Genomics of an emerging clone of Salmonella serovar Typhimurium ST 313 from Nigeria and the Democratic Republic of Congo

Introduction: Salmonella enterica serovar Typhimurium ST313 is an invasive and phylogenetically distinct lineage present in sub-Saharan Africa. We report the presence of S. Typhimurium ST313 from patients in the Democratic Republic of Congo and Nigeria. Methodology: Eighteen S. Typhimurium ST313 isolates were characterized by antimicrobial susceptibility testing, pulsed-field gel electrophoresis (PFGE), and multilocus sequence typing (MLST). Additionally, six of the isolates were characterized by whole genome sequence typing (WGST). The presence of a putative virulence determinant was examined in 177 Salmonella isolates belonging to 57 different serovars. Results: All S. Typhimurium ST313 isolates harbored resistant genes encoded by blaTEM1b, catA1, strA/B, sul1, and dfrA1. Additionally, aac(6’)1aa gene was detected. Phylogenetic analyses revealed close genetic relationships among Congolese and Nigerian isolates from both blood and stool. Comparative genomic analyses identified a putative virulence fragment (ST313-TD) unique to S. Typhimurium ST313 and S. Dublin. Conclusion: We showed in a limited number of isolates that S. Typhimurium ST313 is a prevalent sequence-type causing gastrointestinal diseases and septicemia in patients from Nigeria and DRC. We found three distinct phylogenetic clusters based on the origin of isolation suggesting some spatial evolution. Comparative genomics showed an interesting putative virulence fragment (ST313-TD) unique to S. Typhimurium ST313 and invasive S. Dublin.

Most human infections are self-limiting; however, approximately 5% of all patients infected with non-typhoidal Salmonella will develop bacteremia.The very young, the elderly, the malnourished, or people with underlying diseases such as malaria or HIV are at a significantly higher risk of developing bacteremia compared to otherwise healthy individuals [8].Bacteremic patients have higher rates of hospitalization, often have prolonged courses of illness, and have higher case fatality rates [1,9].
While severe infections with non-typhoidal Salmonella are relatively rare in Europe and North America, several studies have shown that invasive non-typhoidal Salmonella is endemic in sub-Saharan Africa [10][11][12][13].In some of those countries the mortality in children caused by non-typhoidal Salmonella bacteremia exceeds the burden of malaria [12].In the Democratic Republic of Congo (DRC), a study conducted from 2002 to 2006 in a rural children's hospital showed that 62.1% of all bloodstream infections in children were caused by non-typhoidal Salmonella with Salmonella enterica serovars Typhimurium and Enteritidis accounting for 60.5% and 22.3% of the cases, respectively [13].
A retrospective study of S. Typhimurium describing invasive diseases from 1997 to 2004, identified 31 isolates from Malawi and 13 out of 20 from Kenya to be of a novel multilocus sequence type (MLST) ST313 [11].One S. Typhimurium ST313 isolate was completely sequenced and found to be phylogenetically distinct from other S. Typhimurium isolated in sub-Saharan Africa.It was suggested that S. Typhimurium ST313 is strongly associated with invasive disease due to adaptation to human host as a result of genome degradation, similar to the evolutionary history of S. Typhi [11].
However, there is limited data describing the isolation of ST313 from stool and thus it is unknown whether the presence of S. Typhimurium ST313 in invasive diseases is the consequence of the high prevalence of a regionally dominant clone, possibly causing gastroenteritis in a susceptible human population, or due to a more invasive clone which is just one of many strains circulating in the local population [14].
The objective of this study was to investigate the genetic characteristics of 18 S. Typhimurium ST313 isolates in a spatial and temporal context.The isolates were obtained from both human stool and blood samples in patient from two sub-Saharan African countries; Nigeria and the DRC isolated in 2002 and 2005 in Nigeria and from 2002 to 2006 in DRC.

Bacterial isolates and molecular typing
During 2004 and 2005, blood samples were collected from seven major hospitals and a private diagnostic laboratory in the province of Ibadan, Nigeria.A total of 16 Salmonella isolates were recovered from 223 samples; of which seven were S. Typhimurium [15].
From January 2002 to December 2006, blood cultures (n= 1567) of febrile children (n = 1528) either out-patients (n = 829) or hospitalized (n = 699); as well as unknown number of stool cultures were investigated at the Children's Hospital of Lwiro, in DRC.Of the blood cultures, 241 yielded Salmonella of which 133 were S. Typhimurium [13].Unfortunately, it was not possible due to inadequate reporting to obtain an exact number of the stool, which yielded S. Typhimurium.
The procedures for isolation, identification, serotyping, antimicrobial susceptibility testing and PFGE included in this study have been described previously [16].Multilocus sequence typing (MLST) was performed on all of the isolates as described previously [17].

