and > 90% identity. STs were analyzed by using multilocus sequence types (MLST) [35 ] in Ridom SeqSphere + (Ridom, Munster, Germany). Warwick MLST scheme was chosen for E. coli isolates. E. coli isolates with novel STs were submitted to Enterobase [36 (link)] and K. pneumoniae isolates to Institut Pasteur [37 , 38 ] to assign new STs. Phylogenetic analysis was conducted for all E. coli and K. pneumoniae isolates with core genome multilocus sequence typing (cgMLST) by comparing 2513 and 2365 alleles with pairwise missing values, respectively. A cluster threshold was determined by 10 allelic differences [39 ].
9
Genomic Analysis of VREfm Isolates Using Illumina MiSeq
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The VREfm isolates were sequenced on the Illumina MiSeq platform (Illumina Inc., San Diego, USA) as previously described.7 (link) Raw reads were trimmed using BBDuk (https://sourceforge.net/projects/bbmap/ ) with the parameters ktrim = r, k = 23, mink = 11, hdist = 1, tbo, qtrim = r and minlength = 30, and assembled with SKESA v.2.2 with default settings except inclusion of the parameter –allow_snps. Only assemblies with a genome size in the range 2.7–3.2 Mb, a minimum depth of coverage of 30, and N50 of minimum 10 000 were included in the study. We used seqsphere+ v.8.2.0 (Ridom GmbH, Munster, Germany; seqsphere/">http://www.ridom.de/seqsphere/ ) with the previously published scheme for E. faecium for the initial bioinformatic analysis.8 (link) Sequencing reads were aligned, and SNPs were called using the NASP pipeline v.1.1.2.9 (link) In the pipeline, duplicated regions in the reference were masked using NUCmer v.3.1, reads were subsequently mapped to the E. faecium Aus0004 (CP003351.1) reference genome with BWA-mem v.0.7.16 and SNPs were called with GATK v.3.8.0.10–13 (link) Consensus bases had a minimum coverage of 10 and a minimum proportion of 0.9 for the called base. Pairwise comparisons between isolates of patients were performed using the consensus base matrix. Recombination regions were detected for every clone group and filtered out using Gubbins v.3.2.1.14 (link)
10
Comparative Genomics Analysis of Campylobacter jejuni
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Genes were predicted by using the annotation pipeline Prokka (Seemann, 2014 (link)), which depend on Prodigal (Hyatt et al., 2010 (link)) for gene prediction. Core genome multi-locus sequence typing (cgMLST) was made using Ridom SeqSphere+, version 8.2.0, using the Oxford v.1 schema (Cody et al., 2017 (link)). Single-nucleotide polymorphism (SNP) analysis was made using Snippy,2 version 4.0.2. The reference genome used for the SNP analysis was the GenBank C. jejuni reference NC002163.1. The percentage of the reference genome k-mers (20-mers) found in the assemblies was quantified using the tngs tool.
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