Whole genome sequencing
Publicly available genomic sequences were obtained from GenBank (accessed 10/10/2011).Fortythree whole genomic sequences for Salmonella serovar Typhimurium ST313 from Malawi were downloaded from the European Nucleotide Archive, [18] (accessed 14/02/2012) [19].In addition, six strains were sequenced by Illumina GAIIx genome analyzer (Illumina, Inc., San Diego, CA).Raw sequence data have been submitted to the European Nucleotide Archive [18] under accession no.ERP002011.The raw Illumina data were assembled using the pipeline available on the Center for Genomic Epidemiology [20] which is based on Velvet, algorithms for de novo short reads assembly [21].For a complete list of genomic sequence data refer to the supplementary Table 1.

Identification of Single Nucleotide Polymorphisms
Paired-end reads were aligned against the reference genome using Burrows-Wheeler Aligner (BWA) [22]; SNPs were identified using SAMtools [22] and bedtools [23].The informative SNPs required a minimum coverage of 20X and a minimum distance of 20 bps between each SNP.We used the S. Typhimurium ST313 D23580 genome as a reference (National Center for Biotechnology Information, accession: FN424405) in the analysis.Additionally, we included in the analysis only 16 out of 43 previously sequenced and deposited genomes [37 originating from Malawian patients due to a potential low quality of the raw reads in the remaining genomes].The analysis, excluding indels, resulted in 44 SNPs among the six whole genome sequences and a total of 92 from all genomes including those originating from Malawian patients.The informative SNPs from each isolate were concatenated to a single alignment according to the position of the reference genome by Perl script.Subsequently, multiple alignments were performed using MUSCLE from MEGA5 [24].A parsimony tree was generated based on MEGA5 via maximum parsimony method [24].The tree was evaluated for the support of the notes by bootstrap analyses with 10,000 replicates.The approximation of dN/dS ratio has been calculated by dividing the sum of non-synonymous SNPs with the sum of synonymous SNPs on the protein-coding sequences of the reference genome [25].

Resistance gene database
The web-server ResFinder [26, 27] was used to identify acquired antimicrobial resistance genes with a selected threshold equal to 95% identity and results were compared with phenotypic antimicrobial susceptibility testing results.

Identification of core genes
A set of 119 genomes (Supplementary Table 1) from NCBI and the collection of assembled genomes were subjected to gene finding using Prodigal [28].All predicted genes were aligned all-against-all at the amino acid level using BLASTP [29] and further grouped into gene clusters using MCL [30].

Defining gene islands
Identification of variable gene islands was initially performed only from the complete genomes but with plasmids excluded.Islands were defined as containing at least ten non-core genes within a region of DNA no larger than 5,000 bp.This produced 1,305 individual islands, many of which contained the same genes present in different bacterial isolates.Homology reduction was therefore performed using BLASTN alignments of the islands, all-against-all [29].
BLASTN tends to break up long imperfect matches.To avoid this, an overall identity score for every sequence pair was calculated by summarizing the identity from each individual, non-overlapping, hit.Any island pair having more than an overall identity of 70% was considered a variation of the same island and was therefore pruned using the second algorithm of Hobohm et al.This eliminates homology but preservs the maximum size of the data set [31].The resulting set of 205 unique islands was then aligned with BLASTN against all genomes.At this stage we also included the draft genomes.Similar to the alignment for homology reduction, the resulting identity for each island against a given genome was calculated as the sum of the identity for each non-overlapping hit.This provided a distance matrix expressing a percent identity for each island against each genome.This matrix was pruned by removing islands found only in a single genome, or in all examples of subspecies enterica.
This produced a total set of 145 gene islands.A pruned matrix consisting of 145 gene islands in 118 bacterial genomes was clustered in both dimensions and rendered in a heatmap using the R software [32].

Analysis of the putative virulent determinant (ST313-TD)
PCR amplification of a 924 bp long putative virulent determinant (ST313-TD) was performed on a global collection of 177 Salmonella isolates.The isolates belonged to Salmonella enterica subsp.enterica (n = 170), Salmonella enterica subsp.salamae (n = 1), Salmonella enterica subsp.arizonae (n = 1), Salmonella enterica subsp.diarizonae (n = 1), and Salmonella enterica subsp.houtenae (n = 4).Among the Salmonella enterica subsp.The PCR assay was designed to target 518 bp out of the 924 bp corresponding to the ST313-TD determinant.The amplifications were performed with buffer supplied by the manufacturer, 20 pmol/μl of each primer (forward primer: 5'GAA CAG TTT TAG GGC CCA A3' were paired with the reverse primer: 5'GGG AGT TCT TAA CGA TGG AA3') and 0.5 U of Amplicon Taq Polymerase (Ampliqon, Pennsylvania, United States) in a final reaction volume of 50 μl.The following amplification conditions were used: 5 min at 94°C; 25 cycles of 1 min at 94°C, 1 min at 52°C, and 1 min at 72°C; ending with one cycle of 10 min at 72°C. S. Typhimurium ST313 06/004 (DRC) providing an amplicon size of 518 bp was used as positive control.

Epidemiological information of cases from Nigeria and DRC
The seven isolates originating from blood samples were collected in 2004 and 2005 from patient admitted to two hospitals within the city of Ibadan, Nigeria.All originated from infants or children suffering from severe illness such as malaria (laboratory confirmed), typhoid fever (diagnosed as typhoid fever, blood culture revealed S. Typhimurium), septicemia, diarrhea, anemia, and malnutrition (Table ).
Between 2002 to 2006, 11 Salmonella isolates, including three from blood samples, seven from stool samples and one of unknown origin, were collected from children admitted to the Children's Hospital of Lwiro, DRC.Infections included one hospitalacquired infection, eight community-acquired infections, and two of unknown origin.Three patients had primary symptoms of uncomplicated diarrhea and five had diarrhea and septicemia.Four patients also suffered from meningococcemia, pneumonia, pneumococcal meningitis, and malaria; and two suffered from acute protein-energy malnutrition (kwashiorkor) in contrast to the six others where no sign of malnutrition was observed.Neither primary nor secondary symptoms were known for three of the patients.Seven of the patients were treated with antimalaria medication (quinine) prior to blood sample submission.The patients were hospitalized from four to 21 days with a median of ten days (exact hospitalization times were not known for two patients).Five patients were discharged from the hospital as recovered, two died during treatment, one left the hospital prematurely due to war related insecurities, and the outcomes for three of the patients were unknown (Table 1).

Antimicrobial susceptibility testing and resistance genes
The determination of the minimum inhibitory concentration (MIC) of a series of antibacterial agents for 18 S. Typhimurium ST313 isolates revealed two antimicrobial resistance profiles.The most common profile (n = 14) exhibited resistance to six core antimicrobials: ampicillin, chloramphenicol, spectinomycin, streptomycin, sulfamethoxazole, and trimethoprim whereas the other profile (n = 4) showed resistance to tetracycline in addition to first resistance profile (Figure 1).All isolates were susceptible to amoxicillin + clavulanic acid, apramycin, cefotaxime, ceftiofur, ciprofloxacin, colestin, florfenicol, gentamicin, nalidixic acid, and neomycin.The genomic sequence of the six isolates were submitted to the ResFinder based on which the following resistance genes were determined: aac(6')-Iaa (kanamycin), strA, strB (spectinomycin and streptomycin), bla TEM-1b (ampicillin), sul1 (sulfamethoxazole), dfrA1 (trimethoprim), and catA1 (chloramphenicol).In addition to those resistance genes, one isolate resistant to tetracycline also harbored the tet(B) gene (Figure 1).

Multi Locus Sequence Typing and Pulsed-Field Gel Electrophoresis
All 18 isolates belonged to ST313 and exhibited six unique XbaI PFGE patterns.Two PFGE clusters with indistinguishable profiles were observed containing three and eleven isolates, respectively (Figure 1).The cluster containing the three isolates all conferred resistance to the same antimicrobials including tetracycline, were all from Nigeria between 2004 and 2005 and all came from blood samples.Ten of the 11 isolates belonging to the second cluster conferred resistance to the same antimicrobials.However, one of the eleven clustered isolates was also resistant to tetracycline (Figure 1).These 11 closely related isolates originated from Congolese and Nigerian patients from where both stool and blood samples were submitted in a period from 2002 to 2007 (Figure 1).The four isolates not in cluster one or two were all very similar (between 93% and 99% similarity to the remaining isolates).These four isolates were all cultured from both stool and blood samples originating from Congolese and Nigerian patients in 2002 to 2007.

Parsimony SNP tree
The genetic evolution of S. Typhimurium ST313 was examined using analysis of Next Generation Sequence (NGS) data from twenty-two isolates from The parsimony tree was generated based on 92 informative SNPs from twenty-two whole-genome sequences.(A) radial tree layout shows the overview distribution of branches.(B) rectangular tree layout implicates the number of SNPs differences marked in black numbers.
All of the S. Typhimurium ST313 isolates from DRC, Nigeria, and Malawi were grouped within three distinct phylogenetic clusters based on the origin of isolation showing the clear overview of spatial evolution (Figure 2A).The recent study of Okoro et al. suggested that the population of S. Typhimurium ST313 is divided into two distinct lineages and Malawi and DRC served as potentially early transmission hubs in each lineage [33]; the isolates from Nigeria and DRC were very closely related, differing by only 12 -20 SNPs despite the large geographically distance between the countries (Figure 2B).In this study, we observed from zero to six SNPs among the highly clonal isolates from Malawi [19].A similarly low number of SNPs was observed within the Nigerian branch, where only four SNPs separated the isolates; BL25 and B51.The isolates from DRC were subdivided according to the isolation time; 2002 -2003 and 2005 -2007, into two closely related clusters differing by 14 SNPs (Figure 2B).Interestingly, there were only seven SNPs separating the Congolese isolates; 02-03-002 and 02-03-008, despite these being isolated from blood and stool samples, respectively.
The non-synonymous SNP/synonymous SNP ratio (dN/dS) is a measurement of stabilizing selection [34].A ratio of 1 is expected in the absence of selection, a low ratio (dN/dS<1) indicates stabilizing selection, while a high ratio (dN/dS>1) indicates positive selection [35].The genetic evolution among the Nigerian and Congolese isolates seems to be under positive selection as the dN/dS ratio is 1.7 (Supplementary Table 2).Nonetheless, the importance of these finding needs to be confirmed by additional analysis on the larger set of S. Typhimurium ST313 genomes.

Comparative genomic analysis
We identified gene islands in all completely assembled genomes, defined as chromosomal regions containing at least 10 non-core genes in close proximity.These islands were aligned against all genomes (including the fragmented genomes) and alignment identities were clustered into a heatmap (Figure 3 and supplementary figure for the complete isolate name).The heatmap S1 clearly illustrates that several gene islands are ubiquitous within certain serotypes but rarely found in isolates of other serotypes.This is especially evident for S. Typhimurium due to the amount of published data for this serovar, but can also be seen for Salmonella serovars Enteritidis, Derby, and Montevideo.
The S. Typhimurium ST313 genomes are marked by horizontal rectangles in Figure 3 and all clustered together with the exception of one genome, S. Typhimurium ST313 D23580.The genome of D23580 is instead clustered with a group of complete (or nearcomplete) genomes.The reason is that in general, complete or near-complete genomes in Figure 3 typically share certain islands, which are rarely found in the draft sequences.This is an indication that certain regions of the genome are harder to assemble, and thus only fragments of these were found in the draft genomes.As such, this suggests that an assembly bias exists in Figure 3, and one should take care to reference the number of contigs when interpreting the illustration.
In Figure 3, S. Typhimurium ST313 genomes stand out compared to the other Salmonella genomes in five columns marked with numbered vertical rectangles.These regions were extracted and analyzed for functional profiles through Gene Ontology (GO) terms [36] using the Blast2GO suite [37] (data not shown).Region 1 contained 47 genes, of which the vast majority of genes were prophage related.Region 2 contained 45 genes and was dominated by many hypothetical or putative proteins.A few phage-related genes were also found, particularly encoding bacteriophage tail proteins.Region 3 contained 157 genes, including a disproportionate number related to nuclease activities DNA binding, DNA metabolism and recombination.Region 3 also included several known virulence factors, such as type VI systems, and many more putative virulence genes.Region 4 was different from the others in that it was found conserved to about 90-100% in most of the S. Typhimurium investigated except for the S. Typhimurium ST313 genomes, where the conservation was 50% or less.The region contained only 20 genes, but several of those were known virulence factors, which were interestingly not found in S. Typhimurium ST313.
Region 5 contains 123 genes including a disproportionate number related to enzymatic and metabolic processes as well as fsr a gene (locus_tag SeD_A0541), which encodes resistance to fosmidomycin, not previously known virulence factors were found.The region 5 carried a presumptive uncharacterized 17.7 kb gene island, (ST313-GI), present in the S. Typhimurium ST313 sequenced strains including D23580.The gene island ST313-GI is integrated between a tRNA gene at the 5´end encoding a tRNA for threonine and two tRNAs genes at the 3´end encoding tRNAs for arsenic and threonine.ST313-GI, encodes several predicted prophage proteins and other phage-related factors such as an integrase, an excisionase, replication and regulatory proteins, an anti-restriction, repressor, antirepressor and anti-terminator proteins and a transcriptional activator.A putative virulence gene of 924 bp tentatively named ST313-TD was found within ST313-GI which showed high similarity (100% similarity) to a gene annotated in the genomes of S.
Typhimurium ST313 D23580 (accession no.FN424405 gene position 377825..378748) and S. Dublin CT_02021853 (accession no.CP001143) and 3246 (accession no.CM001151) from NCBI, exclusively.In the S. Dublin strains CT_02021853 and 3246, the determinant was contained in a region of app.6.8 kb showing high similarity (99%) to a part of the ST313-GI island in S. Typhimurium ST313.

Distribution of the putative virulence determinant (ST313-TD) among different Salmonella serovars
The presence of ST313-TD was detected in nine isolates assigned to the following serovars; six (n = 6; 100%) S. Dublin originating from Denmark, Taiwan, Thailand, Columbia, and Nigeria; one (n = 2, 50%) The heatmap color indicates the percentage of conservation at the DNA level of 145 gene islands (horizontal axis) in each of the 118 strains under investigation (vertical axis).The location of the ST313 strains are indicated by two black horizontal boxes; the singleton is the D23580 strain from GenBank, while the strains sequenced as part of this work all cluster together.Likewise, the five island regions discussed in the text are marked with vertical boxes.The ST313-GI harboring ST313-TD gene is located in region 5. Also indicated is whether each genome was sequenced to a complete contigous genome, nearly complete (<25 contigs) or should be considered a draft assembly (>25 contigs).Certain islands are typically only found conserved in complete or near-complete genomes, which suggests that the genome quality provides a degree of bias.The representation diplays genomic DNA only, although it cannot be ruled out that some of the draft genomes might contain plasmid DNA not annotated as such.
Salmonella serovar Bredeney of unknown origin; one (n = 6, 17%) Salmonella serovar Saintpaul from Italy, and one (n = 9, 11%) Salmonella serovars Kentucky from Nigeria.None of the five non-ST313 S. Typhimurium isolates included in the collection in this study were positive.

Discussion
The high incidence of invasive salmonellosis in sub-Saharan Africa is a major human health problem [10,11,19].It has been suggested that this is mainly due to a large susceptible population suffering from a range of maladies such as: malaria, diarrhea, septicemia, anemia, HIV, malnutrition, and fever.In particular, malaria has been suspected to increase the risk of invasive non-typhoidal Salmonella (NTS) infections and may contribute to the seasonality of NTS disease [12].Recently, it has also been suggested that a specific highly invasive sub-type of Salmonella; S. Typhimurium ST313 might be causing the majority of the infections [11].The study from Okoro et al. found that S. Typhimurium ST313 could be split into two lineages and provided evidence that these arose independently around 1960 and 1977 from Malawi and DRC, respectively [33].Nonetheless, it remains unknown whether S. Typhimurium ST313 causes mainly invasive diseases in humans or whether it is also a major cause of gastroenteritis.
A recent study of S. Typhimurium ST313 from Malawi revealed that isolates were highly clonal, differing only by a maximum of six SNPs [19].In the study reported here, we also found that isolates were highly clonal despite large temporal and spatial distances.This confirms previous speculations that S. Typhimurium ST313 is widespread in sub-Saharan African countries and is most likely the consequence of a recent emergence, possibly disseminated by the migration of animals and humans or by continental trade.
Until this report, no evidence of S. Typhimurium ST313 being associated with gastroenteritis in sub-Saharan Africa has been published [11].In this study, we found a high degree of similarity between isolates originating from blood and stool samples in DRC; this was supported by the clinical data.These data indicate that the S. Typhimurium ST313 isolates from DRC, and mostly likely all S. Typhimurium ST313, can cause gastroenteritis in humans like other NTS serotypes.However, the dominance of ST313 amongst isolates from blood is puzzling.
Interestingly, we found a putative virulence determinant (ST313-TD) unique to S. Typhimurium ST313, but also present in global isolates of S. Dublin.It is well known that S. Dublin is highly invasive in cattle and humans when compared to other NTS [38].In humans, S. Dublin often results in bacteraemia with severe disease and high mortality [39].In S. Typhimurium ST313, the hypothetical virulence determinant (ST313-TD) is included within a 17.7 kb region that may represent a novel pathogenicity island (ST313-GI).We also observed ST313-GI integrated between tRNA genes.Insertion of phages and pathogenicity islands within or in close proximity to tRNAs is very common [1,8,15,40].It is well known that most of the phages described in Salmonella, are involved in virulence [41] and several other Salmonella gene islands also encode pathogenic functions, e.g.Salmonella pathogenicity islands (SPIs) that encode multiple effectors required for Salmonella virulence [42].
The putative virulent determinant (ST313-TD) was present in a few isolates other than S. Typhimurium ST313 and S. Dublin.Unfortunately, we only have sparse information on those isolates complicating any speculation on why those few isolates represent serotypes which also harbored the genetic determinant.We know that the S. Kentucky isolate from Nigeria harbored the determinant whereas the S. Kentucky isolate from poultry isolated in the United States (US) did not.Two different lineages exist of S. Kentucky; one is present in the US affecting only poultry [43] where the other one is a highly pathogenic lineage causing human infections in Africa and Europe [44].This could explained why only the Nigerian isolate harbored the determinant as we speculate if this isolate belonged to the pathogenic lineage in contrast to the isolates from the US which might belong to the poultry lineage.Due to the low frequency of this putative virulence determinant in other serovars, our data suggest that the impact on acquisition of the gene island needs to be further investigated.
In this study, the 18 S. Typhimurium ST313 isolates from DRC and Nigeria conferred resistance to the exact same panel of antimicrobials; ampicillin, chloramphenicol, kanamycin, streptomycin, sulfamethoxazole, and trimethoprim as observed in isolates from Malawi and Kenya [11].In addition to the antimicrobial resistance pattern observed in Malawi and Kenya, we also revealed that some of the isolates from Nigeria conferred resistance to tetracycline harbored by the tetB gene.The antimicrobial resistance patterns and the corresponding genes are not unique to S. Typhimurium ST313 but frequently found among other NTS and gram negative Enterobacteriaceae [45,46].
This study is limited in terms of the low number of isolates investigated and the lack of clinical details such as HIV status of the patients, co-infections and local population data however, the authors believe that the data raise important questions about the epidemiology of S. Typhimurium ST313.

Conclusions
In this study, we showed in a limited number of isolates that S. Typhimurium ST313 is a prevalent sequence-type causing gastrointestinal diseases and septicemia in patients from Nigeria and DRC.We found three distinct phylogenetic clusters based on the origin of isolation suggesting some spatial evolution.Comparative genomics showed an interesting putative virulent fragment (ST313-TD) unique to S. Typhimurium ST313 and invasive S. Dublin.Further studies will have to be conducted on a large number of isolates and to determine the reservoirs and transmission routes of S. Typhimurium ST313 in sub-Saharan Africa.

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Figure 1 .
Figure 1.Dendrogram showing the genotypic relatedness of 18 S. Typhimurium ST 313 isolates based on XbaI-PFGE fingerprints and results of the antimicrobial susceptibility testing and resistance gene content.

Figure 3 .
Figure 3. Heatmap showing the distribution of gene islands across Salmonella genomes.

Table 1 :
Epidemiological and clinical information for the 18 Salmonella serovar Typhimurium ST313 from DRC and Nigeria.
Multi Locus Sequence Typing (MLST) (multiple schemes) from an assembled genome or from set of reads.Read more: "Multilocus sequence typing of total-genome-sequenced bacteria" by Larsen et al., JCM 2012. Identification of acquired antibiotic resistance genes from a file with sequence reads using the ResFinder tool.Read more: "Identification of acquired antimicrobial resistance genes" by Zankari et al., JAC 2012. Identification of plasmid replicons and typing of those by PlasmidFinder and pMLST tool. Creation of a SNPs phylogenetic tree from assembled genomes or sets of reads.Read more: "snpTree--a web-server to identify and construct SNP trees from whole genome sequence data" by Leekitcharoenphon et al., BMC Genomics 2012.The tools are available free of charge and online http://cge.cbs.dtu.dk/services/all.php